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https://issues.apache.org/jira/browse/SPARK-10772?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14904080#comment-14904080
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Apache Spark commented on SPARK-10772:
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User 'jhu-chang' has created a pull request for this issue:
https://github.com/apache/spark/pull/8881
> NullPointerException when transform function in DStream returns NULL
> ---------------------------------------------------------------------
>
> Key: SPARK-10772
> URL: https://issues.apache.org/jira/browse/SPARK-10772
> Project: Spark
> Issue Type: Bug
> Components: Streaming
> Affects Versions: 1.4.1, 1.5.0
> Reporter: Jack Hu
> Priority: Minor
>
> NullPointerException raises when transform function returns NULL:
> {quote}
> java.lang.NullPointerException
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$clearMetadata$3.apply(DStream.scala:442)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$clearMetadata$3.apply(DStream.scala:441)
> at
> scala.collection.mutable.HashMap$$anon$2$$anonfun$foreach$3.apply(HashMap.scala:107)
> at
> scala.collection.mutable.HashMap$$anon$2$$anonfun$foreach$3.apply(HashMap.scala:107)
> at
> scala.collection.mutable.HashTable$class.foreachEntry(HashTable.scala:226)
> at scala.collection.mutable.HashMap.foreachEntry(HashMap.scala:39)
> at scala.collection.mutable.HashMap$$anon$2.foreach(HashMap.scala:107)
> at
> org.apache.spark.streaming.dstream.DStream.clearMetadata(DStream.scala:441)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$clearMetadata$5.apply(DStream.scala:454)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$clearMetadata$5.apply(DStream.scala:454)
> at scala.collection.immutable.List.foreach(List.scala:318)
> at
> org.apache.spark.streaming.dstream.DStream.clearMetadata(DStream.scala:454)
> at
> org.apache.spark.streaming.DStreamGraph$$anonfun$clearMetadata$2.apply(DStreamGraph.scala:129)
> at
> org.apache.spark.streaming.DStreamGraph$$anonfun$clearMetadata$2.apply(DStreamGraph.scala:129)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at
> org.apache.spark.streaming.DStreamGraph.clearMetadata(DStreamGraph.scala:129)
> at
> org.apache.spark.streaming.scheduler.JobGenerator.clearMetadata(JobGenerator.scala:257)
> at
> org.apache.spark.streaming.scheduler.JobGenerator.org$apache$spark$streaming$scheduler$JobGenerator$$processEvent(JobGenerator.scala:178)
> at
> org.apache.spark.streaming.scheduler.JobGenerator$$anon$1.onReceive(JobGenerator.scala:83)
> at
> org.apache.spark.streaming.scheduler.JobGenerator$$anon$1.onReceive(JobGenerator.scala:82)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
> {quote}
> The code is very simple:
> {code}
> val sc = new SparkContext(conf)
> val sqlContext = new HiveContext(sc)
> import sqlContext.implicits._
> println(">>> create streamingContext.")
> val ssc = new StreamingContext(sc, Seconds(1))
> ssc.queueStream(
> Queue(
> sc.makeRDD(Seq(1)),
> sc.makeRDD(Seq[Int]()),
> sc.makeRDD(Seq(2))
> ), true).transform(rdd => if (rdd.isEmpty()) rdd else
> null).print
> ssc.start()
> {code}
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