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Posted to issues@spark.apache.org by "Sean Owen (JIRA)" <ji...@apache.org> on 2019/01/21 01:30:00 UTC
[jira] [Commented] (SPARK-26228) OOM issue encountered when
computing Gramian matrix
[ https://issues.apache.org/jira/browse/SPARK-26228?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16747603#comment-16747603 ]
Sean Owen commented on SPARK-26228:
-----------------------------------
Yep this is a real problem. The issue is the 'zeroValue" to treeAggregate. It allocates a huge dense matrix of 0s, which must then be serialized several times. This includes a simple check to see if it's serializable, which serializes with JavaSerializer, and at some point that takes so much memory that more than 2GB of bytes are needed somewhere in a ByteArrayOutputStream and it fails. It won't matter how much memory the driver has.
I think the fix is easy; the zero value should just be null, and the seqOp and combOp can easily handle this situation. At least, I tried it locally and it works fine, and doesn't fail upfront at about a 16000x16000 Gramian. It ought to be faster too.
> 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
> Attachments: 1.jpeg
>
>
> {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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