对 Spark RDD 执行收集操作时出错

Question

JDK1.8.0_141
Spark 2.2（随 brew 安装）

我是 Spark 的新手，刚刚使用 brew 安装了它。在 iPython notebook 中，我创建了一个 RDD，它只是一个字符串列表。我运行对其进行了一些转换，一个是使列表中的所有项目成为一个元组的映射函数，另一个是 reduceByKey 函数。

wordsList = ['cat', 'elephant', 'rat', 'rat', 'cat']
wordsRDD = sc.parallelize(wordsList, 4)
wordCountsCollected = (wordsRDD
                       .map(lambda w: (w, 1))
                       .reduceByKey(lambda x,y: x+y)
                       .collect())
print(wordCountsCollected)

一切正常，直到我运行收集它。我得到这个回溯。

---------------------------------------------------------------------------
Py4JJavaError                             Traceback (most recent call last)
<ipython-input-46-88b98f07e38a> in <module>()
      4 wordCountsCollected = (wordsRDD
      5                        .map(lambda w: (w, 1))
----> 6                        .reduceByKey(lambda x,y: x+y)
      7                        .collect())
      8 print(wordCountsCollected)

/usr/local/opt/apache-spark/libexec/python/pyspark/rdd.py in collect(self)
    807         """
    808         with SCCallSiteSync(self.context) as css:
--> 809             port = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
    810         return list(_load_from_socket(port, self._jrdd_deserializer))
    811 

/usr/local/opt/apache-spark/libexec/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py in __call__(self, *args)
   1131         answer = self.gateway_client.send_command(command)
   1132         return_value = get_return_value(
-> 1133             answer, self.gateway_client, self.target_id, self.name)
   1134 
   1135         for temp_arg in temp_args:

/usr/local/opt/apache-spark/libexec/python/lib/py4j-0.10.4-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
    317                 raise Py4JJavaError(
    318                     "An error occurred while calling {0}{1}{2}.\n".
--> 319                     format(target_id, ".", name), value)
    320             else:
    321                 raise Py4JError(

Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 2 in stage 36.0 failed 1 times, most recent failure: Lost task 2.0 in stage 36.0 (TID 97, localhost, executor driver): java.lang.VerifyError: Bad instruction
Exception Details:
  Location:
    org/apache/spark/storage/ShuffleIndexBlockId.shuffleId()I @4: <illegal>
  Reason:
    Error exists in the bytecode
  Bytecode:
    0x0000000: 2ab4 0029 ec                           

    at org.apache.spark.shuffle.IndexShuffleBlockResolver.getIndexFile(IndexShuffleBlockResolver.scala:59)
    at org.apache.spark.shuffle.IndexShuffleBlockResolver.writeIndexFileAndCommit(IndexShuffleBlockResolver.scala:141)
    at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:164)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
    at org.apache.spark.scheduler.Task.run(Task.scala:108)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)

Driver stacktrace:
    at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1499)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage.apply(DAGScheduler.scala:1487)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage.apply(DAGScheduler.scala:1486)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1486)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed.apply(DAGScheduler.scala:814)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed.apply(DAGScheduler.scala:814)
    at scala.Option.foreach(Option.scala:257)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:814)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1714)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1669)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1658)
    at org.apache.spark.util.EventLoop$$anon.run(EventLoop.scala:48)
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:630)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2022)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2043)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2062)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2087)
    at org.apache.spark.rdd.RDD$$anonfun$collect.apply(RDD.scala:936)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
    at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
    at org.apache.spark.rdd.RDD.collect(RDD.scala:935)
    at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:458)
    at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
    at sun.reflect.GeneratedMethodAccessor53.invoke(Unknown Source)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
    at py4j.Gateway.invoke(Gateway.java:280)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:214)
    at java.lang.Thread.run(Thread.java:748)
Caused by: java.lang.VerifyError: Bad instruction
Exception Details:
  Location:
    org/apache/spark/storage/ShuffleIndexBlockId.shuffleId()I @4: <illegal>
  Reason:
    Error exists in the bytecode
  Bytecode:
    0x0000000: 2ab4 0029 ec                           

    at org.apache.spark.shuffle.IndexShuffleBlockResolver.getIndexFile(IndexShuffleBlockResolver.scala:59)
    at org.apache.spark.shuffle.IndexShuffleBlockResolver.writeIndexFileAndCommit(IndexShuffleBlockResolver.scala:141)
    at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:164)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
    at org.apache.spark.scheduler.Task.run(Task.scala:108)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    ... 1 more

iPython 笔记本进口

%pylab inline
import pandas as pd
import seaborn as sns
pd.set_option('display.width', 500)
pd.set_option('display.max_columns', 100)

import findspark
findspark.init()
import pyspark
sc = pyspark.SparkContext()

spark-shell

中的简单命令

Input >>> scala> spark.range(10).show
Output >>> 
+---+
| id|
+---+
|  0|
|  1|
|  2|
|  3|
|  4|
|  5|
|  6|
|  7|
|  8|
|  9|
+---+

Answer 1

我解决了我的问题。我是运行 iPython notebook 上的一个教程，它必须是 python2.7 上的运行，我主要运行在我的电脑上。我应该被所有使用旧语法 "print x" 而不是 print(x) 的打印语句告知。无论如何，在 iPython 笔记本上使用 Apache Spark 的重要库 findspark 安装在 python3.5 上，但没有安装在 python2.7 上，并且在较旧的 python 版本上安装它之后，一切都很糟糕。故事的寓意，请始终检查您的 Python 版本 :)！谢谢大家的帮助。

对 Spark RDD 执行收集操作时出错

Error while performing collect action on Spark RDD

python

java

collect

apache-spark