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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2016/04/06 22:58:25 UTC
[jira] [Commented] (SPARK-14408) Update RDD.treeAggregate not to
use reduce
[ https://issues.apache.org/jira/browse/SPARK-14408?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15229090#comment-15229090 ]
Apache Spark commented on SPARK-14408:
--------------------------------------
User 'jkbradley' has created a pull request for this issue:
https://github.com/apache/spark/pull/12217
> Update RDD.treeAggregate not to use reduce
> ------------------------------------------
>
> Key: SPARK-14408
> URL: https://issues.apache.org/jira/browse/SPARK-14408
> Project: Spark
> Issue Type: Question
> Components: Spark Core
> Reporter: Joseph K. Bradley
> Assignee: Joseph K. Bradley
>
> **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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