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)
--
View this message in context:
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.
---------------------------------------------------------------------
To unsubscribe, e-mail: user-unsubscr...@spark.apache.org
For additional commands, e-mail: user-h...@spark.apache.org
