[ https://issues.apache.org/jira/browse/SPARK-10341?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Davies Liu updated SPARK-10341: ------------------------------- Target Version/s: 1.5.0 (was: 1.5.1) > 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-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org