You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2015/08/28 22:54:46 UTC
[jira] [Commented] (SPARK-10341) SMJ fail with unable to acquire
memory
[ https://issues.apache.org/jira/browse/SPARK-10341?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14720552#comment-14720552 ]
Apache Spark commented on SPARK-10341:
--------------------------------------
User 'davies' has created a pull request for this issue:
https://github.com/apache/spark/pull/8511
> SMJ fail with unable to acquire memory
> --------------------------------------
>
> Key: SPARK-10341
> URL: https://issues.apache.org/jira/browse/SPARK-10341
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.5.0
> Reporter: Davies Liu
> Assignee: Davies Liu
> Priority: Critical
>
> In SMJ, the first ExternalSorter could consume all the memory before spilling, then the second can not even acquire the first page.
> {code}
> ava.io.IOException: Unable to acquire 16777216 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$3.apply(sort.scala:169)
> at org.apache.spark.rdd.MapPartitionsWithPreparationRDD.compute(MapPartitionsWithPreparationRDD.scala:45)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
> at org.apache.spark.rdd.ZippedPartitionsRDD2.compute(ZippedPartitionsRDD.scala:88)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
> at org.apache.spark.scheduler.Task.run(Task.scala:88)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> {code}
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org