+Contains user visits with `USER_ID` and `REFERRER_ID`. + +| DS | USER_ID | REFERRER_ID | +| --- | --- | --- | +| 2020-01-01 | bob | facebook | +| 2020-01-04 | bob | google | +| 2020-01-07 | bob | amazon | + +`BUYS`
+Records completed orders with `USER_ID` and `REFERRER_ID`. + +| DS | USER_ID | REFERRER_ID | +| --- | --- | --- | +| 2020-01-02 | bob | facebook | +| 2020-01-07 | bob | amazon | + +Next, define a conversion metric as follows: + +```yaml +- name: visit_to_buy_conversion_rate_7d + description: "Conversion rate from visiting to transaction in 7 days" + type: conversion + label: Visit to Buy Conversion Rate (7-day window) + type_params: + fills_nulls_with: 0 + conversion_type_params: + base_measure: visits + conversion_measure: sellers + entity: user + window: 7 days +``` + +To calculate the conversion, link the `BUYS` event to the nearest `VISITS` event (or closest base event). The following steps explain this process in more detail: + +### Step 1: Join `VISITS` and `BUYS` + +This step joins the `BUYS` table to the `VISITS` table and gets all combinations of visits-buys events that match the join condition where buys occur within 7 days of the visit (any rows that have the same user and a buy happened at most 7 days after the visit). + +The SQL generated in these steps looks like the following: + +```sql +select + v.ds, + v.user_id, + v.referrer_id, + b.ds, + b.uuid, + 1 as buys +from visits v +inner join ( + select *, uuid_string() as uuid from buys -- Adds a uuid column to uniquely identify the different rows +) b +on +v.user_id = b.user_id and v.ds <= b.ds and v.ds > b.ds - interval '7 days' +``` + +The dataset returns the following (note that there are two potential conversion events for the first visit): + +| V.DS | V.USER_ID | V.REFERRER_ID | B.DS | UUID | BUYS | +| --- | --- | --- | --- | --- | --- | +| 2020-01-01 | bob | facebook | 2020-01-02 | uuid1 | 1 | +| 2020-01-01 | bob | facebook | 2020-01-07 | uuid2 | 1 | +| 2020-01-04 | bob | google | 2020-01-07 | uuid2 | 1 | +| 2020-01-07 | bob | amazon | 2020-01-07 | uuid2 | 1 | + +### Step 2: Refine with window function + +Instead of returning the raw visit values, use window functions to link conversions to the closest base event. You can partition by the conversion source and get the `first_value` ordered by `visit ds`, descending to get the closest base event from the conversion event: + +```sql +select + first_value(v.ds) over (partition by b.ds, b.user_id, b.uuid order by v.ds desc) as v_ds, + first_value(v.user_id) over (partition by b.ds, b.user_id, b.uuid order by v.ds desc) as user_id, + first_value(v.referrer_id) over (partition by b.ds, b.user_id, b.uuid order by v.ds desc) as referrer_id, + b.ds, + b.uuid, + 1 as buys +from visits v +inner join ( + select *, uuid_string() as uuid from buys +) b +on +v.user_id = b.user_id and v.ds <= b.ds and v.ds > b.ds - interval '7 day' +``` + +The dataset returns the following: + +| V.DS | V.USER_ID | V.REFERRER_ID | B.DS | UUID | BUYS | +| --- | --- | --- | --- | --- | --- | +| 2020-01-01 | bob | facebook | 2020-01-02 | uuid1 | 1 | +| 2020-01-07 | bob | amazon | 2020-01-07 | uuid2 | 1 | +| 2020-01-07 | bob | amazon | 2020-01-07 | uuid2 | 1 | +| 2020-01-07 | bob | amazon | 2020-01-07 | uuid2 | 1 | + +This workflow links the two conversions to the correct visit events. Due to the join, you end up with multiple combinations, leading to fanout results. After applying the window function, duplicates appear. + +To resolve this and eliminate duplicates, use a distinct select. The UUID also helps identify which conversion is unique. The next steps provide more detail on how to do this. + +### Step 3: Remove duplicates + +Instead of regular select used in the [Step 2](#step-2-refine-with-window-function), use a distinct select to remove the duplicates: + +```sql +select distinct + first_value(v.ds) over (partition by b.ds, b.user_id, b.uuid order by v.ds desc) as v_ds, + first_value(v.user_id) over (partition by b.ds, b.user_id, b.uuid order by v.ds desc) as user_id, + first_value(v.referrer_id) over (partition by b.ds, b.user_id, b.uuid order by v.ds desc) as referrer_id, + b.ds, + b.uuid, + 1 as buys +from visits v +inner join ( + select *, uuid_string() as uuid from buys +) b +on +v.user_id = b.user_id and v.ds <= b.ds and v.ds > b.ds - interval '7 day'; +``` + +The dataset returns the following: + +| V.DS | V.USER_ID | V.REFERRER_ID | B.DS | UUID | BUYS | +| --- | --- | --- | --- | --- | --- | +| 2020-01-01 | bob | facebook | 2020-01-02 | uuid1 | 1 | +| 2020-01-07 | bob | amazon | 2020-01-07 | uuid2 | 1 | + +You now have a dataset where every conversion is connected to a visit event. To proceed: + +1. Sum up the total conversions in the "conversions" table. +2. Combine this table with the "opportunities" table, matching them based on group keys. +3. Calculate the conversion rate. + +### Step 4: Aggregate and calculate + +Now that you’ve tied each conversion event to a visit, you can calculate the aggregated conversions and opportunities measures. Then, you can join them to calculate the actual conversion rate. The SQL to calculate the conversion rate is as follows: + +```sql +select + coalesce(subq_3.metric_time__day, subq_13.metric_time__day) as metric_time__day, + cast(max(subq_13.buys) as double) / cast(nullif(max(subq_3.visits), 0) as double) as visit_to_buy_conversion_rate_7d +from ( -- base measure + select + metric_time__day, + sum(visits) as mqls + from ( + select + date_trunc('day', first_contact_date) as metric_time__day, + 1 as visits + from visits + ) subq_2 + group by + metric_time__day +) subq_3 +full outer join ( -- conversion measure + select + metric_time__day, + sum(buys) as sellers + from ( + -- ... + -- The output of this subquery is the table produced in Step 3. The SQL is hidden for legibility. + -- To see the full SQL output, add --explain to your conversion metric query. + ) subq_10 + group by + metric_time__day +) subq_13 +on + subq_3.metric_time__day = subq_13.metric_time__day +group by + metric_time__day +``` + +### Additional settings + +Use the following additional settings to customize your conversion metrics: + +- **Null conversion values:** Set null conversions to zero using `fill_nulls_with`. +- **Calculation type:** Choose between showing raw conversions or conversion rate. +- **Constant property:** Add conditions for specific scenarios to join conversions on constant properties. + +
+ - This question is tricky to answer because users could have completed these two conversion milestones across many products. For example, they may have viewed a pair of shoes, then a T-shirt, and eventually checked out with a bow tie. This would still count as a conversion, even though the conversion event only happened for the bow tie. + +Back to the initial questions, you want to see how many customers viewed an item detail page and then completed a purchase for the _same_ product. + +In this case, you want to set `product_id` as the constant property. You can specify this in the configs as follows: + +```yaml +- name: view_item_detail_to_purchase_with_same_item + description: "Conversion rate for users who viewed the item detail page and purchased the item" + type: Conversion + label: View Item Detail > Purchase + type_params: + conversion_type_params: + calculation: conversions + base_measure: view_item_detail + conversion_measure: purchase + entity: user + window: 1 week + constant_properties: + - base_property: product + conversion_property: product +``` + +You will add an additional condition to the join to make sure the constant property is the same across conversions. + +```sql +select distinct + first_value(v.ds) over (partition by buy_source.ds, buy_source.user_id, buy_source.session_id order by v.ds desc rows between unbounded preceding and unbounded following) as ds, + first_value(v.user_id) over (partition by buy_source.ds, buy_source.user_id, buy_source.session_id order by v.ds desc rows between unbounded preceding and unbounded following) as user_id, + first_value(v.referrer_id) over (partition by buy_source.ds, buy_source.user_id, buy_source.session_id order by v.ds desc rows between unbounded preceding and unbounded following) as referrer_id, + buy_source.uuid, + 1 as buys +from {{ source_schema }}.fct_view_item_details v +inner join + ( + select *, {{ generate_random_uuid() }} as uuid from {{ source_schema }}.fct_purchases + ) buy_source +on + v.user_id = buy_source.user_id + and v.ds <= buy_source.ds + and v.ds > buy_source.ds - interval '7 day' + and buy_source.product_id = v.product_id --Joining on the constant property product_id +``` + +
Use both the dbt Cloud CLI and dbt Core with `pip` and create a new virtual environment.
- **Use both dbt Cloud CLI and dbt Core with brew or native installs**
If you use Homebrew, consider aliasing the dbt Cloud CLI as "dbt-cloud" to avoid conflict. For more details, check the [FAQs](#faqs) if your operating system experiences path conflicts.
-- **Reverting back to dbt Core from the dbt Cloud CLI**
+- **Reverting to dbt Core from the dbt Cloud CLI**
If you've already installed the dbt Cloud CLI and need to switch back to dbt Core:
- Uninstall the dbt Cloud CLI using the command: `pip uninstall dbt` - Reinstall dbt Core using the following command, replacing "adapter_name" with the appropriate adapter name: @@ -223,7 +223,7 @@ During the public preview period, we recommend updating before filing a bug repo
Markdown files will use the Markdown syntax `()` | Command-Option-/ | Control-Alt-/ | -| Close the currently active editor tab | Option-W | Alt-W | +| Reveal a list of dbt functions in the editor | Enter two underscores `__` | Enter two underscores `__` | +| Open the command palette to invoke dbt commands and actions | Command-P / Command-Shift-P | Control-P / Control-Shift-P | +| Multi-edit in the editor by selecting multiple lines | Option-Click / Shift-Option-Command / Shift-Option-Click | Hold Alt and Click | +| Open the [**Invocation History Drawer**](/docs/cloud/dbt-cloud-ide/ide-user-interface#invocation-history) located at the bottom of the IDE. | Control-backtick (or Control + `) | Control-backtick (or Ctrl + `) | +| Add a block comment to the selected code. SQL files will use the Jinja syntax `({# #})` rather than the SQL one `(/* */)`.
Markdown files will use the Markdown syntax `()` | Command-Option-/ | Control-Alt-/ | ## Related docs diff --git a/website/docs/docs/cloud/dbt-cloud-ide/lint-format.md b/website/docs/docs/cloud/dbt-cloud-ide/lint-format.md index 733ec9dbcfe..37d8c8d814e 100644 --- a/website/docs/docs/cloud/dbt-cloud-ide/lint-format.md +++ b/website/docs/docs/cloud/dbt-cloud-ide/lint-format.md @@ -14,7 +14,7 @@ Linters analyze code for errors, bugs, and style issues, while formatters fix st -In the dbt Cloud IDE, you have the capability to perform linting, auto-fix, and formatting on five different file types: +In the dbt Cloud IDE, you can perform linting, auto-fix, and formatting on five different file types: - SQL — [Lint](#lint) and fix with SQLFluff, and [format](#format) with sqlfmt - YAML, Markdown, and JSON — Format with Prettier @@ -63,7 +63,7 @@ Linting doesn't support ephemeral models in dbt v1.5 and lower. Refer to the [FA - **Fix** button — Automatically fixes linting errors in the **File editor**. When fixing is complete, you'll see a message confirming the outcome. - Use the **Code Quality** tab to view and debug any code errors. -
-
+
+SQLFluff and sqlfmt are both tools used for formatting SQL code, but some differences may make one preferable to the other depending on your use case.
SQLFluff is a SQL code linter and formatter. This means that it analyzes your code to identify potential issues and bugs, and follows coding standards. It also formats your code according to a set of rules, which are [customizable](#customize-linting), to ensure consistent coding practices. You can also use SQLFluff to keep your SQL code well-formatted and follow styling best practices.
@@ -204,34 +202,37 @@ You can use either SQLFluff or sqlfmt depending on your preference and what work - Use sqlfmt to only have your code well-formatted without analyzing it for errors and bugs. You can use sqlfmt out of the box, making it convenient to use right away without having to configure it. -
+
-When should I use SQLFluff and when should I use sqlfmt?
- -SQLFluff and sqlfmt are both tools used for formatting SQL code, but there are some differences that may make one preferable to the other depending on your use case.+
SQLFluff is a SQL code linter and formatter. This means that it analyzes your code to identify potential issues and bugs, and follows coding standards. It also formats your code according to a set of rules, which are [customizable](#customize-linting), to ensure consistent coding practices. You can also use SQLFluff to keep your SQL code well-formatted and follow styling best practices.
@@ -204,34 +202,37 @@ You can use either SQLFluff or sqlfmt depending on your preference and what work - Use sqlfmt to only have your code well-formatted without analyzing it for errors and bugs. You can use sqlfmt out of the box, making it convenient to use right away without having to configure it. -
-Can I nest
+
To ensure optimal code quality, consistent code, and styles — it's highly recommended you have one main `.sqlfluff` configuration file in the root folder of your project. Having multiple files can result in various different SQL styles in your project.
However, you can customize and include an additional child `.sqlfluff` configuration file within specific subfolders of your dbt project.
By nesting a `.sqlfluff` file in a subfolder, SQLFluff will apply the rules defined in that subfolder's configuration file to any files located within it. The rules specified in the parent `.sqlfluff` file will be used for all other files and folders outside of the subfolder. This hierarchical approach allows for tailored linting rules while maintaining consistency throughout your project. Refer to [SQLFluff documentation](https://docs.sqlfluff.com/en/stable/configuration.html#configuration-files) for more info. -
+
-Can I nest .sqlfluff files?
+However, you can customize and include an additional child `.sqlfluff` configuration file within specific subfolders of your dbt project.
By nesting a `.sqlfluff` file in a subfolder, SQLFluff will apply the rules defined in that subfolder's configuration file to any files located within it. The rules specified in the parent `.sqlfluff` file will be used for all other files and folders outside of the subfolder. This hierarchical approach allows for tailored linting rules while maintaining consistency throughout your project. Refer to [SQLFluff documentation](https://docs.sqlfluff.com/en/stable/configuration.html#configuration-files) for more info. -
-
Currently, running SQLFluff commands from the terminal isn't supported.
-
+
-Can I run SQLFluff commands from the terminal?
+
-Why am I unable to see the
+
Make sure you're on a development branch. Formatting or Linting isn't available on "main" or "read-only" branches.
-
+
-Why am I unable to see the Lint or Format button?
+
-
-— If your lint operation passes despite clear rule violations, confirm you're not linting models with ephemeral models. Linting doesn't support ephemeral models in dbt v1.5 and lower. -
+Why is there inconsistent SQLFluff behavior when running outside the dbt Cloud IDE (such as a GitHub Action)?
-— Double-check your SQLFluff version matches the one in dbt Cloud IDE (found in the Code Quality tab after a lint operation).-— If your lint operation passes despite clear rule violations, confirm you're not linting models with ephemeral models. Linting doesn't support ephemeral models in dbt v1.5 and lower. -
+- If your lint operation passes despite clear rule violations, confirm you're not linting models with ephemeral models. Linting doesn't support ephemeral models in dbt v1.5 and lower. +
Overview of {frontMatter.meta.pypi_package}
+ +-
+
- Maintained by: {frontMatter.meta.maintained_by} +
- Authors: {frontMatter.meta.authors} +
- GitHub repo: {frontMatter.meta.github_repo} +
- PyPI package:
{frontMatter.meta.pypi_package}
+ - Supported dbt Core version: {frontMatter.meta.min_core_version} and newer +
- dbt Cloud support: {frontMatter.meta.cloud_support} +
- Minimum data platform version: {frontMatter.meta.min_supported_version} +
Installing {frontMatter.meta.pypi_package}
+ +Use `pip` to install the adapter, which automatically installs `dbt-core` and any additional dependencies. Use the following command for installation: + +python -m pip install {frontMatter.meta.pypi_package}
+
+
+Connecting to {frontMatter.meta.platform_name}
+ +#### Example profiles.yml +Here is an example of dbt-extrica profiles. At a minimum, you need to specify `type`, `method`, `username`, `password` `host`, `port`, `schema`, `catalog` and `threads`. +The [dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl) allows you to define metrics in code (with [MetricFlow](/docs/build/about-metricflow)) and dynamically generate and query datasets in downstream tools based on their dbt governed assets, such as metrics and models. Integrating with the dbt Semantic Layer will help organizations that use your product make more efficient and trustworthy decisions with their data. It also helps you to avoid duplicative coding, optimize development workflow, ensure data governance, and guarantee consistency for data consumers. diff --git a/website/docs/docs/dbt-cloud-apis/sl-graphql.md b/website/docs/docs/dbt-cloud-apis/sl-graphql.md index 3555b211f4f..f26a19a1930 100644 --- a/website/docs/docs/dbt-cloud-apis/sl-graphql.md +++ b/website/docs/docs/dbt-cloud-apis/sl-graphql.md @@ -22,10 +22,25 @@ GraphQL has several advantages, such as self-documenting, having a strong typing ## dbt Semantic Layer GraphQL API -The dbt Semantic Layer GraphQL API allows you to explore and query metrics and dimensions. Due to its self-documenting nature, you can explore the calls conveniently through the [schema explorer](https://semantic-layer.cloud.getdbt.com/api/graphql). +The dbt Semantic Layer GraphQL API allows you to explore and query metrics and dimensions. Due to its self-documenting nature, you can explore the calls conveniently through a schema explorer. + +The schema explorer URLs vary depending on your [deployment region](/docs/cloud/about-cloud/regions-ip-addresses). Use the following table to find the right link for your region: + +| Deployment type | Schema explorer URL | +| --------------- | ------------------- | +| North America multi-tenant | https://semantic-layer.cloud.getdbt.com/api/graphql | +| EMEA multi-tenant | https://semantic-layer.emea.dbt.com/api/graphql | +| APAC multi-tenant | https://semantic-layer.au.dbt.com/api/graphql | +| Single tenant | `https://YOUR_ACCESS_URL.semantic-layer/api/graphql`
Replace `YOUR_ACCESS_URL` with your specific account prefix with the appropriate Access URL for your region and plan.| +| Multi-cell | `https://YOUR_ACCOUNT_PREFIX.semantic-layer.REGION.dbt.com/api/graphql`
Replace `YOUR_ACCOUNT_PREFIX` with your specific account identifier and `REGION` with your location, which could be `us1.dbt.com`. |
+ +**Example** +- If your Single tenant access URL is `ABC123.getdbt.com`, your schema explorer URL will be `https://ABC123.getdbt.com.semantic-layer/api/graphql`. dbt Partners can use the Semantic Layer GraphQL API to build an integration with the dbt Semantic Layer. +Note that the dbt Semantic Layer API doesn't support `ref` to call dbt objects. Instead, use the complete qualified table name. If you're using dbt macros at query time to calculate your metrics, you should move those calculations into your Semantic Layer metric definitions as code. + ## Requirements to use the GraphQL API - A dbt Cloud project on dbt v1.6 or higher - Metrics are defined and configured @@ -204,6 +219,8 @@ DimensionType = [CATEGORICAL, TIME] ### Querying +When querying for data, _either_ a `groupBy` _or_ a `metrics` selection is required. + **Create Dimension Values query** ```graphql @@ -428,22 +445,35 @@ mutation { } ``` +**Query a categorical dimension on its own** + +```graphql +mutation { + createQuery( + environmentId: 123456 + groupBy: [{name: "customer__customer_type"}] + ) { + queryId + } +} +``` + **Query with a where filter** The `where` filter takes a list argument (or a string for a single input). Depending on the object you are filtering, there are a couple of parameters: - - `Dimension()` — Used for any categorical or time dimensions. If used for a time dimension, granularity is required. For example, `Dimension('metric_time').grain('week')` or `Dimension('customer__country')`. + - `Dimension()` — Used for any categorical or time dimensions. For example, `Dimension('metric_time').grain('week')` or `Dimension('customer__country')`. - `Entity()` — Used for entities like primary and foreign keys, such as `Entity('order_id')`. -Note: If you prefer a more strongly typed `where` clause, you can optionally use `TimeDimension()` to separate out categorical dimensions from time ones. The `TimeDimension` input takes the time dimension name and also requires granularity. For example, `TimeDimension('metric_time', 'MONTH')`. +Note: If you prefer a `where` clause with a more explicit path, you can optionally use `TimeDimension()` to separate categorical dimensions from time ones. The `TimeDimension` input takes the time dimension and optionally the granularity level. `TimeDimension('metric_time', 'month')`. ```graphql mutation { createQuery( environmentId: BigInt! metrics:[{name: "order_total"}] - groupBy:[{name: "customer__customer_type"}, {name: "metric_time", grain: MONTH}] + groupBy:[{name: "customer__customer_type"}, {name: "metric_time", grain: month}] where:[{sql: "{{ Dimension('customer__customer_type') }} = 'new'"}, {sql:"{{ Dimension('metric_time').grain('month') }} > '2022-10-01'"}] ) { queryId @@ -451,6 +481,55 @@ mutation { } ``` +For both `TimeDimension()`, the grain is only required in the WHERE filter if the aggregation time dimensions for the measures and metrics associated with the where filter have different grains. + +For example, consider this Semantic model and Metric configuration, which contains two metrics that are aggregated across different time grains. This example shows a single semantic model, but the same goes for metrics across more than one semantic model. + +```yaml +semantic_model: + name: my_model_source + +defaults: + agg_time_dimension: created_month + measures: + - name: measure_0 + agg: sum + - name: measure_1 + agg: sum + agg_time_dimension: order_year + dimensions: + - name: created_month + type: time + type_params: + time_granularity: month + - name: order_year + type: time + type_params: + time_granularity: year + +metrics: + - name: metric_0 + description: A metric with a month grain. + type: simple + type_params: + measure: measure_0 + - name: metric_1 + description: A metric with a year grain. + type: simple + type_params: + measure: measure_1 +``` + +Assuming the user is querying `metric_0` and `metric_1` together, a valid filter would be: + + * `"{{ TimeDimension('metric_time', 'year') }} > '2020-01-01'"` + +Invalid filters would be: + + * ` "{{ TimeDimension('metric_time') }} > '2020-01-01'"` — metrics in the query are defined based on measures with different grains. + + * `"{{ TimeDimension('metric_time', 'month') }} > '2020-01-01'"` — `metric_1` is not available at a month grain. + **Query with Order** ```graphql diff --git a/website/docs/docs/dbt-cloud-apis/sl-jdbc.md b/website/docs/docs/dbt-cloud-apis/sl-jdbc.md index 345be39635e..2e928db6af2 100644 --- a/website/docs/docs/dbt-cloud-apis/sl-jdbc.md +++ b/website/docs/docs/dbt-cloud-apis/sl-jdbc.md @@ -33,6 +33,8 @@ You *may* be able to use our JDBC API with tools that do not have an official in Refer to [Get started with the dbt Semantic Layer](/docs/use-dbt-semantic-layer/quickstart-sl) for more info. +Note that the dbt Semantic Layer API doesn't support `ref` to call dbt objects. Instead, use the complete qualified table name. If you're using dbt macros at query time to calculate your metrics, you should move those calculations into your Semantic Layer metric definitions as code. + ## Authentication dbt Cloud authorizes requests to the dbt Semantic Layer API. You need to provide an environment ID, host, and [service account tokens](/docs/dbt-cloud-apis/service-tokens). @@ -90,9 +92,9 @@ select * from {{
- When you select a dimension on its own, such as `metric_time` you can use the shorthand method which doesn't need the “Dimension” syntax. However, when you perform operations on the dimension, such as adding granularity, the object syntax `[Dimension('metric_time')` is required. +
- The double underscore `"__"` syntax indicates a mapping from an entity to a dimension, as well as where the dimension is located. For example, `user__country` means someone is looking at the `country` dimension from the `user` table. +So for example, if the `time_dimension_name` is `ds` and the granularity level is yearly, the output is `ds__year`. -- **What is the default output when adding granularity?**
- The default output follows the format `{time_dimension_name}__{granularity_level}`. So for example, if the time dimension name is `ds` and the granularity level is yearly, the output is `ds__year`. +
-:::info Important
-
-If you have not already, you must add `config-version: 2` to your dbt_project.yml file.
-See **Upgrading to v0.17.latest from v0.16** below for more details.
-
-:::
diff --git a/website/docs/docs/deploy/ci-jobs.md b/website/docs/docs/deploy/ci-jobs.md
index 149a6951fdc..9b96bb4b766 100644
--- a/website/docs/docs/deploy/ci-jobs.md
+++ b/website/docs/docs/deploy/ci-jobs.md
@@ -11,12 +11,12 @@ You can set up [continuous integration](/docs/deploy/continuous-integration) (CI
dbt Labs recommends that you create your CI job in a dedicated dbt Cloud [deployment environment](/docs/deploy/deploy-environments#create-a-deployment-environment) that's connected to a staging database. Having a separate environment dedicated for CI will provide better isolation between your temporary CI schema builds and your production data builds. Additionally, sometimes teams need their CI jobs to be triggered when a PR is made to a branch other than main. If your team maintains a staging branch as part of your release process, having a separate environment will allow you to set a [custom branch](/faqs/environments/custom-branch-settings) and, accordingly, the CI job in that dedicated environment will be triggered only when PRs are made to the specified custom branch. To learn more, refer to [Get started with CI tests](/guides/set-up-ci).
+
### Prerequisites
-- You have a dbt Cloud account.
+- You have a dbt Cloud account.
- For the [Concurrent CI checks](/docs/deploy/continuous-integration#concurrent-ci-checks) and [Smart cancellation of stale builds](/docs/deploy/continuous-integration#smart-cancellation) features, your dbt Cloud account must be on the [Team or Enterprise plan](https://www.getdbt.com/pricing/).
-- You must be connected using dbt Cloud’s native Git integration with [GitHub](/docs/cloud/git/connect-github), [GitLab](/docs/cloud/git/connect-gitlab), or [Azure DevOps](/docs/cloud/git/connect-azure-devops).
- - With GitLab, you need a paid or self-hosted account which includes support for GitLab webhooks and [project access tokens](https://docs.gitlab.com/ee/user/project/settings/project_access_tokens.html). With GitLab Free, merge requests will invoke CI jobs but CI status updates (success or failure of the job) will not be reported back to GitLab.
- - If you previously configured your dbt project by providing a generic git URL that clones using SSH, you must reconfigure the project to connect through dbt Cloud's native integration.
+- Set up a [connection with your Git provider](/docs/cloud/git/git-configuration-in-dbt-cloud). This integration lets dbt Cloud run jobs on your behalf for job triggering.
+ - If you're using a native [GitLab](/docs/cloud/git/connect-gitlab) integration, you need a paid or self-hosted account that includes support for GitLab webhooks and [project access tokens](https://docs.gitlab.com/ee/user/project/settings/project_access_tokens.html). If you're using GitLab Free, merge requests will trigger CI jobs but CI job status updates (success or failure of the job) will not be reported back to GitLab.
To make CI job creation easier, many options on the **CI job** page are set to default values that dbt Labs recommends that you use. If you don't want to use the defaults, you can change them.
@@ -63,12 +63,13 @@ If you're not using dbt Cloud’s native Git integration with [GitHub](/docs/cl
1. Set up a CI job with the [Create Job](/dbt-cloud/api-v2#/operations/Create%20Job) API endpoint using `"job_type": ci` or from the [dbt Cloud UI](#set-up-ci-jobs).
-1. Call the [Trigger Job Run](/dbt-cloud/api-v2#/operations/Trigger%20Job%20Run) API endpoint to trigger the CI job. You must include these fields to the payload:
- - Provide the pull request (PR) ID with one of these fields, even if you're using a different Git provider (like Bitbucket). This can make your code less human-readable but it will _not_ affect dbt functionality.
+1. Call the [Trigger Job Run](/dbt-cloud/api-v2#/operations/Trigger%20Job%20Run) API endpoint to trigger the CI job. You must include both of these fields to the payload:
+ - Provide the pull request (PR) ID using one of these fields:
- `github_pull_request_id`
- `gitlab_merge_request_id`
- - `azure_devops_pull_request_id`
+ - `azure_devops_pull_request_id`
+ - `non_native_pull_request_id` (for example, BitBucket)
- Provide the `git_sha` or `git_branch` to target the correct commit or branch to run the job against.
## Example pull requests
@@ -110,22 +111,6 @@ If you're experiencing any issues, review some of the common questions and answe
-
-
Reconnecting your dbt project to use dbt Cloud's native integration with GitHub, GitLab, or Azure DevOps
-
-
-If your dbt project relies the generic git clone method that clones using SSH and deploy keys to connect to your dbt repo, you need to disconnect your repo and reconnect it using the native GitHub, GitLab, or Azure DevOps integration in order to enable dbt Cloud CI.
- First, make sure you have the native GitHub authentication, native GitLab authentication, or native Azure DevOps authentication set up depending on which git provider you use. After you have gone through those steps, go to Account Settings, select Projects and click on the project you'd like to reconnect through native GitHub, GitLab, or Azure DevOps auth. Then click on the repository link.
- - Once you're in the repository page, select Edit and then Disconnect Repository at the bottom.
-
- Confirm that you'd like to disconnect your repository. You should then see a new Configure a repository link in your old repository's place. Click through to the configuration page:
-
- - Select the GitHub, GitLab, or AzureDevOps tab and reselect your repository. That should complete the setup of the project and enable you to set up a dbt Cloud CI job.
- - First, make sure you have the native GitHub authentication, native GitLab authentication, or native Azure DevOps authentication set up depending on which git provider you use. After you have gone through those steps, go to Account Settings, select Projects and click on the project you'd like to reconnect through native GitHub, GitLab, or Azure DevOps auth. Then click on the repository link.
- - Once you're in the repository page, select Edit and then Disconnect Repository at the bottom.
-
- Confirm that you'd like to disconnect your repository. You should then see a new Configure a repository link in your old repository's place. Click through to the configuration page:
-
- - Select the GitHub, GitLab, or AzureDevOps tab and reselect your repository. That should complete the setup of the project and enable you to set up a dbt Cloud CI job.
Error messages that refer to schemas from previous PRs
diff --git a/website/docs/docs/deploy/continuous-integration.md b/website/docs/docs/deploy/continuous-integration.md
index 0f87965aada..22686c44bd2 100644
--- a/website/docs/docs/deploy/continuous-integration.md
+++ b/website/docs/docs/deploy/continuous-integration.md
@@ -50,3 +50,6 @@ When you push a new commit to a PR, dbt Cloud enqueues a new CI run for the late
&jobId=&jobId=&to
```
:::
-
Team and Developer plans are limited to one project each. For additional projects, consider upgrading to the [Enterprise plan](https://www.getdbt.com/pricing/).| | Threads | When dbt builds a project's DAG, it tries to parallelize the execution by using threads. The [thread](/docs/running-a-dbt-project/using-threads) count is the maximum number of paths through the DAG that dbt can work on simultaneously. The default thread count in a job is 4. | | Wait time | Amount of time that dbt Cloud waits before running a job, either because there are no available slots or because a previous run of the same job is still in progress. | diff --git a/website/docs/docs/running-a-dbt-project/using-threads.md b/website/docs/docs/running-a-dbt-project/using-threads.md index 5eede7abc27..af00dd9cc68 100644 --- a/website/docs/docs/running-a-dbt-project/using-threads.md +++ b/website/docs/docs/running-a-dbt-project/using-threads.md @@ -22,5 +22,5 @@ You will define the number of threads in your `profiles.yml` file (for dbt Core ## Related docs -- [About profiles.yml](https://docs.getdbt.com/reference/profiles.yml) +- [About profiles.yml](/docs/core/connect-data-platform/profiles.yml) - [dbt Cloud job scheduler](/docs/deploy/job-scheduler) 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 665260ed9f4..11a610805a9 100644 --- a/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md +++ b/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md @@ -34,7 +34,7 @@ Use this guide to fully experience the power of the universal dbt Semantic Layer - [Define metrics](#define-metrics) in dbt using MetricFlow - [Test and query metrics](#test-and-query-metrics) with MetricFlow - [Run a production job](#run-a-production-job) in dbt Cloud -- [Set up dbt Semantic Layer](#setup) in dbt Cloud +- [Set up dbt Semantic Layer](#set-up-dbt-semantic-layer) in dbt Cloud - [Connect and query API](#connect-and-query-api) with dbt Cloud MetricFlow allows you to define metrics in your dbt project and query them whether in dbt Cloud or dbt Core with [MetricFlow commands](/docs/build/metricflow-commands). diff --git a/website/docs/faqs/API/rotate-token.md b/website/docs/faqs/API/rotate-token.md index 144c834ea8a..4470de72d5a 100644 --- a/website/docs/faqs/API/rotate-token.md +++ b/website/docs/faqs/API/rotate-token.md @@ -36,7 +36,7 @@ curl --location --request POST 'https://YOUR_ACCESS_URL/api/v2/users/YOUR_USER_I * Find your `YOUR_CURRENT_TOKEN` by going to **Profile Settings** -> **API Access** and copying the API key. * Find [`YOUR_ACCESS_URL`](/docs/cloud/about-cloud/regions-ip-addresses) for your region and plan. -:::info Example +Example: If `YOUR_USER_ID` = `123`, `YOUR_CURRENT_TOKEN` = `abcf9g`, and your `ACCESS_URL` = `cloud.getdbt.com`, then your curl request will be: @@ -44,7 +44,7 @@ If `YOUR_USER_ID` = `123`, `YOUR_CURRENT_TOKEN` = `abcf9g`, and your `ACCESS_URL curl --location --request POST 'https://cloud.getdbt.com/api/v2/users/123/apikey/' \ --header 'Authorization: Token abcf9g' ``` -::: + 2. Find the new key in the API response or in dbt Cloud. diff --git a/website/docs/faqs/Accounts/cloud-upgrade-instructions.md b/website/docs/faqs/Accounts/cloud-upgrade-instructions.md index f8daf393f9b..d16651a944c 100644 --- a/website/docs/faqs/Accounts/cloud-upgrade-instructions.md +++ b/website/docs/faqs/Accounts/cloud-upgrade-instructions.md @@ -6,11 +6,13 @@ description: "Instructions for upgrading a dbt Cloud account after the trial end dbt Cloud offers [several plans](https://www.getdbt.com/pricing/) with different features that meet your needs. This document is for dbt Cloud admins and explains how to select a plan in order to continue using dbt Cloud. -:::tip Before you begin -- You **_must_** be part of the [Owner](/docs/cloud/manage-access/self-service-permissions) user group to make billing changes. Users not included in this group will not see these options. +## Prerequisites + +Before you begin: +- You _must_ be part of the [Owner](/docs/cloud/manage-access/self-service-permissions) user group to make billing changes. Users not included in this group will not see these options. - All amounts shown in dbt Cloud are in U.S. Dollars (USD) - When your trial expires, your account's default plan enrollment will be a Team plan. -::: + ## Select a plan diff --git a/website/docs/faqs/Git/git-migration.md b/website/docs/faqs/Git/git-migration.md index 775ae3679e3..156227d59ae 100644 --- a/website/docs/faqs/Git/git-migration.md +++ b/website/docs/faqs/Git/git-migration.md @@ -16,7 +16,7 @@ To migrate from one git provider to another, refer to the following steps to avo 2. Go back to dbt Cloud and set up your [integration for the new git provider](/docs/cloud/git/connect-github), if needed. 3. Disconnect the old repository in dbt Cloud by going to **Account Settings** and then **Projects**. Click on the **Repository** link, then click **Edit** and **Disconnect**. -materializations you're familiar with, `table`, `view`, and `incremental` are implemented as macros in a package that's distributed along with dbt. You can check out the [source code for these materializations](https://github.com/dbt-labs/dbt-core/tree/main/core/dbt/include/global_project/macros/materializations). If you need to create your own materializations, reading these files is a good place to start. Continue reading below for a deep-dive into dbt materializations.
+The model materializations you're familiar with, `table`, `view`, and `incremental` are implemented as macros in a package that's distributed along with dbt. You can check out the [source code for these materializations](https://github.com/dbt-labs/dbt-core/tree/main/core/dbt/adapters/include/global_project/macros/materializations). If you need to create your own materializations, reading these files is a good place to start. Continue reading below for a deep-dive into dbt materializations.
:::caution
diff --git a/website/docs/guides/custom-cicd-pipelines.md b/website/docs/guides/custom-cicd-pipelines.md
index bd6d7617623..1778098f752 100644
--- a/website/docs/guides/custom-cicd-pipelines.md
+++ b/website/docs/guides/custom-cicd-pipelines.md
@@ -511,7 +511,7 @@ This section is only for those projects that connect to their git repository usi
:::
-The setup for this pipeline will use the same steps as the prior page. Before moving on, **follow steps 1-5 from the [prior page](https://docs.getdbt.com/guides/orchestration/custom-cicd-pipelines/3-dbt-cloud-job-on-merge)**
+The setup for this pipeline will use the same steps as the prior page. Before moving on, follow steps 1-5 from the [prior page](https://docs.getdbt.com/guides/custom-cicd-pipelines?step=2).
### 1. Create a pipeline job that runs when PRs are created
diff --git a/website/docs/guides/databricks-qs.md b/website/docs/guides/databricks-qs.md
index 5a0c5536e7f..cb01daec394 100644
--- a/website/docs/guides/databricks-qs.md
+++ b/website/docs/guides/databricks-qs.md
@@ -21,7 +21,6 @@ In this quickstart guide, you'll learn how to use dbt Cloud with Databricks. It
:::tip Videos for you
You can check out [dbt Fundamentals](https://courses.getdbt.com/courses/fundamentals) for free if you're interested in course learning with videos.
-
:::
### Prerequisites
diff --git a/website/docs/guides/debug-schema-names.md b/website/docs/guides/debug-schema-names.md
index c7bf1a195b1..24b7984adf5 100644
--- a/website/docs/guides/debug-schema-names.md
+++ b/website/docs/guides/debug-schema-names.md
@@ -14,11 +14,8 @@ recently_updated: true
## Introduction
-If a model uses the [`schema` config](/reference/resource-properties/schema) but builds under an unexpected schema, here are some steps for debugging the issue.
+If a model uses the [`schema` config](/reference/resource-properties/schema) but builds under an unexpected schema, here are some steps for debugging the issue. The full explanation on custom schemas can be found [here](/docs/build/custom-schemas).
-:::info
-The full explanation on custom schemas can be found [here](/docs/build/custom-schemas).
-:::
You can also follow along via this video:
@@ -94,9 +91,7 @@ Now, re-read through the logic of your `generate_schema_name` macro, and mentall
You should find that the schema dbt is constructing for your model matches the output of your `generate_schema_name` macro.
-:::info
-Note that snapshots do not follow this behavior, check out the docs on [target_schema](/reference/resource-configs/target_schema) instead.
-:::
+Be careful. Snapshots do not follow this behavior, check out the docs on [target_schema](/reference/resource-configs/target_schema) instead.
## Adjust as necessary
diff --git a/website/docs/guides/how-to-use-databricks-workflows-to-run-dbt-cloud-jobs.md b/website/docs/guides/how-to-use-databricks-workflows-to-run-dbt-cloud-jobs.md
index cb3a6804247..a2967ccbe15 100644
--- a/website/docs/guides/how-to-use-databricks-workflows-to-run-dbt-cloud-jobs.md
+++ b/website/docs/guides/how-to-use-databricks-workflows-to-run-dbt-cloud-jobs.md
@@ -128,15 +128,14 @@ if __name__ == '__main__':
4. Replace **``** and **``** with the correct values of your environment and [Access URL](/docs/cloud/about-cloud/regions-ip-addresses) for your region and plan.
-:::tip
- To find these values, navigate to **dbt Cloud**, select **Deploy -> Jobs**. Select the Job you want to run and copy the URL. For example: `https://cloud.getdbt.com/deploy/000000/projects/111111/jobs/222222`
-and therefore valid code would be:
+ * To find these values, navigate to **dbt Cloud**, select **Deploy -> Jobs**. Select the Job you want to run and copy the URL. For example: `https://cloud.getdbt.com/deploy/000000/projects/111111/jobs/222222`
+ and therefore valid code would be:
- # Your URL is structured https:///deploy//projects//jobs/
+Your URL is structured `https:///deploy//projects//jobs/`
account_id = 000000
job_id = 222222
base_url = "cloud.getdbt.com"
-:::
+
5. Run the Notebook. It will fail, but you should see **a `job_id` widget** at the top of your notebook.
@@ -161,9 +160,7 @@ DbtJobRunStatus.RUNNING
DbtJobRunStatus.SUCCESS
```
-:::note
You can cancel the job from dbt Cloud if necessary.
-:::
## Configure the workflows to run the dbt Cloud jobs
diff --git a/website/docs/guides/manual-install-qs.md b/website/docs/guides/manual-install-qs.md
index e9c1af259ac..fcd1e5e9599 100644
--- a/website/docs/guides/manual-install-qs.md
+++ b/website/docs/guides/manual-install-qs.md
@@ -70,7 +70,7 @@ $ pwd
-6. Update the following values in the `dbt_project.yml` file:
+6. dbt provides the following values in the `dbt_project.yml` file:
Team and Developer plans are limited to one project each. For additional projects, consider upgrading to the [Enterprise plan](https://www.getdbt.com/pricing/).| | Threads | When dbt builds a project's DAG, it tries to parallelize the execution by using threads. The [thread](/docs/running-a-dbt-project/using-threads) count is the maximum number of paths through the DAG that dbt can work on simultaneously. The default thread count in a job is 4. | | Wait time | Amount of time that dbt Cloud waits before running a job, either because there are no available slots or because a previous run of the same job is still in progress. | diff --git a/website/docs/docs/running-a-dbt-project/using-threads.md b/website/docs/docs/running-a-dbt-project/using-threads.md index 5eede7abc27..af00dd9cc68 100644 --- a/website/docs/docs/running-a-dbt-project/using-threads.md +++ b/website/docs/docs/running-a-dbt-project/using-threads.md @@ -22,5 +22,5 @@ You will define the number of threads in your `profiles.yml` file (for dbt Core ## Related docs -- [About profiles.yml](https://docs.getdbt.com/reference/profiles.yml) +- [About profiles.yml](/docs/core/connect-data-platform/profiles.yml) - [dbt Cloud job scheduler](/docs/deploy/job-scheduler) 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 665260ed9f4..11a610805a9 100644 --- a/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md +++ b/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md @@ -34,7 +34,7 @@ Use this guide to fully experience the power of the universal dbt Semantic Layer - [Define metrics](#define-metrics) in dbt using MetricFlow - [Test and query metrics](#test-and-query-metrics) with MetricFlow - [Run a production job](#run-a-production-job) in dbt Cloud -- [Set up dbt Semantic Layer](#setup) in dbt Cloud +- [Set up dbt Semantic Layer](#set-up-dbt-semantic-layer) in dbt Cloud - [Connect and query API](#connect-and-query-api) with dbt Cloud MetricFlow allows you to define metrics in your dbt project and query them whether in dbt Cloud or dbt Core with [MetricFlow commands](/docs/build/metricflow-commands). diff --git a/website/docs/faqs/API/rotate-token.md b/website/docs/faqs/API/rotate-token.md index 144c834ea8a..4470de72d5a 100644 --- a/website/docs/faqs/API/rotate-token.md +++ b/website/docs/faqs/API/rotate-token.md @@ -36,7 +36,7 @@ curl --location --request POST 'https://YOUR_ACCESS_URL/api/v2/users/YOUR_USER_I * Find your `YOUR_CURRENT_TOKEN` by going to **Profile Settings** -> **API Access** and copying the API key. * Find [`YOUR_ACCESS_URL`](/docs/cloud/about-cloud/regions-ip-addresses) for your region and plan. -:::info Example +Example: If `YOUR_USER_ID` = `123`, `YOUR_CURRENT_TOKEN` = `abcf9g`, and your `ACCESS_URL` = `cloud.getdbt.com`, then your curl request will be: @@ -44,7 +44,7 @@ If `YOUR_USER_ID` = `123`, `YOUR_CURRENT_TOKEN` = `abcf9g`, and your `ACCESS_URL curl --location --request POST 'https://cloud.getdbt.com/api/v2/users/123/apikey/' \ --header 'Authorization: Token abcf9g' ``` -::: + 2. Find the new key in the API response or in dbt Cloud. diff --git a/website/docs/faqs/Accounts/cloud-upgrade-instructions.md b/website/docs/faqs/Accounts/cloud-upgrade-instructions.md index f8daf393f9b..d16651a944c 100644 --- a/website/docs/faqs/Accounts/cloud-upgrade-instructions.md +++ b/website/docs/faqs/Accounts/cloud-upgrade-instructions.md @@ -6,11 +6,13 @@ description: "Instructions for upgrading a dbt Cloud account after the trial end dbt Cloud offers [several plans](https://www.getdbt.com/pricing/) with different features that meet your needs. This document is for dbt Cloud admins and explains how to select a plan in order to continue using dbt Cloud. -:::tip Before you begin -- You **_must_** be part of the [Owner](/docs/cloud/manage-access/self-service-permissions) user group to make billing changes. Users not included in this group will not see these options. +## Prerequisites + +Before you begin: +- You _must_ be part of the [Owner](/docs/cloud/manage-access/self-service-permissions) user group to make billing changes. Users not included in this group will not see these options. - All amounts shown in dbt Cloud are in U.S. Dollars (USD) - When your trial expires, your account's default plan enrollment will be a Team plan. -::: + ## Select a plan diff --git a/website/docs/faqs/Git/git-migration.md b/website/docs/faqs/Git/git-migration.md index 775ae3679e3..156227d59ae 100644 --- a/website/docs/faqs/Git/git-migration.md +++ b/website/docs/faqs/Git/git-migration.md @@ -16,7 +16,7 @@ To migrate from one git provider to another, refer to the following steps to avo 2. Go back to dbt Cloud and set up your [integration for the new git provider](/docs/cloud/git/connect-github), if needed. 3. Disconnect the old repository in dbt Cloud by going to **Account Settings** and then **Projects**. Click on the **Repository** link, then click **Edit** and **Disconnect**. -
-BigQuery allows defining `not null` constraints. However, it does _not_ support or enforce the definition of unenforced constraints, such as `primary key`.
+BigQuery allows defining and enforcing `not null` constraints, and defining (but _not_ enforcing) `primary key` and `foreign key` constraints (which can be used for query optimization). BigQuery does not support defining or enforcing other constraints. For more information, refer to [Platform constraint support](/docs/collaborate/govern/model-contracts#platform-constraint-support)
Documentation: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-definition-language
diff --git a/website/docs/reference/resource-properties/database.md b/website/docs/reference/resource-properties/database.md
index c2f6ba76dd8..59159495435 100644
--- a/website/docs/reference/resource-properties/database.md
+++ b/website/docs/reference/resource-properties/database.md
@@ -26,12 +26,9 @@ The database that your source is stored in.
Note that to use this parameter, your warehouse must allow cross-database queries.
-:::info
-
#### BigQuery terminology
-If you're using BigQuery, use the _project_ name as the `database:` property.
-:::
+If you're using BigQuery, use the _project_ name as the `database:` property.
## Default
By default, dbt will search in your target database (i.e. the database that you are creating tables and views ).
diff --git a/website/docs/reference/resource-properties/freshness.md b/website/docs/reference/resource-properties/freshness.md
index f332f5a1b8f..0b017991d68 100644
--- a/website/docs/reference/resource-properties/freshness.md
+++ b/website/docs/reference/resource-properties/freshness.md
@@ -37,6 +37,38 @@ A freshness block is used to define the acceptable amount of time between the mo
In the `freshness` block, one or both of `warn_after` and `error_after` can be provided. If neither is provided, then dbt will not calculate freshness snapshots for the tables in this source.
+
+
+In most cases, the `loaded_at_field` is required. Some adapters support calculating source freshness from the warehouse metadata tables and can exclude the `loaded_at_field`.
+
+If a source has a `freshness:` block, dbt will attempt to calculate freshness for that source:
+- If a `loaded_at_field` is provided, dbt will calculate freshness via a select query (behavior prior to v1.7).
+- If a `loaded_at_field` is _not_ provided, dbt will calculate freshness via warehouse metadata tables when possible (new in v1.7 on supported adapters).
+
+Currently, calculating freshness from warehouse metadata tables is supported on:
+- [Snowflake](/reference/resource-configs/snowflake-configs)
+
+Support is coming soon to the following adapters:
+- [Redshift](/reference/resource-configs/redshift-configs)
+- [BigQuery](/reference/resource-configs/bigquery-configs)
+- [Spark](/reference/resource-configs/spark-configs)
+
+Freshness blocks are applied hierarchically:
+- a `freshness` and `loaded_at_field` property added to a source will be applied to all all tables defined in that source
+- a `freshness` and `loaded_at_field` property added to a source _table_ will override any properties applied to the source.
+
+This is useful when all of the tables in a source have the same `loaded_at_field`, as is often the case.
+
+To exclude a source from freshness calculations, you have two options:
+- Don't add a `freshness:` block.
+- Explicitly set `freshness: null`.
+
+## loaded_at_field
+(Optional on adapters that support pulling freshness from warehouse metadata tables, required otherwise.)
+
+
+
+
Additionally, the `loaded_at_field` is required to calculate freshness for a table. If a `loaded_at_field` is not provided, then dbt will not calculate freshness for the table.
Freshness blocks are applied hierarchically:
@@ -47,7 +79,7 @@ This is useful when all of the tables in a source have the same `loaded_at_field
## loaded_at_field
(Required)
-
+
A column name (or expression) that returns a timestamp indicating freshness.
If using a date field, you may have to cast it to a timestamp:
diff --git a/website/docs/reference/resource-properties/schema.md b/website/docs/reference/resource-properties/schema.md
index 9e6a09b8569..157a9ffc0a2 100644
--- a/website/docs/reference/resource-properties/schema.md
+++ b/website/docs/reference/resource-properties/schema.md
@@ -27,12 +27,10 @@ The schema name as stored in the database.
This parameter is useful if you want to use a source name that differs from the schema name.
-:::info
#### BigQuery terminology
-If you're using BigQuery, use the _dataset_ name as the `schema:` property.
-:::
+If you're using BigQuery, use the _dataset_ name as the `schema:` property.
## Default
By default, dbt will use the source's `name:` parameter as the schema name.
diff --git a/website/docs/reference/seed-properties.md b/website/docs/reference/seed-properties.md
index 9201df65f4c..ebe222dd11c 100644
--- a/website/docs/reference/seed-properties.md
+++ b/website/docs/reference/seed-properties.md
@@ -16,6 +16,7 @@ seeds:
[description](/reference/resource-properties/description):
[docs](/reference/resource-configs/docs):
show: true | false
+ node_color: # Use name (such as node_color: purple) or hex code with quotes (such as node_color: "#cd7f32")
[config](/reference/resource-properties/config):
[](/reference/seed-configs):
[tests](/reference/resource-properties/data-tests):
diff --git a/website/docs/reference/snapshot-properties.md b/website/docs/reference/snapshot-properties.md
index 8f01fd8e988..49769af8f6d 100644
--- a/website/docs/reference/snapshot-properties.md
+++ b/website/docs/reference/snapshot-properties.md
@@ -20,6 +20,7 @@ snapshots:
[meta](/reference/resource-configs/meta): {}
[docs](/reference/resource-configs/docs):
show: true | false
+ node_color: # Use name (such as node_color: purple) or hex code with quotes (such as node_color: "#cd7f32")
[config](/reference/resource-properties/config):
[](/reference/snapshot-configs):
[tests](/reference/resource-properties/data-tests):
diff --git a/website/docs/sql-reference/aggregate-functions/sql-avg.md b/website/docs/sql-reference/aggregate-functions/sql-avg.md
index d1dba119292..1512cee7763 100644
--- a/website/docs/sql-reference/aggregate-functions/sql-avg.md
+++ b/website/docs/sql-reference/aggregate-functions/sql-avg.md
@@ -17,6 +17,8 @@ The AVG function is a part of the group of mathematical or aggregate functions (
### AVG function example
+The following example is querying from a sample dataset created by dbt Labs called [jaffle_shop](https://github.com/dbt-labs/jaffle_shop):
+
```sql
select
date_trunc('month', order_date) as order_month,
@@ -26,10 +28,6 @@ where status not in ('returned', 'return_pending')
group by 1
```
-:::note What dataset is this?
-This example is querying from a sample dataset created by dbt Labs called [jaffle_shop](https://github.com/dbt-labs/jaffle_shop).
-:::
-
This query using the Jaffle Shop’s `orders` table will return the rounded order amount per each order month:
| order_month | avg_order_amount |
diff --git a/website/docs/sql-reference/aggregate-functions/sql-count.md b/website/docs/sql-reference/aggregate-functions/sql-count.md
index d65c670df90..1438b7c11d5 100644
--- a/website/docs/sql-reference/aggregate-functions/sql-count.md
+++ b/website/docs/sql-reference/aggregate-functions/sql-count.md
@@ -25,6 +25,8 @@ Let’s take a look at a practical example using COUNT, DISTINCT, and GROUP BY b
### COUNT example
+The following example is querying from a sample dataset created by dbt Labs called [jaffle_shop](https://github.com/dbt-labs/jaffle_shop):
+
```sql
select
date_part('month', order_date) as order_month,
@@ -34,9 +36,6 @@ from {{ ref('orders') }}
group by 1
```
-:::note What dataset is this?
-This example is querying from a sample dataset created by dbt Labs called [jaffle_shop](https://github.com/dbt-labs/jaffle_shop).
-:::
This simple query is something you may do while doing initial exploration of your data; it will return the count of `order_ids` and count of distinct `customer_ids` per order month that appear in the Jaffle Shop’s `orders` table:
diff --git a/website/docs/sql-reference/aggregate-functions/sql-max.md b/website/docs/sql-reference/aggregate-functions/sql-max.md
index 0b5dc5521ea..fab72770af5 100644
--- a/website/docs/sql-reference/aggregate-functions/sql-max.md
+++ b/website/docs/sql-reference/aggregate-functions/sql-max.md
@@ -25,6 +25,8 @@ Let’s take a look at a practical example using MAX and GROUP BY below.
### MAX example
+The following example is querying from a sample dataset created by dbt Labs called [jaffle_shop](https://github.com/dbt-labs/jaffle_shop):
+
```sql
select
date_part('month', order_date) as order_month,
@@ -33,10 +35,6 @@ from {{ ref('orders') }}
group by 1
```
-:::note What dataset is this?
-This example is querying from a sample dataset created by dbt Labs called [jaffle_shop](https://github.com/dbt-labs/jaffle_shop).
-:::
-
This simple query is something you may do while doing initial exploration of your data; it will return the maximum order `amount` per order month that appear in the Jaffle Shop’s `orders` table:
| order_month | max_amount |
diff --git a/website/docs/sql-reference/aggregate-functions/sql-min.md b/website/docs/sql-reference/aggregate-functions/sql-min.md
index 6080bb20c0b..95de0af8df3 100644
--- a/website/docs/sql-reference/aggregate-functions/sql-min.md
+++ b/website/docs/sql-reference/aggregate-functions/sql-min.md
@@ -27,6 +27,8 @@ Let’s take a look at a practical example using MIN below.
### MIN example
+The following example is querying from a sample dataset created by dbt Labs called [jaffle_shop](https://github.com/dbt-labs/jaffle_shop):
+
```sql
select
customer_id,
@@ -37,10 +39,6 @@ group by 1
limit 3
```
-:::note What dataset is this?
-This example is querying from a sample dataset created by dbt Labs called [jaffle_shop](https://github.com/dbt-labs/jaffle_shop).
-:::
-
This simple query is returning the first and last order date for a customer in the Jaffle Shop’s `orders` table:
| customer_id | first_order_date | last_order_date |
diff --git a/website/docs/sql-reference/aggregate-functions/sql-round.md b/website/docs/sql-reference/aggregate-functions/sql-round.md
index bc9669e22cb..a080f5a63e5 100644
--- a/website/docs/sql-reference/aggregate-functions/sql-round.md
+++ b/website/docs/sql-reference/aggregate-functions/sql-round.md
@@ -24,11 +24,8 @@ In this function, you’ll need to input the *numeric* field or data you want ro
### SQL ROUND function example
-:::note What dataset is this?
-This example is querying from a sample dataset created by dbt Labs called [jaffle_shop](https://github.com/dbt-labs/jaffle_shop).
-:::
-You can round some of the numeric fields of the Jaffle Shop’s `orders` model using the following code:
+You can round some of the numeric fields of the [Jaffle Shop’s](https://github.com/dbt-labs/jaffle_shop) `orders` model using the following code:
```sql
select
diff --git a/website/docs/sql-reference/aggregate-functions/sql-sum.md b/website/docs/sql-reference/aggregate-functions/sql-sum.md
index d6ca00c2daa..494a3863ad3 100644
--- a/website/docs/sql-reference/aggregate-functions/sql-sum.md
+++ b/website/docs/sql-reference/aggregate-functions/sql-sum.md
@@ -27,6 +27,8 @@ Let’s take a look at a practical example using the SUM function below.
### SUM example
+The following example is querying from a sample dataset created by dbt Labs called [jaffle_shop](https://github.com/dbt-labs/jaffle_shop):
+
```sql
select
customer_id,
@@ -36,10 +38,6 @@ group by 1
limit 3
```
-:::note What dataset is this?
-This example is querying from a sample dataset created by dbt Labs called [jaffle_shop](https://github.com/dbt-labs/jaffle_shop).
-:::
-
This simple query is returning the summed amount of all orders for a customer in the Jaffle Shop’s `orders` table:
| customer_id | all_orders_amount |
diff --git a/website/docs/terms/data-extraction.md b/website/docs/terms/data-extraction.md
index bc37b68cf66..52148a35421 100644
--- a/website/docs/terms/data-extraction.md
+++ b/website/docs/terms/data-extraction.md
@@ -37,7 +37,7 @@ Obviously, the type of business you work for and the systems your team uses will
The data that is typically extracted and loaded in your data warehouse is data that business users will need for baseline reporting, OKR measurement, or other analytics.
:::tip Don’t fix what’s not broken
-As we just said, there are usually common data sources that data teams will extract from, regardless of business. Instead of writing transformations for these tables and data sources, leverage [dbt packages](https://hub.getdbt.com/) to save yourself some carpal tunnel and use the work someone else has already done for you :)
+As we just said, there are usually common data sources that data teams will extract from, regardless of business. Instead of writing transformations for these tables and data sources, leverage [dbt packages](https://hub.getdbt.com/) to save yourself some carpal tunnel and use the work someone else has already done for you.
:::
## Data extraction tools
diff --git a/website/docs/terms/table.md b/website/docs/terms/table.md
index cbe36ec1315..bfc4e680660 100644
--- a/website/docs/terms/table.md
+++ b/website/docs/terms/table.md
@@ -5,9 +5,6 @@ description: "Read this guide to understand how tables work in dbt."
displayText: table
hoverSnippet: In simplest terms, a table is the direct storage of data in rows and columns. Think excel sheet with raw values in each of the cells.
---
-:::important This page could use some love
-This term would benefit from additional depth and examples. Have knowledge to contribute? [Create an issue in the docs.getdbt.com repository](https://github.com/dbt-labs/docs.getdbt.com/issues/new/choose) to begin the process of becoming a glossary contributor!
-:::
In simplest terms, a table is the direct storage of data in rows and columns. Think excel sheet with raw values in each of the cells.
diff --git a/website/sidebars.js b/website/sidebars.js
index 9085baac54a..5d950f43c26 100644
--- a/website/sidebars.js
+++ b/website/sidebars.js
@@ -212,6 +212,7 @@ const sidebarSettings = {
"docs/core/connect-data-platform/decodable-setup",
"docs/core/connect-data-platform/upsolver-setup",
"docs/core/connect-data-platform/starrocks-setup",
+ "docs/core/connect-data-platform/extrica-setup",
],
},
],
@@ -323,6 +324,7 @@ const sidebarSettings = {
link: { type: "doc", id: "docs/build/metrics-overview" },
items: [
"docs/build/metrics-overview",
+ "docs/build/conversion",
"docs/build/cumulative",
"docs/build/derived",
"docs/build/ratio",
@@ -1028,6 +1030,8 @@ const sidebarSettings = {
id: "best-practices/how-we-build-our-metrics/semantic-layer-1-intro",
},
items: [
+ "best-practices/how-we-build-our-metrics/semantic-layer-1-intro",
+ "best-practices/how-we-build-our-metrics/semantic-layer-2-setup",
"best-practices/how-we-build-our-metrics/semantic-layer-3-build-semantic-models",
"best-practices/how-we-build-our-metrics/semantic-layer-4-build-metrics",
"best-practices/how-we-build-our-metrics/semantic-layer-5-refactor-a-mart",
@@ -1045,6 +1049,7 @@ const sidebarSettings = {
items: [
"best-practices/how-we-mesh/mesh-2-structures",
"best-practices/how-we-mesh/mesh-3-implementation",
+ "best-practices/how-we-mesh/mesh-4-faqs",
],
},
{
diff --git a/website/snippets/_cloud-environments-info.md b/website/snippets/_cloud-environments-info.md
index 6e096b83750..2083d8f07ec 100644
--- a/website/snippets/_cloud-environments-info.md
+++ b/website/snippets/_cloud-environments-info.md
@@ -1,4 +1,3 @@
-
## Types of environments
In dbt Cloud, there are two types of environments:
@@ -34,24 +33,6 @@ Both development and deployment environments have a section called **General Set
- If you select a current version with `(latest)` in the name, your environment will automatically install the latest stable version of the minor version selected.
:::
-### Git repository caching
-
-At the start of every job run, dbt Cloud clones the project's Git repository so it has the latest versions of your project's code and runs `dbt deps` to install your dependencies.
-
-For improved reliability and performance on your job runs, you can enable dbt Cloud to keep a cache of the project's Git repository. So, if there's a third-party outage that causes the cloning operation to fail, dbt Cloud will instead use the cached copy of the repo so your jobs can continue running as scheduled.
-
-dbt Cloud caches your project's Git repo after each successful run and retains it for 8 days if there are no repo updates. It caches all packages regardless of installation method and does not fetch code outside of the job runs.
-
-To enable Git repository caching, select **Account settings** from the gear menu and enable the **Repository caching** option.
-
-
(IDE or dbt Cloud CLI) | W | W | | W | | | | | | | | | | Environments | W | R | R | R | R | W | R | | | R | R | | | Jobs | W | R | R | W | R | W | R | | | R | R | | | Metadata | R | R | R | R | R | R | R | R | | R | R | | -| Permissions | W | | R | R | R | | | | | | W | | -| Profile | W | R | W | R | R | R | | | | R | R | | +| Permissions (Groups & Licenses) | W | | R | R | R | | | | | | W | | +| Profile (Credentials) | W | R | W | R | R | R | | | | R | R | | | Projects | W | W | W | W | W | R | R | | | R | W | | | Repositories | W | | R | R | W | | | | | R | R | | | Runs | W | R | R | W | R | W | R | | | R | R | | diff --git a/website/snippets/_new-sl-setup.md b/website/snippets/_new-sl-setup.md index a02481db33d..a93f233d09c 100644 --- a/website/snippets/_new-sl-setup.md +++ b/website/snippets/_new-sl-setup.md @@ -1,14 +1,12 @@ You can set up the dbt Semantic Layer in dbt Cloud at the environment and project level. Before you begin: -- You must have a dbt Cloud Team or Enterprise account. Suitable for both Multi-tenant and Single-tenant deployment. - - Single-tenant accounts should contact their account representative for necessary setup and enablement. - You must be part of the Owner group, and have the correct [license](/docs/cloud/manage-access/seats-and-users) and [permissions](/docs/cloud/manage-access/self-service-permissions) to configure the Semantic Layer: * Enterprise plan — Developer license with Account Admin permissions. Or Owner with a Developer license, assigned Project Creator, Database Admin, or Admin permissions. * Team plan — Owner with a Developer license. - You must have a successful run in your new environment. :::tip -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. +If you've configured the legacy Semantic Layer, it has been deprecated. 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. @@ -20,7 +18,10 @@ If you've configured the legacy Semantic Layer, it has been deprecated, and dbt
-Project dependencies are designed for the [dbt Mesh](/best-practices/how-we-mesh/mesh-1-intro) and [cross-project reference](/docs/collaborate/govern/project-dependencies#how-to-use-ref) workflow:
+Project dependencies are designed for the [dbt Mesh](/best-practices/how-we-mesh/mesh-1-intro) and [cross-project reference](/docs/collaborate/govern/project-dependencies#how-to-write-cross-project-ref) workflow:
- Use `dependencies.yml` when you need to set up cross-project references between different dbt projects, especially in a dbt Mesh setup.
- Use `dependencies.yml` when you want to include both projects and non-private dbt packages in your project's dependencies.
diff --git a/website/snippets/_privatelink-hostname-restriction.md b/website/snippets/_privatelink-hostname-restriction.md
new file mode 100644
index 00000000000..a4bcd318a15
--- /dev/null
+++ b/website/snippets/_privatelink-hostname-restriction.md
@@ -0,0 +1,5 @@
+:::caution Environment variables
+
+Using [Environment variables](/docs/build/environment-variables) when configuring PrivateLink endpoints isn't supported in dbt Cloud. Instead, use [Extended Attributes](/docs/deploy/deploy-environments#extended-attributes) to dynamically change these values in your dbt Cloud environment.
+
+:::
diff --git a/website/snippets/_sl-define-metrics.md b/website/snippets/_sl-define-metrics.md
index af3ee9f297f..fe169b4a5b4 100644
--- a/website/snippets/_sl-define-metrics.md
+++ b/website/snippets/_sl-define-metrics.md
@@ -1,6 +1,6 @@
Now that you've created your first semantic model, it's time to define your first metric! You can define metrics with the dbt Cloud IDE or command line.
-MetricFlow supports different metric types like [simple](/docs/build/simple), [ratio](/docs/build/ratio), [cumulative](/docs/build/cumulative), and [derived](/docs/build/derived). It's recommended that you read the [metrics overview docs](/docs/build/metrics-overview) before getting started.
+MetricFlow supports different metric types like [conversion](/docs/build/conversion), [simple](/docs/build/simple), [ratio](/docs/build/ratio), [cumulative](/docs/build/cumulative), and [derived](/docs/build/derived). It's recommended that you read the [metrics overview docs](/docs/build/metrics-overview) before getting started.
1. You can define metrics in the same YAML files as your semantic models or create a new file. If you want to create your metrics in a new file, create another directory called `/models/metrics`. The file structure for metrics can become more complex from here if you need to further organize your metrics, for example, by data source or business line.
diff --git a/website/snippets/_upgrade-move.md b/website/snippets/_upgrade-move.md
deleted file mode 100644
index 7572077fd1b..00000000000
--- a/website/snippets/_upgrade-move.md
+++ /dev/null
@@ -1,5 +0,0 @@
-:::important Upgrade Guides Are Moving
-
-The location of the dbt Core upgrade guides has changed, and they will soon be removed from `Guides`. The new location is in the `Docs` tab under `Available dbt versions`. You have been redirected to the new URL, so please update any saved links and bookmarks.
-
-:::
\ No newline at end of file
diff --git a/website/snippets/_v2-sl-prerequisites.md b/website/snippets/_v2-sl-prerequisites.md
index 99d8a945db6..18f228ad3fe 100644
--- a/website/snippets/_v2-sl-prerequisites.md
+++ b/website/snippets/_v2-sl-prerequisites.md
@@ -7,4 +7,4 @@
- Set up the [Semantic Layer API](/docs/dbt-cloud-apis/sl-api-overview) in the integrated tool to import metric definitions.
- 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. +- 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 support the dbt Semantic Layer yet. diff --git a/website/snippets/available-beta-banner.md b/website/snippets/available-beta-banner.md deleted file mode 100644 index 15d365a84b1..00000000000 --- a/website/snippets/available-beta-banner.md +++ /dev/null @@ -1,3 +0,0 @@ -:::info Beta feature -This feature is currently in beta and subject to change. If you are interested in getting access to the beta, please [contact us](mailto:support@getdbt.com). -::: diff --git a/website/snippets/available-prerelease-banner.md b/website/snippets/available-prerelease-banner.md deleted file mode 100644 index 3531a2f646f..00000000000 --- a/website/snippets/available-prerelease-banner.md +++ /dev/null @@ -1,7 +0,0 @@ -:::info Release candidate -dbt Core v1.2 is now available as a **release candidate**. - -For more information on prereleases, see ["About Core versions: Trying prereleases"](core-versions#trying-prereleases). - -Join the [#dbt-prereleases](https://getdbt.slack.com/archives/C016X6ABVUK) channel in the Community Slack so you can be the first to read about prereleases as soon as they're available! -::: diff --git a/website/snippets/quickstarts/schedule-a-job.md b/website/snippets/quickstarts/schedule-a-job.md index ab8f4350dbf..70848388f35 100644 --- a/website/snippets/quickstarts/schedule-a-job.md +++ b/website/snippets/quickstarts/schedule-a-job.md @@ -35,9 +35,9 @@ As the `jaffle_shop` business gains more customers, and those customers create m 8. Click the run and watch its progress under "Run history." 9. Once the run is complete, click **View Documentation** to see the docs for your project. -:::tip + Congratulations 🎉! You've just deployed your first dbt project! -::: + #### FAQs diff --git a/website/snippets/sl-considerations-banner.md b/website/snippets/sl-considerations-banner.md deleted file mode 100644 index 33cfb5edac5..00000000000 --- a/website/snippets/sl-considerations-banner.md +++ /dev/null @@ -1,8 +0,0 @@ -:::caution Considerations - -Some important considerations to know about using the dbt Semantic Layer during the Public Preview: - -- Support for Snowflake data platform only (_additional data platforms coming soon_) -- Support for the deployment environment only (_development experience coming soon_) - -::: diff --git a/website/snippets/test-snippet.md b/website/snippets/test-snippet.md deleted file mode 100644 index c1de326aa7a..00000000000 --- a/website/snippets/test-snippet.md +++ /dev/null @@ -1,8 +0,0 @@ ---- ---- - -### Header 2 - -Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nullam fermentum porttitor dui, id scelerisque enim scelerisque at. Proin imperdiet sem sed magna ornare, sit amet rutrum ligula vehicula. Aenean eget magna placerat, dictum velit sed, dapibus quam. Maecenas lectus tellus, dictum semper gravida vel, feugiat vitae nibh. Vestibulum nec lorem nibh. Fusce nisi felis, tincidunt ac scelerisque ut, aliquam in eros. Praesent euismod dolor ac lacinia laoreet. Phasellus orci orci, scelerisque vitae mollis id, consectetur ut libero. Aenean diam leo, tempor ut vulputate in, laoreet id ipsum. Quisque gravida et ex id eleifend. Etiam ultricies erat diam. Morbi hendrerit, ligula non aliquam tempus, erat elit suscipit quam, eu cursus quam nisi sit amet dui. Cras iaculis risus vel enim tempor molestie. - -Curabitur a porttitor odio. Curabitur sit amet tristique ante. Ut eleifend, erat eget imperdiet accumsan, quam diam sodales dolor, vulputate consequat lacus felis non sapien. Nam et nunc sed diam congue rutrum nec non massa. Nam eget fermentum sem. Nam ac imperdiet massa. Phasellus a elementum dui. diff --git a/website/snippets/tutorial-create-new-dbt-cloud-account.md b/website/snippets/tutorial-create-new-dbt-cloud-account.md deleted file mode 100644 index bdde874d0c9..00000000000 --- a/website/snippets/tutorial-create-new-dbt-cloud-account.md +++ /dev/null @@ -1,10 +0,0 @@ -Let's start this section by creating a dbt Cloud account if you haven't already. - -1. Navigate to [dbt Cloud](https://cloud.getdbt.com). -2. If you don't have a dbt Cloud account, create a new one, and verify your account via email. -3. If you already have a dbt Cloud account, you can create a new project from your existing account: - 1. Click the gear icon in the top-right, then click **Projects**. - 2. Click **+ New Project**. -4. You've arrived at the "Setup a New Project" page. -5. Type "Analytics" in the dbt Project Name field. You will be able to rename this project later. -6. Click **Continue**. \ No newline at end of file diff --git a/website/snippets/tutorial-initiate-project.md b/website/snippets/tutorial-initiate-project.md deleted file mode 100644 index 008b6bdf487..00000000000 --- a/website/snippets/tutorial-initiate-project.md +++ /dev/null @@ -1,44 +0,0 @@ -Now that you have a repository configured, you can initialize your project and start development in dbt Cloud: - -1. Click **Develop** from the upper left. It might take a few minutes for your project to spin up for the first time as it establishes your git connection, clones your repo, and tests the connection to the warehouse. -2. Above the file tree to the left, click **Initialize your project**. This builds out your folder structure with example models. -3. Make your initial commit by clicking **Commit**. Use the commit message `initial commit`. This creates the first commit to your managed repo and allows you to open a branch where you can add new dbt code. -4. Now you should be able to **directly query data from your warehouse** and **execute dbt run**. Paste your following warehouse-specific code in the IDE: - -
-
-
-
-- In the command line bar at the bottom, type `dbt run` and click **Enter**. We will explore what happens in the next section of the tutorial.
diff --git a/website/src/components/detailsToggle/index.js b/website/src/components/detailsToggle/index.js
index ba53192e54b..514ca52ba13 100644
--- a/website/src/components/detailsToggle/index.js
+++ b/website/src/components/detailsToggle/index.js
@@ -3,33 +3,50 @@ import styles from './styles.module.css';
function detailsToggle({ children, alt_header = null }) {
const [isOn, setOn] = useState(false);
- const [hoverActive, setHoverActive] = useState(true);
+ const [isScrolling, setIsScrolling] = useState(false); // New state to track scrolling
const [hoverTimeout, setHoverTimeout] = useState(null);
const handleToggleClick = () => {
- setHoverActive(true); // Disable hover when clicked
setOn(current => !current); // Toggle the current state
-};
-
-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 (!isOn) {
+ };
+
+ const handleMouseEnter = () => {
+ if (isOn || isScrolling) return; // Ignore hover if already open or if scrolling
+ const timeout = setTimeout(() => {
+ if (!isScrolling) setOn(true);
+ }, 700); //
+ setHoverTimeout(timeout);
+ };
+
+ const handleMouseLeave = () => {
+ if (!isOn) {
clearTimeout(hoverTimeout);
setOn(false);
- }
-};
+ }
+ };
+
+ const handleScroll = () => {
+ setIsScrolling(true);
+ clearTimeout(hoverTimeout);
+ //setOn(false);
+
+
+ // Reset scrolling state after a delay
+ setTimeout(() => {
+ setIsScrolling(false);
+ }, 800);
+ };
+
+ useEffect(() => {
+ window.addEventListener('scroll', handleScroll);
+ return () => {
+ window.removeEventListener('scroll', handleScroll);
+ };
+ }, []);
-useEffect(() => {
- return () => clearTimeout(hoverTimeout);
-}, [hoverTimeout]);
+ useEffect(() => {
+ return () => clearTimeout(hoverTimeout);
+ }, [hoverTimeout]);
return (
(IDE or dbt Cloud CLI) | W | W | | W | | | | | | | | | | Environments | W | R | R | R | R | W | R | | | R | R | | | Jobs | W | R | R | W | R | W | R | | | R | R | | | Metadata | R | R | R | R | R | R | R | R | | R | R | | -| Permissions | W | | R | R | R | | | | | | W | | -| Profile | W | R | W | R | R | R | | | | R | R | | +| Permissions (Groups & Licenses) | W | | R | R | R | | | | | | W | | +| Profile (Credentials) | W | R | W | R | R | R | | | | R | R | | | Projects | W | W | W | W | W | R | R | | | R | W | | | Repositories | W | | R | R | W | | | | | R | R | | | Runs | W | R | R | W | R | W | R | | | R | R | | diff --git a/website/snippets/_new-sl-setup.md b/website/snippets/_new-sl-setup.md index a02481db33d..a93f233d09c 100644 --- a/website/snippets/_new-sl-setup.md +++ b/website/snippets/_new-sl-setup.md @@ -1,14 +1,12 @@ You can set up the dbt Semantic Layer in dbt Cloud at the environment and project level. Before you begin: -- You must have a dbt Cloud Team or Enterprise account. Suitable for both Multi-tenant and Single-tenant deployment. - - Single-tenant accounts should contact their account representative for necessary setup and enablement. - You must be part of the Owner group, and have the correct [license](/docs/cloud/manage-access/seats-and-users) and [permissions](/docs/cloud/manage-access/self-service-permissions) to configure the Semantic Layer: * Enterprise plan — Developer license with Account Admin permissions. Or Owner with a Developer license, assigned Project Creator, Database Admin, or Admin permissions. * Team plan — Owner with a Developer license. - You must have a successful run in your new environment. :::tip -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. +If you've configured the legacy Semantic Layer, it has been deprecated. 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. @@ -20,7 +18,10 @@ If you've configured the legacy Semantic Layer, it has been deprecated, and dbt
- 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. +- 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 support the dbt Semantic Layer yet. diff --git a/website/snippets/available-beta-banner.md b/website/snippets/available-beta-banner.md deleted file mode 100644 index 15d365a84b1..00000000000 --- a/website/snippets/available-beta-banner.md +++ /dev/null @@ -1,3 +0,0 @@ -:::info Beta feature -This feature is currently in beta and subject to change. If you are interested in getting access to the beta, please [contact us](mailto:support@getdbt.com). -::: diff --git a/website/snippets/available-prerelease-banner.md b/website/snippets/available-prerelease-banner.md deleted file mode 100644 index 3531a2f646f..00000000000 --- a/website/snippets/available-prerelease-banner.md +++ /dev/null @@ -1,7 +0,0 @@ -:::info Release candidate -dbt Core v1.2 is now available as a **release candidate**. - -For more information on prereleases, see ["About Core versions: Trying prereleases"](core-versions#trying-prereleases). - -Join the [#dbt-prereleases](https://getdbt.slack.com/archives/C016X6ABVUK) channel in the Community Slack so you can be the first to read about prereleases as soon as they're available! -::: diff --git a/website/snippets/quickstarts/schedule-a-job.md b/website/snippets/quickstarts/schedule-a-job.md index ab8f4350dbf..70848388f35 100644 --- a/website/snippets/quickstarts/schedule-a-job.md +++ b/website/snippets/quickstarts/schedule-a-job.md @@ -35,9 +35,9 @@ As the `jaffle_shop` business gains more customers, and those customers create m 8. Click the run and watch its progress under "Run history." 9. Once the run is complete, click **View Documentation** to see the docs for your project. -:::tip + Congratulations 🎉! You've just deployed your first dbt project! -::: + #### FAQs diff --git a/website/snippets/sl-considerations-banner.md b/website/snippets/sl-considerations-banner.md deleted file mode 100644 index 33cfb5edac5..00000000000 --- a/website/snippets/sl-considerations-banner.md +++ /dev/null @@ -1,8 +0,0 @@ -:::caution Considerations - -Some important considerations to know about using the dbt Semantic Layer during the Public Preview: - -- Support for Snowflake data platform only (_additional data platforms coming soon_) -- Support for the deployment environment only (_development experience coming soon_) - -::: diff --git a/website/snippets/test-snippet.md b/website/snippets/test-snippet.md deleted file mode 100644 index c1de326aa7a..00000000000 --- a/website/snippets/test-snippet.md +++ /dev/null @@ -1,8 +0,0 @@ ---- ---- - -### Header 2 - -Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nullam fermentum porttitor dui, id scelerisque enim scelerisque at. Proin imperdiet sem sed magna ornare, sit amet rutrum ligula vehicula. Aenean eget magna placerat, dictum velit sed, dapibus quam. Maecenas lectus tellus, dictum semper gravida vel, feugiat vitae nibh. Vestibulum nec lorem nibh. Fusce nisi felis, tincidunt ac scelerisque ut, aliquam in eros. Praesent euismod dolor ac lacinia laoreet. Phasellus orci orci, scelerisque vitae mollis id, consectetur ut libero. Aenean diam leo, tempor ut vulputate in, laoreet id ipsum. Quisque gravida et ex id eleifend. Etiam ultricies erat diam. Morbi hendrerit, ligula non aliquam tempus, erat elit suscipit quam, eu cursus quam nisi sit amet dui. Cras iaculis risus vel enim tempor molestie. - -Curabitur a porttitor odio. Curabitur sit amet tristique ante. Ut eleifend, erat eget imperdiet accumsan, quam diam sodales dolor, vulputate consequat lacus felis non sapien. Nam et nunc sed diam congue rutrum nec non massa. Nam eget fermentum sem. Nam ac imperdiet massa. Phasellus a elementum dui. diff --git a/website/snippets/tutorial-create-new-dbt-cloud-account.md b/website/snippets/tutorial-create-new-dbt-cloud-account.md deleted file mode 100644 index bdde874d0c9..00000000000 --- a/website/snippets/tutorial-create-new-dbt-cloud-account.md +++ /dev/null @@ -1,10 +0,0 @@ -Let's start this section by creating a dbt Cloud account if you haven't already. - -1. Navigate to [dbt Cloud](https://cloud.getdbt.com). -2. If you don't have a dbt Cloud account, create a new one, and verify your account via email. -3. If you already have a dbt Cloud account, you can create a new project from your existing account: - 1. Click the gear icon in the top-right, then click **Projects**. - 2. Click **+ New Project**. -4. You've arrived at the "Setup a New Project" page. -5. Type "Analytics" in the dbt Project Name field. You will be able to rename this project later. -6. Click **Continue**. \ No newline at end of file diff --git a/website/snippets/tutorial-initiate-project.md b/website/snippets/tutorial-initiate-project.md deleted file mode 100644 index 008b6bdf487..00000000000 --- a/website/snippets/tutorial-initiate-project.md +++ /dev/null @@ -1,44 +0,0 @@ -Now that you have a repository configured, you can initialize your project and start development in dbt Cloud: - -1. Click **Develop** from the upper left. It might take a few minutes for your project to spin up for the first time as it establishes your git connection, clones your repo, and tests the connection to the warehouse. -2. Above the file tree to the left, click **Initialize your project**. This builds out your folder structure with example models. -3. Make your initial commit by clicking **Commit**. Use the commit message `initial commit`. This creates the first commit to your managed repo and allows you to open a branch where you can add new dbt code. -4. Now you should be able to **directly query data from your warehouse** and **execute dbt run**. Paste your following warehouse-specific code in the IDE: - -
-
-```sql
-select * from `dbt-tutorial.jaffle_shop.customers`
-```
-
-
-
-
-
-```sql
-select * from default.jaffle_shop_customers
-```
-
-
-
-
-
-```sql
-select * from jaffle_shop.customers
-```
-
-
-
-
-
-```sql
-select * from raw.jaffle_shop.customers
-```
-
-
-
-
@@ -40,7 +57,7 @@ useEffect(() => {
onMouseLeave={handleMouseLeave}
>
- {alt_header}
+ {alt_header}
{/* Visual disclaimer */}
Hover to view
diff --git a/website/src/components/detailsToggle/styles.module.css b/website/src/components/detailsToggle/styles.module.css
index 446d3197128..b3f4a4886dc 100644
--- a/website/src/components/detailsToggle/styles.module.css
+++ b/website/src/components/detailsToggle/styles.module.css
@@ -1,9 +1,11 @@
-:local(.link) {
+:local(.link) :local(.headerText) {
color: var(--ifm-link-color);
- transition: background-color 0.3s; /* Smooth transition for background color */
+ text-decoration: none;
+ transition: text-decoration 0.3s; /* Smooth transition */
}
-:local(.link:hover), :local(.link:focus) {
+:local(.link:hover) :local(.headerText),
+:local(.link:focus) :local(.headerText) {
text-decoration: underline;
cursor: pointer;
}
@@ -12,6 +14,7 @@
font-size: 0.8em;
color: #666;
margin-left: 10px; /* Adjust as needed */
+ text-decoration: none;
}
:local(.toggle) {
@@ -24,6 +27,7 @@
width: 1.25rem;
vertical-align: middle;
transition: transform 0.3s; /* Smooth transition for toggle icon */
+
}
:local(.toggleUpsideDown) {
diff --git a/website/src/components/faqs/index.js b/website/src/components/faqs/index.js
index 52c4573d883..0741a29cd89 100644
--- a/website/src/components/faqs/index.js
+++ b/website/src/components/faqs/index.js
@@ -3,10 +3,10 @@ import styles from './styles.module.css';
import { usePluginData } from '@docusaurus/useGlobalData';
function FAQ({ path, alt_header = null }) {
-
const [isOn, setOn] = useState(false);
- const [filePath, setFilePath] = useState(path)
- const [fileContent, setFileContent] = useState({})
+ const [filePath, setFilePath] = useState(path);
+ const [fileContent, setFileContent] = useState({});
+ const [hoverTimeout, setHoverTimeout] = useState(null);
// Get all faq file paths from plugin
const { faqFiles } = usePluginData('docusaurus-build-global-data-plugin');
@@ -37,24 +37,45 @@ function FAQ({ path, alt_header = null }) {
}
}, [filePath])
- const toggleOn = function () {
- setOn(!isOn);
+ const handleMouseEnter = () => {
+ setHoverTimeout(setTimeout(() => {
+ setOn(true);
+ }, 500));
+ };
+
+ const handleMouseLeave = () => {
+ if (!isOn) {
+ clearTimeout(hoverTimeout);
+ setOn(false);
}
+};
+
+ useEffect(() => {
+ return () => {
+ if (hoverTimeout) {
+ clearTimeout(hoverTimeout);
+ }
+ };
+ }, [hoverTimeout]);
+
+ const toggleOn = () => {
+ if (hoverTimeout) {
+ clearTimeout(hoverTimeout);
+ }
+ setOn(!isOn);
+ };
return (
-
+
);
}
diff --git a/website/src/components/lightbox/styles.module.css b/website/src/components/lightbox/styles.module.css
index af0bb086cf5..1f50a2f0427 100644
--- a/website/src/components/lightbox/styles.module.css
+++ b/website/src/components/lightbox/styles.module.css
@@ -10,7 +10,7 @@
margin: 10px auto;
padding-right: 10px;
display: block;
- max-width: 400px;
+ max-width: 80%;
}
:local(.collapsed) {
@@ -24,3 +24,9 @@
.rightAlignLightbox {
margin: 10px 0 10px auto;
}
+
+:local(.hovered) {
+ filter: drop-shadow(4px 4px 6px #aaaaaae1);
+ transition: transform 0.3s ease;
+ z-index: 9999;
+}
diff --git a/website/static/img/blog/2024-01-09-defer-in-development/defer-toggle.png b/website/static/img/blog/2024-01-09-defer-in-development/defer-toggle.png
new file mode 100644
index 00000000000..7161dc68b93
Binary files /dev/null and b/website/static/img/blog/2024-01-09-defer-in-development/defer-toggle.png differ
diff --git a/website/static/img/blog/2024-01-09-defer-in-development/prod-and-dev-defer.png b/website/static/img/blog/2024-01-09-defer-in-development/prod-and-dev-defer.png
new file mode 100644
index 00000000000..7ec96a7b598
Binary files /dev/null and b/website/static/img/blog/2024-01-09-defer-in-development/prod-and-dev-defer.png differ
diff --git a/website/static/img/blog/2024-01-09-defer-in-development/prod-and-dev-full.png b/website/static/img/blog/2024-01-09-defer-in-development/prod-and-dev-full.png
new file mode 100644
index 00000000000..4381a13abed
Binary files /dev/null and b/website/static/img/blog/2024-01-09-defer-in-development/prod-and-dev-full.png differ
diff --git a/website/static/img/blog/2024-01-09-defer-in-development/prod-and-dev-mixed.png b/website/static/img/blog/2024-01-09-defer-in-development/prod-and-dev-mixed.png
new file mode 100644
index 00000000000..1020c3b65f0
Binary files /dev/null and b/website/static/img/blog/2024-01-09-defer-in-development/prod-and-dev-mixed.png differ
diff --git a/website/static/img/blog/2024-01-09-defer-in-development/prod-and-dev-model-c.png b/website/static/img/blog/2024-01-09-defer-in-development/prod-and-dev-model-c.png
new file mode 100644
index 00000000000..3f48255ac12
Binary files /dev/null and b/website/static/img/blog/2024-01-09-defer-in-development/prod-and-dev-model-c.png differ
diff --git a/website/static/img/blog/2024-01-09-defer-in-development/prod-environment-plain.png b/website/static/img/blog/2024-01-09-defer-in-development/prod-environment-plain.png
new file mode 100644
index 00000000000..5c2860411ec
Binary files /dev/null and b/website/static/img/blog/2024-01-09-defer-in-development/prod-environment-plain.png differ
diff --git a/website/static/img/blog/2024-01-09-defer-in-development/willem.png b/website/static/img/blog/2024-01-09-defer-in-development/willem.png
new file mode 100644
index 00000000000..bd38e9b0bd4
Binary files /dev/null and b/website/static/img/blog/2024-01-09-defer-in-development/willem.png differ
diff --git a/website/static/img/blog/authors/ejohnston.png b/website/static/img/blog/authors/ejohnston.png
new file mode 100644
index 00000000000..09fc4ed7ba3
Binary files /dev/null and b/website/static/img/blog/authors/ejohnston.png differ
diff --git a/website/static/img/blog/serverless-free-tier-data-stack-with-dlt-and-dbt-core/architecture_diagram.png b/website/static/img/blog/serverless-free-tier-data-stack-with-dlt-and-dbt-core/architecture_diagram.png
new file mode 100644
index 00000000000..ad10d32c2e7
Binary files /dev/null and b/website/static/img/blog/serverless-free-tier-data-stack-with-dlt-and-dbt-core/architecture_diagram.png differ
diff --git a/website/static/img/blog/serverless-free-tier-data-stack-with-dlt-and-dbt-core/map_screenshot.png b/website/static/img/blog/serverless-free-tier-data-stack-with-dlt-and-dbt-core/map_screenshot.png
new file mode 100644
index 00000000000..da8309c2510
Binary files /dev/null and b/website/static/img/blog/serverless-free-tier-data-stack-with-dlt-and-dbt-core/map_screenshot.png differ
diff --git a/website/static/img/docs/dbt-cloud/semantic-layer/conversion-metrics-fill-null.png b/website/static/img/docs/dbt-cloud/semantic-layer/conversion-metrics-fill-null.png
new file mode 100644
index 00000000000..0fd5e206ba7
Binary files /dev/null and b/website/static/img/docs/dbt-cloud/semantic-layer/conversion-metrics-fill-null.png differ
diff --git a/website/static/img/docs/deploy/example-account-settings.png b/website/static/img/docs/deploy/example-account-settings.png
new file mode 100644
index 00000000000..12b8d9bc49f
Binary files /dev/null and b/website/static/img/docs/deploy/example-account-settings.png differ
diff --git a/website/static/img/docs/deploy/example-repo-caching.png b/website/static/img/docs/deploy/example-repo-caching.png
deleted file mode 100644
index 805d845dccb..00000000000
Binary files a/website/static/img/docs/deploy/example-repo-caching.png and /dev/null differ
diff --git a/website/vercel.json b/website/vercel.json
index 35799e24061..1e4cc2fb021 100644
--- a/website/vercel.json
+++ b/website/vercel.json
@@ -2,6 +2,11 @@
"cleanUrls": true,
"trailingSlash": false,
"redirects": [
+ {
+ "source": "/reference/profiles.yml",
+ "destination": "/docs/core/connect-data-platform/profiles.yml",
+ "permanent": true
+ },
{
"source": "/docs/cloud/dbt-cloud-ide/dbt-cloud-tips",
"destination": "/docs/build/dbt-tips",
@@ -3633,8 +3638,8 @@
"permanent": true
},
{
- "source": "/docs/writing-code-in-dbt/jinja-context/as_text",
- "destination": "/reference/dbt-jinja-functions/as_text",
+ "source": "/reference/dbt-jinja-functions/as_text",
+ "destination": "/reference/dbt-jinja-functions",
"permanent": true
},
{
@@ -3847,11 +3852,6 @@
"destination": "/dbt-cloud/api",
"permanent": true
},
- {
- "source": "/reference/data-test-configs",
- "destination": "/reference/test-configs",
- "permanent": true
- },
{
"source": "/reference/declaring-properties",
"destination": "/reference/configs-and-properties",
-
-
- {alt_header || fileContent?.meta && fileContent.meta.title}
-
-
);
}
diff --git a/website/src/components/faqs/styles.module.css b/website/src/components/faqs/styles.module.css
index e19156a3a7b..c179aa85cdc 100644
--- a/website/src/components/faqs/styles.module.css
+++ b/website/src/components/faqs/styles.module.css
@@ -1,9 +1,12 @@
-:local(.link) {
+:local(.link) :local(.headerText) {
color: var(--ifm-link-color);
+ text-decoration: none;
+ transition: text-decoration 0.3s; /* Smooth transition */
}
-:local(.link:hover) {
+:local(.link:hover) :local(.headerText),
+:local(.link:focus) :local(.headerText) {
text-decoration: underline;
cursor: pointer;
}
@@ -24,6 +27,13 @@
filter: invert(1);
}
+:local(.disclaimer) {
+ font-size: 0.8em;
+ color: #666;
+ margin-left: 10px; /* Adjust as needed */
+ text-decoration: none;
+}
+
:local(.body) {
margin-left: 2em;
margin-bottom: 10px;
diff --git a/website/src/components/lightbox/index.js b/website/src/components/lightbox/index.js
index 1c748bbb04f..a846c51b150 100644
--- a/website/src/components/lightbox/index.js
+++ b/website/src/components/lightbox/index.js
@@ -1,34 +1,65 @@
-import React from 'react';
+import React, { useState, useEffect } from 'react';
import styles from './styles.module.css';
import imageCacheWrapper from '../../../functions/image-cache-wrapper';
-function Lightbox({
- src,
- collapsed = false,
- alignment = "center",
- alt = undefined,
- title = undefined,
- width = undefined,
-}) {
-
- // Set alignment class if alignment prop used
- let imageAlignment = ''
- if(alignment === "left") {
- imageAlignment = styles.leftAlignLightbox
- } else if(alignment === "right") {
- imageAlignment = styles.rightAlignLightbox
- }
+function Lightbox({ src, collapsed = false, alignment = "center", alt = undefined, title = undefined, width = undefined }) {
+ const [isHovered, setIsHovered] = useState(false);
+ const [expandImage, setExpandImage] = useState(false);
+ const [isScrolling, setIsScrolling] = useState(false);
+
+ useEffect(() => {
+ let timeoutId;
+ if (isHovered && !isScrolling) {
+ timeoutId = setTimeout(() => {
+ setExpandImage(true);
+ }, 300);
+ }
+ return () => clearTimeout(timeoutId);
+ }, [isHovered, isScrolling]);
+
+ const handleMouseEnter = () => {
+ setTimeout(() => {
+ if (!isScrolling) {
+ setIsHovered(true);
+ }
+ }, 300);
+ };
+
+ const handleMouseLeave = () => {
+ setIsHovered(false);
+ setExpandImage(false);
+ };
+
+ const handleScroll = () => {
+ setIsScrolling(true);
+ setExpandImage(false);
+
+ setTimeout(() => {
+ setIsScrolling(false);
+ }, 300); // Delay to reset scrolling state
+ };
+
+ useEffect(() => {
+ window.addEventListener('scroll', handleScroll);
+ return () => {
+ window.removeEventListener('scroll', handleScroll);
+ };
+ }, []);
return (
<>
-
@@ -37,13 +68,14 @@ function Lightbox({
alt={alt ? alt : title ? title : ''}
title={title ? title : ''}
src={imageCacheWrapper(src)}
+ style={expandImage ? { transform: 'scale(1.2)', transition: 'transform 0.5s ease', zIndex: '9999' } : {}}
/>
{title && (
{ title }
)}
-
+
- {fileContent?.contents && fileContent.contents}
+
+ {alt_header || (fileContent?.meta && fileContent.meta.title)}
+ Hover to view
+
+
+
+ {fileContent?.contents}
-