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Posted to issues@spark.apache.org by "yangping wu (JIRA)" <ji...@apache.org> on 2015/04/08 11:13:12 UTC
[jira] [Created] (SPARK-6770) DirectKafkaInputDStream has not been
initialized when recovery from checkpoint
yangping wu created SPARK-6770:
----------------------------------
Summary: DirectKafkaInputDStream has not been initialized when recovery from checkpoint
Key: SPARK-6770
URL: https://issues.apache.org/jira/browse/SPARK-6770
Project: Spark
Issue Type: Bug
Components: Streaming
Affects Versions: 1.3.0
Reporter: yangping wu
I am read the data from kafka using createDirectStream method and save the received log to Mysql, the code snippets as follows
{code}
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()
{/code}
But when I recovery the program from checkpoint, I encountered an exception:
{code}
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)
{code}
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.
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