If you can share the complete code and a sample file, may be i can try to
reproduce it on my end.
Thanks
Best Regards
On Wed, May 20, 2015 at 7:00 AM, Tapan Sharma <tapan.sha...@gmail.com>
wrote:
> Problem is still there.
> Exception is not coming at the time of reading.
> Also the count of JavaPairRDD is as expected. It is when we are calling
> collect() or toArray() methods, the exception is coming.
> Something to do with Text class even though I haven't used it in the
> program.
>
> Regards
> Tapan
>
> On Tue, May 19, 2015 at 6:26 PM, Akhil Das <ak...@sigmoidanalytics.com>
> wrote:
>
>> Try something like:
>>
>> JavaPairRDD<IntWritable, Text> output = sc.newAPIHadoopFile(inputDir,
>>
>> org.apache.hadoop.mapreduce.lib.input.SequenceFileInputFormat.class,
>> IntWritable.class,
>> Text.class, new Job().getConfiguration());
>>
>> With the type of input format that you require.
>>
>> Thanks
>> Best Regards
>>
>> On Tue, May 19, 2015 at 3:57 PM, Tapan Sharma <tapan.sha...@gmail.com>
>> wrote:
>>
>>> Hi Team,
>>>
>>> I am new to Spark and learning.
>>> I am trying to read image files into spark job. This is how I am doing:
>>> Step 1. Created sequence files with FileName as Key and Binary image as
>>> value. i.e. Text and BytesWritable.
>>> I am able to read these sequence files into Map Reduce programs.
>>>
>>> Step 2.
>>> I understand that Text and BytesWritable are Non Serializable therefore,
>>> I
>>> read the sequence file in Spark as following:
>>>
>>> SparkConf sparkConf = new SparkConf().setAppName("JavaSequenceFile");
>>> JavaSparkContext ctx = new JavaSparkContext(sparkConf);
>>> JavaPairRDD<String, Byte> seqFiles = ctx.sequenceFile(args[0],
>>> String.class, Byte.class) ;
>>> final List<Tuple2<String, Byte>> tuple2s = seqFiles.collect();
>>>
>>>
>>>
>>>
>>> The moment I try to call collect() method to get the keys of sequence
>>> file,
>>> following exception has been thrown
>>>
>>> Can any one help me understanding why collect() method is failing? If I
>>> use
>>> toArray() on seqFiles object then also I am getting same call stack.
>>>
>>> Regards
>>> Tapan
>>>
>>>
>>>
>>> java.io.NotSerializableException: org.apache.hadoop.io.Text
>>> at
>>> java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1183)
>>> at
>>>
>>> java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1547)
>>> at
>>> java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1508)
>>> at
>>>
>>> java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1431)
>>> at
>>> java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1177)
>>> at
>>> java.io.ObjectOutputStream.writeArray(ObjectOutputStream.java:1377)
>>> at
>>> java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1173)
>>> at
>>> java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:347)
>>> at
>>>
>>> org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:42)
>>> at
>>>
>>> org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:73)
>>> at
>>> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:206)
>>> at
>>>
>>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>>> at
>>>
>>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>>> at java.lang.Thread.run(Thread.java:745)
>>> 2015-05-19 15:15:03,705 ERROR [task-result-getter-0]
>>> scheduler.TaskSetManager (Logging.scala:logError(75)) - Task 0.0 in stage
>>> 0.0 (TID 0) had a not serializable result: org.apache.hadoop.io.Text; not
>>> retrying
>>> 2015-05-19 15:15:03,731 INFO [task-result-getter-0]
>>> scheduler.TaskSchedulerImpl (Logging.scala:logInfo(59)) - Removed TaskSet
>>> 0.0, whose tasks have all completed, from pool
>>> 2015-05-19 15:15:03,739 INFO
>>> [sparkDriver-akka.actor.default-dispatcher-2]
>>> scheduler.TaskSchedulerImpl (Logging.scala:logInfo(59)) - Cancelling
>>> stage 0
>>> 2015-05-19 15:15:03,747 INFO [main] scheduler.DAGScheduler
>>> (Logging.scala:logInfo(59)) - Job 0 failed: collect at
>>> JavaSequenceFile.java:44, took 4.421397 s
>>> Exception in thread "main" org.apache.spark.SparkException: Job aborted
>>> due
>>> to stage failure: Task 0.0 in stage 0.0 (TID 0) had a not serializable
>>> result: org.apache.hadoop.io.Text
>>> at
>>> org.apache.spark.scheduler.DAGScheduler.org
>>> $apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1214)
>>> at
>>>
>>> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1203)
>>> at
>>>
>>> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1202)
>>> at
>>>
>>> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
>>> at
>>> scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
>>> at
>>>
>>> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1202)
>>> at
>>>
>>> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:696)
>>> at
>>>
>>> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:696)
>>> at scala.Option.foreach(Option.scala:236)
>>> at
>>>
>>> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:696)
>>> at
>>>
>>> org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1420)
>>> at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
>>> at akka.actor.ActorCell.invoke(ActorCell.scala:456)
>>> at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
>>> at akka.dispatch.Mailbox.run(Mailbox.scala:219)
>>> at
>>>
>>> akka.dispatch.ForkJoinExecutorConfigurator$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)
>>>
>>>
>>>
>>>
>>>
>>>
>>> --
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>>
>
