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Posted to issues@spark.apache.org by "Gaurav Agrawal (JIRA)" <ji...@apache.org> on 2015/06/24 18:10:05 UTC
[jira] [Commented] (SPARK-8595) CLONE - Spark Sql throwing
exception on large partitioned data
[ https://issues.apache.org/jira/browse/SPARK-8595?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14599635#comment-14599635 ]
Gaurav Agrawal commented on SPARK-8595:
---------------------------------------
I have only 24 partitions and getting same error.
5/06/24 15:55:44 ERROR scheduler.LiveListenerBus: Listener EventLoggingListener threw an exception
java.lang.reflect.InvocationTargetException
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at org.apache.spark.scheduler.EventLoggingListener$$anonfun$logEvent$3.apply(EventLoggingListener.scala:144)
at org.apache.spark.scheduler.EventLoggingListener$$anonfun$logEvent$3.apply(EventLoggingListener.scala:144)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.EventLoggingListener.logEvent(EventLoggingListener.scala:144)
at org.apache.spark.scheduler.EventLoggingListener.onApplicationEnd(EventLoggingListener.scala:179)
at org.apache.spark.scheduler.SparkListenerBus$class.onPostEvent(SparkListenerBus.scala:54)
at org.apache.spark.scheduler.LiveListenerBus.onPostEvent(LiveListenerBus.scala:31)
at org.apache.spark.scheduler.LiveListenerBus.onPostEvent(LiveListenerBus.scala:31)
at org.apache.spark.util.ListenerBus$class.postToAll(ListenerBus.scala:53)
at org.apache.spark.util.AsynchronousListenerBus.postToAll(AsynchronousListenerBus.scala:36)
at org.apache.spark.util.AsynchronousListenerBus$$anon$1$$anonfun$run$1.apply$mcV$sp(AsynchronousListenerBus.scala:76)
at org.apache.spark.util.AsynchronousListenerBus$$anon$1$$anonfun$run$1.apply(AsynchronousListenerBus.scala:61)
at org.apache.spark.util.AsynchronousListenerBus$$anon$1$$anonfun$run$1.apply(AsynchronousListenerBus.scala:61)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1618)
at org.apache.spark.util.AsynchronousListenerBus$$anon$1.run(AsynchronousListenerBus.scala:60)
Caused by: java.io.IOException: Filesystem closed
at org.apache.hadoop.hdfs.DFSClient.checkOpen(DFSClient.java:710)
at org.apache.hadoop.hdfs.DFSOutputStream.flushOrSync(DFSOutputStream.java:1857)
at org.apache.hadoop.hdfs.DFSOutputStream.hflush(DFSOutputStream.java:1818)
at org.apache.hadoop.fs.FSDataOutputStream.hflush(FSDataOutputStream.java:138)
... 19 more
15/06/24 15:55:44 INFO handler.ContextHandler: stopped o.s.j.s.ServletContextHandler{/metrics/json,
> CLONE - Spark Sql throwing exception on large partitioned data
> --------------------------------------------------------------
>
> Key: SPARK-8595
> URL: https://issues.apache.org/jira/browse/SPARK-8595
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Reporter: Gaurav Agrawal
> Fix For: 1.2.1
>
>
> Spark connects with Hive Metastore. I am able to run simple queries like show table and select. but throws below exception while running query on the hive Table having large number of partitions.
> {noformat}
> Exception in thread "main" java.lang.reflect.InvocationTargetException
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
> at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:606)
> at org.apache.spark.deploy.worker.DriverWrapper$.main(DriverWrapper.scala:40)
> at`enter code here` org.apache.spark.deploy.worker.DriverWrapper.main(DriverWrapper.scala)
> Caused by: org.apache.hadoop.hive.ql.metadata.HiveException: org.apache.thrift.transport.TTransportException: java.net.SocketTimeoutException: Read timed out
> at org.apache.hadoop.hive.ql.metadata.Hive.getAllPartitionsOf(Hive.java:1785)
> at org.apache.spark.sql.hive.HiveShim$.getAllPartitionsOf(Shim13.scala:316)
> at org.apache.spark.sql.hive.HiveMetastoreCatalog.lookupRelation(HiveMetastoreCatalog.scala:86)
> at org.apache.spark.sql.hive.HiveContext$$anon$1.org$apache$spark$sql$catalyst$analysis$OverrideCatalog$$super$lookupRelation(HiveContext.scala:253)
> at org.apache.spark.sql.catalyst.analysis.OverrideCatalog$$anonfun$lookupRelation$3.apply(Catalog.scala:137)
> at org.apache.spark.sql.catalyst.analysis.OverrideCatalog$$anonfun$lookupRelation$3.apply(Catalog.scala:137)
> at scala.Option.getOrElse(Option.scala:120)
> at org.apache.spark.sql.catalyst.analysis.OverrideCatalog$class.lookupRelation(Catalog.scala:137)
> at org.apache.spark.sql.hive.HiveContext$$anon$1.lookupRelation(HiveContext.scala:253)
> at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$$anonfun$apply$5.applyOrElse(Analyzer.scala:143)
> at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$$anonfun$apply$5.applyOrElse(Analyzer.scala:138)
> at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:144)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:162)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
> at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
> {noformat}
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