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Merge pull request #455 from r-dbi/docs-arrow-tweak
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docs: Fix typos in Arrow vignette
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aviator-app[bot] authored Dec 27, 2023
2 parents 0d069e3 + 5167d47 commit f2fde38
Showing 1 changed file with 7 additions and 8 deletions.
15 changes: 7 additions & 8 deletions vignettes/DBI-arrow.Rmd
Original file line number Diff line number Diff line change
Expand Up @@ -28,7 +28,7 @@ registerS3method("knit_print", "data.frame", "knit_print.data.frame")
## Who this tutorial is for

This tutorial is for you if you want to leverage [Apache Arrow](https://arrow.apache.org/) for accessing and manipulating data on databases.
See `vignette("DBI", package = "DBI")` and `vignette("DBI", package = "DBI-advanced")` for tutorials on accessing data using R's data frames instead of Arrow's structures.
See `vignette("DBI", package = "DBI")` and `vignette("DBI-advanced", package = "DBI")` for tutorials on accessing data using R's data frames instead of Arrow's structures.

## Rationale

Expand All @@ -37,14 +37,14 @@ Apache Arrow is
> a cross-language development platform for in-memory analytics,
suitable for large and huge data, with support for out-of-memory operation.
Arrow is also a data exchange format, the data types covered by Arrow are a superset of the data types supported by SQL databases.
Arrow is also a data exchange format, the data types covered by Arrow align well with the data types supported by SQL databases.

DBI 1.2.0 introduced support for Arrow as a format for exchanging data between R and databases.
The aim is to:

- accelerate data retrieval and loading, by using fewer costly data conversions
- better support reading and summarizing data from a database that is larger than memory
- provide better type fidelity with workflows centered around Arrow
- accelerate data retrieval and loading, by using fewer costly data conversions;
- better support reading and summarizing data from a database that is larger than memory;
- provide better type fidelity with workflows centered around Arrow.

This allows existing code to be used with Arrow, and it allows new code to be written that is more efficient and more flexible than code that uses R's data frames.

Expand All @@ -63,8 +63,8 @@ DBI 1.2.0 introduces new classes and generics for working with Arrow data:
- `dbBindArrow()`
- `dbFetchArrow()`
- `dbFetchArrowChunk()`
- `DBIResultArrow`
- `DBIResultArrowDefault`
- `DBIResultArrow-class`
- `DBIResultArrowDefault-class`

Compatibility is important for DBI, and implementing new generics and classes greatly reduces the risk of breaking existing code.
The DBI package comes with a fully functional fallback implementation for all existing DBI backends.
Expand Down Expand Up @@ -99,7 +99,6 @@ The `dbReadTableArrow()` method reads all rows from a table into an Arrow stream
Arrow objects implement the `as.data.frame()` method, so we can convert the stream to a data frame.

```{r}
dbReadTableArrow(con, "tbl")
stream <- dbReadTableArrow(con, "tbl")
stream
as.data.frame(stream)
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