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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-22084) Performance regression in aggregation strategy
Date Thu, 21 Sep 2017 06:03:00 GMT

    [ https://issues.apache.org/jira/browse/SPARK-22084?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16174314#comment-16174314
] 

Apache Spark commented on SPARK-22084:
--------------------------------------

User 'stanzhai' has created a pull request for this issue:
https://github.com/apache/spark/pull/19301

> Performance regression in aggregation strategy
> ----------------------------------------------
>
>                 Key: SPARK-22084
>                 URL: https://issues.apache.org/jira/browse/SPARK-22084
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 2.0.0, 2.0.1, 2.0.2, 2.1.0, 2.1.1, 2.2.0
>            Reporter: StanZhai
>              Labels: performance
>
> {code:sql}
> SELECT a, SUM(b) AS b0, SUM(b) AS b1 
> FROM VALUES(1, 1), (2, 2) AS (a, b) 
> GROUP BY a
> {code}
> Two exactly the same SUM(b) expressions in the SQL, and the following is the physical
plan in Spark 2.x.
> {code}
> == Physical Plan ==
> *HashAggregate(keys=[a#11], functions=[sum(cast(b#12 as bigint)), sum(cast(b#12 as bigint))])
> +- Exchange hashpartitioning(a#11, 200)
>    +- *HashAggregate(keys=[a#11], functions=[partial_sum(cast(b#12 as bigint)), partial_sum(cast(b#12
as bigint))])
>       +- LocalTableScan [a#11, b#12]
> {code}
> functions in Aggregate should be: functions=[partial_sum(cast(b#12 as bigint))]



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