最近在學(xué)習(xí)Apache Beam.
想把官方提供的WordCount的例子放到spark集群上去運(yùn)行,然后將結(jié)果寫到Hbase.
但是在用spark submit提交jar包的時(shí)候,遇到下面的報(bào)錯:

17/11/15 09:51:38 WARN SparkConf: In Spark 1.0 and later spark.local.dir will be overridden by the value set by the cluster manager (via SPARK_LOCAL_DIRS in mesos/standalone and LOCAL_DIRS in YARN).

Exception in thread "main" java.lang.RuntimeException: java.lang.AssertionError: assertion failed: copyAndReset must return a zero value copy
    at org.apache.beam.runners.spark.SparkPipelineResult.runtimeExceptionFrom(SparkPipelineResult.java:55)
    at org.apache.beam.runners.spark.SparkPipelineResult.beamExceptionFrom(SparkPipelineResult.java:72)
    at org.apache.beam.runners.spark.SparkPipelineResult.waitUntilFinish(SparkPipelineResult.java:99)
    at org.apache.beam.runners.spark.SparkPipelineResult.waitUntilFinish(SparkPipelineResult.java:87)
    at org.apache.beam.examples.WordCount.main(WordCount.java:219)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:729)
    at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:185)
    at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:210)
    at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:124)
    at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.AssertionError: assertion failed: copyAndReset must return a zero value copy
    at scala.Predef$.assert(Predef.scala:170)
    at org.apache.spark.util.AccumulatorV2.writeReplace(AccumulatorV2.scala:157)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at java.io.ObjectStreamClass.invokeWriteReplace(ObjectStreamClass.java:1118)
    at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1136)
    at java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1548)
    at java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1509)
    at java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
    at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
    at java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1548)
    at java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1509)
    at java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
    at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
    at java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1548)
    at java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1509)
    at java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
    at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
    at java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:348)
    at org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:43)
    at org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:100)
    at org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:295)
    at org.apache.spark.util.ClosureCleaner$.org$apache$spark$util$ClosureCleaner$$clean(ClosureCleaner.scala:288)
    at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:108)
    at org.apache.spark.SparkContext.clean(SparkContext.scala:2037)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1.apply(RDD.scala:763)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1.apply(RDD.scala:762)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
    at org.apache.spark.rdd.RDD.withScope(RDD.scala:358)
    at org.apache.spark.rdd.RDD.mapPartitions(RDD.scala:762)
    at org.apache.spark.api.java.JavaRDDLike$class.mapPartitionsToPair(JavaRDDLike.scala:187)
    at org.apache.spark.api.java.AbstractJavaRDDLike.mapPartitionsToPair(JavaRDDLike.scala:45)
    at org.apache.beam.runners.spark.translation.TransformTranslator$6.evaluate(TransformTranslator.java:393)
    at org.apache.beam.runners.spark.translation.TransformTranslator$6.evaluate(TransformTranslator.java:351)
    at org.apache.beam.runners.spark.SparkRunner$Evaluator.doVisitTransform(SparkRunner.java:412)
    at org.apache.beam.runners.spark.SparkRunner$Evaluator.visitPrimitiveTransform(SparkRunner.java:398)
    at org.apache.beam.sdk.runners.TransformHierarchy$Node.visit(TransformHierarchy.java:602)
    at org.apache.beam.sdk.runners.TransformHierarchy$Node.visit(TransformHierarchy.java:594)
    at org.apache.beam.sdk.runners.TransformHierarchy$Node.visit(TransformHierarchy.java:594)
    at org.apache.beam.sdk.runners.TransformHierarchy$Node.visit(TransformHierarchy.java:594)
    at org.apache.beam.sdk.runners.TransformHierarchy$Node.access$500(TransformHierarchy.java:276)
    at org.apache.beam.sdk.runners.TransformHierarchy.visit(TransformHierarchy.java:210)
    at org.apache.beam.sdk.Pipeline.traverseTopologically(Pipeline.java:440)
    at org.apache.beam.runners.spark.SparkRunner$2.run(SparkRunner.java:211)
    at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
    at java.util.concurrent.FutureTask.run(FutureTask.java:266)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    at java.lang.Thread.run(Thread.java:745)

在網(wǎng)上查閱資料,有人說是因?yàn)槟壳癇eam的spark runner只支持1.6.0版本的spark.(stackoverflow上的類似問題)
我把maven中spark的相關(guān)依賴改成了1.6.0,但是因?yàn)閟park集群的版本是2.0.0,所以還是會報(bào)這個錯.
想問問大神是否有辦法,在不改變集群的版本的情況下,能夠解決這個問題.

萬分感謝!