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https://issues.apache.org/jira/browse/SPARK-34464?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Pablo Langa Blanco resolved SPARK-34464.
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Resolution: Not A Bug
> `first` function is sorting the dataset while sometimes it is used to get
> "any value"
> -------------------------------------------------------------------------------------
>
> Key: SPARK-34464
> URL: https://issues.apache.org/jira/browse/SPARK-34464
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.0.0
> Reporter: Louis Fruleux
> Priority: Minor
>
> When one wants to groupBy and take any value (not necessarily the first), one
> usually uses
> [first|https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/functions.scala#L485]
> aggregation function.
> Unfortunately, this method uses a `SortAggregate` for some data types, which
> is not always necessary and might impact performances. Is this the desired
> behavior?
>
>
> {code:java}
> Current behavior:
> val df = Seq((0, "value")).toDF("key", "value")
> df.groupBy("key").agg(first("value")).explain()
> /*
> == Physical Plan ==
> SortAggregate(key=key#342, functions=first(value#343, false))
> +- *(2) Sort key#342 ASC NULLS FIRST, false, 0
> +- Exchange hashpartitioning(key#342, 200)
> +- SortAggregate(key=key#342, functions=partial_first(value#343,
> false))
> +- *(1) Sort key#342 ASC NULLS FIRST, false, 0
> +- LocalTableScan key#342, value#343
> */
> {code}
>
> My understanding of the source code does not allow me to fully understand why
> this is the current behavior.
> The solution might be to implement a new aggregate function. But the code
> would be highly similar to the first one. And if I don't fully understand why
> this
> [createAggregate|https://github.com/apache/spark/blob/3a299aa6480ac22501512cd0310d31a441d7dfdc/sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/AggUtils.scala#L45]
> method falls back to SortAggregate.
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