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https://issues.apache.org/jira/browse/SPARK-30563?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17051073#comment-17051073
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Maxim Gekk commented on SPARK-30563:
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> we spend a lot of time in this loop even
The loop just forces materialization of joined rows. By df.groupBy().count(),
you skip some steps in join, it seems. I think in most cases, users need
results of join but not just count on top of it.
> Regressions in Join benchmarks
> ------------------------------
>
> Key: SPARK-30563
> URL: https://issues.apache.org/jira/browse/SPARK-30563
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.0.0
> Reporter: Maxim Gekk
> Priority: Minor
>
> Regenerated benchmark results in the
> https://github.com/apache/spark/pull/27078 shows many regressions in
> JoinBenchmark. The benchmarked queries slowed down by up to 3 times, see
> old results:
> https://github.com/apache/spark/pull/27078/files#diff-d5cbaab2b49ee9fddfa0e229de8f607dL10
> new results:
> https://github.com/apache/spark/pull/27078/files#diff-d5cbaab2b49ee9fddfa0e229de8f607dR10
> One of the difference in queries is using the `NoOp` datasource in new
> queries.
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