[jira] [Commented] (SPARK-10309) Some tasks failed with Unable to acquire memory

["Naden Franciscus (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-10309?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14940494#comment-14940494 ] 

Naden Franciscus commented on SPARK-10309:
------------------------------------------

Has been difficult to get a clean stacktrace/explain trace because we are executing lots of SQL commands in parallel and we don't know which one is failing. We are absolutely doing lots of joins/aggregation/sorts. 

I have tried increase shuffle.memoryFraction to 0.8 but that didn't help.

This is still an issue with the latest Spark 1.5.2 branch.



> Some tasks failed with Unable to acquire memory
> -----------------------------------------------
>
>                 Key: SPARK-10309
>                 URL: https://issues.apache.org/jira/browse/SPARK-10309
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 1.5.0
>            Reporter: Davies Liu
>
> While running Q53 of TPCDS (scale = 1500) on 24 nodes cluster (12G memory on executor):
> {code}
> java.io.IOException: Unable to acquire 33554432 bytes of memory
>         at org.apache.spark.util.collection.unsafe.sort.UnsafeExternalSorter.acquireNewPage(UnsafeExternalSorter.java:368)
>         at org.apache.spark.util.collection.unsafe.sort.UnsafeExternalSorter.<init>(UnsafeExternalSorter.java:138)
>         at org.apache.spark.util.collection.unsafe.sort.UnsafeExternalSorter.create(UnsafeExternalSorter.java:106)
>         at org.apache.spark.sql.execution.UnsafeExternalRowSorter.<init>(UnsafeExternalRowSorter.java:68)
>         at org.apache.spark.sql.execution.TungstenSort.org$apache$spark$sql$execution$TungstenSort$$preparePartition$1(sort.scala:146)
>         at org.apache.spark.sql.execution.TungstenSort$$anonfun$doExecute$3.apply(sort.scala:169)
>         at org.apache.spark.sql.execution.TungstenSort$$anonfun$doExecute$3.apply(sort.scala:169)
>         at org.apache.spark.rdd.MapPartitionsWithPreparationRDD.compute(MapPartitionsWithPreparationRDD.scala:45)
>         at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
>         at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
>         at org.apache.spark.rdd.ZippedPartitionsRDD2.compute(ZippedPartitionsRDD.scala:88)
>         at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
>         at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
>         at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>         at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
>         at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
>         at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>         at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
>         at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
>         at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
>         at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
>         at org.apache.spark.scheduler.Task.run(Task.scala:88)
>         at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
>         at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>         at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>         at java.lang.Thread.run(Thread.java:745)
> {code}
> The task could finished after retry.



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