From 0a8b4bff972c67d7c8950f1dd7e19cdc1a97529e Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Wed, 30 Aug 2023 13:06:09 +0100 Subject: [PATCH 001/165] clarify macro aren't support in project.yml file --- website/docs/reference/dbt_project.yml.md | 5 +- website/docs/reference/macro-properties.md | 4 +- .../docs/reference/resource-configs/docs.md | 78 ++++++++++++++++--- 3 files changed, 72 insertions(+), 15 deletions(-) diff --git a/website/docs/reference/dbt_project.yml.md b/website/docs/reference/dbt_project.yml.md index 59541a81256..6009033d557 100644 --- a/website/docs/reference/dbt_project.yml.md +++ b/website/docs/reference/dbt_project.yml.md @@ -18,12 +18,13 @@ By default, dbt will look for `dbt_project.yml` in your current working director -The following is a list of all available configurations in the `dbt_project.yml` file. - :::info YAML syntax + dbt uses YAML in a few different places. If you're new to YAML, it would be worth taking the time to learn how arrays, dictionaries and strings are represented. ::: +The following is a list of all available configurations in the `dbt_project.yml` file. Something to note, [Macro properties](/reference/macro-properties) aren't supported in the `dbt_project.yml` file: + ```yml diff --git a/website/docs/reference/macro-properties.md b/website/docs/reference/macro-properties.md index 91ba52de9ca..3b755cd0107 100644 --- a/website/docs/reference/macro-properties.md +++ b/website/docs/reference/macro-properties.md @@ -2,9 +2,9 @@ title: Macro properties --- -Macro properties can be declared in `.yml` files. +Macro properties can be declared in `.yml` files, except in the `dbt_project.yml` files. -You can name these files `whatever_you_want.yml`, and nest them arbitrarily deeply in subfolders. +You can name these files `whatever_you_want.yml`, and nest them arbitrarily deeply in sub-folders. diff --git a/website/docs/reference/resource-configs/docs.md b/website/docs/reference/resource-configs/docs.md index d94b975683d..dff58be8931 100644 --- a/website/docs/reference/resource-configs/docs.md +++ b/website/docs/reference/resource-configs/docs.md @@ -17,10 +17,28 @@ default_value: {show: true} { label: 'Macros', value: 'macros', }, ] }> + +You can use the docs property in YAML files, including the `dbt_project.yml`: + + + +```yml +name: "your_dbt_project_name" +version: "1.0.0" +config-version: 2 + +models: + - name: model_name + docs: + show: true | false +``` + + + ```yml version: 2 @@ -28,7 +46,6 @@ models: - name: model_name docs: show: true | false - ``` @@ -43,6 +60,22 @@ This property is not implemented for sources. +You can use the docs property in YAML files, including the `dbt_project.yml`: + + + +```yml +name: "your_dbt_project_name" +version: "1.0.0" +config-version: 2 + +seeds: + - name: seed_name + docs: + show: true | false +``` + + ```yml @@ -52,15 +85,29 @@ seeds: - name: seed_name docs: show: true | false - ``` - +You can use the docs property in YAML files, including the `dbt_project.yml`: + + + +```yml +name: "your_dbt_project_name" +version: "1.0.0" +config-version: 2 + +snapshots: + - name: snapshot_name + docs: + show: true | false +``` + + ```yml @@ -70,15 +117,29 @@ snapshots: - name: snapshot_name docs: show: true | false - ``` - +You can use the docs property in YAML files, including the `dbt_project.yml`: + + + +```yml +name: "your_dbt_project_name" +version: "1.0.0" +config-version: 2 + +analyses: + - name: analysis_name + docs: + show: true | false +``` + + ```yml @@ -89,16 +150,13 @@ analyses: docs: show: true | false ``` - - +You can use the docs property in YAML files, _except_ in `dbt_project.yml`. [Macro properties](/reference/macro-properties) _are not_ supported in the `dbt_project.yml` file. @@ -109,9 +167,7 @@ macros: - name: macro_name docs: show: true | false - ``` - From cda991a8909f1e68c8b1541ad6bafa39e6695c27 Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Thu, 31 Aug 2023 17:26:00 +0100 Subject: [PATCH 002/165] add snippet and rephrase --- website/docs/reference/analysis-properties.md | 4 +++- website/docs/reference/configs-and-properties.md | 7 +++++-- website/docs/reference/exposure-properties.md | 6 +++++- website/docs/reference/macro-properties.md | 7 +++++-- website/docs/reference/source-properties.md | 10 +++++++--- website/snippets/_config-prop-callout.md | 1 + 6 files changed, 26 insertions(+), 9 deletions(-) create mode 100644 website/snippets/_config-prop-callout.md diff --git a/website/docs/reference/analysis-properties.md b/website/docs/reference/analysis-properties.md index 008da70f9db..c43819c57b9 100644 --- a/website/docs/reference/analysis-properties.md +++ b/website/docs/reference/analysis-properties.md @@ -2,7 +2,9 @@ title: Analysis properties --- -We recommend you define analysis properties in your `analyses/` directory, which is illustrated in the [`analysis-paths`](/reference/project-configs/analysis-paths) configuration. +import PropsCallout from '/snippets/_config-prop-callout.md'; + +We recommend you define analysis properties in your `analyses/` directory, which is illustrated in the [`analysis-paths`](/reference/project-configs/analysis-paths) configuration.
You can name these files `whatever_you_want.yml`, and nest them arbitrarily deeply in subfolders within the `analyses/` or `models/` directory. diff --git a/website/docs/reference/configs-and-properties.md b/website/docs/reference/configs-and-properties.md index c2ad5b77629..76297f695ca 100644 --- a/website/docs/reference/configs-and-properties.md +++ b/website/docs/reference/configs-and-properties.md @@ -64,15 +64,18 @@ Previous versions of the docs referred to these as `schema.yml` files — we've ### Which properties are _not_ also configs? -dbt has the ability to define node configs in `.yml` files, in addition to `config()` blocks and `dbt_project.yml`. But the reverse isn't always true: there are some things in `.yml` files that can _only_ be defined there. +In dbt, you can define node configs in `.yml` files, in addition to `config()` blocks and `dbt_project.yml`. However, some properties are exclusive to `.yml` files. + Certain properties are special, because: + - They have a unique Jinja rendering context - They create new project resources - They don't make sense as hierarchical configuration - They're older properties that haven't yet been redefined as configs -These properties are: +This means "configs" can be set for multiple resources at once in the `dbt_project.yml` file, while "properties" can only be set for one resource at a time. The following properties _cannot_ be configured from `dbt_project.yml`: + - [`description`](/reference/resource-properties/description) - [`tests`](/reference/resource-properties/tests) - [`docs`](/reference/resource-configs/docs) diff --git a/website/docs/reference/exposure-properties.md b/website/docs/reference/exposure-properties.md index aaed2a20a09..7a7b9f18790 100644 --- a/website/docs/reference/exposure-properties.md +++ b/website/docs/reference/exposure-properties.md @@ -8,7 +8,11 @@ description: "Read this guide to understand exposure properties in dbt." - [Declaring resource properties](/reference/configs-and-properties) ## Overview -Exposures are defined in `.yml` files nested under an `exposures:` key. You may define `exposures` in YAML files that also define define `sources` or `models`. + +import PropsCallout from '/snippets/_config-prop-callout.md'; + +Exposures are defined in `.yml` files nested under an `exposures:` key. You may define `exposures` in YAML files that also define `sources` or `models`, except in the `dbt_project.yml` files.
+ You can name these files `whatever_you_want.yml`, and nest them arbitrarily deeply in subfolders within the `models/` directory. diff --git a/website/docs/reference/macro-properties.md b/website/docs/reference/macro-properties.md index 3b755cd0107..2ef2a2fb82e 100644 --- a/website/docs/reference/macro-properties.md +++ b/website/docs/reference/macro-properties.md @@ -1,10 +1,13 @@ --- title: Macro properties +id: macro-properties --- -Macro properties can be declared in `.yml` files, except in the `dbt_project.yml` files. +import PropsCallout from '/snippets/_config-prop-callout.md'; -You can name these files `whatever_you_want.yml`, and nest them arbitrarily deeply in sub-folders. +Macro properties can be declared in `.yml` files, except in the `dbt_project.yml` files.
+ + You can name these files `whatever_you_want.yml`, and nest them arbitrarily deeply in sub-folders: diff --git a/website/docs/reference/source-properties.md b/website/docs/reference/source-properties.md index d20ef5f2877..9388d60a2e9 100644 --- a/website/docs/reference/source-properties.md +++ b/website/docs/reference/source-properties.md @@ -1,5 +1,5 @@ --- -title: "About source properties" +title: "Source properties" description: "Learn how to use source properties in dbt." --- @@ -8,9 +8,13 @@ description: "Learn how to use source properties in dbt." - [Declaring resource properties](/reference/configs-and-properties) ## Overview -Source properties can be declared in `.yml` files in your `models/` directory (as defined by the [`model-paths` config](/reference/project-configs/model-paths)). -You can name these files `whatever_you_want.yml`, and nest them arbitrarily deeply in subfolders within the `models/` directory. +import PropsCallout from '/snippets/_config-prop-callout.md'; + +Source properties can be declared in `.yml` files in your `models/` directory (as defined by the [`model-paths` config](/reference/project-configs/model-paths)), except in the `dbt_project.yml` files.
+ + +You can name these files `whatever_you_want.yml`, and nest them arbitrarily deeply in subfolders within the `models/` directory: diff --git a/website/snippets/_config-prop-callout.md b/website/snippets/_config-prop-callout.md new file mode 100644 index 00000000000..bfb74e1524d --- /dev/null +++ b/website/snippets/_config-prop-callout.md @@ -0,0 +1 @@ +This is because you can set "configs" for many resources in dbt_project.yml, while you can only set "properties" one resource at a time.

Since {props.title} are "properties", this means you cannot configure it from dbt_project.yml. Refer to Configs and properties for more info. From 66ff1df9d87b7b40f5a339257b854d176db8e772 Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Thu, 31 Aug 2023 17:28:08 +0100 Subject: [PATCH 003/165] Update dbt_project.yml.md --- website/docs/reference/dbt_project.yml.md | 10 +++++++--- 1 file changed, 7 insertions(+), 3 deletions(-) diff --git a/website/docs/reference/dbt_project.yml.md b/website/docs/reference/dbt_project.yml.md index 6009033d557..73c661a9751 100644 --- a/website/docs/reference/dbt_project.yml.md +++ b/website/docs/reference/dbt_project.yml.md @@ -4,7 +4,7 @@ -Every [dbt project](/docs/build/projects) needs a `dbt_project.yml` file — this is how dbt knows a directory is a dbt project. It also contains important information that tells dbt how to operate on your project. +Every [dbt project](/docs/build/projects) needs a `dbt_project.yml` file — this is how dbt knows a directory is a dbt project. It also contains important information that tells dbt how to operate your project. @@ -20,10 +20,14 @@ By default, dbt will look for `dbt_project.yml` in your current working director :::info YAML syntax -dbt uses YAML in a few different places. If you're new to YAML, it would be worth taking the time to learn how arrays, dictionaries and strings are represented. +dbt uses YAML in a few different places. If you're new to YAML, it would be worth taking the time to learn how arrays, dictionaries, and strings are represented. ::: -The following is a list of all available configurations in the `dbt_project.yml` file. Something to note, [Macro properties](/reference/macro-properties) aren't supported in the `dbt_project.yml` file: +The following example is a list of all available configurations in the `dbt_project.yml` file. Something to note, the following properties aren't supported in in the `dbt_project.yml` file: + +- [Macro properties](/reference/macro-properties) +- [Analysis properties](/reference/analysis-properties) +- [Semantic model configs](/docs/build/semantic-models) From b163c5bc0576dc69dd967ffb465d86c0926e9b57 Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Thu, 31 Aug 2023 17:28:48 +0100 Subject: [PATCH 004/165] Update website/docs/reference/macro-properties.md Co-authored-by: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> --- website/docs/reference/macro-properties.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/reference/macro-properties.md b/website/docs/reference/macro-properties.md index 3b755cd0107..9e59ca58705 100644 --- a/website/docs/reference/macro-properties.md +++ b/website/docs/reference/macro-properties.md @@ -4,7 +4,7 @@ title: Macro properties Macro properties can be declared in `.yml` files, except in the `dbt_project.yml` files. -You can name these files `whatever_you_want.yml`, and nest them arbitrarily deeply in sub-folders. +You can name these files `whatever_you_want.yml` and nest them arbitrarily deep in sub-folders. From ddd2c636dca4bd307fc9a942b248b65aec6ce8bc Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Thu, 31 Aug 2023 17:28:55 +0100 Subject: [PATCH 005/165] Update website/docs/reference/macro-properties.md Co-authored-by: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> --- website/docs/reference/macro-properties.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/reference/macro-properties.md b/website/docs/reference/macro-properties.md index 9e59ca58705..329a5a94a9f 100644 --- a/website/docs/reference/macro-properties.md +++ b/website/docs/reference/macro-properties.md @@ -2,7 +2,7 @@ title: Macro properties --- -Macro properties can be declared in `.yml` files, except in the `dbt_project.yml` files. +Macro properties can be declared in any `.yml` file except for the `dbt_project.yml` file. You can name these files `whatever_you_want.yml` and nest them arbitrarily deep in sub-folders. From 6d8ce4eab93834bb1319c0c1ae14bac110037d52 Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Thu, 31 Aug 2023 17:32:00 +0100 Subject: [PATCH 006/165] update lang --- website/docs/reference/source-properties.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/reference/source-properties.md b/website/docs/reference/source-properties.md index 9388d60a2e9..4dee14d27f4 100644 --- a/website/docs/reference/source-properties.md +++ b/website/docs/reference/source-properties.md @@ -11,7 +11,7 @@ description: "Learn how to use source properties in dbt." import PropsCallout from '/snippets/_config-prop-callout.md'; -Source properties can be declared in `.yml` files in your `models/` directory (as defined by the [`model-paths` config](/reference/project-configs/model-paths)), except in the `dbt_project.yml` files.
+Source properties can be declared in any `.yml` file in your `models/` directory (as defined by the [`model-paths` config](/reference/project-configs/model-paths)), except for the `dbt_project.yml` file.
You can name these files `whatever_you_want.yml`, and nest them arbitrarily deeply in subfolders within the `models/` directory: From 9a9627afbf3f86094774b3dd93b068c756f7863d Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Wed, 6 Sep 2023 12:04:54 +0100 Subject: [PATCH 007/165] tweak snippet and add versionblock --- website/docs/reference/dbt_project.yml.md | 18 ++++++++++++++++++ website/docs/reference/macro-properties.md | 4 +++- website/snippets/_config-prop-callout.md | 2 +- 3 files changed, 22 insertions(+), 2 deletions(-) diff --git a/website/docs/reference/dbt_project.yml.md b/website/docs/reference/dbt_project.yml.md index 73c661a9751..1e63beae082 100644 --- a/website/docs/reference/dbt_project.yml.md +++ b/website/docs/reference/dbt_project.yml.md @@ -23,11 +23,29 @@ By default, dbt will look for `dbt_project.yml` in your current working director dbt uses YAML in a few different places. If you're new to YAML, it would be worth taking the time to learn how arrays, dictionaries, and strings are represented. ::: + + + +The following example is a list of all available configurations in the `dbt_project.yml` file. Something to note, the following properties aren't supported in in the `dbt_project.yml` file: + +- [Exposure properties](/reference/exposure-properties) +- [Macro properties](/reference/macro-properties) +- [Analysis properties](/reference/analysis-properties) +- [Source properties](/reference/source-properties) + + + + + The following example is a list of all available configurations in the `dbt_project.yml` file. Something to note, the following properties aren't supported in in the `dbt_project.yml` file: +- [Exposure properties](/reference/exposure-properties) - [Macro properties](/reference/macro-properties) - [Analysis properties](/reference/analysis-properties) - [Semantic model configs](/docs/build/semantic-models) +- [Source properties](/reference/source-properties) + + diff --git a/website/docs/reference/macro-properties.md b/website/docs/reference/macro-properties.md index 5fdcea317c8..348eaf6139d 100644 --- a/website/docs/reference/macro-properties.md +++ b/website/docs/reference/macro-properties.md @@ -3,7 +3,9 @@ title: Macro properties id: macro-properties --- -Macro properties can be declared in any `.yml` file except for the `dbt_project.yml` file.
+import PropsCallout from '/snippets/_config-prop-callout.md'; + +Macro properties can be declared in any `.yml` file, except for the `dbt_project.yml` file. You can name these files `whatever_you_want.yml` and nest them arbitrarily deep in sub-folders. diff --git a/website/snippets/_config-prop-callout.md b/website/snippets/_config-prop-callout.md index bfb74e1524d..a0b7e45a1de 100644 --- a/website/snippets/_config-prop-callout.md +++ b/website/snippets/_config-prop-callout.md @@ -1 +1 @@ -This is because you can set "configs" for many resources in dbt_project.yml, while you can only set "properties" one resource at a time.

Since {props.title} are "properties", this means you cannot configure it from dbt_project.yml. Refer to Configs and properties for more info. +This is because you can set "configs" for many resources in dbt_project.yml, while you can only set "properties" one resource at a time.

Since {props.title} are "properties", this means you cannot configure it from dbt_project.yml. Refer to Configs and properties for more info. From a56d9a868b1e3a58e27bccc816d9626ef33127b6 Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Wed, 6 Sep 2023 12:19:04 +0100 Subject: [PATCH 008/165] remove break --- website/docs/docs/build/semantic-models.md | 16 +++++++++++++++- website/docs/reference/dbt_project.yml.md | 6 ++++-- website/docs/reference/exposure-properties.md | 2 +- website/snippets/_config-prop-callout.md | 2 +- 4 files changed, 21 insertions(+), 5 deletions(-) diff --git a/website/docs/docs/build/semantic-models.md b/website/docs/docs/build/semantic-models.md index bb56bd212e6..ca430ae5437 100644 --- a/website/docs/docs/build/semantic-models.md +++ b/website/docs/docs/build/semantic-models.md @@ -8,11 +8,25 @@ sidebar_label: Semantic models tags: [Metrics, Semantic Layer] --- +import PropsCallout from '/snippets/_config-prop-callout.md'; + Semantic models serve as the foundation for defining data in MetricFlow, which powers the dbt Semantic Layer. You can think of semantic models as nodes in your semantic graph, connected via entities as edges. MetricFlow takes semantic models defined in YAML configuration files as inputs and creates a semantic graph that can be used to query metrics. Each semantic model corresponds to a dbt model in your DAG. Therefore you will have one YAML config for each semantic model in your dbt project. You can create multiple semantic models out of a single dbt model, as long as you give each semantic model a unique name. -You can configure semantic models in your dbt project directory in a `YAML` file. Depending on your project structure, you can nest semantic models under a `metrics:` folder or organize them under project sources. + + +You can configure semantic models in your dbt project directory in a `YAML` file, _except_ the `dbt_project.yml` file. Depending on your project structure, you can nest semantic models under a `metrics:` folder or organize them under project sources. + + + + + +You can configure semantic models in your dbt project directory in a `YAML` file, _except_ the `dbt_project.yml` file. + +Depending on your project structure, you can nest semantic models under a `metrics:` folder or organize them under project sources. + + Semantic models have 6 components and this page explains the definitions with some examples: diff --git a/website/docs/reference/dbt_project.yml.md b/website/docs/reference/dbt_project.yml.md index 1e63beae082..0a3b76fe0a8 100644 --- a/website/docs/reference/dbt_project.yml.md +++ b/website/docs/reference/dbt_project.yml.md @@ -26,7 +26,7 @@ dbt uses YAML in a few different places. If you're new to YAML, it would be wort -The following example is a list of all available configurations in the `dbt_project.yml` file. Something to note, the following properties aren't supported in in the `dbt_project.yml` file: +Something to note, the following properties _aren't_ supported in in the `dbt_project.yml` file: - [Exposure properties](/reference/exposure-properties) - [Macro properties](/reference/macro-properties) @@ -37,7 +37,7 @@ The following example is a list of all available configurations in the `dbt_proj -The following example is a list of all available configurations in the `dbt_project.yml` file. Something to note, the following properties aren't supported in in the `dbt_project.yml` file: +Something to note, the following properties _aren't_ supported in in the `dbt_project.yml` file: - [Exposure properties](/reference/exposure-properties) - [Macro properties](/reference/macro-properties) @@ -47,6 +47,8 @@ The following example is a list of all available configurations in the `dbt_proj +The following example is a list of all available configurations in the `dbt_project.yml` file: + ```yml diff --git a/website/docs/reference/exposure-properties.md b/website/docs/reference/exposure-properties.md index 7a7b9f18790..04371d03956 100644 --- a/website/docs/reference/exposure-properties.md +++ b/website/docs/reference/exposure-properties.md @@ -11,7 +11,7 @@ description: "Read this guide to understand exposure properties in dbt." import PropsCallout from '/snippets/_config-prop-callout.md'; -Exposures are defined in `.yml` files nested under an `exposures:` key. You may define `exposures` in YAML files that also define `sources` or `models`, except in the `dbt_project.yml` files.
+Exposures are defined in `.yml` files nested under an `exposures:` key. You may define `exposures` in YAML files that also define `sources` or `models`, _except_ in the `dbt_project.yml` file.
You can name these files `whatever_you_want.yml`, and nest them arbitrarily deeply in subfolders within the `models/` directory. diff --git a/website/snippets/_config-prop-callout.md b/website/snippets/_config-prop-callout.md index a0b7e45a1de..ff49a2d297a 100644 --- a/website/snippets/_config-prop-callout.md +++ b/website/snippets/_config-prop-callout.md @@ -1 +1 @@ -This is because you can set "configs" for many resources in dbt_project.yml, while you can only set "properties" one resource at a time.

Since {props.title} are "properties", this means you cannot configure it from dbt_project.yml. Refer to Configs and properties for more info. +This is because you can set "configs" for many resources in dbt_project.yml, while you can only set "properties" one resource at a time. Since {props.title} are "properties", this means you cannot configure it from dbt_project.yml. Refer to Configs and properties for more info. From 02fb13782f920cdadab5f919022094e92a4a7cba Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Mon, 18 Sep 2023 14:18:50 +0100 Subject: [PATCH 009/165] adding jerco's great feedback --- website/docs/docs/build/semantic-models.md | 4 +- .../docs/reference/configs-and-properties.md | 13 ++-- website/docs/reference/dbt_project.yml.md | 24 +------- website/docs/reference/exposure-properties.md | 2 +- website/docs/reference/macro-properties.md | 2 +- .../docs/reference/resource-configs/docs.md | 59 +------------------ website/docs/reference/source-properties.md | 2 +- website/snippets/_config-prop-callout.md | 2 +- 8 files changed, 15 insertions(+), 93 deletions(-) diff --git a/website/docs/docs/build/semantic-models.md b/website/docs/docs/build/semantic-models.md index ca430ae5437..945282d183a 100644 --- a/website/docs/docs/build/semantic-models.md +++ b/website/docs/docs/build/semantic-models.md @@ -16,13 +16,13 @@ Each semantic model corresponds to a dbt model in your DAG. Therefore you will h -You can configure semantic models in your dbt project directory in a `YAML` file, _except_ the `dbt_project.yml` file. Depending on your project structure, you can nest semantic models under a `metrics:` folder or organize them under project sources. +You can configure semantic models in your dbt project directory in a [`properties.yml` file](/reference/configs-and-properties#where-can-i-define-properties). Depending on your project structure, you can nest semantic models under a `metrics:` folder or organize them under project sources. -You can configure semantic models in your dbt project directory in a `YAML` file, _except_ the `dbt_project.yml` file. +You can configure semantic models in your dbt project directory in a [`.yml` file](/reference/configs-and-properties#where-can-i-define-properties), however, you cannot actually define their properties within the `dbt_project.yml` file. Depending on your project structure, you can nest semantic models under a `metrics:` folder or organize them under project sources. diff --git a/website/docs/reference/configs-and-properties.md b/website/docs/reference/configs-and-properties.md index 76297f695ca..2a483296381 100644 --- a/website/docs/reference/configs-and-properties.md +++ b/website/docs/reference/configs-and-properties.md @@ -3,7 +3,7 @@ title: Configs, properties, what are they? --- Resources in your project—models, snapshots, seeds, tests, and the rest—can have a number of declared **properties**. Resources can also define **configurations**, which are a special kind of property that bring extra abilities. What's the distinction? -- Properties are declared for resources one-by-one in `.yml` files. Configs can be defined there, nested under a `config` property. They can also be set one-by-one via a `config()` macro (right within `.sql` files), and for many resources at once in `dbt_project.yml`. +- Properties are declared for resources one-by-one in `properties.yml` files. Configs can be defined there, nested under a `config` property. They can also be set one-by-one via a `config()` macro (right within `.sql` files), and for many resources at once in `dbt_project.yml`. - Because configs can be set in multiple places, they are also applied hierarchically. An individual resource might _inherit_ or _override_ configs set elsewhere. - You can select resources based on their config values using the `config:` selection method, but not the values of non-config properties @@ -46,9 +46,7 @@ Most configurations are "clobbered" when applied hierarchically. Whenever a more ## Where can I define properties? -In dbt, properties are declared in `.yml` files, in the same directory as your resources. - -You can name these files `whatever_you_want.yml` and nest them arbitrarily deeply in subfolders within each directory. +In dbt, you can use `properties.yml` files to define properties for resources. You can declare properties in `.yml` files, in the same directory as your resources. You can name these files `whatever_you_want.yml` and nest them arbitrarily in sub-folders within each directory. We highly recommend that you define properties in dedicated paths alongside the resources they're describing. @@ -56,16 +54,15 @@ We highly recommend that you define properties in dedicated paths alongside the #### schema.yml files -Previous versions of the docs referred to these as `schema.yml` files — we've moved away from that terminology since the word `schema` is used to mean other things when talking about databases, and people often thought that you _had_ to name these files `schema.yml`. +Previous versions of the docs referred to these as `schema.yml` files — we've moved away from that terminology since the word `schema` is used to mean other things when talking about databases, and people often thought that you _had_ to name these files `schema.yml`. -(Of course, you're still free to name your files `schema.yml`) +Instead, we now refer to these files as `properties.yml` files. (Of course, you're still free to name your files `schema.yml`) ::: ### Which properties are _not_ also configs? -In dbt, you can define node configs in `.yml` files, in addition to `config()` blocks and `dbt_project.yml`. However, some properties are exclusive to `.yml` files. - +In dbt, you can define node configs in `properties.yml` files, in addition to `config()` blocks and `dbt_project.yml`. However, some properties are exclusive to `.yml` files. Certain properties are special, because: diff --git a/website/docs/reference/dbt_project.yml.md b/website/docs/reference/dbt_project.yml.md index 0a3b76fe0a8..5a195dd6662 100644 --- a/website/docs/reference/dbt_project.yml.md +++ b/website/docs/reference/dbt_project.yml.md @@ -23,29 +23,7 @@ By default, dbt will look for `dbt_project.yml` in your current working director dbt uses YAML in a few different places. If you're new to YAML, it would be worth taking the time to learn how arrays, dictionaries, and strings are represented. ::: - - - -Something to note, the following properties _aren't_ supported in in the `dbt_project.yml` file: - -- [Exposure properties](/reference/exposure-properties) -- [Macro properties](/reference/macro-properties) -- [Analysis properties](/reference/analysis-properties) -- [Source properties](/reference/source-properties) - - - - - -Something to note, the following properties _aren't_ supported in in the `dbt_project.yml` file: - -- [Exposure properties](/reference/exposure-properties) -- [Macro properties](/reference/macro-properties) -- [Analysis properties](/reference/analysis-properties) -- [Semantic model configs](/docs/build/semantic-models) -- [Source properties](/reference/source-properties) - - +Something to note, you can't set up a "property" in the `dbt_project.yml` file if it's not a config (an example is [macros](/reference/macro-properties)). This applies to all types of resources. Refer to [Configs and properties](/reference/configs-and-properties) for more detail. The following example is a list of all available configurations in the `dbt_project.yml` file: diff --git a/website/docs/reference/exposure-properties.md b/website/docs/reference/exposure-properties.md index 04371d03956..ffc494f6025 100644 --- a/website/docs/reference/exposure-properties.md +++ b/website/docs/reference/exposure-properties.md @@ -11,7 +11,7 @@ description: "Read this guide to understand exposure properties in dbt." import PropsCallout from '/snippets/_config-prop-callout.md'; -Exposures are defined in `.yml` files nested under an `exposures:` key. You may define `exposures` in YAML files that also define `sources` or `models`, _except_ in the `dbt_project.yml` file.
+Exposures are defined in `.yml` files nested under an `exposures:` key. You may define `exposures` in YAML files that also define `sources` or `models`.
You can name these files `whatever_you_want.yml`, and nest them arbitrarily deeply in subfolders within the `models/` directory. diff --git a/website/docs/reference/macro-properties.md b/website/docs/reference/macro-properties.md index 348eaf6139d..685643a9aaa 100644 --- a/website/docs/reference/macro-properties.md +++ b/website/docs/reference/macro-properties.md @@ -5,7 +5,7 @@ id: macro-properties import PropsCallout from '/snippets/_config-prop-callout.md'; -Macro properties can be declared in any `.yml` file, except for the `dbt_project.yml` file. +Macro properties can be declared in any `.yml` file. You can name these files `whatever_you_want.yml` and nest them arbitrarily deep in sub-folders. diff --git a/website/docs/reference/resource-configs/docs.md b/website/docs/reference/resource-configs/docs.md index dff58be8931..a6e0f4dc9b0 100644 --- a/website/docs/reference/resource-configs/docs.md +++ b/website/docs/reference/resource-configs/docs.md @@ -20,21 +20,8 @@ default_value: {show: true} -You can use the docs property in YAML files, including the `dbt_project.yml`: - - +You can configure `docs` behavior for many resources at once by setting in `dbt_project.yml`. You can also use the `docs` config in `properties.yaml` files, to set or override documentation behaviors for specific resources: -```yml -name: "your_dbt_project_name" -version: "1.0.0" -config-version: 2 - -models: - - name: model_name - docs: - show: true | false -``` - @@ -62,19 +49,6 @@ This property is not implemented for sources. You can use the docs property in YAML files, including the `dbt_project.yml`: - - -```yml -name: "your_dbt_project_name" -version: "1.0.0" -config-version: 2 - -seeds: - - name: seed_name - docs: - show: true | false -``` - @@ -94,20 +68,6 @@ seeds: You can use the docs property in YAML files, including the `dbt_project.yml`: - - -```yml -name: "your_dbt_project_name" -version: "1.0.0" -config-version: 2 - -snapshots: - - name: snapshot_name - docs: - show: true | false -``` - - ```yml @@ -124,21 +84,8 @@ snapshots: -You can use the docs property in YAML files, including the `dbt_project.yml`: +You can use the docs property in YAML files, _except_ in `dbt_project.yml`. Refer to [Analysis properties](/reference/analysis-properties) for more info. - - -```yml -name: "your_dbt_project_name" -version: "1.0.0" -config-version: 2 - -analyses: - - name: analysis_name - docs: - show: true | false -``` - @@ -156,7 +103,7 @@ analyses: -You can use the docs property in YAML files, _except_ in `dbt_project.yml`. [Macro properties](/reference/macro-properties) _are not_ supported in the `dbt_project.yml` file. +You can use the docs property in YAML files, _except_ in `dbt_project.yml`. Refer to [Macro properties](/reference/macro-properties) for more info. diff --git a/website/docs/reference/source-properties.md b/website/docs/reference/source-properties.md index 4dee14d27f4..ead76040b05 100644 --- a/website/docs/reference/source-properties.md +++ b/website/docs/reference/source-properties.md @@ -11,7 +11,7 @@ description: "Learn how to use source properties in dbt." import PropsCallout from '/snippets/_config-prop-callout.md'; -Source properties can be declared in any `.yml` file in your `models/` directory (as defined by the [`model-paths` config](/reference/project-configs/model-paths)), except for the `dbt_project.yml` file.
+Source properties can be declared in any `.yml` file in your `models/` directory (as defined by the [`model-paths` config](/reference/project-configs/model-paths)).
You can name these files `whatever_you_want.yml`, and nest them arbitrarily deeply in subfolders within the `models/` directory: diff --git a/website/snippets/_config-prop-callout.md b/website/snippets/_config-prop-callout.md index ff49a2d297a..f21c335734a 100644 --- a/website/snippets/_config-prop-callout.md +++ b/website/snippets/_config-prop-callout.md @@ -1 +1 @@ -This is because you can set "configs" for many resources in dbt_project.yml, while you can only set "properties" one resource at a time. Since {props.title} are "properties", this means you cannot configure it from dbt_project.yml. Refer to Configs and properties for more info. +{props.title} are "special properties" in that you can't configure them in the dbt_project.yml file or using config() blocks. Refer to Configs and properties for more info. From 1872ce1d2f4edc719efb748cdc1684ad26f714d2 Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Mon, 18 Sep 2023 14:32:21 +0100 Subject: [PATCH 010/165] clarify --- website/docs/reference/configs-and-properties.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/website/docs/reference/configs-and-properties.md b/website/docs/reference/configs-and-properties.md index 2a483296381..61e401f016d 100644 --- a/website/docs/reference/configs-and-properties.md +++ b/website/docs/reference/configs-and-properties.md @@ -62,7 +62,7 @@ Instead, we now refer to these files as `properties.yml` files. (Of course, you' ### Which properties are _not_ also configs? -In dbt, you can define node configs in `properties.yml` files, in addition to `config()` blocks and `dbt_project.yml`. However, some properties are exclusive to `.yml` files. +In dbt, you can define node configs in `properties.yml` files, in addition to `config()` blocks and `dbt_project.yml`. However, some special properties can only be defined in the `.yml` file and you cannot configure them using `config()` blocks or the `dbt_project.yml` file: Certain properties are special, because: @@ -71,7 +71,7 @@ Certain properties are special, because: - They don't make sense as hierarchical configuration - They're older properties that haven't yet been redefined as configs -This means "configs" can be set for multiple resources at once in the `dbt_project.yml` file, while "properties" can only be set for one resource at a time. The following properties _cannot_ be configured from `dbt_project.yml`: +These properties are: - [`description`](/reference/resource-properties/description) - [`tests`](/reference/resource-properties/tests) From 56fbe0ae0dd3c62839c4bd23865beb26a57a8390 Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Mon, 18 Sep 2023 14:38:53 +0100 Subject: [PATCH 011/165] change yaml to `properties.yml` --- website/docs/docs/build/semantic-models.md | 2 +- website/docs/reference/exposure-properties.md | 2 +- website/docs/reference/macro-properties.md | 2 +- website/docs/reference/source-properties.md | 2 +- 4 files changed, 4 insertions(+), 4 deletions(-) diff --git a/website/docs/docs/build/semantic-models.md b/website/docs/docs/build/semantic-models.md index 945282d183a..af4dff406c5 100644 --- a/website/docs/docs/build/semantic-models.md +++ b/website/docs/docs/build/semantic-models.md @@ -22,7 +22,7 @@ You can configure semantic models in your dbt project directory in a [`propertie -You can configure semantic models in your dbt project directory in a [`.yml` file](/reference/configs-and-properties#where-can-i-define-properties), however, you cannot actually define their properties within the `dbt_project.yml` file. +You can configure semantic models in your dbt project directory in a [`properties.yml` file](/reference/configs-and-properties#where-can-i-define-properties), however, you cannot actually define their properties within the `dbt_project.yml` file. Depending on your project structure, you can nest semantic models under a `metrics:` folder or organize them under project sources. diff --git a/website/docs/reference/exposure-properties.md b/website/docs/reference/exposure-properties.md index ffc494f6025..0bd4cf771af 100644 --- a/website/docs/reference/exposure-properties.md +++ b/website/docs/reference/exposure-properties.md @@ -11,7 +11,7 @@ description: "Read this guide to understand exposure properties in dbt." import PropsCallout from '/snippets/_config-prop-callout.md'; -Exposures are defined in `.yml` files nested under an `exposures:` key. You may define `exposures` in YAML files that also define `sources` or `models`.
+Exposures are defined in `properties.yml` files nested under an `exposures:` key. You may define `exposures` in YAML files that also define `sources` or `models`.
You can name these files `whatever_you_want.yml`, and nest them arbitrarily deeply in subfolders within the `models/` directory. diff --git a/website/docs/reference/macro-properties.md b/website/docs/reference/macro-properties.md index 685643a9aaa..cd9ca559bac 100644 --- a/website/docs/reference/macro-properties.md +++ b/website/docs/reference/macro-properties.md @@ -5,7 +5,7 @@ id: macro-properties import PropsCallout from '/snippets/_config-prop-callout.md'; -Macro properties can be declared in any `.yml` file. +Macro properties can be declared in any `properties.yml` file. You can name these files `whatever_you_want.yml` and nest them arbitrarily deep in sub-folders. diff --git a/website/docs/reference/source-properties.md b/website/docs/reference/source-properties.md index ead76040b05..d107881967e 100644 --- a/website/docs/reference/source-properties.md +++ b/website/docs/reference/source-properties.md @@ -11,7 +11,7 @@ description: "Learn how to use source properties in dbt." import PropsCallout from '/snippets/_config-prop-callout.md'; -Source properties can be declared in any `.yml` file in your `models/` directory (as defined by the [`model-paths` config](/reference/project-configs/model-paths)).
+Source properties can be declared in any `properties.yml` file in your `models/` directory (as defined by the [`model-paths` config](/reference/project-configs/model-paths)).
You can name these files `whatever_you_want.yml`, and nest them arbitrarily deeply in subfolders within the `models/` directory: From 5ec1c05b15bea8e52181681f7c9b1882eec25181 Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Tue, 7 Nov 2023 11:27:41 +0000 Subject: [PATCH 012/165] add table --- .../docs/reference/configs-and-properties.md | 18 +++++++++++++++++- 1 file changed, 17 insertions(+), 1 deletion(-) diff --git a/website/docs/reference/configs-and-properties.md b/website/docs/reference/configs-and-properties.md index 61e401f016d..c427a87e795 100644 --- a/website/docs/reference/configs-and-properties.md +++ b/website/docs/reference/configs-and-properties.md @@ -11,7 +11,7 @@ A rule of thumb: properties declare things _about_ your project resources; confi For example, you can use resource **properties** to: * Describe models, snapshots, seed files, and their columns -- Assert "truths" about a model, in the form of [tests](/docs/build/tests), e.g. "this `id` column is unique" +* Assert "truths" about a model, in the form of [tests](/docs/build/tests), e.g. "this `id` column is unique" * Define pointers to existing tables that contain raw data, in the form of [sources](/docs/build/sources), and assert the expected "freshness" of this raw data * Define official downstream uses of your data models, in the form of [exposures](/docs/build/exposures) @@ -21,6 +21,21 @@ Whereas you can use **configurations** to: * Declare whether a resource should persist its descriptions as comments in the database * Apply tags and "meta" properties +### Resource, properties, and configs table + +| Resource type | Description | Supported properties | Supported configurations | Config inheritance | +|---------------|------------------|-----------------------|-----------------------------|----------------------| +| Models | Describes models and their columns | columns, tests, docs, macros | tags, materialized, persist_docs, tags, etc. | `properties.yml` -> `.yml file` -> `dbt_project.yml` | +| Snapshots | Periodic snapshots of data | tests, macros | tags, materialized, etc. | In-file `config()` block -> `.yml file` -> `dbt_project.yml` | +| Seeds | Uploaded source data for models | tests, macros | tags, persist_docs, etc. | In-file `config()` block -> `.yml file` -> `dbt_project.yml` | +| Tests | Asserts "truths" about models | description, tags, macros | In-file `config()` block -> `.yml file` -> `dbt_project.yml` | +| Sources | Pointers to tables with raw data | description, columns, tests, docs, macros | tags, persist_docs, etc. | `properties.yml` -> `.yml file` -> `dbt_project.yml` | +| Exposures | Official downstream uses of data models | description, columns, tests, docs, macros | tags, materialized, etc. | `properties.yml` -> `.yml file` -> `dbt_project.yml` | +| | | | | | +| Configurations| Extra abilities for resources | | | In-file `config()` block -> `.yml file` -> `dbt_project.yml` | +| | | | | | +| Special properties (not configs)| Special properties with unique rendering context | description, tests, docs, columns, quote, source properties, exposure properties, macro properties | | `properties.yml` | + ## Where can I define configs? Depending on the resource type, configurations can be defined: @@ -202,3 +217,4 @@ Runtime Error ``` This error occurred because a semicolon (`;`) was accidentally used instead of a colon (`:`) after the `description` field. To resolve issues like this, find the `.yml` file referenced in the error message and fix any syntax errors present in the file. There are online YAML validators that can be helpful here, but please be mindful of submitting sensitive information to third-party applications! + From ef8c3bc39c8303032571d5c4794980a7921a2579 Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Wed, 8 Nov 2023 14:51:17 +0000 Subject: [PATCH 013/165] Update configs-and-properties.md --- .../docs/reference/configs-and-properties.md | 19 ++----------------- 1 file changed, 2 insertions(+), 17 deletions(-) diff --git a/website/docs/reference/configs-and-properties.md b/website/docs/reference/configs-and-properties.md index c427a87e795..9a45d2bd220 100644 --- a/website/docs/reference/configs-and-properties.md +++ b/website/docs/reference/configs-and-properties.md @@ -21,21 +21,6 @@ Whereas you can use **configurations** to: * Declare whether a resource should persist its descriptions as comments in the database * Apply tags and "meta" properties -### Resource, properties, and configs table - -| Resource type | Description | Supported properties | Supported configurations | Config inheritance | -|---------------|------------------|-----------------------|-----------------------------|----------------------| -| Models | Describes models and their columns | columns, tests, docs, macros | tags, materialized, persist_docs, tags, etc. | `properties.yml` -> `.yml file` -> `dbt_project.yml` | -| Snapshots | Periodic snapshots of data | tests, macros | tags, materialized, etc. | In-file `config()` block -> `.yml file` -> `dbt_project.yml` | -| Seeds | Uploaded source data for models | tests, macros | tags, persist_docs, etc. | In-file `config()` block -> `.yml file` -> `dbt_project.yml` | -| Tests | Asserts "truths" about models | description, tags, macros | In-file `config()` block -> `.yml file` -> `dbt_project.yml` | -| Sources | Pointers to tables with raw data | description, columns, tests, docs, macros | tags, persist_docs, etc. | `properties.yml` -> `.yml file` -> `dbt_project.yml` | -| Exposures | Official downstream uses of data models | description, columns, tests, docs, macros | tags, materialized, etc. | `properties.yml` -> `.yml file` -> `dbt_project.yml` | -| | | | | | -| Configurations| Extra abilities for resources | | | In-file `config()` block -> `.yml file` -> `dbt_project.yml` | -| | | | | | -| Special properties (not configs)| Special properties with unique rendering context | description, tests, docs, columns, quote, source properties, exposure properties, macro properties | | `properties.yml` | - ## Where can I define configs? Depending on the resource type, configurations can be defined: @@ -50,11 +35,11 @@ dbt prioritizes configurations in order of specificity, from most specificity to Note - Generic tests work a little differently when it comes to specificity. See [test configs](/reference/test-configs). -Within the project file, configurations are also applied hierarchically. The most-specific config always "wins": In the project file, configurations applied to a `marketing` subdirectory will take precedence over configurations applied to the entire `jaffle_shop` project. To apply a configuration to a model, or directory of models, define the resource path as nested dictionary keys. +Within the project file, configurations are also applied hierarchically. The most specific config always "wins": In the project file, configurations applied to a `marketing` subdirectory will take precedence over configurations applied to the entire `jaffle_shop` project. To apply a configuration to a model, or directory of models, define the resource path as nested dictionary keys. ### Combining configs -Most configurations are "clobbered" when applied hierarchically. Whenever a more-specific value is available, it will completely replace the less-specific value. Note that a few configs have different merge behavior: +Most configurations are "clobbered" when applied hierarchically. Whenever a more specific value is available, it will completely replace the less specific value. Note that a few configs have different merge behavior: - [`tags`](tags) are additive. If a model has some tags configured in `dbt_project.yml`, and more tags applied in its `.sql` file, the final set of tags will include all of them. - [`meta`](/reference/resource-configs/meta) dictionaries are merged (a more specific key-value pair replaces a less specific value with the same key) - [`pre-hook` and `post-hook`](/reference/resource-configs/pre-hook-post-hook) are also additive. From 02a3cae7ca77942a2f40027cce16c25fabc36443 Mon Sep 17 00:00:00 2001 From: Doug Beatty <44704949+dbeatty10@users.noreply.github.com> Date: Fri, 10 Nov 2023 08:40:11 -0700 Subject: [PATCH 014/165] Remove trailing space --- website/docs/reference/configs-and-properties.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/reference/configs-and-properties.md b/website/docs/reference/configs-and-properties.md index 9a45d2bd220..4fb9dda5aa2 100644 --- a/website/docs/reference/configs-and-properties.md +++ b/website/docs/reference/configs-and-properties.md @@ -54,7 +54,7 @@ We highly recommend that you define properties in dedicated paths alongside the #### schema.yml files -Previous versions of the docs referred to these as `schema.yml` files — we've moved away from that terminology since the word `schema` is used to mean other things when talking about databases, and people often thought that you _had_ to name these files `schema.yml`. +Previous versions of the docs referred to these as `schema.yml` files — we've moved away from that terminology since the word `schema` is used to mean other things when talking about databases, and people often thought that you _had_ to name these files `schema.yml`. Instead, we now refer to these files as `properties.yml` files. (Of course, you're still free to name your files `schema.yml`) From a1a8e7ff1f278c916aee2efd92bff6ae2b2750a2 Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Wed, 22 Nov 2023 07:26:03 -0500 Subject: [PATCH 015/165] Update docs.md --- website/docs/reference/resource-configs/docs.md | 15 +++------------ 1 file changed, 3 insertions(+), 12 deletions(-) diff --git a/website/docs/reference/resource-configs/docs.md b/website/docs/reference/resource-configs/docs.md index 12f95f8958e..c5e35dd64f4 100644 --- a/website/docs/reference/resource-configs/docs.md +++ b/website/docs/reference/resource-configs/docs.md @@ -20,9 +20,6 @@ default_value: {show: true} -You can configure `docs` behavior for many resources at once by setting in `dbt_project.yml`. You can also use the `docs` config in `properties.yaml` files, to set or override documentation behaviors for specific resources: - - @@ -48,9 +45,6 @@ This property is not implemented for sources. -You can use the docs property in YAML files, including the `dbt_project.yml`: - - ```yml @@ -67,8 +61,6 @@ seeds: -You can use the docs property in YAML files, including the `dbt_project.yml`: - ```yml @@ -85,9 +77,6 @@ snapshots: -You can use the docs property in YAML files, _except_ in `dbt_project.yml`. Refer to [Analysis properties](/reference/analysis-properties) for more info. - - ```yml @@ -104,7 +93,9 @@ analyses: -You can use the docs property in YAML files, _except_ in `dbt_project.yml`. Refer to [Macro properties](/reference/macro-properties) for more info. + From bc7c2f50ec734c085810a9df83c58ebe287ff9c0 Mon Sep 17 00:00:00 2001 From: Joel Labes Date: Tue, 28 Nov 2023 13:17:13 +1300 Subject: [PATCH 016/165] Update model-contracts.md --- website/docs/docs/collaborate/govern/model-contracts.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/docs/collaborate/govern/model-contracts.md b/website/docs/docs/collaborate/govern/model-contracts.md index 342d86c1a77..6a9980b73c5 100644 --- a/website/docs/docs/collaborate/govern/model-contracts.md +++ b/website/docs/docs/collaborate/govern/model-contracts.md @@ -91,7 +91,7 @@ When building a model with a defined contract, dbt will do two things differentl Select the adapter-specific tab for more information on [constraint](/reference/resource-properties/constraints) support across platforms. Constraints fall into three categories based on support and platform enforcement: - **Supported and enforced** — The model won't build if it violates the constraint. -- **Supported and not enforced** — The platform supports specifying the type of constraint, but a model can still build even if building the model violates the constraint. This constraint exists for metadata purposes only. This is common for modern cloud data warehouses and less common for legacy databases. +- **Supported and not enforced** — The platform supports specifying the type of constraint, but a model can still build even if building the model violates the constraint. This constraint exists for metadata purposes only. Enforcement is more common for transactional databases, unlike cloud data warehouses. - **Not supported and not enforced** — You can't specify the type of constraint for the platform. From 8a317004b72ae9231844bb1c953dba518af2c267 Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Tue, 28 Nov 2023 07:19:45 -0500 Subject: [PATCH 017/165] Update website/docs/docs/collaborate/govern/model-contracts.md --- website/docs/docs/collaborate/govern/model-contracts.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/docs/collaborate/govern/model-contracts.md b/website/docs/docs/collaborate/govern/model-contracts.md index 6a9980b73c5..bb011119958 100644 --- a/website/docs/docs/collaborate/govern/model-contracts.md +++ b/website/docs/docs/collaborate/govern/model-contracts.md @@ -91,7 +91,7 @@ When building a model with a defined contract, dbt will do two things differentl Select the adapter-specific tab for more information on [constraint](/reference/resource-properties/constraints) support across platforms. Constraints fall into three categories based on support and platform enforcement: - **Supported and enforced** — The model won't build if it violates the constraint. -- **Supported and not enforced** — The platform supports specifying the type of constraint, but a model can still build even if building the model violates the constraint. This constraint exists for metadata purposes only. Enforcement is more common for transactional databases, unlike cloud data warehouses. +- **Supported and not enforced** — The platform supports specifying the type of constraint, but a model can still build even if building the model violates the constraint. This constraint exists for metadata purposes only. This approach is more typical in cloud data warehouses than in transactional databases, where strict rule enforcement is more common. - **Not supported and not enforced** — You can't specify the type of constraint for the platform. From e79d4f0ed4066392825bdfb0ee73eda210efd246 Mon Sep 17 00:00:00 2001 From: Camille Kesser <101661315+camillek-db@users.noreply.github.com> Date: Thu, 30 Nov 2023 13:40:32 -0600 Subject: [PATCH 018/165] Fix z-order syntax --- website/docs/guides/dbt-models-on-databricks.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/guides/dbt-models-on-databricks.md b/website/docs/guides/dbt-models-on-databricks.md index 489a3c28467..283ef9b4ba4 100644 --- a/website/docs/guides/dbt-models-on-databricks.md +++ b/website/docs/guides/dbt-models-on-databricks.md @@ -72,7 +72,7 @@ Most compute engines work best when file sizes are between 32 MB and 256 MB. In Under the hood, Databricks will naturally [cluster data based on when it was ingested](https://www.databricks.com/blog/2022/11/18/introducing-ingestion-time-clustering-dbr-112.html). Since many queries include timestamps in `where` conditionals, this will naturally lead to a large amount of file skipping for enhanced performance. Nevertheless, if you have other high cardinality columns (basically columns with a large amount of distinct values such as id columns) that are frequently used in `join` keys or `where` conditionals, performance can typically be augmented further by leveraging Z-order. -The SQL syntax for the Z-Order command is `OPTIMIZE TABLE Z-ORDER BY (col1,col2,col3,etc)`. One caveat to be aware of is that you will rarely want to Z-Order by more than three columns. You will likely want to either run Z-order on run end after your model builds or run Z-Order as a separate scheduled job on a consistent cadence, whether it is daily, weekly, or monthly. +The SQL syntax for the Z-Order command is `OPTIMIZE table_name ZORDER BY (col1,col2,col3,etc)`. One caveat to be aware of is that you will rarely want to Z-Order by more than three columns. You will likely want to either run Z-order on run end after your model builds or run Z-Order as a separate scheduled job on a consistent cadence, whether it is daily, weekly, or monthly. ```sql config( From 3590022abfc320305002404e27a7d812965a3617 Mon Sep 17 00:00:00 2001 From: Ernesto Ongaro Date: Mon, 4 Dec 2023 11:56:34 +0000 Subject: [PATCH 019/165] Add related defer in Cloud doc --- website/docs/reference/node-selection/defer.md | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/website/docs/reference/node-selection/defer.md b/website/docs/reference/node-selection/defer.md index 03c3b2aac12..81a0f4a0328 100644 --- a/website/docs/reference/node-selection/defer.md +++ b/website/docs/reference/node-selection/defer.md @@ -234,3 +234,8 @@ dbt will check to see if `dev_alice.model_a` exists. If it doesn't exist, dbt wi + +## Related docs + +- [Using defer in dbt Cloud](/docs/cloud/about-cloud-develop-defer) + From 384066249358358a05dead9b6438369f9267b2da Mon Sep 17 00:00:00 2001 From: Mike Alfare Date: Mon, 4 Dec 2023 14:55:08 -0500 Subject: [PATCH 020/165] add materialized view configuration --- .../resource-configs/bigquery-configs.md | 97 +++++++++++++++++++ 1 file changed, 97 insertions(+) diff --git a/website/docs/reference/resource-configs/bigquery-configs.md b/website/docs/reference/resource-configs/bigquery-configs.md index ffbaa37c059..eabefe90d4e 100644 --- a/website/docs/reference/resource-configs/bigquery-configs.md +++ b/website/docs/reference/resource-configs/bigquery-configs.md @@ -718,3 +718,100 @@ Views with this configuration will be able to select from objects in `project_1. The `grant_access_to` config is not thread-safe when multiple views need to be authorized for the same dataset. The initial `dbt run` operation after a new `grant_access_to` config is added should therefore be executed in a single thread. Subsequent runs using the same configuration will not attempt to re-apply existing access grants, and can make use of multiple threads. + + +## Materialized views + +The BigQuery adapter supports [materialized views](https://cloud.google.com/bigquery/docs/materialized-views-intro) +with the following configuration parameters: + +| Parameter | Type | Default | Change Monitoring Support | Reference | +|------------------------------|----------------------|---------|---------------------------|--------------------------------------------------| +| `cluster_by` | LIST[STRING] | `None` | DROP/CREATE | [Clustering](#clustering-clause) | +| `partition_by` | DICT | `None` | DROP/CREATE | [Partitioning](#partition-clause) | +| `enable_refresh` | BOOLEAN | `True` | ALTER | [Auto-refresh](#auto-refresh) | +| `refresh_interval_minutes` | FLOAT | `30` | ALTER | [Auto-refresh](#auto-refresh) | +| `max_staleness` (in Preview) | INTERVAL | `None` | ALTER | [Auto-refresh](#auto-refresh) | +| `description` | STRING | `None` | ALTER | | +| `labels` | DICT[STRING, STRING] | `None` | ALTER | [Labels](#specifying-labels) | +| `hours_to_expiration` | INTEGER | `None` | ALTER | [Table expiration](controlling-table-expiration) | +| `kms_key_name` | STRING | `None` | ALTER | [KMS encryption](#using-kms-encryption) | + +#### Sample model file: + + + +```sql +{{ config( + materialized='materialized_view', + cluster_by=['', ...], + partition_by={ + 'field': '', + 'data_type': '', + + # only if `data_type` is not 'int64' + 'granularity': '' + + # only if `data_type` is 'int64' + 'range': { + 'start': , + 'end': , + 'interval': , + } + }, + + # auto-refresh options + enable_refresh=, + refresh_interval_minutes=, + max_staleness='', + + # additional options + description='', + labels={'': '', ...}, + hours_to_expiration=, + kms_key_name='', +) }} + +select * from {{ ref('my_base_table') }} +``` + + + +Many of these parameters correspond to their table counterparts and have been linked above. +The set of parameters which are unique to materialized views covers auto-refresh functionality, which is covered [below](#auto-refresh). + +Find more information about these parameters in the BigQuery docs: +- [CREATE MATERIALIZED VIEW statement](https://cloud.google.com/bigquery/docs/reference/standard-sql/data-definition-language#create_materialized_view_statement) +- [materialized_view_option_list](https://cloud.google.com/bigquery/docs/reference/standard-sql/data-definition-language#materialized_view_option_list) + +### Auto-refresh + +| Parameter | Type | Default | Change Monitoring Support | +|-------------------------------|----------|---------|---------------------------| +| `enable_refresh` | BOOLEAN | `True` | ALTER | +| `max_staleness` (in Preview) | INTERVAL | `None` | ALTER | +| `refresh_interval_minutes` | FLOAT | `30` | ALTER | + +BigQuery supports [automatic refresh](https://cloud.google.com/bigquery/docs/materialized-views-manage#automatic_refresh) configuration for materialized views. +By default, a materialized view will automatically refresh within 5 minutes of changes in the base table, but no more frequently than every 30 minutes. +BigQuery only officially supports configuration of the frequency (the "30 minutes" part); +however, there is a feature in preview that allows for configuration of the staleness (the "5 minutes" part). +dbt will monitor these parameters for changes and apply them using an `ALTER` statement. + +Find more information about these parameters in the BigQuery docs: +- [materialized_view_option_list](https://cloud.google.com/bigquery/docs/reference/standard-sql/data-definition-language#materialized_view_option_list) +- [max_staleness](https://cloud.google.com/bigquery/docs/materialized-views-create#max_staleness) + +### Limitations + +As with most data platforms, there are limitations associated with materialized views. Some worth noting include: + +- Materialized view SQL has a [limited feature set](https://cloud.google.com/bigquery/docs/materialized-views-create#supported-mvs) +- Materialized view SQL cannot be updated; the materialized view must go through a `--full-refresh` (DROP/CREATE) +- The `partition_by` clause on a materialized view must match that of the underlying base table +- While materialized views can have descriptions, materialized view *columns* cannot +- Recreating/dropping the base table requires recreating/dropping the materialized view + +Find more information about materialized view limitations in Google's BigQuery [docs](https://cloud.google.com/bigquery/docs/materialized-views-intro#limitations). + + From 2ccbc79b386aa9193357cb0ccbf643f4f55a1f19 Mon Sep 17 00:00:00 2001 From: Mike Alfare Date: Mon, 4 Dec 2023 17:27:58 -0500 Subject: [PATCH 021/165] add dynamic table configuration for snowflake --- .../resource-configs/snowflake-configs.md | 85 ++++++++++--------- 1 file changed, 46 insertions(+), 39 deletions(-) diff --git a/website/docs/reference/resource-configs/snowflake-configs.md b/website/docs/reference/resource-configs/snowflake-configs.md index 30c7966ec68..6c7ba86d353 100644 --- a/website/docs/reference/resource-configs/snowflake-configs.md +++ b/website/docs/reference/resource-configs/snowflake-configs.md @@ -346,82 +346,87 @@ In the configuration format for the model SQL file: ## Dynamic tables -The Snowflake adapter supports [dynamic tables](https://docs.snowflake.com/en/sql-reference/sql/create-dynamic-table). +The Snowflake adapter supports [dynamic tables](https://docs.snowflake.com/en/user-guide/dynamic-tables-about). This materialization is specific to Snowflake, which means that any model configuration that would normally come along for the ride from `dbt-core` (e.g. as with a `view`) may not be available for dynamic tables. This gap will decrease in future patches and versions. While this materialization is specific to Snowflake, it very much follows the implementation of [materialized views](/docs/build/materializations#Materialized-View). In particular, dynamic tables have access to the `on_configuration_change` setting. -There are also some limitations that we hope to address in the next version. +Dynamic tables are supported with the following configuration parameters: -### Parameters +| Parameter | Type | Required | Default | Change Monitoring Support | Reference | +|---------------------------|----------|----------|-----------|---------------------------|----------------------------------------------| +| `on_configuration_change` | STRING | NO | `'apply'` | N/A | | +| `target_lag` | STRING | YES | | ALTER | [Target lag](#target-lag) | +| `snowflake_warehouse` | STRING | YES | | ALTER | [Warehouse](#configuring-virtual-warehouses) | -Dynamic tables in `dbt-snowflake` require the following parameters: -- `target_lag` -- `snowflake_warehouse` -- `on_configuration_change` +#### Sample model file: -To learn more about each parameter and what values it can take, see -the Snowflake docs page: [`CREATE DYNAMIC TABLE: Parameters`](https://docs.snowflake.com/en/sql-reference/sql/create-dynamic-table). - -### Usage - -You can create a dynamic table by editing _one_ of these files: - -- the SQL file for your model -- the `dbt_project.yml` configuration file - -The following examples create a dynamic table: - - + ```sql {{ config( - materialized = 'dynamic_table', - snowflake_warehouse = 'snowflake_warehouse', - target_lag = '10 minutes', + materialized='dynamic_table', + on_configuration_change='', + target_lag='< { seconds | minutes | hours | days } | DOWNSTREAM>', + snowflake_warehouse='', ) }} + +select * from {{ ref('my_base_table') }} ``` +#### Sample project file: + ```yaml models: path: materialized: dynamic_table - snowflake_warehouse: snowflake_warehouse - target_lag: '10 minutes' + on_configuration_change: '' + snowflake_warehouse: '' + target_lag: '< { seconds | minutes | hours | days } | DOWNSTREAM>' ``` -### Monitored configuration changes +Find more information about these parameters in the Snowflake docs: +- [CREATE DYNAMIC TABLE](https://docs.snowflake.com/en/sql-reference/sql/create-dynamic-table) -The settings below are monitored for changes applicable to `on_configuration_change`. +### Target lag -#### Target lag +Snowflake allows two configuration scenarios for scheduling automatic refreshes: time-based and dependency-based. +For time-based automatic refreshes, provide a value of the form ` { seconds | minutes | hours | days }`. +For example, if the dynamic table needs to be updated every 30 minutes, use `target_lag='30 minutes'`. +However, for scenarios where the referenced objects are themselves dynamic tables, it might be desirable to refresh +the dynamic table whenever the underlying dynamic table is refreshed. In this scenario, use `target_lag='downstream'`. +This allows for refresh schedules to be controlled once, at the source, instead of at each layer. -Changes to `target_lag` can be applied by running an `ALTER` statement. Refreshing is essentially -always on for dynamic tables; this setting changes how frequently the dynamic table is updated. +### Limitations -#### Warehouse +As with materialized views on most data platforms, there are limitations associated with dynamic tables. Some worth noting include: -Changes to `snowflake_warehouse` can be applied via an `ALTER` statement. +- Dynamic table SQL has a [limited feature set](https://docs.snowflake.com/en/user-guide/dynamic-tables-tasks-create#query-constructs-not-currently-supported-in-dynamic-tables) +- Dynamic table SQL cannot be updated; the dynamic table must go through a `--full-refresh` (DROP/CREATE) +- Dynamic tables cannot be downstream from: materialized views, external tables, streams +- Dynamic tables cannot reference a view that is downstream from another dynamic table -### Limitations +Find more information about dynamic table limitations in Snowflake's [docs](https://docs.snowflake.com/en/user-guide/dynamic-tables-tasks-create#dynamic-table-limitations-and-supported-functions). + + #### Changing materialization to and from "dynamic_table" -Swapping an already materialized model to be a dynamic table and vice versa. -The workaround is manually dropping the existing materialization in the data warehouse prior to calling `dbt run`. -Normally, re-running with the `--full-refresh` flag would resolve this, but not in this case. -This would only need to be done once as the existing object would then be a dynamic table. +Version `1.6.x` does not support altering the materialization from a non-dynamic table be a dynamic table and vice versa. +Re-running with the `--full-refresh` does not resolve this either. +The workaround is manually dropping the existing model in the warehouse prior to calling `dbt run`. +This only needs to be done once for the conversion. For example, assume for the example model below, `my_model`, has already been materialized to the underlying data platform via `dbt run`. -If the user changes the model's config to `materialized="dynamic_table"`, they will get an error. +If the model config is updated to `materialized="dynamic_table"`, dbt will return an error. The workaround is to execute `DROP TABLE my_model` on the data warehouse before trying the model again. @@ -429,7 +434,7 @@ The workaround is to execute `DROP TABLE my_model` on the data warehouse before ```yaml {{ config( - materialized="table" # or any model type eg view, incremental + materialized="table" # or any model type (e.g. view, incremental) ) }} ``` @@ -437,3 +442,5 @@ The workaround is to execute `DROP TABLE my_model` on the data warehouse before + + From 89503381a1a0cbe76c4caacb9def3071e4a7d782 Mon Sep 17 00:00:00 2001 From: Joel Labes Date: Tue, 5 Dec 2023 15:52:47 +1300 Subject: [PATCH 022/165] Fix image issues in airflow guide --- website/docs/guides/airflow-and-dbt-cloud.md | 188 +++++++----------- .../connection-type-configured.png | Bin 0 -> 251473 bytes 2 files changed, 69 insertions(+), 119 deletions(-) create mode 100644 website/static/img/guides/orchestration/airflow-and-dbt-cloud/connection-type-configured.png diff --git a/website/docs/guides/airflow-and-dbt-cloud.md b/website/docs/guides/airflow-and-dbt-cloud.md index a3ff59af14e..0473043f16f 100644 --- a/website/docs/guides/airflow-and-dbt-cloud.md +++ b/website/docs/guides/airflow-and-dbt-cloud.md @@ -11,50 +11,29 @@ recently_updated: true ## Introduction -In some cases, [Airflow](https://airflow.apache.org/) may be the preferred orchestrator for your organization over working fully within dbt Cloud. There are a few reasons your team might be considering using Airflow to orchestrate your dbt jobs: - -- Your team is already using Airflow to orchestrate other processes -- Your team needs to ensure that a [dbt job](https://docs.getdbt.com/docs/dbt-cloud/cloud-overview#schedule-and-run-dbt-jobs-in-production) kicks off before or after another process outside of dbt Cloud -- Your team needs flexibility to manage more complex scheduling, such as kicking off one dbt job only after another has completed -- Your team wants to own their own orchestration solution -- You need code to work right now without starting from scratch - -### Prerequisites - -- [dbt Cloud Teams or Enterprise account](https://www.getdbt.com/pricing/) (with [admin access](https://docs.getdbt.com/docs/cloud/manage-access/enterprise-permissions)) in order to create a service token. Permissions for service tokens can be found [here](https://docs.getdbt.com/docs/dbt-cloud-apis/service-tokens#permissions-for-service-account-tokens). -- A [free Docker account](https://hub.docker.com/signup) in order to sign in to Docker Desktop, which will be installed in the initial setup. -- A local digital scratchpad for temporarily copy-pasting API keys and URLs - -### Airflow + dbt Core - -There are [so many great examples](https://gitlab.com/gitlab-data/analytics/-/blob/master/dags/transformation/dbt_snowplow_backfill.py) from GitLab through their open source data engineering work. This is especially appropriate if you are well-versed in Kubernetes, CI/CD, and docker task management when building your airflow pipelines. If this is you and your team, you’re in good hands reading through more details [here](https://about.gitlab.com/handbook/business-technology/data-team/platform/infrastructure/#airflow) and [here](https://about.gitlab.com/handbook/business-technology/data-team/platform/dbt-guide/). - -### Airflow + dbt Cloud API w/Custom Scripts - -This has served as a bridge until the fabled Astronomer + dbt Labs-built dbt Cloud provider became generally available [here](https://registry.astronomer.io/providers/dbt%20Cloud/versions/latest). - -There are many different permutations of this over time: - -- [Custom Python Scripts](https://github.com/sungchun12/airflow-dbt-cloud/blob/main/archive/dbt_cloud_example.py): This is an airflow DAG based on [custom python API utilities](https://github.com/sungchun12/airflow-dbt-cloud/blob/main/archive/dbt_cloud_utils.py) -- [Make API requests directly through the BashOperator based on the docs](https://docs.getdbt.com/dbt-cloud/api-v2-legacy#operation/triggerRun): You can make cURL requests to invoke dbt Cloud to do what you want -- For more options, check out the [official dbt Docs](/docs/deploy/deployments#airflow) on the various ways teams are running dbt in airflow - -These solutions are great, but can be difficult to trust as your team grows and management for things like: testing, job definitions, secrets, and pipelines increase past your team’s capacity. Roles become blurry (or were never clearly defined at the start!). Both data and analytics engineers start digging through custom logging within each other’s workflows to make heads or tails of where and what the issue really is. Not to mention that when the issue is found, it can be even harder to decide on the best path forward for safely implementing fixes. This complex workflow and unclear delineation on process management results in a lot of misunderstandings and wasted time just trying to get the process to work smoothly! +Many organization already use [Airflow](https://airflow.apache.org/) to orchestrate their data workflows. dbt Cloud works great with Airflow, letting you execute your dbt code in dbt Cloud while keeping orchestration duties with Airflow. This ensures your project's metadata (important for tools like dbt Explorer) is available and up-to-date, while still enabling you to use Airflow for general tasks such as: +- Scheduling other processes outside of dbt runs +- Ensuring that a [dbt job](https://docs.getdbt.com/docs/dbt-cloud/cloud-overview#schedule-and-run-dbt-jobs-in-production) kicks off before or after another process outside of dbt Cloud +- Triggering a dbt job only after another has completed In this guide, you'll learn how to: -1. Creating a working local Airflow environment -2. Invoking a dbt Cloud job with Airflow (with proof!) -3. Reusing tested and trusted Airflow code for your specific use cases +1. Create a working local Airflow environment +2. Invoke a dbt Cloud job with Airflow +3. Reuse tested and trusted Airflow code for your specific use cases You’ll also gain a better understanding of how this will: - Reduce the cognitive load when building and maintaining pipelines - Avoid dependency hell (think: `pip install` conflicts) -- Implement better recoveries from failures -- Define clearer workflows so that data and analytics engineers work better, together ♥️ +- Define clearer handoff of workflows between data engineers and analytics engineers +## Prerequisites + +- [dbt Cloud Teams or Enterprise account](https://www.getdbt.com/pricing/) (with [admin access](https://docs.getdbt.com/docs/cloud/manage-access/enterprise-permissions)) in order to create a service token. Permissions for service tokens can be found [here](https://docs.getdbt.com/docs/dbt-cloud-apis/service-tokens#permissions-for-service-account-tokens). +- A [free Docker account](https://hub.docker.com/signup) in order to sign in to Docker Desktop, which will be installed in the initial setup. +- A local digital scratchpad for temporarily copy-pasting API keys and URLs 🙌 Let’s get started! 🙌 @@ -72,7 +51,7 @@ brew install astro ## Install and start Docker Desktop -Docker allows us to spin up an environment with all the apps and dependencies we need for the example. +Docker allows us to spin up an environment with all the apps and dependencies we need for this guide. Follow the instructions [here](https://docs.docker.com/desktop/) to install Docker desktop for your own operating system. Once Docker is installed, ensure you have it up and running for the next steps. @@ -80,7 +59,7 @@ Follow the instructions [here](https://docs.docker.com/desktop/) to install Dock ## Clone the airflow-dbt-cloud repository -Open your terminal and clone the [airflow-dbt-cloud repository](https://github.com/sungchun12/airflow-dbt-cloud.git). This contains example Airflow DAGs that you’ll use to orchestrate your dbt Cloud job. Once cloned, navigate into the `airflow-dbt-cloud` project. +Open your terminal and clone the [airflow-dbt-cloud repository](https://github.com/sungchun12/airflow-dbt-cloud). This contains example Airflow DAGs that you’ll use to orchestrate your dbt Cloud job. Once cloned, navigate into the `airflow-dbt-cloud` project. ```bash git clone https://github.com/sungchun12/airflow-dbt-cloud.git @@ -91,12 +70,9 @@ cd airflow-dbt-cloud ## Start the Docker container -You can initialize an Astronomer project in an empty local directory using a Docker container, and then run your project locally using the `start` command. - -1. Run the following commands to initialize your project and start your local Airflow deployment: +1. From the `airflow-dbt-cloud` directory you cloned and opened in the prior step, run the following command to start your local Airflow deployment: ```bash - astro dev init astro dev start ``` @@ -110,10 +86,10 @@ You can initialize an Astronomer project in an empty local directory using a Doc Airflow Webserver: http://localhost:8080 Postgres Database: localhost:5432/postgres The default Airflow UI credentials are: admin:admin - The default Postrgres DB credentials are: postgres:postgres + The default Postgres DB credentials are: postgres:postgres ``` -2. Open the Airflow interface. Launch your web browser and navigate to the address for the **Airflow Webserver** from your output in Step 1. +2. Open the Airflow interface. Launch your web browser and navigate to the address for the **Airflow Webserver** from your output above (for us, `http://localhost:8080`). This will take you to your local instance of Airflow. You’ll need to log in with the **default credentials**: @@ -126,15 +102,15 @@ You can initialize an Astronomer project in an empty local directory using a Doc ## Create a dbt Cloud service token -Create a service token from within dbt Cloud using the instructions [found here](https://docs.getdbt.com/docs/dbt-cloud-apis/service-tokens). Ensure that you save a copy of the token, as you won’t be able to access this later. In this example we use `Account Admin`, but you can also use `Job Admin` instead for token permissions. +[Create a service token](/docs/dbt-cloud-apis/service-tokens) with `Job Admin` privileges from within dbt Cloud. Ensure that you save a copy of the token, as you won’t be able to access this later. ## Create a dbt Cloud job -In your dbt Cloud account create a job, paying special attention to the information in the bullets below. Additional information for creating a dbt Cloud job can be found [here](/guides/bigquery). +[Create a job in your dbt Cloud account](/docs/deploy/deploy-jobs#create-and-schedule-jobs), paying special attention to the information in the bullets below. -- Configure the job with the commands that you want to include when this job kicks off, as Airflow will be referring to the job’s configurations for this rather than being explicitly coded in the Airflow DAG. This job will run a set of commands rather than a single command. +- Configure the job with the full commands that you want to include when this job kicks off. This sample code has Airflow triggering the dbt Cloud job and all of its commands, instead of explicitly identifying individual models to run from inside of Airflow. - Ensure that the schedule is turned **off** since we’ll be using Airflow to kick things off. - Once you hit `save` on the job, make sure you copy the URL and save it for referencing later. The url will look similar to this: @@ -144,77 +120,59 @@ https://cloud.getdbt.com/#/accounts/{account_id}/projects/{project_id}/jobs/{job -## Add your dbt Cloud API token as a secure connection +## Connect dbt Cloud to Airflow - +Now you have all the working pieces to get up and running with Airflow + dbt Cloud. It's time to **set up a connection** and **run a DAG in Airflow** that kicks off a dbt Cloud job. -Now you have all the working pieces to get up and running with Airflow + dbt Cloud. Let’s dive into make this all work together. We will **set up a connection** and **run a DAG in Airflow** that kicks off a dbt Cloud job. - -1. Navigate to Admin and click on **Connections** +1. From the Airflow interface, navigate to Admin and click on **Connections** ![Airflow connections menu](/img/guides/orchestration/airflow-and-dbt-cloud/airflow-connections-menu.png) 2. Click on the `+` sign to add a new connection, then click on the drop down to search for the dbt Cloud Connection Type - ![Create connection](/img/guides/orchestration/airflow-and-dbt-cloud/create-connection.png) - ![Connection type](/img/guides/orchestration/airflow-and-dbt-cloud/connection-type.png) 3. Add in your connection details and your default dbt Cloud account id. This is found in your dbt Cloud URL after the accounts route section (`/accounts/{YOUR_ACCOUNT_ID}`), for example the account with id 16173 would see this in their URL: `https://cloud.getdbt.com/#/accounts/16173/projects/36467/jobs/65767/` -![https://lh3.googleusercontent.com/sRxe5xbv_LYhIKblc7eiY7AmByr1OibOac2_fIe54rpU3TBGwjMpdi_j0EPEFzM1_gNQXry7Jsm8aVw9wQBSNs1I6Cyzpvijaj0VGwSnmVf3OEV8Hv5EPOQHrwQgK2RhNBdyBxN2](https://lh3.googleusercontent.com/sRxe5xbv_LYhIKblc7eiY7AmByr1OibOac2_fIe54rpU3TBGwjMpdi_j0EPEFzM1_gNQXry7Jsm8aVw9wQBSNs1I6Cyzpvijaj0VGwSnmVf3OEV8Hv5EPOQHrwQgK2RhNBdyBxN2) + ![Connection type](/img/guides/orchestration/airflow-and-dbt-cloud/connection-type-configured.png) -## Add your `job_id` and `account_id` config details to the python file +## Update the placeholders in the sample code - Add your `job_id` and `account_id` config details to the python file: [dbt_cloud_provider_eltml.py](https://github.com/sungchun12/airflow-dbt-cloud/blob/main/dags/dbt_cloud_provider_eltml.py). + Add your `account_id` and `job_id` to the python file [dbt_cloud_provider_eltml.py](https://github.com/sungchun12/airflow-dbt-cloud/blob/main/dags/dbt_cloud_provider_eltml.py). -1. You’ll find these details within the dbt Cloud job URL, see the comments in the code snippet below for an example. +Both IDs are included inside of the dbt Cloud job URL as shown in the following snippets: - ```python - # dbt Cloud Job URL: https://cloud.getdbt.com/#/accounts/16173/projects/36467/jobs/65767/ - # account_id: 16173 - #job_id: 65767 +```python +# For the dbt Cloud Job URL https://cloud.getdbt.com/#/accounts/16173/projects/36467/jobs/65767/ +# The account_id is 16173 - # line 28 - default_args={"dbt_cloud_conn_id": "dbt_cloud", "account_id": 16173}, - - trigger_dbt_cloud_job_run = DbtCloudRunJobOperator( - task_id="trigger_dbt_cloud_job_run", - job_id=65767, # line 39 - check_interval=10, - timeout=300, - ) - ``` - -2. Turn on the DAG and verify the job succeeded after running. Note: screenshots taken from different job runs, but the user experience is consistent. - - ![https://lh6.googleusercontent.com/p8AqQRy0UGVLjDGPmcuGYmQ_BRodyL0Zis-eQgSmp69EHbKW51o4S-bCl1fXHlOmwpYEBxD0A-O1Q1hwt-VDVMO1wWH-AIeaoelBx06JXRJ0m1OcHaPpFKH0xDiduIhNlQhhbLiy](https://lh6.googleusercontent.com/p8AqQRy0UGVLjDGPmcuGYmQ_BRodyL0Zis-eQgSmp69EHbKW51o4S-bCl1fXHlOmwpYEBxD0A-O1Q1hwt-VDVMO1wWH-AIeaoelBx06JXRJ0m1OcHaPpFKH0xDiduIhNlQhhbLiy) - - ![Airflow DAG](/img/guides/orchestration/airflow-and-dbt-cloud/airflow-dag.png) - - ![Task run instance](/img/guides/orchestration/airflow-and-dbt-cloud/task-run-instance.png) - - ![https://lh6.googleusercontent.com/S9QdGhLAdioZ3x634CChugsJRiSVtTTd5CTXbRL8ADA6nSbAlNn4zV0jb3aC946c8SGi9FRTfyTFXqjcM-EBrJNK5hQ0HHAsR5Fj7NbdGoUfBI7xFmgeoPqnoYpjyZzRZlXkjtxS](https://lh6.googleusercontent.com/S9QdGhLAdioZ3x634CChugsJRiSVtTTd5CTXbRL8ADA6nSbAlNn4zV0jb3aC946c8SGi9FRTfyTFXqjcM-EBrJNK5hQ0HHAsR5Fj7NbdGoUfBI7xFmgeoPqnoYpjyZzRZlXkjtxS) - -## How do I rerun the dbt Cloud job and downstream tasks in my pipeline? - -If you have worked with dbt Cloud before, you have likely encountered cases where a job fails. In those cases, you have likely logged into dbt Cloud, investigated the error, and then manually restarted the job. - -This section of the guide will show you how to restart the job directly from Airflow. This will specifically run *just* the `trigger_dbt_cloud_job_run` and downstream tasks of the Airflow DAG and not the entire DAG. If only the transformation step fails, you don’t need to re-run the extract and load processes. Let’s jump into how to do that in Airflow. - -1. Click on the task +# Update line 28 +default_args={"dbt_cloud_conn_id": "dbt_cloud", "account_id": 16173}, +``` - ![Task DAG view](/img/guides/orchestration/airflow-and-dbt-cloud/task-dag-view.png) +```python +# For the dbt Cloud Job URL https://cloud.getdbt.com/#/accounts/16173/projects/36467/jobs/65767/ +# The job_id is 65767 + +# Update line 39 +trigger_dbt_cloud_job_run = DbtCloudRunJobOperator( + task_id="trigger_dbt_cloud_job_run", + job_id=65767, + check_interval=10, + timeout=300, + ) +``` -2. Clear the task instance + - ![Clear task instance](/img/guides/orchestration/airflow-and-dbt-cloud/clear-task-instance.png) +## Run the Airflow DAG - ![Approve clearing](/img/guides/orchestration/airflow-and-dbt-cloud/approve-clearing.png) +Turn on the DAG and trigger it to run. Verify the job succeeded after running. -3. Watch it rerun in real time +![Airflow DAG](/img/guides/orchestration/airflow-and-dbt-cloud/airflow-dag.png) - ![Re-run](/img/guides/orchestration/airflow-and-dbt-cloud/re-run.png) +Click Monitor Job Run to open the run details in dbt Cloud. +![Task run instance](/img/guides/orchestration/airflow-and-dbt-cloud/task-run-instance.png) ## Cleaning up @@ -224,9 +182,9 @@ At the end of this guide, make sure you shut down your docker container. When y $ astrocloud dev stop [+] Running 3/3 - ⠿ Container airflow-dbt-cloud_e3fe3c-webserver-1 Stopped 7.5s - ⠿ Container airflow-dbt-cloud_e3fe3c-scheduler-1 Stopped 3.3s - ⠿ Container airflow-dbt-cloud_e3fe3c-postgres-1 Stopped 0.3s + ⠿ Container airflow-dbt-cloud_e3fe3c-webserver-1 Stopped 7.5s + ⠿ Container airflow-dbt-cloud_e3fe3c-scheduler-1 Stopped 3.3s + ⠿ Container airflow-dbt-cloud_e3fe3c-postgres-1 Stopped 0.3s ``` To verify that the deployment has stopped, use the following command: @@ -244,37 +202,29 @@ airflow-dbt-cloud_e3fe3c-scheduler-1 exited airflow-dbt-cloud_e3fe3c-postgres-1 exited ``` - + ## Frequently asked questions ### How can we run specific subsections of the dbt DAG in Airflow? -Because of the way we configured the dbt Cloud job to run in Airflow, you can leave this job to your analytics engineers to define in the job configurations from dbt Cloud. If, for example, we need to run hourly-tagged models every hour and daily-tagged models daily, we can create jobs like `Hourly Run` or `Daily Run` and utilize the commands `dbt run -s tag:hourly` and `dbt run -s tag:daily` within each, respectively. We only need to grab our dbt Cloud `account` and `job id`, configure it in an Airflow DAG with the code provided, and then we can be on your way. See more node selection options: [here](/reference/node-selection/syntax) - -### How can I re-run models from the point of failure? - -You may want to parse the dbt DAG in Airflow to get the benefit of re-running from the point of failure. However, when you have hundreds of models in your DAG expanded out, it becomes useless for diagnosis and rerunning due to the overhead that comes along with creating an expansive Airflow DAG. +Because the Airflow DAG references dbt Cloud jobs, your analytics engineers can take responsibility for configuring the jobs in dbt Cloud. -You can’t re-run from failure natively in dbt Cloud today (feature coming!), but you can use a custom rerun parser. +For example, to run some models hourly and others daily, there will be jobs like `Hourly Run` or `Daily Run` using the commands `dbt run --select tag:hourly` and `dbt run --select tag:daily` respectively. Once configured in dbt Cloud, these can be added as steps in an Airflow DAG as shown in this guide. Refer to our full [node selection syntax docs here](/reference/node-selection/syntax). -Using a simple python script coupled with the dbt Cloud provider, you can: - -- Avoid managing artifacts in a separate storage bucket(dbt Cloud does this for you) -- Avoid building your own parsing logic -- Get clear logs on what models you're rerunning in dbt Cloud (without hard coding step override commands) - -Watch the video below to see how it works! +### How can I re-run models from the point of failure? - +You can trigger re-run from point of failure with the `rerun` API endpoint. See the docs on [retrying jobs](/docs/deploy/retry-jobs) for more information. ### Should Airflow run one big dbt job or many dbt jobs? -Overall we recommend being as purposeful and minimalistic as you can. This is because dbt manages all of the dependencies between models and the orchestration of running those dependencies in order, which in turn has benefits in terms of warehouse processing efforts. +dbt jobs are most effective when a build command contains as many models at once as is practical. This is because dbt manages the dependencies between models and coordinates running them in order, which ensures that your jobs can run in a highly parallelized fashion. It also streamlines the debugging process when a model fails and enables re-run from point of failure. + +As an explicit example, it's not recommended to have a dbt job for every single node in your DAG. Try combining your steps according to desired run frequency, or grouping by department (finance, marketing, customer success...) instead. ### We want to kick off our dbt jobs after our ingestion tool (such as Fivetran) / data pipelines are done loading data. Any best practices around that? -Our friends at Astronomer answer this question with this example: [here](https://registry.astronomer.io/dags/fivetran-dbt-cloud-census) +Astronomer's DAG registry has a sample workflow combining Fivetran, dbt Cloud and Census [here](https://registry.astronomer.io/dags/fivetran-dbt_cloud-census/versions/3.0.0). ### How do you set up a CI/CD workflow with Airflow? @@ -285,12 +235,12 @@ Check out these two resources for accomplishing your own CI/CD pipeline: ### Can dbt dynamically create tasks in the DAG like Airflow can? -We prefer to keep models bundled vs. unbundled. You can go this route, but if you have hundreds of dbt models, it’s more effective to let the dbt Cloud job handle the models and dependencies. Bundling provides the solution to clear observability when things go wrong - we've seen more success in having the ability to clearly see issues in a bundled dbt Cloud job than combing through the nodes of an expansive Airflow DAG. If you still have a use case for this level of control though, our friends at Astronomer answer this question [here](https://www.astronomer.io/blog/airflow-dbt-1/)! +As discussed above, we prefer to keep jobs bundled together and containing as many nodes as are necessary. If you must run nodes one at a time for some reason, then review [this article](https://www.astronomer.io/blog/airflow-dbt-1/) for some pointers. -### Can you trigger notifications if a dbt job fails with Airflow? Is there any way to access the status of the dbt Job to do that? +### Can you trigger notifications if a dbt job fails with Airflow? -Yes, either through [Airflow's email/slack](https://www.astronomer.io/guides/error-notifications-in-airflow/) functionality by itself or combined with [dbt Cloud's notifications](/docs/deploy/job-notifications), which support email and slack notifications. +Yes, either through [Airflow's email/slack](https://www.astronomer.io/guides/error-notifications-in-airflow/) functionality, or [dbt Cloud's notifications](/docs/deploy/job-notifications), which support email and Slack notifications. You could also create a [webhook](/docs/deploy/webhooks). -### Are there decision criteria for how to best work with dbt Cloud and airflow? +### How should I plan my dbt Cloud + Airflow implementation? -Check out this deep dive into planning your dbt Cloud + Airflow implementation [here](https://www.youtube.com/watch?v=n7IIThR8hGk)! +Check out [this recording](https://www.youtube.com/watch?v=n7IIThR8hGk) of a dbt meetup for some tips. diff --git a/website/static/img/guides/orchestration/airflow-and-dbt-cloud/connection-type-configured.png b/website/static/img/guides/orchestration/airflow-and-dbt-cloud/connection-type-configured.png new file mode 100644 index 0000000000000000000000000000000000000000..f77d3e188fcad1702a9071fbdf3891cd6aececd5 GIT binary patch literal 251473 zcmZU(19TwkEc1>qHaVb}|#&wrz7JHcsq`b7D@M`RBR!zVCb2_wBW+ ztGcRwRlTwH+ST0=%8F7*2zUqp002owT3i(XfGGw5Am8CWeP~oIF}eT%gla1>F=ZJs zF%o5G2XiZ1GXOw3A|(x0IcXI;@bYh2Sa2#T1Z@Eqm@zOJ6?ojU3MUh&EczK5t*f#9 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a/website/docs/guides/airflow-and-dbt-cloud.md +++ b/website/docs/guides/airflow-and-dbt-cloud.md @@ -31,7 +31,7 @@ You’ll also gain a better understanding of how this will: ## Prerequisites -- [dbt Cloud Teams or Enterprise account](https://www.getdbt.com/pricing/) (with [admin access](https://docs.getdbt.com/docs/cloud/manage-access/enterprise-permissions)) in order to create a service token. Permissions for service tokens can be found [here](https://docs.getdbt.com/docs/dbt-cloud-apis/service-tokens#permissions-for-service-account-tokens). +- [dbt Cloud Teams or Enterprise account](https://www.getdbt.com/pricing/) (with [admin access](/docs/cloud/manage-access/enterprise-permissions)) in order to create a service token. Permissions for service tokens can be found [here](/docs/dbt-cloud-apis/service-tokens#permissions-for-service-account-tokens). - A [free Docker account](https://hub.docker.com/signup) in order to sign in to Docker Desktop, which will be installed in the initial setup. - A local digital scratchpad for temporarily copy-pasting API keys and URLs From 5057aea21c992b9dbe556bb723027a9390b81165 Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Tue, 5 Dec 2023 07:26:27 -0500 Subject: [PATCH 024/165] Update website/docs/guides/airflow-and-dbt-cloud.md --- website/docs/guides/airflow-and-dbt-cloud.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/guides/airflow-and-dbt-cloud.md b/website/docs/guides/airflow-and-dbt-cloud.md index 89de21cd992..b3c331920c8 100644 --- a/website/docs/guides/airflow-and-dbt-cloud.md +++ b/website/docs/guides/airflow-and-dbt-cloud.md @@ -14,7 +14,7 @@ recently_updated: true Many organization already use [Airflow](https://airflow.apache.org/) to orchestrate their data workflows. dbt Cloud works great with Airflow, letting you execute your dbt code in dbt Cloud while keeping orchestration duties with Airflow. This ensures your project's metadata (important for tools like dbt Explorer) is available and up-to-date, while still enabling you to use Airflow for general tasks such as: - Scheduling other processes outside of dbt runs -- Ensuring that a [dbt job](https://docs.getdbt.com/docs/dbt-cloud/cloud-overview#schedule-and-run-dbt-jobs-in-production) kicks off before or after another process outside of dbt Cloud +- Ensuring that a [dbt job](/docs/dbt-cloud/cloud-overview#schedule-and-run-dbt-jobs-in-production) kicks off before or after another process outside of dbt Cloud - Triggering a dbt job only after another has completed In this guide, you'll learn how to: From a649e0e61f3d8fcd3727573c699db6c7dc5f49a8 Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Tue, 5 Dec 2023 11:14:00 -0500 Subject: [PATCH 025/165] Update website/docs/guides/airflow-and-dbt-cloud.md --- website/docs/guides/airflow-and-dbt-cloud.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/guides/airflow-and-dbt-cloud.md b/website/docs/guides/airflow-and-dbt-cloud.md index b3c331920c8..e7f754ef02d 100644 --- a/website/docs/guides/airflow-and-dbt-cloud.md +++ b/website/docs/guides/airflow-and-dbt-cloud.md @@ -14,7 +14,7 @@ recently_updated: true Many organization already use [Airflow](https://airflow.apache.org/) to orchestrate their data workflows. dbt Cloud works great with Airflow, letting you execute your dbt code in dbt Cloud while keeping orchestration duties with Airflow. This ensures your project's metadata (important for tools like dbt Explorer) is available and up-to-date, while still enabling you to use Airflow for general tasks such as: - Scheduling other processes outside of dbt runs -- Ensuring that a [dbt job](/docs/dbt-cloud/cloud-overview#schedule-and-run-dbt-jobs-in-production) kicks off before or after another process outside of dbt Cloud +- Ensuring that a [dbt job](/docs/deploy/job-scheduler) kicks off before or after another process outside of dbt Cloud - Triggering a dbt job only after another has completed In this guide, you'll learn how to: From bf57f5102375efbb1cddd19bb11c519eaddf0cab Mon Sep 17 00:00:00 2001 From: Mike Alfare Date: Tue, 5 Dec 2023 12:31:58 -0500 Subject: [PATCH 026/165] add materialized view configuration for redshift --- .../resource-configs/redshift-configs.md | 84 ++++++++++++++----- 1 file changed, 64 insertions(+), 20 deletions(-) diff --git a/website/docs/reference/resource-configs/redshift-configs.md b/website/docs/reference/resource-configs/redshift-configs.md index 9bd127a1e1a..ea0e4cad7b5 100644 --- a/website/docs/reference/resource-configs/redshift-configs.md +++ b/website/docs/reference/resource-configs/redshift-configs.md @@ -111,40 +111,82 @@ models: ## Materialized views -The Redshift adapter supports [materialized views](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-overview.html). -Redshift-specific configuration includes the typical `dist`, `sort_type`, `sort`, and `backup`. -For materialized views, there is also the `auto_refresh` setting, which allows Redshift to [automatically refresh](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-refresh.html) the materialized view for you. -The remaining configuration follows the general [materialized view](/docs/build/materializations#Materialized-View) configuration. -There are also some limitations that we hope to address in the next version. +The Redshift adapter supports [materialized views](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-overview.html) +with the following configuration parameters: -### Monitored configuration changes +| Parameter | Type | Default | Change Monitoring Support | Reference | +|----------------|--------------|------------------------|---------------------------|-------------------------------------------------| +| `dist` | STRING | `'EVEN'` | DROP/CREATE | [Sortkey / Distkey](#using-sortkey-and-distkey) | +| `sort` | LIST[STRING] | `None` | DROP/CREATE | [Sortkey / Distkey](#using-sortkey-and-distkey) | +| `sort_type` | STRING | `'AUTO'` if no `sort` | DROP/CREATE | [Sortkey / Distkey](#using-sortkey-and-distkey) | +| | | `'COMPOUND'` if `sort` | | | +| `auto_refresh` | BOOLEAN | `False` | ALTER | [Auto refresh](#auto-refresh) | +| `backup` | BOOLEAN | `True` | N/A | [Backup](#backup) | -The settings below are monitored for changes applicable to `on_configuration_change`. +#### Sample model file: -#### Dist + -Changes to `dist` will result in a full refresh of the existing materialized view (applied at the time of the next `dbt run` of the model). Redshift requires a materialized view to be -dropped and recreated to apply a change to the `distkey` or `diststyle`. +```sql +{{ config( + materialized='materialized_view', + dist='{ ALL | AUTO | EVEN | }', + sort=['', ...], + sort_type='{ AUTO | COMPOUND | INTERLEAVED }' + auto_refresh=, + backup=, +) }} + +select * from {{ ref('my_base_table') }} +``` + + + +Many of these parameters correspond to their table counterparts and have been linked above. +The set of parameters which are unique to materialized views covers auto-refresh and backup functionality, which is covered below. + +Find more information about these parameters in the Redshift docs: +- [CREATE MATERIALIZED VIEW](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-create-sql-command.html) + +#### Auto-refresh -#### Sort type, sort +| Parameter | Type | Default | Change Monitoring Support | +|----------------|---------|---------|---------------------------| +| `auto_refresh` | BOOLEAN | `False` | ALTER | -Changes to `sort_type` or `sort` will result in a full refresh. Redshift requires a materialized -view to be dropped and recreated to apply a change to the `sortkey` or `sortstyle`. +Redshift supports [automatic refresh](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-refresh.html#materialized-view-auto-refresh) configuration for materialized views. +By default, a materialized view will not automatically refresh. +dbt will monitor this parameter for changes and apply them using an `ALTER` statement. + +Find more information about this parameter in the Redshift docs: +- [Parameters](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-create-sql-command.html#mv_CREATE_MATERIALIZED_VIEW-parameters) #### Backup -Changes to `backup` will result in a full refresh. Redshift requires a materialized -view to be dropped and recreated to apply a change to the `backup` setting. +| Parameter | Type | Default | Change Monitoring Support | +|-----------|---------|---------|---------------------------| +| `backup` | BOOLEAN | `True` | N/A | -#### Auto refresh +Redshift supports [backup](https://docs.aws.amazon.com/redshift/latest/mgmt/working-with-snapshots.html) configuration of clusters at the object level. +This parameter identifies if the materialized view should be backed up as part of the cluster snapshot. +By default, a materialized view will be backed up during a cluster snapshot. +dbt cannot monitor this parameter as it is not queryable within Redshift. +If the value is changed, the materialized view will need to go through a `--full-refresh` in order to set it. -The `auto_refresh` setting can be updated via an `ALTER` statement. This setting effectively toggles -automatic refreshes on or off. The default setting for this config is off (`False`). If this -is the only configuration change for the materialized view, dbt will choose to apply -an `ALTER` statement instead of issuing a full refresh, +Find more information about this parameter in the Redshift docs: +- [Parameters](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-create-sql-command.html#mv_CREATE_MATERIALIZED_VIEW-parameters) ### Limitations +As with most data platforms, there are limitations associated with materialized views. Some worth noting include: + +- Materialized views cannot reference: views, temporary tables, user defined functions, late-binding tables +- Auto-refresh cannot be used if the materialized view references: mutable functions, external schemas, another materialized view + +Find more information about materialized view limitations in Redshift's [docs](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-create-sql-command.html#mv_CREATE_MATERIALIZED_VIEW-limitations). + + + #### Changing materialization from "materialized_view" to "table" or "view" Swapping a materialized view to a table or view is not supported. @@ -157,3 +199,5 @@ If the user changes the model's config to `materialized="table"`, they will get The workaround is to execute `DROP MATERIALIZED VIEW my_mv CASCADE` on the data warehouse before trying the model again. + + From 406b40851a34268a194b2ae0e15ca5c180c09e92 Mon Sep 17 00:00:00 2001 From: Mike Alfare Date: Tue, 5 Dec 2023 13:10:15 -0500 Subject: [PATCH 027/165] add materialized view configuration for postgres --- .../resource-configs/postgres-configs.md | 46 ++++++++++++++----- 1 file changed, 35 insertions(+), 11 deletions(-) diff --git a/website/docs/reference/resource-configs/postgres-configs.md b/website/docs/reference/resource-configs/postgres-configs.md index 97a695ee12e..f9bd4e11cbc 100644 --- a/website/docs/reference/resource-configs/postgres-configs.md +++ b/website/docs/reference/resource-configs/postgres-configs.md @@ -108,21 +108,43 @@ models: ## Materialized views -The Postgres adapter supports [materialized views](https://www.postgresql.org/docs/current/rules-materializedviews.html). -Indexes are the only configuration that is specific to `dbt-postgres`. -The remaining configuration follows the general [materialized view](/docs/build/materializations#materialized-view) configuration. -There are also some limitations that we hope to address in the next version. +The Postgres adapter supports [materialized views](https://www.postgresql.org/docs/current/rules-materializedviews.html) +with the following configuration parameters: -### Monitored configuration changes +| Parameter | Type | Required | Default | Change Monitoring Support | Reference | +|---------------------------|------------|----------|-----------|---------------------------|---------------------| +| `on_configuration_change` | STRING | NO | `'apply'` | N/A | | +| `indexes` | LIST[DICT] | NO | | ALTER | [Indexes](#indexes) | -The settings below are monitored for changes applicable to `on_configuration_change`. +#### Sample model file: -#### Indexes + -Index changes (`CREATE`, `DROP`) can be applied without the need to rebuild the materialized view. -This differs from a table model, where the table needs to be dropped and re-created to update the indexes. -If the `indexes` portion of the `config` block is updated, the changes will be detected and applied -directly to the materialized view in place. +```sql +{{ config( + materialized='materialized_view', + on_configuration_change='{ apply | continue | fail }' + indexes=[ + { + 'columns': ['', ...], + 'unique': }, + 'type': '{ HASH | B-TREE | GIST | SP-GIST | GIN | BRIN }', + ] +) }} + +select * from {{ ref('my_base_table') }} +``` + + + +The `indexes` parameter corresponds to that of a table, as linked above. +It's worth noting that, unlike with tables, dbt will monitor this parameter for changes and apply the changes without dropping the materialized view. +This happens via a `DROP/CREATE` of the indexes, which could be thought of as a `ALTER` of the materialized view. + +Find more information about materialized view parameters in the Postgres docs: +- [CREATE MATERIALIZED VIEW](https://www.postgresql.org/docs/current/sql-creatematerializedview.html) + + ### Limitations @@ -138,3 +160,5 @@ If the user changes the model's config to `materialized="materialized_view"`, th The solution is to execute `DROP TABLE my_model` on the data warehouse before trying the model again. + + From 99ba899848b319af3943c0b526ff6754de21bd29 Mon Sep 17 00:00:00 2001 From: Mike Alfare Date: Tue, 5 Dec 2023 13:16:15 -0500 Subject: [PATCH 028/165] add required column --- .../resource-configs/redshift-configs.md | 28 +++++++++---------- 1 file changed, 14 insertions(+), 14 deletions(-) diff --git a/website/docs/reference/resource-configs/redshift-configs.md b/website/docs/reference/resource-configs/redshift-configs.md index ea0e4cad7b5..635fecc5e02 100644 --- a/website/docs/reference/resource-configs/redshift-configs.md +++ b/website/docs/reference/resource-configs/redshift-configs.md @@ -114,14 +114,14 @@ models: The Redshift adapter supports [materialized views](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-overview.html) with the following configuration parameters: -| Parameter | Type | Default | Change Monitoring Support | Reference | -|----------------|--------------|------------------------|---------------------------|-------------------------------------------------| -| `dist` | STRING | `'EVEN'` | DROP/CREATE | [Sortkey / Distkey](#using-sortkey-and-distkey) | -| `sort` | LIST[STRING] | `None` | DROP/CREATE | [Sortkey / Distkey](#using-sortkey-and-distkey) | -| `sort_type` | STRING | `'AUTO'` if no `sort` | DROP/CREATE | [Sortkey / Distkey](#using-sortkey-and-distkey) | -| | | `'COMPOUND'` if `sort` | | | -| `auto_refresh` | BOOLEAN | `False` | ALTER | [Auto refresh](#auto-refresh) | -| `backup` | BOOLEAN | `True` | N/A | [Backup](#backup) | +| Parameter | Type | Required | Default | Change Monitoring Support | Reference | +|----------------|--------------|----------|------------------------|---------------------------|-------------------------------------------------| +| `dist` | STRING | NO | `'EVEN'` | DROP/CREATE | [Sortkey / Distkey](#using-sortkey-and-distkey) | +| `sort` | LIST[STRING] | NO | | DROP/CREATE | [Sortkey / Distkey](#using-sortkey-and-distkey) | +| `sort_type` | STRING | NO | `'AUTO'` if no `sort` | DROP/CREATE | [Sortkey / Distkey](#using-sortkey-and-distkey) | +| | | | `'COMPOUND'` if `sort` | | | +| `auto_refresh` | BOOLEAN | NO | `False` | ALTER | [Auto refresh](#auto-refresh) | +| `backup` | BOOLEAN | HO | `True` | N/A | [Backup](#backup) | #### Sample model file: @@ -150,9 +150,9 @@ Find more information about these parameters in the Redshift docs: #### Auto-refresh -| Parameter | Type | Default | Change Monitoring Support | -|----------------|---------|---------|---------------------------| -| `auto_refresh` | BOOLEAN | `False` | ALTER | +| Parameter | Type | Required | Default | Change Monitoring Support | +|----------------|---------|----------|---------|---------------------------| +| `auto_refresh` | BOOLEAN | NO | `False` | ALTER | Redshift supports [automatic refresh](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-refresh.html#materialized-view-auto-refresh) configuration for materialized views. By default, a materialized view will not automatically refresh. @@ -163,9 +163,9 @@ Find more information about this parameter in the Redshift docs: #### Backup -| Parameter | Type | Default | Change Monitoring Support | -|-----------|---------|---------|---------------------------| -| `backup` | BOOLEAN | `True` | N/A | +| Parameter | Type | Required | Default | Change Monitoring Support | +|-----------|---------|----------|---------|---------------------------| +| `backup` | BOOLEAN | NO | `True` | N/A | Redshift supports [backup](https://docs.aws.amazon.com/redshift/latest/mgmt/working-with-snapshots.html) configuration of clusters at the object level. This parameter identifies if the materialized view should be backed up as part of the cluster snapshot. From 0256471955d8480994f515a9e98092317939ea8d Mon Sep 17 00:00:00 2001 From: Mike Alfare Date: Tue, 5 Dec 2023 13:19:21 -0500 Subject: [PATCH 029/165] add required column --- .../resource-configs/bigquery-configs.md | 32 +++++++++---------- 1 file changed, 16 insertions(+), 16 deletions(-) diff --git a/website/docs/reference/resource-configs/bigquery-configs.md b/website/docs/reference/resource-configs/bigquery-configs.md index eabefe90d4e..9d2b4abed75 100644 --- a/website/docs/reference/resource-configs/bigquery-configs.md +++ b/website/docs/reference/resource-configs/bigquery-configs.md @@ -725,17 +725,17 @@ The `grant_access_to` config is not thread-safe when multiple views need to be a The BigQuery adapter supports [materialized views](https://cloud.google.com/bigquery/docs/materialized-views-intro) with the following configuration parameters: -| Parameter | Type | Default | Change Monitoring Support | Reference | -|------------------------------|----------------------|---------|---------------------------|--------------------------------------------------| -| `cluster_by` | LIST[STRING] | `None` | DROP/CREATE | [Clustering](#clustering-clause) | -| `partition_by` | DICT | `None` | DROP/CREATE | [Partitioning](#partition-clause) | -| `enable_refresh` | BOOLEAN | `True` | ALTER | [Auto-refresh](#auto-refresh) | -| `refresh_interval_minutes` | FLOAT | `30` | ALTER | [Auto-refresh](#auto-refresh) | -| `max_staleness` (in Preview) | INTERVAL | `None` | ALTER | [Auto-refresh](#auto-refresh) | -| `description` | STRING | `None` | ALTER | | -| `labels` | DICT[STRING, STRING] | `None` | ALTER | [Labels](#specifying-labels) | -| `hours_to_expiration` | INTEGER | `None` | ALTER | [Table expiration](controlling-table-expiration) | -| `kms_key_name` | STRING | `None` | ALTER | [KMS encryption](#using-kms-encryption) | +| Parameter | Type | Required | Default | Change Monitoring Support | Reference | +|------------------------------|----------------------|----------|---------|---------------------------|--------------------------------------------------| +| `cluster_by` | LIST[STRING] | NO | | DROP/CREATE | [Clustering](#clustering-clause) | +| `partition_by` | DICT | NO | | DROP/CREATE | [Partitioning](#partition-clause) | +| `enable_refresh` | BOOLEAN | NO | `True` | ALTER | [Auto-refresh](#auto-refresh) | +| `refresh_interval_minutes` | FLOAT | NO | `30` | ALTER | [Auto-refresh](#auto-refresh) | +| `max_staleness` (in Preview) | INTERVAL | NO | | ALTER | [Auto-refresh](#auto-refresh) | +| `description` | STRING | NO | | ALTER | | +| `labels` | DICT[STRING, STRING] | NO | | ALTER | [Labels](#specifying-labels) | +| `hours_to_expiration` | INTEGER | NO | | ALTER | [Table expiration](controlling-table-expiration) | +| `kms_key_name` | STRING | NO | | ALTER | [KMS encryption](#using-kms-encryption) | #### Sample model file: @@ -786,11 +786,11 @@ Find more information about these parameters in the BigQuery docs: ### Auto-refresh -| Parameter | Type | Default | Change Monitoring Support | -|-------------------------------|----------|---------|---------------------------| -| `enable_refresh` | BOOLEAN | `True` | ALTER | -| `max_staleness` (in Preview) | INTERVAL | `None` | ALTER | -| `refresh_interval_minutes` | FLOAT | `30` | ALTER | +| Parameter | Type | Required | Default | Change Monitoring Support | +|-------------------------------|----------|----------|---------|---------------------------| +| `enable_refresh` | BOOLEAN | NO | `True` | ALTER | +| `refresh_interval_minutes` | FLOAT | NO | `30` | ALTER | +| `max_staleness` (in Preview) | INTERVAL | NO | | ALTER | BigQuery supports [automatic refresh](https://cloud.google.com/bigquery/docs/materialized-views-manage#automatic_refresh) configuration for materialized views. By default, a materialized view will automatically refresh within 5 minutes of changes in the base table, but no more frequently than every 30 minutes. From 88d681930b0ed629ed3c5e464cc65ec692d4d036 Mon Sep 17 00:00:00 2001 From: Mike Alfare Date: Tue, 5 Dec 2023 13:23:01 -0500 Subject: [PATCH 030/165] add on_configuration_change --- .../resource-configs/bigquery-configs.md | 24 ++++++++++--------- 1 file changed, 13 insertions(+), 11 deletions(-) diff --git a/website/docs/reference/resource-configs/bigquery-configs.md b/website/docs/reference/resource-configs/bigquery-configs.md index 9d2b4abed75..97acb73ce33 100644 --- a/website/docs/reference/resource-configs/bigquery-configs.md +++ b/website/docs/reference/resource-configs/bigquery-configs.md @@ -725,17 +725,18 @@ The `grant_access_to` config is not thread-safe when multiple views need to be a The BigQuery adapter supports [materialized views](https://cloud.google.com/bigquery/docs/materialized-views-intro) with the following configuration parameters: -| Parameter | Type | Required | Default | Change Monitoring Support | Reference | -|------------------------------|----------------------|----------|---------|---------------------------|--------------------------------------------------| -| `cluster_by` | LIST[STRING] | NO | | DROP/CREATE | [Clustering](#clustering-clause) | -| `partition_by` | DICT | NO | | DROP/CREATE | [Partitioning](#partition-clause) | -| `enable_refresh` | BOOLEAN | NO | `True` | ALTER | [Auto-refresh](#auto-refresh) | -| `refresh_interval_minutes` | FLOAT | NO | `30` | ALTER | [Auto-refresh](#auto-refresh) | -| `max_staleness` (in Preview) | INTERVAL | NO | | ALTER | [Auto-refresh](#auto-refresh) | -| `description` | STRING | NO | | ALTER | | -| `labels` | DICT[STRING, STRING] | NO | | ALTER | [Labels](#specifying-labels) | -| `hours_to_expiration` | INTEGER | NO | | ALTER | [Table expiration](controlling-table-expiration) | -| `kms_key_name` | STRING | NO | | ALTER | [KMS encryption](#using-kms-encryption) | +| Parameter | Type | Required | Default | Change Monitoring Support | Reference | +|------------------------------|----------------------|----------|-----------|---------------------------|--------------------------------------------------| +| `on_configuration_change` | STRING | NO | `'apply'` | N/A | | +| `cluster_by` | LIST[STRING] | NO | | DROP/CREATE | [Clustering](#clustering-clause) | +| `partition_by` | DICT | NO | | DROP/CREATE | [Partitioning](#partition-clause) | +| `enable_refresh` | BOOLEAN | NO | `True` | ALTER | [Auto-refresh](#auto-refresh) | +| `refresh_interval_minutes` | FLOAT | NO | `30` | ALTER | [Auto-refresh](#auto-refresh) | +| `max_staleness` (in Preview) | INTERVAL | NO | | ALTER | [Auto-refresh](#auto-refresh) | +| `description` | STRING | NO | | ALTER | | +| `labels` | DICT[STRING, STRING] | NO | | ALTER | [Labels](#specifying-labels) | +| `hours_to_expiration` | INTEGER | NO | | ALTER | [Table expiration](controlling-table-expiration) | +| `kms_key_name` | STRING | NO | | ALTER | [KMS encryption](#using-kms-encryption) | #### Sample model file: @@ -744,6 +745,7 @@ with the following configuration parameters: ```sql {{ config( materialized='materialized_view', + on_configuration_change='{ apply | continue | fail }' cluster_by=['', ...], partition_by={ 'field': '', From bd764ceb01701d9d36ded64b4ae02843ac49a23c Mon Sep 17 00:00:00 2001 From: Mike Alfare Date: Tue, 5 Dec 2023 13:24:48 -0500 Subject: [PATCH 031/165] add on_configuration_change --- .../resource-configs/redshift-configs.md | 18 ++++++++++-------- 1 file changed, 10 insertions(+), 8 deletions(-) diff --git a/website/docs/reference/resource-configs/redshift-configs.md b/website/docs/reference/resource-configs/redshift-configs.md index 635fecc5e02..8c9b015ded3 100644 --- a/website/docs/reference/resource-configs/redshift-configs.md +++ b/website/docs/reference/resource-configs/redshift-configs.md @@ -114,14 +114,15 @@ models: The Redshift adapter supports [materialized views](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-overview.html) with the following configuration parameters: -| Parameter | Type | Required | Default | Change Monitoring Support | Reference | -|----------------|--------------|----------|------------------------|---------------------------|-------------------------------------------------| -| `dist` | STRING | NO | `'EVEN'` | DROP/CREATE | [Sortkey / Distkey](#using-sortkey-and-distkey) | -| `sort` | LIST[STRING] | NO | | DROP/CREATE | [Sortkey / Distkey](#using-sortkey-and-distkey) | -| `sort_type` | STRING | NO | `'AUTO'` if no `sort` | DROP/CREATE | [Sortkey / Distkey](#using-sortkey-and-distkey) | -| | | | `'COMPOUND'` if `sort` | | | -| `auto_refresh` | BOOLEAN | NO | `False` | ALTER | [Auto refresh](#auto-refresh) | -| `backup` | BOOLEAN | HO | `True` | N/A | [Backup](#backup) | +| Parameter | Type | Required | Default | Change Monitoring Support | Reference | +|---------------------------|--------------|----------|------------------------|---------------------------|-------------------------------------------------| +| `on_configuration_change` | STRING | NO | `'apply'` | N/A | | +| `dist` | STRING | NO | `'EVEN'` | DROP/CREATE | [Sortkey / Distkey](#using-sortkey-and-distkey) | +| `sort` | LIST[STRING] | NO | | DROP/CREATE | [Sortkey / Distkey](#using-sortkey-and-distkey) | +| `sort_type` | STRING | NO | `'AUTO'` if no `sort` | DROP/CREATE | [Sortkey / Distkey](#using-sortkey-and-distkey) | +| | | | `'COMPOUND'` if `sort` | | | +| `auto_refresh` | BOOLEAN | NO | `False` | ALTER | [Auto refresh](#auto-refresh) | +| `backup` | BOOLEAN | HO | `True` | N/A | [Backup](#backup) | #### Sample model file: @@ -130,6 +131,7 @@ with the following configuration parameters: ```sql {{ config( materialized='materialized_view', + on_configuration_change='{ apply | continue | fail }' dist='{ ALL | AUTO | EVEN | }', sort=['', ...], sort_type='{ AUTO | COMPOUND | INTERLEAVED }' From 3ca806c8e56a14ebf3c470a19bf625b8342a8379 Mon Sep 17 00:00:00 2001 From: Mike Alfare Date: Tue, 5 Dec 2023 13:25:57 -0500 Subject: [PATCH 032/165] add on_configuration_change --- website/docs/reference/resource-configs/snowflake-configs.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/reference/resource-configs/snowflake-configs.md b/website/docs/reference/resource-configs/snowflake-configs.md index 6c7ba86d353..39dd4430c4c 100644 --- a/website/docs/reference/resource-configs/snowflake-configs.md +++ b/website/docs/reference/resource-configs/snowflake-configs.md @@ -368,7 +368,7 @@ Dynamic tables are supported with the following configuration parameters: ```sql {{ config( materialized='dynamic_table', - on_configuration_change='', + on_configuration_change='{ apply | continue | fail }', target_lag='< { seconds | minutes | hours | days } | DOWNSTREAM>', snowflake_warehouse='', ) }} From c42bc24c0d484a4d10ad93825c2e3b1500a378c5 Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Tue, 5 Dec 2023 14:56:03 -0500 Subject: [PATCH 033/165] Changing `tests` to `data-tests` --- .../blog/2021-11-22-dbt-labs-pr-template.md | 2 +- website/blog/2021-11-22-primary-keys.md | 2 +- ...1-11-29-dbt-airflow-spiritual-alignment.md | 2 +- ...build-a-mature-dbt-project-from-scratch.md | 2 +- .../blog/2022-04-19-complex-deduplication.md | 2 +- website/blog/2022-09-28-analyst-to-ae.md | 2 +- .../best-practices/custom-generic-tests.md | 2 +- .../docs/build/{tests.md => data-tests.md} | 46 +++++++++---------- website/docs/docs/build/jinja-macros.md | 2 +- website/docs/docs/build/projects.md | 2 +- website/docs/docs/build/sources.md | 2 +- website/docs/docs/build/sql-models.md | 2 +- .../docs/docs/collaborate/documentation.md | 4 +- .../docs/docs/collaborate/explore-projects.md | 2 +- .../collaborate/govern/model-contracts.md | 2 +- .../03-upgrading-to-dbt-utils-v1.0.md | 2 +- .../core-upgrade/07-upgrading-to-v1.1.md | 2 +- .../core-upgrade/08-upgrading-to-v1.0.md | 2 +- .../core-upgrade/10-upgrading-to-v0.20.md | 6 +-- website/docs/docs/introduction.md | 2 +- .../faqs/Models/specifying-column-types.md | 2 +- .../faqs/Project/properties-not-in-config.md | 2 +- website/docs/faqs/Tests/available-tests.md | 2 +- .../docs/faqs/Tests/custom-test-thresholds.md | 2 +- website/docs/guides/building-packages.md | 2 +- website/docs/guides/dbt-python-snowpark.md | 2 +- ...oductionize-your-dbt-databricks-project.md | 2 +- website/docs/reference/commands/test.md | 2 +- .../docs/reference/configs-and-properties.md | 6 +-- .../{test-configs.md => data-test-configs.md} | 26 +++++------ website/docs/reference/dbt_project.yml.md | 6 +-- website/docs/reference/model-properties.md | 8 ++-- .../docs/reference/node-selection/methods.md | 2 +- .../reference/project-configs/test-paths.md | 2 +- .../docs/reference/resource-configs/alias.md | 2 +- .../reference/resource-configs/database.md | 2 +- .../docs/reference/resource-configs/meta.md | 2 +- .../resource-configs/store_failures_as.md | 4 +- .../reference/resource-properties/columns.md | 8 ++-- .../reference/resource-properties/config.md | 2 +- .../{tests.md => data-tests.md} | 38 +++++++-------- website/docs/reference/seed-properties.md | 4 +- website/docs/reference/snapshot-properties.md | 4 +- website/docs/reference/source-properties.md | 4 +- website/docs/terms/data-wrangling.md | 2 +- website/docs/terms/primary-key.md | 4 +- website/docs/terms/surrogate-key.md | 2 +- website/sidebars.js | 4 +- website/snippets/_run-result.md | 2 +- .../snippets/tutorial-add-tests-to-models.md | 2 +- 50 files changed, 121 insertions(+), 121 deletions(-) rename website/docs/docs/build/{tests.md => data-tests.md} (67%) rename website/docs/reference/{test-configs.md => data-test-configs.md} (87%) rename website/docs/reference/resource-properties/{tests.md => data-tests.md} (83%) diff --git a/website/blog/2021-11-22-dbt-labs-pr-template.md b/website/blog/2021-11-22-dbt-labs-pr-template.md index 40d4960ac18..439a02371ec 100644 --- a/website/blog/2021-11-22-dbt-labs-pr-template.md +++ b/website/blog/2021-11-22-dbt-labs-pr-template.md @@ -70,7 +70,7 @@ Checking for things like modularity and 1:1 relationships between sources and st #### Validation of models: -This section should show something to confirm that your model is doing what you intended it to do. This could be a [dbt test](/docs/build/tests) like uniqueness or not null, or could be an ad-hoc query that you wrote to validate your data. Here is a screenshot from a test run on a local development branch: +This section should show something to confirm that your model is doing what you intended it to do. This could be a [dbt test](/docs/build/data-tests) like uniqueness or not null, or could be an ad-hoc query that you wrote to validate your data. Here is a screenshot from a test run on a local development branch: ![test validation](/img/blog/pr-template-test-validation.png "dbt test validation") diff --git a/website/blog/2021-11-22-primary-keys.md b/website/blog/2021-11-22-primary-keys.md index 84c92055eb0..d5f87cddd94 100644 --- a/website/blog/2021-11-22-primary-keys.md +++ b/website/blog/2021-11-22-primary-keys.md @@ -51,7 +51,7 @@ In the days before testing your data was commonplace, you often found out that y ## How to test primary keys with dbt -Today, you can add two simple [dbt tests](/docs/build/tests) onto your primary keys and feel secure that you are going to catch the vast majority of problems in your data. +Today, you can add two simple [dbt tests](/docs/build/data-tests) onto your primary keys and feel secure that you are going to catch the vast majority of problems in your data. Not surprisingly, these two tests correspond to the two most common errors found on your primary keys, and are usually the first tests that teams testing data with dbt implement: diff --git a/website/blog/2021-11-29-dbt-airflow-spiritual-alignment.md b/website/blog/2021-11-29-dbt-airflow-spiritual-alignment.md index b179c0f5c7c..d20c7d139d0 100644 --- a/website/blog/2021-11-29-dbt-airflow-spiritual-alignment.md +++ b/website/blog/2021-11-29-dbt-airflow-spiritual-alignment.md @@ -90,7 +90,7 @@ So instead of getting bogged down in defining roles, let’s focus on hard skill The common skills needed for implementing any flavor of dbt (Core or Cloud) are: * SQL: ‘nuff said -* YAML: required to generate config files for [writing tests on data models](/docs/build/tests) +* YAML: required to generate config files for [writing tests on data models](/docs/build/data-tests) * [Jinja](/guides/using-jinja): allows you to write DRY code (using [macros](/docs/build/jinja-macros), for loops, if statements, etc) YAML + Jinja can be learned pretty quickly, but SQL is the non-negotiable you’ll need to get started. diff --git a/website/blog/2021-12-05-how-to-build-a-mature-dbt-project-from-scratch.md b/website/blog/2021-12-05-how-to-build-a-mature-dbt-project-from-scratch.md index 8ea387cf00c..f3a24a0febd 100644 --- a/website/blog/2021-12-05-how-to-build-a-mature-dbt-project-from-scratch.md +++ b/website/blog/2021-12-05-how-to-build-a-mature-dbt-project-from-scratch.md @@ -87,7 +87,7 @@ The most important thing we’re introducing when your project is an infant is t * Introduce modularity with [{{ ref() }}](/reference/dbt-jinja-functions/ref) and [{{ source() }}](/reference/dbt-jinja-functions/source) -* [Document](/docs/collaborate/documentation) and [test](/docs/build/tests) your first models +* [Document](/docs/collaborate/documentation) and [test](/docs/build/data-tests) your first models ![image alt text](/img/blog/building-a-mature-dbt-project-from-scratch/image_3.png) diff --git a/website/blog/2022-04-19-complex-deduplication.md b/website/blog/2022-04-19-complex-deduplication.md index daacff4eec6..f8cece85b61 100644 --- a/website/blog/2022-04-19-complex-deduplication.md +++ b/website/blog/2022-04-19-complex-deduplication.md @@ -146,7 +146,7 @@ select * from filter_real_diffs > *What happens in this step? You check your data because you are thorough!* -Good thing dbt has already built this for you. Add a [unique test](/docs/build/tests#generic-tests) to your YAML model block for your `grain_id` in this de-duped staging model, and give it a dbt test! +Good thing dbt has already built this for you. Add a [unique test](/docs/build/data-tests#generic-tests) to your YAML model block for your `grain_id` in this de-duped staging model, and give it a dbt test! ```yaml models: diff --git a/website/blog/2022-09-28-analyst-to-ae.md b/website/blog/2022-09-28-analyst-to-ae.md index 7c8ccaeabec..bf19bbae59e 100644 --- a/website/blog/2022-09-28-analyst-to-ae.md +++ b/website/blog/2022-09-28-analyst-to-ae.md @@ -111,7 +111,7 @@ The analyst caught the issue because they have the appropriate context to valida An analyst is able to identify which areas do *not* need to be 100% accurate, which means they can also identify which areas *do* need to be 100% accurate. -> dbt makes it very quick to add [data quality tests](/docs/build/tests). In fact, it’s so quick, that it’ll take an analyst longer to write up what tests they want than it would take for an analyst to completely finish coding them. +> dbt makes it very quick to add [data quality tests](/docs/build/data-tests). In fact, it’s so quick, that it’ll take an analyst longer to write up what tests they want than it would take for an analyst to completely finish coding them. When data quality issues are identified by the business, we often see that analysts are the first ones to be asked: diff --git a/website/docs/best-practices/custom-generic-tests.md b/website/docs/best-practices/custom-generic-tests.md index f2d84e38853..cd6dced8ad2 100644 --- a/website/docs/best-practices/custom-generic-tests.md +++ b/website/docs/best-practices/custom-generic-tests.md @@ -6,7 +6,7 @@ displayText: Writing custom generic tests hoverSnippet: Learn how to define your own custom generic tests. --- -dbt ships with [Not Null](/reference/resource-properties/tests#not-null), [Unique](/reference/resource-properties/tests#unique), [Relationships](/reference/resource-properties/tests#relationships), and [Accepted Values](/reference/resource-properties/tests#accepted-values) generic tests. (These used to be called "schema tests," and you'll still see that name in some places.) Under the hood, these generic tests are defined as `test` blocks (like macros) in a globally accessible dbt project. You can find the source code for these tests in the [global project](https://github.com/dbt-labs/dbt-core/tree/main/core/dbt/include/global_project/macros/generic_test_sql). +dbt ships with [Not Null](/reference/resource-properties/data-tests#not-null), [Unique](/reference/resource-properties/data-tests#unique), [Relationships](/reference/resource-properties/data-tests#relationships), and [Accepted Values](/reference/resource-properties/data-tests#accepted-values) generic tests. (These used to be called "schema tests," and you'll still see that name in some places.) Under the hood, these generic tests are defined as `test` blocks (like macros) in a globally accessible dbt project. You can find the source code for these tests in the [global project](https://github.com/dbt-labs/dbt-core/tree/main/core/dbt/include/global_project/macros/generic_test_sql). :::info There are tons of generic tests defined in open source packages, such as [dbt-utils](https://hub.getdbt.com/dbt-labs/dbt_utils/latest/) and [dbt-expectations](https://hub.getdbt.com/calogica/dbt_expectations/latest/) — the test you're looking for might already be here! diff --git a/website/docs/docs/build/tests.md b/website/docs/docs/build/data-tests.md similarity index 67% rename from website/docs/docs/build/tests.md rename to website/docs/docs/build/data-tests.md index 3d86dc6a81b..a63b25dffca 100644 --- a/website/docs/docs/build/tests.md +++ b/website/docs/docs/build/data-tests.md @@ -1,41 +1,41 @@ --- -title: "Add tests to your DAG" -sidebar_label: "Tests" -description: "Read this tutorial to learn how to use tests when building in dbt." +title: "Add data tests to your DAG" +sidebar_label: "Data tests" +description: "Read this tutorial to learn how to use data tests when building in dbt." search_weight: "heavy" -id: "tests" +id: "data-tests" keywords: - test, tests, testing, dag --- ## Related reference docs * [Test command](/reference/commands/test) -* [Test properties](/reference/resource-properties/tests) -* [Test configurations](/reference/test-configs) +* [Data test properties](/reference/resource-properties/data-tests) +* [Data test configurations](/reference/data-test-configs) * [Test selection examples](/reference/node-selection/test-selection-examples) ## Overview -Tests are assertions you make about your models and other resources in your dbt project (e.g. sources, seeds and snapshots). When you run `dbt test`, dbt will tell you if each test in your project passes or fails. +Data tests are assertions you make about your models and other resources in your dbt project (e.g. sources, seeds and snapshots). When you run `dbt test`, dbt will tell you if each test in your project passes or fails. -You can use tests to improve the integrity of the SQL in each model by making assertions about the results generated. Out of the box, you can test whether a specified column in a model only contains non-null values, unique values, or values that have a corresponding value in another model (for example, a `customer_id` for an `order` corresponds to an `id` in the `customers` model), and values from a specified list. You can extend tests to suit business logic specific to your organization – any assertion that you can make about your model in the form of a select query can be turned into a test. +You can use data tests to improve the integrity of the SQL in each model by making assertions about the results generated. Out of the box, you can test whether a specified column in a model only contains non-null values, unique values, or values that have a corresponding value in another model (for example, a `customer_id` for an `order` corresponds to an `id` in the `customers` model), and values from a specified list. You can extend data tests to suit business logic specific to your organization – any assertion that you can make about your model in the form of a select query can be turned into a data test. -Both types of tests return a set of failing records. Previously, generic/schema tests returned a numeric value representing failures. Generic tests (f.k.a. schema tests) are defined using `test` blocks instead of macros prefixed `test_`. +Both types of tests return a set of failing records. Previously, generic/schema tests returned a numeric value representing failures. Generic data tests (f.k.a. schema tests) are defined using `test` blocks instead of macros prefixed `test_`. -Like almost everything in dbt, tests are SQL queries. In particular, they are `select` statements that seek to grab "failing" records, ones that disprove your assertion. If you assert that a column is unique in a model, the test query selects for duplicates; if you assert that a column is never null, the test seeks after nulls. If the test returns zero failing rows, it passes, and your assertion has been validated. +Like almost everything in dbt, data tests are SQL queries. In particular, they are `select` statements that seek to grab "failing" records, ones that disprove your assertion. If you assert that a column is unique in a model, the test query selects for duplicates; if you assert that a column is never null, the test seeks after nulls. If the test returns zero failing rows, it passes, and your assertion has been validated. -There are two ways of defining tests in dbt: +There are two ways of defining data tests in dbt: * A **singular** test is testing in its simplest form: If you can write a SQL query that returns failing rows, you can save that query in a `.sql` file within your [test directory](/reference/project-configs/test-paths). It's now a test, and it will be executed by the `dbt test` command. * A **generic** test is a parameterized query that accepts arguments. The test query is defined in a special `test` block (like a [macro](jinja-macros)). Once defined, you can reference the generic test by name throughout your `.yml` files—define it on models, columns, sources, snapshots, and seeds. dbt ships with four generic tests built in, and we think you should use them! -Defining tests is a great way to confirm that your code is working correctly, and helps prevent regressions when your code changes. Because you can use them over and over again, making similar assertions with minor variations, generic tests tend to be much more common—they should make up the bulk of your dbt testing suite. That said, both ways of defining tests have their time and place. +Defining data tests is a great way to confirm that your code is working correctly, and helps prevent regressions when your code changes. Because you can use them over and over again, making similar assertions with minor variations, generic data tests tend to be much more common—they should make up the bulk of your dbt testing suite. That said, both ways of defining data tests have their time and place. -:::tip Creating your first tests +:::tip Creating your first data tests If you're new to dbt, we recommend that you check out our [quickstart guide](/guides) to build your first dbt project with models and tests. ::: -## Singular tests +## Singular data tests -The simplest way to define a test is by writing the exact SQL that will return failing records. We call these "singular" tests, because they're one-off assertions usable for a single purpose. +The simplest way to define a data test is by writing the exact SQL that will return failing records. We call these "singular" tests, because they're one-off assertions usable for a single purpose. These tests are defined in `.sql` files, typically in your `tests` directory (as defined by your [`test-paths` config](/reference/project-configs/test-paths)). You can use Jinja (including `ref` and `source`) in the test definition, just like you can when creating models. Each `.sql` file contains one `select` statement, and it defines one test: @@ -56,10 +56,10 @@ having not(total_amount >= 0) The name of this test is the name of the file: `assert_total_payment_amount_is_positive`. Simple enough. -Singular tests are easy to write—so easy that you may find yourself writing the same basic structure over and over, only changing the name of a column or model. By that point, the test isn't so singular! In that case, we recommend... +Singular data tests are easy to write—so easy that you may find yourself writing the same basic structure over and over, only changing the name of a column or model. By that point, the test isn't so singular! In that case, we recommend... ## Generic tests -Certain tests are generic: they can be reused over and over again. A generic test is defined in a `test` block, which contains a parametrized query and accepts arguments. It might look like: +Certain data tests are generic: they can be reused over and over again. A generic test is defined in a `test` block, which contains a parametrized query and accepts arguments. It might look like: ```sql {% test not_null(model, column_name) %} @@ -77,7 +77,7 @@ You'll notice that there are two arguments, `model` and `column_name`, which are If this is your first time working with adding properties to a resource, check out the docs on [declaring properties](/reference/configs-and-properties). ::: -Out of the box, dbt ships with four generic tests already defined: `unique`, `not_null`, `accepted_values` and `relationships`. Here's a full example using those tests on an `orders` model: +Out of the box, dbt ships with four generic data tests already defined: `unique`, `not_null`, `accepted_values` and `relationships`. Here's a full example using those tests on an `orders` model: ```yml version: 2 @@ -100,17 +100,17 @@ models: field: id ``` -In plain English, these tests translate to: +In plain English, these data tests translate to: * `unique`: the `order_id` column in the `orders` model should be unique * `not_null`: the `order_id` column in the `orders` model should not contain null values * `accepted_values`: the `status` column in the `orders` should be one of `'placed'`, `'shipped'`, `'completed'`, or `'returned'` * `relationships`: each `customer_id` in the `orders` model exists as an `id` in the `customers` (also known as referential integrity) -Behind the scenes, dbt constructs a `select` query for each test, using the parametrized query from the generic test block. These queries return the rows where your assertion is _not_ true; if the test returns zero rows, your assertion passes. +Behind the scenes, dbt constructs a `select` query for each data test, using the parametrized query from the generic test block. These queries return the rows where your assertion is _not_ true; if the test returns zero rows, your assertion passes. -You can find more information about these tests, and additional configurations (including [`severity`](/reference/resource-configs/severity) and [`tags`](/reference/resource-configs/tags)) in the [reference section](/reference/resource-properties/tests). +You can find more information about these tests, and additional configurations (including [`severity`](/reference/resource-configs/severity) and [`tags`](/reference/resource-configs/tags)) in the [reference section](/reference/resource-properties/data-tests). -### More generic tests +### More generic data tests Those four tests are enough to get you started. You'll quickly find you want to use a wider variety of tests—a good thing! You can also install generic tests from a package, or write your own, to use (and reuse) across your dbt project. Check out the [guide on custom generic tests](/best-practices/writing-custom-generic-tests) for more information. @@ -241,7 +241,7 @@ where {{ column_name }} is null ## Storing test failures -Normally, a test query will calculate failures as part of its execution. If you set the optional `--store-failures` flag, the [`store_failures`](/reference/resource-configs/store_failures), or the [`store_failures_as`](/reference/resource-configs/store_failures_as) configs, dbt will first save the results of a test query to a table in the database, and then query that table to calculate the number of failures. +Normally, a data test query will calculate failures as part of its execution. If you set the optional `--store-failures` flag, the [`store_failures`](/reference/resource-configs/store_failures), or the [`store_failures_as`](/reference/resource-configs/store_failures_as) configs, dbt will first save the results of a test query to a table in the database, and then query that table to calculate the number of failures. This workflow allows you to query and examine failing records much more quickly in development: diff --git a/website/docs/docs/build/jinja-macros.md b/website/docs/docs/build/jinja-macros.md index 135db740f75..074e648d410 100644 --- a/website/docs/docs/build/jinja-macros.md +++ b/website/docs/docs/build/jinja-macros.md @@ -23,7 +23,7 @@ Using Jinja turns your dbt project into a programming environment for SQL, givin In fact, if you've used the [`{{ ref() }}` function](/reference/dbt-jinja-functions/ref), you're already using Jinja! -Jinja can be used in any SQL in a dbt project, including [models](/docs/build/sql-models), [analyses](/docs/build/analyses), [tests](/docs/build/tests), and even [hooks](/docs/build/hooks-operations). +Jinja can be used in any SQL in a dbt project, including [models](/docs/build/sql-models), [analyses](/docs/build/analyses), [tests](/docs/build/data-tests), and even [hooks](/docs/build/hooks-operations). :::info Ready to get started with Jinja and macros? diff --git a/website/docs/docs/build/projects.md b/website/docs/docs/build/projects.md index a54f6042cce..d268ec09920 100644 --- a/website/docs/docs/build/projects.md +++ b/website/docs/docs/build/projects.md @@ -14,7 +14,7 @@ At a minimum, all a project needs is the `dbt_project.yml` project configuration | [models](/docs/build/models) | Each model lives in a single file and contains logic that either transforms raw data into a dataset that is ready for analytics or, more often, is an intermediate step in such a transformation. | | [snapshots](/docs/build/snapshots) | A way to capture the state of your mutable tables so you can refer to it later. | | [seeds](/docs/build/seeds) | CSV files with static data that you can load into your data platform with dbt. | -| [tests](/docs/build/tests) | SQL queries that you can write to test the models and resources in your project. | +| [tests](/docs/build/data-tests) | SQL queries that you can write to test the models and resources in your project. | | [macros](/docs/build/jinja-macros) | Blocks of code that you can reuse multiple times. | | [docs](/docs/collaborate/documentation) | Docs for your project that you can build. | | [sources](/docs/build/sources) | A way to name and describe the data loaded into your warehouse by your Extract and Load tools. | diff --git a/website/docs/docs/build/sources.md b/website/docs/docs/build/sources.md index a657b6257c9..ae6024a3e58 100644 --- a/website/docs/docs/build/sources.md +++ b/website/docs/docs/build/sources.md @@ -91,7 +91,7 @@ You can also: - Add tests to sources - Add descriptions to sources, that get rendered as part of your documentation site -These should be familiar concepts if you've already added tests and descriptions to your models (if not check out the guides on [testing](/docs/build/tests) and [documentation](/docs/collaborate/documentation)). +These should be familiar concepts if you've already added tests and descriptions to your models (if not check out the guides on [testing](/docs/build/data-tests) and [documentation](/docs/collaborate/documentation)). diff --git a/website/docs/docs/build/sql-models.md b/website/docs/docs/build/sql-models.md index 237ac84c0c2..a0dd174278b 100644 --- a/website/docs/docs/build/sql-models.md +++ b/website/docs/docs/build/sql-models.md @@ -262,7 +262,7 @@ Additionally, the `ref` function encourages you to write modular transformations ## Testing and documenting models -You can also document and test models — skip ahead to the section on [testing](/docs/build/tests) and [documentation](/docs/collaborate/documentation) for more information. +You can also document and test models — skip ahead to the section on [testing](/docs/build/data-tests) and [documentation](/docs/collaborate/documentation) for more information. ## Additional FAQs diff --git a/website/docs/docs/collaborate/documentation.md b/website/docs/docs/collaborate/documentation.md index 16a4e610c70..1a989806851 100644 --- a/website/docs/docs/collaborate/documentation.md +++ b/website/docs/docs/collaborate/documentation.md @@ -15,7 +15,7 @@ pagination_prev: null ## Assumed knowledge -* [Tests](/docs/build/tests) +* [Tests](/docs/build/data-tests) ## Overview @@ -32,7 +32,7 @@ Here's an example docs site: ## Adding descriptions to your project -To add descriptions to your project, use the `description:` key in the same files where you declare [tests](/docs/build/tests), like so: +To add descriptions to your project, use the `description:` key in the same files where you declare [tests](/docs/build/data-tests), like so: diff --git a/website/docs/docs/collaborate/explore-projects.md b/website/docs/docs/collaborate/explore-projects.md index 78fe6f45cc7..ed5dee93317 100644 --- a/website/docs/docs/collaborate/explore-projects.md +++ b/website/docs/docs/collaborate/explore-projects.md @@ -149,7 +149,7 @@ An example of the details you might get for a model: - **Lineage** graph — The model’s lineage graph that you can interact with. The graph includes one parent node and one child node from the model. Click the Expand icon in the graph's upper right corner to view the model in full lineage graph mode. - **Description** section — A [description of the model](/docs/collaborate/documentation#adding-descriptions-to-your-project). - **Recent** section — Information on the last time the model ran, how long it ran for, whether the run was successful, the job ID, and the run ID. - - **Tests** section — [Tests](/docs/build/tests) for the model, including a status indicator for the latest test status. A :white_check_mark: denotes a passing test. + - **Tests** section — [Tests](/docs/build/data-tests) for the model, including a status indicator for the latest test status. A :white_check_mark: denotes a passing test. - **Details** section — Key properties like the model’s relation name (for example, how it’s represented and how you can query it in the data platform: `database.schema.identifier`); model governance attributes like access, group, and if contracted; and more. - **Relationships** section — The nodes the model **Depends On**, is **Referenced by**, and (if applicable) is **Used by** for projects that have declared the models' project as a dependency. - **Code** tab — The source code and compiled code for the model. diff --git a/website/docs/docs/collaborate/govern/model-contracts.md b/website/docs/docs/collaborate/govern/model-contracts.md index 342d86c1a77..a083c3e6d2b 100644 --- a/website/docs/docs/collaborate/govern/model-contracts.md +++ b/website/docs/docs/collaborate/govern/model-contracts.md @@ -183,7 +183,7 @@ Any model meeting the criteria described above _can_ define a contract. We recom A model's contract defines the **shape** of the returned dataset. If the model's logic or input data doesn't conform to that shape, the model does not build. -[Tests](/docs/build/tests) are a more flexible mechanism for validating the content of your model _after_ it's built. So long as you can write the query, you can run the test. Tests are more configurable, such as with [custom severity thresholds](/reference/resource-configs/severity). They are easier to debug after finding failures, because you can query the already-built model, or [store the failing records in the data warehouse](/reference/resource-configs/store_failures). +[Tests](/docs/build/data-tests) are a more flexible mechanism for validating the content of your model _after_ it's built. So long as you can write the query, you can run the test. Tests are more configurable, such as with [custom severity thresholds](/reference/resource-configs/severity). They are easier to debug after finding failures, because you can query the already-built model, or [store the failing records in the data warehouse](/reference/resource-configs/store_failures). In some cases, you can replace a test with its equivalent constraint. This has the advantage of guaranteeing the validation at build time, and it probably requires less compute (cost) in your data platform. The prerequisites for replacing a test with a constraint are: - Making sure that your data platform can support and enforce the constraint that you need. Most platforms only enforce `not_null`. diff --git a/website/docs/docs/dbt-versions/core-upgrade/03-upgrading-to-dbt-utils-v1.0.md b/website/docs/docs/dbt-versions/core-upgrade/03-upgrading-to-dbt-utils-v1.0.md index a7b302c9a58..229a54627fc 100644 --- a/website/docs/docs/dbt-versions/core-upgrade/03-upgrading-to-dbt-utils-v1.0.md +++ b/website/docs/docs/dbt-versions/core-upgrade/03-upgrading-to-dbt-utils-v1.0.md @@ -82,7 +82,7 @@ models: # ...with this... where: "created_at > '2018-12-31'" ``` -**Note** — This may cause some tests to get the same autogenerated names. To resolve this, you can [define a custom name for a test](/reference/resource-properties/tests#define-a-custom-name-for-one-test). +**Note** — This may cause some tests to get the same autogenerated names. To resolve this, you can [define a custom name for a test](/reference/resource-properties/data-tests#define-a-custom-name-for-one-test). - The deprecated `unique_where` and `not_null_where` tests have been removed, because [where is now available natively to all tests](https://docs.getdbt.com/reference/resource-configs/where). To migrate, find and replace `dbt_utils.unique_where` with `unique` and `dbt_utils.not_null_where` with `not_null`. - `dbt_utils.current_timestamp()` is replaced by `dbt.current_timestamp()`. - Note that Postgres and Snowflake’s implementation of `dbt.current_timestamp()` differs from the old `dbt_utils` one ([full details here](https://github.com/dbt-labs/dbt-utils/pull/597#issuecomment-1231074577)). If you use Postgres or Snowflake and need identical backwards-compatible behavior, use `dbt.current_timestamp_backcompat()`. This discrepancy will hopefully be reconciled in a future version of dbt Core. diff --git a/website/docs/docs/dbt-versions/core-upgrade/07-upgrading-to-v1.1.md b/website/docs/docs/dbt-versions/core-upgrade/07-upgrading-to-v1.1.md index 12f0f42354a..868f3c7ed04 100644 --- a/website/docs/docs/dbt-versions/core-upgrade/07-upgrading-to-v1.1.md +++ b/website/docs/docs/dbt-versions/core-upgrade/07-upgrading-to-v1.1.md @@ -43,7 +43,7 @@ Expected a schema version of "https://schemas.getdbt.com/dbt/manifest/v5.json" i [**Incremental models**](/docs/build/incremental-models) can now accept a list of multiple columns as their `unique_key`, for models that need a combination of columns to uniquely identify each row. This is supported by the most common data warehouses, for incremental strategies that make use of the `unique_key` config (`merge` and `delete+insert`). -[**Generic tests**](/reference/resource-properties/tests) can define custom names. This is useful to "prettify" the synthetic name that dbt applies automatically. It's needed to disambiguate the case when the same generic test is defined multiple times with different configurations. +[**Generic tests**](/reference/resource-properties/data-tests) can define custom names. This is useful to "prettify" the synthetic name that dbt applies automatically. It's needed to disambiguate the case when the same generic test is defined multiple times with different configurations. [**Sources**](/reference/source-properties) can define configuration inline with other `.yml` properties, just like other resource types. The only supported config is `enabled`; you can use this to dynamically enable/disable sources based on environment or package variables. diff --git a/website/docs/docs/dbt-versions/core-upgrade/08-upgrading-to-v1.0.md b/website/docs/docs/dbt-versions/core-upgrade/08-upgrading-to-v1.0.md index 6e437638ef6..0460186551d 100644 --- a/website/docs/docs/dbt-versions/core-upgrade/08-upgrading-to-v1.0.md +++ b/website/docs/docs/dbt-versions/core-upgrade/08-upgrading-to-v1.0.md @@ -34,7 +34,7 @@ dbt Core major version 1.0 includes a number of breaking changes! Wherever possi ### Tests -The two **test types** are now "singular" and "generic" (instead of "data" and "schema", respectively). The `test_type:` selection method accepts `test_type:singular` and `test_type:generic`. (It will also accept `test_type:schema` and `test_type:data` for backwards compatibility.) **Not backwards compatible:** The `--data` and `--schema` flags to dbt test are no longer supported, and tests no longer have the tags `'data'` and `'schema'` automatically applied. Updated docs: [tests](/docs/build/tests), [test selection](/reference/node-selection/test-selection-examples), [selection methods](/reference/node-selection/methods). +The two **test types** are now "singular" and "generic" (instead of "data" and "schema", respectively). The `test_type:` selection method accepts `test_type:singular` and `test_type:generic`. (It will also accept `test_type:schema` and `test_type:data` for backwards compatibility.) **Not backwards compatible:** The `--data` and `--schema` flags to dbt test are no longer supported, and tests no longer have the tags `'data'` and `'schema'` automatically applied. Updated docs: [tests](/docs/build/data-tests), [test selection](/reference/node-selection/test-selection-examples), [selection methods](/reference/node-selection/methods). The `greedy` flag/property has been renamed to **`indirect_selection`**, which is now eager by default. **Note:** This reverts test selection to its pre-v0.20 behavior by default. `dbt test -s my_model` _will_ select multi-parent tests, such as `relationships`, that depend on unselected resources. To achieve the behavior change in v0.20 + v0.21, set `--indirect-selection=cautious` on the CLI or `indirect_selection: cautious` in YAML selectors. Updated docs: [test selection examples](/reference/node-selection/test-selection-examples), [yaml selectors](/reference/node-selection/yaml-selectors). diff --git a/website/docs/docs/dbt-versions/core-upgrade/10-upgrading-to-v0.20.md b/website/docs/docs/dbt-versions/core-upgrade/10-upgrading-to-v0.20.md index 9ff5695d5dc..be6054087b3 100644 --- a/website/docs/docs/dbt-versions/core-upgrade/10-upgrading-to-v0.20.md +++ b/website/docs/docs/dbt-versions/core-upgrade/10-upgrading-to-v0.20.md @@ -29,9 +29,9 @@ dbt Core v0.20 has reached the end of critical support. No new patch versions wi ### Tests -- [Building a dbt Project: tests](/docs/build/tests) -- [Test Configs](/reference/test-configs) -- [Test properties](/reference/resource-properties/tests) +- [Building a dbt Project: tests](/docs/build/data-tests) +- [Test Configs](/reference/data-test-configs) +- [Test properties](/reference/resource-properties/data-tests) - [Node Selection](/reference/node-selection/syntax) (with updated [test selection examples](/reference/node-selection/test-selection-examples)) - [Writing custom generic tests](/best-practices/writing-custom-generic-tests) diff --git a/website/docs/docs/introduction.md b/website/docs/docs/introduction.md index c575a9ae657..08564aeb2f0 100644 --- a/website/docs/docs/introduction.md +++ b/website/docs/docs/introduction.md @@ -56,7 +56,7 @@ As a dbt user, your main focus will be on writing models (i.e. select queries) t | Use a code compiler | SQL files can contain Jinja, a lightweight templating language. Using Jinja in SQL provides a way to use control structures in your queries. For example, `if` statements and `for` loops. It also enables repeated SQL to be shared through `macros`. Read more about [Macros](/docs/build/jinja-macros).| | Determine the order of model execution | Often, when transforming data, it makes sense to do so in a staged approach. dbt provides a mechanism to implement transformations in stages through the [ref function](/reference/dbt-jinja-functions/ref). Rather than selecting from existing tables and views in your warehouse, you can select from another model.| | Document your dbt project | dbt provides a mechanism to write, version-control, and share documentation for your dbt models. You can write descriptions (in plain text or markdown) for each model and field. In dbt Cloud, you can auto-generate the documentation when your dbt project runs. Read more about the [Documentation](/docs/collaborate/documentation).| -| Test your models | Tests provide a way to improve the integrity of the SQL in each model by making assertions about the results generated by a model. Read more about writing tests for your models [Testing](/docs/build/tests)| +| Test your models | Tests provide a way to improve the integrity of the SQL in each model by making assertions about the results generated by a model. Read more about writing tests for your models [Testing](/docs/build/data-tests)| | Manage packages | dbt ships with a package manager, which allows analysts to use and publish both public and private repositories of dbt code which can then be referenced by others. Read more about [Package Management](/docs/build/packages). | | Load seed files| Often in analytics, raw values need to be mapped to a more readable value (for example, converting a country-code to a country name) or enriched with static or infrequently changing data. These data sources, known as seed files, can be saved as a CSV file in your `project` and loaded into your data warehouse using the `seed` command. Read more about [Seeds](/docs/build/seeds).| | Snapshot data | Often, records in a data source are mutable, in that they change over time. This can be difficult to handle in analytics if you want to reconstruct historic values. dbt provides a mechanism to snapshot raw data for a point in time, through use of [snapshots](/docs/build/snapshots).| diff --git a/website/docs/faqs/Models/specifying-column-types.md b/website/docs/faqs/Models/specifying-column-types.md index 8e8379c4ec1..ff29085f160 100644 --- a/website/docs/faqs/Models/specifying-column-types.md +++ b/website/docs/faqs/Models/specifying-column-types.md @@ -38,6 +38,6 @@ So long as your model queries return the correct column type, the table you crea To define additional column options: -* Rather than enforcing uniqueness and not-null constraints on your column, use dbt's [testing](/docs/build/tests) functionality to check that your assertions about your model hold true. +* Rather than enforcing uniqueness and not-null constraints on your column, use dbt's [testing](/docs/build/data-tests) functionality to check that your assertions about your model hold true. * Rather than creating default values for a column, use SQL to express defaults (e.g. `coalesce(updated_at, current_timestamp()) as updated_at`) * In edge-cases where you _do_ need to alter a column (e.g. column-level encoding on Redshift), consider implementing this via a [post-hook](/reference/resource-configs/pre-hook-post-hook). diff --git a/website/docs/faqs/Project/properties-not-in-config.md b/website/docs/faqs/Project/properties-not-in-config.md index d1aea32b687..76de58404a9 100644 --- a/website/docs/faqs/Project/properties-not-in-config.md +++ b/website/docs/faqs/Project/properties-not-in-config.md @@ -16,7 +16,7 @@ Certain properties are special, because: These properties are: - [`description`](/reference/resource-properties/description) -- [`tests`](/reference/resource-properties/tests) +- [`tests`](/reference/resource-properties/data-tests) - [`docs`](/reference/resource-configs/docs) - `columns` - [`quote`](/reference/resource-properties/quote) diff --git a/website/docs/faqs/Tests/available-tests.md b/website/docs/faqs/Tests/available-tests.md index f08e6841bd0..225331d2256 100644 --- a/website/docs/faqs/Tests/available-tests.md +++ b/website/docs/faqs/Tests/available-tests.md @@ -12,6 +12,6 @@ Out of the box, dbt ships with the following tests: * `accepted_values` * `relationships` (i.e. referential integrity) -You can also write your own [custom schema tests](/docs/build/tests). +You can also write your own [custom schema tests](/docs/build/data-tests). Some additional custom schema tests have been open-sourced in the [dbt-utils package](https://github.com/dbt-labs/dbt-utils/tree/0.2.4/#schema-tests), check out the docs on [packages](/docs/build/packages) to learn how to make these tests available in your project. diff --git a/website/docs/faqs/Tests/custom-test-thresholds.md b/website/docs/faqs/Tests/custom-test-thresholds.md index 34d2eec7494..400a5b4e28b 100644 --- a/website/docs/faqs/Tests/custom-test-thresholds.md +++ b/website/docs/faqs/Tests/custom-test-thresholds.md @@ -10,5 +10,5 @@ As of `v0.20.0`, you can use the `error_if` and `warn_if` configs to set custom For dbt `v0.19.0` and earlier, you could try these possible solutions: -* Setting the [severity](/reference/resource-properties/tests#severity) to `warn`, or: +* Setting the [severity](/reference/resource-properties/data-tests#severity) to `warn`, or: * Writing a [custom generic test](/best-practices/writing-custom-generic-tests) that accepts a threshold argument ([example](https://discourse.getdbt.com/t/creating-an-error-threshold-for-schema-tests/966)) diff --git a/website/docs/guides/building-packages.md b/website/docs/guides/building-packages.md index 641a1c6af6d..55f0c2ed912 100644 --- a/website/docs/guides/building-packages.md +++ b/website/docs/guides/building-packages.md @@ -104,7 +104,7 @@ dbt makes it possible for users of your package to override your model properties defined in a `.yml` file --> config defined in the project file. -Note - Generic tests work a little differently when it comes to specificity. See [test configs](/reference/test-configs). +Note - Generic tests work a little differently when it comes to specificity. See [test configs](/reference/data-test-configs). Within the project file, configurations are also applied hierarchically. The most specific config always "wins": In the project file, configurations applied to a `marketing` subdirectory will take precedence over configurations applied to the entire `jaffle_shop` project. To apply a configuration to a model, or directory of models, define the resource path as nested dictionary keys. @@ -76,7 +76,7 @@ Certain properties are special, because: These properties are: - [`description`](/reference/resource-properties/description) -- [`tests`](/reference/resource-properties/tests) +- [`tests`](/reference/resource-properties/data-tests) - [`docs`](/reference/resource-configs/docs) - [`columns`](/reference/resource-properties/columns) - [`quote`](/reference/resource-properties/quote) diff --git a/website/docs/reference/test-configs.md b/website/docs/reference/data-test-configs.md similarity index 87% rename from website/docs/reference/test-configs.md rename to website/docs/reference/data-test-configs.md index 960e8d5471a..13154832cef 100644 --- a/website/docs/reference/test-configs.md +++ b/website/docs/reference/data-test-configs.md @@ -1,8 +1,8 @@ --- -title: Test configurations -description: "Read this guide to learn about using test configurations in dbt." +title: Data test configurations +description: "Read this guide to learn about using data test configurations in dbt." meta: - resource_type: Tests + resource_type: Data tests --- import ConfigResource from '/snippets/_config-description-resource.md'; import ConfigGeneral from '/snippets/_config-description-general.md'; @@ -10,20 +10,20 @@ import ConfigGeneral from '/snippets/_config-description-general.md'; ## Related documentation -* [Tests](/docs/build/tests) +* [Data tests](/docs/build/data-tests) -Tests can be configured in a few different ways: -1. Properties within `.yml` definition (generic tests only, see [test properties](/reference/resource-properties/tests) for full syntax) +Data tests can be configured in a few different ways: +1. Properties within `.yml` definition (generic tests only, see [test properties](/reference/resource-properties/data-tests) for full syntax) 2. A `config()` block within the test's SQL definition 3. In `dbt_project.yml` -Test configs are applied hierarchically, in the order of specificity outlined above. In the case of a singular test, the `config()` block within the SQL definition takes precedence over configs in the project file. In the case of a specific instance of a generic test, the test's `.yml` properties would take precedence over any values set in its generic SQL definition's `config()`, which in turn would take precedence over values set in `dbt_project.yml`. +Data test configs are applied hierarchically, in the order of specificity outlined above. In the case of a singular test, the `config()` block within the SQL definition takes precedence over configs in the project file. In the case of a specific instance of a generic test, the test's `.yml` properties would take precedence over any values set in its generic SQL definition's `config()`, which in turn would take precedence over values set in `dbt_project.yml`. ## Available configurations Click the link on each configuration option to read more about what it can do. -### Test-specific configurations +### Data test-specific configurations @@ -204,7 +204,7 @@ version: 2 [alias](/reference/resource-configs/alias): ``` -This configuration mechanism is supported for specific instances of generic tests only. To configure a specific singular test, you should use the `config()` macro in its SQL definition. +This configuration mechanism is supported for specific instances of generic data tests only. To configure a specific singular test, you should use the `config()` macro in its SQL definition. @@ -216,7 +216,7 @@ This configuration mechanism is supported for specific instances of generic test #### Add a tag to one test -If a specific instance of a generic test: +If a specific instance of a generic data test: @@ -232,7 +232,7 @@ models: -If a singular test: +If a singular data test: @@ -244,7 +244,7 @@ select ... -#### Set the default severity for all instances of a generic test +#### Set the default severity for all instances of a generic data test @@ -260,7 +260,7 @@ select ... -#### Disable all tests from a package +#### Disable alldata tests from a package diff --git a/website/docs/reference/dbt_project.yml.md b/website/docs/reference/dbt_project.yml.md index 34af0f696c7..7b5d54c3e03 100644 --- a/website/docs/reference/dbt_project.yml.md +++ b/website/docs/reference/dbt_project.yml.md @@ -81,7 +81,7 @@ sources: [](source-configs) tests: - [](/reference/test-configs) + [](/reference/data-test-configs) vars: [](/docs/build/project-variables) @@ -153,7 +153,7 @@ sources: [](source-configs) tests: - [](/reference/test-configs) + [](/reference/data-test-configs) vars: [](/docs/build/project-variables) @@ -222,7 +222,7 @@ sources: [](source-configs) tests: - [](/reference/test-configs) + [](/reference/data-test-configs) vars: [](/docs/build/project-variables) diff --git a/website/docs/reference/model-properties.md b/website/docs/reference/model-properties.md index 63adc1f0d63..a384307678f 100644 --- a/website/docs/reference/model-properties.md +++ b/website/docs/reference/model-properties.md @@ -23,7 +23,7 @@ models: [](/reference/model-configs): [constraints](/reference/resource-properties/constraints): - - [tests](/reference/resource-properties/tests): + [tests](/reference/resource-properties/data-tests): - - ... # declare additional tests [columns](/reference/resource-properties/columns): @@ -33,7 +33,7 @@ models: [quote](/reference/resource-properties/quote): true | false [constraints](/reference/resource-properties/constraints): - - [tests](/reference/resource-properties/tests): + [tests](/reference/resource-properties/data-tests): - - ... # declare additional tests [tags](/reference/resource-configs/tags): [] @@ -51,7 +51,7 @@ models: - [config](/reference/resource-properties/config): [](/reference/model-configs): - [tests](/reference/resource-properties/tests): + [tests](/reference/resource-properties/data-tests): - - ... # declare additional tests columns: @@ -63,7 +63,7 @@ models: [quote](/reference/resource-properties/quote): true | false [constraints](/reference/resource-properties/constraints): - - [tests](/reference/resource-properties/tests): + [tests](/reference/resource-properties/data-tests): - - ... # declare additional tests [tags](/reference/resource-configs/tags): [] diff --git a/website/docs/reference/node-selection/methods.md b/website/docs/reference/node-selection/methods.md index e29612e3401..2ffe0ea599e 100644 --- a/website/docs/reference/node-selection/methods.md +++ b/website/docs/reference/node-selection/methods.md @@ -173,7 +173,7 @@ dbt test --select "test_type:singular" # run all singular tests The `test_name` method is used to select tests based on the name of the generic test that defines it. For more information about how generic tests are defined, read about -[tests](/docs/build/tests). +[tests](/docs/build/data-tests). ```bash diff --git a/website/docs/reference/project-configs/test-paths.md b/website/docs/reference/project-configs/test-paths.md index e3d0e0b76fa..59f17db05eb 100644 --- a/website/docs/reference/project-configs/test-paths.md +++ b/website/docs/reference/project-configs/test-paths.md @@ -13,7 +13,7 @@ test-paths: [directorypath] ## Definition -Optionally specify a custom list of directories where [singular tests](/docs/build/tests) are located. +Optionally specify a custom list of directories where [singular tests](/docs/build/data-tests) are located. ## Default diff --git a/website/docs/reference/resource-configs/alias.md b/website/docs/reference/resource-configs/alias.md index 6b7588ecaf7..fbedb4597e6 100644 --- a/website/docs/reference/resource-configs/alias.md +++ b/website/docs/reference/resource-configs/alias.md @@ -112,7 +112,7 @@ When using `--store-failures`, this would return the name `analytics.finance.ord ## Definition -Optionally specify a custom alias for a [model](/docs/build/models), [tests](/docs/build/tests), [snapshots](/docs/build/snapshots), or [seed](/docs/build/seeds). +Optionally specify a custom alias for a [model](/docs/build/models), [tests](/docs/build/data-tests), [snapshots](/docs/build/snapshots), or [seed](/docs/build/seeds). When dbt creates a relation (/) in a database, it creates it as: `{{ database }}.{{ schema }}.{{ identifier }}`, e.g. `analytics.finance.payments` diff --git a/website/docs/reference/resource-configs/database.md b/website/docs/reference/resource-configs/database.md index 7d91358ff01..82c7b2cca92 100644 --- a/website/docs/reference/resource-configs/database.md +++ b/website/docs/reference/resource-configs/database.md @@ -70,7 +70,7 @@ This would result in the generated relation being located in the `reporting` dat ## Definition -Optionally specify a custom database for a [model](/docs/build/sql-models), [seed](/docs/build/seeds), or [tests](/docs/build/tests). (To specify a database for a [snapshot](/docs/build/snapshots), use the [`target_database` config](/reference/resource-configs/target_database)). +Optionally specify a custom database for a [model](/docs/build/sql-models), [seed](/docs/build/seeds), or [tests](/docs/build/data-tests). (To specify a database for a [snapshot](/docs/build/snapshots), use the [`target_database` config](/reference/resource-configs/target_database)). When dbt creates a relation (/) in a database, it creates it as: `{{ database }}.{{ schema }}.{{ identifier }}`, e.g. `analytics.finance.payments` diff --git a/website/docs/reference/resource-configs/meta.md b/website/docs/reference/resource-configs/meta.md index bc0c0c7c041..470bac35ba7 100644 --- a/website/docs/reference/resource-configs/meta.md +++ b/website/docs/reference/resource-configs/meta.md @@ -127,7 +127,7 @@ See [configs and properties](/reference/configs-and-properties) for details. -You can't add YAML `meta` configs for [generic tests](/docs/build/tests#generic-tests). However, you can add `meta` properties to [singular tests](/docs/build/tests#singular-tests) using `config()` at the top of the test file. +You can't add YAML `meta` configs for [generic tests](/docs/build/data-tests#generic-tests). However, you can add `meta` properties to [singular tests](/docs/build/data-tests#singular-tests) using `config()` at the top of the test file. diff --git a/website/docs/reference/resource-configs/store_failures_as.md b/website/docs/reference/resource-configs/store_failures_as.md index a9149360089..fd561176008 100644 --- a/website/docs/reference/resource-configs/store_failures_as.md +++ b/website/docs/reference/resource-configs/store_failures_as.md @@ -70,7 +70,7 @@ As with most other configurations, `store_failures_as` is "clobbered" when appli Additional resources: -- [Test configurations](/reference/test-configs#related-documentation) -- [Test-specific configurations](/reference/test-configs#test-specific-configurations) +- [Test configurations](/reference/data-test-configs#related-documentation) +- [Test-specific configurations](/reference/data-test-configs#test-specific-configurations) - [Configuring directories of models in dbt_project.yml](/reference/model-configs#configuring-directories-of-models-in-dbt_projectyml) - [Config inheritance](/reference/configs-and-properties#config-inheritance) \ No newline at end of file diff --git a/website/docs/reference/resource-properties/columns.md b/website/docs/reference/resource-properties/columns.md index ff8aa8734c6..74727977feb 100644 --- a/website/docs/reference/resource-properties/columns.md +++ b/website/docs/reference/resource-properties/columns.md @@ -28,7 +28,7 @@ models: data_type: [description](/reference/resource-properties/description): [quote](/reference/resource-properties/quote): true | false - [tests](/reference/resource-properties/tests): ... + [tests](/reference/resource-properties/data-tests): ... [tags](/reference/resource-configs/tags): ... [meta](/reference/resource-configs/meta): ... - name: @@ -55,7 +55,7 @@ sources: [description](/reference/resource-properties/description): data_type: [quote](/reference/resource-properties/quote): true | false - [tests](/reference/resource-properties/tests): ... + [tests](/reference/resource-properties/data-tests): ... [tags](/reference/resource-configs/tags): ... [meta](/reference/resource-configs/meta): ... - name: @@ -81,7 +81,7 @@ seeds: [description](/reference/resource-properties/description): data_type: [quote](/reference/resource-properties/quote): true | false - [tests](/reference/resource-properties/tests): ... + [tests](/reference/resource-properties/data-tests): ... [tags](/reference/resource-configs/tags): ... [meta](/reference/resource-configs/meta): ... - name: @@ -106,7 +106,7 @@ snapshots: [description](/reference/resource-properties/description): data_type: [quote](/reference/resource-properties/quote): true | false - [tests](/reference/resource-properties/tests): ... + [tests](/reference/resource-properties/data-tests): ... [tags](/reference/resource-configs/tags): ... [meta](/reference/resource-configs/meta): ... - name: diff --git a/website/docs/reference/resource-properties/config.md b/website/docs/reference/resource-properties/config.md index 55d2f64d9ff..89d189d8a78 100644 --- a/website/docs/reference/resource-properties/config.md +++ b/website/docs/reference/resource-properties/config.md @@ -98,7 +98,7 @@ version: 2 - [](#test_name): : config: - [](/reference/test-configs): + [](/reference/data-test-configs): ... ``` diff --git a/website/docs/reference/resource-properties/tests.md b/website/docs/reference/resource-properties/data-tests.md similarity index 83% rename from website/docs/reference/resource-properties/tests.md rename to website/docs/reference/resource-properties/data-tests.md index 0fe86ccc57d..96ee322efc0 100644 --- a/website/docs/reference/resource-properties/tests.md +++ b/website/docs/reference/resource-properties/data-tests.md @@ -1,8 +1,8 @@ --- -title: "About tests property" -sidebar_label: "tests" +title: "About data tests property" +sidebar_label: "Data tests" resource_types: all -datatype: test +datatype: data-test keywords: [test, tests, custom tests, custom test name, test name] --- @@ -30,7 +30,7 @@ models: - [](#test_name): : [config](/reference/resource-properties/config): - [](/reference/test-configs): + [](/reference/data-test-configs): [columns](/reference/resource-properties/columns): - name: @@ -39,7 +39,7 @@ models: - [](#test_name): : [config](/reference/resource-properties/config): - [](/reference/test-configs): + [](/reference/data-test-configs): ``` @@ -62,7 +62,7 @@ sources: - [](#test_name): : [config](/reference/resource-properties/config): - [](/reference/test-configs): + [](/reference/data-test-configs): columns: - name: @@ -71,7 +71,7 @@ sources: - [](#test_name): : [config](/reference/resource-properties/config): - [](/reference/test-configs): + [](/reference/data-test-configs): ``` @@ -93,7 +93,7 @@ seeds: - [](#test_name): : [config](/reference/resource-properties/config): - [](/reference/test-configs): + [](/reference/data-test-configs): columns: - name: @@ -102,7 +102,7 @@ seeds: - [](#test_name): : [config](/reference/resource-properties/config): - [](/reference/test-configs): + [](/reference/data-test-configs): ``` @@ -124,7 +124,7 @@ snapshots: - [](#test_name): : [config](/reference/resource-properties/config): - [](/reference/test-configs): + [](/reference/data-test-configs): columns: - name: @@ -133,7 +133,7 @@ snapshots: - [](#test_name): : [config](/reference/resource-properties/config): - [](/reference/test-configs): + [](/reference/data-test-configs): ``` @@ -152,17 +152,17 @@ This feature is not implemented for analyses. ## Related documentation -* [Testing guide](/docs/build/tests) +* [Testing guide](/docs/build/data-tests) ## Description -The `tests` property defines assertions about a column, , or . The property contains a list of [generic tests](/docs/build/tests#generic-tests), referenced by name, which can include the four built-in generic tests available in dbt. For example, you can add tests that ensure a column contains no duplicates and zero null values. Any arguments or [configurations](/reference/test-configs) passed to those tests should be nested below the test name. +The data `tests` property defines assertions about a column, , or . The property contains a list of [generic tests](/docs/build/data-tests#generic-tests), referenced by name, which can include the four built-in generic tests available in dbt. For example, you can add tests that ensure a column contains no duplicates and zero null values. Any arguments or [configurations](/reference/data-test-configs) passed to those tests should be nested below the test name. Once these tests are defined, you can validate their correctness by running `dbt test`. -## Out-of-the-box tests +## Out-of-the-box data tests -There are four generic tests that are available out of the box, for everyone using dbt. +There are four generic data tests that are available out of the box, for everyone using dbt. ### `not_null` @@ -262,7 +262,7 @@ The `to` argument accepts a [Relation](/reference/dbt-classes#relation) – this ## Additional examples ### Test an expression -Some tests require multiple columns, so it doesn't make sense to nest them under the `columns:` key. In this case, you can apply the test to the model (or source, seed, or snapshot) instead: +Some data tests require multiple columns, so it doesn't make sense to nest them under the `columns:` key. In this case, you can apply the test to the model (or source, seed, or snapshot) instead: @@ -300,7 +300,7 @@ models: Check out the guide on writing a [custom generic test](/best-practices/writing-custom-generic-tests) for more information. -### Custom test name +### Custom data test name By default, dbt will synthesize a name for your generic test by concatenating: - test name (`not_null`, `unique`, etc) @@ -434,11 +434,11 @@ $ dbt test 12:48:04 Done. PASS=2 WARN=0 ERROR=0 SKIP=0 TOTAL=2 ``` -**If using [`store_failures`](/reference/resource-configs/store_failures):** dbt uses each test's name as the name of the table in which to store any failing records. If you have defined a custom name for one test, that custom name will also be used for its table of failures. You may optionally configure an [`alias`](/reference/resource-configs/alias) for the test, to separately control both the name of the test (for metadata) and the name of its database table (for storing failures). +**If using [`store_failures`](/reference/resource-configs/store_failures):** dbt uses each data test's name as the name of the table in which to store any failing records. If you have defined a custom name for one test, that custom name will also be used for its table of failures. You may optionally configure an [`alias`](/reference/resource-configs/alias) for the test, to separately control both the name of the test (for metadata) and the name of its database table (for storing failures). ### Alternative format for defining tests -When defining a generic test with several arguments and configurations, the YAML can look and feel unwieldy. If you find it easier, you can define the same test properties as top-level keys of a single dictionary, by providing the test name as `test_name` instead. It's totally up to you. +When defining a generic data test with several arguments and configurations, the YAML can look and feel unwieldy. If you find it easier, you can define the same test properties as top-level keys of a single dictionary, by providing the test name as `test_name` instead. It's totally up to you. This example is identical to the one above: diff --git a/website/docs/reference/seed-properties.md b/website/docs/reference/seed-properties.md index 85e7be21ae1..9201df65f4c 100644 --- a/website/docs/reference/seed-properties.md +++ b/website/docs/reference/seed-properties.md @@ -18,7 +18,7 @@ seeds: show: true | false [config](/reference/resource-properties/config): [](/reference/seed-configs): - [tests](/reference/resource-properties/tests): + [tests](/reference/resource-properties/data-tests): - - ... # declare additional tests columns: @@ -27,7 +27,7 @@ seeds: [meta](/reference/resource-configs/meta): {} [quote](/reference/resource-properties/quote): true | false [tags](/reference/resource-configs/tags): [] - [tests](/reference/resource-properties/tests): + [tests](/reference/resource-properties/data-tests): - - ... # declare additional tests diff --git a/website/docs/reference/snapshot-properties.md b/website/docs/reference/snapshot-properties.md index 301747e9325..8f01fd8e988 100644 --- a/website/docs/reference/snapshot-properties.md +++ b/website/docs/reference/snapshot-properties.md @@ -22,7 +22,7 @@ snapshots: show: true | false [config](/reference/resource-properties/config): [](/reference/snapshot-configs): - [tests](/reference/resource-properties/tests): + [tests](/reference/resource-properties/data-tests): - - ... columns: @@ -31,7 +31,7 @@ snapshots: [meta](/reference/resource-configs/meta): {} [quote](/reference/resource-properties/quote): true | false [tags](/reference/resource-configs/tags): [] - [tests](/reference/resource-properties/tests): + [tests](/reference/resource-properties/data-tests): - - ... # declare additional tests - ... # declare properties of additional columns diff --git a/website/docs/reference/source-properties.md b/website/docs/reference/source-properties.md index d107881967e..aa95a19327c 100644 --- a/website/docs/reference/source-properties.md +++ b/website/docs/reference/source-properties.md @@ -57,7 +57,7 @@ sources: [meta](/reference/resource-configs/meta): {} [identifier](/reference/resource-properties/identifier): [loaded_at_field](/reference/resource-properties/freshness#loaded_at_field): - [tests](/reference/resource-properties/tests): + [tests](/reference/resource-properties/data-tests): - - ... # declare additional tests [tags](/reference/resource-configs/tags): [] @@ -80,7 +80,7 @@ sources: [description](/reference/resource-properties/description): [meta](/reference/resource-configs/meta): {} [quote](/reference/resource-properties/quote): true | false - [tests](/reference/resource-properties/tests): + [tests](/reference/resource-properties/data-tests): - - ... # declare additional tests [tags](/reference/resource-configs/tags): [] diff --git a/website/docs/terms/data-wrangling.md b/website/docs/terms/data-wrangling.md index 58034fe8e91..d71013524ca 100644 --- a/website/docs/terms/data-wrangling.md +++ b/website/docs/terms/data-wrangling.md @@ -150,7 +150,7 @@ For nested data types such as JSON, you’ll want to check out the JSON parsing ### Validating -dbt offers [generic tests](/docs/build/tests#more-generic-tests) in every dbt project that allows you to validate accepted, unique, and null values. They also allow you to validate the relationships between tables and that the primary key is unique. +dbt offers [generic tests](/docs/build/data-tests#more-generic-tests) in every dbt project that allows you to validate accepted, unique, and null values. They also allow you to validate the relationships between tables and that the primary key is unique. If you can’t find what you need with the generic tests, you can download an additional dbt testing package called [dbt_expectations](https://hub.getdbt.com/calogica/dbt_expectations/0.1.2/) that dives even deeper into how you can test the values in your columns. This package has useful tests like `expect_column_values_to_be_in_type_list`, `expect_column_values_to_be_between`, and `expect_column_value_lengths_to_equal`. diff --git a/website/docs/terms/primary-key.md b/website/docs/terms/primary-key.md index 4acd1e8c46d..5724e2b3b6e 100644 --- a/website/docs/terms/primary-key.md +++ b/website/docs/terms/primary-key.md @@ -108,7 +108,7 @@ In general for Redshift, it’s still good practice to define your primary keys ### Google BigQuery -BigQuery is pretty unique here in that it doesn’t support or enforce primary keys. If your team is on BigQuery, you’ll need to have some [pretty solid testing](/docs/build/tests) in place to ensure your primary key fields are unique and non-null. +BigQuery is pretty unique here in that it doesn’t support or enforce primary keys. If your team is on BigQuery, you’ll need to have some [pretty solid testing](/docs/build/data-tests) in place to ensure your primary key fields are unique and non-null. ### Databricks @@ -141,7 +141,7 @@ If you don't have a field in your table that would act as a natural primary key, If your data warehouse doesn’t provide out-of-the box support and enforcement for primary keys, it’s important to clearly label and put your own constraints on primary key fields. This could look like: * **Creating a consistent naming convention for your primary keys**: You may see an `id` field or fields prefixed with `pk_` (ex. `pk_order_id`) to identify primary keys. You may also see the primary key be named as the obvious table grain (ex. In the jaffle shop’s `orders` table, the primary key is called `order_id`). -* **Adding automated [tests](/docs/build/tests) to your data models**: Use a data tool, such as dbt, to create not null and unique tests for your primary key fields. +* **Adding automated [tests](/docs/build/data-tests) to your data models**: Use a data tool, such as dbt, to create not null and unique tests for your primary key fields. ## Testing primary keys diff --git a/website/docs/terms/surrogate-key.md b/website/docs/terms/surrogate-key.md index e57a0b74a7f..9b8c932ee5a 100644 --- a/website/docs/terms/surrogate-key.md +++ b/website/docs/terms/surrogate-key.md @@ -177,7 +177,7 @@ After executing this, the table would now have the `unique_id` field now uniquel Amazing, you just made a surrogate key! You can just move on to the next data model, right? No!! It’s critically important to test your surrogate keys for uniqueness and non-null values to ensure that the correct fields were chosen to create the surrogate key. -In order to test for null and unique values you can utilize code-based tests like [dbt tests](/docs/build/tests), that can check fields for nullness and uniqueness. You can additionally utilize simple SQL queries or unit tests to check if surrogate key count and non-nullness is correct. +In order to test for null and unique values you can utilize code-based tests like [dbt tests](/docs/build/data-tests), that can check fields for nullness and uniqueness. You can additionally utilize simple SQL queries or unit tests to check if surrogate key count and non-nullness is correct. ## A note on hashing algorithms diff --git a/website/sidebars.js b/website/sidebars.js index 598fffc7f0d..42269c49a76 100644 --- a/website/sidebars.js +++ b/website/sidebars.js @@ -277,7 +277,7 @@ const sidebarSettings = { }, "docs/build/snapshots", "docs/build/seeds", - "docs/build/tests", + "docs/build/data-tests", "docs/build/jinja-macros", "docs/build/sources", "docs/build/exposures", @@ -743,7 +743,7 @@ const sidebarSettings = { "reference/resource-properties/latest_version", "reference/resource-properties/include-exclude", "reference/resource-properties/quote", - "reference/resource-properties/tests", + "reference/resource-properties/data-tests", "reference/resource-properties/versions", ], }, diff --git a/website/snippets/_run-result.md b/website/snippets/_run-result.md index 77a35676e86..28de3a97cb6 100644 --- a/website/snippets/_run-result.md +++ b/website/snippets/_run-result.md @@ -1,2 +1,2 @@ -- `adapter_response`: Dictionary of metadata returned from the database, which varies by adapter. For example, success `code`, number of `rows_affected`, total `bytes_processed`, and so on. Not applicable for [tests](/docs/build/tests). +- `adapter_response`: Dictionary of metadata returned from the database, which varies by adapter. For example, success `code`, number of `rows_affected`, total `bytes_processed`, and so on. Not applicable for [tests](/docs/build/data-tests). * `rows_affected` returns the number of rows modified by the last statement executed. In cases where the query's row count can't be determined or isn't applicable (such as when creating a view), a [standard value](https://peps.python.org/pep-0249/#rowcount) of `-1` is returned for `rowcount`. diff --git a/website/snippets/tutorial-add-tests-to-models.md b/website/snippets/tutorial-add-tests-to-models.md index 491fc72ba85..f743c2bf947 100644 --- a/website/snippets/tutorial-add-tests-to-models.md +++ b/website/snippets/tutorial-add-tests-to-models.md @@ -1,4 +1,4 @@ -Adding [tests](/docs/build/tests) to a project helps validate that your models are working correctly. +Adding [tests](/docs/build/data-tests) to a project helps validate that your models are working correctly. To add tests to your project: From 102e11546b02c409341de36adc2f15850c000388 Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Tue, 5 Dec 2023 15:03:46 -0500 Subject: [PATCH 034/165] adding redirects --- website/vercel.json | 15 +++++++++++++++ 1 file changed, 15 insertions(+) diff --git a/website/vercel.json b/website/vercel.json index 3377b49278d..41b10f9c773 100644 --- a/website/vercel.json +++ b/website/vercel.json @@ -2,6 +2,21 @@ "cleanUrls": true, "trailingSlash": false, "redirects": [ + { + "source": "/reference/test-configs", + "destination": "/reference/data-test-configs", + "permanent": true + }, + { + "source": "/reference/resource-properties/tests", + "destination": "/reference/resource-properties/data-tests",, + "permanent": true + }, + { + "source": "/docs/build/tests", + "destination": "/docs/build/data-tests", + "permanent": true + }, { "source": "/docs/cloud/dbt-cloud-ide", "destination": "/docs/cloud/dbt-cloud-ide/develop-in-the-cloud", From 807ebbcfb7e53387388adcf0d65645027916ccbe Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Tue, 5 Dec 2023 15:06:32 -0500 Subject: [PATCH 035/165] Fixing syntax --- website/vercel.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/vercel.json b/website/vercel.json index 41b10f9c773..5cdc2656948 100644 --- a/website/vercel.json +++ b/website/vercel.json @@ -9,7 +9,7 @@ }, { "source": "/reference/resource-properties/tests", - "destination": "/reference/resource-properties/data-tests",, + "destination": "/reference/resource-properties/data-tests", "permanent": true }, { From 6c459adc0db4888f7c8043b1587ec08757ce8c0b Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Tue, 5 Dec 2023 15:13:15 -0500 Subject: [PATCH 036/165] Fixing sidebar name --- website/sidebars.js | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/sidebars.js b/website/sidebars.js index 42269c49a76..7a05539d05f 100644 --- a/website/sidebars.js +++ b/website/sidebars.js @@ -809,7 +809,7 @@ const sidebarSettings = { type: "category", label: "For tests", items: [ - "reference/test-configs", + "reference/data-test-configs", "reference/resource-configs/fail_calc", "reference/resource-configs/limit", "reference/resource-configs/severity", From 55d37b71142f270cff5cdce03b74d528f31e7f9b Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Tue, 5 Dec 2023 16:35:28 -0500 Subject: [PATCH 037/165] Apply suggestions from code review --- .../resource-configs/redshift-configs.md | 19 ++++++++----------- 1 file changed, 8 insertions(+), 11 deletions(-) diff --git a/website/docs/reference/resource-configs/redshift-configs.md b/website/docs/reference/resource-configs/redshift-configs.md index 8c9b015ded3..0e079453ec6 100644 --- a/website/docs/reference/resource-configs/redshift-configs.md +++ b/website/docs/reference/resource-configs/redshift-configs.md @@ -145,10 +145,9 @@ select * from {{ ref('my_base_table') }} Many of these parameters correspond to their table counterparts and have been linked above. -The set of parameters which are unique to materialized views covers auto-refresh and backup functionality, which is covered below. +The parameters unique to materialized views are the auto-refresh and backup functionality, which are covered below. -Find more information about these parameters in the Redshift docs: -- [CREATE MATERIALIZED VIEW](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-create-sql-command.html) +Find more information about the [CREATE MATERIALIZED VIEW](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-create-sql-command.html) parameters in the Redshift docs. #### Auto-refresh @@ -157,11 +156,10 @@ Find more information about these parameters in the Redshift docs: | `auto_refresh` | BOOLEAN | NO | `False` | ALTER | Redshift supports [automatic refresh](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-refresh.html#materialized-view-auto-refresh) configuration for materialized views. -By default, a materialized view will not automatically refresh. -dbt will monitor this parameter for changes and apply them using an `ALTER` statement. +By default, a materialized view does not automatically refresh. +dbt monitors this parameter for changes and applies them using an `ALTER` statement. -Find more information about this parameter in the Redshift docs: -- [Parameters](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-create-sql-command.html#mv_CREATE_MATERIALIZED_VIEW-parameters) +Find more information about the [parameters](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-create-sql-command.html#mv_CREATE_MATERIALIZED_VIEW-parameters) in the Redshift docs. #### Backup @@ -175,15 +173,14 @@ By default, a materialized view will be backed up during a cluster snapshot. dbt cannot monitor this parameter as it is not queryable within Redshift. If the value is changed, the materialized view will need to go through a `--full-refresh` in order to set it. -Find more information about this parameter in the Redshift docs: -- [Parameters](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-create-sql-command.html#mv_CREATE_MATERIALIZED_VIEW-parameters) +Find more information about the [parameters](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-create-sql-command.html#mv_CREATE_MATERIALIZED_VIEW-parameters) in the Redshift docs. ### Limitations As with most data platforms, there are limitations associated with materialized views. Some worth noting include: -- Materialized views cannot reference: views, temporary tables, user defined functions, late-binding tables -- Auto-refresh cannot be used if the materialized view references: mutable functions, external schemas, another materialized view +- Materialized views cannot reference views, temporary tables, user-defined functions, or late-binding tables. +- Auto-refresh cannot be used if the materialized view references mutable functions, external schemas, or another materialized view. Find more information about materialized view limitations in Redshift's [docs](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-create-sql-command.html#mv_CREATE_MATERIALIZED_VIEW-limitations). From 465a360978addfca419099f0dd37e23bcf31b4b6 Mon Sep 17 00:00:00 2001 From: Doug Beatty <44704949+dbeatty10@users.noreply.github.com> Date: Tue, 5 Dec 2023 17:39:44 -0700 Subject: [PATCH 038/165] Example to use instead of N.B. --- contributing/content-style-guide.md | 3 +++ 1 file changed, 3 insertions(+) diff --git a/contributing/content-style-guide.md b/contributing/content-style-guide.md index e6fafec4593..4ebbf83bf5f 100644 --- a/contributing/content-style-guide.md +++ b/contributing/content-style-guide.md @@ -479,6 +479,9 @@ Some common Latin abbreviations and other words to use instead: | i.e. | that is | Use incremental models when your dbt runs are becoming too slow (that is, don't start with incremental models) | | e.g. |

  • for example
  • like
|
  • Join both the dedicated #adapter-ecosystem channel in dbt Slack and the channel for your adapter's data store (for example, #db-sqlserver and #db-athena)
  • Using Jinja in SQL provides a way to use control structures (like `if` statements and `for` loops) in your queries
| | etc. |
  • and more
  • and so forth
|
  • A continuous integration environment running pull requests in GitHub, GitLab, and more
  • While reasonable defaults are provided for many such operations (like `create_schema`, `drop_schema`, `create_table`, and so forth), you might need to override one or more macros when building a new adapter
| +| N.B. | note | Note: State-based selection is a powerful, complex feature. | + +https://www.thoughtco.com/n-b-latin-abbreviations-in-english-3972787 ### Prepositions From 573b65ec1d72b73fd4797bf233dc91298a5d0fac Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Wed, 6 Dec 2023 07:33:33 -0500 Subject: [PATCH 039/165] deprecated content --- website/docs/docs/build/metrics.md | 696 ------------------ website/docs/docs/build/projects.md | 2 +- .../avail-sl-integrations.md | 25 - .../docs/use-dbt-semantic-layer/dbt-sl.md | 99 --- .../use-dbt-semantic-layer/quickstart-sl.md | 263 ------- .../docs/use-dbt-semantic-layer/setup-sl.md | 5 - .../use-dbt-semantic-layer/sl-architecture.md | 32 - .../docs/use-dbt-semantic-layer/tableau.md | 1 - website/vercel.json | 5 + 9 files changed, 6 insertions(+), 1122 deletions(-) delete mode 100644 website/docs/docs/build/metrics.md diff --git a/website/docs/docs/build/metrics.md b/website/docs/docs/build/metrics.md deleted file mode 100644 index 7afcb41c2e4..00000000000 --- a/website/docs/docs/build/metrics.md +++ /dev/null @@ -1,696 +0,0 @@ ---- -title: "Metrics" -id: "metrics" -description: "When you define metrics in dbt projects, you encode crucial business logic in tested, version-controlled code. The dbt metrics layer helps you standardize metrics within your organization." -keywords: - - dbt metrics layer -tags: [Metrics] ---- - -import DeprecationNotice from '/snippets/_sl-deprecation-notice.md'; - - - - - - -The dbt Semantic Layer has undergone a [significant revamp](https://www.getdbt.com/blog/dbt-semantic-layer-whats-next/), improving governance, introducing new APIs, and making it more efficient to define/query metrics. This revamp means the dbt_metrics package and the legacy Semantic Layer, available in dbt v1.5 or lower, are no longer supported and won't receive any code fixes. - -**What’s changed?**

-The dbt_metrics package has been [deprecated](https://docs.getdbt.com/blog/deprecating-dbt-metrics) and replaced with [MetricFlow](/docs/build/about-metricflow?version=1.6), a new framework for defining metrics in dbt. This means dbt_metrics is no longer supported after dbt v1.5 and won't receive any code fixes. We will also remove the dbt_metrics spec and docs when it's fully deprecated. - -**Who does this affect?**

-Anyone who uses the dbt_metrics package or is integrated with the legacy Semantic Layer. The new Semantic Layer is available to [Team or Enterprise](https://www.getdbt.com/pricing/) multi-tenant dbt Cloud plans [hosted in North America](/docs/cloud/about-cloud/regions-ip-addresses). You must be on dbt v1.6 or higher to access it. All users can define metrics using MetricFlow. Users on dbt Cloud Developer plans or dbt Core can only use it to define and test metrics locally, but can't dynamically query them with integrated tools. - -**What should you do?**

-If you've defined metrics using dbt_metrics or integrated with the legacy Semantic Layer, we **highly** recommend you [upgrade your dbt version](/docs/dbt-versions/upgrade-core-in-cloud) to dbt v1.6 or higher to use MetricFlow or the new dbt Semantic Layer. To migrate to the new Semantic Layer, refer to the dedicated [migration guide](/guides/sl-migration) for more info. - - - - - - - -A metric is an aggregation over a that supports zero or more dimensions. Some examples of metrics include: -- active users -- monthly recurring revenue (mrr) - -In v1.0, dbt supports metric definitions as a new node type. Like [exposures](exposures), metrics appear as nodes in the directed acyclic graph (DAG) and can be expressed in YAML files. Defining metrics in dbt projects encodes crucial business logic in tested, version-controlled code. Further, you can expose these metrics definitions to downstream tooling, which drives consistency and precision in metric reporting. - -### Benefits of defining metrics - -**Use metric specifications in downstream tools** -dbt's compilation context can access metrics via the [`graph.metrics` variable](graph). The [manifest artifact](manifest-json) includes metrics for downstream metadata consumption. - -**See and select dependencies** -As with Exposures, you can see everything that rolls up into a metric (`dbt ls -s +metric:*`), and visualize them in [dbt documentation](documentation). For more information, see "[The `metric:` selection method](node-selection/methods#the-metric-method)." - - - -## Defining a metric - -You can define metrics in `.yml` files nested under a `metrics:` key. Metric names must: -- contain only letters, numbers, and underscores (no spaces or special characters) -- begin with a letter -- contain no more than 250 characters - -For a short human-friendly name with title casing, spaces, and special characters, use the `label` property. - -### Example definition - - - - - -```yaml -# models/marts/product/schema.yml - -version: 2 - -models: - - name: dim_customers - ... - -metrics: - - name: rolling_new_customers - label: New Customers - model: ref('dim_customers') - [description](description): "The 14 day rolling count of paying customers using the product" - - calculation_method: count_distinct - expression: user_id - - timestamp: signup_date - time_grains: [day, week, month, quarter, year] - - dimensions: - - plan - - country - - window: - count: 14 - period: day - - filters: - - field: is_paying - operator: 'is' - value: 'true' - - field: lifetime_value - operator: '>=' - value: '100' - - field: company_name - operator: '!=' - value: "'Acme, Inc'" - - field: signup_date - operator: '>=' - value: "'2020-01-01'" - - # general properties - [config](resource-properties/config): - enabled: true | false - treat_null_values_as_zero: true | false - - [meta](resource-configs/meta): {team: Finance} -``` - - - - -```yaml -# models/marts/product/schema.yml - -version: 2 - -models: - - name: dim_customers - ... - -metrics: - - name: rolling_new_customers - label: New Customers - model: ref('dim_customers') - description: "The 14 day rolling count of paying customers using the product" - - type: count_distinct - sql: user_id - - timestamp: signup_date - time_grains: [day, week, month, quarter, year, all_time] - - dimensions: - - plan - - country - - filters: - - field: is_paying - operator: 'is' - value: 'true' - - field: lifetime_value - operator: '>=' - value: '100' - - field: company_name - operator: '!=' - value: "'Acme, Inc'" - - field: signup_date - operator: '>=' - value: "'2020-01-01'" - - meta: {team: Finance} -``` - - - - -:::caution - -- You cannot define metrics on [ephemeral models](https://docs.getdbt.com/docs/build/materializations#ephemeral). To define a metric, the materialization must have a representation in the data warehouse. - -::: - - -### Available properties -Metrics can have many declared **properties**, which define aspects of your metric. More information on [properties and configs can be found here](https://docs.getdbt.com/reference/configs-and-properties). - - - -| Field | Description | Example | Required? | -|-------------|-------------------------------------------------------------|---------------------------------|-----------| -| name | A unique identifier for the metric | new_customers | yes | -| model | The dbt model that powers this metric | dim_customers | yes (no for `derived` metrics)| -| label | A short for name / label for the metric | New Customers | yes | -| description | Long form, human-readable description for the metric | The number of customers who.... | no | -| calculation_method | The method of calculation (aggregation or derived) that is applied to the expression | count_distinct | yes | -| expression | The expression to aggregate/calculate over | user_id, cast(user_id as int) |yes | -| timestamp | The time-based component of the metric | signup_date | no yes | -| time_grains | One or more "grains" at which the metric can be evaluated. For more information, see the "Custom Calendar" section. | [day, week, month, quarter, year] | no yes | -| dimensions | A list of dimensions to group or filter the metric by | [plan, country] | no | -| window | A dictionary for aggregating over a window of time. Used for rolling metrics such as 14 day rolling average. Acceptable periods are: [`day`,`week`,`month`, `year`, `all_time`] | {count: 14, period: day} | no | -| filters | A list of filters to apply before calculating the metric | See below | no | -| config | [Optional configurations](https://github.com/dbt-labs/dbt_metrics#accepted-metric-configurations) for calculating this metric | {treat_null_values_as_zero: true} | no | -| meta | Arbitrary key/value store | {team: Finance} | no | - - - - - -| Field | Description | Example | Required? | -|-------------|-------------------------------------------------------------|---------------------------------|-----------| -| name | A unique identifier for the metric | new_customers | yes | -| model | The dbt model that powers this metric | dim_customers | yes (no for `derived` metrics)| -| label | A short for name / label for the metric | New Customers |yes | -| description | Long form, human-readable description for the metric | The number of customers who.... | no | -| type | The method of calculation (aggregation or derived) that is applied to the expression | count_distinct | yes | -| sql | The expression to aggregate/calculate over | user_id, cast(user_id as int) | yes | -| timestamp | The time-based component of the metric | signup_date | yes | -| time_grains | One or more "grains" at which the metric can be evaluated | [day, week, month, quarter, year, all_time] | yes | -| dimensions | A list of dimensions to group or filter the metric by | [plan, country] | no | -| filters | A list of filters to apply before calculating the metric | See below | no | -| meta | Arbitrary key/value store | {team: Finance} | no | - - - - -### Available calculation methods - - - -The method of calculation (aggregation or derived) that is applied to the expression. - - - - -The type of calculation (aggregation or expression) that is applied to the sql property. - - - -| Metric Calculation Method | Description | -|----------------|----------------------------------------------------------------------------| -| count | This metric type will apply the `count` aggregation to the specified field | -| count_distinct | This metric type will apply the `count` aggregation to the specified field, with an additional distinct statement inside the aggregation | -| sum | This metric type will apply the `sum` aggregation to the specified field | -| average | This metric type will apply the `average` aggregation to the specified field | -| min | This metric type will apply the `min` aggregation to the specified field | -| max | This metric type will apply the `max` aggregation to the specified field | -| median | This metric type will apply the `median` aggregation to the specified field, or an alternative `percentile_cont` aggregation if `median` is not available | -|derived expression | This metric type is defined as any _non-aggregating_ calculation of 1 or more metrics | - - - -### Derived Metrics -In v1.2, support was added for `derived` metrics (previously named `expression`), which are defined as non-aggregating calculations of 1 or more metrics. An example of this would be `{{metric('total_revenue')}} / {{metric('count_of_customers')}}`. - - By defining these metrics, you are able to create metrics like: -- ratios -- subtractions -- any arbitrary calculation - -As long as the two (or more) base metrics (metrics that comprise the `derived` metric) share the specified `time_grains` and `dimensions`, those attributes can be used in any downstream metrics macro. - -An example definition of an `derived` metric is: - - - - -```yaml -# models/marts/product/schema.yml -version: 2 - -models: - - name: dim_customers - ... - -metrics: - - name: average_revenue_per_customer - label: Average Revenue Per Customer - description: "The average revenue received per customer" - - calculation_method: derived - expression: "{{metric('total_revenue')}} / {{metric('count_of_customers')}}" - - timestamp: order_date - time_grains: [day, week, month, quarter, year, all_time] - dimensions: - - had_discount - - order_country - -``` - - - - - -### Expression Metrics -In v1.2, support was added for `expression` metrics, which are defined as non-aggregating calculations of 1 or more metrics. By defining these metrics, you are able to create metrics like: -- ratios -- subtractions -- any arbitrary calculation - -As long as the two+ base metrics (the metrics that comprise the `expression` metric) share the specified `time_grains` and `dimensions`, those attributes can be used in any downstream metrics macro. - -An example definition of an `expression` metric is: - - - - -```yaml -# models/marts/product/schema.yml -version: 2 - -models: - - name: dim_customers - ... - -metrics: - - name: average_revenue_per_customer - label: Average Revenue Per Customer - description: "The average revenue received per customer" - - type: expression - sql: "{{metric('total_revenue')}} / {{metric('count_of_customers')}}" - - timestamp: order_date - time_grains: [day, week, month, quarter, year, all_time] - dimensions: - - had_discount - - order_country - -``` - - -### Filters -Filters should be defined as a list of dictionaries that define predicates for the metric. Filters are combined using AND clauses. For more control, users can (and should) include the complex logic in the model powering the metric. - -All three properties (`field`, `operator`, `value`) are required for each defined filter. - -Note that `value` must be defined as a string in YAML, because it will be compiled into queries as part of a string. If your filter's value needs to be surrounded by quotes inside the query (e.g. text or dates), use `"'nested'"` quotes: - -```yml - filters: - - field: is_paying - operator: 'is' - value: 'true' - - field: lifetime_value - operator: '>=' - value: '100' - - field: company_name - operator: '!=' - value: "'Acme, Inc'" - - field: signup_date - operator: '>=' - value: "'2020-01-01'" -``` - -### Calendar -The dbt_metrics package contains a [basic calendar table](https://github.com/dbt-labs/dbt_metrics/blob/main/models/dbt_metrics_default_calendar.sql) that is created as part of your `dbt run`. It contains dates between 2010-01-01 and 2029-12-31. - -If you want to use a custom calendar, you can replace the default with any table which meets the following requirements: -- Contains a `date_day` column. -- Contains the following columns: `date_week`, `date_month`, `date_quarter`, `date_year`, or equivalents. -- Additional date columns need to be prefixed with `date_`, e.g. `date_4_5_4_month` for a 4-5-4 retail calendar date set. Dimensions can have any name (see following section). - -To do this, set the value of the `dbt_metrics_calendar_model` variable in your `dbt_project.yml` file: -```yaml -#dbt_project.yml -config-version: 2 -[...] -vars: - dbt_metrics_calendar_model: my_custom_calendar -``` - -#### Dimensions from calendar tables -You may want to aggregate metrics by a dimension in your custom calendar table, for example is_weekend. You can include this within the list of dimensions in the macro call without it needing to be defined in the metric definition. - -To do so, set a list variable at the project level called custom_calendar_dimension_list, as shown in the example below. - -```yaml -#dbt_project.yml -vars: - custom_calendar_dimension_list: ["is_weekend"] -``` - - - -### Configuration - -Metric nodes now accept `config` dictionaries like other dbt resources. Specify Metric configs in the metric yml itself, or for groups of metrics in the `dbt_project.yml` file. - - - - - - - - -```yml -version: 2 -metrics: - - name: config_metric - label: Example Metric with Config - model: ref(‘my_model’) - calculation_method: count - timestamp: date_field - time_grains: [day, week, month] - config: - enabled: true -``` - - - - - - - - -```yml -metrics: - your_project_name: - +enabled: true -``` - - - - - - - - -#### Accepted Metric Configurations - -The following is the list of currently accepted metric configs: - -| Config | Type | Accepted Values | Default Value | Description | -|--------|------|-----------------|---------------|-------------| -| `enabled` | boolean | True/False | True | Enables or disables a metric node. When disabled, dbt will not consider it as part of your project. | -| `treat_null_values_as_zero` | boolean | True/False | True | Controls the `coalesce` behavior for metrics. By default, when there are no observations for a metric, the output of the metric as well as [Period over Period](#secondary-calculations) secondary calculations will include a `coalesce({{ field }}, 0)` to return 0's rather than nulls. Setting this config to False instead returns `NULL` values. | - - - -## Querying Your Metric - -:::caution dbt_metrics is no longer supported -The dbt_metrics package has been deprecated and replaced with [MetricFlow](/docs/build/about-metricflow?version=1.6), a new way framework for defining metrics in dbt. This means dbt_metrics is no longer supported after dbt v1.5 and won't receive any code fixes. -::: - -You can dynamically query metrics directly in dbt and verify them before running a job in the deployment environment. To query your defined metric, you must have the [dbt_metrics package](https://github.com/dbt-labs/dbt_metrics) installed. Information on how to [install packages can be found here](https://docs.getdbt.com/docs/build/packages#how-do-i-add-a-package-to-my-project). - -Use the following [metrics package](https://hub.getdbt.com/dbt-labs/metrics/latest/) installation code in your packages.yml file and run `dbt deps` to install the metrics package: - - - -```yml -packages: - - package: dbt-labs/metrics - version: [">=1.3.0", "<1.4.0"] -``` - - - - - -```yml -packages: - - package: dbt-labs/metrics - version: [">=0.3.0", "<0.4.0"] -``` - - - -Once the package has been installed with `dbt deps`, make sure to run the `dbt_metrics_default_calendar` model as this is required for macros used to query metrics. More information on this, and additional calendar functionality, can be found in the [project README](https://github.com/dbt-labs/dbt_metrics#calendar). - -### Querying metrics with `metrics.calculate` -Use the `metrics.calculate` macro along with defined metrics to generate a SQL statement that runs the metric aggregation to return the correct metric dataset. Example below: - - - -```sql -select * -from {{ metrics.calculate( - metric('new_customers'), - grain='week', - dimensions=['plan', 'country'] -) }} -``` - - - -### Supported inputs -The example above doesn't display all the potential inputs you can provide to the macro. - -You may find some pieces of functionality, like secondary calculations, complicated to use. We recommend reviewing the [package README](https://github.com/dbt-labs/dbt_metrics) for more in-depth information about each of the inputs that are not covered in the table below. - - -| Input | Example | Description | Required | -| ----------- | ----------- | ----------- | -----------| -| metric_list | `metric('some_metric)'`,
[`metric('some_metric)'`,
`metric('some_other_metric)'`]
 | The metric(s) to be queried by the macro. If multiple metrics required, provide in list format. | Required | -| grain | `'day'`, `'week'`,
`'month'`, `'quarter'`,
`'year'`
| The time grain that the metric will be aggregated to in the returned dataset | Optional | -| dimensions | [`'plan'`,
`'country'`] | The dimensions you want the metric to be aggregated by in the returned dataset | Optional | -| secondary_calculations | [`metrics.period_over_period( comparison_strategy="ratio", interval=1, alias="pop_1wk")`] | Performs the specified secondary calculation on the metric results. Examples include period over period calculations, rolling calculations, and period to date calculations. | Optional | -| start_date | `'2022-01-01'` | Limits the date range of data used in the metric calculation by not querying data before this date | Optional | -| end_date | `'2022-12-31'` | Limits the date range of data used in the metric calculation by not querying data after this date | Optional | -| where | `plan='paying_customer'` | A sql statement, or series of sql statements, that alter the **final** CTE in the generated sql. Most often used to limit the data to specific values of dimensions provided | Optional | - -### Secondary Calculations -Secondary calculations are window functions you can add to the metric calculation and perform on the primary metric or metrics. - -You can use them to compare values to an earlier period, calculate year-to-date sums, and return rolling averages. You can add custom secondary calculations into dbt projects - for more information on this, reference the [package README](https://github.com/dbt-labs/dbt_metrics#secondary-calculations). - -The supported Secondary Calculations are: - -#### Period over Period: - -The period over period secondary calculation performs a calculation against the metric(s) in question by either determining the difference or the ratio between two points in time. The input variable, which looks at the grain selected in the macro, determines the other point. - -| Input | Example | Description | Required | -| -------------------------- | ----------- | ----------- | -----------| -| `comparison_strategy` | `ratio` or `difference` | How to calculate the delta between the two periods | Yes | -| `interval` | 1 | Integer - the number of time grains to look back | Yes | -| `alias` | `week_over_week` | The column alias for the resulting calculation | No | -| `metric_list` | `base_sum_metric` | List of metrics that the secondary calculation should be applied to. Default is all metrics selected | No | - -#### Period to Date: - -The period to date secondary calculation performs an aggregation on a defined period of time that is equal to or higher than the grain selected. For example, when you want to display a month_to_date value alongside your weekly grained metric. - -| Input | Example | Description | Required | -| -------------------------- | ----------- | ----------- | -----------| -| `aggregate` | `max`, `average` | The aggregation to use in the window function. Options vary based on the primary aggregation and are enforced in [validate_aggregate_coherence()](https://github.com/dbt-labs/dbt_metrics/blob/main/macros/validation/validate_aggregate_coherence.sql). | Yes | -| `period` | `"day"`, `"week"` | The time grain to aggregate to. One of [`"day"`, `"week"`, `"month"`, `"quarter"`, `"year"`]. Must be at equal or coarser (higher, more aggregated) granularity than the metric's grain (see [Time Grains](#time-grains) below). In example grain of `month`, the acceptable periods would be `month`, `quarter`, or `year`. | Yes | -| `alias` | `month_to_date` | The column alias for the resulting calculation | No | -| `metric_list` | `base_sum_metric` | List of metrics that the secondary calculation should be applied to. Default is all metrics selected | No | - -#### Rolling: - - - -The rolling secondary calculation performs an aggregation on a number of rows in metric dataset. For example, if the user selects the `week` grain and sets a rolling secondary calculation to `4` then the value returned will be a rolling 4 week calculation of whatever aggregation type was selected. If the `interval` input is not provided then the rolling caclulation will be unbounded on all preceding rows. - -| Input | Example | Description | Required | -| -------------------------- | ----------- | ----------- | -----------| -| `aggregate` | `max`, `average` | The aggregation to use in the window function. Options vary based on the primary aggregation and are enforced in [validate_aggregate_coherence()](https://github.com/dbt-labs/dbt_metrics/blob/main/macros/validation/validate_aggregate_coherence.sql). | Yes | -| `interval` | 1 | Integer - the number of time grains to look back | No | -| `alias` | `month_to_date` | The column alias for the resulting calculation | No | -| `metric_list` | `base_sum_metric` | List of metrics that the secondary calculation should be applied to. Default is all metrics selected | No | - - - - -The rolling secondary calculation performs an aggregation on a number of rows in the metric dataset. For example, if the user selects the `week` grain and sets a rolling secondary calculation to `4`, then the value returned will be a rolling 4-week calculation of whatever aggregation type was selected. - -| Input | Example | Description | Required | -| -------------------------- | ----------- | ----------- | -----------| -| `aggregate` | `max`, `average` | The aggregation to use in the window function. Options vary based on the primary aggregation and are enforced in [validate_aggregate_coherence()](https://github.com/dbt-labs/dbt_metrics/blob/main/macros/validation/validate_aggregate_coherence.sql). | Yes | -| `interval` | 1 | Integer - the number of time grains to look back | Yes | -| `alias` | `month_to_date` | The column alias for the resulting calculation | No | -| `metric_list` | `base_sum_metric` | List of metrics that the secondary calculation should be applied to. Default is all metrics selected | No | - - - - -#### Prior: -The prior secondary calculation returns the value from a specified number of intervals before the row. - -| Input | Example | Description | Required | -| -------------------------- | ----------- | ----------- | -----------| -| `interval` | 1 | Integer - the number of time grains to look back | Yes | -| `alias` | `2_weeks_prior` | The column alias for the resulting calculation | No | -| `metric_list` | `base_sum_metric` | List of metrics that the secondary calculation should be applied to. Default is all metrics selected | No | - - - -### Developing metrics with `metrics.develop` - - - -There may be times you want to test what a metric might look like before defining it in your project. In these cases, use the `develop` metric, which allows you to provide metric(s) in a contained yml so you can simulate what a defined metric might look like in your project. - -```sql -{% set my_metric_yml -%} -{% raw %} - -metrics: - -- The name of the metric does not need to be develop_metric - - name: develop_metric - model: ref('fact_orders') - label: Total Discount ($) - timestamp: order_date - time_grains: [day, week, month, quarter, year, all_time] - calculation_method: average - expression: discount_total - dimensions: - - had_discount - - order_country - -{% endraw %} -{%- endset %} - -select * -from {{ metrics.develop( - develop_yml=my_metric_yml, - metric_list=['develop_metric'], - grain='month' - ) - }} -``` - -**Important caveat** - The metric list input for the `metrics.develop` macro takes in the metric names themselves, not the `metric('name')` statement that the `calculate` macro uses. Using the example above: - -- ✅ `['develop_metric']` -- ❌ `[metric('develop_metric')]` - - - - - -There may be times you want to test what a metric might look like before defining it in your project. In these cases, the `develop` metric, which allows you to provide a single metric in a contained yml so you can simulate what a defined metric might look like in your project. - - -```sql -{% set my_metric_yml -%} -{% raw %} - -metrics: - - name: develop_metric - model: ref('fact_orders') - label: Total Discount ($) - timestamp: order_date - time_grains: [day, week, month, quarter, year, all_time] - type: average - sql: discount_total - dimensions: - - had_discount - - order_country - -{% endraw %} -{%- endset %} - -select * -from {{ metrics.develop( - develop_yml=my_metric_yml, - grain='month' - ) - }} -``` - - - -#### Multiple/Derived Metrics with `metrics.develop` -If you have a more complicated use case that you are interested in testing, the develop macro also supports this behavior. The only caveat is that you must include the raw tags for any provided metric yml that contains a derived metric. Example below: - -``` -{% set my_metric_yml -%} -{% raw %} - -metrics: - - name: develop_metric - model: ref('fact_orders') - label: Total Discount ($) - timestamp: order_date - time_grains: [day, week, month] - calculation_method: average - expression: discount_total - dimensions: - - had_discount - - order_country - - - name: derived_metric - label: Total Discount ($) - timestamp: order_date - time_grains: [day, week, month] - calculation_method: derived - expression: "{{ metric('develop_metric') }} - 1 " - dimensions: - - had_discount - - order_country - - - name: some_other_metric_not_using - label: Total Discount ($) - timestamp: order_date - time_grains: [day, week, month] - calculation_method: derived - expression: "{{ metric('derived_metric') }} - 1 " - dimensions: - - had_discount - - order_country - -{% endraw %} -{%- endset %} - -select * -from {{ metrics.develop( - develop_yml=my_metric_yml, - metric_list=['derived_metric'] - grain='month' - ) - }} -``` - -The above example will return a dataset that contains the metric provided in the metric list (`derived_metric`) and the parent metric (`develop_metric`). It will not contain `some_other_metric_not_using` as it is not designated in the metric list or a parent of the metrics included. - -**Important caveat** - You _must_ wrap the `expression` property for `derived` metrics in double quotes to render it. For example, `expression: "{{ metric('develop_metric') }} - 1 "`. - - - - - - - diff --git a/website/docs/docs/build/projects.md b/website/docs/docs/build/projects.md index a54f6042cce..829245de6fc 100644 --- a/website/docs/docs/build/projects.md +++ b/website/docs/docs/build/projects.md @@ -19,7 +19,7 @@ At a minimum, all a project needs is the `dbt_project.yml` project configuration | [docs](/docs/collaborate/documentation) | Docs for your project that you can build. | | [sources](/docs/build/sources) | A way to name and describe the data loaded into your warehouse by your Extract and Load tools. | | [exposures](/docs/build/exposures) | A way to define and describe a downstream use of your project. | -| [metrics](/docs/build/metrics) | A way for you to define metrics for your project. | +| [metrics](/docs/build/build-metrics-intro) | A way for you to define metrics for your project. | | [groups](/docs/build/groups) | Groups enable collaborative node organization in restricted collections. | | [analysis](/docs/build/analyses) | A way to organize analytical SQL queries in your project such as the general ledger from your QuickBooks. | diff --git a/website/docs/docs/use-dbt-semantic-layer/avail-sl-integrations.md b/website/docs/docs/use-dbt-semantic-layer/avail-sl-integrations.md index be02fedb230..045838602a9 100644 --- a/website/docs/docs/use-dbt-semantic-layer/avail-sl-integrations.md +++ b/website/docs/docs/use-dbt-semantic-layer/avail-sl-integrations.md @@ -9,9 +9,6 @@ meta: api_name: dbt Semantic Layer APIs --- - - - There are a number of data applications that seamlessly integrate with the dbt Semantic Layer, powered by MetricFlow, from business intelligence tools to notebooks, spreadsheets, data catalogs, and more. These integrations allow you to query and unlock valuable insights from your data ecosystem. Use the [dbt Semantic Layer APIs](/docs/dbt-cloud-apis/sl-api-overview) to simplify metric queries, optimize your development workflow, and reduce coding. This approach also ensures data governance and consistency for data consumers. @@ -34,25 +31,3 @@ import AvailIntegrations from '/snippets/_sl-partner-links.md'; - [dbt Semantic Layer API query syntax](/docs/dbt-cloud-apis/sl-jdbc#querying-the-api-for-metric-metadata) - [Hex dbt Semantic Layer cells](https://learn.hex.tech/docs/logic-cell-types/transform-cells/dbt-metrics-cells) to set up SQL cells in Hex. - [Resolve 'Failed APN'](/faqs/Troubleshooting/sl-alpn-error) error when connecting to the dbt Semantic Layer. - - - - - -import DeprecationNotice from '/snippets/_sl-deprecation-notice.md'; - - - -A wide variety of data applications across the modern data stack natively integrate with the dbt Semantic Layer and dbt metrics — from Business Intelligence tools to notebooks, data catalogs, and more. - -The dbt Semantic Layer integrations are capable of querying dbt metrics, importing definitions, surfacing the underlying data in partner tools, and leveraging the dbt Server. - -For information on the partner integrations, their documentation, and more — refer to the [dbt Semantic Layer integrations](https://www.getdbt.com/product/semantic-layer-integrations) page. - - - -## Related docs - -- [About the dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl) - - diff --git a/website/docs/docs/use-dbt-semantic-layer/dbt-sl.md b/website/docs/docs/use-dbt-semantic-layer/dbt-sl.md index 8387e934d84..cde9ae4afbb 100644 --- a/website/docs/docs/use-dbt-semantic-layer/dbt-sl.md +++ b/website/docs/docs/use-dbt-semantic-layer/dbt-sl.md @@ -9,9 +9,6 @@ pagination_next: "docs/use-dbt-semantic-layer/quickstart-sl" pagination_prev: null --- - - - The dbt Semantic Layer, powered by [MetricFlow](/docs/build/about-metricflow), simplifies the process of defining and using critical business metrics, like `revenue` in the modeling layer (your dbt project). By centralizing metric definitions, data teams can ensure consistent self-service access to these metrics in downstream data tools and applications. The dbt Semantic Layer eliminates duplicate coding by allowing data teams to define metrics on top of existing models and automatically handles data joins. @@ -62,99 +59,3 @@ plan="dbt Cloud Team or Enterprise" icon="dbt-bit"/> - - - - - -import DeprecationNotice from '/snippets/_sl-deprecation-notice.md'; - - - -The dbt Semantic Layer allows your data teams to centrally define essential business metrics like `revenue`, `customer`, and `churn` in the modeling layer (your dbt project) for consistent self-service within downstream data tools like BI and metadata management solutions. The dbt Semantic Layer provides the flexibility to define metrics on top of your existing models and then query those metrics and models in your analysis tools of choice. - -Resulting in less duplicate coding for data teams and more consistency for data consumers. - -The dbt Semantic Layer has these main parts: - -- Define your metrics in version-controlled dbt project code using [MetricFlow](/docs/build/about-metricflow) - * dbt_metrics is now deprecated -- Import your metric definitions using the [Discovery API](/docs/dbt-cloud-apis/discovery-api) -- Query your metric data with the dbt Proxy Server -- Explore and analyze dbt metrics in downstream tools - -### What makes the dbt Semantic Layer different? - -The dbt Semantic Layer reduces code duplication and inconsistency regarding your business metrics. By moving metric definitions out of the BI layer and into the modeling layer, your data teams can feel confident that different business units are working from the same metric definitions, regardless of their tool of choice. If a metric definition changes in dbt, it’s refreshed everywhere it’s invoked and creates consistency across all applications. You can also use the dbt Semantic Layer to query models and use macros. - - -## Prerequisites - - - - - - -## Manage metrics - -:::info 📌 - -New to dbt or metrics? Check out our [quickstart guide](/guides) to build your first dbt project! If you'd like to define your first metrics, try our [Jaffle Shop](https://github.com/dbt-labs/jaffle_shop_metrics) example project. - -::: - -If you're not sure whether to define a metric in dbt or not, ask yourself the following: - -> *Is this something our teams consistently need to report on?* - -An important business metric should be: - -- Well-defined (the definition is agreed upon throughout the entire organization) -- Time-bound (able to be compared across time) - -A great example of this is **revenue**. It can be aggregated on multiple levels (weekly, monthly, and so on) and is key for the broader business to understand. - -- ✅ `Monthly recurring revenue` or `Weekly active users` or `Average order value` -- ❌ `1-off experimental metric` - - -### Design and define metrics - -You can design and define your metrics in `.yml` files nested under a metrics key in your dbt project. For more information, refer to these docs:
- -- [dbt metrics](docs/build/metrics) for in-depth detail on attributes, filters, how to define and query your metrics, and [dbt-metrics package](https://github.com/dbt-labs/dbt_metrics) -- [dbt Semantic Layer quickstart](/docs/use-dbt-semantic-layer/quickstart-semantic-layer) to get started - -## Related questions - -
- How do I migrate from the legacy Semantic Layer to the new one? -
-
If you're using the legacy Semantic Layer, we highly recommend you upgrade your dbt version to dbt v1.6 or higher to use the new dbt Semantic Layer. Refer to the dedicated migration guide for more info.
-
-
- -
- How are you storing my data? -
-
The dbt Semantic Layer doesn't store, cache, or log your data. On each query to the Semantic Layer, the resulting data passes through dbt Cloud servers where it's never stored, cached, or logged. The data from your data platform gets routed through dbt Cloud servers to your connecting data tool.
-
-
-
- Is the dbt Semantic Layer open source? -
-
Some components of the dbt Semantic Layer are open source like dbt-core, the dbt_metrics package, and the BSL-licensed dbt-server. The dbt Proxy Server (what is actually compiling the dbt code) and the Discovery API are not open source.



- -During Public Preview, the dbt Semantic Layer is open to all dbt Cloud tiers — Developer, Team, and Enterprise.



- -
-
-
- Is there a dbt Semantic Layer discussion hub? -
-
Yes, absolutely! Join the dbt Slack community and #dbt-cloud-semantic-layer slack channel for all things related to the dbt Semantic Layer. -
-
-
-

- diff --git a/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md b/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md index 62437f4ecd6..19fcc4b9eda 100644 --- a/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md +++ b/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md @@ -8,8 +8,6 @@ meta: api_name: dbt Semantic Layer APIs --- - - import CreateModel from '/snippets/_sl-create-semanticmodel.md'; import DefineMetrics from '/snippets/_sl-define-metrics.md'; @@ -98,264 +96,3 @@ import SlFaqs from '/snippets/_sl-faqs.md'; - [Available integrations](/docs/use-dbt-semantic-layer/avail-sl-integrations) - Demo on [how to define and query metrics with MetricFlow](https://www.loom.com/share/60a76f6034b0441788d73638808e92ac?sid=861a94ac-25eb-4fd8-a310-58e159950f5a) - [Billing](/docs/cloud/billing) - - - - - -import DeprecationNotice from '/snippets/_sl-deprecation-notice.md'; - - - -To try out the features of the dbt Semantic Layer, you first need to have a dbt project set up. This quickstart guide will lay out the following steps, and recommends a workflow that demonstrates some of its essential features: - -- Install dbt metrics package - * Note: this package will be deprecated very soon and we highly recommend you to use the new [dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl?version=1.6), available in dbt v 1.6 or higher. -- Define metrics -- Query, and run metrics -- Configure the dbt Semantic Layer - -## Prerequisites - -To use the dbt Semantic Layer, you’ll need to meet the following: - - - - - - -:::info 📌 - -New to dbt or metrics? Check out our [quickstart guide](/guides) to build your first dbt project! If you'd like to define your first metrics, try our [Jaffle Shop](https://github.com/dbt-labs/jaffle_shop_metrics) example project. - -::: - -## Installing dbt metrics package - -The dbt Semantic Layer supports the calculation of metrics by using the [dbt metrics package](https://hub.getdbt.com/dbt-labs/metrics/latest/). You can install the dbt metrics package in your dbt project by copying the below code blocks. - - - -```yml -packages: - - package: dbt-labs/metrics - version: [">=1.3.0", "<1.4.0"] -``` - - - - - -```yml -packages: - - package: dbt-labs/metrics - version: [">=0.3.0", "<0.4.0"] -``` - - - - -1. Paste the dbt metrics package code in your `packages.yml` file. -2. Run the [`dbt deps` command](/reference/commands/deps) to install the package. -3. If you see a successful result, you have now installed the dbt metrics package successfully! -4. If you have any errors during the `dbt deps` command run, review the system logs for more information on how to resolve them. Make sure you use a dbt metrics package that’s compatible with your dbt environment version. - - - -## Design and define metrics - -Review our helpful metrics video below, which explains what metrics are, why they're important and how you can get started: - - - -Now that you've organized your metrics folder and files, you can define your metrics in `.yml` files nested under a `metrics` key. - -1. Add the metric definitions found in the [Jaffle Shop](https://github.com/dbt-labs/jaffle_shop_metrics) example to your dbt project. For example, to add an expenses metric, reference the following metrics you can define directly in your metrics folder: - - - -```sql -version: 2 - -metrics: - - name: expenses - label: Expenses - model: ref('orders') - description: "The total expenses of our jaffle business" - - calculation_method: sum - expression: amount / 4 - - timestamp: order_date - time_grains: [day, week, month, year] - - dimensions: - - customer_status - - had_credit_card_payment - - had_coupon_payment - - had_bank_transfer_payment - - had_gift_card_payment - - filters: - - field: status - operator: '=' - value: "'completed'" -``` - - - - -```sql -version: 2 - -metrics: - - name: expenses - label: Expenses - model: ref('orders') - description: "The total expenses of our jaffle business" - - type: sum - sql: amount / 4 - - timestamp: order_date - time_grains: [day, week, month, year] - - dimensions: - - customer_status - - had_credit_card_payment - - had_coupon_payment - - had_bank_transfer_payment - - had_gift_card_payment - - filters: - - field: status - operator: '=' - value: "'completed'" -``` - - -1. Click **Save** and then **Compile** the code. -2. Commit and merge the code changes that contain the metric definitions. -3. If you'd like to further design and define your own metrics, review the following documentation: - - - [dbt metrics](/docs/build/metrics) will provide you in-depth detail on attributes, properties, filters, and how to define and query metrics. - -## Develop and query metrics - -You can dynamically develop and query metrics directly in dbt and verify their accuracy _before_ running a job in the deployment environment by using the `metrics.calculate` and `metrics.develop` macros. - -To understand when and how to use the macros above, review [dbt metrics](/docs/build/metrics) and make sure you install the [dbt_metrics package](https://github.com/dbt-labs/dbt_metrics) first before using the above macros. - -:::info 📌 - -**Note:** You will need access to dbt Cloud and the dbt Semantic Layer from your integrated partner tool of choice. - -::: - -## Run your production job - -Once you’ve defined metrics in your dbt project, you can perform a job run in your deployment environment to materialize your metrics. The deployment environment is only supported for the dbt Semantic Layer at this moment. - -1. Go to **Deploy** in the navigation and select **Jobs** to re-run the job with the most recent code in the deployment environment. -2. Your metric should appear as a red node in the dbt Cloud IDE and dbt directed acyclic graphs (DAG). - - - - -**What’s happening internally?** - -- Merging the code into your main branch allows dbt Cloud to pull those changes and builds the definition in the manifest produced by the run. -- Re-running the job in the deployment environment helps materialize the models, which the metrics depend on, in the data platform. It also makes sure that the manifest is up to date. -- Your dbt Discovery API pulls in the most recent manifest and allows your integration information to extract metadata from it. - -## Set up dbt Semantic Layer - - - - -## Troubleshooting - -If you're encountering some issues when defining your metrics or setting up the dbt Semantic Layer, check out a list of answers to some of the questions or problems you may be experiencing. - -
- How are you storing my data? -
-
The dbt Semantic Layer does not store, or cache, or log your data. On each query to the Semantic Layer, the resulting data passes through dbt Cloud servers where it is never stored, cached, or logged. The data from your data platform gets routed through dbt Cloud servers, to your connecting data tool.
-
-
-
- Is the dbt Semantic Layer open source? -
-
Some components of the dbt Semantic Layer are open source like dbt-core, the dbt_metrics package, and the BSL-licensed dbt-server. The dbt Proxy Server (what is actually compiling the dbt code) and the Discovery API are not open sources.



- -During Public Preview, the dbt Semantic Layer is open to all dbt Cloud tiers (Developer, Team, and Enterprise).



-
    -
  • dbt Core users can define metrics in their dbt Core projects and calculate them using macros from the metrics package. To use the dbt Semantic Layer integrations, you will need to have a dbt Cloud account.




    • -
  • Developer accounts will be able to query the Proxy Server using SQL, but will not be able to browse pre-populated dbt metrics in external tools, which requires access to the Discovery API.




    • -
  • Team and Enterprise accounts will be able to set up the Semantic Layer and Discovery API in the integrated partner tool to import metric definitions.
    • -
-
-
-
-
- The dbt_metrics_calendar_table does not exist or is not authorized? -
-
All metrics queries are dependent on either the dbt_metrics_calendar_table or a custom calendar set in the users dbt_project.yml. If you have not created this model in the database, these queries will fail and you'll most likely see the following error message: - -Object DATABASE.SCHEMA.DBT_METRICS_DEFAULT_CALENDAR does not exist or not authorized.

- -Fix: - -
    -
  • If developing locally, run dbt run --select dbt_metrics_default_calendar


    • -
  • If you are using this in production, make sure that you perform a full dbt build or dbt run. If you are running specific selects in your production job, then you will not create this required model.
    • -
-
-
-
-
- Ephemeral Models - Object does not exist or is not authorized -
-
Metrics cannot be defined on ephemeral models because we reference the underlying table in the query that generates the metric so we need the table/view to exist in the database. If your table/view does not exist in your database, you might see this error message: - - Object 'DATABASE.SCHEMA.METRIC_MODEL_TABLE' does not exist or not authorized.

- -Fix: -
    -
  • You will need to materialize the model that the metric is built on as a table/view/incremental.
    • -
-
-
-
- -
- Mismatched Versions - metric type is ‘’ -
-
If you’re running dbt_metrics ≥v0.3.2 but have dbt-core version ≥1.3.0, you’ll likely see these error messages: - -
    -
  • Error message 1: The metric NAME also references ... but its type is ''. Only metrics of type expression can reference other metrics.
    • -
  • Error message 2: Unknown aggregation style: > in macro default__gen_primary_metric_aggregate (macros/sql_gen/gen_primary_metric_aggregate.sql)
    • -
-The reason you're experiencing this error is because we changed the type property of the metric spec in dbt-core v1.3.0. The new name is calculation_method and the package reflects that new name, so it isn’t finding any type when we try and run outdated code on it.

- -Fix: - - - -
-
-
-

- - -## Next steps - -Are you ready to define your own metrics and bring consistency to data consumers? Review the following documents to understand how to structure, define, and query metrics, and set up the dbt Semantic Layer: - -- [dbt metrics](/docs/build/metrics) for in-depth detail on attributes, properties, filters, and how to define and query metrics -- [dbt Server repo](https://github.com/dbt-labs/dbt-server), which is a persisted HTTP server that wraps dbt core to handle RESTful API requests for dbt operations. - - diff --git a/website/docs/docs/use-dbt-semantic-layer/setup-sl.md b/website/docs/docs/use-dbt-semantic-layer/setup-sl.md index 33f1f43f614..fb7b853ad24 100644 --- a/website/docs/docs/use-dbt-semantic-layer/setup-sl.md +++ b/website/docs/docs/use-dbt-semantic-layer/setup-sl.md @@ -6,9 +6,6 @@ sidebar_label: "Set up your Semantic Layer" tags: [Semantic Layer] --- - - - With the dbt Semantic Layer, you can centrally define business metrics, reduce code duplication and inconsistency, create self-service in downstream tools, and more. Configure the dbt Semantic Layer in dbt Cloud to connect with your integrated partner tool. ## Prerequisites @@ -88,8 +85,6 @@ It is _not_ recommended that you use your dbt Cloud credentials due to elevated
- - ## Related docs - [Build your metrics](/docs/build/build-metrics-intro) diff --git a/website/docs/docs/use-dbt-semantic-layer/sl-architecture.md b/website/docs/docs/use-dbt-semantic-layer/sl-architecture.md index 9aea2ab42b0..f1fd13944e9 100644 --- a/website/docs/docs/use-dbt-semantic-layer/sl-architecture.md +++ b/website/docs/docs/use-dbt-semantic-layer/sl-architecture.md @@ -7,9 +7,6 @@ tags: [Semantic Layer] pagination_next: null --- - - - The dbt Semantic Layer allows you to define metrics and use various interfaces to query them. The Semantic Layer does the heavy lifting to find where the queried data exists in your data platform and generates the SQL to make the request (including performing joins). @@ -46,32 +43,3 @@ The following table compares the features available in dbt Cloud and source avai import SlFaqs from '/snippets/_sl-faqs.md'; - - - - - -import DeprecationNotice from '/snippets/_sl-deprecation-notice.md'; - - - -## Product architecture - -The dbt Semantic Layer product architecture includes four primary components: - -| Components | Information | Developer plans | Team plans | Enterprise plans | License | -| --- | --- | :---: | :---: | :---: | --- | -| **[dbt project](/docs/build/metrics)** | Define models and metrics in dbt Core.
*Note, we will deprecate and no longer support the dbt_metrics package. | ✅ | ✅ | ✅ | Open source, Core | -| **[dbt Server](https://github.com/dbt-labs/dbt-server)**| A persisted HTTP server that wraps dbt core to handle RESTful API requests for dbt operations. | ✅ | ✅ | ✅ | BSL | -| **SQL Proxy** | Reverse-proxy that accepts dbt-SQL (SQL + Jinja like query models and metrics, use macros), compiles the query into pure SQL, and executes the query against the data platform. | ✅

_* Available during Public Preview only_ | ✅ | ✅ | Proprietary, Cloud (Team & Enterprise) | -| **[Discovery API](/docs/dbt-cloud-apis/discovery-api)** | Accesses metric definitions primarily via integrations and is the source of truth for objects defined in dbt projects (like models, macros, sources, metrics). The Discovery API is updated at the end of every dbt Cloud run. | ❌ | ✅ | ✅ | Proprietary, Cloud (Team & Enterprise) | - - - -dbt Semantic Layer integrations will: - -- Leverage the Discovery API to fetch a list of objects and their attributes, like metrics -- Generate a dbt-SQL statement -- Then query the SQL proxy to evaluate the results of this statement - - diff --git a/website/docs/docs/use-dbt-semantic-layer/tableau.md b/website/docs/docs/use-dbt-semantic-layer/tableau.md index 0f12a75f468..689df12ec6a 100644 --- a/website/docs/docs/use-dbt-semantic-layer/tableau.md +++ b/website/docs/docs/use-dbt-semantic-layer/tableau.md @@ -9,7 +9,6 @@ sidebar_label: "Tableau (beta)" The Tableau integration with the dbt Semantic Layer is a [beta feature](/docs/dbt-versions/product-lifecycles#dbt-cloud). ::: - The Tableau integration allows you to use worksheets to query the Semantic Layer directly and produce your dashboards with trusted data. This integration provides a live connection to the dbt Semantic Layer through Tableau Desktop or Tableau Server. diff --git a/website/vercel.json b/website/vercel.json index 3377b49278d..2329cac0941 100644 --- a/website/vercel.json +++ b/website/vercel.json @@ -2,6 +2,11 @@ "cleanUrls": true, "trailingSlash": false, "redirects": [ + { + "source": "/docs/build/metrics", + "destination": "/docs/build/build-metrics-intro", + "permanent": true + }, { "source": "/docs/cloud/dbt-cloud-ide", "destination": "/docs/cloud/dbt-cloud-ide/develop-in-the-cloud", From 8b00253997ff14a9b2f6777da8f13d374493b423 Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Wed, 6 Dec 2023 12:57:02 -0500 Subject: [PATCH 040/165] updat elink --- website/docs/reference/node-selection/methods.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/website/docs/reference/node-selection/methods.md b/website/docs/reference/node-selection/methods.md index e29612e3401..1b3c5be980b 100644 --- a/website/docs/reference/node-selection/methods.md +++ b/website/docs/reference/node-selection/methods.md @@ -244,7 +244,7 @@ dbt ls --select "+exposure:*" --resource-type source # list all sources upstr ### The "metric" method -The `metric` method is used to select parent resources of a specified [metric](/docs/build/metrics). Use in conjunction with the `+` operator. +The `metric` method is used to select parent resources of a specified [metric](/docs/build/build-metrics-intro). Use in conjunction with the `+` operator. ```bash dbt build --select "+metric:weekly_active_users" # build all resources upstream of weekly_active_users metric @@ -367,4 +367,4 @@ dbt list --select semantic_model:* # list all semantic models dbt list --select +semantic_model:orders # list your semantic model named "orders" and all upstream resources ``` - \ No newline at end of file + From 54b29418138dfae2e7c153a83a3b1e8b9d1ae26c Mon Sep 17 00:00:00 2001 From: Mike Alfare <13974384+mikealfare@users.noreply.github.com> Date: Wed, 6 Dec 2023 17:36:24 -0500 Subject: [PATCH 041/165] Update website/docs/reference/resource-configs/postgres-configs.md Co-authored-by: Doug Beatty <44704949+dbeatty10@users.noreply.github.com> --- website/docs/reference/resource-configs/postgres-configs.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/reference/resource-configs/postgres-configs.md b/website/docs/reference/resource-configs/postgres-configs.md index f9bd4e11cbc..855c17d8883 100644 --- a/website/docs/reference/resource-configs/postgres-configs.md +++ b/website/docs/reference/resource-configs/postgres-configs.md @@ -127,7 +127,7 @@ with the following configuration parameters: indexes=[ { 'columns': ['', ...], - 'unique': }, + 'unique': , 'type': '{ HASH | B-TREE | GIST | SP-GIST | GIN | BRIN }', ] ) }} From 964e12563623525ccffc3a52ab6b2b2795f957f2 Mon Sep 17 00:00:00 2001 From: Mike Alfare <13974384+mikealfare@users.noreply.github.com> Date: Wed, 6 Dec 2023 17:36:39 -0500 Subject: [PATCH 042/165] Update website/docs/reference/resource-configs/postgres-configs.md Co-authored-by: Doug Beatty <44704949+dbeatty10@users.noreply.github.com> --- website/docs/reference/resource-configs/postgres-configs.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/reference/resource-configs/postgres-configs.md b/website/docs/reference/resource-configs/postgres-configs.md index 855c17d8883..109bd595bb9 100644 --- a/website/docs/reference/resource-configs/postgres-configs.md +++ b/website/docs/reference/resource-configs/postgres-configs.md @@ -129,7 +129,7 @@ with the following configuration parameters: 'columns': ['', ...], 'unique': , 'type': '{ HASH | B-TREE | GIST | SP-GIST | GIN | BRIN }', - ] + }] ) }} select * from {{ ref('my_base_table') }} From a6f69eb551ce902cef2a9191c3bef052e98e664d Mon Sep 17 00:00:00 2001 From: Mike Alfare <13974384+mikealfare@users.noreply.github.com> Date: Wed, 6 Dec 2023 17:47:36 -0500 Subject: [PATCH 043/165] Update website/docs/reference/resource-configs/snowflake-configs.md Co-authored-by: Doug Beatty <44704949+dbeatty10@users.noreply.github.com> --- website/docs/reference/resource-configs/snowflake-configs.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/reference/resource-configs/snowflake-configs.md b/website/docs/reference/resource-configs/snowflake-configs.md index 39dd4430c4c..900860ea287 100644 --- a/website/docs/reference/resource-configs/snowflake-configs.md +++ b/website/docs/reference/resource-configs/snowflake-configs.md @@ -357,7 +357,7 @@ Dynamic tables are supported with the following configuration parameters: | Parameter | Type | Required | Default | Change Monitoring Support | Reference | |---------------------------|----------|----------|-----------|---------------------------|----------------------------------------------| -| `on_configuration_change` | STRING | NO | `'apply'` | N/A | | +| `on_configuration_change` | STRING | NO | `apply` | N/A | | | `target_lag` | STRING | YES | | ALTER | [Target lag](#target-lag) | | `snowflake_warehouse` | STRING | YES | | ALTER | [Warehouse](#configuring-virtual-warehouses) | From 0d4dd63ad767fcb480ca39f9ee8d2999e920a1d1 Mon Sep 17 00:00:00 2001 From: Mike Alfare Date: Wed, 6 Dec 2023 21:40:59 -0500 Subject: [PATCH 044/165] incorporate style standards --- .../resource-configs/postgres-configs.md | 86 +++++++++++++++---- 1 file changed, 70 insertions(+), 16 deletions(-) diff --git a/website/docs/reference/resource-configs/postgres-configs.md b/website/docs/reference/resource-configs/postgres-configs.md index 109bd595bb9..98ef0d56d27 100644 --- a/website/docs/reference/resource-configs/postgres-configs.md +++ b/website/docs/reference/resource-configs/postgres-configs.md @@ -111,32 +111,86 @@ models: The Postgres adapter supports [materialized views](https://www.postgresql.org/docs/current/rules-materializedviews.html) with the following configuration parameters: -| Parameter | Type | Required | Default | Change Monitoring Support | Reference | -|---------------------------|------------|----------|-----------|---------------------------|---------------------| -| `on_configuration_change` | STRING | NO | `'apply'` | N/A | | -| `indexes` | LIST[DICT] | NO | | ALTER | [Indexes](#indexes) | +| Parameter | Type | Required | Default | Change Monitoring Support | +|---------------------------|------------------|----------|---------|---------------------------| +| `on_configuration_change` | | no | `apply` | n/a | +| [`indexes`](#indexes) | [{}] | no | `none` | alter | + + + + -#### Sample model file: + - +```yaml +models: + [](/reference/resource-configs/resource-path): + [+](/reference/resource-configs/plus-prefix)[materialized](/reference/resource-configs/materialized): materialized_view + [+](/reference/resource-configs/plus-prefix)on_configuration_change: apply | continue | fail + [+](/reference/resource-configs/plus-prefix)[indexes](#indexes): + - columns: [] + unique: true | false + type: hash | btree +``` -```sql + + + + + + + + +```yaml +version: 2 + +models: + - name: [] + config: + [materialized](/reference/resource-configs/materialized): materialized_view + on_configuration_change: apply | continue | fail + [indexes](#indexes): + - columns: [] + unique: true | false + type: hash | btree +``` + + + + + + + + + +```jinja {{ config( - materialized='materialized_view', - on_configuration_change='{ apply | continue | fail }' - indexes=[ + [materialized](/reference/resource-configs/materialized)="materialized_view", + on_configuration_change="apply" | "continue" | "fail" + [indexes](#indexes)=[ { - 'columns': ['', ...], - 'unique': , - 'type': '{ HASH | B-TREE | GIST | SP-GIST | GIN | BRIN }', - }] + "columns": [""], + "unique": true | false, + "type": "hash" | "btree", + } + ] ) }} - -select * from {{ ref('my_base_table') }} ``` + + + + The `indexes` parameter corresponds to that of a table, as linked above. It's worth noting that, unlike with tables, dbt will monitor this parameter for changes and apply the changes without dropping the materialized view. This happens via a `DROP/CREATE` of the indexes, which could be thought of as a `ALTER` of the materialized view. From bd6c4fc146678f0aeae9a9e15f15b2591cdd4bf8 Mon Sep 17 00:00:00 2001 From: Mike Alfare Date: Wed, 6 Dec 2023 22:08:42 -0500 Subject: [PATCH 045/165] incorporate style standards --- website/docs/reference/resource-configs/postgres-configs.md | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/website/docs/reference/resource-configs/postgres-configs.md b/website/docs/reference/resource-configs/postgres-configs.md index 98ef0d56d27..d5960231c66 100644 --- a/website/docs/reference/resource-configs/postgres-configs.md +++ b/website/docs/reference/resource-configs/postgres-configs.md @@ -145,6 +145,7 @@ models: + @@ -167,6 +168,7 @@ models: + @@ -174,7 +176,7 @@ models: ```jinja {{ config( [materialized](/reference/resource-configs/materialized)="materialized_view", - on_configuration_change="apply" | "continue" | "fail" + on_configuration_change="apply" | "continue" | "fail", [indexes](#indexes)=[ { "columns": [""], From 5e904f13d54f8228f2c89848f8ca8a0440b5f026 Mon Sep 17 00:00:00 2001 From: Mike Alfare Date: Wed, 6 Dec 2023 22:34:56 -0500 Subject: [PATCH 046/165] remove tabs to test build --- .../resource-configs/postgres-configs.md | 77 ------------------- 1 file changed, 77 deletions(-) diff --git a/website/docs/reference/resource-configs/postgres-configs.md b/website/docs/reference/resource-configs/postgres-configs.md index d5960231c66..c4d60ba905d 100644 --- a/website/docs/reference/resource-configs/postgres-configs.md +++ b/website/docs/reference/resource-configs/postgres-configs.md @@ -116,83 +116,6 @@ with the following configuration parameters: | `on_configuration_change` | | no | `apply` | n/a | | [`indexes`](#indexes) | [{}] | no | `none` | alter | - - - - - - -```yaml -models: - [](/reference/resource-configs/resource-path): - [+](/reference/resource-configs/plus-prefix)[materialized](/reference/resource-configs/materialized): materialized_view - [+](/reference/resource-configs/plus-prefix)on_configuration_change: apply | continue | fail - [+](/reference/resource-configs/plus-prefix)[indexes](#indexes): - - columns: [] - unique: true | false - type: hash | btree -``` - - - - - - - - - - -```yaml -version: 2 - -models: - - name: [] - config: - [materialized](/reference/resource-configs/materialized): materialized_view - on_configuration_change: apply | continue | fail - [indexes](#indexes): - - columns: [] - unique: true | false - type: hash | btree -``` - - - - - - - - - - -```jinja -{{ config( - [materialized](/reference/resource-configs/materialized)="materialized_view", - on_configuration_change="apply" | "continue" | "fail", - [indexes](#indexes)=[ - { - "columns": [""], - "unique": true | false, - "type": "hash" | "btree", - } - ] -) }} -``` - - - - - - - The `indexes` parameter corresponds to that of a table, as linked above. It's worth noting that, unlike with tables, dbt will monitor this parameter for changes and apply the changes without dropping the materialized view. This happens via a `DROP/CREATE` of the indexes, which could be thought of as a `ALTER` of the materialized view. From 76df337ea6acb03da8fcd1ab313deb6ed0e4e4c3 Mon Sep 17 00:00:00 2001 From: Mike Alfare Date: Wed, 6 Dec 2023 22:43:16 -0500 Subject: [PATCH 047/165] remove quotes to test build --- website/docs/reference/resource-configs/postgres-configs.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/website/docs/reference/resource-configs/postgres-configs.md b/website/docs/reference/resource-configs/postgres-configs.md index c4d60ba905d..de084f9eb02 100644 --- a/website/docs/reference/resource-configs/postgres-configs.md +++ b/website/docs/reference/resource-configs/postgres-configs.md @@ -111,10 +111,10 @@ models: The Postgres adapter supports [materialized views](https://www.postgresql.org/docs/current/rules-materializedviews.html) with the following configuration parameters: -| Parameter | Type | Required | Default | Change Monitoring Support | -|---------------------------|------------------|----------|---------|---------------------------| +| Parameter | Type | Required | Default | Change Monitoring Support | +|-------------------------|------------------|----------|---------|---------------------------| | `on_configuration_change` | | no | `apply` | n/a | -| [`indexes`](#indexes) | [{}] | no | `none` | alter | +| [indexes](#indexes) | [{}] | no | `none` | alter | The `indexes` parameter corresponds to that of a table, as linked above. It's worth noting that, unlike with tables, dbt will monitor this parameter for changes and apply the changes without dropping the materialized view. From b744ea85e0b24fcbad5a73d4c2fc4d8deba1e206 Mon Sep 17 00:00:00 2001 From: Mike Alfare Date: Wed, 6 Dec 2023 22:53:13 -0500 Subject: [PATCH 048/165] test build --- .../reference/resource-configs/postgres-configs.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/website/docs/reference/resource-configs/postgres-configs.md b/website/docs/reference/resource-configs/postgres-configs.md index de084f9eb02..e230641c37a 100644 --- a/website/docs/reference/resource-configs/postgres-configs.md +++ b/website/docs/reference/resource-configs/postgres-configs.md @@ -111,10 +111,10 @@ models: The Postgres adapter supports [materialized views](https://www.postgresql.org/docs/current/rules-materializedviews.html) with the following configuration parameters: -| Parameter | Type | Required | Default | Change Monitoring Support | -|-------------------------|------------------|----------|---------|---------------------------| -| `on_configuration_change` | | no | `apply` | n/a | -| [indexes](#indexes) | [{}] | no | `none` | alter | +| Parameter | Type | Required | Default | Change Monitoring Support | +|---------------------------|--------------|----------|---------|---------------------------| +| `on_configuration_change` | | no | `apply` | n/a | +| [indexes](#indexes) | | no | `none` | alter | The `indexes` parameter corresponds to that of a table, as linked above. It's worth noting that, unlike with tables, dbt will monitor this parameter for changes and apply the changes without dropping the materialized view. @@ -123,7 +123,7 @@ This happens via a `DROP/CREATE` of the indexes, which could be thought of as a Find more information about materialized view parameters in the Postgres docs: - [CREATE MATERIALIZED VIEW](https://www.postgresql.org/docs/current/sql-creatematerializedview.html) - + ### Limitations From fb00255b8588c8df6a324f00780adc85858978b1 Mon Sep 17 00:00:00 2001 From: Mike Alfare Date: Wed, 6 Dec 2023 22:59:24 -0500 Subject: [PATCH 049/165] test build --- .../docs/reference/resource-configs/postgres-configs.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/website/docs/reference/resource-configs/postgres-configs.md b/website/docs/reference/resource-configs/postgres-configs.md index e230641c37a..d4e53efbc1d 100644 --- a/website/docs/reference/resource-configs/postgres-configs.md +++ b/website/docs/reference/resource-configs/postgres-configs.md @@ -111,10 +111,10 @@ models: The Postgres adapter supports [materialized views](https://www.postgresql.org/docs/current/rules-materializedviews.html) with the following configuration parameters: -| Parameter | Type | Required | Default | Change Monitoring Support | -|---------------------------|--------------|----------|---------|---------------------------| -| `on_configuration_change` | | no | `apply` | n/a | -| [indexes](#indexes) | | no | `none` | alter | +| Parameter | Type | Required | Default | Change Monitoring Support | +|---------------------------|------------|----------|---------|---------------------------| +| `on_configuration_change` | string | no | `apply` | n/a | +| [indexes](#indexes) | dictionary | no | `none` | alter | The `indexes` parameter corresponds to that of a table, as linked above. It's worth noting that, unlike with tables, dbt will monitor this parameter for changes and apply the changes without dropping the materialized view. From d19ea838bfd9d1538e7c1e264886e0620feebada Mon Sep 17 00:00:00 2001 From: Mike Alfare Date: Wed, 6 Dec 2023 23:08:08 -0500 Subject: [PATCH 050/165] add tabs back in --- .../resource-configs/postgres-configs.md | 78 +++++++++++++++++++ 1 file changed, 78 insertions(+) diff --git a/website/docs/reference/resource-configs/postgres-configs.md b/website/docs/reference/resource-configs/postgres-configs.md index d4e53efbc1d..d47aaad7559 100644 --- a/website/docs/reference/resource-configs/postgres-configs.md +++ b/website/docs/reference/resource-configs/postgres-configs.md @@ -116,6 +116,84 @@ with the following configuration parameters: | `on_configuration_change` | string | no | `apply` | n/a | | [indexes](#indexes) | dictionary | no | `none` | alter | + + + + + + + +```yaml +models: + [](/reference/resource-configs/resource-path): + [+](/reference/resource-configs/plus-prefix)[materialized](/reference/resource-configs/materialized): materialized_view + [+](/reference/resource-configs/plus-prefix)on_configuration_change: apply | continue | fail + [+](/reference/resource-configs/plus-prefix)[indexes](#indexes): + - columns: [] + unique: true | false + type: hash | btree +``` + + + + + + + + + + +```yaml +version: 2 + +models: + - name: [] + config: + [materialized](/reference/resource-configs/materialized): materialized_view + on_configuration_change: apply | continue | fail + [indexes](#indexes): + - columns: [] + unique: true | false + type: hash | btree +``` + + + + + + + + + + +```jinja +{{ config( + [materialized](/reference/resource-configs/materialized)="materialized_view", + on_configuration_change="apply" | "continue" | "fail", + [indexes](#indexes)=[ + { + "columns": [""], + "unique": true | false, + "type": "hash" | "btree", + } + ] +) }} +``` + + + + + + + The `indexes` parameter corresponds to that of a table, as linked above. It's worth noting that, unlike with tables, dbt will monitor this parameter for changes and apply the changes without dropping the materialized view. This happens via a `DROP/CREATE` of the indexes, which could be thought of as a `ALTER` of the materialized view. From 139046b04d6d55fae6336ede64dbdf8afa7a7556 Mon Sep 17 00:00:00 2001 From: Mike Alfare Date: Wed, 6 Dec 2023 23:33:23 -0500 Subject: [PATCH 051/165] add formatting back --- .../docs/reference/resource-configs/postgres-configs.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/website/docs/reference/resource-configs/postgres-configs.md b/website/docs/reference/resource-configs/postgres-configs.md index d47aaad7559..c904802d598 100644 --- a/website/docs/reference/resource-configs/postgres-configs.md +++ b/website/docs/reference/resource-configs/postgres-configs.md @@ -111,10 +111,10 @@ models: The Postgres adapter supports [materialized views](https://www.postgresql.org/docs/current/rules-materializedviews.html) with the following configuration parameters: -| Parameter | Type | Required | Default | Change Monitoring Support | -|---------------------------|------------|----------|---------|---------------------------| -| `on_configuration_change` | string | no | `apply` | n/a | -| [indexes](#indexes) | dictionary | no | `none` | alter | +| Parameter | Type | Required | Default | Change Monitoring Support | +|---------------------------|--------------------|----------|---------|---------------------------| +| `on_configuration_change` | `` | no | `apply` | n/a | +| [`indexes`](#indexes) | `[{}]` | no | `none` | alter | Date: Thu, 7 Dec 2023 09:49:50 -0500 Subject: [PATCH 052/165] removing metric and metrics schema --- .../schema-discovery-job-metric.mdx | 58 ------------------ .../schema-discovery-job-metrics.mdx | 60 ------------------- website/sidebars.js | 2 - website/vercel.json | 10 ++++ 4 files changed, 10 insertions(+), 120 deletions(-) delete mode 100644 website/docs/docs/dbt-cloud-apis/schema-discovery-job-metric.mdx delete mode 100644 website/docs/docs/dbt-cloud-apis/schema-discovery-job-metrics.mdx diff --git a/website/docs/docs/dbt-cloud-apis/schema-discovery-job-metric.mdx b/website/docs/docs/dbt-cloud-apis/schema-discovery-job-metric.mdx deleted file mode 100644 index 3a8a52a19cb..00000000000 --- a/website/docs/docs/dbt-cloud-apis/schema-discovery-job-metric.mdx +++ /dev/null @@ -1,58 +0,0 @@ ---- -title: "Metric object schema" -sidebar_label: "Metric" -id: "discovery-schema-job-metric" ---- - -import { NodeArgsTable, SchemaTable } from "./schema"; - -The metric object allows you to query information about [metrics](/docs/build/metrics). - -### Arguments - -When querying for a `metric`, the following arguments are available. - - - -Below we show some illustrative example queries and outline the schema (all possible fields you can query) of the metric object. - -### Example query - -The example query below outputs information about a metric. You can also add any field from the model endpoint (the example simply selects name). This includes schema, database, uniqueId, columns, and more. For details, refer to [Model object schema](/docs/dbt-cloud-apis/discovery-schema-job-model). - - -```graphql -{ - job(id: 123) { - metric(uniqueId: "metric.jaffle_shop.new_customers") { - uniqueId - name - packageName - tags - label - runId - description - type - sql - timestamp - timeGrains - dimensions - meta - resourceType - filters { - field - operator - value - } - model { - name - } - } - } -} -``` - -### Fields -When querying for a `metric`, the following fields are available: - - diff --git a/website/docs/docs/dbt-cloud-apis/schema-discovery-job-metrics.mdx b/website/docs/docs/dbt-cloud-apis/schema-discovery-job-metrics.mdx deleted file mode 100644 index 174dd5b676a..00000000000 --- a/website/docs/docs/dbt-cloud-apis/schema-discovery-job-metrics.mdx +++ /dev/null @@ -1,60 +0,0 @@ ---- -title: "Metrics object schema" -sidebar_label: "Metrics" -id: "discovery-schema-job-metrics" ---- - -import { NodeArgsTable, SchemaTable } from "./schema"; - -The metrics object allows you to query information about [metrics](/docs/build/metrics). - - -### Arguments - -When querying for `metrics`, the following arguments are available. - - - -Below we show some illustrative example queries and outline the schema (all possible fields you can query) of the metrics object. - -### Example query - -The example query returns information about all metrics for the given job. - -```graphql -{ - job(id: 123) { - metrics { - uniqueId - name - packageName - tags - label - runId - description - type - sql - timestamp - timeGrains - dimensions - meta - resourceType - filters { - field - operator - value - } - model { - name - } - } - } -} -``` - -### Fields -The metrics object can access the _same fields_ as the [metric node](/docs/dbt-cloud-apis/discovery-schema-job-metric). The difference is that the metrics object can output a list so instead of querying for fields for one specific metric, you can query for those parameters for all metrics in a run. - -When querying for `metrics`, the following fields are available: - - diff --git a/website/sidebars.js b/website/sidebars.js index 598fffc7f0d..792645b53e7 100644 --- a/website/sidebars.js +++ b/website/sidebars.js @@ -556,8 +556,6 @@ const sidebarSettings = { "docs/dbt-cloud-apis/discovery-schema-job", "docs/dbt-cloud-apis/discovery-schema-job-model", "docs/dbt-cloud-apis/discovery-schema-job-models", - "docs/dbt-cloud-apis/discovery-schema-job-metric", - "docs/dbt-cloud-apis/discovery-schema-job-metrics", "docs/dbt-cloud-apis/discovery-schema-job-source", "docs/dbt-cloud-apis/discovery-schema-job-sources", "docs/dbt-cloud-apis/discovery-schema-job-seed", diff --git a/website/vercel.json b/website/vercel.json index 2329cac0941..eb057123cde 100644 --- a/website/vercel.json +++ b/website/vercel.json @@ -2,6 +2,16 @@ "cleanUrls": true, "trailingSlash": false, "redirects": [ + { + "source": "/docs/dbt-cloud-apis/discovery-schema-job-metric", + "destination": "/docs/dbt-cloud-apis/discovery-schema-environment", + "permanent": true + }, + { + "source": "/docs/dbt-cloud-apis/discovery-schema-job-metrics", + "destination": "/docs/dbt-cloud-apis/discovery-schema-environment", + "permanent": true + }, { "source": "/docs/build/metrics", "destination": "/docs/build/build-metrics-intro", From deee6a8f96ff41a50cd0f01ee3fb192a20708cf8 Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Thu, 7 Dec 2023 11:26:56 -0500 Subject: [PATCH 053/165] Update website/docs/reference/data-test-configs.md Co-authored-by: Doug Beatty <44704949+dbeatty10@users.noreply.github.com> --- website/docs/reference/data-test-configs.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/reference/data-test-configs.md b/website/docs/reference/data-test-configs.md index 13154832cef..5f922d08c6b 100644 --- a/website/docs/reference/data-test-configs.md +++ b/website/docs/reference/data-test-configs.md @@ -260,7 +260,7 @@ select ... -#### Disable alldata tests from a package +#### Disable all data tests from a package From d4f8ff1e05305168162db0d2ce58a21e892dd28c Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Thu, 7 Dec 2023 11:27:21 -0500 Subject: [PATCH 054/165] Update website/docs/best-practices/custom-generic-tests.md Co-authored-by: Grace Goheen <53586774+graciegoheen@users.noreply.github.com> --- website/docs/best-practices/custom-generic-tests.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/best-practices/custom-generic-tests.md b/website/docs/best-practices/custom-generic-tests.md index cd6dced8ad2..bd232a0a5d5 100644 --- a/website/docs/best-practices/custom-generic-tests.md +++ b/website/docs/best-practices/custom-generic-tests.md @@ -9,7 +9,7 @@ hoverSnippet: Learn how to define your own custom generic tests. dbt ships with [Not Null](/reference/resource-properties/data-tests#not-null), [Unique](/reference/resource-properties/data-tests#unique), [Relationships](/reference/resource-properties/data-tests#relationships), and [Accepted Values](/reference/resource-properties/data-tests#accepted-values) generic tests. (These used to be called "schema tests," and you'll still see that name in some places.) Under the hood, these generic tests are defined as `test` blocks (like macros) in a globally accessible dbt project. You can find the source code for these tests in the [global project](https://github.com/dbt-labs/dbt-core/tree/main/core/dbt/include/global_project/macros/generic_test_sql). :::info -There are tons of generic tests defined in open source packages, such as [dbt-utils](https://hub.getdbt.com/dbt-labs/dbt_utils/latest/) and [dbt-expectations](https://hub.getdbt.com/calogica/dbt_expectations/latest/) — the test you're looking for might already be here! +There are tons of generic data tests defined in open source packages, such as [dbt-utils](https://hub.getdbt.com/dbt-labs/dbt_utils/latest/) and [dbt-expectations](https://hub.getdbt.com/calogica/dbt_expectations/latest/) — the test you're looking for might already be here! ::: ### Generic tests with standard arguments From 1aa147a33b2a79cb038763d2a9cc2222bb2ae85a Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Thu, 7 Dec 2023 11:28:17 -0500 Subject: [PATCH 055/165] Update website/docs/best-practices/custom-generic-tests.md Co-authored-by: Grace Goheen <53586774+graciegoheen@users.noreply.github.com> --- website/docs/best-practices/custom-generic-tests.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/best-practices/custom-generic-tests.md b/website/docs/best-practices/custom-generic-tests.md index bd232a0a5d5..3f59d6916c6 100644 --- a/website/docs/best-practices/custom-generic-tests.md +++ b/website/docs/best-practices/custom-generic-tests.md @@ -6,7 +6,7 @@ displayText: Writing custom generic tests hoverSnippet: Learn how to define your own custom generic tests. --- -dbt ships with [Not Null](/reference/resource-properties/data-tests#not-null), [Unique](/reference/resource-properties/data-tests#unique), [Relationships](/reference/resource-properties/data-tests#relationships), and [Accepted Values](/reference/resource-properties/data-tests#accepted-values) generic tests. (These used to be called "schema tests," and you'll still see that name in some places.) Under the hood, these generic tests are defined as `test` blocks (like macros) in a globally accessible dbt project. You can find the source code for these tests in the [global project](https://github.com/dbt-labs/dbt-core/tree/main/core/dbt/include/global_project/macros/generic_test_sql). +dbt ships with [Not Null](/reference/resource-properties/data-tests#not-null), [Unique](/reference/resource-properties/data-tests#unique), [Relationships](/reference/resource-properties/data-tests#relationships), and [Accepted Values](/reference/resource-properties/data-tests#accepted-values) generic data tests. (These used to be called "schema tests," and you'll still see that name in some places.) Under the hood, these generic data tests are defined as `test` blocks (like macros) in a globally accessible dbt project. You can find the source code for these tests in the [global project](https://github.com/dbt-labs/dbt-core/tree/main/core/dbt/include/global_project/macros/generic_test_sql). :::info There are tons of generic data tests defined in open source packages, such as [dbt-utils](https://hub.getdbt.com/dbt-labs/dbt_utils/latest/) and [dbt-expectations](https://hub.getdbt.com/calogica/dbt_expectations/latest/) — the test you're looking for might already be here! From 4ce204051236ff2cbe3f9239b3345d5f9c287093 Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Thu, 7 Dec 2023 11:28:28 -0500 Subject: [PATCH 056/165] Update website/docs/docs/build/data-tests.md Co-authored-by: Grace Goheen <53586774+graciegoheen@users.noreply.github.com> --- website/docs/docs/build/data-tests.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/docs/build/data-tests.md b/website/docs/docs/build/data-tests.md index a63b25dffca..3ff0564526c 100644 --- a/website/docs/docs/build/data-tests.md +++ b/website/docs/docs/build/data-tests.md @@ -19,7 +19,7 @@ Data tests are assertions you make about your models and other resources in your You can use data tests to improve the integrity of the SQL in each model by making assertions about the results generated. Out of the box, you can test whether a specified column in a model only contains non-null values, unique values, or values that have a corresponding value in another model (for example, a `customer_id` for an `order` corresponds to an `id` in the `customers` model), and values from a specified list. You can extend data tests to suit business logic specific to your organization – any assertion that you can make about your model in the form of a select query can be turned into a data test. -Both types of tests return a set of failing records. Previously, generic/schema tests returned a numeric value representing failures. Generic data tests (f.k.a. schema tests) are defined using `test` blocks instead of macros prefixed `test_`. +Data tests return a set of failing records. Generic data tests (f.k.a. schema tests) are defined using `test` blocks. Like almost everything in dbt, data tests are SQL queries. In particular, they are `select` statements that seek to grab "failing" records, ones that disprove your assertion. If you assert that a column is unique in a model, the test query selects for duplicates; if you assert that a column is never null, the test seeks after nulls. If the test returns zero failing rows, it passes, and your assertion has been validated. From 97ccd64672c38790a8106a5cbb4b7d59fc4f819a Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Thu, 7 Dec 2023 11:28:37 -0500 Subject: [PATCH 057/165] Update website/docs/terms/data-wrangling.md Co-authored-by: Grace Goheen <53586774+graciegoheen@users.noreply.github.com> --- website/docs/terms/data-wrangling.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/terms/data-wrangling.md b/website/docs/terms/data-wrangling.md index d71013524ca..96f3e938411 100644 --- a/website/docs/terms/data-wrangling.md +++ b/website/docs/terms/data-wrangling.md @@ -152,7 +152,7 @@ For nested data types such as JSON, you’ll want to check out the JSON parsing dbt offers [generic tests](/docs/build/data-tests#more-generic-tests) in every dbt project that allows you to validate accepted, unique, and null values. They also allow you to validate the relationships between tables and that the primary key is unique. -If you can’t find what you need with the generic tests, you can download an additional dbt testing package called [dbt_expectations](https://hub.getdbt.com/calogica/dbt_expectations/0.1.2/) that dives even deeper into how you can test the values in your columns. This package has useful tests like `expect_column_values_to_be_in_type_list`, `expect_column_values_to_be_between`, and `expect_column_value_lengths_to_equal`. +If you can’t find what you need with the generic tests, you can download an additional dbt testing package called [dbt_expectations](https://hub.getdbt.com/calogica/dbt_expectations/0.1.2/) that dives even deeper into how you can test the values in your columns. This package has useful data tests like `expect_column_values_to_be_in_type_list`, `expect_column_values_to_be_between`, and `expect_column_value_lengths_to_equal`. ## Conclusion From c11032e963dfc902366fd27c40fae42d6a1f252f Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Thu, 7 Dec 2023 11:28:44 -0500 Subject: [PATCH 058/165] Update website/docs/terms/primary-key.md Co-authored-by: Grace Goheen <53586774+graciegoheen@users.noreply.github.com> --- website/docs/terms/primary-key.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/terms/primary-key.md b/website/docs/terms/primary-key.md index 5724e2b3b6e..489085342da 100644 --- a/website/docs/terms/primary-key.md +++ b/website/docs/terms/primary-key.md @@ -141,7 +141,7 @@ If you don't have a field in your table that would act as a natural primary key, If your data warehouse doesn’t provide out-of-the box support and enforcement for primary keys, it’s important to clearly label and put your own constraints on primary key fields. This could look like: * **Creating a consistent naming convention for your primary keys**: You may see an `id` field or fields prefixed with `pk_` (ex. `pk_order_id`) to identify primary keys. You may also see the primary key be named as the obvious table grain (ex. In the jaffle shop’s `orders` table, the primary key is called `order_id`). -* **Adding automated [tests](/docs/build/data-tests) to your data models**: Use a data tool, such as dbt, to create not null and unique tests for your primary key fields. +* **Adding automated [data tests](/docs/build/data-tests) to your data models**: Use a data tool, such as dbt, to create not null and unique tests for your primary key fields. ## Testing primary keys From ca9395ff2b53ad151944fcca664c1cc2b909c81f Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Thu, 7 Dec 2023 11:28:56 -0500 Subject: [PATCH 059/165] Update website/docs/terms/surrogate-key.md Co-authored-by: Grace Goheen <53586774+graciegoheen@users.noreply.github.com> --- website/docs/terms/surrogate-key.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/terms/surrogate-key.md b/website/docs/terms/surrogate-key.md index 9b8c932ee5a..1c4d7f21d57 100644 --- a/website/docs/terms/surrogate-key.md +++ b/website/docs/terms/surrogate-key.md @@ -177,7 +177,7 @@ After executing this, the table would now have the `unique_id` field now uniquel Amazing, you just made a surrogate key! You can just move on to the next data model, right? No!! It’s critically important to test your surrogate keys for uniqueness and non-null values to ensure that the correct fields were chosen to create the surrogate key. -In order to test for null and unique values you can utilize code-based tests like [dbt tests](/docs/build/data-tests), that can check fields for nullness and uniqueness. You can additionally utilize simple SQL queries or unit tests to check if surrogate key count and non-nullness is correct. +In order to test for null and unique values you can utilize code-based data tests like [dbt tests](/docs/build/data-tests), that can check fields for nullness and uniqueness. You can additionally utilize simple SQL queries or unit tests to check if surrogate key count and non-nullness is correct. ## A note on hashing algorithms From d4c9d1be12103955f14af54796a7dc27e4babc96 Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Thu, 7 Dec 2023 11:29:05 -0500 Subject: [PATCH 060/165] Update website/docs/docs/build/data-tests.md Co-authored-by: Grace Goheen <53586774+graciegoheen@users.noreply.github.com> --- website/docs/docs/build/data-tests.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/docs/build/data-tests.md b/website/docs/docs/build/data-tests.md index 3ff0564526c..a5995759f2a 100644 --- a/website/docs/docs/build/data-tests.md +++ b/website/docs/docs/build/data-tests.md @@ -21,7 +21,7 @@ You can use data tests to improve the integrity of the SQL in each model by maki Data tests return a set of failing records. Generic data tests (f.k.a. schema tests) are defined using `test` blocks. -Like almost everything in dbt, data tests are SQL queries. In particular, they are `select` statements that seek to grab "failing" records, ones that disprove your assertion. If you assert that a column is unique in a model, the test query selects for duplicates; if you assert that a column is never null, the test seeks after nulls. If the test returns zero failing rows, it passes, and your assertion has been validated. +Like almost everything in dbt, data tests are SQL queries. In particular, they are `select` statements that seek to grab "failing" records, ones that disprove your assertion. If you assert that a column is unique in a model, the test query selects for duplicates; if you assert that a column is never null, the test seeks after nulls. If the data test returns zero failing rows, it passes, and your assertion has been validated. There are two ways of defining data tests in dbt: * A **singular** test is testing in its simplest form: If you can write a SQL query that returns failing rows, you can save that query in a `.sql` file within your [test directory](/reference/project-configs/test-paths). It's now a test, and it will be executed by the `dbt test` command. From 9ddd75a8a0bdb65fe518344ecb5f523306148fe4 Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Thu, 7 Dec 2023 11:29:12 -0500 Subject: [PATCH 061/165] Update website/docs/terms/primary-key.md Co-authored-by: Grace Goheen <53586774+graciegoheen@users.noreply.github.com> --- website/docs/terms/primary-key.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/terms/primary-key.md b/website/docs/terms/primary-key.md index 489085342da..fde3ff44ac7 100644 --- a/website/docs/terms/primary-key.md +++ b/website/docs/terms/primary-key.md @@ -108,7 +108,7 @@ In general for Redshift, it’s still good practice to define your primary keys ### Google BigQuery -BigQuery is pretty unique here in that it doesn’t support or enforce primary keys. If your team is on BigQuery, you’ll need to have some [pretty solid testing](/docs/build/data-tests) in place to ensure your primary key fields are unique and non-null. +BigQuery is pretty unique here in that it doesn’t support or enforce primary keys. If your team is on BigQuery, you’ll need to have some [pretty solid data testing](/docs/build/data-tests) in place to ensure your primary key fields are unique and non-null. ### Databricks From 20b746e238f93b187867a6b2ccefc9eaf9f6bfdb Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Thu, 7 Dec 2023 11:30:50 -0500 Subject: [PATCH 062/165] Update website/docs/best-practices/custom-generic-tests.md --- website/docs/best-practices/custom-generic-tests.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/best-practices/custom-generic-tests.md b/website/docs/best-practices/custom-generic-tests.md index 3f59d6916c6..4be3caeef5a 100644 --- a/website/docs/best-practices/custom-generic-tests.md +++ b/website/docs/best-practices/custom-generic-tests.md @@ -3,7 +3,7 @@ title: "Writing custom generic tests" id: "writing-custom-generic-tests" description: Learn how to define your own custom generic tests. displayText: Writing custom generic tests -hoverSnippet: Learn how to define your own custom generic tests. +hoverSnippet: Learn how to write your own custom generic tests. --- dbt ships with [Not Null](/reference/resource-properties/data-tests#not-null), [Unique](/reference/resource-properties/data-tests#unique), [Relationships](/reference/resource-properties/data-tests#relationships), and [Accepted Values](/reference/resource-properties/data-tests#accepted-values) generic data tests. (These used to be called "schema tests," and you'll still see that name in some places.) Under the hood, these generic data tests are defined as `test` blocks (like macros) in a globally accessible dbt project. You can find the source code for these tests in the [global project](https://github.com/dbt-labs/dbt-core/tree/main/core/dbt/include/global_project/macros/generic_test_sql). From 01fe6448de311e61d1ab7e38f56db5235b097bd6 Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Thu, 7 Dec 2023 11:31:56 -0500 Subject: [PATCH 063/165] Update custom-generic-tests.md --- website/docs/best-practices/custom-generic-tests.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/website/docs/best-practices/custom-generic-tests.md b/website/docs/best-practices/custom-generic-tests.md index 4be3caeef5a..e96fc864ee6 100644 --- a/website/docs/best-practices/custom-generic-tests.md +++ b/website/docs/best-practices/custom-generic-tests.md @@ -1,9 +1,9 @@ --- -title: "Writing custom generic tests" +title: "Writing custom generic data tests" id: "writing-custom-generic-tests" -description: Learn how to define your own custom generic tests. -displayText: Writing custom generic tests -hoverSnippet: Learn how to write your own custom generic tests. +description: Learn how to define your own custom generic data tests. +displayText: Writing custom generic data tests +hoverSnippet: Learn how to write your own custom generic data tests. --- dbt ships with [Not Null](/reference/resource-properties/data-tests#not-null), [Unique](/reference/resource-properties/data-tests#unique), [Relationships](/reference/resource-properties/data-tests#relationships), and [Accepted Values](/reference/resource-properties/data-tests#accepted-values) generic data tests. (These used to be called "schema tests," and you'll still see that name in some places.) Under the hood, these generic data tests are defined as `test` blocks (like macros) in a globally accessible dbt project. You can find the source code for these tests in the [global project](https://github.com/dbt-labs/dbt-core/tree/main/core/dbt/include/global_project/macros/generic_test_sql). From f50eb361a0066c9a264361d3bbce909ac0240eb2 Mon Sep 17 00:00:00 2001 From: Mike Alfare Date: Thu, 7 Dec 2023 12:20:56 -0500 Subject: [PATCH 064/165] update to use appropriate style guidelines --- .../resource-configs/bigquery-configs.md | 165 +++++++++++++----- 1 file changed, 126 insertions(+), 39 deletions(-) diff --git a/website/docs/reference/resource-configs/bigquery-configs.md b/website/docs/reference/resource-configs/bigquery-configs.md index 97acb73ce33..f9b447fdc0b 100644 --- a/website/docs/reference/resource-configs/bigquery-configs.md +++ b/website/docs/reference/resource-configs/bigquery-configs.md @@ -725,60 +725,147 @@ The `grant_access_to` config is not thread-safe when multiple views need to be a The BigQuery adapter supports [materialized views](https://cloud.google.com/bigquery/docs/materialized-views-intro) with the following configuration parameters: -| Parameter | Type | Required | Default | Change Monitoring Support | Reference | -|------------------------------|----------------------|----------|-----------|---------------------------|--------------------------------------------------| -| `on_configuration_change` | STRING | NO | `'apply'` | N/A | | -| `cluster_by` | LIST[STRING] | NO | | DROP/CREATE | [Clustering](#clustering-clause) | -| `partition_by` | DICT | NO | | DROP/CREATE | [Partitioning](#partition-clause) | -| `enable_refresh` | BOOLEAN | NO | `True` | ALTER | [Auto-refresh](#auto-refresh) | -| `refresh_interval_minutes` | FLOAT | NO | `30` | ALTER | [Auto-refresh](#auto-refresh) | -| `max_staleness` (in Preview) | INTERVAL | NO | | ALTER | [Auto-refresh](#auto-refresh) | -| `description` | STRING | NO | | ALTER | | -| `labels` | DICT[STRING, STRING] | NO | | ALTER | [Labels](#specifying-labels) | -| `hours_to_expiration` | INTEGER | NO | | ALTER | [Table expiration](controlling-table-expiration) | -| `kms_key_name` | STRING | NO | | ALTER | [KMS encryption](#using-kms-encryption) | - -#### Sample model file: - - +| Parameter | Type | Required | Default | Change Monitoring Support | +|--------------------------------------------------------|------------------------|----------|---------|---------------------------| +| `on_configuration_change` | `` | no | `apply` | n/a | +| [`cluster_by`](#clustering-clause) | `[]` | no | `none` | drop/create | +| [`partition_by`](#partition-clause) | `{}` | no | `none` | drop/create | +| [`enable_refresh`](#auto-refresh) | `` | no | `true` | alter | +| [`refresh_interval_minutes`](#auto-refresh) | `` | no | `30` | alter | +| [`max_staleness`](#auto-refresh) (in Preview) | `` | no | `none` | alter | +| `description` | `` | no | `none` | alter | +| [`labels`](#specifying-labels) | `{: }` | no | `none` | alter | +| [`hours_to_expiration`](#controlling-table-expiration) | `` | no | `none` | alter | +| [`kms_key_name`](#using-kms-encryption) | `` | no | `none` | alter | -```sql + + + + + + +directly to the materialized view in place. + +```yaml +models: + [](/reference/resource-configs/resource-path): + [+](/reference/resource-configs/plus-prefix)[materialized](/reference/resource-configs/materialized): materialized_view + [+](/reference/resource-configs/plus-prefix)on_configuration_change: apply | continue | fail + [+](/reference/resource-configs/plus-prefix)[cluster_by](#clustering-clause): | [] + [+](/reference/resource-configs/plus-prefix)[partition_by](#partition-clause): + - field: + - data_type: timestamp | date | datetime | int64 + # only if `data_type` is not 'int64' + - granularity: hour | day | month | year + # only if `data_type` is 'int64' + - range: + - start: + - end: + - interval: + [+](/reference/resource-configs/plus-prefix)[enable_refresh](#auto-refresh): true | false + [+](/reference/resource-configs/plus-prefix)[refresh_interval_minutes](#auto-refresh): + [+](/reference/resource-configs/plus-prefix)[max_staleness](#auto-refresh): + [+](/reference/resource-configs/plus-prefix)description: + [+](/reference/resource-configs/plus-prefix)[labels](#specifying-labels): {: } + [+](/reference/resource-configs/plus-prefix)[hours_to_expiration](#acontrolling-table-expiration): + [+](/reference/resource-configs/plus-prefix)[kms_key_name](##using-kms-encryption): +``` + + + + + + + + + + +```yaml +version: 2 + +models: + - name: [] + config: + [materialized](/reference/resource-configs/materialized): materialized_view + on_configuration_change: apply | continue | fail + [cluster_by](#clustering-clause): | [] + [partition_by](#partition-clause): + - field: + - data_type: timestamp | date | datetime | int64 + # only if `data_type` is not 'int64' + - granularity: hour | day | month | year + # only if `data_type` is 'int64' + - range: + - start: + - end: + - interval: + [enable_refresh](#auto-refresh): true | false + [refresh_interval_minutes](#auto-refresh): + [max_staleness](#auto-refresh): + description: + [labels](#specifying-labels): {: } + [hours_to_expiration](#acontrolling-table-expiration): + [kms_key_name](##using-kms-encryption): +``` + + + + + + + + + + +```jinja {{ config( materialized='materialized_view', - on_configuration_change='{ apply | continue | fail }' - cluster_by=['', ...], + on_configuration_change="apply" | "continue" | "fail", + cluster_by="" | [""], partition_by={ - 'field': '', - 'data_type': '', + "field": "", + "data_type": "timestamp" | "date" | "datetime" | "int64", # only if `data_type` is not 'int64' - 'granularity': '' + "granularity": "hour" | "day" | "month" | "year, # only if `data_type` is 'int64' - 'range': { - 'start': , - 'end': , - 'interval': , + "range": { + "start": , + "end": , + "interval": , } }, # auto-refresh options - enable_refresh=, + enable_refresh= true | false, refresh_interval_minutes=, - max_staleness='', + max_staleness="", # additional options - description='', - labels={'': '', ...}, - hours_to_expiration=, - kms_key_name='', + description="", + labels={ + "": "", + }, + hours_to_expiration=, + kms_key_name="", ) }} - -select * from {{ ref('my_base_table') }} ``` + + + + Many of these parameters correspond to their table counterparts and have been linked above. The set of parameters which are unique to materialized views covers auto-refresh functionality, which is covered [below](#auto-refresh). @@ -788,11 +875,11 @@ Find more information about these parameters in the BigQuery docs: ### Auto-refresh -| Parameter | Type | Required | Default | Change Monitoring Support | -|-------------------------------|----------|----------|---------|---------------------------| -| `enable_refresh` | BOOLEAN | NO | `True` | ALTER | -| `refresh_interval_minutes` | FLOAT | NO | `30` | ALTER | -| `max_staleness` (in Preview) | INTERVAL | NO | | ALTER | +| Parameter | Type | Required | Default | Change Monitoring Support | +|------------------------------|--------------|----------|---------|---------------------------| +| `enable_refresh` | `` | no | `true` | alter | +| `refresh_interval_minutes` | `` | no | `30` | alter | +| `max_staleness` (in Preview) | `` | no | `none` | alter | BigQuery supports [automatic refresh](https://cloud.google.com/bigquery/docs/materialized-views-manage#automatic_refresh) configuration for materialized views. By default, a materialized view will automatically refresh within 5 minutes of changes in the base table, but no more frequently than every 30 minutes. From 503253ef6a6b3ba5f6eb0586e6053bc26dcade6c Mon Sep 17 00:00:00 2001 From: Mike Alfare Date: Thu, 7 Dec 2023 12:33:30 -0500 Subject: [PATCH 065/165] update to use appropriate style guidelines --- .../resource-configs/snowflake-configs.md | 81 ++++++++++++++----- 1 file changed, 59 insertions(+), 22 deletions(-) diff --git a/website/docs/reference/resource-configs/snowflake-configs.md b/website/docs/reference/resource-configs/snowflake-configs.md index 900860ea287..c6ef5c4b339 100644 --- a/website/docs/reference/resource-configs/snowflake-configs.md +++ b/website/docs/reference/resource-configs/snowflake-configs.md @@ -355,44 +355,81 @@ of [materialized views](/docs/build/materializations#Materialized-View). In particular, dynamic tables have access to the `on_configuration_change` setting. Dynamic tables are supported with the following configuration parameters: -| Parameter | Type | Required | Default | Change Monitoring Support | Reference | -|---------------------------|----------|----------|-----------|---------------------------|----------------------------------------------| -| `on_configuration_change` | STRING | NO | `apply` | N/A | | -| `target_lag` | STRING | YES | | ALTER | [Target lag](#target-lag) | -| `snowflake_warehouse` | STRING | YES | | ALTER | [Warehouse](#configuring-virtual-warehouses) | +| Parameter | Type | Required | Default | Change Monitoring Support | +|----------------------------------------------------------|------------|----------|---------|---------------------------| +| `on_configuration_change` | `` | no | `apply` | n/a | +| [`target_lag`](#target-lag) | `` | yes | | alter | +| [`snowflake_warehouse`](#configuring-virtual-warehouses) | `` | yes | | alter | -#### Sample model file: + - -```sql -{{ config( - materialized='dynamic_table', - on_configuration_change='{ apply | continue | fail }', - target_lag='< { seconds | minutes | hours | days } | DOWNSTREAM>', - snowflake_warehouse='', -) }} + + + -select * from {{ ref('my_base_table') }} +```yaml +models: + [](/reference/resource-configs/resource-path): + [+](/reference/resource-configs/plus-prefix)[materialized](/reference/resource-configs/materialized): dynamic_table + [+](/reference/resource-configs/plus-prefix)on_configuration_change: apply | continue | fail + [+](/reference/resource-configs/plus-prefix)[target_lag](#target-lag): downstream | + [+](/reference/resource-configs/plus-prefix)[snowflake_warehouse](#configuring-virtual-warehouses): ``` -#### Sample project file: + - + + + + ```yaml +version: 2 + models: - path: - materialized: dynamic_table - on_configuration_change: '' - snowflake_warehouse: '' - target_lag: '< { seconds | minutes | hours | days } | DOWNSTREAM>' + - name: [] + config: + [materialized](/reference/resource-configs/materialized): dynamic_table + on_configuration_change: apply | continue | fail + [target_lag](#target-lag): downstream | + [snowflake_warehouse](#configuring-virtual-warehouses): ``` + + + + + + + +```jinja +{{ config( + materialized="dynamic_table", + on_configuration_change="apply" | "continue" | "fail", + target_lag="downstream" | " seconds | minutes | hours | days", + snowflake_warehouse="", +) }} +``` + + + + + + + Find more information about these parameters in the Snowflake docs: - [CREATE DYNAMIC TABLE](https://docs.snowflake.com/en/sql-reference/sql/create-dynamic-table) From ab2584c86a86052c84a1da4cda57ce8f391a0331 Mon Sep 17 00:00:00 2001 From: Mike Alfare Date: Thu, 7 Dec 2023 13:11:04 -0500 Subject: [PATCH 066/165] update to use appropriate style guidelines --- .../resource-configs/redshift-configs.md | 112 +++++++++++++----- 1 file changed, 85 insertions(+), 27 deletions(-) diff --git a/website/docs/reference/resource-configs/redshift-configs.md b/website/docs/reference/resource-configs/redshift-configs.md index 0e079453ec6..44b66b30005 100644 --- a/website/docs/reference/resource-configs/redshift-configs.md +++ b/website/docs/reference/resource-configs/redshift-configs.md @@ -114,36 +114,94 @@ models: The Redshift adapter supports [materialized views](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-overview.html) with the following configuration parameters: -| Parameter | Type | Required | Default | Change Monitoring Support | Reference | -|---------------------------|--------------|----------|------------------------|---------------------------|-------------------------------------------------| -| `on_configuration_change` | STRING | NO | `'apply'` | N/A | | -| `dist` | STRING | NO | `'EVEN'` | DROP/CREATE | [Sortkey / Distkey](#using-sortkey-and-distkey) | -| `sort` | LIST[STRING] | NO | | DROP/CREATE | [Sortkey / Distkey](#using-sortkey-and-distkey) | -| `sort_type` | STRING | NO | `'AUTO'` if no `sort` | DROP/CREATE | [Sortkey / Distkey](#using-sortkey-and-distkey) | -| | | | `'COMPOUND'` if `sort` | | | -| `auto_refresh` | BOOLEAN | NO | `False` | ALTER | [Auto refresh](#auto-refresh) | -| `backup` | BOOLEAN | HO | `True` | N/A | [Backup](#backup) | +| Parameter | Type | Required | Default | Change Monitoring Support | +|-------------------------------------------|--------------|----------|----------------------|---------------------------| +| `on_configuration_change` | `` | no | `apply` | n/a | +| [`dist`](#using-sortkey-and-distkey) | `` | no | `even` | drop/create | +| [`sort`](#using-sortkey-and-distkey) | `[]` | no | `none` | drop/create | +| [`sort_type`](#using-sortkey-and-distkey) | `` | no | `auto` if no `sort` | drop/create | +| | | | `compound` if `sort` | | +| [`auto_refresh`](#auto-refresh) | `` | no | `false` | alter | +| [`backup`](#backup) | `` | no | `true` | n/a | + + + + + -#### Sample model file: + - +```yaml +models: + [](/reference/resource-configs/resource-path): + [+](/reference/resource-configs/plus-prefix)[materialized](/reference/resource-configs/materialized): materialized_view + [+](/reference/resource-configs/plus-prefix)on_configuration_change: apply | continue | fail + [+](/reference/resource-configs/plus-prefix)[dist](#using-sortkey-and-distkey): all | auto | even | + [+](/reference/resource-configs/plus-prefix)[sort](#using-sortkey-and-distkey): | [] + [+](/reference/resource-configs/plus-prefix)[sort_type](#using-sortkey-and-distkey): auto | compound | interleaved + [+](/reference/resource-configs/plus-prefix)[auto_refresh](#auto-refresh): true | false + [+](/reference/resource-configs/plus-prefix)[backup](#backup): true | false +``` -```sql + + + + + + + + + +```yaml +version: 2 + +models: + - name: [] + config: + [materialized](/reference/resource-configs/materialized): materialized_view + on_configuration_change: apply | continue | fail + [dist](#using-sortkey-and-distkey): all | auto | even | + [sort](#using-sortkey-and-distkey): | [] + [sort_type](#using-sortkey-and-distkey): auto | compound | interleaved + [auto_refresh](#auto-refresh): true | false + [backup](#backup): true | false +``` + + + + + + + + + + +```jinja {{ config( - materialized='materialized_view', - on_configuration_change='{ apply | continue | fail }' - dist='{ ALL | AUTO | EVEN | }', - sort=['', ...], - sort_type='{ AUTO | COMPOUND | INTERLEAVED }' - auto_refresh=, - backup=, + materialized="materialized_view", + on_configuration_change="apply" | "continue" | "fail", + dist="all" | "auto" | "even" | "", + sort=[""], + sort_type="auto" | "compound" | "interleaved", + auto_refresh=true | false, + backup=true | false, ) }} - -select * from {{ ref('my_base_table') }} ``` + + + + Many of these parameters correspond to their table counterparts and have been linked above. The parameters unique to materialized views are the auto-refresh and backup functionality, which are covered below. @@ -151,9 +209,9 @@ Find more information about the [CREATE MATERIALIZED VIEW](https://docs.aws.amaz #### Auto-refresh -| Parameter | Type | Required | Default | Change Monitoring Support | -|----------------|---------|----------|---------|---------------------------| -| `auto_refresh` | BOOLEAN | NO | `False` | ALTER | +| Parameter | Type | Required | Default | Change Monitoring Support | +|----------------|-------------|----------|---------|---------------------------| +| `auto_refresh` | `` | no | `false` | alter | Redshift supports [automatic refresh](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-refresh.html#materialized-view-auto-refresh) configuration for materialized views. By default, a materialized view does not automatically refresh. @@ -163,9 +221,9 @@ Find more information about the [parameters](https://docs.aws.amazon.com/redshif #### Backup -| Parameter | Type | Required | Default | Change Monitoring Support | -|-----------|---------|----------|---------|---------------------------| -| `backup` | BOOLEAN | NO | `True` | N/A | +| Parameter | Type | Required | Default | Change Monitoring Support | +|-----------|-------------|----------|---------|---------------------------| +| `backup` | `` | no | `true` | n/a | Redshift supports [backup](https://docs.aws.amazon.com/redshift/latest/mgmt/working-with-snapshots.html) configuration of clusters at the object level. This parameter identifies if the materialized view should be backed up as part of the cluster snapshot. From 552b5393566aafe26163904d817f4cb4201f07f8 Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Thu, 7 Dec 2023 15:25:26 -0500 Subject: [PATCH 067/165] Update website/docs/docs/build/data-tests.md Co-authored-by: Grace Goheen <53586774+graciegoheen@users.noreply.github.com> --- website/docs/docs/build/data-tests.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/docs/build/data-tests.md b/website/docs/docs/build/data-tests.md index a5995759f2a..32a50dba800 100644 --- a/website/docs/docs/build/data-tests.md +++ b/website/docs/docs/build/data-tests.md @@ -24,7 +24,7 @@ Data tests return a set of failing records. Generic data tests (f.k.a. schema te Like almost everything in dbt, data tests are SQL queries. In particular, they are `select` statements that seek to grab "failing" records, ones that disprove your assertion. If you assert that a column is unique in a model, the test query selects for duplicates; if you assert that a column is never null, the test seeks after nulls. If the data test returns zero failing rows, it passes, and your assertion has been validated. There are two ways of defining data tests in dbt: -* A **singular** test is testing in its simplest form: If you can write a SQL query that returns failing rows, you can save that query in a `.sql` file within your [test directory](/reference/project-configs/test-paths). It's now a test, and it will be executed by the `dbt test` command. +* A **singular** data test is testing in its simplest form: If you can write a SQL query that returns failing rows, you can save that query in a `.sql` file within your [test directory](/reference/project-configs/test-paths). It's now a data test, and it will be executed by the `dbt test` command. * A **generic** test is a parameterized query that accepts arguments. The test query is defined in a special `test` block (like a [macro](jinja-macros)). Once defined, you can reference the generic test by name throughout your `.yml` files—define it on models, columns, sources, snapshots, and seeds. dbt ships with four generic tests built in, and we think you should use them! Defining data tests is a great way to confirm that your code is working correctly, and helps prevent regressions when your code changes. Because you can use them over and over again, making similar assertions with minor variations, generic data tests tend to be much more common—they should make up the bulk of your dbt testing suite. That said, both ways of defining data tests have their time and place. From 3f984083d6423b8aac18867a5767bae43082b95d Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Thu, 7 Dec 2023 15:51:06 -0500 Subject: [PATCH 068/165] Updating links --- .../blog/2022-10-19-polyglot-dbt-python-dataframes-and-sql.md | 2 +- website/blog/2023-01-24-aggregating-test-failures.md | 2 +- website/docs/guides/dbt-python-snowpark.md | 2 +- website/docs/reference/resource-configs/meta.md | 2 +- website/docs/reference/resource-configs/store_failures_as.md | 2 +- 5 files changed, 5 insertions(+), 5 deletions(-) diff --git a/website/blog/2022-10-19-polyglot-dbt-python-dataframes-and-sql.md b/website/blog/2022-10-19-polyglot-dbt-python-dataframes-and-sql.md index bab92000a16..9c04bd73a9a 100644 --- a/website/blog/2022-10-19-polyglot-dbt-python-dataframes-and-sql.md +++ b/website/blog/2022-10-19-polyglot-dbt-python-dataframes-and-sql.md @@ -135,7 +135,7 @@ This model tries to parse the raw string value into a Python datetime. When not During the build process, dbt will check if any of the values are null. This is using the built-in [`not_null`](https://docs.getdbt.com/docs/building-a-dbt-project/tests#generic-tests) test, which will generate and execute SQL in the data platform. -Our initial recommendation for testing Python models is to use [generic](https://docs.getdbt.com/docs/building-a-dbt-project/tests#generic-tests) and [singular](https://docs.getdbt.com/docs/building-a-dbt-project/tests#singular-tests) tests. +Our initial recommendation for testing Python models is to use [generic](https://docs.getdbt.com/docs/building-a-dbt-project/tests#generic-tests) and [singular](https://docs.getdbt.com/docs/building-a-dbt-project/tests#singular-data-tests) tests. ```yaml version: 2 diff --git a/website/blog/2023-01-24-aggregating-test-failures.md b/website/blog/2023-01-24-aggregating-test-failures.md index d82c202b376..2319da910a6 100644 --- a/website/blog/2023-01-24-aggregating-test-failures.md +++ b/website/blog/2023-01-24-aggregating-test-failures.md @@ -30,7 +30,7 @@ _It should be noted that this framework is for dbt v1.0+ on BigQuery. Small adap When we talk about high quality data tests, we aren’t just referencing high quality code, but rather the informational quality of our testing framework and their corresponding error messages. Originally, we theorized that any test that cannot be acted upon is a test that should not be implemented. Later, we realized there is a time and place for tests that should receive attention at a critical mass of failures. All we needed was a higher specificity system: tests should have an explicit severity ranking associated with them, equipped to filter out the noise of common, but low concern, failures. Each test should also mesh into established [RACI](https://project-management.com/understanding-responsibility-assignment-matrix-raci-matrix/) guidelines that state which groups tackle what failures, and what constitutes a critical mass. -To ensure that tests are always acted upon, we implement tests differently depending on the user groups that must act when a test fails. This led us to have two main classes of tests — Data Integrity Tests (called [Generic Tests](https://docs.getdbt.com/docs/build/tests) in dbt docs) and Context Driven Tests (called [Singular Tests](https://docs.getdbt.com/docs/build/tests#singular-tests) in dbt docs), with varying levels of severity across both test classes. +To ensure that tests are always acted upon, we implement tests differently depending on the user groups that must act when a test fails. This led us to have two main classes of tests — Data Integrity Tests (called [Generic Tests](https://docs.getdbt.com/docs/build/tests) in dbt docs) and Context Driven Tests (called [Singular Tests](https://docs.getdbt.com/docs/build/tests#singular-data-tests) in dbt docs), with varying levels of severity across both test classes. Data Integrity tests (Generic Tests)  are simple — they’re tests akin to a uniqueness check or not null constraint. These tests are usually actionable by the data platform team rather than subject matter experts. We define Data Integrity tests in our YAML files, similar to how they are [outlined by dbt’s documentation on generic tests](https://docs.getdbt.com/docs/build/tests). They look something like this — diff --git a/website/docs/guides/dbt-python-snowpark.md b/website/docs/guides/dbt-python-snowpark.md index e2f314ada55..fa39ed6d423 100644 --- a/website/docs/guides/dbt-python-snowpark.md +++ b/website/docs/guides/dbt-python-snowpark.md @@ -1720,7 +1720,7 @@ We test data models for mainly two reasons: - Ensure that our source data is clean on ingestion before we start data modeling/transformation (aka avoid garbage in, garbage out problem). - Make sure we don’t introduce bugs in the transformation code we wrote (stop ourselves from creating bad joins/fanouts). -Testing in dbt comes in two flavors: [generic](/docs/build/data-tests#generic-tests) and [singular](/docs/build/data-tests#singular-tests). +Testing in dbt comes in two flavors: [generic](/docs/build/data-tests#generic-tests) and [singular](/docs/build/data-tests#singular-data-tests). You define them in a test block (similar to a macro) and once defined, you can reference them by name in your `.yml` files (applying them to models, columns, sources, snapshots, and seeds). diff --git a/website/docs/reference/resource-configs/meta.md b/website/docs/reference/resource-configs/meta.md index 470bac35ba7..6a69536bb2a 100644 --- a/website/docs/reference/resource-configs/meta.md +++ b/website/docs/reference/resource-configs/meta.md @@ -127,7 +127,7 @@ See [configs and properties](/reference/configs-and-properties) for details. -You can't add YAML `meta` configs for [generic tests](/docs/build/data-tests#generic-tests). However, you can add `meta` properties to [singular tests](/docs/build/data-tests#singular-tests) using `config()` at the top of the test file. +You can't add YAML `meta` configs for [generic tests](/docs/build/data-tests#generic-tests). However, you can add `meta` properties to [singular tests](/docs/build/data-tests#singular-data-tests) using `config()` at the top of the test file. diff --git a/website/docs/reference/resource-configs/store_failures_as.md b/website/docs/reference/resource-configs/store_failures_as.md index fd561176008..52ec2e3bd3a 100644 --- a/website/docs/reference/resource-configs/store_failures_as.md +++ b/website/docs/reference/resource-configs/store_failures_as.md @@ -17,7 +17,7 @@ You can configure it in all the same places as `store_failures`, including singu #### Singular test -[Singular test](https://docs.getdbt.com/docs/build/tests#singular-tests) in `tests/singular/check_something.sql` file +[Singular test](https://docs.getdbt.com/docs/build/tests#singular-data-tests) in `tests/singular/check_something.sql` file ```sql {{ config(store_failures_as="table") }} From 7f758f499a464c32418d8f6d2b8601d3e9321761 Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Thu, 7 Dec 2023 16:02:42 -0500 Subject: [PATCH 069/165] updating links --- website/blog/2022-04-19-complex-deduplication.md | 2 +- .../blog/2022-10-19-polyglot-dbt-python-dataframes-and-sql.md | 4 ++-- website/blog/2023-07-03-data-vault-2-0-with-dbt-cloud.md | 2 +- website/docs/guides/dbt-python-snowpark.md | 2 +- website/docs/reference/resource-configs/meta.md | 2 +- website/docs/reference/resource-configs/store_failures_as.md | 2 +- website/docs/reference/resource-properties/data-tests.md | 2 +- 7 files changed, 8 insertions(+), 8 deletions(-) diff --git a/website/blog/2022-04-19-complex-deduplication.md b/website/blog/2022-04-19-complex-deduplication.md index f8cece85b61..f33e6a8fe35 100644 --- a/website/blog/2022-04-19-complex-deduplication.md +++ b/website/blog/2022-04-19-complex-deduplication.md @@ -146,7 +146,7 @@ select * from filter_real_diffs > *What happens in this step? You check your data because you are thorough!* -Good thing dbt has already built this for you. Add a [unique test](/docs/build/data-tests#generic-tests) to your YAML model block for your `grain_id` in this de-duped staging model, and give it a dbt test! +Good thing dbt has already built this for you. Add a [unique test](/docs/build/data-tests#generic-data-tests) to your YAML model block for your `grain_id` in this de-duped staging model, and give it a dbt test! ```yaml models: diff --git a/website/blog/2022-10-19-polyglot-dbt-python-dataframes-and-sql.md b/website/blog/2022-10-19-polyglot-dbt-python-dataframes-and-sql.md index 9c04bd73a9a..694f6ddc105 100644 --- a/website/blog/2022-10-19-polyglot-dbt-python-dataframes-and-sql.md +++ b/website/blog/2022-10-19-polyglot-dbt-python-dataframes-and-sql.md @@ -133,9 +133,9 @@ This model tries to parse the raw string value into a Python datetime. When not #### Testing the result -During the build process, dbt will check if any of the values are null. This is using the built-in [`not_null`](https://docs.getdbt.com/docs/building-a-dbt-project/tests#generic-tests) test, which will generate and execute SQL in the data platform. +During the build process, dbt will check if any of the values are null. This is using the built-in [`not_null`](https://docs.getdbt.com/docs/building-a-dbt-project/tests#generic-data-tests) test, which will generate and execute SQL in the data platform. -Our initial recommendation for testing Python models is to use [generic](https://docs.getdbt.com/docs/building-a-dbt-project/tests#generic-tests) and [singular](https://docs.getdbt.com/docs/building-a-dbt-project/tests#singular-data-tests) tests. +Our initial recommendation for testing Python models is to use [generic](https://docs.getdbt.com/docs/building-a-dbt-project/tests#generic-data-tests) and [singular](https://docs.getdbt.com/docs/building-a-dbt-project/tests#singular-data-tests) tests. ```yaml version: 2 diff --git a/website/blog/2023-07-03-data-vault-2-0-with-dbt-cloud.md b/website/blog/2023-07-03-data-vault-2-0-with-dbt-cloud.md index 2a4879ac98d..6b1012a5320 100644 --- a/website/blog/2023-07-03-data-vault-2-0-with-dbt-cloud.md +++ b/website/blog/2023-07-03-data-vault-2-0-with-dbt-cloud.md @@ -143,7 +143,7 @@ To help you get started, [we have created a template GitHub project](https://git ### Entity Relation Diagrams (ERDs) and dbt -Data lineage is dbt's strength, but sometimes it's not enough to help you to understand the relationships between Data Vault components like a classic ERD would. There are a few open source packages to visualize the entities in your Data Vault built with dbt. I recommend checking out the [dbterd](https://dbterd.datnguyen.de/1.2/index.html) which turns your [dbt relationship data quality checks](https://docs.getdbt.com/docs/build/tests#generic-tests) into an ERD. +Data lineage is dbt's strength, but sometimes it's not enough to help you to understand the relationships between Data Vault components like a classic ERD would. There are a few open source packages to visualize the entities in your Data Vault built with dbt. I recommend checking out the [dbterd](https://dbterd.datnguyen.de/1.2/index.html) which turns your [dbt relationship data quality checks](https://docs.getdbt.com/docs/build/tests#generic-data-tests) into an ERD. ## Summary diff --git a/website/docs/guides/dbt-python-snowpark.md b/website/docs/guides/dbt-python-snowpark.md index fa39ed6d423..110445344e9 100644 --- a/website/docs/guides/dbt-python-snowpark.md +++ b/website/docs/guides/dbt-python-snowpark.md @@ -1720,7 +1720,7 @@ We test data models for mainly two reasons: - Ensure that our source data is clean on ingestion before we start data modeling/transformation (aka avoid garbage in, garbage out problem). - Make sure we don’t introduce bugs in the transformation code we wrote (stop ourselves from creating bad joins/fanouts). -Testing in dbt comes in two flavors: [generic](/docs/build/data-tests#generic-tests) and [singular](/docs/build/data-tests#singular-data-tests). +Testing in dbt comes in two flavors: [generic](/docs/build/data-tests#generic-data-tests) and [singular](/docs/build/data-tests#singular-data-tests). You define them in a test block (similar to a macro) and once defined, you can reference them by name in your `.yml` files (applying them to models, columns, sources, snapshots, and seeds). diff --git a/website/docs/reference/resource-configs/meta.md b/website/docs/reference/resource-configs/meta.md index 6a69536bb2a..bd9755548ab 100644 --- a/website/docs/reference/resource-configs/meta.md +++ b/website/docs/reference/resource-configs/meta.md @@ -127,7 +127,7 @@ See [configs and properties](/reference/configs-and-properties) for details. -You can't add YAML `meta` configs for [generic tests](/docs/build/data-tests#generic-tests). However, you can add `meta` properties to [singular tests](/docs/build/data-tests#singular-data-tests) using `config()` at the top of the test file. +You can't add YAML `meta` configs for [generic tests](/docs/build/data-tests#generic-data-tests). However, you can add `meta` properties to [singular tests](/docs/build/data-tests#singular-data-tests) using `config()` at the top of the test file. diff --git a/website/docs/reference/resource-configs/store_failures_as.md b/website/docs/reference/resource-configs/store_failures_as.md index 52ec2e3bd3a..e12c00c7fba 100644 --- a/website/docs/reference/resource-configs/store_failures_as.md +++ b/website/docs/reference/resource-configs/store_failures_as.md @@ -29,7 +29,7 @@ where 1=0 #### Generic test -[Generic tests](https://docs.getdbt.com/docs/build/tests#generic-tests) in `models/_models.yml` file +[Generic tests](https://docs.getdbt.com/docs/build/tests#generic-data-tests) in `models/_models.yml` file ```yaml models: diff --git a/website/docs/reference/resource-properties/data-tests.md b/website/docs/reference/resource-properties/data-tests.md index 96ee322efc0..7b658acf949 100644 --- a/website/docs/reference/resource-properties/data-tests.md +++ b/website/docs/reference/resource-properties/data-tests.md @@ -156,7 +156,7 @@ This feature is not implemented for analyses. ## Description -The data `tests` property defines assertions about a column, , or . The property contains a list of [generic tests](/docs/build/data-tests#generic-tests), referenced by name, which can include the four built-in generic tests available in dbt. For example, you can add tests that ensure a column contains no duplicates and zero null values. Any arguments or [configurations](/reference/data-test-configs) passed to those tests should be nested below the test name. +The data `tests` property defines assertions about a column, , or . The property contains a list of [generic tests](/docs/build/data-tests#generic-data-tests), referenced by name, which can include the four built-in generic tests available in dbt. For example, you can add tests that ensure a column contains no duplicates and zero null values. Any arguments or [configurations](/reference/data-test-configs) passed to those tests should be nested below the test name. Once these tests are defined, you can validate their correctness by running `dbt test`. From 1ba9c68e0f9eb90d6022890509f4d20e6d9c15f5 Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Thu, 7 Dec 2023 16:07:26 -0500 Subject: [PATCH 070/165] Apply suggestions from code review Co-authored-by: Grace Goheen <53586774+graciegoheen@users.noreply.github.com> --- website/docs/docs/build/data-tests.md | 16 ++++++++-------- website/docs/docs/build/projects.md | 2 +- website/docs/docs/build/sources.md | 2 +- .../docs/collaborate/govern/model-contracts.md | 4 ++-- .../docs/faqs/Models/specifying-column-types.md | 2 +- website/docs/faqs/Tests/available-tests.md | 2 +- 6 files changed, 14 insertions(+), 14 deletions(-) diff --git a/website/docs/docs/build/data-tests.md b/website/docs/docs/build/data-tests.md index 32a50dba800..d981d7e272d 100644 --- a/website/docs/docs/build/data-tests.md +++ b/website/docs/docs/build/data-tests.md @@ -25,9 +25,9 @@ Like almost everything in dbt, data tests are SQL queries. In particular, they a There are two ways of defining data tests in dbt: * A **singular** data test is testing in its simplest form: If you can write a SQL query that returns failing rows, you can save that query in a `.sql` file within your [test directory](/reference/project-configs/test-paths). It's now a data test, and it will be executed by the `dbt test` command. -* A **generic** test is a parameterized query that accepts arguments. The test query is defined in a special `test` block (like a [macro](jinja-macros)). Once defined, you can reference the generic test by name throughout your `.yml` files—define it on models, columns, sources, snapshots, and seeds. dbt ships with four generic tests built in, and we think you should use them! +* A **generic** data test is a parameterized query that accepts arguments. The test query is defined in a special `test` block (like a [macro](jinja-macros)). Once defined, you can reference the generic test by name throughout your `.yml` files—define it on models, columns, sources, snapshots, and seeds. dbt ships with four generic data tests built in, and we think you should use them! -Defining data tests is a great way to confirm that your code is working correctly, and helps prevent regressions when your code changes. Because you can use them over and over again, making similar assertions with minor variations, generic data tests tend to be much more common—they should make up the bulk of your dbt testing suite. That said, both ways of defining data tests have their time and place. +Defining data tests is a great way to confirm that your outputs and inputs are as expected, and helps prevent regressions when your code changes. Because you can use them over and over again, making similar assertions with minor variations, generic data tests tend to be much more common—they should make up the bulk of your dbt data testing suite. That said, both ways of defining data tests have their time and place. :::tip Creating your first data tests If you're new to dbt, we recommend that you check out our [quickstart guide](/guides) to build your first dbt project with models and tests. @@ -35,9 +35,9 @@ If you're new to dbt, we recommend that you check out our [quickstart guide](/gu ## Singular data tests -The simplest way to define a data test is by writing the exact SQL that will return failing records. We call these "singular" tests, because they're one-off assertions usable for a single purpose. +The simplest way to define a data test is by writing the exact SQL that will return failing records. We call these "singular" data tests, because they're one-off assertions usable for a single purpose. -These tests are defined in `.sql` files, typically in your `tests` directory (as defined by your [`test-paths` config](/reference/project-configs/test-paths)). You can use Jinja (including `ref` and `source`) in the test definition, just like you can when creating models. Each `.sql` file contains one `select` statement, and it defines one test: +These tests are defined in `.sql` files, typically in your `tests` directory (as defined by your [`test-paths` config](/reference/project-configs/test-paths)). You can use Jinja (including `ref` and `source`) in the test definition, just like you can when creating models. Each `.sql` file contains one `select` statement, and it defines one data test: @@ -58,8 +58,8 @@ The name of this test is the name of the file: `assert_total_payment_amount_is_p Singular data tests are easy to write—so easy that you may find yourself writing the same basic structure over and over, only changing the name of a column or model. By that point, the test isn't so singular! In that case, we recommend... -## Generic tests -Certain data tests are generic: they can be reused over and over again. A generic test is defined in a `test` block, which contains a parametrized query and accepts arguments. It might look like: +## Generic data tests +Certain data tests are generic: they can be reused over and over again. A generic data test is defined in a `test` block, which contains a parametrized query and accepts arguments. It might look like: ```sql {% test not_null(model, column_name) %} @@ -108,11 +108,11 @@ In plain English, these data tests translate to: Behind the scenes, dbt constructs a `select` query for each data test, using the parametrized query from the generic test block. These queries return the rows where your assertion is _not_ true; if the test returns zero rows, your assertion passes. -You can find more information about these tests, and additional configurations (including [`severity`](/reference/resource-configs/severity) and [`tags`](/reference/resource-configs/tags)) in the [reference section](/reference/resource-properties/data-tests). +You can find more information about these data tests, and additional configurations (including [`severity`](/reference/resource-configs/severity) and [`tags`](/reference/resource-configs/tags)) in the [reference section](/reference/resource-properties/data-tests). ### More generic data tests -Those four tests are enough to get you started. You'll quickly find you want to use a wider variety of tests—a good thing! You can also install generic tests from a package, or write your own, to use (and reuse) across your dbt project. Check out the [guide on custom generic tests](/best-practices/writing-custom-generic-tests) for more information. +Those four tests are enough to get you started. You'll quickly find you want to use a wider variety of tests—a good thing! You can also install generic data tests from a package, or write your own, to use (and reuse) across your dbt project. Check out the [guide on custom generic tests](/best-practices/writing-custom-generic-tests) for more information. :::info There are generic tests defined in some open source packages, such as [dbt-utils](https://hub.getdbt.com/dbt-labs/dbt_utils/latest/) and [dbt-expectations](https://hub.getdbt.com/calogica/dbt_expectations/latest/) — skip ahead to the docs on [packages](/docs/build/packages) to learn more! diff --git a/website/docs/docs/build/projects.md b/website/docs/docs/build/projects.md index d268ec09920..c5e08177dee 100644 --- a/website/docs/docs/build/projects.md +++ b/website/docs/docs/build/projects.md @@ -14,7 +14,7 @@ At a minimum, all a project needs is the `dbt_project.yml` project configuration | [models](/docs/build/models) | Each model lives in a single file and contains logic that either transforms raw data into a dataset that is ready for analytics or, more often, is an intermediate step in such a transformation. | | [snapshots](/docs/build/snapshots) | A way to capture the state of your mutable tables so you can refer to it later. | | [seeds](/docs/build/seeds) | CSV files with static data that you can load into your data platform with dbt. | -| [tests](/docs/build/data-tests) | SQL queries that you can write to test the models and resources in your project. | +| [data tests](/docs/build/data-tests) | SQL queries that you can write to test the models and resources in your project. | | [macros](/docs/build/jinja-macros) | Blocks of code that you can reuse multiple times. | | [docs](/docs/collaborate/documentation) | Docs for your project that you can build. | | [sources](/docs/build/sources) | A way to name and describe the data loaded into your warehouse by your Extract and Load tools. | diff --git a/website/docs/docs/build/sources.md b/website/docs/docs/build/sources.md index ae6024a3e58..466bcedc688 100644 --- a/website/docs/docs/build/sources.md +++ b/website/docs/docs/build/sources.md @@ -88,7 +88,7 @@ Using the `{{ source () }}` function also creates a dependency between the model ### Testing and documenting sources You can also: -- Add tests to sources +- Add data tests to sources - Add descriptions to sources, that get rendered as part of your documentation site These should be familiar concepts if you've already added tests and descriptions to your models (if not check out the guides on [testing](/docs/build/data-tests) and [documentation](/docs/collaborate/documentation)). diff --git a/website/docs/docs/collaborate/govern/model-contracts.md b/website/docs/docs/collaborate/govern/model-contracts.md index a083c3e6d2b..8e7598f8e3b 100644 --- a/website/docs/docs/collaborate/govern/model-contracts.md +++ b/website/docs/docs/collaborate/govern/model-contracts.md @@ -183,9 +183,9 @@ Any model meeting the criteria described above _can_ define a contract. We recom A model's contract defines the **shape** of the returned dataset. If the model's logic or input data doesn't conform to that shape, the model does not build. -[Tests](/docs/build/data-tests) are a more flexible mechanism for validating the content of your model _after_ it's built. So long as you can write the query, you can run the test. Tests are more configurable, such as with [custom severity thresholds](/reference/resource-configs/severity). They are easier to debug after finding failures, because you can query the already-built model, or [store the failing records in the data warehouse](/reference/resource-configs/store_failures). +[Data Tests](/docs/build/data-tests) are a more flexible mechanism for validating the content of your model _after_ it's built. So long as you can write the query, you can run the data test. Data tests are more configurable, such as with [custom severity thresholds](/reference/resource-configs/severity). They are easier to debug after finding failures, because you can query the already-built model, or [store the failing records in the data warehouse](/reference/resource-configs/store_failures). -In some cases, you can replace a test with its equivalent constraint. This has the advantage of guaranteeing the validation at build time, and it probably requires less compute (cost) in your data platform. The prerequisites for replacing a test with a constraint are: +In some cases, you can replace a data test with its equivalent constraint. This has the advantage of guaranteeing the validation at build time, and it probably requires less compute (cost) in your data platform. The prerequisites for replacing a data test with a constraint are: - Making sure that your data platform can support and enforce the constraint that you need. Most platforms only enforce `not_null`. - Materializing your model as `table` or `incremental` (**not** `view` or `ephemeral`). - Defining a full contract for this model by specifying the `name` and `data_type` of each column. diff --git a/website/docs/faqs/Models/specifying-column-types.md b/website/docs/faqs/Models/specifying-column-types.md index ff29085f160..904c616d89a 100644 --- a/website/docs/faqs/Models/specifying-column-types.md +++ b/website/docs/faqs/Models/specifying-column-types.md @@ -38,6 +38,6 @@ So long as your model queries return the correct column type, the table you crea To define additional column options: -* Rather than enforcing uniqueness and not-null constraints on your column, use dbt's [testing](/docs/build/data-tests) functionality to check that your assertions about your model hold true. +* Rather than enforcing uniqueness and not-null constraints on your column, use dbt's [data testing](/docs/build/data-tests) functionality to check that your assertions about your model hold true. * Rather than creating default values for a column, use SQL to express defaults (e.g. `coalesce(updated_at, current_timestamp()) as updated_at`) * In edge-cases where you _do_ need to alter a column (e.g. column-level encoding on Redshift), consider implementing this via a [post-hook](/reference/resource-configs/pre-hook-post-hook). diff --git a/website/docs/faqs/Tests/available-tests.md b/website/docs/faqs/Tests/available-tests.md index 225331d2256..2b5fd3ff55c 100644 --- a/website/docs/faqs/Tests/available-tests.md +++ b/website/docs/faqs/Tests/available-tests.md @@ -12,6 +12,6 @@ Out of the box, dbt ships with the following tests: * `accepted_values` * `relationships` (i.e. referential integrity) -You can also write your own [custom schema tests](/docs/build/data-tests). +You can also write your own [custom schema data tests](/docs/build/data-tests). Some additional custom schema tests have been open-sourced in the [dbt-utils package](https://github.com/dbt-labs/dbt-utils/tree/0.2.4/#schema-tests), check out the docs on [packages](/docs/build/packages) to learn how to make these tests available in your project. From f967d2db344309dc1fd37962f45040adea651dd2 Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Thu, 7 Dec 2023 16:13:55 -0500 Subject: [PATCH 071/165] Apply suggestions from code review Co-authored-by: Grace Goheen <53586774+graciegoheen@users.noreply.github.com> --- website/docs/reference/configs-and-properties.md | 4 ++-- website/docs/reference/model-properties.md | 8 ++++---- website/docs/reference/resource-configs/alias.md | 2 +- website/docs/reference/resource-configs/database.md | 2 +- .../docs/reference/resource-configs/store_failures_as.md | 4 ++-- website/docs/reference/resource-properties/data-tests.md | 4 ++-- website/docs/terms/data-wrangling.md | 2 +- 7 files changed, 13 insertions(+), 13 deletions(-) diff --git a/website/docs/reference/configs-and-properties.md b/website/docs/reference/configs-and-properties.md index c96fe7be299..9464faf719d 100644 --- a/website/docs/reference/configs-and-properties.md +++ b/website/docs/reference/configs-and-properties.md @@ -11,7 +11,7 @@ A rule of thumb: properties declare things _about_ your project resources; confi For example, you can use resource **properties** to: * Describe models, snapshots, seed files, and their columns -* Assert "truths" about a model, in the form of [tests](/docs/build/data-tests), e.g. "this `id` column is unique" +* Assert "truths" about a model, in the form of [data tests](/docs/build/data-tests), e.g. "this `id` column is unique" * Define pointers to existing tables that contain raw data, in the form of [sources](/docs/build/sources), and assert the expected "freshness" of this raw data * Define official downstream uses of your data models, in the form of [exposures](/docs/build/exposures) @@ -33,7 +33,7 @@ Depending on the resource type, configurations can be defined: dbt prioritizes configurations in order of specificity, from most specificity to least specificity. This generally follows the order above: an in-file `config()` block --> properties defined in a `.yml` file --> config defined in the project file. -Note - Generic tests work a little differently when it comes to specificity. See [test configs](/reference/data-test-configs). +Note - Generic data tests work a little differently when it comes to specificity. See [test configs](/reference/data-test-configs). Within the project file, configurations are also applied hierarchically. The most specific config always "wins": In the project file, configurations applied to a `marketing` subdirectory will take precedence over configurations applied to the entire `jaffle_shop` project. To apply a configuration to a model, or directory of models, define the resource path as nested dictionary keys. diff --git a/website/docs/reference/model-properties.md b/website/docs/reference/model-properties.md index a384307678f..65f9307b5b3 100644 --- a/website/docs/reference/model-properties.md +++ b/website/docs/reference/model-properties.md @@ -25,7 +25,7 @@ models: - [tests](/reference/resource-properties/data-tests): - - - ... # declare additional tests + - ... # declare additional data tests [columns](/reference/resource-properties/columns): - name: # required [description](/reference/resource-properties/description): @@ -35,7 +35,7 @@ models: - [tests](/reference/resource-properties/data-tests): - - - ... # declare additional tests + - ... # declare additional data tests [tags](/reference/resource-configs/tags): [] - name: ... # declare properties of additional columns @@ -53,7 +53,7 @@ models: [](/reference/model-configs): [tests](/reference/resource-properties/data-tests): - - - ... # declare additional tests + - ... # declare additional data tests columns: # include/exclude columns from the top-level model properties - [include](/reference/resource-properties/include-exclude): @@ -65,7 +65,7 @@ models: - [tests](/reference/resource-properties/data-tests): - - - ... # declare additional tests + - ... # declare additional data tests [tags](/reference/resource-configs/tags): [] - v: ... # declare additional versions diff --git a/website/docs/reference/resource-configs/alias.md b/website/docs/reference/resource-configs/alias.md index fbedb4597e6..e1d3ae41f8b 100644 --- a/website/docs/reference/resource-configs/alias.md +++ b/website/docs/reference/resource-configs/alias.md @@ -112,7 +112,7 @@ When using `--store-failures`, this would return the name `analytics.finance.ord ## Definition -Optionally specify a custom alias for a [model](/docs/build/models), [tests](/docs/build/data-tests), [snapshots](/docs/build/snapshots), or [seed](/docs/build/seeds). +Optionally specify a custom alias for a [model](/docs/build/models), [data test](/docs/build/data-tests), [snapshot](/docs/build/snapshots), or [seed](/docs/build/seeds). When dbt creates a relation (/) in a database, it creates it as: `{{ database }}.{{ schema }}.{{ identifier }}`, e.g. `analytics.finance.payments` diff --git a/website/docs/reference/resource-configs/database.md b/website/docs/reference/resource-configs/database.md index 82c7b2cca92..19c9eca272d 100644 --- a/website/docs/reference/resource-configs/database.md +++ b/website/docs/reference/resource-configs/database.md @@ -70,7 +70,7 @@ This would result in the generated relation being located in the `reporting` dat ## Definition -Optionally specify a custom database for a [model](/docs/build/sql-models), [seed](/docs/build/seeds), or [tests](/docs/build/data-tests). (To specify a database for a [snapshot](/docs/build/snapshots), use the [`target_database` config](/reference/resource-configs/target_database)). +Optionally specify a custom database for a [model](/docs/build/sql-models), [seed](/docs/build/seeds), or [data test](/docs/build/data-tests). (To specify a database for a [snapshot](/docs/build/snapshots), use the [`target_database` config](/reference/resource-configs/target_database)). When dbt creates a relation (/) in a database, it creates it as: `{{ database }}.{{ schema }}.{{ identifier }}`, e.g. `analytics.finance.payments` diff --git a/website/docs/reference/resource-configs/store_failures_as.md b/website/docs/reference/resource-configs/store_failures_as.md index e12c00c7fba..08ae10e5309 100644 --- a/website/docs/reference/resource-configs/store_failures_as.md +++ b/website/docs/reference/resource-configs/store_failures_as.md @@ -70,7 +70,7 @@ As with most other configurations, `store_failures_as` is "clobbered" when appli Additional resources: -- [Test configurations](/reference/data-test-configs#related-documentation) -- [Test-specific configurations](/reference/data-test-configs#test-specific-configurations) +- [Data test configurations](/reference/data-test-configs#related-documentation) +- [Data test-specific configurations](/reference/data-test-configs#test-specific-configurations) - [Configuring directories of models in dbt_project.yml](/reference/model-configs#configuring-directories-of-models-in-dbt_projectyml) - [Config inheritance](/reference/configs-and-properties#config-inheritance) \ No newline at end of file diff --git a/website/docs/reference/resource-properties/data-tests.md b/website/docs/reference/resource-properties/data-tests.md index 7b658acf949..ce557ebeb4f 100644 --- a/website/docs/reference/resource-properties/data-tests.md +++ b/website/docs/reference/resource-properties/data-tests.md @@ -152,7 +152,7 @@ This feature is not implemented for analyses. ## Related documentation -* [Testing guide](/docs/build/data-tests) +* [Data testing guide](/docs/build/data-tests) ## Description @@ -262,7 +262,7 @@ The `to` argument accepts a [Relation](/reference/dbt-classes#relation) – this ## Additional examples ### Test an expression -Some data tests require multiple columns, so it doesn't make sense to nest them under the `columns:` key. In this case, you can apply the test to the model (or source, seed, or snapshot) instead: +Some data tests require multiple columns, so it doesn't make sense to nest them under the `columns:` key. In this case, you can apply the data test to the model (or source, seed, or snapshot) instead: diff --git a/website/docs/terms/data-wrangling.md b/website/docs/terms/data-wrangling.md index 2fbb8d41942..e1aabdea8bd 100644 --- a/website/docs/terms/data-wrangling.md +++ b/website/docs/terms/data-wrangling.md @@ -150,7 +150,7 @@ For nested data types such as JSON, you’ll want to check out the JSON parsing ### Validating -dbt offers [generic tests](/docs/build/data-tests#more-generic-tests) in every dbt project that allows you to validate accepted, unique, and null values. They also allow you to validate the relationships between tables and that the primary key is unique. +dbt offers [generic data tests](/docs/build/data-tests#more-generic-tests) in every dbt project that allows you to validate accepted, unique, and null values. They also allow you to validate the relationships between tables and that the primary key is unique. If you can’t find what you need with the generic tests, you can download an additional dbt testing package called [dbt_expectations](https://hub.getdbt.com/calogica/dbt_expectations/0.1.2/) that dives even deeper into how you can test the values in your columns. This package has useful data tests like `expect_column_values_to_be_in_type_list`, `expect_column_values_to_be_between`, and `expect_column_value_lengths_to_equal`. From 428d05e562808ff9d13bad1abd2665061794821f Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Thu, 7 Dec 2023 19:00:59 -0500 Subject: [PATCH 072/165] #custon --- website/docs/reference/resource-configs/store_failures_as.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/reference/resource-configs/store_failures_as.md b/website/docs/reference/resource-configs/store_failures_as.md index e12c00c7fba..e9ca1ce4c5b 100644 --- a/website/docs/reference/resource-configs/store_failures_as.md +++ b/website/docs/reference/resource-configs/store_failures_as.md @@ -71,6 +71,6 @@ As with most other configurations, `store_failures_as` is "clobbered" when appli Additional resources: - [Test configurations](/reference/data-test-configs#related-documentation) -- [Test-specific configurations](/reference/data-test-configs#test-specific-configurations) +- [Test-specific configurations](/reference/data-test-configs#test-data-specific-configurations) - [Configuring directories of models in dbt_project.yml](/reference/model-configs#configuring-directories-of-models-in-dbt_projectyml) - [Config inheritance](/reference/configs-and-properties#config-inheritance) \ No newline at end of file From b8e3a12b3baac6c5ac3312a06dd04d431c4f2386 Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Thu, 7 Dec 2023 19:05:00 -0500 Subject: [PATCH 073/165] Fixin links --- website/docs/terms/data-wrangling.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/terms/data-wrangling.md b/website/docs/terms/data-wrangling.md index e1aabdea8bd..46a14a25949 100644 --- a/website/docs/terms/data-wrangling.md +++ b/website/docs/terms/data-wrangling.md @@ -150,7 +150,7 @@ For nested data types such as JSON, you’ll want to check out the JSON parsing ### Validating -dbt offers [generic data tests](/docs/build/data-tests#more-generic-tests) in every dbt project that allows you to validate accepted, unique, and null values. They also allow you to validate the relationships between tables and that the primary key is unique. +dbt offers [generic data tests](/docs/build/data-tests#more-generic-data-tests) in every dbt project that allows you to validate accepted, unique, and null values. They also allow you to validate the relationships between tables and that the primary key is unique. If you can’t find what you need with the generic tests, you can download an additional dbt testing package called [dbt_expectations](https://hub.getdbt.com/calogica/dbt_expectations/0.1.2/) that dives even deeper into how you can test the values in your columns. This package has useful data tests like `expect_column_values_to_be_in_type_list`, `expect_column_values_to_be_between`, and `expect_column_value_lengths_to_equal`. From c5858e6038496449c123bb1243a5209c3ca6e821 Mon Sep 17 00:00:00 2001 From: Tania <92768464+Tonayya@users.noreply.github.com> Date: Fri, 8 Dec 2023 13:56:43 +1100 Subject: [PATCH 074/165] Update deploy-jobs.md Added some examples where we are using the L expression to specify the last day of the month. Relevant conversation can be found in Slack [here](https://dbt-labs.slack.com/archives/C04KKUHLT32/p1702002328874979). --- website/docs/docs/deploy/deploy-jobs.md | 17 ++++++++++++----- 1 file changed, 12 insertions(+), 5 deletions(-) diff --git a/website/docs/docs/deploy/deploy-jobs.md b/website/docs/docs/deploy/deploy-jobs.md index e43020bf66e..cb62de00e7e 100644 --- a/website/docs/docs/deploy/deploy-jobs.md +++ b/website/docs/docs/deploy/deploy-jobs.md @@ -87,12 +87,19 @@ Use tools such as [crontab.guru](https://crontab.guru/) to generate the correct Refer to the following example snippets: -- `0 * * * *`: Every hour, at minute 0 -- `*/5 * * * *`: Every 5 minutes -- `5 4 * * *`: At exactly 4:05 AM UTC -- `30 */4 * * *`: At minute 30 past every 4th hour (e.g. 4:30AM, 8:30AM, 12:30PM, etc., all UTC) -- `0 0 */2 * *`: At midnight UTC every other day +- `0 * * * *`: Every hour, at minute 0. +- `*/5 * * * *`: Every 5 minutes. +- `5 4 * * *`: At exactly 4:05 AM UTC. +- `30 */4 * * *`: At minute 30 past every 4th hour (e.g. 4:30AM, 8:30AM, 12:30PM, etc., all UTC). +- `0 0 */2 * *`: At midnight UTC every other day. - `0 0 * * 1`: At midnight UTC every Monday. +- `0 0 L * *`: At 12:00 AM, on the last day of the month. +- `0 0 L 1,2,3,4,5,6,8,9,10,11,12 *`: At 12:00 AM, on the last day of the month, only in January, February, March, April, May, June, August, September, October, November, and December. +- `0 0 L 7 *`: At 12:00 AM, on the last day of the month, only in July. +- `0 0 L * FRI,SAT`: At 12:00 AM, on the last day of the month, and on Friday and Saturday. +- `0 12 L * *`: At 12:00 PM, on the last day of the month. +- `0 7 L * 5`: At 07:00 AM, on the last day of the month, and on Friday. +- `30 14 L * *`: At 02:30 PM, on the last day of the month. ## Related docs From b0b94c64f9ee1978ac2f0a6bfe21bb1a695b9d05 Mon Sep 17 00:00:00 2001 From: Mike Alfare Date: Thu, 7 Dec 2023 23:18:29 -0500 Subject: [PATCH 075/165] combine sort type option into the same row --- .../resource-configs/redshift-configs.md | 17 ++++++++--------- 1 file changed, 8 insertions(+), 9 deletions(-) diff --git a/website/docs/reference/resource-configs/redshift-configs.md b/website/docs/reference/resource-configs/redshift-configs.md index 44b66b30005..c7fc0671c0b 100644 --- a/website/docs/reference/resource-configs/redshift-configs.md +++ b/website/docs/reference/resource-configs/redshift-configs.md @@ -114,15 +114,14 @@ models: The Redshift adapter supports [materialized views](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-overview.html) with the following configuration parameters: -| Parameter | Type | Required | Default | Change Monitoring Support | -|-------------------------------------------|--------------|----------|----------------------|---------------------------| -| `on_configuration_change` | `` | no | `apply` | n/a | -| [`dist`](#using-sortkey-and-distkey) | `` | no | `even` | drop/create | -| [`sort`](#using-sortkey-and-distkey) | `[]` | no | `none` | drop/create | -| [`sort_type`](#using-sortkey-and-distkey) | `` | no | `auto` if no `sort` | drop/create | -| | | | `compound` if `sort` | | -| [`auto_refresh`](#auto-refresh) | `` | no | `false` | alter | -| [`backup`](#backup) | `` | no | `true` | n/a | +| Parameter | Type | Required | Default | Change Monitoring Support | +|-------------------------------------------|--------------|----------|------------------------------------------------|---------------------------| +| `on_configuration_change` | `` | no | `apply` | n/a | +| [`dist`](#using-sortkey-and-distkey) | `` | no | `even` | drop/create | +| [`sort`](#using-sortkey-and-distkey) | `[]` | no | `none` | drop/create | +| [`sort_type`](#using-sortkey-and-distkey) | `` | no | `auto` if no `sort`
`compound` if `sort` | drop/create | +| [`auto_refresh`](#auto-refresh) | `` | no | `false` | alter | +| [`backup`](#backup) | `` | no | `true` | n/a | Date: Fri, 8 Dec 2023 07:14:15 -0500 Subject: [PATCH 076/165] Update website/docs/docs/deploy/deploy-jobs.md --- website/docs/docs/deploy/deploy-jobs.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/docs/deploy/deploy-jobs.md b/website/docs/docs/deploy/deploy-jobs.md index cb62de00e7e..d7fe0b361d2 100644 --- a/website/docs/docs/deploy/deploy-jobs.md +++ b/website/docs/docs/deploy/deploy-jobs.md @@ -90,7 +90,7 @@ Refer to the following example snippets: - `0 * * * *`: Every hour, at minute 0. - `*/5 * * * *`: Every 5 minutes. - `5 4 * * *`: At exactly 4:05 AM UTC. -- `30 */4 * * *`: At minute 30 past every 4th hour (e.g. 4:30AM, 8:30AM, 12:30PM, etc., all UTC). +- `30 */4 * * *`: At minute 30 past every 4th hour (such as 4:30 AM, 8:30 AM, 12:30 PM, and so on, all UTC). - `0 0 */2 * *`: At midnight UTC every other day. - `0 0 * * 1`: At midnight UTC every Monday. - `0 0 L * *`: At 12:00 AM, on the last day of the month. From 69227e0d4f178e4b6472d6fbdef7bd469366d49e Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Fri, 8 Dec 2023 07:14:42 -0500 Subject: [PATCH 077/165] Update website/docs/docs/deploy/deploy-jobs.md --- website/docs/docs/deploy/deploy-jobs.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/docs/deploy/deploy-jobs.md b/website/docs/docs/deploy/deploy-jobs.md index d7fe0b361d2..09b5491b1db 100644 --- a/website/docs/docs/deploy/deploy-jobs.md +++ b/website/docs/docs/deploy/deploy-jobs.md @@ -93,7 +93,7 @@ Refer to the following example snippets: - `30 */4 * * *`: At minute 30 past every 4th hour (such as 4:30 AM, 8:30 AM, 12:30 PM, and so on, all UTC). - `0 0 */2 * *`: At midnight UTC every other day. - `0 0 * * 1`: At midnight UTC every Monday. -- `0 0 L * *`: At 12:00 AM, on the last day of the month. +- `0 0 L * *`: At 12:00 AM (midnight), on the last day of the month. - `0 0 L 1,2,3,4,5,6,8,9,10,11,12 *`: At 12:00 AM, on the last day of the month, only in January, February, March, April, May, June, August, September, October, November, and December. - `0 0 L 7 *`: At 12:00 AM, on the last day of the month, only in July. - `0 0 L * FRI,SAT`: At 12:00 AM, on the last day of the month, and on Friday and Saturday. From f076c2d6742a70832801f7522cb65954d09c2fad Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Fri, 8 Dec 2023 07:15:01 -0500 Subject: [PATCH 078/165] Update website/docs/docs/deploy/deploy-jobs.md --- website/docs/docs/deploy/deploy-jobs.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/docs/deploy/deploy-jobs.md b/website/docs/docs/deploy/deploy-jobs.md index 09b5491b1db..ef46b368b91 100644 --- a/website/docs/docs/deploy/deploy-jobs.md +++ b/website/docs/docs/deploy/deploy-jobs.md @@ -91,7 +91,7 @@ Refer to the following example snippets: - `*/5 * * * *`: Every 5 minutes. - `5 4 * * *`: At exactly 4:05 AM UTC. - `30 */4 * * *`: At minute 30 past every 4th hour (such as 4:30 AM, 8:30 AM, 12:30 PM, and so on, all UTC). -- `0 0 */2 * *`: At midnight UTC every other day. +- `0 0 */2 * *`: At 12:00 AM (midnight) UTC every other day. - `0 0 * * 1`: At midnight UTC every Monday. - `0 0 L * *`: At 12:00 AM (midnight), on the last day of the month. - `0 0 L 1,2,3,4,5,6,8,9,10,11,12 *`: At 12:00 AM, on the last day of the month, only in January, February, March, April, May, June, August, September, October, November, and December. From e3c7326f12994ed901a5d9de2a9934e2dea48569 Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Fri, 8 Dec 2023 07:16:50 -0500 Subject: [PATCH 079/165] Update website/docs/docs/deploy/deploy-jobs.md --- website/docs/docs/deploy/deploy-jobs.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/docs/deploy/deploy-jobs.md b/website/docs/docs/deploy/deploy-jobs.md index ef46b368b91..5c7ef0ca8b3 100644 --- a/website/docs/docs/deploy/deploy-jobs.md +++ b/website/docs/docs/deploy/deploy-jobs.md @@ -97,7 +97,7 @@ Refer to the following example snippets: - `0 0 L 1,2,3,4,5,6,8,9,10,11,12 *`: At 12:00 AM, on the last day of the month, only in January, February, March, April, May, June, August, September, October, November, and December. - `0 0 L 7 *`: At 12:00 AM, on the last day of the month, only in July. - `0 0 L * FRI,SAT`: At 12:00 AM, on the last day of the month, and on Friday and Saturday. -- `0 12 L * *`: At 12:00 PM, on the last day of the month. +- `0 12 L * *`: At 12:00 PM (afternoon), on the last day of the month. - `0 7 L * 5`: At 07:00 AM, on the last day of the month, and on Friday. - `30 14 L * *`: At 02:30 PM, on the last day of the month. From b237f544d461378bcab7b8ea5590543b5fbfe618 Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Fri, 8 Dec 2023 07:26:55 -0500 Subject: [PATCH 080/165] Update website/docs/docs/deploy/deploy-jobs.md --- website/docs/docs/deploy/deploy-jobs.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/docs/deploy/deploy-jobs.md b/website/docs/docs/deploy/deploy-jobs.md index 5c7ef0ca8b3..cee6e245359 100644 --- a/website/docs/docs/deploy/deploy-jobs.md +++ b/website/docs/docs/deploy/deploy-jobs.md @@ -84,7 +84,7 @@ To fully customize the scheduling of your job, choose the **Custom cron schedule Use tools such as [crontab.guru](https://crontab.guru/) to generate the correct cron syntax. This tool allows you to input cron snippets and returns their plain English translations. -Refer to the following example snippets: +Here are examples of cron job schedules. The dbt Cloud job scheduler supports using `L` to schedule jobs on the last day of the month: - `0 * * * *`: Every hour, at minute 0. From aa7b29da2104fca529a615f0d1eddbc0224c145e Mon Sep 17 00:00:00 2001 From: Mike Alfare Date: Fri, 8 Dec 2023 15:32:25 -0500 Subject: [PATCH 081/165] add reference links to config block version --- .../reference/resource-configs/redshift-configs.md | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/website/docs/reference/resource-configs/redshift-configs.md b/website/docs/reference/resource-configs/redshift-configs.md index c7fc0671c0b..f610d19a346 100644 --- a/website/docs/reference/resource-configs/redshift-configs.md +++ b/website/docs/reference/resource-configs/redshift-configs.md @@ -185,13 +185,13 @@ models: ```jinja {{ config( - materialized="materialized_view", + [materialized](/reference/resource-configs/materialized)="materialized_view", on_configuration_change="apply" | "continue" | "fail", - dist="all" | "auto" | "even" | "", - sort=[""], - sort_type="auto" | "compound" | "interleaved", - auto_refresh=true | false, - backup=true | false, + [dist](#using-sortkey-and-distkey)="all" | "auto" | "even" | "", + [sort](#using-sortkey-and-distkey)=[""], + [sort_type](#using-sortkey-and-distkey)="auto" | "compound" | "interleaved", + [auto_refresh](#auto-refresh)=true | false, + [backup](#backup)=true | false, ) }} ``` From 20ae17beeecb7d2eced51a81f1f157421139b372 Mon Sep 17 00:00:00 2001 From: Mike Alfare Date: Fri, 8 Dec 2023 15:34:31 -0500 Subject: [PATCH 082/165] add reference links to config block version --- .../resource-configs/bigquery-configs.md | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/website/docs/reference/resource-configs/bigquery-configs.md b/website/docs/reference/resource-configs/bigquery-configs.md index f9b447fdc0b..ea20be4fb41 100644 --- a/website/docs/reference/resource-configs/bigquery-configs.md +++ b/website/docs/reference/resource-configs/bigquery-configs.md @@ -827,10 +827,10 @@ models: ```jinja {{ config( - materialized='materialized_view', + [materialized](/reference/resource-configs/materialized)='materialized_view', on_configuration_change="apply" | "continue" | "fail", - cluster_by="" | [""], - partition_by={ + [cluster_by](#clustering-clause)="" | [""], + [partition_by](#partition-clause)={ "field": "", "data_type": "timestamp" | "date" | "datetime" | "int64", @@ -846,17 +846,17 @@ models: }, # auto-refresh options - enable_refresh= true | false, - refresh_interval_minutes=, - max_staleness="", + [enable_refresh](#auto-refresh)= true | false, + [refresh_interval_minutes](#auto-refresh)=, + [max_staleness](#auto-refresh)="", # additional options description="", - labels={ + [labels](#specifying-labels)={ "": "", }, - hours_to_expiration=, - kms_key_name="", + [hours_to_expiration](#acontrolling-table-expiration)=, + [kms_key_name](##using-kms-encryption)="", ) }} ``` From ecc39ab9c905e9750016e7f9d689aeafd508fbbc Mon Sep 17 00:00:00 2001 From: Mike Alfare Date: Fri, 8 Dec 2023 15:35:39 -0500 Subject: [PATCH 083/165] add reference links to config block version --- .../docs/reference/resource-configs/snowflake-configs.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/website/docs/reference/resource-configs/snowflake-configs.md b/website/docs/reference/resource-configs/snowflake-configs.md index c6ef5c4b339..a5c2e6f57d9 100644 --- a/website/docs/reference/resource-configs/snowflake-configs.md +++ b/website/docs/reference/resource-configs/snowflake-configs.md @@ -417,10 +417,10 @@ models: ```jinja {{ config( - materialized="dynamic_table", + [materialized](/reference/resource-configs/materialized)="dynamic_table", on_configuration_change="apply" | "continue" | "fail", - target_lag="downstream" | " seconds | minutes | hours | days", - snowflake_warehouse="", + [target_lag](#target-lag)="downstream" | " seconds | minutes | hours | days", + [snowflake_warehouse](#configuring-virtual-warehouses)="", ) }} ``` From 08972fe81b37c325692942689cbb772b6c4b67fe Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Mon, 11 Dec 2023 10:16:18 -0500 Subject: [PATCH 084/165] clarify and add links --- .../docs/reference/node-selection/syntax.md | 27 ++++++++++++++----- 1 file changed, 21 insertions(+), 6 deletions(-) diff --git a/website/docs/reference/node-selection/syntax.md b/website/docs/reference/node-selection/syntax.md index d0ea4a9acd8..14ec34eb8a6 100644 --- a/website/docs/reference/node-selection/syntax.md +++ b/website/docs/reference/node-selection/syntax.md @@ -35,7 +35,7 @@ To follow [POSIX standards](https://pubs.opengroup.org/onlinepubs/9699919799/bas 3. dbt now has a list of still-selected resources of varying types. As a final step, it tosses away any resource that does not match the resource type of the current task. (Only seeds are kept for `dbt seed`, only models for `dbt run`, only tests for `dbt test`, and so on.) -### Shorthand +## Shorthand Select resources to build (run, test, seed, snapshot) or check freshness: `--select`, `-s` @@ -43,6 +43,10 @@ Select resources to build (run, test, seed, snapshot) or check freshness: `--sel By default, `dbt run` will execute _all_ of the models in the dependency graph. During development (and deployment), it is useful to specify only a subset of models to run. Use the `--select` flag with `dbt run` to select a subset of models to run. Note that the following arguments (`--select`, `--exclude`, and `--selector`) also apply to other dbt tasks, such as `test` and `build`. + + + + The `--select` flag accepts one or more arguments. Each argument can be one of: 1. a package name @@ -52,8 +56,7 @@ The `--select` flag accepts one or more arguments. Each argument can be one of: Examples: - - ```bash +```bash dbt run --select "my_dbt_project_name" # runs all models in your project dbt run --select "my_dbt_model" # runs a specific model dbt run --select "path.to.my.models" # runs all models in a specific directory @@ -61,12 +64,20 @@ dbt run --select "my_package.some_model" # run a specific model in a specific pa dbt run --select "tag:nightly" # run models with the "nightly" tag dbt run --select "path/to/models" # run models contained in path/to/models dbt run --select "path/to/my_model.sql" # run a specific model by its path - ``` +``` -dbt supports a shorthand language for defining subsets of nodes. This language uses the characters `+`, `@`, `*`, and `,`. + + - ```bash +dbt supports a shorthand language for defining subsets of nodes. This language uses the following characters: + +- plus operator [(`+`)](/reference/node-selection/graph-operators#the-plus-operator) +- at operator [(`@`)](/reference/node-selection/graph-operators#the-at-operator) +- asterisk operator (`*`) +- comma operator (`,`) + +```bash # multiple arguments can be provided to --select dbt run --select "my_first_model my_second_model" @@ -77,6 +88,10 @@ dbt run --select "tag:nightly my_model finance.base.*" dbt run --select "path:marts/finance,tag:nightly,config.materialized:table" ``` + + + + As your selection logic gets more complex, and becomes unwieldly to type out as command-line arguments, consider using a [yaml selector](/reference/node-selection/yaml-selectors). You can use a predefined definition with the `--selector` flag. Note that when you're using `--selector`, most other flags (namely `--select` and `--exclude`) will be ignored. From e198da4b6fce4188af82c308544717d0590805ec Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Mon, 11 Dec 2023 10:16:59 -0500 Subject: [PATCH 085/165] add example --- website/docs/reference/node-selection/syntax.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/website/docs/reference/node-selection/syntax.md b/website/docs/reference/node-selection/syntax.md index 14ec34eb8a6..1edc28a4c41 100644 --- a/website/docs/reference/node-selection/syntax.md +++ b/website/docs/reference/node-selection/syntax.md @@ -77,6 +77,8 @@ dbt supports a shorthand language for defining subsets of nodes. This language u - asterisk operator (`*`) - comma operator (`,`) +Examples: + ```bash # multiple arguments can be provided to --select dbt run --select "my_first_model my_second_model" From f4ceaf326758cc037e8ce2e2ee3bf56d9515a5fd Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Mon, 11 Dec 2023 10:26:59 -0500 Subject: [PATCH 086/165] fix label --- website/docs/reference/node-selection/syntax.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/website/docs/reference/node-selection/syntax.md b/website/docs/reference/node-selection/syntax.md index 1edc28a4c41..31e4f878ff3 100644 --- a/website/docs/reference/node-selection/syntax.md +++ b/website/docs/reference/node-selection/syntax.md @@ -45,7 +45,7 @@ By default, `dbt run` will execute _all_ of the models in the dependency graph. - + The `--select` flag accepts one or more arguments. Each argument can be one of: @@ -68,7 +68,7 @@ dbt run --select "path/to/my_model.sql" # run a specific model by its path - + dbt supports a shorthand language for defining subsets of nodes. This language uses the following characters: From d569754aa118ac1260cdd80a3e9745c323ac6329 Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Mon, 11 Dec 2023 11:37:45 -0500 Subject: [PATCH 087/165] update sidebar --- website/sidebars.js | 1 - 1 file changed, 1 deletion(-) diff --git a/website/sidebars.js b/website/sidebars.js index 792645b53e7..544b3a1e92a 100644 --- a/website/sidebars.js +++ b/website/sidebars.js @@ -281,7 +281,6 @@ const sidebarSettings = { "docs/build/jinja-macros", "docs/build/sources", "docs/build/exposures", - "docs/build/metrics", "docs/build/groups", "docs/build/analyses", ], From 8ee808d9145107c71abe59e8e2016ab45a4772d9 Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Mon, 11 Dec 2023 11:59:10 -0500 Subject: [PATCH 088/165] Create legacy-sl.md --- .../release-notes/74-Dec-2023/legacy-sl.md | 13 +++++++++++++ 1 file changed, 13 insertions(+) create mode 100644 website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md diff --git a/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md b/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md new file mode 100644 index 00000000000..00b1dd4b74c --- /dev/null +++ b/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md @@ -0,0 +1,13 @@ +--- +title: "Deprecation: dbt Metrics and the Legacy dbt Semantic Layer for Git repository caching" +description: "December 2023: dbt Cloud can cache your project's code (as well as other dbt packages) to ensure runs can begin despite an upstream Git provider's outage." +sidebar_label: "Deprecation: Support for Git repository caching" +sidebar_position: 10 +date: 2023-12-15 +--- + +Now available for dbt Cloud Enterprise plans is a new option to enable Git repository caching for your job runs. When enabled, dbt Cloud caches your dbt project's Git repository and uses the cached copy instead if there's an outage with the Git provider. This feature improves the reliability and stability of your job runs. + +To learn more, refer to [Repo caching](/docs/deploy/deploy-environments#git-repository-caching). + + From 9edcc6d61566ca4c9da4c615f15ac92a0af7dd1f Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Mon, 11 Dec 2023 12:24:46 -0500 Subject: [PATCH 089/165] update rn --- .../release-notes/74-Dec-2023/legacy-sl.md | 12 +++++------- 1 file changed, 5 insertions(+), 7 deletions(-) diff --git a/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md b/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md index 00b1dd4b74c..fbe5396d9a6 100644 --- a/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md +++ b/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md @@ -1,13 +1,11 @@ --- -title: "Deprecation: dbt Metrics and the Legacy dbt Semantic Layer for Git repository caching" -description: "December 2023: dbt Cloud can cache your project's code (as well as other dbt packages) to ensure runs can begin despite an upstream Git provider's outage." -sidebar_label: "Deprecation: Support for Git repository caching" +title: "Deprecation: dbt Metrics and the legacy dbt Semantic Layer is now deprecated" +description: "December 2023: For users on dbt v1.5 and lower, dbt Metrics and the legacy dbt Semantic Layer has been deprecated. Use the migration guide to migrate to and access the latest dbt Semantic Layer. " +sidebar_label: "Deprecation: dbt Metrics and Legacy dbt Semantic Layer" sidebar_position: 10 date: 2023-12-15 --- -Now available for dbt Cloud Enterprise plans is a new option to enable Git repository caching for your job runs. When enabled, dbt Cloud caches your dbt project's Git repository and uses the cached copy instead if there's an outage with the Git provider. This feature improves the reliability and stability of your job runs. +On December 15th, 2023, dbt Labs deprecated dbt Metrics and the legacy dbt Semantic Layer, both supported on dbt version 1.5 or lower. This deprecation means dbt Metrics and the legacy Semantic Layer will no longer be supported. We will also remove the product from the dbt Cloud user interface and [documentation site](https://docs.getdbt.com/). -To learn more, refer to [Repo caching](/docs/deploy/deploy-environments#git-repository-caching). - - +To access the [re-released dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl), switch to the latest version using the dedicated [migration guide](/guides/sl-migration?step=1). From f9c7d9bd40d686fc7029321a9ca8b2c77f677430 Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Mon, 11 Dec 2023 12:58:19 -0500 Subject: [PATCH 090/165] tweaks of rn --- .../release-notes/74-Dec-2023/legacy-sl.md | 25 +++++++-- .../docs/use-dbt-semantic-layer/setup-sl.md | 51 ------------------- website/snippets/sl-prerequisites.md | 38 -------------- website/snippets/sl-public-preview-banner.md | 7 --- website/snippets/sl-set-up-steps.md | 30 ----------- 5 files changed, 22 insertions(+), 129 deletions(-) delete mode 100644 website/snippets/sl-prerequisites.md delete mode 100644 website/snippets/sl-public-preview-banner.md delete mode 100644 website/snippets/sl-set-up-steps.md diff --git a/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md b/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md index fbe5396d9a6..395ad258b62 100644 --- a/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md +++ b/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md @@ -2,10 +2,29 @@ title: "Deprecation: dbt Metrics and the legacy dbt Semantic Layer is now deprecated" description: "December 2023: For users on dbt v1.5 and lower, dbt Metrics and the legacy dbt Semantic Layer has been deprecated. Use the migration guide to migrate to and access the latest dbt Semantic Layer. " sidebar_label: "Deprecation: dbt Metrics and Legacy dbt Semantic Layer" -sidebar_position: 10 +sidebar_position: 09 date: 2023-12-15 --- -On December 15th, 2023, dbt Labs deprecated dbt Metrics and the legacy dbt Semantic Layer, both supported on dbt version 1.5 or lower. This deprecation means dbt Metrics and the legacy Semantic Layer will no longer be supported. We will also remove the product from the dbt Cloud user interface and [documentation site](https://docs.getdbt.com/). +dbt Labs has deprecated dbt Metrics and the legacy dbt Semantic Layer, both supported on dbt version 1.5 or lower. These changes will be in effect on _December 15th, 2023_. -To access the [re-released dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl), switch to the latest version using the dedicated [migration guide](/guides/sl-migration?step=1). +This deprecation means dbt Metrics and the legacy Semantic Layer will no longer be supported. We will also remove the product from the dbt Cloud user interface and [documentation site](https://docs.getdbt.com/). + +### Why this change? + +We understand that changes of this nature can be disruptive and we believe in the potential of the new direction. The [re-released dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl), powered by MetricFlow, is a significantly improved foundation that enables more flexible query generation, faster performance, and a more dynamic consumption experience. It’s a step towards a brighter future for dbt and its community. + +### Key changes + +- Legacy Semantic Layer and dbt Metrics will officially be deprecated on December 15th, 2023. +- MetricFlow has replaced dbt Metrics for the construction of semantic logic. The `dbt_metrics` package will no longer be supported. +- Exports replaces Materializations. Exports will be available in December or January in dbt Cloud and replaces the previous materializations functionality. + +### Actions + +- If you're using the legacy dbt Semantic Layer or dbt Metrics, use the [dbt Semantic Layer migration guide](/guides/sl-migration?step=1) to migrate over to the re-released dbt Semantic Layer. +- Engage and share feedback with the dbt Labs team and dbt Community slack using channels like [#dbt-cloud-semantic-layer](https://getdbt.slack.com/archives/C046L0VTVR6) and [#dbt-metricflow](https://getdbt.slack.com/archives/C02CCBBBR1D). Or reach out to your dbt Cloud account representative. +- Refer to some additional info and resources to help you upgrade your dbt version: + + - [Upgrade version in dbt Cloud](/docs/dbt-versions/upgrade-core-in-cloud) + - [Version migration guides](/docs/dbt-versions/core-upgrade) diff --git a/website/docs/docs/use-dbt-semantic-layer/setup-sl.md b/website/docs/docs/use-dbt-semantic-layer/setup-sl.md index fb7b853ad24..0944e5ce1e1 100644 --- a/website/docs/docs/use-dbt-semantic-layer/setup-sl.md +++ b/website/docs/docs/use-dbt-semantic-layer/setup-sl.md @@ -32,58 +32,7 @@ import SlSetUp from '/snippets/_new-sl-setup.md'; 8. You’re done 🎉! The semantic layer should is now enabled for your project. --> - - - -import DeprecationNotice from '/snippets/_sl-deprecation-notice.md'; - - - -With the dbt Semantic Layer, you can define business metrics, reduce code duplication and inconsistency, create self-service in downstream tools, and more. Configure the dbt Semantic Layer in dbt Cloud to connect with your integrated partner tool. - -## Prerequisites - - - - -## Set up dbt Semantic Layer - -:::tip -If you're using the legacy Semantic Layer, dbt Labs strongly recommends that you [upgrade your dbt version](/docs/dbt-versions/upgrade-core-in-cloud) to dbt v1.6 or higher to use the latest dbt Semantic Layer. Refer to the dedicated [migration guide](/guides/sl-migration) for more info. - -::: - - * Team and Enterprise accounts can set up the Semantic Layer and [Discovery API](/docs/dbt-cloud-apis/discovery-api) in the integrated partner tool to import metric definitions. - * Developer accounts can query the Proxy Server using SQL but won't be able to browse dbt metrics in external tools, which requires access to the Discovery API. - - -1. Log in to your dbt Cloud account. -2. Go to **Account Settings**, and then **Service Tokens** to create a new [service account API token](/docs/dbt-cloud-apis/service-tokens). Save your token somewhere safe. -3. Assign permissions to service account tokens depending on the integration tool you choose. Refer to the [integration partner documentation](https://www.getdbt.com/product/semantic-layer-integrations) to determine the permission sets you need to assign. -4. Go to **Deploy** > **Environments**, and select your **Deployment** environment. -5. Click **Settings** on the top right side of the page. -6. Click **Edit** on the top right side of the page. -7. Select dbt version 1.2 or higher. -8. Toggle the Semantic Layer **On**. -9. Copy the full proxy server URL (like `https://eagle-hqya7.proxy.cloud.getdbt.com`) to connect to your [integrated partner tool](https://www.getdbt.com/product/semantic-layer-integrations). -10. Use the URL in the data source configuration of the integrated partner tool. -11. Use the data platform login credentials that make sense for how the data is consumed. - -:::info📌 - -It is _not_ recommended that you use your dbt Cloud credentials due to elevated permissions. Instead, you can use your specific integration tool permissions. - -::: - -12. Set up the [Discovery API](/docs/dbt-cloud-apis/discovery-api) (Team and Enterprise accounts only) in the integrated partner tool to import the metric definitions. The [integrated partner tool](https://www.getdbt.com/product/semantic-layer-integrations) will treat the dbt Server as another data source (like a data platform). This requires: - -- The account ID, environment ID, and job ID (which is visible in the job URL) -- An [API service token](/docs/dbt-cloud-apis/service-tokens) with job admin and metadata permissions -- Add the items above to the relevant fields in your integration tool - - -
## Related docs diff --git a/website/snippets/sl-prerequisites.md b/website/snippets/sl-prerequisites.md deleted file mode 100644 index 0c100c299b0..00000000000 --- a/website/snippets/sl-prerequisites.md +++ /dev/null @@ -1,38 +0,0 @@ - - -- Have a multi-tenant dbt Cloud instance, hosted in North America
-- Have both your production and development environments running dbt version 1.3 or higher
-- Use Snowflake data platform
-- Install the dbt metrics package version >=1.3.0, <1.4.0 in your dbt project
- * **Note** — After installing the dbt metrics package and updating the `packages.yml` file, make sure you run at least one model. -- Set up the Discovery API in the integrated tool to import metric definitions - * Developer accounts will be able to query the Proxy Server using SQL, but will not be able to browse pre-populated dbt metrics in external tools, which requires access to the Discovery API
-- Recommended - Review the dbt metrics page
- - - - - -- Have a multi-tenant dbt Cloud instance, hosted in North America
-- Have both your production and development environments running dbt version 1.3 or higher
-- Use Snowflake data platform
-- Install the dbt metrics package version >=1.3.0, <1.4.0 in your dbt project
- * **Note** — After installing the dbt metrics package and updating the `packages.yml` file, make sure you run at least one model. -- Set up the Discovery API in the integrated tool to import metric definitions - * Developer accounts will be able to query the Proxy Server using SQL, but will not be able to browse pre-populated dbt metrics in external tools, which requires access to the Discovery API
-- Recommended - Review the dbt metrics page
- - - - - -- Have a multi-tenant dbt Cloud instance, hosted in North America
-- Have both your production and development environments running dbt version 1.2
-- Use Snowflake data platform
-- Install the dbt metrics package version >=0.3.0, <0.4.0 in your dbt project
- * **Note** — After installing the dbt metrics package and updating the `packages.yml` file, make sure you run at least one model. -- Set up the Discovery API in the integrated tool to import metric definitions - * Developer accounts will be able to query the Proxy Server using SQL, but will not be able to browse pre-populated dbt metrics in external tools, which requires access to the Discovery API
-- Recommended - Review the dbt metrics page
- - diff --git a/website/snippets/sl-public-preview-banner.md b/website/snippets/sl-public-preview-banner.md deleted file mode 100644 index e97527d356d..00000000000 --- a/website/snippets/sl-public-preview-banner.md +++ /dev/null @@ -1,7 +0,0 @@ -:::info 📌 - -The dbt Semantic Layer is currently available in Public Preview for multi-tenant dbt Cloud accounts hosted in North America. If you log in via https://cloud.getdbt.com/, you can access the Semantic Layer. If you log in with [another URL](/docs/cloud/about-cloud/regions-ip-addresses), the dbt Semantic Layer will be available in the future. - -For more info, review the [Prerequisites](/docs/use-dbt-semantic-layer/dbt-semantic-layer#prerequisites), [Public Preview](/docs/use-dbt-semantic-layer/quickstart-semantic-layer#public-preview), and [Product architecture](/docs/use-dbt-semantic-layer/dbt-semantic-layer#product-architecture) sections. - -::: diff --git a/website/snippets/sl-set-up-steps.md b/website/snippets/sl-set-up-steps.md deleted file mode 100644 index 295253fb994..00000000000 --- a/website/snippets/sl-set-up-steps.md +++ /dev/null @@ -1,30 +0,0 @@ - -Before you continue with the following steps, you **must** have a multi-tenant dbt Cloud account hosted in North America. - * Team and Enterprise accounts can set up the Semantic Layer and [Discovery API](/docs/dbt-cloud-apis/discovery-api) in the integrated partner tool to import metric definition. - * Developer accounts can query the Proxy Server using SQL but won't be able to browse dbt metrics in external tools, which requires access to the Discovery API. - -You can set up the dbt Semantic Layer in dbt Cloud at the environment level by following these steps: - -1. Login to your dbt Cloud account -2. Go to **Account Settings**, and then **Service Tokens** to create a new [service account API token](/docs/dbt-cloud-apis/service-tokens). Save your token somewhere safe. -3. Assign permissions to service account tokens depending on the integration tool you choose. You can review the [integration partner documentation](https://www.getdbt.com/product/semantic-layer-integrations) to determine the permission sets you need to assign. -4. Go to **Deploy** and then **Environment**, and select your **Deployment** environment. -5. Click on **Settings** on the top right side of the page. -6. Click **Edit** on the top right side of the page. -7. Select dbt version 1.2 or higher. -8. Toggle the Semantic Layer **On**. -9. Copy the full proxy server URL (like `https://eagle-hqya7.proxy.cloud.getdbt.com`) to connect to your [integrated partner tool](https://www.getdbt.com/product/semantic-layer-integrations). -10. Use the URL in the data source configuration of the integrated partner tool. -11. Use the data platform login credentials that make sense for how the data is consumed. - -:::info📌 - -Note - It is _not_ recommended that you use your dbt Cloud credentials due to elevated permissions. Instead, you can use your specific integration tool permissions. - -::: - -12. Set up the [Discovery API](/docs/dbt-cloud-apis/discovery-api) (Team and Enterprise accounts only) in the integrated partner tool to import the metric definitions. The [integrated partner tool](https://www.getdbt.com/product/semantic-layer-integrations) will treat the dbt Server as another data source (like a data platform). This requires: - -- The account ID, environment ID, and job ID (visible in the job URL) -- An [API service token](/docs/dbt-cloud-apis/service-tokens) with job admin and metadata permissions -- Add the items above to the relevant fields in your integration tool From 4113f882dd26f043edd1fd70ade408ac6fa3705c Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Mon, 11 Dec 2023 12:59:55 -0500 Subject: [PATCH 091/165] remove link as redundant --- .../docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md b/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md index 395ad258b62..11bd25a7020 100644 --- a/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md +++ b/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md @@ -8,7 +8,7 @@ date: 2023-12-15 dbt Labs has deprecated dbt Metrics and the legacy dbt Semantic Layer, both supported on dbt version 1.5 or lower. These changes will be in effect on _December 15th, 2023_. -This deprecation means dbt Metrics and the legacy Semantic Layer will no longer be supported. We will also remove the product from the dbt Cloud user interface and [documentation site](https://docs.getdbt.com/). +This deprecation means dbt Metrics and the legacy Semantic Layer will no longer be supported. We will also remove the product from the dbt Cloud user interface and documentation site. ### Why this change? 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zYWkF_^cz;T$u1o*BDe4&i`70UZY$nU(ouS;#JbJy-1)Y^ByH(n2o><9|678OaEHF{ z4c7v^vh~{b)kQ`3HK9VJNSViZd&nWI){w|s2|mWY{S7yK{w{-Riu&AFS5mw!#R6Ti zh3rkB%nMtU)}=oIGC<|Vvse#(CGp& fsqvEs|9O12oY!aa4kuYL{z_HxfkNTEr!W5>58}}f From 36a30c0ce3d0176bf2ff7633deeb7593e2810202 Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Mon, 11 Dec 2023 14:25:10 -0500 Subject: [PATCH 093/165] fix broken links --- .../docs/dbt-versions/core-upgrade/04-upgrading-to-v1.4.md | 2 +- .../docs/dbt-versions/core-upgrade/05-upgrading-to-v1.3.md | 2 +- .../docs/dbt-versions/core-upgrade/06-upgrading-to-v1.2.md | 2 +- .../docs/dbt-versions/core-upgrade/08-upgrading-to-v1.0.md | 2 +- website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md | 2 +- website/docs/guides/dbt-models-on-databricks.md | 2 +- website/docs/sql-reference/aggregate-functions/sql-count.md | 4 ++-- website/docs/terms/dry.md | 6 ++++-- 8 files changed, 12 insertions(+), 10 deletions(-) diff --git a/website/docs/docs/dbt-versions/core-upgrade/04-upgrading-to-v1.4.md b/website/docs/docs/dbt-versions/core-upgrade/04-upgrading-to-v1.4.md index a946bdf369b..240f0b86de3 100644 --- a/website/docs/docs/dbt-versions/core-upgrade/04-upgrading-to-v1.4.md +++ b/website/docs/docs/dbt-versions/core-upgrade/04-upgrading-to-v1.4.md @@ -48,7 +48,7 @@ For more detailed information and to ask any questions, please visit [dbt-core/d - [**Events and structured logging**](/reference/events-logging): dbt's event system got a makeover. Expect more consistency in the availability and structure of information, backed by type-safe event schemas. - [**Python support**](/faqs/Core/install-python-compatibility): Python 3.11 was released in October 2022. It is officially supported in dbt-core v1.4, although full support depends also on the adapter plugin for your data platform. According to the Python maintainers, "Python 3.11 is between 10-60% faster than Python 3.10." We encourage you to try [`dbt parse`](/reference/commands/parse) with dbt Core v1.4 + Python 3.11, and compare the timing with dbt Core v1.3 + Python 3.10. Let us know what you find! -- [**Metrics**](/docs/build/metrics): `time_grain` is optional, to provide better ergonomics around metrics that aren't time-bound. +- [**Metrics**](/docs/build/build-metrics-intro): `time_grain` is optional, to provide better ergonomics around metrics that aren't time-bound. - **dbt-Jinja context:** The [local_md5](/reference/dbt-jinja-functions/local_md5) context method will calculate an [MD5 hash](https://en.wikipedia.org/wiki/MD5) for use _within_ dbt. (Not to be confused with SQL md5!) - [**Exposures**](/docs/build/exposures) can now depend on `metrics`. - [**"Tarball" packages**](/docs/build/packages#internally-hosted-tarball-URL): Some organizations have security requirements to pull resources only from internal services. To address the need to install packages from hosted environments (such as Artifactory or cloud storage buckets), it's possible to specify any accessible URL where a compressed dbt package can be downloaded. diff --git a/website/docs/docs/dbt-versions/core-upgrade/05-upgrading-to-v1.3.md b/website/docs/docs/dbt-versions/core-upgrade/05-upgrading-to-v1.3.md index d9d97f17dc5..5a381b16928 100644 --- a/website/docs/docs/dbt-versions/core-upgrade/05-upgrading-to-v1.3.md +++ b/website/docs/docs/dbt-versions/core-upgrade/05-upgrading-to-v1.3.md @@ -49,7 +49,7 @@ GitHub discussion with details: [dbt-labs/dbt-core#6011](https://github.com/dbt- ## New and changed documentation - **[Python models](/docs/build/python-models)** are natively supported in `dbt-core` for the first time, on data warehouses that support Python runtimes. -- Updates made to **[Metrics](/docs/build/metrics)** reflect their new syntax for definition, as well as additional properties that are now available. +- Updates made to **[Metrics](/docs/build/build-metrics-intro)** reflect their new syntax for definition, as well as additional properties that are now available. - Plus, a few related updates to **[exposure properties](/reference/exposure-properties)**: `config`, `label`, and `name` validation. - **[Custom `node_color`](/reference/resource-configs/docs.md)** in `dbt-docs`. For the first time, you can control the colors displayed in dbt's DAG. Want bronze, silver, and gold layers? It's at your fingertips. diff --git a/website/docs/docs/dbt-versions/core-upgrade/06-upgrading-to-v1.2.md b/website/docs/docs/dbt-versions/core-upgrade/06-upgrading-to-v1.2.md index 72a3e0c82ad..cd75e7f411b 100644 --- a/website/docs/docs/dbt-versions/core-upgrade/06-upgrading-to-v1.2.md +++ b/website/docs/docs/dbt-versions/core-upgrade/06-upgrading-to-v1.2.md @@ -34,7 +34,7 @@ See GitHub discussion [dbt-labs/dbt-core#5468](https://github.com/dbt-labs/dbt-c ## New and changed functionality - **[Grants](/reference/resource-configs/grants)** are natively supported in `dbt-core` for the first time. That support extends to all standard materializations, and the most popular adapters. If you already use hooks to apply simple grants, we encourage you to use built-in `grants` to configure your models, seeds, and snapshots instead. This will enable you to [DRY](https://en.wikipedia.org/wiki/Don%27t_repeat_yourself) up your duplicated or boilerplate code. -- **[Metrics](/docs/build/metrics)** now support an `expression` type (metrics-on-metrics), as well as a `metric()` function to use when referencing metrics from within models, macros, or `expression`-type metrics. For more information on how to use expression metrics, check out the [**`dbt_metrics` package**](https://github.com/dbt-labs/dbt_metrics) +- **[Metrics](/docs/build/build-metrics-intro)** now support an `expression` type (metrics-on-metrics), as well as a `metric()` function to use when referencing metrics from within models, macros, or `expression`-type metrics. For more information on how to use expression metrics, check out the [**`dbt_metrics` package**](https://github.com/dbt-labs/dbt_metrics) - **[dbt-Jinja functions](/reference/dbt-jinja-functions)** now include the [`itertools` Python module](/reference/dbt-jinja-functions/modules#itertools), as well as the [set](/reference/dbt-jinja-functions/set) and [zip](/reference/dbt-jinja-functions/zip) functions. - **[Node selection](/reference/node-selection/syntax)** includes a [file selection method](/reference/node-selection/methods#the-file-method) (`-s model.sql`), and [yaml selector](/reference/node-selection/yaml-selectors) inheritance. - **[Global configs](/reference/global-configs/about-global-configs)** now include CLI flag and environment variable settings for [`target-path`](/reference/project-configs/target-path) and [`log-path`](/reference/project-configs/log-path), which can be used to override the values set in `dbt_project.yml` diff --git a/website/docs/docs/dbt-versions/core-upgrade/08-upgrading-to-v1.0.md b/website/docs/docs/dbt-versions/core-upgrade/08-upgrading-to-v1.0.md index 6e437638ef6..99de91c6565 100644 --- a/website/docs/docs/dbt-versions/core-upgrade/08-upgrading-to-v1.0.md +++ b/website/docs/docs/dbt-versions/core-upgrade/08-upgrading-to-v1.0.md @@ -70,7 +70,7 @@ Several under-the-hood changes from past minor versions, tagged with deprecation ## New features and changed documentation -- Add [metrics](/docs/build/metrics), a new node type +- Add [metrics](/docs/build/build-metrics-intro), a new node type - [Generic tests](/best-practices/writing-custom-generic-tests) can be defined in `tests/generic` (new), in addition to `macros/` (as before) - [Parsing](/reference/parsing): partial parsing and static parsing have been turned on by default. - [Global configs](/reference/global-configs/about-global-configs) have been standardized. Related updates to [global CLI flags](/reference/global-cli-flags) and [`profiles.yml`](/docs/core/connect-data-platform/profiles.yml). diff --git a/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md b/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md index 19fcc4b9eda..2ca81a0daf2 100644 --- a/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md +++ b/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md @@ -92,7 +92,7 @@ import SlFaqs from '/snippets/_sl-faqs.md'; ## Next steps -- [Set up dbt Semantic Layer](docs/use-dbt-semantic-layer/setup-dbt-sl) +- [Set up dbt Semantic Layer](/docs/use-dbt-semantic-layer/setup-dbt-sl) - [Available integrations](/docs/use-dbt-semantic-layer/avail-sl-integrations) - Demo on [how to define and query metrics with MetricFlow](https://www.loom.com/share/60a76f6034b0441788d73638808e92ac?sid=861a94ac-25eb-4fd8-a310-58e159950f5a) - [Billing](/docs/cloud/billing) diff --git a/website/docs/guides/dbt-models-on-databricks.md b/website/docs/guides/dbt-models-on-databricks.md index 489a3c28467..907b677cff9 100644 --- a/website/docs/guides/dbt-models-on-databricks.md +++ b/website/docs/guides/dbt-models-on-databricks.md @@ -104,7 +104,7 @@ When you delete a record from a Delta table, it is a soft delete. What this mean Now onto the most final layer — the gold marts that business stakeholders typically interact with from their preferred BI tool. The considerations here will be fairly similar to the silver layer except that these marts are more likely to handling aggregations. Further, you will likely want to be even more intentional about Z-Ordering these tables as SLAs tend to be lower with these direct stakeholder facing tables. -In addition, these tables are well suited for defining [dbt metrics](/docs/build/metrics) on to ensure simplicity and consistency across your key business KPIs! Using the [dbt_metrics package](https://hub.getdbt.com/dbt-labs/metrics/latest/), you can query the metrics inside of your own dbt project even. With the upcoming Semantic Layer Integration, you can also then query the metrics in any of the partner integrated tools. +In addition, these tables are well suited for defining [metrics](/docs/build/build-metrics-intro) on to ensure simplicity and consistency across your key business KPIs! Using the [MetricFlow](https://github.com/dbt-labs/metricflow), you can query the metrics inside of your own dbt project even. With the upcoming Semantic Layer Integration, you can also then query the metrics in any of the partner integrated tools. ### Filter rows in target and/or source diff --git a/website/docs/sql-reference/aggregate-functions/sql-count.md b/website/docs/sql-reference/aggregate-functions/sql-count.md index 42ece4b124f..d65c670df90 100644 --- a/website/docs/sql-reference/aggregate-functions/sql-count.md +++ b/website/docs/sql-reference/aggregate-functions/sql-count.md @@ -60,6 +60,6 @@ Some data warehouses, such as Snowflake and Google BigQuery, additionally suppor We most commonly see queries using COUNT to: - Perform initial data exploration on a dataset to understand dataset volume, primary key uniqueness, distribution of column values, and more. - Calculate the counts of key business metrics (daily orders, customers created, etc.) in your data models or BI tool. -- Define [dbt metrics](/docs/build/metrics) to aggregate key metrics. +- Define [metrics](/docs/build/build-metrics-intro) to aggregate key metrics. -This isn’t an extensive list of where your team may be using COUNT throughout your development work, dbt models, and BI tool logic, but it contains some common scenarios analytics engineers face day-to-day. \ No newline at end of file +This isn’t an extensive list of where your team may be using COUNT throughout your development work, dbt models, and BI tool logic, but it contains some common scenarios analytics engineers face day-to-day. diff --git a/website/docs/terms/dry.md b/website/docs/terms/dry.md index b1649278cd2..ec1c9229567 100644 --- a/website/docs/terms/dry.md +++ b/website/docs/terms/dry.md @@ -42,8 +42,10 @@ Most teams have essential business logic that defines the successes and failures By writing DRY definitions for key business logic and metrics that are referenced throughout a dbt project and/or BI (business intelligence) tool, data teams can create those single, unambiguous, and authoritative representations for their essential transformations. Gone are the days of 15 different definitions and values for churn, and in are the days of standardization and DRYness. -:::note Experimental dbt Metrics! -dbt v1.0 currently supports the use of experimental metrics, time series aggregations over a table that support zero or one dimensions. Using [dbt Metrics](/docs/build/metrics), data teams can define metric calculations, ownerships, and definitions in a YAML file that lives within their dbt project. dbt Metrics are in their experimental stage; if you’re interesting in learning more about dbt Metrics, please make sure to join the #dbt-metrics-and-server channel in the [dbt Community Slack](https://www.getdbt.com/community/join-the-community/). +:::important dbt Semantic Layer, powered by MetricFlow + +The [dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl), powered by [MetricFlow](/docs/build/about-metricflow), simplifies the process of defining and using critical business metrics, like revenue in the modeling layer (your dbt project). By centralizing metric definitions, data teams can ensure consistent self-service access to these metrics in downstream data tools and applications. The dbt Semantic Layer eliminates duplicate coding by allowing data teams to define metrics on top of existing models and automatically handles data joins. + ::: ## Tools to help you write DRY code From c4cdcda7ea7bb5bdbb38e9e5fd1f529445a954cb Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Mon, 11 Dec 2023 14:58:45 -0500 Subject: [PATCH 094/165] fix broken links --- website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md | 2 +- website/docs/sql-reference/aggregate-functions/sql-sum.md | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md b/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md index 2ca81a0daf2..9625621562e 100644 --- a/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md +++ b/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md @@ -92,7 +92,7 @@ import SlFaqs from '/snippets/_sl-faqs.md'; ## Next steps -- [Set up dbt Semantic Layer](/docs/use-dbt-semantic-layer/setup-dbt-sl) +- [Set up dbt Semantic Layer](/docs/use-dbt-semantic-layer/setup-sl) - [Available integrations](/docs/use-dbt-semantic-layer/avail-sl-integrations) - Demo on [how to define and query metrics with MetricFlow](https://www.loom.com/share/60a76f6034b0441788d73638808e92ac?sid=861a94ac-25eb-4fd8-a310-58e159950f5a) - [Billing](/docs/cloud/billing) diff --git a/website/docs/sql-reference/aggregate-functions/sql-sum.md b/website/docs/sql-reference/aggregate-functions/sql-sum.md index cb9235798d2..d6ca00c2daa 100644 --- a/website/docs/sql-reference/aggregate-functions/sql-sum.md +++ b/website/docs/sql-reference/aggregate-functions/sql-sum.md @@ -57,8 +57,8 @@ All modern data warehouses support the ability to use the SUM function (and foll We most commonly see queries using SUM to: - Calculate the cumulative sum of a metric across a customer/user id using a CASE WHEN statement (ex. `sum(case when order_array is not null then 1 else 0 end) as count_orders`) -- Create [dbt metrics](/docs/build/metrics) for key business values, such as LTV +- Create [dbt metrics](/docs/build/build-metrics-intro) for key business values, such as LTV - Calculate the total of a field across a dimension (ex. total session time, total time spent per ticket) that you typically use in `fct_` or `dim_` models - Summing clicks, spend, impressions, and other key ad reporting metrics in tables from ad platforms -This isn’t an extensive list of where your team may be using SUM throughout your development work, dbt models, and BI tool logic, but it contains some common scenarios analytics engineers face day-to-day. \ No newline at end of file +This isn’t an extensive list of where your team may be using SUM throughout your development work, dbt models, and BI tool logic, but it contains some common scenarios analytics engineers face day-to-day. From f0235af5df5e5c6d7a8c3b67dedcd8e04d398a22 Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Mon, 11 Dec 2023 15:29:13 -0500 Subject: [PATCH 095/165] remove version blocks --- website/snippets/_v2-sl-prerequisites.md | 30 ------------------------ 1 file changed, 30 deletions(-) diff --git a/website/snippets/_v2-sl-prerequisites.md b/website/snippets/_v2-sl-prerequisites.md index eb8b5fc27e4..99d8a945db6 100644 --- a/website/snippets/_v2-sl-prerequisites.md +++ b/website/snippets/_v2-sl-prerequisites.md @@ -1,6 +1,3 @@ - - - - Have a dbt Cloud Team or Enterprise account. Suitable for both Multi-tenant and Single-tenant deployment. - Note: Single-tenant accounts should contact their account representative for necessary setup and enablement. - Have both your production and development environments running [dbt version 1.6 or higher](/docs/dbt-versions/upgrade-core-in-cloud). @@ -11,30 +8,3 @@ - dbt Core or Developer accounts can define metrics but won't be able to dynamically query them.
- Understand [MetricFlow's](/docs/build/about-metricflow) key concepts, which powers the latest dbt Semantic Layer. - Note that SSH tunneling for [Postgres and Redshift](/docs/cloud/connect-data-platform/connect-redshift-postgresql-alloydb) connections, [PrivateLink](/docs/cloud/secure/about-privatelink), and [Single sign-on (SSO)](/docs/cloud/manage-access/sso-overview) doesn't supported the dbt Semantic Layer yet. - - - - - - -- Have a multi-tenant dbt Cloud instance, hosted in North America
-- Have both your production and development environments running dbt version 1.3 or higher
-- Use Snowflake data platform
-- Install the dbt metrics package version >=1.3.0, <1.4.0 in your dbt project
- * **Note** — After installing the dbt metrics package and updating the `packages.yml` file, make sure you run at least one model. -- Set up the Discovery API in the integrated tool to import metric definitions - * Developer accounts will be able to query the Proxy Server using SQL, but will not be able to browse pre-populated dbt metrics in external tools, which requires access to the Discovery API
- - - - - -- Have a multi-tenant dbt Cloud instance, hosted in North America
-- Have both your production and development environments running dbt version 1.2
-- Use Snowflake data platform
-- Install the dbt metrics package version >=0.3.0, <0.4.0 in your dbt project
- * **Note** — After installing the dbt metrics package and updating the `packages.yml` file, make sure you run at least one model. -- Set up the Discovery API in the integrated tool to import metric definitions - * Developer accounts will be able to query the Proxy Server using SQL, but will not be able to browse pre-populated dbt metrics in external tools, which requires access to the Discovery API
- - From 3a0d77cc2dd9ec76a54cc3a249009c8dba8f162c Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Mon, 11 Dec 2023 15:45:55 -0500 Subject: [PATCH 096/165] Update website/docs/reference/node-selection/syntax.md Co-authored-by: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> --- website/docs/reference/node-selection/syntax.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/reference/node-selection/syntax.md b/website/docs/reference/node-selection/syntax.md index 31e4f878ff3..d7d2136b325 100644 --- a/website/docs/reference/node-selection/syntax.md +++ b/website/docs/reference/node-selection/syntax.md @@ -45,7 +45,7 @@ By default, `dbt run` will execute _all_ of the models in the dependency graph. - + The `--select` flag accepts one or more arguments. Each argument can be one of: From 706dbb021e9335e0bbc7104d2ba5b7a624d102d4 Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Mon, 11 Dec 2023 15:46:09 -0500 Subject: [PATCH 097/165] Update website/docs/reference/node-selection/syntax.md Co-authored-by: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> --- website/docs/reference/node-selection/syntax.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/reference/node-selection/syntax.md b/website/docs/reference/node-selection/syntax.md index d7d2136b325..969db486c0e 100644 --- a/website/docs/reference/node-selection/syntax.md +++ b/website/docs/reference/node-selection/syntax.md @@ -68,7 +68,7 @@ dbt run --select "path/to/my_model.sql" # run a specific model by its path - + dbt supports a shorthand language for defining subsets of nodes. This language uses the following characters: From 0408a62be7f2d9e9ef21948b9fb3def422600430 Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Mon, 11 Dec 2023 15:56:28 -0500 Subject: [PATCH 098/165] tweak --- website/snippets/_new-sl-setup.md | 2 +- website/snippets/_sl-test-and-query-metrics.md | 1 - 2 files changed, 1 insertion(+), 2 deletions(-) diff --git a/website/snippets/_new-sl-setup.md b/website/snippets/_new-sl-setup.md index 18e75c3278d..c69cb23f425 100644 --- a/website/snippets/_new-sl-setup.md +++ b/website/snippets/_new-sl-setup.md @@ -8,7 +8,7 @@ You can set up the dbt Semantic Layer in dbt Cloud at the environment and projec - You must have a successful run in your new environment. :::tip -If you're using the legacy Semantic Layer, dbt Labs strongly recommends that you [upgrade your dbt version](/docs/dbt-versions/upgrade-core-in-cloud) to dbt version 1.6 or newer to use the latest dbt Semantic Layer. Refer to the dedicated [migration guide](/guides/sl-migration) for details. +If you've configured the legacy Semantic Layer, dbt Labs strongly recommends that you [upgrade your dbt version](/docs/dbt-versions/upgrade-core-in-cloud) to dbt version 1.6 or higher to use the latest dbt Semantic Layer. Refer to the dedicated [migration guide](/guides/sl-migration) for details. ::: 1. In dbt Cloud, create a new [deployment environment](/docs/deploy/deploy-environments#create-a-deployment-environment) or use an existing environment on dbt 1.6 or higher. diff --git a/website/snippets/_sl-test-and-query-metrics.md b/website/snippets/_sl-test-and-query-metrics.md index 2e9490f089d..b0db4bb520d 100644 --- a/website/snippets/_sl-test-and-query-metrics.md +++ b/website/snippets/_sl-test-and-query-metrics.md @@ -65,4 +65,3 @@ To streamline your metric querying process, you can connect to the [dbt Semantic - From b6a08ea56cf65415976626e9e3dfda0bc098cdd9 Mon Sep 17 00:00:00 2001 From: Jordan Stein Date: Mon, 11 Dec 2023 20:03:57 -0800 Subject: [PATCH 099/165] sl blog --- ...-12-11-semantic-layer-on-semantic-layer.md | 98 ++++++++++++++++++ website/blog/authors.yml | 8 ++ .../Screenshot-dag.png | Bin 0 -> 290575 bytes .../Screenshot-gsheets.png | Bin 0 -> 104987 bytes .../Screenshot-hex.png | Bin 0 -> 280943 bytes .../Screenshot-metrics-dag.png | Bin 0 -> 332777 bytes website/static/img/blog/authors/jordan.jpeg | Bin 0 -> 180802 bytes 7 files changed, 106 insertions(+) create mode 100644 website/blog/2023-12-11-semantic-layer-on-semantic-layer.md create mode 100644 website/static/img/blog/2023-12-11-semantic-layer-on-semantic-layer/Screenshot-dag.png create mode 100644 website/static/img/blog/2023-12-11-semantic-layer-on-semantic-layer/Screenshot-gsheets.png create mode 100644 website/static/img/blog/2023-12-11-semantic-layer-on-semantic-layer/Screenshot-hex.png create mode 100644 website/static/img/blog/2023-12-11-semantic-layer-on-semantic-layer/Screenshot-metrics-dag.png create mode 100644 website/static/img/blog/authors/jordan.jpeg diff --git a/website/blog/2023-12-11-semantic-layer-on-semantic-layer.md b/website/blog/2023-12-11-semantic-layer-on-semantic-layer.md new file mode 100644 index 00000000000..b321f0cd78d --- /dev/null +++ b/website/blog/2023-12-11-semantic-layer-on-semantic-layer.md @@ -0,0 +1,98 @@ +--- +title: "How we built consitent product launch metrics with the dbt Semantic Layer." +description: "We built and end-to-end data pipeline for measuring the launch of the dbt Semantic Layer using the dbt Semantic Layer." +slug: product-analytics-pipeline-with-dbt-semantic-layer + +authors: [jordan_stein] + +tags: [dbt Cloud] +hide_table_of_contents: false + +date: 2023-12-11 +is_featured: false +--- +There’s nothing quite like the feeling of launching a new product. +On launch day emotions can range from excitement, to fear, to accomplishment all in the same hour. +Once the dust settles and the product is in the wild, the next thing the team needs to do is track how the product is doing. +How many users do we have? How is performance looking? What features are customers using? How often? Answering these questions is vital to understanding the success of any product launch. + +At dbt we recently made the [Semantic Layer Generally Available](https://www.getdbt.com/blog/new-dbt-cloud-features-announced-at-coalesce-2023). The Semantic Layer lets teams define business metrics centrally, in dbt, and access them in multiple analytics tools through our semantic layer APIs. +I’m a Product Manager on the Semantic Layer team, and the launch of the Semantic Layer put our team in an interesting, somewhat “meta,” position: we need to understand how a product launch is doing, and the product we just launched is designed to make defining and consuming metrics much more efficient. It’s the perfect opportunity to put the semantic layer through its paces for product analytics. This blog post walks through the end-to-end process we used to set up product analytics for the dbt Semantic Layer using the dbt Semantic Layer. + +## Getting your data ready for metrics + +The first steps to building a product analytics pipeline with the Semantic Layer look the same as just using dbt - it’s all about data transformation. The steps we followed were broadly: + +1. Work with engineering to understand the data sources. In our case, it’s db exports from Semantic Layer Server. +2. Load the data into our warehouse. We use Fivetran and Snowflake. +3. Transform the data into normalized tables with dbt. This step is a classic. dbt’s bread and butter. You probably know the drill by now. + +There are [plenty of other great resources](https://docs.getdbt.com/docs/build/projects) on how to accomplish the above steps, I’m going to skip that in this post and focus on how we built business metrics using the Semantic Layer. Once the data is loaded and modeling is complete, our DAG for the Semantic Layer data looks like the following: + +![Screenshot 2023-09-28 at 4.05.25 PM.png](../static/img/blog/2023-12-11-semantic-layer-on-semantic-layer/Screenshot-dag.png) + +*Good old-fashioned debt DAG, with an extra node at the end* + + + +Let’s walk through the DAG from left to right: First, we have raw tables from the Semantic Layer Server loaded into our warehouse, next we have staging models where we apply business logic and finally a clean, normalized `fct_semantic_layer_queries` model. Finally, we built a semantic model named `semantic_layer_queries` on top of our normalized fact model. This is a typical DAG for a dbt project that contains semantic objects. Now let’s zoom in to the section of the DAG that contains our semantic layer objects and look in more detail at how we defined our semantic layer product metrics. + +## How we build semantic models and metrics + +What [is a semantic model](https://docs.getdbt.com/docs/build/semantic-models)? Put simply, semantic models contain the components we need to build metrics. Semantic models are YAML files that live in your dbt project. They contain metadata about your dbt models in a format that MetricFlow, the query builder that powers the semantic layer, can understand. The DAG below in [dbt Explorer](https://docs.getdbt.com/docs/collaborate/explore-projects) shows the metrics we’ve built off of `semantic_layer_queries`. + +![Screenshot 2023-10-11 at 4.41.13 PM.png](../static/img/blog/2023-12-11-semantic-layer-on-semantic-layer/Screenshot-metrics-dag.png) + + *Semantic Layer DAG in dbt Explorer* + +Let’s dig into semantic models and metrics a bit more, and explain some of the data modeling decisions we made. First, we needed to decide what model to use as a base for our semantic model. We decide to use`fct_semantic_layer`queries as our base model because defining a semantic model on top of a normalized fact table gives us maximum flexibility to join to other tables. This increased the number of dimensions available, which means we can answer more questions. + +You may wonder: why not just build our metrics on top of raw tables and let MetricFlow figure out the rest? The reality is, that you will almost almost always need to do some form of data modeling to create the data set you want to build your metrics off of. MetricFlow’s job isn’t to do data modeling. The transformation step is done with dbt. + +Next, we had to decide what we wanted to put into our semantic models. Semantic models contain [dimensions](https://docs.getdbt.com/docs/build/dimensions), [measures](https://docs.getdbt.com/docs/build/measures), and [entities](https://docs.getdbt.com/docs/build/entities). We took the following approach to add each of these components: + +- Dimensions: We included all the relevant dimensions in our semantic model that stakeholders might ask for, like the time a query was created, the query status, and booleans showing if a query contained certain elements like a where filter or multiple metrics. +- Entities: We added entities to our semantic model, like dbt cloud environment id. Entities function as join keys in semantic models, which means any other semantic models that have a j[oinable entity](https://docs.getdbt.com/docs/build/join-logic) can be used when querying metrics. +- Measures: Next we added Measures. Measures define the aggregation you want to run on your data. I think of measures as a metric primitive, we’ll use them to build metrics and can reuse them to keep our code [DRY](https://docs.getdbt.com/terms/dry). + +Finally, we reference the measures defined in our semantic model to create metrics. Our initial set of usage metrics are all relatively simple aggregations. For example, the total number of queries run. + +```yaml +metrics: + - name: queries + description: The total number of queries run + type: simple + label: Semantic Layer Queries + type_params: + measure: queries +``` + +*Queries metric configuration** + +Having our metrics in the semantic layer is powerful in a few ways. Firstly, metric definitions and the generated SQL are centralized, and live in our dbt project, instead of being scattered across BI tools or sql clients. Secondly, the types of queries I can run are dynamic and flexible. Traditionally, I would materialize a cube or rollup table which needs to contain all the different dimensional slices my users might be curious about. Now, users can join tables and add dimensionality to their metrics queries on the fly at query time, saving our data team cycles of updating and adding new fields to rollup tables. Thirdly, we can expose these metrics to a variety of downstream BI tools so stakeholders in product, finance, or GTM can understand product performance regardless of their technical skills. + +Now that we’ve done the pipeline work to set up our metrics for the semantic layer launch we’re ready to analyze how the launch went! + +## Our Finance, Operations and GTM teams are all looking at the same metrics 😊 + +To query to Semantic Layer you have two paths: you can query metrics directly through the Semantic Layer APIs or use one of our [first-class integrations](https://docs.getdbt.com/docs/use-dbt-semantic-layer/avail-sl-integrations). Our analytics team and product teams are big Hex users, while our operations and finance teams live and breathe Google Sheets, so it’s important for us to have the same metric definitions available in both tools. + +The leg work of building our pipeline and defining metrics is all done, which makes last-mile consumption much easier. First, we set up a launch dashboard in Hex as the source of truth for semantic layer product metrics. This tool is used by cross-functional partners like marketing, sales, and the executive team to easily check product and usage metrics like total semantic layer queries, or weekly active semantic layer users. To set up our Hex connection, we simply enter a few details from our dbt Cloud environment and then we can work with metrics directly in Hex notebooks. We can use the JDBC interface, or use Hex’s GUI metric builder to build reports. We run all our WBRs off this dashboard, which allows us to spot trends in consumption and react quickly to changes in our business. + +![Screenshot 2023-12-06 at 2.52.03 PM.png](../static/img/blog/2023-12-11-semantic-layer-on-semantic-layer/Screenshot-hex.png) + +*Semantic Layer query builder in Hex* + +On the finance and operations side, product usage data is crucial to making informed pricing decisions. All our pricing models are created in spreadsheets, so we leverage the Google Sheets integration to give those teams access to consistent data sets without the need to download CSVs from the Hex dashboard. This lets the Pricing team add dimensional slices, like tier and company size, to the data in a self-serve manner without having to request data team resources to generate those insights. This allows our finance team to iteratively build financial models and be more self-sufficient in pulling data, instead of relying on data team resources. + +![Screenshot 2023-12-06 at 2.56.18 PM.png](../static/img/blog/2023-12-11-semantic-layer-on-semantic-layer/Screenshot-gsheets.png) + + *Semantic Layer query builder in Google Sheets* + +As a former data scientist and data engineer, I personally think this is a huge improvement over the approach I would have used without the semantic layer. My old approach would have been to materialize One Big Table with all the numeric and categorical columns I needed for analysis. Then write a ton of SQL in Hex or various notebooks to create reports for stakeholders. Inevitably I’m signing up for more development cycles to update the pipeline whenever a new dimension needs to be added or the data needs to be aggregated in a slightly different way. From a data team management perspective, using a central semantic layer saves data analysts cycles since users can more easily self-serve. At every company I’ve ever worked at, data analysts are always in high demand, with more requests than they can reasonably accomplish. This means any time a stakeholder can self-serve their data without pulling us in is a huge win. + +## The Result: Consistent Governed Metrics + +And just like that, we have an end-to-end pipeline for product analytics on the dbt Semantic Layer using the dbt Semantic Layer 🤯. Part of the foundational work to build this pipeline will be familiar to you, like building out a normalized fact table using dbt. Hopefully walking through the next step of adding semantic models and metrics on top of those dbt models helped give you some ideas about how you can use the semantic layer for your team. Having launch metrics defined in dbt made keeping the entire organization up to date on product adoption and performance much easier. Instead of a rollup table or static materialized cubes, we added flexible metrics without rewriting logic in SQL, or adding additional tables to the end of our DAG. + +The result is access to consistent and governed metrics in the tool our stakeholders are already using to do their jobs. We are able to keep the entire organization aligned and give them access to consistent, accurate data they need to do their part to make the semantic layer product successful. Thanks for reading! If you’re thinking of using the semantic layer, or have questions we’re always happy to keep the conversation going in the [dbt community slack.](https://www.getdbt.com/community/join-the-community) Drop us a note in #dbt-cloud-semantic-layer. We’d love to hear from you! \ No newline at end of file diff --git a/website/blog/authors.yml b/website/blog/authors.yml index 31d69824ed4..cd2bd162935 100644 --- a/website/blog/authors.yml +++ b/website/blog/authors.yml @@ -287,6 +287,14 @@ jonathan_natkins: url: https://twitter.com/nattyice name: Jon "Natty" Natkins organization: dbt Labs +jordan_stein: + image_url: /img/blog/authors/jordan.jpeg + job_title: Product Manager + links: + - icon: fa-linkedin + url: https://www.linkedin.com/in/jstein5/ + name: Jordan Stein + organization: dbt Labs josh_fell: image_url: /img/blog/authors/josh-fell.jpeg diff --git a/website/static/img/blog/2023-12-11-semantic-layer-on-semantic-layer/Screenshot-dag.png b/website/static/img/blog/2023-12-11-semantic-layer-on-semantic-layer/Screenshot-dag.png new file mode 100644 index 0000000000000000000000000000000000000000..c053e595b778b0e65e32ca32e12345f858f4e566 GIT binary patch literal 290575 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Once you have set up your Host and Token and are able to run `databricks workspace ls /Users/`, you can proceed with the rest of this guide. -## Configure Databricks workflows for dbt Cloud jobs - -To use Databricks workflows for running dbt Cloud jobs, you need to perform the following steps: - -- [Set up a Databricks secret scope](#set-up-a-databricks-secret-scope) -- [Create a Databricks Python notebook](#create-a-databricks-python-notebook) -- [Configure the workflows to run the dbt Cloud jobs](#configure-the-workflows-to-run-the-dbt-cloud-jobs) - ## Set up a Databricks secret scope 1. Retrieve **[User API Token](https://docs.getdbt.com/docs/dbt-cloud-apis/user-tokens#user-api-tokens) **or **[Service Account Token](https://docs.getdbt.com/docs/dbt-cloud-apis/service-tokens#generating-service-account-tokens) **from dbt Cloud From a080863bb7bbe1b5695947be4aea5933bb0403d1 Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Tue, 12 Dec 2023 06:55:34 -0500 Subject: [PATCH 101/165] add more node operator examples --- website/docs/reference/node-selection/syntax.md | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/website/docs/reference/node-selection/syntax.md b/website/docs/reference/node-selection/syntax.md index 969db486c0e..22946903b7d 100644 --- a/website/docs/reference/node-selection/syntax.md +++ b/website/docs/reference/node-selection/syntax.md @@ -43,7 +43,6 @@ Select resources to build (run, test, seed, snapshot) or check freshness: `--sel By default, `dbt run` will execute _all_ of the models in the dependency graph. During development (and deployment), it is useful to specify only a subset of models to run. Use the `--select` flag with `dbt run` to select a subset of models to run. Note that the following arguments (`--select`, `--exclude`, and `--selector`) also apply to other dbt tasks, such as `test` and `build`. - @@ -81,7 +80,13 @@ Examples: ```bash # multiple arguments can be provided to --select - dbt run --select "my_first_model my_second_model" +dbt run --select "my_first_model my_second_model" + +# select my_model and all of its children +dbt run --select "my_model+" + +# select my_model, its children, and the parents of its children +dbt run --models @my_model # these arguments can be projects, models, directory paths, tags, or sources dbt run --select "tag:nightly my_model finance.base.*" From eda9ad9438f6776358661dc41b0c80b3e84fd65f Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Tue, 12 Dec 2023 07:41:51 -0500 Subject: [PATCH 102/165] add notice --- website/docs/docs/dbt-cloud-apis/sl-api-overview.md | 8 +++----- website/docs/docs/dbt-cloud-apis/sl-graphql.md | 6 +++--- website/docs/docs/dbt-cloud-apis/sl-jdbc.md | 6 +++--- website/docs/docs/dbt-cloud-apis/sl-manifest.md | 7 +++---- .../docs/use-dbt-semantic-layer/avail-sl-integrations.md | 8 ++++++++ website/docs/docs/use-dbt-semantic-layer/dbt-sl.md | 7 +++++++ website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md | 7 +++++++ website/docs/docs/use-dbt-semantic-layer/setup-sl.md | 8 ++++++++ .../docs/docs/use-dbt-semantic-layer/sl-architecture.md | 8 ++++++++ website/snippets/_sl-deprecation-notice.md | 6 ++---- 10 files changed, 52 insertions(+), 19 deletions(-) diff --git a/website/docs/docs/dbt-cloud-apis/sl-api-overview.md b/website/docs/docs/dbt-cloud-apis/sl-api-overview.md index 3ddbf76d152..6644d3e4b8b 100644 --- a/website/docs/docs/dbt-cloud-apis/sl-api-overview.md +++ b/website/docs/docs/dbt-cloud-apis/sl-api-overview.md @@ -9,10 +9,10 @@ pagination_next: "docs/dbt-cloud-apis/sl-jdbc" -import LegacyInfo from '/snippets/_legacy-sl-callout.md'; - - +import DeprecationNotice from '/snippets/_sl-deprecation-notice.md'; + + The rapid growth of different tools in the modern data stack has helped data professionals address the diverse needs of different teams. The downside of this growth is the fragmentation of business logic across teams, tools, and workloads. @@ -57,5 +57,3 @@ plan="dbt Cloud Team or Enterprise" icon="dbt-bit"/> - - diff --git a/website/docs/docs/dbt-cloud-apis/sl-graphql.md b/website/docs/docs/dbt-cloud-apis/sl-graphql.md index b7d13d0d453..3555b211f4f 100644 --- a/website/docs/docs/dbt-cloud-apis/sl-graphql.md +++ b/website/docs/docs/dbt-cloud-apis/sl-graphql.md @@ -7,10 +7,10 @@ tags: [Semantic Layer, APIs] -import LegacyInfo from '/snippets/_legacy-sl-callout.md'; - - +import DeprecationNotice from '/snippets/_sl-deprecation-notice.md'; + + diff --git a/website/docs/docs/dbt-cloud-apis/sl-jdbc.md b/website/docs/docs/dbt-cloud-apis/sl-jdbc.md index aba309566f8..45b012c67c6 100644 --- a/website/docs/docs/dbt-cloud-apis/sl-jdbc.md +++ b/website/docs/docs/dbt-cloud-apis/sl-jdbc.md @@ -7,10 +7,10 @@ tags: [Semantic Layer, API] -import LegacyInfo from '/snippets/_legacy-sl-callout.md'; - - +import DeprecationNotice from '/snippets/_sl-deprecation-notice.md'; + + The dbt Semantic Layer Java Database Connectivity (JDBC) API enables users to query metrics and dimensions using the JDBC protocol, while also providing standard metadata functionality. diff --git a/website/docs/docs/dbt-cloud-apis/sl-manifest.md b/website/docs/docs/dbt-cloud-apis/sl-manifest.md index 6ecac495869..eefa0bfc15e 100644 --- a/website/docs/docs/dbt-cloud-apis/sl-manifest.md +++ b/website/docs/docs/dbt-cloud-apis/sl-manifest.md @@ -9,10 +9,10 @@ pagination_next: null -import LegacyInfo from '/snippets/_legacy-sl-callout.md'; - - +import DeprecationNotice from '/snippets/_sl-deprecation-notice.md'; + + dbt creates an [artifact](/reference/artifacts/dbt-artifacts) file called the _Semantic Manifest_ (`semantic_manifest.json`), which MetricFlow requires to build and run metric queries properly for the dbt Semantic Layer. This artifact contains comprehensive information about your dbt Semantic Layer. It is an internal file that acts as the integration point with MetricFlow. @@ -97,4 +97,3 @@ Top-level keys for the semantic manifest are: - [dbt Semantic Layer API](/docs/dbt-cloud-apis/sl-api-overview) - [About dbt artifacts](/reference/artifacts/dbt-artifacts) - diff --git a/website/docs/docs/use-dbt-semantic-layer/avail-sl-integrations.md b/website/docs/docs/use-dbt-semantic-layer/avail-sl-integrations.md index 045838602a9..eb05fc75649 100644 --- a/website/docs/docs/use-dbt-semantic-layer/avail-sl-integrations.md +++ b/website/docs/docs/use-dbt-semantic-layer/avail-sl-integrations.md @@ -9,6 +9,14 @@ meta: api_name: dbt Semantic Layer APIs --- + + +import DeprecationNotice from '/snippets/_sl-deprecation-notice.md'; + + + + + There are a number of data applications that seamlessly integrate with the dbt Semantic Layer, powered by MetricFlow, from business intelligence tools to notebooks, spreadsheets, data catalogs, and more. These integrations allow you to query and unlock valuable insights from your data ecosystem. Use the [dbt Semantic Layer APIs](/docs/dbt-cloud-apis/sl-api-overview) to simplify metric queries, optimize your development workflow, and reduce coding. This approach also ensures data governance and consistency for data consumers. diff --git a/website/docs/docs/use-dbt-semantic-layer/dbt-sl.md b/website/docs/docs/use-dbt-semantic-layer/dbt-sl.md index cde9ae4afbb..ccbef5a6639 100644 --- a/website/docs/docs/use-dbt-semantic-layer/dbt-sl.md +++ b/website/docs/docs/use-dbt-semantic-layer/dbt-sl.md @@ -9,6 +9,13 @@ pagination_next: "docs/use-dbt-semantic-layer/quickstart-sl" pagination_prev: null --- + + +import DeprecationNotice from '/snippets/_sl-deprecation-notice.md'; + + + + The dbt Semantic Layer, powered by [MetricFlow](/docs/build/about-metricflow), simplifies the process of defining and using critical business metrics, like `revenue` in the modeling layer (your dbt project). By centralizing metric definitions, data teams can ensure consistent self-service access to these metrics in downstream data tools and applications. The dbt Semantic Layer eliminates duplicate coding by allowing data teams to define metrics on top of existing models and automatically handles data joins. diff --git a/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md b/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md index 9625621562e..3d8cdb5a56b 100644 --- a/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md +++ b/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md @@ -8,6 +8,13 @@ meta: api_name: dbt Semantic Layer APIs --- + + +import DeprecationNotice from '/snippets/_sl-deprecation-notice.md'; + + + + import CreateModel from '/snippets/_sl-create-semanticmodel.md'; import DefineMetrics from '/snippets/_sl-define-metrics.md'; diff --git a/website/docs/docs/use-dbt-semantic-layer/setup-sl.md b/website/docs/docs/use-dbt-semantic-layer/setup-sl.md index 0944e5ce1e1..1016de1830a 100644 --- a/website/docs/docs/use-dbt-semantic-layer/setup-sl.md +++ b/website/docs/docs/use-dbt-semantic-layer/setup-sl.md @@ -6,6 +6,14 @@ sidebar_label: "Set up your Semantic Layer" tags: [Semantic Layer] --- + + +import DeprecationNotice from '/snippets/_sl-deprecation-notice.md'; + + + + + With the dbt Semantic Layer, you can centrally define business metrics, reduce code duplication and inconsistency, create self-service in downstream tools, and more. Configure the dbt Semantic Layer in dbt Cloud to connect with your integrated partner tool. ## Prerequisites diff --git a/website/docs/docs/use-dbt-semantic-layer/sl-architecture.md b/website/docs/docs/use-dbt-semantic-layer/sl-architecture.md index f1fd13944e9..459fcfc487f 100644 --- a/website/docs/docs/use-dbt-semantic-layer/sl-architecture.md +++ b/website/docs/docs/use-dbt-semantic-layer/sl-architecture.md @@ -7,6 +7,14 @@ tags: [Semantic Layer] pagination_next: null --- + + +import DeprecationNotice from '/snippets/_sl-deprecation-notice.md'; + + + + + The dbt Semantic Layer allows you to define metrics and use various interfaces to query them. The Semantic Layer does the heavy lifting to find where the queried data exists in your data platform and generates the SQL to make the request (including performing joins). diff --git a/website/snippets/_sl-deprecation-notice.md b/website/snippets/_sl-deprecation-notice.md index 19bf19c2d90..d19dd78ca15 100644 --- a/website/snippets/_sl-deprecation-notice.md +++ b/website/snippets/_sl-deprecation-notice.md @@ -1,7 +1,5 @@ :::info Deprecation of dbt Metrics and the legacy dbt Semantic Layer -For users of the dbt Semantic Layer on version 1.5 or lower — Support for dbt Metrics and the legacy dbt Semantic Layer ends on December 15th, 2023. To access the latest features, migrate to the updated version using the [dbt Semantic Layer migration guide](/guides/sl-migration). - - -After December 15th, dbt Labs will no longer support these deprecated features, they will be removed from the dbt Cloud user interface, and their documentation removed from the docs site. +dbt Labs has deprecated dbt Metrics and the legacy dbt Semantic Layer, both supported on dbt version 1.5 or lower. These changes went into effect on December 15th, 2023. +To switch over and access [MetricFlow](/docs/build/build-metrics-intro) or the re-released dbt Semantic Layer, use the [dbt Semantic Layer migration guide](/guides/sl-migration) and [upgrade your version](/docs/dbt-versions/upgrade-core-in-cloud) in dbt Cloud. ::: From a7612764497537d23987f148a4d7e52b2cbfff7b Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Tue, 12 Dec 2023 07:44:25 -0500 Subject: [PATCH 103/165] update notice --- .../docs/use-dbt-semantic-layer/quickstart-sl.md | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md b/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md index 3d8cdb5a56b..665260ed9f4 100644 --- a/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md +++ b/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md @@ -8,6 +8,13 @@ meta: api_name: dbt Semantic Layer APIs --- +import CreateModel from '/snippets/_sl-create-semanticmodel.md'; +import DefineMetrics from '/snippets/_sl-define-metrics.md'; +import ConfigMetric from '/snippets/_sl-configure-metricflow.md'; +import TestQuery from '/snippets/_sl-test-and-query-metrics.md'; +import ConnectQueryAPI from '/snippets/_sl-connect-and-query-api.md'; +import RunProdJob from '/snippets/_sl-run-prod-job.md'; + import DeprecationNotice from '/snippets/_sl-deprecation-notice.md'; @@ -16,13 +23,6 @@ import DeprecationNotice from '/snippets/_sl-deprecation-notice.md'; -import CreateModel from '/snippets/_sl-create-semanticmodel.md'; -import DefineMetrics from '/snippets/_sl-define-metrics.md'; -import ConfigMetric from '/snippets/_sl-configure-metricflow.md'; -import TestQuery from '/snippets/_sl-test-and-query-metrics.md'; -import ConnectQueryAPI from '/snippets/_sl-connect-and-query-api.md'; -import RunProdJob from '/snippets/_sl-run-prod-job.md'; - The dbt Semantic Layer, powered by [MetricFlow](/docs/build/about-metricflow), simplifies defining and using critical business metrics. It centralizes metric definitions, eliminates duplicate coding, and ensures consistent self-service access to metrics in downstream tools. From 4cdfdf65ad5f6dec6d890f397f03c28db0bba5e3 Mon Sep 17 00:00:00 2001 From: Amy Chen <46451573+amychen1776@users.noreply.github.com> Date: Tue, 12 Dec 2023 08:12:38 -0500 Subject: [PATCH 104/165] Update databricks-configs.md --- .../resource-configs/databricks-configs.md | 19 +++++++++++-------- 1 file changed, 11 insertions(+), 8 deletions(-) diff --git a/website/docs/reference/resource-configs/databricks-configs.md b/website/docs/reference/resource-configs/databricks-configs.md index 8426846997c..fb3c9e7f5c3 100644 --- a/website/docs/reference/resource-configs/databricks-configs.md +++ b/website/docs/reference/resource-configs/databricks-configs.md @@ -365,9 +365,18 @@ insert into analytics.replace_where_incremental ## Selecting compute per model -Beginning in version 1.7.2, you can assign which compute resource to use on a per-model basis. +Beginning in version 1.7.2, you can assign which compute resource to use on a per-model basis. For SQL models, you can select a SQL Warehouse (serverless or provisioned) or an all purpose cluster. For details on how this feature interacts with python models, see [Specifying compute for Python models](#specifying-compute-for-python-models). + +:::note + +This is an optional setting. If you do not configure this as shown below, we will default to the compute specified by http_path in the top level of the output section in your profile. +This is also the compute that will be used for tasks not associated with a particular model, such as gathering metadata for all tables in a schema. + +::: + + To take advantage of this capability, you will need to add compute blocks to your profile: @@ -500,12 +509,6 @@ select * from {{ ref('seed') }} -:::note - -In the absence of a specified compute, we will default to the compute specified by http_path in the top level of the output section in your profile. -This is also the compute that will be used for tasks not associated with a particular model, such as gathering metadata for all tables in a schema. - -::: To validate that the specified compute is being used, look for lines in your dbt.log like: @@ -525,7 +528,7 @@ Materializing a python model requires execution of SQL as well as python. Specifically, if your python model is incremental, the current execution pattern involves executing python to create a staging table that is then merged into your target table using SQL. The python code needs to run on an all purpose cluster, while the SQL code can run on an all purpose cluster or a SQL Warehouse. When you specify your `databricks_compute` for a python model, you are currently only specifying which compute to use when running the model-specific SQL. -If you wish to use a different compute for executing the python itself, you must specify an alternate `http_path` in the config for the model: +If you wish to use a different compute for executing the python itself, you must specify an alternate `http_path` in the config for the model. Please note that declaring a separate SQL compute and a python compute for your python dbt models is optional. If you wish to do this: From 52c289c47c2467f09dea2a917dd530b4d4ef889a Mon Sep 17 00:00:00 2001 From: Thomas Lento Date: Tue, 12 Dec 2023 09:05:49 -0800 Subject: [PATCH 105/165] Switch SCD example to entity type `natural` We recommend using the `natural` type for what is normally the `primary` entity in an SCD semantic model layout. The distinction is that `primary` indicates one row per entity value, while `natural` does not, and in an SCD context there is one row per entity value/time window set, rather than one row per entity value as in standard conformed dimension tables. --- website/docs/docs/build/dimensions.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/website/docs/docs/build/dimensions.md b/website/docs/docs/build/dimensions.md index 683ff730d3c..97e2fdd502e 100644 --- a/website/docs/docs/build/dimensions.md +++ b/website/docs/docs/build/dimensions.md @@ -252,7 +252,7 @@ This example shows how to create slowly changing dimensions (SCD) using a semant | 333 | 2 | 2020-08-19 | 2021-10-22| | 333 | 3 | 2021-10-22 | 2048-01-01| -Take note of the extra arguments under `validity_params`: `is_start` and `is_end`. These arguments indicate the columns in the SCD table that contain the start and end dates for each tier (or beginning or ending timestamp column for a dimensional value). +Take note of the extra arguments under `validity_params`: `is_start` and `is_end`. These arguments indicate the columns in the SCD table that contain the start and end dates for each tier (or beginning or ending timestamp column for a dimensional value). Note also the entity is tagged as `natural` - this is to distinguish it from a `primary` entity, where we expect one row per entity value. Here, we expect one row per entity value/validity window combination. ```yaml semantic_models: @@ -282,7 +282,7 @@ semantic_models: entities: - name: sales_person - type: primary + type: natural expr: sales_person_id ``` From 62def67a0d548d3bca1609acdfe62f61bf023876 Mon Sep 17 00:00:00 2001 From: Thomas Lento Date: Tue, 12 Dec 2023 09:34:06 -0800 Subject: [PATCH 106/165] Apply suggestions from code review Co-authored-by: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> --- website/docs/docs/build/dimensions.md | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/website/docs/docs/build/dimensions.md b/website/docs/docs/build/dimensions.md index 97e2fdd502e..3c4edd9aef0 100644 --- a/website/docs/docs/build/dimensions.md +++ b/website/docs/docs/build/dimensions.md @@ -252,7 +252,8 @@ This example shows how to create slowly changing dimensions (SCD) using a semant | 333 | 2 | 2020-08-19 | 2021-10-22| | 333 | 3 | 2021-10-22 | 2048-01-01| -Take note of the extra arguments under `validity_params`: `is_start` and `is_end`. These arguments indicate the columns in the SCD table that contain the start and end dates for each tier (or beginning or ending timestamp column for a dimensional value). Note also the entity is tagged as `natural` - this is to distinguish it from a `primary` entity, where we expect one row per entity value. Here, we expect one row per entity value/validity window combination. + +The `validity_params` include two important arguments — `is_start` and `is_end`. These specify the columns in the SCD table that mark the start and end dates (or timestamps) for each tier or dimension. Additionally, the entity is tagged as `natural` to differentiate it from a `primary` entity. In a `primary` entity, each entity value has one row. In contrast, a `natural` entity has one row for each combination of entity value and its validity period. ```yaml semantic_models: @@ -280,6 +281,8 @@ semantic_models: - name: tier type: categorical + primary_entity: sales_person + entities: - name: sales_person type: natural From 7166bb7314a80c18a584965e5d67ced6f9444dae Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Tue, 12 Dec 2023 13:03:00 -0500 Subject: [PATCH 107/165] tweak --- .../release-notes/74-Dec-2023/legacy-sl.md | 31 +++++++++++++------ 1 file changed, 21 insertions(+), 10 deletions(-) diff --git a/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md b/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md index 11bd25a7020..c1949f8dfdc 100644 --- a/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md +++ b/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md @@ -8,23 +8,34 @@ date: 2023-12-15 dbt Labs has deprecated dbt Metrics and the legacy dbt Semantic Layer, both supported on dbt version 1.5 or lower. These changes will be in effect on _December 15th, 2023_. -This deprecation means dbt Metrics and the legacy Semantic Layer will no longer be supported. We will also remove the product from the dbt Cloud user interface and documentation site. +This deprecation means dbt Metrics and the legacy Semantic Layer will no longer be supported. We will also remove the feature from the dbt Cloud user interface and documentation site. ### Why this change? -We understand that changes of this nature can be disruptive and we believe in the potential of the new direction. The [re-released dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl), powered by MetricFlow, is a significantly improved foundation that enables more flexible query generation, faster performance, and a more dynamic consumption experience. It’s a step towards a brighter future for dbt and its community. +The [re-released dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl), powered by MetricFlow, offers enhanced flexibility, performance, and user experience, marking a significant advancement for the dbt community. -### Key changes +### Key changes and impact -- Legacy Semantic Layer and dbt Metrics will officially be deprecated on December 15th, 2023. -- MetricFlow has replaced dbt Metrics for the construction of semantic logic. The `dbt_metrics` package will no longer be supported. -- Exports replaces Materializations. Exports will be available in December or January in dbt Cloud and replaces the previous materializations functionality. +- **Deprecation date** — The legacy Semantic Layer and dbt Metrics will be officially deprecated on December 15th, 2023. +- **Replacement** — [MetricFlow](/docs/build/build-metrics-intro) replaces dbt Metrics for defining semantic logic. The `dbt_metrics` package will no longer be supported post-deprecation. +- **New feature** — Exports replaces the materializations functionality and will be available in dbt Cloud in December or January. -### Actions -- If you're using the legacy dbt Semantic Layer or dbt Metrics, use the [dbt Semantic Layer migration guide](/guides/sl-migration?step=1) to migrate over to the re-released dbt Semantic Layer. -- Engage and share feedback with the dbt Labs team and dbt Community slack using channels like [#dbt-cloud-semantic-layer](https://getdbt.slack.com/archives/C046L0VTVR6) and [#dbt-metricflow](https://getdbt.slack.com/archives/C02CCBBBR1D). Or reach out to your dbt Cloud account representative. -- Refer to some additional info and resources to help you upgrade your dbt version: +### Breaking changes and recommendations + +- For users on dbt version 1.6 and lower with dbt Metrics and Snowflake proxy: + - **Impact**: Post-deprecation, queries using the proxy _will not_ run. + - **Action required:** _Immediate_ migration is necessary. Refer to the [dbt Semantic Layer migration guide](/guides/sl-migration?step=1) + +- For users on dbt version 1.6 and lower using dbt Metrics without Snowflake proxy: + - **Impact**: No immediate disruption, but the package will not receive updates or support after deprecation + - **Recommendation**: Plan migration to the new Semantic Layer for compatibility with dbt version 1.6 and higher. + +### Engage and support + +- Feedback and community support — Engage and share feedback with the dbt Labs team and dbt Community slack using channels like [#dbt-cloud-semantic-layer](https://getdbt.slack.com/archives/C046L0VTVR6) and [#dbt-metricflow](https://getdbt.slack.com/archives/C02CCBBBR1D). Or reach out to your dbt Cloud account representative. + +- Resources for upgrading —Refer to some additional info and resources to help you upgrade your dbt version: - [Upgrade version in dbt Cloud](/docs/dbt-versions/upgrade-core-in-cloud) - [Version migration guides](/docs/dbt-versions/core-upgrade) From c84a378eba2a16cb041c0443c7c8e44fcdea6a40 Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Tue, 12 Dec 2023 13:03:46 -0500 Subject: [PATCH 108/165] change --- .../docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md b/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md index c1949f8dfdc..4c8d4278ef5 100644 --- a/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md +++ b/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md @@ -29,7 +29,7 @@ The [re-released dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl), power - For users on dbt version 1.6 and lower using dbt Metrics without Snowflake proxy: - **Impact**: No immediate disruption, but the package will not receive updates or support after deprecation - - **Recommendation**: Plan migration to the new Semantic Layer for compatibility with dbt version 1.6 and higher. + - **Recommendation**: Plan migration to the re-released Semantic Layer for compatibility with dbt version 1.6 and higher. ### Engage and support From b8095bc6fa033d64101659808eca3b4641a853d7 Mon Sep 17 00:00:00 2001 From: Jordan Date: Tue, 12 Dec 2023 10:08:16 -0800 Subject: [PATCH 109/165] Update website/blog/2023-12-11-semantic-layer-on-semantic-layer.md Co-authored-by: Jason Ganz --- website/blog/2023-12-11-semantic-layer-on-semantic-layer.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/blog/2023-12-11-semantic-layer-on-semantic-layer.md b/website/blog/2023-12-11-semantic-layer-on-semantic-layer.md index b321f0cd78d..1bc07d71e58 100644 --- a/website/blog/2023-12-11-semantic-layer-on-semantic-layer.md +++ b/website/blog/2023-12-11-semantic-layer-on-semantic-layer.md @@ -8,7 +8,7 @@ authors: [jordan_stein] tags: [dbt Cloud] hide_table_of_contents: false -date: 2023-12-11 +date: 2023-12-12 is_featured: false --- There’s nothing quite like the feeling of launching a new product. From a0b2d9d4262c2e300c6c384048be75b922bb6ea7 Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Tue, 12 Dec 2023 13:09:02 -0500 Subject: [PATCH 110/165] fi bullets --- .../docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md | 2 -- 1 file changed, 2 deletions(-) diff --git a/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md b/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md index 4c8d4278ef5..e940583c602 100644 --- a/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md +++ b/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md @@ -34,8 +34,6 @@ The [re-released dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl), power ### Engage and support - Feedback and community support — Engage and share feedback with the dbt Labs team and dbt Community slack using channels like [#dbt-cloud-semantic-layer](https://getdbt.slack.com/archives/C046L0VTVR6) and [#dbt-metricflow](https://getdbt.slack.com/archives/C02CCBBBR1D). Or reach out to your dbt Cloud account representative. - - Resources for upgrading —Refer to some additional info and resources to help you upgrade your dbt version: - - [Upgrade version in dbt Cloud](/docs/dbt-versions/upgrade-core-in-cloud) - [Version migration guides](/docs/dbt-versions/core-upgrade) From dc5320b82f97f8a866004e34eaa76ca461e1e747 Mon Sep 17 00:00:00 2001 From: Jordan Date: Tue, 12 Dec 2023 10:13:31 -0800 Subject: [PATCH 111/165] Update website/blog/2023-12-11-semantic-layer-on-semantic-layer.md Co-authored-by: Jason Ganz --- website/blog/2023-12-11-semantic-layer-on-semantic-layer.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/blog/2023-12-11-semantic-layer-on-semantic-layer.md b/website/blog/2023-12-11-semantic-layer-on-semantic-layer.md index 1bc07d71e58..1b93981287c 100644 --- a/website/blog/2023-12-11-semantic-layer-on-semantic-layer.md +++ b/website/blog/2023-12-11-semantic-layer-on-semantic-layer.md @@ -18,7 +18,7 @@ How many users do we have? How is performance looking? What features are custome At dbt we recently made the [Semantic Layer Generally Available](https://www.getdbt.com/blog/new-dbt-cloud-features-announced-at-coalesce-2023). The Semantic Layer lets teams define business metrics centrally, in dbt, and access them in multiple analytics tools through our semantic layer APIs. I’m a Product Manager on the Semantic Layer team, and the launch of the Semantic Layer put our team in an interesting, somewhat “meta,” position: we need to understand how a product launch is doing, and the product we just launched is designed to make defining and consuming metrics much more efficient. It’s the perfect opportunity to put the semantic layer through its paces for product analytics. This blog post walks through the end-to-end process we used to set up product analytics for the dbt Semantic Layer using the dbt Semantic Layer. - + ## Getting your data ready for metrics The first steps to building a product analytics pipeline with the Semantic Layer look the same as just using dbt - it’s all about data transformation. The steps we followed were broadly: From c90a2815cc2ca0f44a92adce1103683732059226 Mon Sep 17 00:00:00 2001 From: Jordan Date: Tue, 12 Dec 2023 10:14:20 -0800 Subject: [PATCH 112/165] Update 2023-12-11-semantic-layer-on-semantic-layer.md --- website/blog/2023-12-11-semantic-layer-on-semantic-layer.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/website/blog/2023-12-11-semantic-layer-on-semantic-layer.md b/website/blog/2023-12-11-semantic-layer-on-semantic-layer.md index 1b93981287c..4537f25ead1 100644 --- a/website/blog/2023-12-11-semantic-layer-on-semantic-layer.md +++ b/website/blog/2023-12-11-semantic-layer-on-semantic-layer.md @@ -37,7 +37,7 @@ There are [plenty of other great resources](https://docs.getdbt.com/docs/build/p Let’s walk through the DAG from left to right: First, we have raw tables from the Semantic Layer Server loaded into our warehouse, next we have staging models where we apply business logic and finally a clean, normalized `fct_semantic_layer_queries` model. Finally, we built a semantic model named `semantic_layer_queries` on top of our normalized fact model. This is a typical DAG for a dbt project that contains semantic objects. Now let’s zoom in to the section of the DAG that contains our semantic layer objects and look in more detail at how we defined our semantic layer product metrics. -## How we build semantic models and metrics +## [How we build semantic models and metrics](https://docs.getdbt.com/best-practices/how-we-build-our-metrics/semantic-layer-1-intro) What [is a semantic model](https://docs.getdbt.com/docs/build/semantic-models)? Put simply, semantic models contain the components we need to build metrics. Semantic models are YAML files that live in your dbt project. They contain metadata about your dbt models in a format that MetricFlow, the query builder that powers the semantic layer, can understand. The DAG below in [dbt Explorer](https://docs.getdbt.com/docs/collaborate/explore-projects) shows the metrics we’ve built off of `semantic_layer_queries`. @@ -95,4 +95,4 @@ As a former data scientist and data engineer, I personally think this is a huge And just like that, we have an end-to-end pipeline for product analytics on the dbt Semantic Layer using the dbt Semantic Layer 🤯. Part of the foundational work to build this pipeline will be familiar to you, like building out a normalized fact table using dbt. Hopefully walking through the next step of adding semantic models and metrics on top of those dbt models helped give you some ideas about how you can use the semantic layer for your team. Having launch metrics defined in dbt made keeping the entire organization up to date on product adoption and performance much easier. Instead of a rollup table or static materialized cubes, we added flexible metrics without rewriting logic in SQL, or adding additional tables to the end of our DAG. -The result is access to consistent and governed metrics in the tool our stakeholders are already using to do their jobs. We are able to keep the entire organization aligned and give them access to consistent, accurate data they need to do their part to make the semantic layer product successful. Thanks for reading! If you’re thinking of using the semantic layer, or have questions we’re always happy to keep the conversation going in the [dbt community slack.](https://www.getdbt.com/community/join-the-community) Drop us a note in #dbt-cloud-semantic-layer. We’d love to hear from you! \ No newline at end of file +The result is access to consistent and governed metrics in the tool our stakeholders are already using to do their jobs. We are able to keep the entire organization aligned and give them access to consistent, accurate data they need to do their part to make the semantic layer product successful. Thanks for reading! If you’re thinking of using the semantic layer, or have questions we’re always happy to keep the conversation going in the [dbt community slack.](https://www.getdbt.com/community/join-the-community) Drop us a note in #dbt-cloud-semantic-layer. We’d love to hear from you! From 4ddba3212e6d29a2d123d914f061d29a652a85ee Mon Sep 17 00:00:00 2001 From: Jordan Stein Date: Mon, 11 Dec 2023 20:12:48 -0800 Subject: [PATCH 113/165] update images --- ...023-12-11-semantic-layer-on-semantic-layer.md | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/website/blog/2023-12-11-semantic-layer-on-semantic-layer.md b/website/blog/2023-12-11-semantic-layer-on-semantic-layer.md index 4537f25ead1..18e8ca96a81 100644 --- a/website/blog/2023-12-11-semantic-layer-on-semantic-layer.md +++ b/website/blog/2023-12-11-semantic-layer-on-semantic-layer.md @@ -29,9 +29,10 @@ The first steps to building a product analytics pipeline with the Semantic Layer There are [plenty of other great resources](https://docs.getdbt.com/docs/build/projects) on how to accomplish the above steps, I’m going to skip that in this post and focus on how we built business metrics using the Semantic Layer. Once the data is loaded and modeling is complete, our DAG for the Semantic Layer data looks like the following: -![Screenshot 2023-09-28 at 4.05.25 PM.png](../static/img/blog/2023-12-11-semantic-layer-on-semantic-layer/Screenshot-dag.png) -*Good old-fashioned debt DAG, with an extra node at the end* + + + @@ -41,9 +42,8 @@ Let’s walk through the DAG from left to right: First, we have raw tables from What [is a semantic model](https://docs.getdbt.com/docs/build/semantic-models)? Put simply, semantic models contain the components we need to build metrics. Semantic models are YAML files that live in your dbt project. They contain metadata about your dbt models in a format that MetricFlow, the query builder that powers the semantic layer, can understand. The DAG below in [dbt Explorer](https://docs.getdbt.com/docs/collaborate/explore-projects) shows the metrics we’ve built off of `semantic_layer_queries`. -![Screenshot 2023-10-11 at 4.41.13 PM.png](../static/img/blog/2023-12-11-semantic-layer-on-semantic-layer/Screenshot-metrics-dag.png) + - *Semantic Layer DAG in dbt Explorer* Let’s dig into semantic models and metrics a bit more, and explain some of the data modeling decisions we made. First, we needed to decide what model to use as a base for our semantic model. We decide to use`fct_semantic_layer`queries as our base model because defining a semantic model on top of a normalized fact table gives us maximum flexibility to join to other tables. This increased the number of dimensions available, which means we can answer more questions. @@ -79,15 +79,15 @@ To query to Semantic Layer you have two paths: you can query metrics directly th The leg work of building our pipeline and defining metrics is all done, which makes last-mile consumption much easier. First, we set up a launch dashboard in Hex as the source of truth for semantic layer product metrics. This tool is used by cross-functional partners like marketing, sales, and the executive team to easily check product and usage metrics like total semantic layer queries, or weekly active semantic layer users. To set up our Hex connection, we simply enter a few details from our dbt Cloud environment and then we can work with metrics directly in Hex notebooks. We can use the JDBC interface, or use Hex’s GUI metric builder to build reports. We run all our WBRs off this dashboard, which allows us to spot trends in consumption and react quickly to changes in our business. -![Screenshot 2023-12-06 at 2.52.03 PM.png](../static/img/blog/2023-12-11-semantic-layer-on-semantic-layer/Screenshot-hex.png) -*Semantic Layer query builder in Hex* + + On the finance and operations side, product usage data is crucial to making informed pricing decisions. All our pricing models are created in spreadsheets, so we leverage the Google Sheets integration to give those teams access to consistent data sets without the need to download CSVs from the Hex dashboard. This lets the Pricing team add dimensional slices, like tier and company size, to the data in a self-serve manner without having to request data team resources to generate those insights. This allows our finance team to iteratively build financial models and be more self-sufficient in pulling data, instead of relying on data team resources. -![Screenshot 2023-12-06 at 2.56.18 PM.png](../static/img/blog/2023-12-11-semantic-layer-on-semantic-layer/Screenshot-gsheets.png) - *Semantic Layer query builder in Google Sheets* + + As a former data scientist and data engineer, I personally think this is a huge improvement over the approach I would have used without the semantic layer. My old approach would have been to materialize One Big Table with all the numeric and categorical columns I needed for analysis. Then write a ton of SQL in Hex or various notebooks to create reports for stakeholders. Inevitably I’m signing up for more development cycles to update the pipeline whenever a new dimension needs to be added or the data needs to be aggregated in a slightly different way. From a data team management perspective, using a central semantic layer saves data analysts cycles since users can more easily self-serve. At every company I’ve ever worked at, data analysts are always in high demand, with more requests than they can reasonably accomplish. This means any time a stakeholder can self-serve their data without pulling us in is a huge win. From 4ab9c07dd03cbefbf3bb3a498f23d5d44fb73078 Mon Sep 17 00:00:00 2001 From: Jordan Stein Date: Tue, 12 Dec 2023 10:19:41 -0800 Subject: [PATCH 114/165] update caption for metric config --- website/blog/2023-12-11-semantic-layer-on-semantic-layer.md | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/website/blog/2023-12-11-semantic-layer-on-semantic-layer.md b/website/blog/2023-12-11-semantic-layer-on-semantic-layer.md index 18e8ca96a81..1b80297bb44 100644 --- a/website/blog/2023-12-11-semantic-layer-on-semantic-layer.md +++ b/website/blog/2023-12-11-semantic-layer-on-semantic-layer.md @@ -58,6 +58,7 @@ Next, we had to decide what we wanted to put into our semantic models. Semantic Finally, we reference the measures defined in our semantic model to create metrics. Our initial set of usage metrics are all relatively simple aggregations. For example, the total number of queries run. ```yaml +## Example of a metric definition metrics: - name: queries description: The total number of queries run @@ -67,8 +68,6 @@ metrics: measure: queries ``` -*Queries metric configuration** - Having our metrics in the semantic layer is powerful in a few ways. Firstly, metric definitions and the generated SQL are centralized, and live in our dbt project, instead of being scattered across BI tools or sql clients. Secondly, the types of queries I can run are dynamic and flexible. Traditionally, I would materialize a cube or rollup table which needs to contain all the different dimensional slices my users might be curious about. Now, users can join tables and add dimensionality to their metrics queries on the fly at query time, saving our data team cycles of updating and adding new fields to rollup tables. Thirdly, we can expose these metrics to a variety of downstream BI tools so stakeholders in product, finance, or GTM can understand product performance regardless of their technical skills. Now that we’ve done the pipeline work to set up our metrics for the semantic layer launch we’re ready to analyze how the launch went! From 3d38463b2ea1a0267a5f82b0de765d4d00171c59 Mon Sep 17 00:00:00 2001 From: Jordan Stein Date: Tue, 12 Dec 2023 10:22:34 -0800 Subject: [PATCH 115/165] remove beta flag --- .../how-we-build-our-metrics/semantic-layer-1-intro.md | 4 ---- 1 file changed, 4 deletions(-) diff --git a/website/docs/best-practices/how-we-build-our-metrics/semantic-layer-1-intro.md b/website/docs/best-practices/how-we-build-our-metrics/semantic-layer-1-intro.md index 19c6717063c..ee3d4262882 100644 --- a/website/docs/best-practices/how-we-build-our-metrics/semantic-layer-1-intro.md +++ b/website/docs/best-practices/how-we-build-our-metrics/semantic-layer-1-intro.md @@ -4,10 +4,6 @@ description: Getting started with the dbt and MetricFlow hoverSnippet: Learn how to get started with the dbt and MetricFlow --- -:::tip -**This is a guide for a beta product.** We anticipate this guide will evolve alongside the Semantic Layer through community collaboration. We welcome discussions, ideas, issues, and contributions to refining best practices. -::: - Flying cars, hoverboards, and true self-service analytics: this is the future we were promised. The first two might still be a few years out, but real self-service analytics is here today. With dbt Cloud's Semantic Layer, you can resolve the tension between accuracy and flexibility that has hampered analytics tools for years, empowering everybody in your organization to explore a shared reality of metrics. Best of all for analytics engineers, building with these new tools will significantly [DRY](https://docs.getdbt.com/terms/dry) up and simplify your codebase. As you'll see, the deep interaction between your dbt models and the Semantic Layer make your dbt project the ideal place to craft your metrics. ## Learning goals From 279238f500dbdef1a30ea098a4d48318757aa0a7 Mon Sep 17 00:00:00 2001 From: Mike Alfare <13974384+mikealfare@users.noreply.github.com> Date: Tue, 12 Dec 2023 18:06:04 -0500 Subject: [PATCH 116/165] Update website/docs/reference/resource-configs/bigquery-configs.md Co-authored-by: Doug Beatty <44704949+dbeatty10@users.noreply.github.com> --- website/docs/reference/resource-configs/bigquery-configs.md | 1 - 1 file changed, 1 deletion(-) diff --git a/website/docs/reference/resource-configs/bigquery-configs.md b/website/docs/reference/resource-configs/bigquery-configs.md index ea20be4fb41..9e61a8d5265 100644 --- a/website/docs/reference/resource-configs/bigquery-configs.md +++ b/website/docs/reference/resource-configs/bigquery-configs.md @@ -752,7 +752,6 @@ with the following configuration parameters: -directly to the materialized view in place. ```yaml models: From 06e7ad826d952b54c466779f742bcb60e65b7f5d Mon Sep 17 00:00:00 2001 From: Doug Beatty <44704949+dbeatty10@users.noreply.github.com> Date: Tue, 12 Dec 2023 16:41:34 -0700 Subject: [PATCH 117/165] Fix missing end backtick for config name --- .../core-upgrade/11-Older versions/upgrading-to-0-14-0.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/docs/dbt-versions/core-upgrade/11-Older versions/upgrading-to-0-14-0.md b/website/docs/docs/dbt-versions/core-upgrade/11-Older versions/upgrading-to-0-14-0.md index 036a9a2aedf..48aa14a42e5 100644 --- a/website/docs/docs/dbt-versions/core-upgrade/11-Older versions/upgrading-to-0-14-0.md +++ b/website/docs/docs/dbt-versions/core-upgrade/11-Older versions/upgrading-to-0-14-0.md @@ -189,7 +189,7 @@ models: -**Configuring the `incremental_strategy for a single model:** +**Configuring the `incremental_strategy` for a single model:** From 219dfcc92ad84dea5df5380128dfb845904f1b12 Mon Sep 17 00:00:00 2001 From: Doug Beatty <44704949+dbeatty10@users.noreply.github.com> Date: Tue, 12 Dec 2023 17:09:21 -0700 Subject: [PATCH 118/165] OSS expectations for testing in pull requests --- website/docs/community/resources/oss-expectations.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/website/docs/community/resources/oss-expectations.md b/website/docs/community/resources/oss-expectations.md index 9c916de1240..762e87d97fb 100644 --- a/website/docs/community/resources/oss-expectations.md +++ b/website/docs/community/resources/oss-expectations.md @@ -94,6 +94,8 @@ PRs are your surest way to make the change you want to see in dbt / packages / d **Every PR should be associated with an issue.** Why? Before you spend a lot of time working on a contribution, we want to make sure that your proposal will be accepted. You should open an issue first, describing your desired outcome and outlining your planned change. If you've found an older issue that's already open, comment on it with an outline for your planned implementation. Exception to this rule: If you're just opening a PR for a cosmetic fix, such as a typo in documentation, an issue isn't needed. +**PRs should include robust testing.** With the goal to substantially cut down the number and impact of regressions, we are taking a more meticulous approach to the tests that we require to merge a pull request. We recognize that robust testing can often take significantly more effort than the main portion of the code. Thank you for your help in contributing to this goal! + **Our goal is to review most new PRs within 7 days.** The first review will include some high-level comments about the implementation, including (at a high level) whether it’s something we think suitable to merge. Depending on the scope of the PR, the first review may include line-level code suggestions, or we may delay specific code review until the PR is more finalized / until we have more time. **Automation that can help us:** Many repositories have a template for pull request descriptions, which will include a checklist that must be completed before the PR can be merged. You don’t have to do all of these things to get an initial PR, but they definitely help. Those many include things like: From 254c514b590bd96575883b66566ab5bc83dd9f75 Mon Sep 17 00:00:00 2001 From: Joel Labes Date: Wed, 13 Dec 2023 16:45:05 +1300 Subject: [PATCH 119/165] Fix typos in blog name and description --- website/blog/2023-12-11-semantic-layer-on-semantic-layer.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/website/blog/2023-12-11-semantic-layer-on-semantic-layer.md b/website/blog/2023-12-11-semantic-layer-on-semantic-layer.md index 1b80297bb44..ea77072a6dd 100644 --- a/website/blog/2023-12-11-semantic-layer-on-semantic-layer.md +++ b/website/blog/2023-12-11-semantic-layer-on-semantic-layer.md @@ -1,6 +1,6 @@ --- -title: "How we built consitent product launch metrics with the dbt Semantic Layer." -description: "We built and end-to-end data pipeline for measuring the launch of the dbt Semantic Layer using the dbt Semantic Layer." +title: "How we built consistent product launch metrics with the dbt Semantic Layer." +description: "We built an end-to-end data pipeline for measuring the launch of the dbt Semantic Layer using the dbt Semantic Layer." slug: product-analytics-pipeline-with-dbt-semantic-layer authors: [jordan_stein] From 99a3ed283f118aba1463bf99a330669991108793 Mon Sep 17 00:00:00 2001 From: Erik Mathiesen Date: Wed, 13 Dec 2023 09:50:05 +0100 Subject: [PATCH 120/165] Update infer-dbt documentation to fix broken links and add configuration page. --- .../core/connect-data-platform/infer-setup.md | 25 +++++++++--- .../resource-configs/infer-configs.md | 39 +++++++++++++++++++ website/sidebars.js | 1 + 3 files changed, 59 insertions(+), 6 deletions(-) create mode 100644 website/docs/reference/resource-configs/infer-configs.md diff --git a/website/docs/docs/core/connect-data-platform/infer-setup.md b/website/docs/docs/core/connect-data-platform/infer-setup.md index 7642c553cc4..c04fba59a56 100644 --- a/website/docs/docs/core/connect-data-platform/infer-setup.md +++ b/website/docs/docs/core/connect-data-platform/infer-setup.md @@ -12,16 +12,21 @@ meta: slack_channel_name: n/a slack_channel_link: platform_name: 'Infer' - config_page: '/reference/resource-configs/no-configs' + config_page: '/reference/resource-configs/infer-configs' min_supported_version: n/a --- +:::info Vendor-supported plugin + +Certain core functionality may vary. If you would like to report a bug, request a feature, or contribute, you can check out the linked repository and open an issue. + +::: + import SetUpPages from '/snippets/_setup-pages-intro.md'; - ## Connecting to Infer with **dbt-infer** Infer allows you to perform advanced ML Analytics within SQL as if native to your data warehouse. @@ -30,10 +35,18 @@ you can build advanced analysis for any business use case. Read more about SQL-inf and Infer in the [Infer documentation](https://docs.getinfer.io/). The `dbt-infer` package allow you to use SQL-inf easily within your DBT models. -You can read more about the `dbt-infer` package itself and how it connecst to Infer in the [dbt-infer documentation](https://dbt.getinfer.io/). +You can read more about the `dbt-infer` package itself and how it connects to Infer in the [dbt-infer documentation](https://dbt.getinfer.io/). + +The dbt-infer adapter is maintained via PyPi and installed with pip. +To install the latest dbt-infer package simply run the following within the same shell as you run dbt. +```python +pip install dbt-infer +``` + +Versioning of dbt-infer follows the standard dbt versioning scheme - meaning if you are using dbt 1.2 the corresponding dbt-infer will be named 1.2.x where is the latest minor version number. Before using SQL-inf in your DBT models you need to setup an Infer account and generate an API-key for the connection. -You can read how to do that in the [Getting Started Guide](https://dbt.getinfer.io/docs/getting_started#sign-up-to-infer). +You can read how to do that in the [Getting Started Guide](https://docs.getinfer.io/docs/reference/integrations/dbt). The profile configuration in `profiles.yml` for `dbt-infer` should look something like this: @@ -101,10 +114,10 @@ as native SQL functions. Infer supports a number of SQL-inf commands, including `PREDICT`, `EXPLAIN`, `CLUSTER`, `SIMILAR_TO`, `TOPICS`, `SENTIMENT`. -You can read more about SQL-inf and the commands it supports in the [SQL-inf Reference Guide](https://docs.getinfer.io/docs/reference). +You can read more about SQL-inf and the commands it supports in the [SQL-inf Reference Guide](https://docs.getinfer.io/docs/category/commands). To get you started we will give a brief example here of what such a model might look like. -You can find other more complex examples on the [dbt-infer examples page](https://dbt.getinfer.io/docs/examples). +You can find other more complex examples in the [dbt-infer examples repo](https://github.com/inferlabs/dbt-infer-examples). In our simple example, we will show how to use a previous model 'user_features' to predict churn by predicting the column `has_churned`. diff --git a/website/docs/reference/resource-configs/infer-configs.md b/website/docs/reference/resource-configs/infer-configs.md new file mode 100644 index 00000000000..c4837806935 --- /dev/null +++ b/website/docs/reference/resource-configs/infer-configs.md @@ -0,0 +1,39 @@ +--- +title: "Infer configurations" +description: "Read this guide to understand how to configure Infer with dbt." +id: "infer-configs" +--- + + +## Authentication + +To connect to Infer from your dbt instance you need to set up a correct profile in your `profiles.yml`. + +The format of this should look like this: + + + +```yaml +: + target: + outputs: + : + type: infer + url: "" + username: "" + apikey: "" + data_config: + [configuration for your underlying data warehouse] +``` + + + +### Description of Infer Profile Fields + +| Field | Required | Description | +|------------|----------|---------------------------------------------------------------------------------------------------------------------------------------------------| +| `type` | Yes | Must be set to `infer`. This must be included either in `profiles.yml` or in the `dbt_project.yml` file. | +| `url` | Yes | The host name of the Infer server to connect to. Typically this is `https://app.getinfer.io`. | +| `username` | Yes | Your Infer username - the one you use to login. | +| `apikey` | Yes | Your Infer api key. | +| `data_config` | Yes | The configuration for your underlying data warehouse. The format of this follows the format of the configuration for your data warehouse adapter. | diff --git a/website/sidebars.js b/website/sidebars.js index 598fffc7f0d..ba00ba582b2 100644 --- a/website/sidebars.js +++ b/website/sidebars.js @@ -723,6 +723,7 @@ const sidebarSettings = { "reference/resource-configs/oracle-configs", "reference/resource-configs/upsolver-configs", "reference/resource-configs/starrocks-configs", + "reference/resource-configs/infer-configs", ], }, { From a4e83e41016851832a7107bfcd246724eabb877a Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Wed, 13 Dec 2023 07:17:50 -0500 Subject: [PATCH 121/165] Update website/snippets/_sl-deprecation-notice.md Co-authored-by: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> --- website/snippets/_sl-deprecation-notice.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/snippets/_sl-deprecation-notice.md b/website/snippets/_sl-deprecation-notice.md index d19dd78ca15..610b1574b7d 100644 --- a/website/snippets/_sl-deprecation-notice.md +++ b/website/snippets/_sl-deprecation-notice.md @@ -1,5 +1,5 @@ :::info Deprecation of dbt Metrics and the legacy dbt Semantic Layer dbt Labs has deprecated dbt Metrics and the legacy dbt Semantic Layer, both supported on dbt version 1.5 or lower. These changes went into effect on December 15th, 2023. -To switch over and access [MetricFlow](/docs/build/build-metrics-intro) or the re-released dbt Semantic Layer, use the [dbt Semantic Layer migration guide](/guides/sl-migration) and [upgrade your version](/docs/dbt-versions/upgrade-core-in-cloud) in dbt Cloud. +To migrate and access [MetricFlow](/docs/build/build-metrics-intro) or the re-released dbt Semantic Layer, use the [dbt Semantic Layer migration guide](/guides/sl-migration) and [upgrade your version](/docs/dbt-versions/upgrade-core-in-cloud) in dbt Cloud. ::: From 735edf3eada82d5628b523ff265f7cead70155fc Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Wed, 13 Dec 2023 07:18:14 -0500 Subject: [PATCH 122/165] Update website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md Co-authored-by: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> --- .../docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md b/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md index e940583c602..efb13132506 100644 --- a/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md +++ b/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md @@ -8,7 +8,7 @@ date: 2023-12-15 dbt Labs has deprecated dbt Metrics and the legacy dbt Semantic Layer, both supported on dbt version 1.5 or lower. These changes will be in effect on _December 15th, 2023_. -This deprecation means dbt Metrics and the legacy Semantic Layer will no longer be supported. We will also remove the feature from the dbt Cloud user interface and documentation site. +This deprecation means dbt Metrics and the legacy Semantic Layer are no longer supported. We also removed the feature from the dbt Cloud user interface and documentation site. ### Why this change? From 5a2b28ecac45fb4e347ea31bbf2aae39684e5bae Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Wed, 13 Dec 2023 07:19:24 -0500 Subject: [PATCH 123/165] Update website/snippets/_new-sl-setup.md Co-authored-by: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> --- website/snippets/_new-sl-setup.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/snippets/_new-sl-setup.md b/website/snippets/_new-sl-setup.md index c69cb23f425..a02481db33d 100644 --- a/website/snippets/_new-sl-setup.md +++ b/website/snippets/_new-sl-setup.md @@ -8,7 +8,7 @@ You can set up the dbt Semantic Layer in dbt Cloud at the environment and projec - You must have a successful run in your new environment. :::tip -If you've configured the legacy Semantic Layer, dbt Labs strongly recommends that you [upgrade your dbt version](/docs/dbt-versions/upgrade-core-in-cloud) to dbt version 1.6 or higher to use the latest dbt Semantic Layer. Refer to the dedicated [migration guide](/guides/sl-migration) for details. +If you've configured the legacy Semantic Layer, it has been deprecated, and dbt Labs strongly recommends that you [upgrade your dbt version](/docs/dbt-versions/upgrade-core-in-cloud) to dbt version 1.6 or higher to use the latest dbt Semantic Layer. Refer to the dedicated [migration guide](/guides/sl-migration) for details. ::: 1. In dbt Cloud, create a new [deployment environment](/docs/deploy/deploy-environments#create-a-deployment-environment) or use an existing environment on dbt 1.6 or higher. From 1d66dfd2e538d6c84e3f1c1d076cf717b0145fbe Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Wed, 13 Dec 2023 07:32:16 -0500 Subject: [PATCH 124/165] Update website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md --- .../docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md b/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md index efb13132506..bc761d35e82 100644 --- a/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md +++ b/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md @@ -6,7 +6,7 @@ sidebar_position: 09 date: 2023-12-15 --- -dbt Labs has deprecated dbt Metrics and the legacy dbt Semantic Layer, both supported on dbt version 1.5 or lower. These changes will be in effect on _December 15th, 2023_. +dbt Labs has deprecated dbt Metrics and the legacy dbt Semantic Layer, both supported on dbt version 1.5 or lower. This change starts on December 15th, 2023. This deprecation means dbt Metrics and the legacy Semantic Layer are no longer supported. We also removed the feature from the dbt Cloud user interface and documentation site. From 0a73352bfa3de4ffa59190c83cbaa22005103857 Mon Sep 17 00:00:00 2001 From: Doug Beatty <44704949+dbeatty10@users.noreply.github.com> Date: Wed, 13 Dec 2023 08:41:17 -0700 Subject: [PATCH 125/165] Correct default incremental strategy for dbt-databricks `merge` has been the default since dbt-databricks 1.0.0: https://github.com/databricks/dbt-databricks/blob/7ad5507a8a38bde682bb28eb37466bbfc341ac94/CHANGELOG.md?plain=1#L404 --- website/docs/docs/build/incremental-models.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/website/docs/docs/build/incremental-models.md b/website/docs/docs/build/incremental-models.md index 3a597499f04..afff3950c44 100644 --- a/website/docs/docs/build/incremental-models.md +++ b/website/docs/docs/build/incremental-models.md @@ -256,7 +256,7 @@ The `merge` strategy is available in dbt-postgres and dbt-redshift beginning in | [dbt-redshift](/reference/resource-configs/redshift-configs#incremental-materialization-strategies) | `append` | `delete+insert` | | [dbt-bigquery](/reference/resource-configs/bigquery-configs#merge-behavior-incremental-models) | `merge` | `insert_overwrite` | | [dbt-spark](/reference/resource-configs/spark-configs#incremental-models) | `append` | `merge` (Delta only) `insert_overwrite` | -| [dbt-databricks](/reference/resource-configs/databricks-configs#incremental-models) | `append` | `merge` (Delta only) `insert_overwrite` | +| [dbt-databricks](/reference/resource-configs/databricks-configs#incremental-models) | `merge` | `append`, `insert_overwrite` | | [dbt-snowflake](/reference/resource-configs/snowflake-configs#merge-behavior-incremental-models) | `merge` | `append`, `delete+insert` | | [dbt-trino](/reference/resource-configs/trino-configs#incremental) | `append` | `merge` `delete+insert` | @@ -271,7 +271,7 @@ The `merge` strategy is available in dbt-postgres and dbt-redshift beginning in | [dbt-redshift](/reference/resource-configs/redshift-configs#incremental-materialization-strategies) | `append` | `merge`, `delete+insert` | | [dbt-bigquery](/reference/resource-configs/bigquery-configs#merge-behavior-incremental-models) | `merge` | `insert_overwrite` | | [dbt-spark](/reference/resource-configs/spark-configs#incremental-models) | `append` | `merge` (Delta only) `insert_overwrite` | -| [dbt-databricks](/reference/resource-configs/databricks-configs#incremental-models) | `append` | `merge` (Delta only) `insert_overwrite` | +| [dbt-databricks](/reference/resource-configs/databricks-configs#incremental-models) | `merge` | `append`, `insert_overwrite` | | [dbt-snowflake](/reference/resource-configs/snowflake-configs#merge-behavior-incremental-models) | `merge` | `append`, `delete+insert` | | [dbt-trino](/reference/resource-configs/trino-configs#incremental) | `append` | `merge` `delete+insert` | From 7d56df5d580e7954718292f2945354d2fada5307 Mon Sep 17 00:00:00 2001 From: Doug Beatty <44704949+dbeatty10@users.noreply.github.com> Date: Wed, 13 Dec 2023 09:18:09 -0700 Subject: [PATCH 126/165] Commas for consistency --- website/docs/docs/build/incremental-models.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/website/docs/docs/build/incremental-models.md b/website/docs/docs/build/incremental-models.md index afff3950c44..fc9a8313d60 100644 --- a/website/docs/docs/build/incremental-models.md +++ b/website/docs/docs/build/incremental-models.md @@ -258,7 +258,7 @@ The `merge` strategy is available in dbt-postgres and dbt-redshift beginning in | [dbt-spark](/reference/resource-configs/spark-configs#incremental-models) | `append` | `merge` (Delta only) `insert_overwrite` | | [dbt-databricks](/reference/resource-configs/databricks-configs#incremental-models) | `merge` | `append`, `insert_overwrite` | | [dbt-snowflake](/reference/resource-configs/snowflake-configs#merge-behavior-incremental-models) | `merge` | `append`, `delete+insert` | -| [dbt-trino](/reference/resource-configs/trino-configs#incremental) | `append` | `merge` `delete+insert` | +| [dbt-trino](/reference/resource-configs/trino-configs#incremental) | `append` | `merge`, `delete+insert` | @@ -273,7 +273,7 @@ The `merge` strategy is available in dbt-postgres and dbt-redshift beginning in | [dbt-spark](/reference/resource-configs/spark-configs#incremental-models) | `append` | `merge` (Delta only) `insert_overwrite` | | [dbt-databricks](/reference/resource-configs/databricks-configs#incremental-models) | `merge` | `append`, `insert_overwrite` | | [dbt-snowflake](/reference/resource-configs/snowflake-configs#merge-behavior-incremental-models) | `merge` | `append`, `delete+insert` | -| [dbt-trino](/reference/resource-configs/trino-configs#incremental) | `append` | `merge` `delete+insert` | +| [dbt-trino](/reference/resource-configs/trino-configs#incremental) | `append` | `merge`, `delete+insert` | From 55f9664e864cf5f580b36762aaa0388f049d93f0 Mon Sep 17 00:00:00 2001 From: Doug Beatty <44704949+dbeatty10@users.noreply.github.com> Date: Wed, 13 Dec 2023 09:24:18 -0700 Subject: [PATCH 127/165] Remove out-dated references to Delta --- website/docs/docs/build/incremental-models.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/website/docs/docs/build/incremental-models.md b/website/docs/docs/build/incremental-models.md index fc9a8313d60..f55870a3425 100644 --- a/website/docs/docs/build/incremental-models.md +++ b/website/docs/docs/build/incremental-models.md @@ -255,7 +255,7 @@ The `merge` strategy is available in dbt-postgres and dbt-redshift beginning in | [dbt-postgres](/reference/resource-configs/postgres-configs#incremental-materialization-strategies) | `append` | `delete+insert` | | [dbt-redshift](/reference/resource-configs/redshift-configs#incremental-materialization-strategies) | `append` | `delete+insert` | | [dbt-bigquery](/reference/resource-configs/bigquery-configs#merge-behavior-incremental-models) | `merge` | `insert_overwrite` | -| [dbt-spark](/reference/resource-configs/spark-configs#incremental-models) | `append` | `merge` (Delta only) `insert_overwrite` | +| [dbt-spark](/reference/resource-configs/spark-configs#incremental-models) | `append` | `merge`, `insert_overwrite` | | [dbt-databricks](/reference/resource-configs/databricks-configs#incremental-models) | `merge` | `append`, `insert_overwrite` | | [dbt-snowflake](/reference/resource-configs/snowflake-configs#merge-behavior-incremental-models) | `merge` | `append`, `delete+insert` | | [dbt-trino](/reference/resource-configs/trino-configs#incremental) | `append` | `merge`, `delete+insert` | @@ -270,7 +270,7 @@ The `merge` strategy is available in dbt-postgres and dbt-redshift beginning in | [dbt-postgres](/reference/resource-configs/postgres-configs#incremental-materialization-strategies) | `append` | `merge` , `delete+insert` | | [dbt-redshift](/reference/resource-configs/redshift-configs#incremental-materialization-strategies) | `append` | `merge`, `delete+insert` | | [dbt-bigquery](/reference/resource-configs/bigquery-configs#merge-behavior-incremental-models) | `merge` | `insert_overwrite` | -| [dbt-spark](/reference/resource-configs/spark-configs#incremental-models) | `append` | `merge` (Delta only) `insert_overwrite` | +| [dbt-spark](/reference/resource-configs/spark-configs#incremental-models) | `append` | `merge`, `insert_overwrite` | | [dbt-databricks](/reference/resource-configs/databricks-configs#incremental-models) | `merge` | `append`, `insert_overwrite` | | [dbt-snowflake](/reference/resource-configs/snowflake-configs#merge-behavior-incremental-models) | `merge` | `append`, `delete+insert` | | [dbt-trino](/reference/resource-configs/trino-configs#incremental) | `append` | `merge`, `delete+insert` | From 69ca5bab37fa9f6ef10a36007bb476e2c85bc3f5 Mon Sep 17 00:00:00 2001 From: Doug Beatty <44704949+dbeatty10@users.noreply.github.com> Date: Wed, 13 Dec 2023 09:26:28 -0700 Subject: [PATCH 128/165] Standardize width of markdown table --- website/docs/docs/build/incremental-models.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/website/docs/docs/build/incremental-models.md b/website/docs/docs/build/incremental-models.md index f55870a3425..01a392c12fe 100644 --- a/website/docs/docs/build/incremental-models.md +++ b/website/docs/docs/build/incremental-models.md @@ -258,7 +258,7 @@ The `merge` strategy is available in dbt-postgres and dbt-redshift beginning in | [dbt-spark](/reference/resource-configs/spark-configs#incremental-models) | `append` | `merge`, `insert_overwrite` | | [dbt-databricks](/reference/resource-configs/databricks-configs#incremental-models) | `merge` | `append`, `insert_overwrite` | | [dbt-snowflake](/reference/resource-configs/snowflake-configs#merge-behavior-incremental-models) | `merge` | `append`, `delete+insert` | -| [dbt-trino](/reference/resource-configs/trino-configs#incremental) | `append` | `merge`, `delete+insert` | +| [dbt-trino](/reference/resource-configs/trino-configs#incremental) | `append` | `merge`, `delete+insert` | @@ -267,13 +267,13 @@ The `merge` strategy is available in dbt-postgres and dbt-redshift beginning in | data platform adapter | default strategy | additional supported strategies | | :----------------- | :----------------| : ---------------------------------- | -| [dbt-postgres](/reference/resource-configs/postgres-configs#incremental-materialization-strategies) | `append` | `merge` , `delete+insert` | -| [dbt-redshift](/reference/resource-configs/redshift-configs#incremental-materialization-strategies) | `append` | `merge`, `delete+insert` | +| [dbt-postgres](/reference/resource-configs/postgres-configs#incremental-materialization-strategies) | `append` | `merge` , `delete+insert` | +| [dbt-redshift](/reference/resource-configs/redshift-configs#incremental-materialization-strategies) | `append` | `merge`, `delete+insert` | | [dbt-bigquery](/reference/resource-configs/bigquery-configs#merge-behavior-incremental-models) | `merge` | `insert_overwrite` | | [dbt-spark](/reference/resource-configs/spark-configs#incremental-models) | `append` | `merge`, `insert_overwrite` | | [dbt-databricks](/reference/resource-configs/databricks-configs#incremental-models) | `merge` | `append`, `insert_overwrite` | | [dbt-snowflake](/reference/resource-configs/snowflake-configs#merge-behavior-incremental-models) | `merge` | `append`, `delete+insert` | -| [dbt-trino](/reference/resource-configs/trino-configs#incremental) | `append` | `merge`, `delete+insert` | +| [dbt-trino](/reference/resource-configs/trino-configs#incremental) | `append` | `merge`, `delete+insert` | From 808336651e2b733db9ece174a06f7a277ee84a7c Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Wed, 13 Dec 2023 11:28:33 -0500 Subject: [PATCH 129/165] Update website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md --- .../docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md b/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md index bc761d35e82..df4616f4d43 100644 --- a/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md +++ b/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md @@ -18,7 +18,7 @@ The [re-released dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl), power - **Deprecation date** — The legacy Semantic Layer and dbt Metrics will be officially deprecated on December 15th, 2023. - **Replacement** — [MetricFlow](/docs/build/build-metrics-intro) replaces dbt Metrics for defining semantic logic. The `dbt_metrics` package will no longer be supported post-deprecation. -- **New feature** — Exports replaces the materializations functionality and will be available in dbt Cloud in December or January. +- **New feature** — Exports replaces the materializing data with `metrics.calculate` functionality and will be available in dbt Cloud in December or January. ### Breaking changes and recommendations From 1fc78210e06413cc8722b6d323298cdd92735ffe Mon Sep 17 00:00:00 2001 From: Mike Alfare Date: Wed, 13 Dec 2023 12:04:45 -0500 Subject: [PATCH 130/165] add link to description docs --- .../resource-configs/bigquery-configs.md | 30 +++++++++---------- 1 file changed, 15 insertions(+), 15 deletions(-) diff --git a/website/docs/reference/resource-configs/bigquery-configs.md b/website/docs/reference/resource-configs/bigquery-configs.md index 9e61a8d5265..d47562ec2bb 100644 --- a/website/docs/reference/resource-configs/bigquery-configs.md +++ b/website/docs/reference/resource-configs/bigquery-configs.md @@ -725,18 +725,18 @@ The `grant_access_to` config is not thread-safe when multiple views need to be a The BigQuery adapter supports [materialized views](https://cloud.google.com/bigquery/docs/materialized-views-intro) with the following configuration parameters: -| Parameter | Type | Required | Default | Change Monitoring Support | -|--------------------------------------------------------|------------------------|----------|---------|---------------------------| -| `on_configuration_change` | `` | no | `apply` | n/a | -| [`cluster_by`](#clustering-clause) | `[]` | no | `none` | drop/create | -| [`partition_by`](#partition-clause) | `{}` | no | `none` | drop/create | -| [`enable_refresh`](#auto-refresh) | `` | no | `true` | alter | -| [`refresh_interval_minutes`](#auto-refresh) | `` | no | `30` | alter | -| [`max_staleness`](#auto-refresh) (in Preview) | `` | no | `none` | alter | -| `description` | `` | no | `none` | alter | -| [`labels`](#specifying-labels) | `{: }` | no | `none` | alter | -| [`hours_to_expiration`](#controlling-table-expiration) | `` | no | `none` | alter | -| [`kms_key_name`](#using-kms-encryption) | `` | no | `none` | alter | +| Parameter | Type | Required | Default | Change Monitoring Support | +|-------------------------------------------------------------|------------------------|----------|---------|---------------------------| +| `on_configuration_change` | `` | no | `apply` | n/a | +| [`cluster_by`](#clustering-clause) | `[]` | no | `none` | drop/create | +| [`partition_by`](#partition-clause) | `{}` | no | `none` | drop/create | +| [`enable_refresh`](#auto-refresh) | `` | no | `true` | alter | +| [`refresh_interval_minutes`](#auto-refresh) | `` | no | `30` | alter | +| [`max_staleness`](#auto-refresh) (in Preview) | `` | no | `none` | alter | +| [`description`](/reference/resource-properties/description) | `` | no | `none` | alter | +| [`labels`](#specifying-labels) | `{: }` | no | `none` | alter | +| [`hours_to_expiration`](#controlling-table-expiration) | `` | no | `none` | alter | +| [`kms_key_name`](#using-kms-encryption) | `` | no | `none` | alter | [+](/reference/resource-configs/plus-prefix)[max_staleness](#auto-refresh): - [+](/reference/resource-configs/plus-prefix)description: + [+](/reference/resource-configs/plus-prefix)[description](/reference/resource-properties/description): [+](/reference/resource-configs/plus-prefix)[labels](#specifying-labels): {: } [+](/reference/resource-configs/plus-prefix)[hours_to_expiration](#acontrolling-table-expiration): [+](/reference/resource-configs/plus-prefix)[kms_key_name](##using-kms-encryption): @@ -809,7 +809,7 @@ models: [enable_refresh](#auto-refresh): true | false [refresh_interval_minutes](#auto-refresh): [max_staleness](#auto-refresh): - description: + [description](/reference/resource-properties/description): [labels](#specifying-labels): {: } [hours_to_expiration](#acontrolling-table-expiration): [kms_key_name](##using-kms-encryption): @@ -850,7 +850,7 @@ models: [max_staleness](#auto-refresh)="", # additional options - description="", + [description](/reference/resource-properties/description)="", [labels](#specifying-labels)={ "": "", }, From 8f1268241aad643772c0e9308eff5a2c7ada5ac8 Mon Sep 17 00:00:00 2001 From: Doug Beatty <44704949+dbeatty10@users.noreply.github.com> Date: Wed, 13 Dec 2023 10:13:54 -0700 Subject: [PATCH 131/165] Update description of robust testing --- website/docs/community/resources/oss-expectations.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/community/resources/oss-expectations.md b/website/docs/community/resources/oss-expectations.md index 762e87d97fb..a57df7fe67f 100644 --- a/website/docs/community/resources/oss-expectations.md +++ b/website/docs/community/resources/oss-expectations.md @@ -94,7 +94,7 @@ PRs are your surest way to make the change you want to see in dbt / packages / d **Every PR should be associated with an issue.** Why? Before you spend a lot of time working on a contribution, we want to make sure that your proposal will be accepted. You should open an issue first, describing your desired outcome and outlining your planned change. If you've found an older issue that's already open, comment on it with an outline for your planned implementation. Exception to this rule: If you're just opening a PR for a cosmetic fix, such as a typo in documentation, an issue isn't needed. -**PRs should include robust testing.** With the goal to substantially cut down the number and impact of regressions, we are taking a more meticulous approach to the tests that we require to merge a pull request. We recognize that robust testing can often take significantly more effort than the main portion of the code. Thank you for your help in contributing to this goal! +**PRs should include robust testing.** Comprehensive testing within pull requests is crucial for the stability of our project. By prioritizing robust testing, we ensure the reliability of our codebase, minimize unforeseen issues and safeguard against potential regressions. We understand that creating thorough tests often requires significant effort, and your dedication to this process greatly contributes to the project's overall reliability. Thank you for your commitment to maintaining the integrity of our codebase!" **Our goal is to review most new PRs within 7 days.** The first review will include some high-level comments about the implementation, including (at a high level) whether it’s something we think suitable to merge. Depending on the scope of the PR, the first review may include line-level code suggestions, or we may delay specific code review until the PR is more finalized / until we have more time. From 776e159ed5fc67e138965b071253ac44eaee54b2 Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Wed, 13 Dec 2023 12:36:52 -0500 Subject: [PATCH 132/165] Apply suggestions from code review --- .../resource-configs/bigquery-configs.md | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/website/docs/reference/resource-configs/bigquery-configs.md b/website/docs/reference/resource-configs/bigquery-configs.md index d47562ec2bb..d3497a02caf 100644 --- a/website/docs/reference/resource-configs/bigquery-configs.md +++ b/website/docs/reference/resource-configs/bigquery-configs.md @@ -866,7 +866,7 @@ models: Many of these parameters correspond to their table counterparts and have been linked above. -The set of parameters which are unique to materialized views covers auto-refresh functionality, which is covered [below](#auto-refresh). +The set of parameters unique to materialized views covers [auto-refresh functionality](#auto-refresh). Find more information about these parameters in the BigQuery docs: - [CREATE MATERIALIZED VIEW statement](https://cloud.google.com/bigquery/docs/reference/standard-sql/data-definition-language#create_materialized_view_statement) @@ -881,9 +881,9 @@ Find more information about these parameters in the BigQuery docs: | `max_staleness` (in Preview) | `` | no | `none` | alter | BigQuery supports [automatic refresh](https://cloud.google.com/bigquery/docs/materialized-views-manage#automatic_refresh) configuration for materialized views. -By default, a materialized view will automatically refresh within 5 minutes of changes in the base table, but no more frequently than every 30 minutes. -BigQuery only officially supports configuration of the frequency (the "30 minutes" part); -however, there is a feature in preview that allows for configuration of the staleness (the "5 minutes" part). +By default, a materialized view will automatically refresh within 5 minutes of changes in the base table, but not more frequently than once every 30 minutes. +BigQuery only officially supports the configuration of the frequency (the "once every 30 minutes" frequency); +however, there is a feature in preview that allows for the configuration of the staleness (the "5 minutes" refresh). dbt will monitor these parameters for changes and apply them using an `ALTER` statement. Find more information about these parameters in the BigQuery docs: @@ -894,11 +894,11 @@ Find more information about these parameters in the BigQuery docs: As with most data platforms, there are limitations associated with materialized views. Some worth noting include: -- Materialized view SQL has a [limited feature set](https://cloud.google.com/bigquery/docs/materialized-views-create#supported-mvs) -- Materialized view SQL cannot be updated; the materialized view must go through a `--full-refresh` (DROP/CREATE) -- The `partition_by` clause on a materialized view must match that of the underlying base table -- While materialized views can have descriptions, materialized view *columns* cannot -- Recreating/dropping the base table requires recreating/dropping the materialized view +- Materialized view SQL has a [limited feature set](https://cloud.google.com/bigquery/docs/materialized-views-create#supported-mvs). +- Materialized view SQL cannot be updated; the materialized view must go through a `--full-refresh` (DROP/CREATE). +- The `partition_by` clause on a materialized view must match that of the underlying base table. +- While materialized views can have descriptions, materialized view *columns* cannot. +- Recreating/dropping the base table requires recreating/dropping the materialized view. Find more information about materialized view limitations in Google's BigQuery [docs](https://cloud.google.com/bigquery/docs/materialized-views-intro#limitations). From 5d2fd560124e5cf89797a484f52abe3307da736d Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Wed, 13 Dec 2023 13:16:18 -0500 Subject: [PATCH 133/165] Update snowflake-configs.md --- .../resource-configs/snowflake-configs.md | 17 +++++++---------- 1 file changed, 7 insertions(+), 10 deletions(-) diff --git a/website/docs/reference/resource-configs/snowflake-configs.md b/website/docs/reference/resource-configs/snowflake-configs.md index a5c2e6f57d9..a24b072d39c 100644 --- a/website/docs/reference/resource-configs/snowflake-configs.md +++ b/website/docs/reference/resource-configs/snowflake-configs.md @@ -435,21 +435,18 @@ Find more information about these parameters in the Snowflake docs: ### Target lag -Snowflake allows two configuration scenarios for scheduling automatic refreshes: time-based and dependency-based. -For time-based automatic refreshes, provide a value of the form ` { seconds | minutes | hours | days }`. -For example, if the dynamic table needs to be updated every 30 minutes, use `target_lag='30 minutes'`. -However, for scenarios where the referenced objects are themselves dynamic tables, it might be desirable to refresh -the dynamic table whenever the underlying dynamic table is refreshed. In this scenario, use `target_lag='downstream'`. -This allows for refresh schedules to be controlled once, at the source, instead of at each layer. +Snowflake allows two configuration scenarios for scheduling automatic refreshes: +- **Time-based** — Provide a value of the form ` { seconds | minutes | hours | days }`. For example, if the dynamic table needs to be updated every 30 minutes, use `target_lag='30 minutes'`. +- **Downstream** — For scenarios where the referenced objects are themselves dynamic tables, it might be desirable to refresh the dynamic table whenever the underlying dynamic table is refreshed. In this scenario, use `target_lag='downstream'`. This allows for refresh schedules to be controlled once, at the source, instead of at each layer. ### Limitations As with materialized views on most data platforms, there are limitations associated with dynamic tables. Some worth noting include: -- Dynamic table SQL has a [limited feature set](https://docs.snowflake.com/en/user-guide/dynamic-tables-tasks-create#query-constructs-not-currently-supported-in-dynamic-tables) -- Dynamic table SQL cannot be updated; the dynamic table must go through a `--full-refresh` (DROP/CREATE) -- Dynamic tables cannot be downstream from: materialized views, external tables, streams -- Dynamic tables cannot reference a view that is downstream from another dynamic table +- Dynamic table SQL has a [limited feature set](https://docs.snowflake.com/en/user-guide/dynamic-tables-tasks-create#query-constructs-not-currently-supported-in-dynamic-tables). +- Dynamic table SQL cannot be updated; the dynamic table must go through a `--full-refresh` (DROP/CREATE). +- Dynamic tables cannot be downstream from: materialized views, external tables, streams. +- Dynamic tables cannot reference a view that is downstream from another dynamic table. Find more information about dynamic table limitations in Snowflake's [docs](https://docs.snowflake.com/en/user-guide/dynamic-tables-tasks-create#dynamic-table-limitations-and-supported-functions). From 9923e29b4820d489aaaad4957e010d5639bcc93b Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Wed, 13 Dec 2023 13:24:38 -0500 Subject: [PATCH 134/165] Apply suggestions from code review --- website/docs/reference/resource-configs/redshift-configs.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/website/docs/reference/resource-configs/redshift-configs.md b/website/docs/reference/resource-configs/redshift-configs.md index f610d19a346..b559c0451b0 100644 --- a/website/docs/reference/resource-configs/redshift-configs.md +++ b/website/docs/reference/resource-configs/redshift-configs.md @@ -202,7 +202,7 @@ models: Many of these parameters correspond to their table counterparts and have been linked above. -The parameters unique to materialized views are the auto-refresh and backup functionality, which are covered below. +The parameters unique to materialized views are the [auto-refresh](#auto-refresh) and [backup](#backup) functionality, which are covered below. Find more information about the [CREATE MATERIALIZED VIEW](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-create-sql-command.html) parameters in the Redshift docs. @@ -216,7 +216,7 @@ Redshift supports [automatic refresh](https://docs.aws.amazon.com/redshift/lates By default, a materialized view does not automatically refresh. dbt monitors this parameter for changes and applies them using an `ALTER` statement. -Find more information about the [parameters](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-create-sql-command.html#mv_CREATE_MATERIALIZED_VIEW-parameters) in the Redshift docs. +Learn more information about the [parameters](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-create-sql-command.html#mv_CREATE_MATERIALIZED_VIEW-parameters) in the Redshift docs. #### Backup @@ -230,7 +230,7 @@ By default, a materialized view will be backed up during a cluster snapshot. dbt cannot monitor this parameter as it is not queryable within Redshift. If the value is changed, the materialized view will need to go through a `--full-refresh` in order to set it. -Find more information about the [parameters](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-create-sql-command.html#mv_CREATE_MATERIALIZED_VIEW-parameters) in the Redshift docs. +Learn more about the [parameters](https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-create-sql-command.html#mv_CREATE_MATERIALIZED_VIEW-parameters) in the Redshift docs. ### Limitations From b84b59eba4b990ef6ca4c1c883b658f0a3f34bd7 Mon Sep 17 00:00:00 2001 From: Mike Alfare Date: Wed, 13 Dec 2023 14:11:45 -0500 Subject: [PATCH 135/165] update downstream option for target_lag, fix external docs reference to be consistent --- .../docs/reference/resource-configs/snowflake-configs.md | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/website/docs/reference/resource-configs/snowflake-configs.md b/website/docs/reference/resource-configs/snowflake-configs.md index a24b072d39c..aa2bf370df6 100644 --- a/website/docs/reference/resource-configs/snowflake-configs.md +++ b/website/docs/reference/resource-configs/snowflake-configs.md @@ -430,14 +430,15 @@ models: -Find more information about these parameters in the Snowflake docs: -- [CREATE DYNAMIC TABLE](https://docs.snowflake.com/en/sql-reference/sql/create-dynamic-table) +Find more information about these parameters in Snowflake's [docs](https://docs.snowflake.com/en/sql-reference/sql/create-dynamic-table): ### Target lag Snowflake allows two configuration scenarios for scheduling automatic refreshes: - **Time-based** — Provide a value of the form ` { seconds | minutes | hours | days }`. For example, if the dynamic table needs to be updated every 30 minutes, use `target_lag='30 minutes'`. -- **Downstream** — For scenarios where the referenced objects are themselves dynamic tables, it might be desirable to refresh the dynamic table whenever the underlying dynamic table is refreshed. In this scenario, use `target_lag='downstream'`. This allows for refresh schedules to be controlled once, at the source, instead of at each layer. +- **Downstream** — Applicable when the dynamic table is referenced by other dynamic tables. In this scenario, `target_lag='downstream'` allows for refreshes to be controlled at the target, instead of at each layer. + +Find more information about `target_lag` in Snowflake's [docs](https://docs.snowflake.com/en/user-guide/dynamic-tables-refresh#understanding-target-lag). ### Limitations From 6ac9d633d37c75762bfff7a349a13ffbb72bf4fd Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Wed, 13 Dec 2023 14:14:16 -0500 Subject: [PATCH 136/165] Apply suggestions from code review --- website/docs/reference/resource-configs/postgres-configs.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/website/docs/reference/resource-configs/postgres-configs.md b/website/docs/reference/resource-configs/postgres-configs.md index c904802d598..c01ea9ea718 100644 --- a/website/docs/reference/resource-configs/postgres-configs.md +++ b/website/docs/reference/resource-configs/postgres-configs.md @@ -194,9 +194,9 @@ models: -The `indexes` parameter corresponds to that of a table, as linked above. -It's worth noting that, unlike with tables, dbt will monitor this parameter for changes and apply the changes without dropping the materialized view. -This happens via a `DROP/CREATE` of the indexes, which could be thought of as a `ALTER` of the materialized view. +The [`indexes`](#indexes) parameter corresponds to that of a table, as explained above. +It's worth noting that, unlike with tables, dbt monitors this parameter for changes and applies the changes without dropping the materialized view. +This happens via a `DROP/CREATE` of the indexes, which can be thought of as an `ALTER` of the materialized view. Find more information about materialized view parameters in the Postgres docs: - [CREATE MATERIALIZED VIEW](https://www.postgresql.org/docs/current/sql-creatematerializedview.html) From e4b780cefa4fd7852ca593488faed5c150beb7d3 Mon Sep 17 00:00:00 2001 From: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> Date: Wed, 13 Dec 2023 14:14:42 -0500 Subject: [PATCH 137/165] Update website/docs/reference/resource-configs/postgres-configs.md --- website/docs/reference/resource-configs/postgres-configs.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/reference/resource-configs/postgres-configs.md b/website/docs/reference/resource-configs/postgres-configs.md index c01ea9ea718..8465a5cbb31 100644 --- a/website/docs/reference/resource-configs/postgres-configs.md +++ b/website/docs/reference/resource-configs/postgres-configs.md @@ -195,7 +195,7 @@ models: The [`indexes`](#indexes) parameter corresponds to that of a table, as explained above. -It's worth noting that, unlike with tables, dbt monitors this parameter for changes and applies the changes without dropping the materialized view. +It's worth noting that, unlike tables, dbt monitors this parameter for changes and applies the changes without dropping the materialized view. This happens via a `DROP/CREATE` of the indexes, which can be thought of as an `ALTER` of the materialized view. Find more information about materialized view parameters in the Postgres docs: From 0c9243f0ecc3075597b3ee06b794e810ecb36df3 Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Wed, 13 Dec 2023 15:15:27 -0500 Subject: [PATCH 138/165] Create index.js add javascript --- website/src/components/detailsToggle/index.js | 56 +++++++++++++++++++ 1 file changed, 56 insertions(+) create mode 100644 website/src/components/detailsToggle/index.js diff --git a/website/src/components/detailsToggle/index.js b/website/src/components/detailsToggle/index.js new file mode 100644 index 00000000000..1c571d6d033 --- /dev/null +++ b/website/src/components/detailsToggle/index.js @@ -0,0 +1,56 @@ +import React, { useState, useEffect } from 'react'; +import styles from './styles.module.css'; + +function DetailsToggle({ children, alt_header = null }) { + const [isOn, setOn] = useState(false); + const [hoverActive, setHoverActive] = useState(true); + const [hoverTimeout, setHoverTimeout] = useState(null); + + const handleToggleClick = () => { + setOn(!isOn); + setHoverActive(isOn); // Toggle hover activation based on current state + }; + + const handleMouseEnter = () => { + if (!hoverActive) return; // Ignore hover if disabled + const timeout = setTimeout(() => { + setOn(true); + }, 500); // 500ms delay + setHoverTimeout(timeout); + }; + + const handleMouseLeave = () => { + if (hoverActive) { + clearTimeout(hoverTimeout); + setOn(false); // Collapse content only if it was opened by hover + } + }; + + useEffect(() => { + return () => clearTimeout(hoverTimeout); + }, [hoverTimeout]); + + return ( +

    + ); +} + +export default DetailsToggle; From b43e0c9a15026df6353dc4634ffb001b1a8dcf05 Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Wed, 13 Dec 2023 15:15:58 -0500 Subject: [PATCH 139/165] Create styles.module.css add css for hover --- .../detailsToggle/styles.module.css | 51 +++++++++++++++++++ 1 file changed, 51 insertions(+) create mode 100644 website/src/components/detailsToggle/styles.module.css diff --git a/website/src/components/detailsToggle/styles.module.css b/website/src/components/detailsToggle/styles.module.css new file mode 100644 index 00000000000..446d3197128 --- /dev/null +++ b/website/src/components/detailsToggle/styles.module.css @@ -0,0 +1,51 @@ +:local(.link) { + color: var(--ifm-link-color); + transition: background-color 0.3s; /* Smooth transition for background color */ +} + +:local(.link:hover), :local(.link:focus) { + text-decoration: underline; + cursor: pointer; +} + +:local(.disclaimer) { + font-size: 0.8em; + color: #666; + margin-left: 10px; /* Adjust as needed */ +} + +:local(.toggle) { + background-image: var(--ifm-menu-link-sublist-icon); + background-size: 1.25rem 1.25rem; + background-position: center; + content: ' '; + display: inline-block; + height: 1.25rem; + width: 1.25rem; + vertical-align: middle; + transition: transform 0.3s; /* Smooth transition for toggle icon */ +} + +:local(.toggleUpsideDown) { + transform: rotateX(180deg) +} + +/* hack for unswizzled FAQ arrows */ +:local(html[data-theme='dark'] .toggle) { + filter: invert(1); +} + +:local(.body) { + margin-left: 2em; + margin-bottom: 10px; + padding: 20px; + background-color: #e3f8f8; +} + +:local(html[data-theme='dark'] .body) { + background: #333b47; +} + +:local(.body > p:last-child) { + margin-bottom: 0px; +} From 290059d9b7bce2ca5043eec28de153ff22d8250d Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Wed, 13 Dec 2023 15:16:45 -0500 Subject: [PATCH 140/165] Update index.js adding to the mdx them file so script runs --- website/src/theme/MDXComponents/index.js | 2 ++ 1 file changed, 2 insertions(+) diff --git a/website/src/theme/MDXComponents/index.js b/website/src/theme/MDXComponents/index.js index dead3375489..2a412e198f1 100644 --- a/website/src/theme/MDXComponents/index.js +++ b/website/src/theme/MDXComponents/index.js @@ -43,6 +43,7 @@ import CommunitySpotlightList from '@site/src/components/communitySpotlightList' import dbtEditor from '@site/src/components/dbt-editor'; import Icon from '@site/src/components/icon'; import Lifecycle from '@site/src/components/lifeCycle'; +import detailsToggle from '@site/src/components/detailsToggle'; const MDXComponents = { head: MDXHead, @@ -92,5 +93,6 @@ const MDXComponents = { dbtEditor: dbtEditor, Icon: Icon, Lifecycle: Lifecycle, + detailsToggle: detailsToggle, }; export default MDXComponents; From 86520bbea8cb0ec8e113b27a0a8a54e5890a0161 Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Wed, 13 Dec 2023 15:39:26 -0500 Subject: [PATCH 141/165] add detailsToggle to Sl docs --- website/snippets/_sl-faqs.md | 66 ++++++++++++++++++++++++------------ 1 file changed, 45 insertions(+), 21 deletions(-) diff --git a/website/snippets/_sl-faqs.md b/website/snippets/_sl-faqs.md index def8f3837f6..092929e1066 100644 --- a/website/snippets/_sl-faqs.md +++ b/website/snippets/_sl-faqs.md @@ -1,33 +1,57 @@ -- **Is the dbt Semantic Layer open source?** - - The dbt Semantic Layer is proprietary; however, some components of the dbt Semantic Layer are open source, such as dbt-core and MetricFlow. + - dbt Cloud Developer or dbt Core users can define metrics in their project, including a local dbt Core project, using the dbt Cloud IDE, dbt Cloud CLI, or dbt Core CLI. However, to experience the universal dbt Semantic Layer and access those metrics using the API or downstream tools, users must be on a dbt Cloud [Team or Enterprise](https://www.getdbt.com/pricing/) plan. +The dbt Semantic Layer is proprietary; however, some components of the dbt Semantic Layer are open source, such as dbt-core and MetricFlow. - Refer to [Billing](https://docs.getdbt.com/docs/cloud/billing) for more information. +dbt Cloud Developer or dbt Core users can define metrics in their project, including a local dbt Core project, using the dbt Cloud IDE, dbt Cloud CLI, or dbt Core CLI. However, to experience the universal dbt Semantic Layer and access those metrics using the API or downstream tools, users must be on a dbt Cloud [Team or Enterprise](https://www.getdbt.com/pricing/) plan. -- **How can open-source users use the dbt Semantic Layer?** - - The dbt Semantic Layer requires the use of the dbt Cloud-provided service for coordinating query requests. Open source users who don’t use dbt Cloud can currently work around the lack of a service layer. They can do this by running `mf query --explain` in the command line. This command generates SQL code, which they can then use in their current systems for running and managing queries. +Refer to Billing for more information. + + + + + +The dbt Semantic Layer requires the use of the dbt Cloud-provided service for coordinating query requests. Open source users who don’t use dbt Cloud can currently work around the lack of a service layer. They can do this by running `mf query --explain` in the command line. This command generates SQL code, which they can then use in their current systems for running and managing queries. - As we refine MetricFlow’s API layers, some users may find it easier to set up their own custom service layers for managing query requests. This is not currently recommended, as the API boundaries around MetricFlow are not sufficiently well-defined for broad-based community use +As we refine MetricFlow’s API layers, some users may find it easier to set up their own custom service layers for managing query requests. This is not currently recommended, as the API boundaries around MetricFlow are not sufficiently well-defined for broad-based community use + + -- **Why is my query limited to 100 rows in the dbt Cloud CLI?** -- The default `limit` for query issues from the dbt Cloud CLI is 100 rows. We set this default to prevent returning unnecessarily large data sets as the dbt Cloud CLI is typically used to query the dbt Semantic Layer during the development process, not for production reporting or to access large data sets. For most workflows, you only need to return a subset of the data. + + +The default `limit` for query issues from the dbt Cloud CLI is 100 rows. We set this default to prevent returning unnecessarily large data sets as the dbt Cloud CLI is typically used to query the dbt Semantic Layer during the development process, not for production reporting or to access large data sets. For most workflows, you only need to return a subset of the data. - However, you can change this limit if needed by setting the `--limit` option in your query. For example, to return 1000 rows, you can run `dbt sl list metrics --limit 1000`. +However, you can change this limit if needed by setting the `--limit` option in your query. For example, to return 1000 rows, you can run `dbt sl list metrics --limit 1000`. + + -- **Can I reference MetricFlow queries inside dbt models?** - - dbt relies on Jinja macros to compile SQL, while MetricFlow is Python-based and does direct SQL rendering targeting at a specific dialect. MetricFlow does not support pass-through rendering of Jinja macros, so we can’t easily reference MetricFlow queries inside of dbt models. + + +dbt relies on Jinja macros to compile SQL, while MetricFlow is Python-based and does direct SQL rendering targeting at a specific dialect. MetricFlow does not support pass-through rendering of Jinja macros, so we can’t easily reference MetricFlow queries inside of dbt models. - Beyond the technical challenges that could be overcome, we see Metrics as the leaf node of your DAG, and a place for users to consume metrics. If you need to do additional transformation on top of a metric, this is usually a sign that there is more modeling that needs to be done. +Beyond the technical challenges that could be overcome, we see Metrics as the leaf node of your DAG, and a place for users to consume metrics. If you need to do additional transformation on top of a metric, this is usually a sign that there is more modeling that needs to be done. + + + + + +You can use the upcoming feature, Exports, which will allow you to create a [pre-defined](/docs/build/saved-queries) MetricFlow query as a table in your data platform. This feature will be available to dbt Cloud customers only. This is because MetricFlow is primarily for query rendering while dispatching the relevant query and performing any DDL is the domain of the service layer on top of MetricFlow. + + + + + +If you're using the legacy Semantic Layer, we highly recommend you [upgrade your dbt version](/docs/dbt-versions/upgrade-core-in-cloud) to dbt v1.6 or higher to use the new dbt Semantic Layer. Refer to the dedicated [migration guide](/guides/sl-migration) for more info. + + + + + +User data passes through the Semantic Layer on its way back from the warehouse. dbt Labs ensures security by authenticating through the customer's data warehouse. Currently, we don't cache data for the long term, but it might temporarily stay in the system for up to 10 minutes, usually less. In the future, we'll introduce a caching feature that allows us to cache data on our infrastructure for up to 24 hours. -- **Can I create tables in my data platform using MetricFlow?** - - You can use the upcoming feature, Exports, which will allow you to create a [pre-defined](/docs/build/saved-queries) MetricFlow query as a table in your data platform. This feature will be available to dbt Cloud customers only. This is because MetricFlow is primarily for query rendering while dispatching the relevant query and performing any DDL is the domain of the service layer on top of MetricFlow. + -- **How do I migrate from the legacy Semantic Layer to the new one?** - - If you're using the legacy Semantic Layer, we highly recommend you [upgrade your dbt version](/docs/dbt-versions/upgrade-core-in-cloud) to dbt v1.6 or higher to use the new dbt Semantic Layer. Refer to the dedicated [migration guide](/guides/sl-migration) for more info. + -- **How are you storing my data?** - - User data passes through the Semantic Layer on its way back from the warehouse. dbt Labs ensures security by authenticating through the customer's data warehouse. Currently, we don't cache data for the long term, but it might temporarily stay in the system for up to 10 minutes, usually less. In the future, we'll introduce a caching feature that allows us to cache data on our infrastructure for up to 24 hours. +Yes absolutely! Join the [dbt Slack community](https://getdbt.slack.com) and [#dbt-cloud-semantic-layer slack channel](https://getdbt.slack.com/archives/C046L0VTVR6) for all things related to the dbt Semantic Layer. -- **Is there a dbt Semantic Layer discussion hub?** - - Yes absolutely! Join the [dbt Slack community](https://getdbt.slack.com) and [#dbt-cloud-semantic-layer slack channel](https://getdbt.slack.com/archives/C046L0VTVR6) for all things related to the dbt Semantic Layer. + From 726240a001a5f817b898c28ed74c66fe278a92f0 Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Wed, 13 Dec 2023 15:43:57 -0500 Subject: [PATCH 142/165] add to cloud cli --- .../docs/docs/cloud/cloud-cli-installation.md | 33 +++++++++++-------- 1 file changed, 19 insertions(+), 14 deletions(-) diff --git a/website/docs/docs/cloud/cloud-cli-installation.md b/website/docs/docs/cloud/cloud-cli-installation.md index 8d2196696aa..6dad5a105ad 100644 --- a/website/docs/docs/cloud/cloud-cli-installation.md +++ b/website/docs/docs/cloud/cloud-cli-installation.md @@ -258,16 +258,17 @@ To use these extensions, such as dbt-power-user, with the dbt Cloud CLI, you can ## FAQs -
    + -What's the difference between the dbt Cloud CLI and dbt Core? -The dbt Cloud CLI and dbt Core, an open-source project, are both command line tools that enable you to run dbt commands. The key distinction is the dbt Cloud CLI is tailored for dbt Cloud's infrastructure and integrates with all its features. +The dbt Cloud CLI and dbt Core, an open-source project, are both command line tools that enable you to run dbt commands. -
    +The key distinction is the dbt Cloud CLI is tailored for dbt Cloud's infrastructure and integrates with all its features. -
    -How do I run both the dbt Cloud CLI and dbt Core? -For compatibility, both the dbt Cloud CLI and dbt Core are invoked by running dbt. This can create path conflicts if your operating system selects one over the other based on your $PATH environment variable (settings).
    + + + + +For compatibility, both the dbt Cloud CLI and dbt Core are invoked by running `dbt`. This can create path conflicts if your operating system selects one over the other based on your $PATH environment variable (settings). If you have dbt Core installed locally, either: @@ -276,10 +277,11 @@ If you have dbt Core installed locally, either: 3. (Advanced users) Install natively, but modify the $PATH environment variable to correctly point to the dbt Cloud CLI binary to use both dbt Cloud CLI and dbt Core together. You can always uninstall the dbt Cloud CLI to return to using dbt Core. -
    -
    -How to create an alias? + + + + To create an alias for the dbt Cloud CLI:
    1. Open your shell's profile configuration file. Depending on your shell and system, this could be ~/.bashrc, ~/.bash_profile, ~/.zshrc, or another file.
    @@ -297,9 +299,12 @@ As an example, in bash you would run: source ~/.bashrc
    This alias will allow you to use the dbt-cloud command to invoke the dbt Cloud CLI while having dbt Core installed natively. -
    -
    -Why am I receiving a Session occupied error? + + + + + If you've ran a dbt command and receive a Session occupied error, you can reattach to your existing session with dbt reattach and then press Control-C and choose to cancel the invocation. -
    + + From d81f7cd3ca07a5f7e4d8950b8fd2c9e79ae55550 Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Wed, 13 Dec 2023 15:44:28 -0500 Subject: [PATCH 143/165] remove h --- website/docs/docs/cloud/cloud-cli-installation.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/docs/cloud/cloud-cli-installation.md b/website/docs/docs/cloud/cloud-cli-installation.md index 6dad5a105ad..7d459cdd91d 100644 --- a/website/docs/docs/cloud/cloud-cli-installation.md +++ b/website/docs/docs/cloud/cloud-cli-installation.md @@ -280,7 +280,7 @@ You can always uninstall the dbt Cloud CLI to return to using dbt Core. - + To create an alias for the dbt Cloud CLI:
    From 09c7e5023f71ad8fe888ee00fca191eed3d4c25b Mon Sep 17 00:00:00 2001 From: Doug Beatty <44704949+dbeatty10@users.noreply.github.com> Date: Wed, 13 Dec 2023 15:19:24 -0700 Subject: [PATCH 144/165] Too many backticks --- website/docs/reference/resource-configs/access.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/reference/resource-configs/access.md b/website/docs/reference/resource-configs/access.md index da50e48d2f0..fcde93647a1 100644 --- a/website/docs/reference/resource-configs/access.md +++ b/website/docs/reference/resource-configs/access.md @@ -27,7 +27,7 @@ You can apply access modifiers in config files, including `the dbt_project.yml`, There are multiple approaches to configuring access: -In the model configs of `dbt_project.yml``: +In the model configs of `dbt_project.yml`: ```yaml models: From a216a24c20cd299d8ffd91dcb267cc410e37ce0c Mon Sep 17 00:00:00 2001 From: Doug Beatty <44704949+dbeatty10@users.noreply.github.com> Date: Wed, 13 Dec 2023 16:09:12 -0700 Subject: [PATCH 145/165] Remove rogue hyperlink --- website/docs/reference/dbt-jinja-functions/config.md | 2 -- 1 file changed, 2 deletions(-) diff --git a/website/docs/reference/dbt-jinja-functions/config.md b/website/docs/reference/dbt-jinja-functions/config.md index c2fc8f96e5b..3903c82eef7 100644 --- a/website/docs/reference/dbt-jinja-functions/config.md +++ b/website/docs/reference/dbt-jinja-functions/config.md @@ -25,8 +25,6 @@ is responsible for handling model code that looks like this: ``` Review [Model configurations](/reference/model-configs) for examples and more information on valid arguments. -https://docs.getdbt.com/reference/model-configs - ## config.get __Args__: From e2e5630f0b51520addc95d5c5f3415d5f22da89c Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Wed, 13 Dec 2023 19:53:06 -0500 Subject: [PATCH 146/165] remove callout multi hop joins are supported now for the SL and MF so this pr removes callout that states multi hop joins aren't supported --- website/docs/docs/build/join-logic.md | 7 ------- 1 file changed, 7 deletions(-) diff --git a/website/docs/docs/build/join-logic.md b/website/docs/docs/build/join-logic.md index 9039822c9fd..29b9d101a59 100644 --- a/website/docs/docs/build/join-logic.md +++ b/website/docs/docs/build/join-logic.md @@ -84,10 +84,6 @@ mf query --metrics average_purchase_price --dimensions metric_time,user_id__type ## Multi-hop joins -:::info -This feature is currently in development and not currently available. -::: - MetricFlow allows users to join measures and dimensions across a graph of entities, which we refer to as a 'multi-hop join.' This is because users can move from one table to another like a 'hop' within a graph. Here's an example schema for reference: @@ -134,9 +130,6 @@ semantic_models: ### Query multi-hop joins -:::info -This feature is currently in development and not currently available. -::: To query dimensions _without_ a multi-hop join involved, you can use the fully qualified dimension name with the syntax entity double underscore (dunder) dimension, like `entity__dimension`. From ade6d8a78752ba23c2d674652cd612dd6b317e4f Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Wed, 13 Dec 2023 22:10:38 -0500 Subject: [PATCH 147/165] add !isOn --- website/src/components/detailsToggle/index.js | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/website/src/components/detailsToggle/index.js b/website/src/components/detailsToggle/index.js index 1c571d6d033..e264a75939c 100644 --- a/website/src/components/detailsToggle/index.js +++ b/website/src/components/detailsToggle/index.js @@ -1,7 +1,7 @@ import React, { useState, useEffect } from 'react'; import styles from './styles.module.css'; -function DetailsToggle({ children, alt_header = null }) { +function detailsToggle({ children, alt_header = null }) { const [isOn, setOn] = useState(false); const [hoverActive, setHoverActive] = useState(true); const [hoverTimeout, setHoverTimeout] = useState(null); @@ -20,9 +20,9 @@ function DetailsToggle({ children, alt_header = null }) { }; const handleMouseLeave = () => { - if (hoverActive) { + if (hoverActive && isOn) { clearTimeout(hoverTimeout); - setOn(false); // Collapse content only if it was opened by hover + } }; @@ -53,4 +53,4 @@ function DetailsToggle({ children, alt_header = null }) { ); } -export default DetailsToggle; +export default detailsToggle; From bd100327d88e1b9e8fd3909c41dc13251f60c5be Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Wed, 13 Dec 2023 22:19:05 -0500 Subject: [PATCH 148/165] adjust click with setOnfalse --- website/src/components/detailsToggle/index.js | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/website/src/components/detailsToggle/index.js b/website/src/components/detailsToggle/index.js index e264a75939c..90464328f8b 100644 --- a/website/src/components/detailsToggle/index.js +++ b/website/src/components/detailsToggle/index.js @@ -7,7 +7,7 @@ function detailsToggle({ children, alt_header = null }) { const [hoverTimeout, setHoverTimeout] = useState(null); const handleToggleClick = () => { - setOn(!isOn); + setOn(false); setHoverActive(isOn); // Toggle hover activation based on current state }; @@ -20,9 +20,10 @@ function detailsToggle({ children, alt_header = null }) { }; const handleMouseLeave = () => { - if (hoverActive && isOn) { + if (hoverActive && !isOn) { clearTimeout(hoverTimeout); - + setOn(false); + // isOn (false); can't be used here but setOn triggers a re-render } }; From b5274a89e6e5a53fea4559208283fa0c9390bbe8 Mon Sep 17 00:00:00 2001 From: Doug Beatty <44704949+dbeatty10@users.noreply.github.com> Date: Thu, 14 Dec 2023 08:00:17 -0700 Subject: [PATCH 149/165] Dynamic default `incremental_strategy` for dbt-postgres --- .../docs/reference/resource-configs/postgres-configs.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/website/docs/reference/resource-configs/postgres-configs.md b/website/docs/reference/resource-configs/postgres-configs.md index 8465a5cbb31..fcc0d91a47c 100644 --- a/website/docs/reference/resource-configs/postgres-configs.md +++ b/website/docs/reference/resource-configs/postgres-configs.md @@ -10,16 +10,16 @@ In dbt-postgres, the following incremental materialization strategies are suppor -- `append` (default) -- `delete+insert` +- `append` (default when `unique_key` is not defined) +- `delete+insert` (default when `unique_key` is defined) -- `append` (default) +- `append` (default when `unique_key` is not defined) - `merge` -- `delete+insert` +- `delete+insert` (default when `unique_key` is defined) From c5261be89222a50c2b50c636a8fe2d87ca4e9770 Mon Sep 17 00:00:00 2001 From: Doug Beatty <44704949+dbeatty10@users.noreply.github.com> Date: Thu, 14 Dec 2023 08:02:37 -0700 Subject: [PATCH 150/165] Dynamic default `incremental_strategy` for dbt-redshift --- .../reference/resource-configs/redshift-configs.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/website/docs/reference/resource-configs/redshift-configs.md b/website/docs/reference/resource-configs/redshift-configs.md index b559c0451b0..85b2af0c552 100644 --- a/website/docs/reference/resource-configs/redshift-configs.md +++ b/website/docs/reference/resource-configs/redshift-configs.md @@ -16,16 +16,16 @@ In dbt-redshift, the following incremental materialization strategies are suppor -- `append` (default) -- `delete+insert` - +- `append` (default when `unique_key` is not defined) +- `delete+insert` (default when `unique_key` is defined) + -- `append` (default) +- `append` (default when `unique_key` is not defined) - `merge` -- `delete+insert` +- `delete+insert` (default when `unique_key` is defined) From 3b5db5cca2f31756b61b49d3cdf579b8592f13f9 Mon Sep 17 00:00:00 2001 From: Doug Beatty <44704949+dbeatty10@users.noreply.github.com> Date: Thu, 14 Dec 2023 12:32:05 -0700 Subject: [PATCH 151/165] `merge` is the default `incremental_strategy` since dbt-databricks 1.0.0 (#4653) ### Previews - [Incremental strategies](https://docs-getdbt-com-git-dbeatty-dbt-databricks-merg-0a4e67-dbt-labs.vercel.app/reference/resource-configs/databricks-configs#incremental-models) - [`merge` strategy](https://docs-getdbt-com-git-dbeatty-dbt-databricks-merg-0a4e67-dbt-labs.vercel.app//reference/resource-configs/databricks-configs#the-merge-strategy) - [`append` strategy](https://docs-getdbt-com-git-dbeatty-dbt-databricks-merg-0a4e67-dbt-labs.vercel.app/reference/resource-configs/databricks-configs#the-append-strategy) ## What are you changing in this pull request and why? `merge` has been the default incremental strategy for dbt-databricks since [1.0.0](https://github.com/databricks/dbt-databricks/blob/7ad5507a8a38bde682bb28eb37466bbfc341ac94/CHANGELOG.md?plain=1#L404) ## Checklist - [x] Review the [Content style guide](https://github.com/dbt-labs/docs.getdbt.com/blob/current/contributing/content-style-guide.md) so my content adheres to these guidelines. --------- Co-authored-by: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> --- .../docs/reference/resource-configs/databricks-configs.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/website/docs/reference/resource-configs/databricks-configs.md b/website/docs/reference/resource-configs/databricks-configs.md index fb3c9e7f5c3..677cad57ce6 100644 --- a/website/docs/reference/resource-configs/databricks-configs.md +++ b/website/docs/reference/resource-configs/databricks-configs.md @@ -38,9 +38,9 @@ When materializing a model as `table`, you may include several optional configs ## Incremental models dbt-databricks plugin leans heavily on the [`incremental_strategy` config](/docs/build/incremental-models#about-incremental_strategy). This config tells the incremental materialization how to build models in runs beyond their first. It can be set to one of four values: - - **`append`** (default): Insert new records without updating or overwriting any existing data. + - **`append`**: Insert new records without updating or overwriting any existing data. - **`insert_overwrite`**: If `partition_by` is specified, overwrite partitions in the with new data. If no `partition_by` is specified, overwrite the entire table with new data. - - **`merge`** (Delta and Hudi file format only): Match records based on a `unique_key`, updating old records, and inserting new ones. (If no `unique_key` is specified, all new data is inserted, similar to `append`.) + - **`merge`** (default; Delta and Hudi file format only): Match records based on a `unique_key`, updating old records, and inserting new ones. (If no `unique_key` is specified, all new data is inserted, similar to `append`.) - **`replace_where`** (Delta file format only): Match records based on `incremental_predicates`, replacing all records that match the predicates from the existing table with records matching the predicates from the new data. (If no `incremental_predicates` are specified, all new data is inserted, similar to `append`.) Each of these strategies has its pros and cons, which we'll discuss below. As with any model config, `incremental_strategy` may be specified in `dbt_project.yml` or within a model file's `config()` block. @@ -49,8 +49,6 @@ Each of these strategies has its pros and cons, which we'll discuss below. As wi Following the `append` strategy, dbt will perform an `insert into` statement with all new data. The appeal of this strategy is that it is straightforward and functional across all platforms, file types, connection methods, and Apache Spark versions. However, this strategy _cannot_ update, overwrite, or delete existing data, so it is likely to insert duplicate records for many data sources. -Specifying `append` as the incremental strategy is optional, since it's the default strategy used when none is specified. - Date: Thu, 14 Dec 2023 13:17:06 -0700 Subject: [PATCH 152/165] Display supported incremental strategies in a tabular format (#4649) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit [Preview](https://docs-getdbt-com-git-dbeatty-tabular-incremental-326e95-dbt-labs.vercel.app/docs/build/incremental-models#supported-incremental-strategies-by-adapter) resolves #4634 ## What are you changing in this pull request and why? The main aim is to be able to easily answer each of these questions: - which adapters support the `delete+insert` strategy? - what are the names of the standard incremental strategies that are supported in at least one adapter? - what are the names of the standard incremental strategies that are supported most frequently? - what are the names of the standard incremental strategies that are supported least frequently? A tabular representation with one column per strategy is the easiest way to answer all of the above. ## Design decisions to be made 1. Style of the icons 1. Number of tables ### Style of the icons Any of these could work: ✅ - Green check mark ✔️ - Heavy check mark 🟢 - Green circle We probably wouldn't choose any of these: ☑️ - Ballot box with check 🆗 - OK button 👍 - Thumbs up etc. ### Number of tables We have several options: 1. Keep the status quo 1. Split into two tables: one for the available strategies, and another for the defaults 1. Keep a single table, keeping the "default strategy" column, but replacing the "additional supported strategies" with one column per strategy 1. Defer the default strategy information to each adapter-specific config page instead (see [dbt-bigquery](https://docs.getdbt.com/reference/resource-configs/bigquery-configs#merge-behavior-incremental-models) or [dbt-redshift](https://docs.getdbt.com/reference/resource-configs/redshift-configs#incremental-materialization-strategies) for examples) ### Trade-offs I strongly prefer not staying with the status quo, or I wouldn't have opened this issue 🤣 Splitting into two separate tables would solve the key problem, but at the cost of taking up more vertical space on the page. Keeping a single table but refactoring it would work for me. Completely moving the default strategy information into the adapter-specific pages might be the best of all worlds. It would solve the problem at hand while preserving documentation about the default strategy that is relevant for a particular adapter. dbt-postgres and dbt-redshift in particular have caveats related to the default -- it will change [depending if a `unique_key` is defined ](https://github.com/dbt-labs/docs.getdbt.com/issues/4651)or not. ## 🎩 [Preview](https://docs-getdbt-com-git-dbeatty-tabular-incremental-326e95-dbt-labs.vercel.app/docs/build/incremental-models#supported-incremental-strategies-by-adapter) ### v3 (final) image image ### v2 image ### v1 **Note:** I've since removed the 2nd table that has the defaults, but here's what it looked like with them: image image ## Checklist - [x] Review the [Content style guide](https://github.com/dbt-labs/docs.getdbt.com/blob/current/contributing/content-style-guide.md) so my content adheres to these guidelines. --------- Co-authored-by: Matt Shaver <60105315+matthewshaver@users.noreply.github.com> --- website/docs/docs/build/incremental-models.md | 38 +++++++++---------- 1 file changed, 18 insertions(+), 20 deletions(-) diff --git a/website/docs/docs/build/incremental-models.md b/website/docs/docs/build/incremental-models.md index 01a392c12fe..46788758ee6 100644 --- a/website/docs/docs/build/incremental-models.md +++ b/website/docs/docs/build/incremental-models.md @@ -249,31 +249,29 @@ The `merge` strategy is available in dbt-postgres and dbt-redshift beginning in - -| data platform adapter | default strategy | additional supported strategies | -| :-------------------| ---------------- | -------------------- | -| [dbt-postgres](/reference/resource-configs/postgres-configs#incremental-materialization-strategies) | `append` | `delete+insert` | -| [dbt-redshift](/reference/resource-configs/redshift-configs#incremental-materialization-strategies) | `append` | `delete+insert` | -| [dbt-bigquery](/reference/resource-configs/bigquery-configs#merge-behavior-incremental-models) | `merge` | `insert_overwrite` | -| [dbt-spark](/reference/resource-configs/spark-configs#incremental-models) | `append` | `merge`, `insert_overwrite` | -| [dbt-databricks](/reference/resource-configs/databricks-configs#incremental-models) | `merge` | `append`, `insert_overwrite` | -| [dbt-snowflake](/reference/resource-configs/snowflake-configs#merge-behavior-incremental-models) | `merge` | `append`, `delete+insert` | -| [dbt-trino](/reference/resource-configs/trino-configs#incremental) | `append` | `merge`, `delete+insert` | +| data platform adapter | `append` | `merge` | `delete+insert` | `insert_overwrite` | +|-----------------------------------------------------------------------------------------------------|:--------:|:-------:|:---------------:|:------------------:| +| [dbt-postgres](/reference/resource-configs/postgres-configs#incremental-materialization-strategies) | ✅ | | ✅ | | +| [dbt-redshift](/reference/resource-configs/redshift-configs#incremental-materialization-strategies) | ✅ | | ✅ | | +| [dbt-bigquery](/reference/resource-configs/bigquery-configs#merge-behavior-incremental-models) | | ✅ | | ✅ | +| [dbt-spark](/reference/resource-configs/spark-configs#incremental-models) | ✅ | ✅ | | ✅ | +| [dbt-databricks](/reference/resource-configs/databricks-configs#incremental-models) | ✅ | ✅ | | ✅ | +| [dbt-snowflake](/reference/resource-configs/snowflake-configs#merge-behavior-incremental-models) | ✅ | ✅ | ✅ | | +| [dbt-trino](/reference/resource-configs/trino-configs#incremental) | ✅ | ✅ | ✅ | | - -| data platform adapter | default strategy | additional supported strategies | -| :----------------- | :----------------| : ---------------------------------- | -| [dbt-postgres](/reference/resource-configs/postgres-configs#incremental-materialization-strategies) | `append` | `merge` , `delete+insert` | -| [dbt-redshift](/reference/resource-configs/redshift-configs#incremental-materialization-strategies) | `append` | `merge`, `delete+insert` | -| [dbt-bigquery](/reference/resource-configs/bigquery-configs#merge-behavior-incremental-models) | `merge` | `insert_overwrite` | -| [dbt-spark](/reference/resource-configs/spark-configs#incremental-models) | `append` | `merge`, `insert_overwrite` | -| [dbt-databricks](/reference/resource-configs/databricks-configs#incremental-models) | `merge` | `append`, `insert_overwrite` | -| [dbt-snowflake](/reference/resource-configs/snowflake-configs#merge-behavior-incremental-models) | `merge` | `append`, `delete+insert` | -| [dbt-trino](/reference/resource-configs/trino-configs#incremental) | `append` | `merge`, `delete+insert` | +| data platform adapter | `append` | `merge` | `delete+insert` | `insert_overwrite` | +|-----------------------------------------------------------------------------------------------------|:--------:|:-------:|:---------------:|:------------------:| +| [dbt-postgres](/reference/resource-configs/postgres-configs#incremental-materialization-strategies) | ✅ | ✅ | ✅ | | +| [dbt-redshift](/reference/resource-configs/redshift-configs#incremental-materialization-strategies) | ✅ | ✅ | ✅ | | +| [dbt-bigquery](/reference/resource-configs/bigquery-configs#merge-behavior-incremental-models) | | ✅ | | ✅ | +| [dbt-spark](/reference/resource-configs/spark-configs#incremental-models) | ✅ | ✅ | | ✅ | +| [dbt-databricks](/reference/resource-configs/databricks-configs#incremental-models) | ✅ | ✅ | | ✅ | +| [dbt-snowflake](/reference/resource-configs/snowflake-configs#merge-behavior-incremental-models) | ✅ | ✅ | ✅ | | +| [dbt-trino](/reference/resource-configs/trino-configs#incremental) | ✅ | ✅ | ✅ | | From ead19cd468b7a448487b6eb3c6a19e34f8ea7b5c Mon Sep 17 00:00:00 2001 From: David Birks Date: Fri, 15 Dec 2023 00:05:06 -0500 Subject: [PATCH 153/165] Fix customers spelling --- website/docs/guides/snowflake-qs.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/guides/snowflake-qs.md b/website/docs/guides/snowflake-qs.md index abb18276b97..5b4f9e3e2be 100644 --- a/website/docs/guides/snowflake-qs.md +++ b/website/docs/guides/snowflake-qs.md @@ -462,7 +462,7 @@ Sources make it possible to name and describe the data loaded into your warehous 5. Execute `dbt run`. - The results of your `dbt run` will be exactly the same as the previous step. Your `stg_cusutomers` and `stg_orders` + The results of your `dbt run` will be exactly the same as the previous step. Your `stg_customers` and `stg_orders` models will still query from the same raw data source in Snowflake. By using `source`, you can test and document your raw data and also understand the lineage of your sources. From 96cf752987ebfdb5542fe2133779f0da3e21c6ce Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Fri, 15 Dec 2023 11:14:22 -0500 Subject: [PATCH 154/165] Update legacy-sl.md fix spacing --- .../docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md b/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md index df4616f4d43..0eecfea623e 100644 --- a/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md +++ b/website/docs/docs/dbt-versions/release-notes/74-Dec-2023/legacy-sl.md @@ -34,6 +34,6 @@ The [re-released dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl), power ### Engage and support - Feedback and community support — Engage and share feedback with the dbt Labs team and dbt Community slack using channels like [#dbt-cloud-semantic-layer](https://getdbt.slack.com/archives/C046L0VTVR6) and [#dbt-metricflow](https://getdbt.slack.com/archives/C02CCBBBR1D). Or reach out to your dbt Cloud account representative. -- Resources for upgrading —Refer to some additional info and resources to help you upgrade your dbt version: +- Resources for upgrading — Refer to some additional info and resources to help you upgrade your dbt version: - [Upgrade version in dbt Cloud](/docs/dbt-versions/upgrade-core-in-cloud) - [Version migration guides](/docs/dbt-versions/core-upgrade) From 203cb05ac1f1974f4233a9d6ec864aeda0d46532 Mon Sep 17 00:00:00 2001 From: Doug Beatty <44704949+dbeatty10@users.noreply.github.com> Date: Fri, 15 Dec 2023 09:31:14 -0700 Subject: [PATCH 155/165] Explain how transactions (and rollbacks) are handled for incremental strategies (#4655) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit [Preview](https://docs-getdbt-com-git-dbeatty-explain-incremental-957f61-dbt-labs.vercel.app/docs/build/incremental-models#how-do-incremental-models-work-behind-the-scenes) ## What are you changing in this pull request and why? resolves #4635 The goal of this issue is to document the answer to this question from https://github.com/dbt-labs/dbt-core/issues/7011#issuecomment-1443698015: > For the DML, we know that only the delete+insert strategy will work, and not merge. With delete+insert incremental strategy, does Dbt wrap both in a single transaction? If not, and they are treated as 2 separate transactions that would be bad. For example, the delete could succeed, and the subsequent insert could fail. The table would then be left with deleted records = Not Good. Can you elaborate on how Dbt already handles that. I cannot find it anywhere in the doc. ### 🎩 image ## Checklist - [x] Review the [Content style guide](https://github.com/dbt-labs/docs.getdbt.com/blob/current/contributing/content-style-guide.md) so my content adheres to these guidelines. --------- Co-authored-by: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> --- website/docs/docs/build/incremental-models.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/docs/build/incremental-models.md b/website/docs/docs/build/incremental-models.md index 46788758ee6..2a247263159 100644 --- a/website/docs/docs/build/incremental-models.md +++ b/website/docs/docs/build/incremental-models.md @@ -174,7 +174,7 @@ dbt's incremental materialization works differently on different databases. Wher On warehouses that do not support `merge` statements, a merge is implemented by first using a `delete` statement to delete records in the target table that are to be updated, and then an `insert` statement. -Transaction management is used to ensure this is executed as a single unit of work. +Transaction management, a process used in certain data platforms, ensures that a set of actions is treated as a single unit of work (or task). If any part of the unit of work fails, dbt will roll back open transactions and restore the database to a good state. ## What if the columns of my incremental model change? From c9ce5465bd5464326830ad61fbd13beae48b3c53 Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Fri, 15 Dec 2023 15:24:18 -0500 Subject: [PATCH 156/165] update behavior adn code --- website/src/components/detailsToggle/index.js | 36 +++++++++---------- 1 file changed, 18 insertions(+), 18 deletions(-) diff --git a/website/src/components/detailsToggle/index.js b/website/src/components/detailsToggle/index.js index 90464328f8b..ba53192e54b 100644 --- a/website/src/components/detailsToggle/index.js +++ b/website/src/components/detailsToggle/index.js @@ -7,29 +7,29 @@ function detailsToggle({ children, alt_header = null }) { const [hoverTimeout, setHoverTimeout] = useState(null); const handleToggleClick = () => { - setOn(false); - setHoverActive(isOn); // Toggle hover activation based on current state - }; + setHoverActive(true); // Disable hover when clicked + setOn(current => !current); // Toggle the current state +}; - const handleMouseEnter = () => { - if (!hoverActive) return; // Ignore hover if disabled - const timeout = setTimeout(() => { - setOn(true); - }, 500); // 500ms delay - setHoverTimeout(timeout); - }; +const handleMouseEnter = () => { + if (isOn) return; // Ignore hover if already open + setHoverActive(true); // Enable hover + const timeout = setTimeout(() => { + if (hoverActive) setOn(true); + }, 500); + setHoverTimeout(timeout); +}; - const handleMouseLeave = () => { - if (hoverActive && !isOn) { +const handleMouseLeave = () => { + if (!isOn) { clearTimeout(hoverTimeout); setOn(false); - // isOn (false); can't be used here but setOn triggers a re-render - } - }; + } +}; - useEffect(() => { - return () => clearTimeout(hoverTimeout); - }, [hoverTimeout]); +useEffect(() => { + return () => clearTimeout(hoverTimeout); +}, [hoverTimeout]); return (
    From 8c7913dee94d5ee88ad589de25b698b1d6780d86 Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Fri, 15 Dec 2023 15:38:53 -0500 Subject: [PATCH 157/165] Update _sl-faqs.md --- website/snippets/_sl-faqs.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/snippets/_sl-faqs.md b/website/snippets/_sl-faqs.md index 092929e1066..75583bfa2f6 100644 --- a/website/snippets/_sl-faqs.md +++ b/website/snippets/_sl-faqs.md @@ -44,7 +44,7 @@ If you're using the legacy Semantic Layer, we highly recommend you [upgrade your - + User data passes through the Semantic Layer on its way back from the warehouse. dbt Labs ensures security by authenticating through the customer's data warehouse. Currently, we don't cache data for the long term, but it might temporarily stay in the system for up to 10 minutes, usually less. In the future, we'll introduce a caching feature that allows us to cache data on our infrastructure for up to 24 hours. From 05523d4c34078676212d6186f11aab10f86b7113 Mon Sep 17 00:00:00 2001 From: Doug Beatty <44704949+dbeatty10@users.noreply.github.com> Date: Fri, 15 Dec 2023 15:49:08 -0700 Subject: [PATCH 158/165] Only display intro (rather than entire article) during listing of blog posts --- .../blog/2023-05-02-modeling-ragged-time-varying-hierarchies.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/website/blog/2023-05-02-modeling-ragged-time-varying-hierarchies.md b/website/blog/2023-05-02-modeling-ragged-time-varying-hierarchies.md index d436df2628a..f719bdb40cb 100644 --- a/website/blog/2023-05-02-modeling-ragged-time-varying-hierarchies.md +++ b/website/blog/2023-05-02-modeling-ragged-time-varying-hierarchies.md @@ -16,6 +16,8 @@ This article covers an approach to handling time-varying ragged hierarchies in a To help visualize this data, we're going to pretend we are a company that manufactures and rents out eBikes in a ride share application. When we build a bike, we keep track of the serial numbers of the components that make up the bike. Any time something breaks and needs to be replaced, we track the old parts that were removed and the new parts that were installed. We also precisely track the mileage accumulated on each of our bikes. Our primary analytical goal is to be able to report on the expected lifetime of each component, so we can prioritize improving that component and reduce costly maintenance. + + ## Data model Obviously, a real bike could have a hundred or more separate components. To keep things simple for this article, let's just consider the bike, the frame, a wheel, the wheel rim, tire, and tube. Our component hierarchy looks like: From 7ad36fdb848d35009f57c1939b24032e9f67861a Mon Sep 17 00:00:00 2001 From: Doug Beatty <44704949+dbeatty10@users.noreply.github.com> Date: Sun, 17 Dec 2023 11:15:58 -0700 Subject: [PATCH 159/165] Update dbt_project.yml.md Remove duplicated content --- website/docs/reference/dbt_project.yml.md | 22 ---------------------- 1 file changed, 22 deletions(-) diff --git a/website/docs/reference/dbt_project.yml.md b/website/docs/reference/dbt_project.yml.md index d130b5cf1f5..9252d13681f 100644 --- a/website/docs/reference/dbt_project.yml.md +++ b/website/docs/reference/dbt_project.yml.md @@ -25,28 +25,6 @@ Something to note, you can't set up a "property" in the `dbt_project.yml` file i The following example is a list of all available configurations in the `dbt_project.yml` file: - - - -By default, dbt will look for `dbt_project.yml` in your current working directory and its parents, but you can set a different directory using the `--project-dir` flag. - - - - - -By default, dbt will look for `dbt_project.yml` in your current working directory and its parents, but you can set a different directory using the `--project-dir` flag or the `DBT_PROJECT_DIR` environment variable. - -Starting from dbt v1.5 and higher, you can specify your dbt Cloud project ID in the `dbt_project.yml` file using `project-id` under the `dbt-cloud` config. To find your project ID, check your dbt Cloud project URL, such as `https://cloud.getdbt.com/11/projects/123456`, where the project ID is `123456`. - - - -The following is a list of all available configurations in the `dbt_project.yml` file. - -:::info YAML syntax -dbt uses YAML in a few different places. If you're new to YAML, it would be worth taking the time to learn how arrays, dictionaries and strings are represented. -::: - - From c26bc3965a4bfb0c72eb8f128ddc21a28cded1b5 Mon Sep 17 00:00:00 2001 From: Doug Beatty <44704949+dbeatty10@users.noreply.github.com> Date: Sun, 17 Dec 2023 11:27:13 -0700 Subject: [PATCH 160/165] Remove extra newline --- website/docs/reference/dbt_project.yml.md | 1 - 1 file changed, 1 deletion(-) diff --git a/website/docs/reference/dbt_project.yml.md b/website/docs/reference/dbt_project.yml.md index 9252d13681f..a5ad601f78b 100644 --- a/website/docs/reference/dbt_project.yml.md +++ b/website/docs/reference/dbt_project.yml.md @@ -16,7 +16,6 @@ Starting from dbt v1.5 and higher, you can specify your dbt Cloud project ID in :::info YAML syntax - dbt uses YAML in a few different places. If you're new to YAML, it would be worth taking the time to learn how arrays, dictionaries, and strings are represented. ::: From eca769c4c039407207a33bf9f554e438489fbe4f Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Mon, 18 Dec 2023 06:01:18 -0500 Subject: [PATCH 161/165] link to clone in ci job best practices this pr adds a link to the clone in a ci job best practices guide as a callout per slack request https://dbt-labs.slack.com/archives/C02NCQ9483C/p1702655617781059 --- website/blog/2023-10-31-to-defer-or-to-clone.md | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/website/blog/2023-10-31-to-defer-or-to-clone.md b/website/blog/2023-10-31-to-defer-or-to-clone.md index a39fc3ac0b7..2d72eee3297 100755 --- a/website/blog/2023-10-31-to-defer-or-to-clone.md +++ b/website/blog/2023-10-31-to-defer-or-to-clone.md @@ -91,6 +91,10 @@ Using the cheat sheet above, let’s explore a few common scenarios and explore 2. **[Slim CI](https://discourse.getdbt.com/t/how-we-sped-up-our-ci-runs-by-10x-using-slim-ci/2603)** + :::tip Use `dbt clone` in CI jobs + Learn how to [use `dbt clone` in CI jobs](/best-practices/clone-incremental-models) to efficiently test modified incremental models, simulating post-merge behavior while avoiding full-refresh costs. + ::: + In this scenario, we want to: 1. Refer to production models wherever possible to speed up continuous integration (CI) runs 2. Only run and test models in the CI staging environment that have changed from the production environment @@ -98,7 +102,7 @@ Using the cheat sheet above, let’s explore a few common scenarios and explore Therefore, we should use **defer** in this scenario -3. **[Blue/Green Deployments](https://discourse.getdbt.com/t/performing-a-blue-green-deploy-of-your-dbt-project-on-snowflake/1349)** +4. **[Blue/Green Deployments](https://discourse.getdbt.com/t/performing-a-blue-green-deploy-of-your-dbt-project-on-snowflake/1349)** In this scenario, we want to: 1. Ensure that all tests are always passing on the production dataset, even if that dataset is slightly stale From c1a6d9c9e3e5e50595deb09e8060044e290a1b1d Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Mon, 18 Dec 2023 06:02:12 -0500 Subject: [PATCH 162/165] Update website/blog/2023-10-31-to-defer-or-to-clone.md --- website/blog/2023-10-31-to-defer-or-to-clone.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/blog/2023-10-31-to-defer-or-to-clone.md b/website/blog/2023-10-31-to-defer-or-to-clone.md index 2d72eee3297..4777022e5cd 100755 --- a/website/blog/2023-10-31-to-defer-or-to-clone.md +++ b/website/blog/2023-10-31-to-defer-or-to-clone.md @@ -102,7 +102,7 @@ Using the cheat sheet above, let’s explore a few common scenarios and explore Therefore, we should use **defer** in this scenario -4. **[Blue/Green Deployments](https://discourse.getdbt.com/t/performing-a-blue-green-deploy-of-your-dbt-project-on-snowflake/1349)** +3. **[Blue/Green Deployments](https://discourse.getdbt.com/t/performing-a-blue-green-deploy-of-your-dbt-project-on-snowflake/1349)** In this scenario, we want to: 1. Ensure that all tests are always passing on the production dataset, even if that dataset is slightly stale From 301c8a9e04d559bacf80e0e7591d6e094064267f Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Mon, 18 Dec 2023 06:03:30 -0500 Subject: [PATCH 163/165] Update website/blog/2023-10-31-to-defer-or-to-clone.md --- website/blog/2023-10-31-to-defer-or-to-clone.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/blog/2023-10-31-to-defer-or-to-clone.md b/website/blog/2023-10-31-to-defer-or-to-clone.md index 4777022e5cd..53b40f244dd 100755 --- a/website/blog/2023-10-31-to-defer-or-to-clone.md +++ b/website/blog/2023-10-31-to-defer-or-to-clone.md @@ -91,7 +91,7 @@ Using the cheat sheet above, let’s explore a few common scenarios and explore 2. **[Slim CI](https://discourse.getdbt.com/t/how-we-sped-up-our-ci-runs-by-10x-using-slim-ci/2603)** - :::tip Use `dbt clone` in CI jobs + :::tip Use `dbt clone` in CI jobs to test incremental models Learn how to [use `dbt clone` in CI jobs](/best-practices/clone-incremental-models) to efficiently test modified incremental models, simulating post-merge behavior while avoiding full-refresh costs. ::: From 7d81a535342e01891f2d5837ded9975ef338e639 Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Mon, 18 Dec 2023 06:13:53 -0500 Subject: [PATCH 164/165] Update 2023-10-31-to-defer-or-to-clone.md --- website/blog/2023-10-31-to-defer-or-to-clone.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/website/blog/2023-10-31-to-defer-or-to-clone.md b/website/blog/2023-10-31-to-defer-or-to-clone.md index 53b40f244dd..9454ad11281 100755 --- a/website/blog/2023-10-31-to-defer-or-to-clone.md +++ b/website/blog/2023-10-31-to-defer-or-to-clone.md @@ -91,18 +91,18 @@ Using the cheat sheet above, let’s explore a few common scenarios and explore 2. **[Slim CI](https://discourse.getdbt.com/t/how-we-sped-up-our-ci-runs-by-10x-using-slim-ci/2603)** - :::tip Use `dbt clone` in CI jobs to test incremental models - Learn how to [use `dbt clone` in CI jobs](/best-practices/clone-incremental-models) to efficiently test modified incremental models, simulating post-merge behavior while avoiding full-refresh costs. - ::: - In this scenario, we want to: 1. Refer to production models wherever possible to speed up continuous integration (CI) runs 2. Only run and test models in the CI staging environment that have changed from the production environment 3. Reference models from different environments – prod for unchanged models, and staging for modified models Therefore, we should use **defer** in this scenario + + :::tip Use `dbt clone` in CI jobs to test incremental models + Learn how to [use `dbt clone` in CI jobs](/best-practices/clone-incremental-models) to efficiently test modified incremental models, simulating post-merge behavior while avoiding full-refresh costs. + ::: -3. **[Blue/Green Deployments](https://discourse.getdbt.com/t/performing-a-blue-green-deploy-of-your-dbt-project-on-snowflake/1349)** +4. **[Blue/Green Deployments](https://discourse.getdbt.com/t/performing-a-blue-green-deploy-of-your-dbt-project-on-snowflake/1349)** In this scenario, we want to: 1. Ensure that all tests are always passing on the production dataset, even if that dataset is slightly stale From 25c2af99bde23bfe607004b9eb29188d67015b8b Mon Sep 17 00:00:00 2001 From: mirnawong1 <89008547+mirnawong1@users.noreply.github.com> Date: Mon, 18 Dec 2023 06:48:37 -0500 Subject: [PATCH 165/165] Update 2023-10-31-to-defer-or-to-clone.md --- website/blog/2023-10-31-to-defer-or-to-clone.md | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/website/blog/2023-10-31-to-defer-or-to-clone.md b/website/blog/2023-10-31-to-defer-or-to-clone.md index 9454ad11281..00aa8c7f7e5 100755 --- a/website/blog/2023-10-31-to-defer-or-to-clone.md +++ b/website/blog/2023-10-31-to-defer-or-to-clone.md @@ -87,7 +87,7 @@ Using the cheat sheet above, let’s explore a few common scenarios and explore 1. Make a copy of our production dataset available in our downstream BI tool 2. To safely iterate on this copy without breaking production datasets - Therefore, we should use **clone** in this scenario + Therefore, we should use **clone** in this scenario. 2. **[Slim CI](https://discourse.getdbt.com/t/how-we-sped-up-our-ci-runs-by-10x-using-slim-ci/2603)** @@ -96,13 +96,13 @@ Using the cheat sheet above, let’s explore a few common scenarios and explore 2. Only run and test models in the CI staging environment that have changed from the production environment 3. Reference models from different environments – prod for unchanged models, and staging for modified models - Therefore, we should use **defer** in this scenario + Therefore, we should use **defer** in this scenario. - :::tip Use `dbt clone` in CI jobs to test incremental models - Learn how to [use `dbt clone` in CI jobs](/best-practices/clone-incremental-models) to efficiently test modified incremental models, simulating post-merge behavior while avoiding full-refresh costs. - ::: +:::tip Use `dbt clone` in CI jobs to test incremental models +Learn how to [use `dbt clone` in CI jobs](/best-practices/clone-incremental-models) to efficiently test modified incremental models, simulating post-merge behavior while avoiding full-refresh costs. +::: -4. **[Blue/Green Deployments](https://discourse.getdbt.com/t/performing-a-blue-green-deploy-of-your-dbt-project-on-snowflake/1349)** +3. **[Blue/Green Deployments](https://discourse.getdbt.com/t/performing-a-blue-green-deploy-of-your-dbt-project-on-snowflake/1349)** In this scenario, we want to: 1. Ensure that all tests are always passing on the production dataset, even if that dataset is slightly stale