[SPARK-6770] DirectKafkaInputDStream has not been initialized when recovery from checkpoint

• Type: Bug
• Status: Closed
• Priority: Major
• Resolution: Not A Problem
• Affects Version/s: 1.3.0
• Component/s: DStreams
• Assignee: Unassigned
• Reporter: iteblog
• Created: 08/Apr/15 09:12
• Updated: 08/May/15 09:56
• Resolved: 08/May/15 09:56

Description

I am read data from kafka using createDirectStream method and save the received log to Mysql, the code snippets as follows

    def functionToCreateContext(): StreamingContext = {
      val sparkConf = new SparkConf()
      val sc = new SparkContext(sparkConf)
      val ssc = new StreamingContext(sc, Seconds(10))
      ssc.checkpoint("/tmp/kafka/channel/offset") // set checkpoint directory
      ssc
    }

    val struct = StructType(StructField("log", StringType) ::Nil)

    // Get StreamingContext from checkpoint data or create a new one
    val ssc = StreamingContext.getOrCreate("/tmp/kafka/channel/offset", functionToCreateContext)

    val SDB = KafkaUtils.createDirectStream[String, String, StringDecoder, StringDecoder](ssc, kafkaParams, topics)
    val sqlContext = new org.apache.spark.sql.SQLContext(ssc.sparkContext)
    SDB.foreachRDD(rdd => {
      val result = rdd.map(item => {
        println(item)
        val result = item._2 match {
          case e: String => Row.apply(e)
          case _ => Row.apply("")
        }
        result
      })

      println(result.count())
      val df = sqlContext.createDataFrame(result, struct)
      df.insertIntoJDBC(url, "test", overwrite = false)
    })
    ssc.start()
    ssc.awaitTermination()
    ssc.stop()

But when I recovery the program from checkpoint, I encountered an exception:

Exception in thread "main" org.apache.spark.SparkException: org.apache.spark.streaming.kafka.DirectKafkaInputDStream@41a80e5a has not been initialized
	at org.apache.spark.streaming.dstream.DStream.isTimeValid(DStream.scala:266)
	at org.apache.spark.streaming.dstream.InputDStream.isTimeValid(InputDStream.scala:51)
	at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:287)
	at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:287)
	at scala.Option.orElse(Option.scala:257)
	at org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:284)
	at org.apache.spark.streaming.dstream.ForEachDStream.generateJob(ForEachDStream.scala:38)
	at org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:116)
	at org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:116)
	at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:251)
	at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:251)
	at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
	at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
	at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:251)
	at scala.collection.AbstractTraversable.flatMap(Traversable.scala:105)
	at org.apache.spark.streaming.DStreamGraph.generateJobs(DStreamGraph.scala:116)
	at org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$restart$4.apply(JobGenerator.scala:223)
	at org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$restart$4.apply(JobGenerator.scala:218)
	at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
	at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
	at org.apache.spark.streaming.scheduler.JobGenerator.restart(JobGenerator.scala:218)
	at org.apache.spark.streaming.scheduler.JobGenerator.start(JobGenerator.scala:89)
	at org.apache.spark.streaming.scheduler.JobScheduler.start(JobScheduler.scala:67)
	at org.apache.spark.streaming.StreamingContext.start(StreamingContext.scala:512)
	at logstatstreaming.UserChannelTodb$.main(UserChannelTodb.scala:57)
	at logstatstreaming.UserChannelTodb.main(UserChannelTodb.scala)
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
	at java.lang.reflect.Method.invoke(Method.java:597)
	at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:569)
	at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:166)
	at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:189)
	at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:110)
	at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)

Not sure if this is a bug or a feature, but it's not obvious, so wanted to create a JIRA to make sure we document this behavior.Is someone can help me to see the reasons? Thank you.