Thanks. I will try and let you know. But what exactly is an issue? Any
pointers?
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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>> http://apache-spark-user-list.1001560.n3.nabble.com/Reading-Binary-files-in-Spark-program-tp22942.html
>> Sent from the Apache Spark User List mailing list archive at Nabble.com.
>>
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>
