ianmcook commented on a change in pull request #10001:
URL: https://github.com/apache/arrow/pull/10001#discussion_r611874806
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File path: r/NEWS.md
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@@ -21,14 +21,47 @@
## dplyr methods
-* `dplyr::mutate()` is now supported in Arrow for many applications. For
queries on `Table` and `RecordBatch` that are not yet supported in Arrow, the
implementation falls back to pulling data into an R `data.frame` first, as in
the previous release. For queries on `Dataset`, it raises an error if the
feature is not implemented.
+Many more `dplyr` verbs are supported on Arrow objects:
+
+* `dplyr::mutate()` is now supported in Arrow for many applications. For
queries on `Table` and `RecordBatch` that are not yet supported in Arrow, the
implementation falls back to pulling data into an R `data.frame` first, as in
the previous release. For queries on `Dataset`, it raises an error if the
function is not implemented. The main `mutate()` features that cannot yet be
called on Arrow objects are (1) `mutate()` after `group_by()` (which is
typically used in combination with aggregation) and (2) queries that use
`dplyr::across()`.
Review comment:
Consider adding a few words like this to rationalize the different
behaviors
```suggestion
* `dplyr::mutate()` is now supported in Arrow for many applications. For
queries on `Table` and `RecordBatch` that are not yet supported in Arrow, the
implementation falls back to pulling data into an in-memory R `data.frame`
first, as in the previous release. For queries on `Dataset` (which can be
larger than memory), it raises an error if the function is not implemented. The
main `mutate()` features that cannot yet be called on Arrow objects are (1)
`mutate()` after `group_by()` (which is typically used in combination with
aggregation) and (2) queries that use `dplyr::across()`.
```
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