Jack Hu created SPARK-10772:
-------------------------------
Summary: 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: 1.5.0, 1.4.1
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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