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https://issues.apache.org/jira/browse/SPARK-16440?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15384608#comment-15384608
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Apache Spark commented on SPARK-16440:
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User 'AnthonyTruchet' has created a pull request for this issue:
https://github.com/apache/spark/pull/14268
> Undeleted broadcast variables in Word2Vec causing OoM for long runs
> --------------------------------------------------------------------
>
> Key: SPARK-16440
> URL: https://issues.apache.org/jira/browse/SPARK-16440
> Project: Spark
> Issue Type: Bug
> Components: MLlib
> Affects Versions: 1.6.0, 1.6.1, 1.6.2, 2.0.0
> Reporter: Anthony Truchet
> Assignee: Sean Owen
> Fix For: 1.6.3, 2.0.0
>
> Original Estimate: 4h
> Remaining Estimate: 4h
>
> Three broadcast variables created at the beginning of {{Word2Vec.fit()}} are
> never deleted nor unpersisted. This seems to cause excessive memory
> consumption on the driver for a job running hundreds of successive training.
> They are
> {code}
> val expTable = sc.broadcast(createExpTable())
> val bcVocab = sc.broadcast(vocab)
> val bcVocabHash = sc.broadcast(vocabHash)
> {code}
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