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Test Results 566 files ± 0 566 suites ±0 1h 29m 12s ⏱️ +11s Results for commit 411afe8. ± Comparison against base commit 8314de4. This pull request removes 28 and adds 30 tests. Note that renamed tests count towards both.♻️ This comment has been updated with latest results. |
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This provides shortcuts for
groupBy(...).as[...]that make it easier to use column-basedgroupByKey.Calling
Dataset.groupBy(...).as[K, T]should be preferred over callingDataset.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 columnidis the grouping key, whileds.groupBy($"id").as[Int, V]tells Catalyst thatdsis to be grouped by (partitioned and ordered by) columnid.The new column-based
groupByKeymethods make it easier for users to find a way to express the grouping by expressions. Looking at theDatasetAPI, the user findsgroupByKeywithColumn. The existinggroupBymethod returns aRelationalGroupedDataset, which provides theas[K, V]method, which allows for the same semantics, but is difficult to find.The new column-based
groupByKeymethods further do not require the user to specify the typeVof the originalDataset[V], asgroupByKeyhas access to the type / encoder:vs.