2016-12-01 108 views
1

我試圖讓火花集羣正常工作。請注意,它是由其他人設置的。我試圖通過Spark Streaming來結合Kafka,但是每當我嘗試使用PySpark時,即使沒有使用Spark Streaming,我也會得到以下錯誤。Pyspark Kafka Streaming

從我的理解星火主機正在發送的從節點使用spark.driver.extraClassPathspark-defaults.conf文件的卡夫卡流罐子的位置,罐子中的所有節點,包括主上的正確位置。

我發現奇怪的一件事是,當spark-defaults.con文件指示該罐位於/usr/local/src中時,節點似乎正在尋找/jar目錄中的罐子。

我做了更改後重置所有節點,我甚至刪除了jar的引用,但節點仍然在尋找它。

Py4JJavaError        Traceback (most recent call last) 
<ipython-input-3-3d993e9922f2> in <module>() 
----> 1 data = df.select('subject_id', 'date').where("stats is not null and date > '2009-10-31' and date < '2010-03-01'").first() 

/usr/local/src/spark-2.0.0-bin-hadoop2.7/python/pyspark/sql/dataframe.pyc in first(self) 
    804   Row(age=2, name=u'Alice') 
    805   """ 
--> 806   return self.head() 
    807 
    808  @ignore_unicode_prefix 

/usr/local/src/spark-2.0.0-bin-hadoop2.7/python/pyspark/sql/dataframe.pyc in head(self, n) 
    792   """ 
    793   if n is None: 
--> 794    rs = self.head(1) 
    795    return rs[0] if rs else None 
    796   return self.take(n) 

/usr/local/src/spark-2.0.0-bin-hadoop2.7/python/pyspark/sql/dataframe.pyc in head(self, n) 
    794    rs = self.head(1) 
    795    return rs[0] if rs else None 
--> 796   return self.take(n) 
    797 
    798  @ignore_unicode_prefix 

/usr/local/src/spark-2.0.0-bin-hadoop2.7/python/pyspark/sql/dataframe.pyc in take(self, num) 
    348   with SCCallSiteSync(self._sc) as css: 
    349    port = self._sc._jvm.org.apache.spark.sql.execution.python.EvaluatePython.takeAndServe(
--> 350     self._jdf, num) 
    351   return list(_load_from_socket(port, BatchedSerializer(PickleSerializer()))) 
    352 

/usr/local/src/spark-2.0.0-bin-hadoop2.7/python/lib/py4j-0.10.1-src.zip/py4j/java_gateway.py in __call__(self, *args) 
    931   answer = self.gateway_client.send_command(command) 
    932   return_value = get_return_value(
--> 933    answer, self.gateway_client, self.target_id, self.name) 
    934 
    935   for temp_arg in temp_args: 

/usr/local/src/spark-2.0.0-bin-hadoop2.7/python/pyspark/sql/utils.pyc in deco(*a, **kw) 
    61  def deco(*a, **kw): 
    62   try: 
---> 63    return f(*a, **kw) 
    64   except py4j.protocol.Py4JJavaError as e: 
    65    s = e.java_exception.toString() 

/usr/local/src/spark-2.0.0-bin-hadoop2.7/python/lib/py4j-0.10.1-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name) 
    310     raise Py4JJavaError(
    311      "An error occurred while calling {0}{1}{2}.\n". 
--> 312      format(target_id, ".", name), value) 
    313    else: 
    314     raise Py4JError(

Py4JJavaError: An error occurred while calling z:org.apache.spark.sql.execution.python.EvaluatePython.takeAndServe. 
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 3, 10.95.96.142): java.lang.RuntimeException: Stream '/jars/spark-streaming-kafka-0-8-assembly_2.11-2.0.1.jar' was not found. 
    at org.apache.spark.network.client.TransportResponseHandler.handle(TransportResponseHandler.java:223) 
    at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:121) 
    at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:51) 
    at io.netty.channel.SimpleChannelInboundHandler.channelRead(SimpleChannelInboundHandler.java:105) 
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308) 
    at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294) 
    at io.netty.handler.timeout.IdleStateHandler.channelRead(IdleStateHandler.java:266) 
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308) 
    at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294) 
    at io.netty.handler.codec.MessageToMessageDecoder.channelRead(MessageToMessageDecoder.java:103) 
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308) 
    at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294) 
    at org.apache.spark.network.util.TransportFrameDecoder.channelRead(TransportFrameDecoder.java:85) 
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308) 
    at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294) 
    at io.netty.channel.DefaultChannelPipeline.fireChannelRead(DefaultChannelPipeline.java:846) 
    at io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:131) 
    at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:511) 
    at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:468) 
    at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:382) 
    at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:354) 
    at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:111) 
    at java.lang.Thread.run(Thread.java:745) 

Driver stacktrace: 
    at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1450) 
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1438) 
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1437) 
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) 
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) 
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1437) 
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811) 
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811) 
    at scala.Option.foreach(Option.scala:257) 
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:811) 
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1659) 
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1618) 
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1607) 
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) 
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:632) 
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1871) 
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1884) 
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1897) 
    at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:347) 
    at org.apache.spark.sql.execution.python.EvaluatePython$$anonfun$takeAndServe$1.apply$mcI$sp(EvaluatePython.scala:41) 
    at org.apache.spark.sql.execution.python.EvaluatePython$$anonfun$takeAndServe$1.apply(EvaluatePython.scala:39) 
    at org.apache.spark.sql.execution.python.EvaluatePython$$anonfun$takeAndServe$1.apply(EvaluatePython.scala:39) 
    at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57) 
    at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2532) 
    at org.apache.spark.sql.execution.python.EvaluatePython$.takeAndServe(EvaluatePython.scala:39) 
    at org.apache.spark.sql.execution.python.EvaluatePython.takeAndServe(EvaluatePython.scala) 
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) 
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) 
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) 
    at java.lang.reflect.Method.invoke(Method.java:606) 
    at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:237) 
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) 
    at py4j.Gateway.invoke(Gateway.java:280) 
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:128) 
    at py4j.commands.CallCommand.execute(CallCommand.java:79) 
    at py4j.GatewayConnection.run(GatewayConnection.java:211) 
    at java.lang.Thread.run(Thread.java:745) 
Caused by: java.lang.RuntimeException: Stream '/jars/spark-streaming-kafka-0-8-assembly_2.11-2.0.1.jar' was not found. 
    at org.apache.spark.network.client.TransportResponseHandler.handle(TransportResponseHandler.java:223) 
    at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:121) 
    at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:51) 
    at io.netty.channel.SimpleChannelInboundHandler.channelRead(SimpleChannelInboundHandler.java:105) 
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308) 
    at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294) 
    at io.netty.handler.timeout.IdleStateHandler.channelRead(IdleStateHandler.java:266) 
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308) 
    at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294) 
    at io.netty.handler.codec.MessageToMessageDecoder.channelRead(MessageToMessageDecoder.java:103) 
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308) 
    at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294) 
    at org.apache.spark.network.util.TransportFrameDecoder.channelRead(TransportFrameDecoder.java:85) 
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308) 
    at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294) 
    at io.netty.channel.DefaultChannelPipeline.fireChannelRead(DefaultChannelPipeline.java:846) 
    at io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:131) 
    at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:511) 
    at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:468) 
    at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:382) 
    at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:354) 
    at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:111) 
    ... 1 more 

回答

0

所以這個問題歸結爲尋找其中配置實際上被設置。在我發現spark-submit的電話後,我發現添加的罐子被:分隔,而不是,,所以火花正在將多個罐子視爲一個罐子。有趣的是stacktrace考慮了:定界符,並且只給出spark-streaming-kafka作爲未被發現。

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