使用不可序列化的 Spark 从 HBase 流式传输

Question

我正在尝试使用 Spark 从 HBase 流式传输数据。当我运行 Scala 脚本时，这是我得到的错误：

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

起初我以为我的数据格式不正确，所以我尝试创建一个只有一行的非常基本的 table：

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

即使有这一行，我仍然得到同样的错误。有什么明显的我想念的吗？这是脚本：

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：根据要求，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.apply(DAGScheduler.scala:1203)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage.apply(DAGScheduler.scala:1202)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1202)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed.apply(DAGScheduler.scala:696)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed.apply(DAGScheduler.scala:696)
    at scala.Option.foreach(Option.scala:236)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:696)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive.applyOrElse(DAGScheduler.scala:1420)
    at akka.actor.Actor$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)

Answer 1

通过将 rdd 映射到 toStringBinary

解决了这个问题

Answer 2

RDD 中的元组必须可序列化为 return 给驱动程序。首先尝试将元组映射到字符串。

rdd.map(_.toString).first

Answer 3

将ImmutableBytesWritable转换为String如下：

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

Answer 4

对整个数据集进行一些改进。

rdd.map(_.toString()).collect().foreach(println)

使用不可序列化的 Spark 从 HBase 流式传输

Streaming from HBase using Spark not serializable

hbase

scala

apache-spark