Ted,
Here is the full stack trace coming from spark-shell:
14/09/03 16:21:03 ERROR scheduler.JobScheduler: Error running job streaming
job 1409786463000 ms.0
org.apache.spark.SparkException: Job aborted due to stage failure: Task not
serializable: java.io.NotSerializableException:
org.apache.spark.streaming.StreamingContext
at org.apache.spark.scheduler.DAGScheduler.org
$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1033)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1017)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1015)
at
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at
org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1015)
at org.apache.spark.scheduler.DAGScheduler.org
$apache$spark$scheduler$DAGScheduler$$submitMissingTasks(DAGScheduler.scala:770)
at org.apache.spark.scheduler.DAGScheduler.org
$apache$spark$scheduler$DAGScheduler$$submitStage(DAGScheduler.scala:713)
at
org.apache.spark.scheduler.DAGScheduler.handleJobSubmitted(DAGScheduler.scala:697)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1176)
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
at akka.actor.ActorCell.invoke(ActorCell.scala:456)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
at akka.dispatch.Mailbox.run(Mailbox.scala:219)
at
akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at
scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at
scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
Basically, what I am doing on the terminal where I run nc -lk, I type in
words separated by commas and hit enter i.e. "bill,ted".
On Wed, Sep 3, 2014 at 2:36 PM, Ted Yu <yuzhih...@gmail.com> wrote:
> Adding back user@
>
> I am not familiar with the NotSerializableException. Can you show the
> full stack trace ?
>
> See SPARK-1297 for changes you need to make so that Spark works with
> hbase 0.98
>
> Cheers
>
>
> On Wed, Sep 3, 2014 at 2:33 PM, Kevin Peng <kpe...@gmail.com> wrote:
>
>> Ted,
>>
>> The hbase-site.xml is in the classpath (had worse issues before... until
>> I figured that it wasn't in the path).
>>
>> I get the following error in the spark-shell:
>> org.apache.spark.SparkException: Job aborted due to stage failure: Task
>> not serializable: java.io.NotSerializableException:
>> org.apache.spark.streaming.StreamingContext
>> at org.apache.spark.scheduler.DAGScheduler.org
>> $apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.sc
>> ...
>>
>> I also double checked the hbase table, just in case, and nothing new is
>> written in there.
>>
>> I am using hbase version: 0.98.1-cdh5.1.0 the default one with the
>> CDH5.1.0 distro.
>>
>> Thank you for the help.
>>
>>
>> On Wed, Sep 3, 2014 at 2:09 PM, Ted Yu <yuzhih...@gmail.com> wrote:
>>
>>> Is hbase-site.xml in the classpath ?
>>> Do you observe any exception from the code below or in region server log
>>> ?
>>>
>>> Which hbase release are you using ?
>>>
>>>
>>> On Wed, Sep 3, 2014 at 2:05 PM, kpeng1 <kpe...@gmail.com> wrote:
>>>
>>>> I have been trying to understand how spark streaming and hbase connect,
>>>> but
>>>> have not been successful. What I am trying to do is given a spark
>>>> stream,
>>>> process that stream and store the results in an hbase table. So far
>>>> this is
>>>> what I have:
>>>>
>>>> import org.apache.spark.SparkConf
>>>> import org.apache.spark.streaming.{Seconds, StreamingContext}
>>>> import org.apache.spark.streaming.StreamingContext._
>>>> import org.apache.spark.storage.StorageLevel
>>>> import org.apache.hadoop.hbase.HBaseConfiguration
>>>> import org.apache.hadoop.hbase.client.{HBaseAdmin,HTable,Put,Get}
>>>> import org.apache.hadoop.hbase.util.Bytes
>>>>
>>>> def blah(row: Array[String]) {
>>>> val hConf = new HBaseConfiguration()
>>>> val hTable = new HTable(hConf, "table")
>>>> val thePut = new Put(Bytes.toBytes(row(0)))
>>>> thePut.add(Bytes.toBytes("cf"), Bytes.toBytes(row(0)),
>>>> Bytes.toBytes(row(0)))
>>>> hTable.put(thePut)
>>>> }
>>>>
>>>> val ssc = new StreamingContext(sc, Seconds(1))
>>>> val lines = ssc.socketTextStream("localhost", 9999,
>>>> StorageLevel.MEMORY_AND_DISK_SER)
>>>> val words = lines.map(_.split(","))
>>>> val store = words.foreachRDD(rdd => rdd.foreach(blah))
>>>> ssc.start()
>>>>
>>>> I am currently running the above code in spark-shell. I am not sure
>>>> what I
>>>> am doing wrong.
>>>>
>>>>
>>>>
>>>> --
>>>> View this message in context:
>>>> http://apache-spark-user-list.1001560.n3.nabble.com/Spark-Streaming-into-HBase-tp13378.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
>>>>
>>>>
>>>
>>
>
