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Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2022/10/18 08:10:21 UTC
[GitHub] [spark] EnricoMi opened a new pull request, #38296: [SPARK-40830][SQL] Provide groupByKey shurtcuts for groupBy.as
EnricoMi opened a new pull request, #38296:
URL: https://github.com/apache/spark/pull/38296
### What changes were proposed in this pull request?
This documents that `groupBy(...).as[...]` should be preferred over `groupByKey(...)`.
It further provides shortcuts for `groupBy(...).as[...]` that make it easier to use column-based `groupByKey`.
### Why are the changes needed?
Calling `Dataset.groupBy(...).as[K, T]` should be preferred over calling `Dataset.groupByKey(...)` whenever possible. The former allows Catalyst to exploit existing partitioning and ordering of the Dataset, while the latter hides from Catalyst which columns are used to create the keys.
_When the dataset is already partitioned and ordered by the grouping columns, `Dataset.groupByKey(...)` will repartition and order the entire dataset again._
Example:
Calling `ds.groupByKey(_.id)` hides from Catalyst that column `id` is the grouping key, while `ds.groupBy($"id").as[Int, V]` tells Catalyst that `ds` is to be grouped by (partitioned and ordered by) column `id`.
The new column-based `groupByKey` methods make it easier for users to find a way to express the grouping by expressions. Looking at the `Dataset` API, the user finds `groupByKey` with `Column`. The existing `groupBy` method returns a `RelationalGroupedDataset`, which provides the `as[K, V]` method, which allows for the same semantics, but is difficult to find.
The new column-based `groupByKey` methods further do not require the user to specify the type `V` of the original `Dataset[V]`, as `groupByKey` has access to the type / encoder:
ds.groupBy($"id").as[Int, V]
vs.
ds.groupByKey[Int]($"id")
### Does this PR introduce _any_ user-facing change?
**Note: This breaks compilation when function name is used with existing `groupByKey`:**
Was:
groupByKey(identity)
Now:
groupByKey(identity(_))
It adds these methods:
Scala:
- `Dataset.groupByKey[K](Column*)`
- `Dataset.groupByKey[K](String, String*)`
Java:
- `Dataset.groupByKey[K](Encoder[K], Column...)`
- `Dataset.groupByKey[K](Encoder[K], String, String...)`
### How was this patch tested?
Adds tests to `DatasetSuite` and `JavaDatasetSuite`.
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[GitHub] [spark] AmplabJenkins commented on pull request #38296: [SPARK-40830][SQL] Provide groupByKey shurtcuts for groupBy.as
Posted by GitBox <gi...@apache.org>.
AmplabJenkins commented on PR #38296:
URL: https://github.com/apache/spark/pull/38296#issuecomment-1282039598
Can one of the admins verify this patch?
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[GitHub] [spark] github-actions[bot] commented on pull request #38296: [SPARK-40830][SQL] Provide groupByKey shortcuts for groupBy.as
Posted by "github-actions[bot] (via GitHub)" <gi...@apache.org>.
github-actions[bot] commented on PR #38296:
URL: https://github.com/apache/spark/pull/38296#issuecomment-1613947428
We're closing this PR because it hasn't been updated in a while. This isn't a judgement on the merit of the PR in any way. It's just a way of keeping the PR queue manageable.
If you'd like to revive this PR, please reopen it and ask a committer to remove the Stale tag!
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[GitHub] [spark] github-actions[bot] closed pull request #38296: [SPARK-40830][SQL] Provide groupByKey shortcuts for groupBy.as
Posted by "github-actions[bot] (via GitHub)" <gi...@apache.org>.
github-actions[bot] closed pull request #38296: [SPARK-40830][SQL] Provide groupByKey shortcuts for groupBy.as
URL: https://github.com/apache/spark/pull/38296
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