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Posted to issues@spark.apache.org by "Apache Spark (Jira)" <ji...@apache.org> on 2020/08/31 07:15:00 UTC
[jira] [Commented] (SPARK-32753) Deduplicating and repartitioning
the same column create duplicate rows with AQE
[ https://issues.apache.org/jira/browse/SPARK-32753?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17187506#comment-17187506 ]
Apache Spark commented on SPARK-32753:
--------------------------------------
User 'manuzhang' has created a pull request for this issue:
https://github.com/apache/spark/pull/29593
> Deduplicating and repartitioning the same column create duplicate rows with AQE
> -------------------------------------------------------------------------------
>
> Key: SPARK-32753
> URL: https://issues.apache.org/jira/browse/SPARK-32753
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.0.0
> Reporter: Manu Zhang
> Priority: Minor
>
> To reproduce:
> {code:java}
> spark.range(10).union(spark.range(10)).createOrReplaceTempView("v1")
> val df = spark.sql("select id from v1 group by id distribute by id")
> println(df.collect().toArray.mkString(","))
> println(df.queryExecution.executedPlan)
> // With AQE
> [4],[0],[3],[2],[1],[7],[6],[8],[5],[9],[4],[0],[3],[2],[1],[7],[6],[8],[5],[9]
> AdaptiveSparkPlan(isFinalPlan=true)
> +- CustomShuffleReader local
> +- ShuffleQueryStage 0
> +- Exchange hashpartitioning(id#183L, 10), true
> +- *(3) HashAggregate(keys=[id#183L], functions=[], output=[id#183L])
> +- Union
> :- *(1) Range (0, 10, step=1, splits=2)
> +- *(2) Range (0, 10, step=1, splits=2)
> // Without AQE
> [4],[7],[0],[6],[8],[3],[2],[5],[1],[9]
> *(4) HashAggregate(keys=[id#206L], functions=[], output=[id#206L])
> +- Exchange hashpartitioning(id#206L, 10), true
> +- *(3) HashAggregate(keys=[id#206L], functions=[], output=[id#206L])
> +- Union
> :- *(1) Range (0, 10, step=1, splits=2)
> +- *(2) Range (0, 10, step=1, splits=2){code}
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