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Posted to issues@spark.apache.org by "Sean Owen (JIRA)" <ji...@apache.org> on 2017/11/19 12:27:00 UTC
[jira] [Resolved] (SPARK-19476) Running threads in Spark DataFrame
foreachPartition() causes NullPointerException
[ https://issues.apache.org/jira/browse/SPARK-19476?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Sean Owen resolved SPARK-19476.
-------------------------------
Resolution: Not A Problem
> Running threads in Spark DataFrame foreachPartition() causes NullPointerException
> ---------------------------------------------------------------------------------
>
> Key: SPARK-19476
> URL: https://issues.apache.org/jira/browse/SPARK-19476
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 1.6.0, 1.6.1, 1.6.2, 1.6.3, 2.0.0, 2.0.1, 2.0.2, 2.1.0
> Reporter: Gal Topper
> Priority: Minor
>
> First reported on [Stack overflow|http://stackoverflow.com/questions/41674069/running-threads-in-spark-dataframe-foreachpartition].
> I use multiple threads inside foreachPartition(), which works great for me except for when the underlying iterator is TungstenAggregationIterator. Here is a minimal code snippet to reproduce:
> {code:title=Reproduce.scala|borderStyle=solid}
> import scala.concurrent.ExecutionContext.Implicits.global
> import scala.concurrent.duration.Duration
> import scala.concurrent.{Await, Future}
> import org.apache.spark.SparkContext
> import org.apache.spark.sql.SQLContext
> object Reproduce extends App {
> val sc = new SparkContext("local", "reproduce")
> val sqlContext = new SQLContext(sc)
> import sqlContext.implicits._
> val df = sc.parallelize(Seq(1)).toDF("number").groupBy("number").count()
> df.foreachPartition { iterator =>
> val f = Future(iterator.toVector)
> Await.result(f, Duration.Inf)
> }
> }
> {code}
> When I run this, I get:
> {noformat}
> java.lang.NullPointerException
> at org.apache.spark.sql.execution.aggregate.TungstenAggregationIterator.next(TungstenAggregationIterator.scala:751)
> at org.apache.spark.sql.execution.aggregate.TungstenAggregationIterator.next(TungstenAggregationIterator.scala:84)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
> at scala.collection.Iterator$class.foreach(Iterator.scala:893)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
> {noformat}
> I believe I actually understand why this happens - TungstenAggregationIterator uses a ThreadLocal variable that returns null when called from a thread other than the original thread that got the iterator from Spark. From examining the code, this does not appear to differ between recent Spark versions.
> However, this limitation is specific to TungstenAggregationIterator, and not documented, as far as I'm aware.
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