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https://issues.apache.org/jira/browse/SPARK-26228?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16706667#comment-16706667
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shahid edited comment on SPARK-26228 at 12/3/18 5:25 AM:
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Hi [~hibayesian], could you please share the full log of the error, if you
have. Thanks
(btw 16000*16000*8 < 2^31 -1 )
was (Author: shahid):
Hi [~hibayesian], could you please share the full log of the error, if you
have. Thanks
> OOM issue encountered when computing Gramian matrix
> ----------------------------------------------------
>
> Key: SPARK-26228
> URL: https://issues.apache.org/jira/browse/SPARK-26228
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Affects Versions: 2.3.0
> Reporter: Chen Lin
> Priority: Major
>
> {quote}/**
> * Computes the Gramian matrix `A^T A`.
> *
> * @note This cannot be computed on matrices with more than 65535 columns.
> */
> {quote}
> As the above annotation of computeGramianMatrix in RowMatrix.scala said, it
> supports computing on matrices with no more than 65535 columns.
> However, we find that it will throw OOM(Request Array Size Exceeds VM Limit)
> when computing on matrices with 16000 columns.
> The root casue seems that the TreeAggregate writes a very long buffer array
> (16000*16000*8) which exceeds jvm limit(2^31 - 1).
> Does RowMatrix really supports computing on matrices with no more than 65535
> columns?
> I doubt that computeGramianMatrix has a very serious performance issue.
> Do anyone has done some performance expriments before?
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