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https://issues.apache.org/jira/browse/SPARK-14408?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16036516#comment-16036516
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Apache Spark commented on SPARK-14408:
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User 'HyukjinKwon' has created a pull request for this issue:
https://github.com/apache/spark/pull/18198
> Update RDD.treeAggregate not to use reduce
> ------------------------------------------
>
> Key: SPARK-14408
> URL: https://issues.apache.org/jira/browse/SPARK-14408
> Project: Spark
> Issue Type: Bug
> Components: ML, MLlib, Spark Core
> Reporter: Joseph K. Bradley
> Assignee: Joseph K. Bradley
> Priority: Minor
>
> **Issue**
> In MLlib, we have assumed that {{RDD.treeAggregate}} allows the {{seqOp}} and
> {{combOp}} functions to modify and return their first argument, just like
> {{RDD.aggregate}}. However, it is not documented that way.
> I started to add docs to this effect, but then noticed that {{treeAggregate}}
> uses {{reduceByKey}} and {{reduce}} in its implementation, neither of which
> technically allows the seq/combOps to modify and return their first arguments.
> **Question**: Is the implementation safe, or does it need to be updated?
> **Decision**: Avoid using reduce. Use fold instead.
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