[ https://issues.apache.org/jira/browse/SPARK-20080?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Sean Owen resolved SPARK-20080. ------------------------------- Resolution: Fixed [~hryhoriev.nick] I can't understand what you're reporting here, and so it's not nearly suitable as a JIRA. Please read http://spark.apache.org/contributing.html This is not a place for technical support, but for describing clear issues or improvements along with a specific change if possible. If you significantly improve the the description here, I will reopen it. Do not reopen this issue on your own. > Spak streaming application do not throw serialisation exception in foreachRDD > ----------------------------------------------------------------------------- > > Key: SPARK-20080 > URL: https://issues.apache.org/jira/browse/SPARK-20080 > Project: Spark > Issue Type: Bug > Components: DStreams > Affects Versions: 2.1.0 > Environment: local spark and yarn from big top 1.1.0 version > Reporter: Nick Hryhoriev > Priority: Minor > > When i try use or init org.slf4j.Logger inside foreachPartition, that > extracted to trait method. > What was called in foreachRDD. > I have found that foreachPartition method do not execute and no exception > appeared. > Tested on local and yarn mode spark. > code can be found on > [github|https://github.com/GrigorievNick/Spark2_1TraitLoggerSerialisationBug/tree/9da55393850df9fe19f5ff3e63b47ec2d1f67e17]. > There are two main class that explain problem. > if i will run same code with batch job. I will get right exception. > {code:java} > Exception in thread "main" org.apache.spark.SparkException: Task not > serializable > at > org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:298) > at > org.apache.spark.util.ClosureCleaner$.org$apache$spark$util$ClosureCleaner$$clean(ClosureCleaner.scala:288) > at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:108) > at org.apache.spark.SparkContext.clean(SparkContext.scala:2094) > at > org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:924) > at > org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:923) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) > at org.apache.spark.rdd.RDD.withScope(RDD.scala:362) > at org.apache.spark.rdd.RDD.foreachPartition(RDD.scala:923) > at TraitWithMethod$class.executeForEachpartitoin(TraitWithMethod.scala:12) > at ReproduceBugMain$.executeForEachpartitoin(ReproduceBugMain.scala:7) > at ReproduceBugMain$.main(ReproduceBugMain.scala:14) > at ReproduceBugMain.main(ReproduceBugMain.scala) > at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) > at > sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) > at > sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) > at java.lang.reflect.Method.invoke(Method.java:498) > at com.intellij.rt.execution.application.AppMain.main(AppMain.java:147) > Caused by: java.io.NotSerializableException: ReproduceBugMain$ > Serialization stack: > - object not serializable (class: ReproduceBugMain$, value: > ReproduceBugMain$@3935e9a8) > - field (class: TraitWithMethod$$anonfun$executeForEachpartitoin$1, name: > $outer, type: interface TraitWithMethod) > - object (class TraitWithMethod$$anonfun$executeForEachpartitoin$1, > <function1>) > at > org.apache.spark.serializer.SerializationDebugger$.improveException(SerializationDebugger.scala:40) > at > org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:46) > at > org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:100) > at > org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:295) > ... 18 more > {code} > On Github can be found 2 commit. 1 initial i add link on it(this one contain > sptreaming example). and Last one with batch job example -- This message was sent by Atlassian JIRA (v6.3.15#6346) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org