[ https://issues.apache.org/jira/browse/SPARK-22276?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16205400#comment-16205400 ]
Liang-Chi Hsieh commented on SPARK-22276: ----------------------------------------- Can you provide an simple example to reproduce this issue? Then it is easier to verify the problem. > Unnecessary repartitioning > -------------------------- > > Key: SPARK-22276 > URL: https://issues.apache.org/jira/browse/SPARK-22276 > Project: Spark > Issue Type: Bug > Components: Optimizer > Affects Versions: 2.2.0 > Reporter: Fernando Pereira > > When a dataframe is sorted it is partitioned with a RangePartitioner. > If later we aggregate by the exact same fields over which sort was applied > there is a new (apparently useless) Exchange repartitioning by a > HashPartitioner. > In my use case the groupBy exchange is still very costly as the aggregate > function won't reduce the data volume. > Is there any reason why groupBy always shuffles data, or could this be > improved? > Is there currently a way to workaround for the moment, without going to > mapPartitions? -- This message was sent by Atlassian JIRA (v6.4.14#64029) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org