2015-01-26 41 views
2

我想从使用Spark的HBase流式传输数据。当我运行的Scala脚本,这是错误我得到:使用Spark不能序列化从HBase流式传输

ERROR Executor: Exception in task 0.0 in stage 10.0 (TID 10) 
java.io.NotSerializableException: org.apache.hadoop.hbase.io.ImmutableBytesWritable 

我起初以为我的数据格式不正确,所以我想只有一个行创建一个非常基本的表:

row1 column=fam1:c1, timestamp=1422306700801, value=abc 

即使这一行,我仍然会得到相同的错误。任何明显的我失踪?这里的脚本:

def convertScanToString(scan: Scan): String = { 
    val out: ByteArrayOutputStream = new ByteArrayOutputStream 
    val dos: DataOutputStream = new DataOutputStream(out) 
    scan.write(dos) 
    Base64.encodeBytes(out.toByteArray) 
} 

val conf = HBaseConfiguration.create() 
val scan = new Scan() 
scan.setCaching(500) 
scan.setCacheBlocks(false) 
conf.set(TableInputFormat.INPUT_TABLE, "test_table") 
conf.set(TableInputFormat.SCAN, convertScanToString(scan)) 
val rdd = sc.newAPIHadoopRDD(conf, classOf[TableInputFormat], classOf[ImmutableBytesWritable], classOf[Result]) 
rdd.first 

编辑:按照要求,这里是完整的堆栈跟踪

15/01/26 21:50:50 ERROR Executor: Exception in task 0.0 in stage 14.0 (TID 14) 
java.io.NotSerializableException: org.apache.hadoop.hbase.io.ImmutableBytesWritable 
    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:744) 
15/01/26 21:50:50 ERROR TaskSetManager: Task 0.0 in stage 14.0 (TID 14) had a not serializable result: org.apache.hadoop.hbase.io.ImmutableBytesWritable; not retrying 
15/01/26 21:50:50 INFO TaskSchedulerImpl: Removed TaskSet 14.0, whose tasks have all completed, from pool 
15/01/26 21:50:50 INFO TaskSchedulerImpl: Cancelling stage 14 
15/01/26 21:50:50 INFO DAGScheduler: Job 14 failed: first at <console>:207, took 0.021506 s 
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0.0 in stage 14.0 (TID 14) had a not serializable result: org.apache.hadoop.hbase.io.ImmutableBytesWritable 
    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$2.applyOrElse(DAGScheduler.scala:1420) 
    at akka.actor.Actor$class.aroundReceive(Actor.scala:465) 
    at org.apache.spark.scheduler.DAGSchedulerEventProcessActor.aroundReceive(DAGScheduler.scala:1375) 
    at akka.actor.ActorCell.receiveMessage(ActorCell.scala:516) 
    at akka.actor.ActorCell.invoke(ActorCell.scala:487) 
    at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:238) 
    at akka.dispatch.Mailbox.run(Mailbox.scala:220) 
    at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:393) 
    at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260) 
    at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339) 
    at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979) 
    at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107) 
+0

您可以更新您的问题,包括完整的堆栈跟踪,而不仅仅是最后的例外呢? – 2015-01-26 22:24:09

回答

0

与toStringBinary

+0

你能指导我通过你的解决方案我面临同样的问题: – sau 2015-03-23 12:09:24

+0

@petfreshman请您提供解决方案的代码片段或示例吗? – devl 2015-04-27 14:59:27

4

映射RDD在RDD的元组必须是可序列化来解决这个返回到驱动程序。尝试首先将元组映射到一个字符串。

rdd.map(_.toString).first 
0

转换的ImmutableBytesWritableString如下:

import org.apache.hadoop.hbase.util.Bytes 
rdd.map(t=> (Bytes.toStringBinary(t._1.get()), t._2)) 
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