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https://issues.apache.org/jira/browse/SPARK-13747?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15581113#comment-15581113
]
Low Chin Wei commented on SPARK-13747:
--------------------------------------
It is running on Akka, with forkjoin dispatcher. There are 2 actors running
concurrently doing different Spark job using the same SparkSession. I can't
give the full stack, but here is the outline:
java.lang.IllegalArgumentException: spark.sql.execution.id is already set
at
org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:81)
~[spark-sql_2.11-2.0.1.jar:2.0.1]
at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2546)
~[spark-sql_2.11-2.0.1.jar:2.0.1]
at
org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2192)
~[spark-sql_2.11-2.0.1.jar:2.0.1]
at
org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Dataset.scala:2199)
~[spark-sql_2.11-2.0.1.jar:2.0.1]
at
org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2227)
~[spark-sql_2.11-2.0.1.jar:2.0.1]
at
org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2226)
~[spark-sql_2.11-2.0.1.jar:2.0.1]
at org.apache.spark.sql.Dataset.withCallback(Dataset.scala:2559)
~[spark-sql_2.11-2.0.1.jar:2.0.1]
at org.apache.spark.sql.Dataset.count(Dataset.scala:2226)
~[spark-sql_2.11-2.0.1.jar:2.0.1]
<-- Here is the code that call the df.count -->
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:526)
[akka-actor_2.11-2.4.8.jar:na]
at akka.actor.ActorCell.invoke(ActorCell.scala:495)
[akka-actor_2.11-2.4.8.jar:na]
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:257)
[akka-actor_2.11-2.4.8.jar:na]
at akka.dispatch.Mailbox.run(Mailbox.scala:224)
[akka-actor_2.11-2.4.8.jar:na]
at akka.dispatch.Mailbox.exec(Mailbox.scala:234)
[akka-actor_2.11-2.4.8.jar:na]
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
[scala-library-2.11.8.jar:na]
at
scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
[scala-library-2.11.8.jar:na]
at
scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
[scala-library-2.11.8.jar:na]
at
scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
[scala-library-2.11.8.jar:na]
> Concurrent execution in SQL doesn't work with Scala ForkJoinPool
> ----------------------------------------------------------------
>
> Key: SPARK-13747
> URL: https://issues.apache.org/jira/browse/SPARK-13747
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.0.0
> Reporter: Shixiong Zhu
> Assignee: Andrew Or
> Fix For: 2.0.0
>
>
> Run the following codes may fail
> {code}
> (1 to 100).par.foreach { _ =>
> println(sc.parallelize(1 to 5).map { i => (i, i) }.toDF("a", "b").count())
> }
> java.lang.IllegalArgumentException: spark.sql.execution.id is already set
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:87)
>
> at
> org.apache.spark.sql.DataFrame.withNewExecutionId(DataFrame.scala:1904)
> at org.apache.spark.sql.DataFrame.collect(DataFrame.scala:1385)
> {code}
> This is because SparkContext.runJob can be suspended when using a
> ForkJoinPool (e.g.,scala.concurrent.ExecutionContext.Implicits.global) as it
> calls Await.ready (introduced by https://github.com/apache/spark/pull/9264).
> So when SparkContext.runJob is suspended, ForkJoinPool will run another task
> in the same thread, however, the local properties has been polluted.
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