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https://issues.apache.org/jira/browse/SPARK-40830?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Enrico Minack updated SPARK-40830:
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Description:
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.
Example:
Calling {{ds.groupByKey(_.id)}} hides from Catalyst that column id is the
grouping key.
With {{ds.groupBy($"id").as[Int, V]}} tells Catalyst that {{ds}} is to be
grouped by (partitioned and ordered by) column "id".
This fact should be documented. Further, {{groupByKey}} methods with {{Column}}
and {{String}} arguments would help to short cut {{groupByKey.as}} and avoid
the {{groupBy(func)}} methods.
was:
Calling {{Dataset.groupBy(...).as[K, T]}} should be preferred over calling
{{Dataset.groupByKey(...)}} whenever possible. The former allows Catalyst to
exploit existing partitioning and ordering of the Dataset, while the latter
hides the columns used to create the keys from Catalyst.
Example:
Calling {{ds.groupByKey(_.id)}} hides from Catalyst that column id is the
grouping key.
With {{ds.groupBy($"id").as[Int, V]}} tells Catalyst that {{ds}} is to be
grouped by (partitioned and ordered by) column "id".
This fact should be documented. Further, {{groupByKey}} methods with {{Column}}
and {{String}} arguments would help to short cut {{groupByKey.as}} and avoid
the {{groupBy(func)}} methods.
> Dataset.groupBy.as should be preferred over Dataset.groupByKey
> --------------------------------------------------------------
>
> Key: SPARK-40830
> URL: https://issues.apache.org/jira/browse/SPARK-40830
> Project: Spark
> Issue Type: Improvement
> Components: Documentation, SQL
> Affects Versions: 3.4.0
> Reporter: Enrico Minack
> Priority: Minor
>
> 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.
> Example:
> Calling {{ds.groupByKey(_.id)}} hides from Catalyst that column id is the
> grouping key.
> With {{ds.groupBy($"id").as[Int, V]}} tells Catalyst that {{ds}} is to be
> grouped by (partitioned and ordered by) column "id".
> This fact should be documented. Further, {{groupByKey}} methods with
> {{Column}} and {{String}} arguments would help to short cut {{groupByKey.as}}
> and avoid the {{groupBy(func)}} methods.
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