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From "Sean Owen (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-5386) Reduce fails with vectors of big length
Date Fri, 23 Jan 2015 18:11:35 GMT

    [ https://issues.apache.org/jira/browse/SPARK-5386?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14289633#comment-14289633
] 

Sean Owen commented on SPARK-5386:
----------------------------------

You are allocating 8G for executors? or just the workers? standalone mode?

Someone who knows a little more might be able to confirm or deny, but I think you're hitting
trouble allocating such a large chunk of memory at once. It may be that there is enough heap
but not all in one place, and making a huge dense vector means allocating a huge array of
doubles. Or it could simply be a really abrupt out-of-memory condition, because in fact it's
holding several of these vectors in memory at once and running out.

> Reduce fails with vectors of big length
> ---------------------------------------
>
>                 Key: SPARK-5386
>                 URL: https://issues.apache.org/jira/browse/SPARK-5386
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>    Affects Versions: 1.2.0
>         Environment: Overall:
> 6 machine cluster (Xeon 3.3GHz 4 cores, 16GB RAM, Ubuntu), each runs 2 Workers
> Spark:
> ./spark-shell --executor-memory 8G --driver-memory 8G
> spark.driver.maxResultSize 0
> "java.io.tmpdir" and "spark.local.dir" set to a disk with a lot of free space
>            Reporter: Alexander Ulanov
>             Fix For: 1.3.0
>
>
> Code:
> import org.apache.spark.mllib.rdd.RDDFunctions._
> import breeze.linalg._
> import org.apache.log4j._
> Logger.getRootLogger.setLevel(Level.OFF)
> val n = 60000000
> val p = 12
> val vv = sc.parallelize(0 until p, p).map(i => DenseVector.rand[Double]( n ))
> vv.reduce(_ + _)
> When executing in shell it crashes after some period of time. One of the node contain
the following in stdout:
> Java HotSpot(TM) 64-Bit Server VM warning: INFO: os::commit_memory(0x0000000755500000,
2863661056, 0) failed; error='Cannot allocate memory' (errno=12)
> #
> # There is insufficient memory for the Java Runtime Environment to continue.
> # Native memory allocation (malloc) failed to allocate 2863661056 bytes for committing
reserved memory.
> # An error report file with more information is saved as:
> # /datac/spark/app-20150123091936-0000/89/hs_err_pid2247.log
> During the execution there is a message: Job aborted due to stage failure: Exception
while getting task result: java.io.IOException: Connection from server-12.net/10.10.10.10:54701
closed



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