Re: Error in starting Spark Streaming Context

2015-10-22 Thread Tiago Albineli Motta
e computation
>ssc.awaitTermination()
>
>}
>
>def managingContext():StreamingContext =
>   {
>//making spark context
>val conf = new
> SparkConf().setMaster("local[*]").setAppName("twitterConnector")
>val ssc = new StreamingContext(conf, Seconds(1))
>val sqlContext = new org.apache.spark.sql.SQLContext(ssc.sparkContext)
>import sqlContext.implicits._
>
>//checkpointing
>ssc.checkpoint("hdfsDirectory")
>ssc
>}
> def fetchTweets (ssc : StreamingContext , atwitter :
> Option[twitter4j.auth.Authorization]) : Unit = {
>
>
>val tweets
> =TwitterUtils.createStream(ssc,atwitter,Nil,StorageLevel.MEMORY_AND_DISK_2)
>val twt = tweets.window(Seconds(10),Seconds(10))
>   //checkpoint duration
>   /twt.checkpoint(new Duration(1000))
>
>//processing
>case class Tweet(createdAt:Long, text:String)
>twt.map(status=>
>Tweet(status.getCreatedAt().getTime()/1000, status.getText())
>)
>twt.print()
>   }
>
>
>
> --
> View this message in context:
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Re: Error in starting Spark Streaming Context

2015-10-22 Thread Tiago Albineli Motta
at twitter.streamingSpark$.main(App.scala:26)
>> at twitter.streamingSpark.main(App.scala)
>> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>> at
>>
>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
>> at
>>
>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
>> at java.lang.reflect.Method.invoke(Method.java:606)
>> at
>>
>> org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:664)
>> at
>> org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:169)
>> at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:192)
>> at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:111)
>> at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
>>
>> The relavent code is
>>
>>  def twitterConnector() :Unit =
>>  {
>>  val atwitter=managingCredentials()
>>
>>val ssc=StreamingContext.getOrCreate("hdfsDirectory",()=> {
>> managingContext() })
>>fetchTweets(ssc, atwitter )
>>
>>ssc.start() // Start the computation
>>ssc.awaitTermination()
>>
>>}
>>
>>def managingContext():StreamingContext =
>>   {
>>//making spark context
>>val conf = new
>> SparkConf().setMaster("local[*]").setAppName("twitterConnector")
>>    val ssc = new StreamingContext(conf, Seconds(1))
>>val sqlContext = new org.apache.spark.sql.SQLContext(ssc.sparkContext)
>>import sqlContext.implicits._
>>
>>//checkpointing
>>ssc.checkpoint("hdfsDirectory")
>>ssc
>>}
>> def fetchTweets (ssc : StreamingContext , atwitter :
>> Option[twitter4j.auth.Authorization]) : Unit = {
>>
>>
>>val tweets
>>
>> =TwitterUtils.createStream(ssc,atwitter,Nil,StorageLevel.MEMORY_AND_DISK_2)
>>val twt = tweets.window(Seconds(10),Seconds(10))
>>   //checkpoint duration
>>   /twt.checkpoint(new Duration(1000))
>>
>>//processing
>>case class Tweet(createdAt:Long, text:String)
>>twt.map(status=>
>>Tweet(status.getCreatedAt().getTime()/1000, status.getText())
>>)
>>twt.print()
>>   }
>>
>>
>>
>> --
>> View this message in context:
>> http://apache-spark-user-list.1001560.n3.nabble.com/Error-in-starting-Spark-Streaming-Context-tp24063.html
>> Sent from the Apache Spark User List mailing list archive at Nabble.com.
>>
>> -
>> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org
>> For additional commands, e-mail: user-h...@spark.apache.org
>>
>>
>


Error in starting Spark Streaming Context

2015-07-29 Thread Sadaf
Hi

I am new to Spark Streaming and writing a code for twitter connector. when i
run this code more than one time, it gives the following exception. I have
to create a new hdfs directory for checkpointing each time to make it run
successfully and moreover it doesn't get stopped. 

ERROR StreamingContext: Error starting the context, marking it as stopped
org.apache.spark.SparkException:
org.apache.spark.streaming.dstream.WindowedDStream@532d0784 has not been
initialized
at
org.apache.spark.streaming.dstream.DStream.isTimeValid(DStream.scala:321)
at
org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:342)
at
org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:342)
at scala.Option.orElse(Option.scala:257)
at
org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:339)
at
org.apache.spark.streaming.dstream.ForEachDStream.generateJob(ForEachDStream.scala:38)
at
org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:120)
at
org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:120)
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:120)
at
org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$restart$4.apply(JobGenerator.scala:227)
at
org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$restart$4.apply(JobGenerator.scala:222)
at
scala.collection.IndexedSeqOptimized$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:222)
at
org.apache.spark.streaming.scheduler.JobGenerator.start(JobGenerator.scala:92)
at
org.apache.spark.streaming.scheduler.JobScheduler.start(JobScheduler.scala:73)
at
org.apache.spark.streaming.StreamingContext.liftedTree1$1(StreamingContext.scala:588)
at
org.apache.spark.streaming.StreamingContext.start(StreamingContext.scala:586)
at twitter.streamingSpark$.twitterConnector(App.scala:38)
at twitter.streamingSpark$.main(App.scala:26)
at twitter.streamingSpark.main(App.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at
org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:664)
at
org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:169)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:192)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:111)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)

The relavent code is

 def twitterConnector() :Unit =
 {
 val atwitter=managingCredentials()

   val ssc=StreamingContext.getOrCreate(hdfsDirectory,()= {  
managingContext() })
   fetchTweets(ssc, atwitter )

   ssc.start() // Start the computation
   ssc.awaitTermination()

   }

   def managingContext():StreamingContext =
  {
   //making spark context
   val conf = new
SparkConf().setMaster(local[*]).setAppName(twitterConnector)
   val ssc = new StreamingContext(conf, Seconds(1))
   val sqlContext = new org.apache.spark.sql.SQLContext(ssc.sparkContext)
   import sqlContext.implicits._

   //checkpointing  
   ssc.checkpoint(hdfsDirectory)
   ssc
   }
def fetchTweets (ssc : StreamingContext , atwitter :
Option[twitter4j.auth.Authorization]) : Unit = {


   val tweets
=TwitterUtils.createStream(ssc,atwitter,Nil,StorageLevel.MEMORY_AND_DISK_2)
   val twt = tweets.window(Seconds(10),Seconds(10))
  //checkpoint duration
  /twt.checkpoint(new Duration(1000))

   //processing
   case class Tweet(createdAt:Long, text:String)
   twt.map(status=
   Tweet(status.getCreatedAt().getTime()/1000, status.getText())
   )
   twt.print()
  }



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