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From "Alexander Ulanov (JIRA)" <>
Subject [jira] [Created] (SPARK-5386) Reduce fails with vectors of big length
Date Fri, 23 Jan 2015 17:51:34 GMT
Alexander Ulanov created SPARK-5386:

             Summary: Reduce fails with vectors of big length
                 Key: SPARK-5386
             Project: Spark
          Issue Type: Bug
          Components: Spark Core
    Affects Versions: 1.2.0
         Environment: 6 machine cluster (Xeon 3.3GHz 4 cores, 16GB RAM, Ubuntu), each runs
2 Workers
./spark-shell --executor-memory 8G --driver-memory 8G

            Reporter: Alexander Ulanov
             Fix For: 1.3.0


import org.apache.spark.mllib.rdd.RDDFunctions._
import breeze.linalg._
import org.apache.log4j._
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
# 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: Connection from

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