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https://issues.apache.org/jira/browse/SPARK-32724?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Hyukjin Kwon resolved SPARK-32724.
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Resolution: Invalid
> java.io.IOException: Stream is corrupted when tried to inner join 4 huge
> tables. Currently using pyspark version 2.4.0-cdh6.3.1
> ---------------------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-32724
> URL: https://issues.apache.org/jira/browse/SPARK-32724
> Project: Spark
> Issue Type: Question
> Components: PySpark, Spark Core
> Affects Versions: 2.4.0
> Reporter: Kannan
> Priority: Major
>
> When i try to join the 4 tables with 1M data i am getting below error.
> Py4JJavaError: An error occurred while calling o453.count. :
> org.apache.spark.SparkException: Job aborted due to stage failure: Aborting
> TaskSet 27.0 because task 9 (partition 9) cannot run anywhere due to node and
> executor blacklist. Most recent failure: Lost task 9.1 in stage 27.0 (TID
> 267, si-159l.de.des.com, executor 17): java.io.IOException: Stream is
> corrupted at
> net.jpountz.lz4.LZ4BlockInputStream.refill(LZ4BlockInputStream.java:202) at
> net.jpountz.lz4.LZ4BlockInputStream.refill(LZ4BlockInputStream.java:228) at
> net.jpountz.lz4.LZ4BlockInputStream.read(LZ4BlockInputStream.java:157) at
> org.apache.spark.io.ReadAheadInputStream$1.run(ReadAheadInputStream.java:168)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
> at java.lang.Thread.run(Thread.java:748) Blacklisting behavior can be
> configured via spark.blacklist.*. at
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1890)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1878)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1877)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) at
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1877)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:929)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:929)
> at scala.Option.foreach(Option.scala:257) at
> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:929)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2111)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2060)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2049)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49) at
> org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:740) at
> org.apache.spark.SparkContext.runJob(SparkContext.scala:2081) at
> org.apache.spark.SparkContext.runJob(SparkContext.scala:2102) at
> org.apache.spark.SparkContext.runJob(SparkContext.scala:2121) at
> org.apache.spark.SparkContext.runJob(SparkContext.scala:2146) at
> org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:945) at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
> at org.apache.spark.rdd.RDD.withScope(RDD.scala:363) at
> org.apache.spark.rdd.RDD.collect(RDD.scala:944) at
> org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:299)
> at org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2830) at
> org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2829) at
> org.apache.spark.sql.Dataset$$anonfun$53.apply(Dataset.scala:3364) at
> org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78)
> at
> org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
> at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3363) at
> org.apache.spark.sql.Dataset.count(Dataset.scala:2829) 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
> py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) at
> py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) at
> py4j.Gateway.invoke(Gateway.java:282) at
> py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) at
> py4j.commands.CallCommand.execute(CallCommand.java:79) at
> py4j.GatewayConnection.run(GatewayConnection.java:238) at
> java.lang.Thread.run(Thread.java:748)
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