如何在Apache Spark上对整数列表进行排序？

时间：2018-09-02 14:06:51

标签： python-2.7 sorting apache-spark pyspark rdd

最近，我开始使用Apache Spark对大量数据进行排序。

在最初的测试中，我尝试在 PySpark 上并行对整数列表进行排序，但是显然使用 sortByKey（）方法时发生了错误。

>>> rdd = sc.parallelize([5,3,4,7,6,9])
>>> rdd.sortByKey(True)

2018-09-02 10:39:42 ERROR Executor:91 - Exception in task 2.0 in stage 1.0 (TID 6)
org.apache.spark.api.python.PythonException: Traceback (most recent call last):
  File "C:\spark-2.3.1-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\worker.py", line 230, in main
  File "C:\spark-2.3.1-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\worker.py", line 225, in process
  File "C:\spark-2.3.1-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\serializers.py", line 372, in dump_stream
    vs = list(itertools.islice(iterator, batch))
  File "C:\spark-2.3.1-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\util.py", line 55, in wrapper
    return f(*args, **kwargs)
  File "C:\spark-2.3.1-bin-hadoop2.7\python\pyspark\rdd.py", line 690, in <lambda>
    samples = self.sample(False, fraction, 1).map(lambda kv: kv[0]).collect()
TypeError: 'int' object has no attribute '__getitem__'

        at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:298)
        at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:438)
        at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:421)
        at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:252)
        at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
        at scala.collection.Iterator$class.foreach(Iterator.scala:893)
        at org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28)
        at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
        at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
        at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
        at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
        at org.apache.spark.InterruptibleIterator.to(InterruptibleIterator.scala:28)
        at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)
        at org.apache.spark.InterruptibleIterator.toBuffer(InterruptibleIterator.scala:28)
        at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)
        at org.apache.spark.InterruptibleIterator.toArray(InterruptibleIterator.scala:28)
        at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)
        at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)
        at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2074)
        at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2074)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
        at org.apache.spark.scheduler.Task.run(Task.scala:109)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
        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)
2018-09-02 10:39:42 WARN  TaskSetManager:66 - Lost task 2.0 in stage 1.0 (TID 6, localhost, executor driver): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
  File "C:\spark-2.3.1-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\worker.py", line 230, in main
  File "C:\spark-2.3.1-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\worker.py", line 225, in process
  File "C:\spark-2.3.1-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\serializers.py", line 372, in dump_stream
    vs = list(itertools.islice(iterator, batch))
  File "C:\spark-2.3.1-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\util.py", line 55, in wrapper
    return f(*args, **kwargs)
  File "C:\spark-2.3.1-bin-hadoop2.7\python\pyspark\rdd.py", line 690, in <lambda>
    samples = self.sample(False, fraction, 1).map(lambda kv: kv[0]).collect()
TypeError: 'int' object has no attribute '__getitem__'

        at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:298)
        at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:438)
        at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:421)
        at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:252)
        at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
        at scala.collection.Iterator$class.foreach(Iterator.scala:893)
        at org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28)
        at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
        at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
        at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
        at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
        at org.apache.spark.InterruptibleIterator.to(InterruptibleIterator.scala:28)
        at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)
        at org.apache.spark.InterruptibleIterator.toBuffer(InterruptibleIterator.scala:28)
        at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)
        at org.apache.spark.InterruptibleIterator.toArray(InterruptibleIterator.scala:28)
        at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)
        at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)
        at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2074)
        at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2074)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
        at org.apache.spark.scheduler.Task.run(Task.scala:109)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
        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)

2018-09-02 10:39:42 ERROR TaskSetManager:70 - Task 2 in stage 1.0 failed 1 times; aborting job
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "C:\spark-2.3.1-bin-hadoop2.7\python\pyspark\rdd.py", line 690, in sortByKey
    samples = self.sample(False, fraction, 1).map(lambda kv: kv[0]).collect()
  File "C:\spark-2.3.1-bin-hadoop2.7\python\pyspark\rdd.py", line 834, in collect
    sock_info = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
  File "C:\spark-2.3.1-bin-hadoop2.7\python\lib\py4j-0.10.7-src.zip\py4j\java_gateway.py", line 1257, in __call__
  File "C:\spark-2.3.1-bin-hadoop2.7\python\pyspark\sql\utils.py", line 63, in deco
    return f(*a, **kw)
  File "C:\spark-2.3.1-bin-hadoop2.7\python\lib\py4j-0.10.7-src.zip\py4j\protocol.py", line 328, in get_return_value
py4j.protocol.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 1.0 failed 1 times, most recent failure: Lost task 2.0 in stage 1.0 (TID 6, localhost, executor driver): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
  File "C:\spark-2.3.1-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\worker.py", line 230, in main
  File "C:\spark-2.3.1-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\worker.py", line 225, in process
  File "C:\spark-2.3.1-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\serializers.py", line 372, in dump_stream
    vs = list(itertools.islice(iterator, batch))
  File "C:\spark-2.3.1-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\util.py", line 55, in wrapper
    return f(*args, **kwargs)
  File "C:\spark-2.3.1-bin-hadoop2.7\python\pyspark\rdd.py", line 690, in <lambda>
    samples = self.sample(False, fraction, 1).map(lambda kv: kv[0]).collect()
TypeError: 'int' object has no attribute '__getitem__'

        at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:298)
        at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:438)
        at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:421)
        at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:252)
        at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
        at scala.collection.Iterator$class.foreach(Iterator.scala:893)
        at org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28)
        at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
        at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
        at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
        at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
        at org.apache.spark.InterruptibleIterator.to(InterruptibleIterator.scala:28)
        at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)
        at org.apache.spark.InterruptibleIterator.toBuffer(InterruptibleIterator.scala:28)
        at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)
        at org.apache.spark.InterruptibleIterator.toArray(InterruptibleIterator.scala:28)
        at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)
        at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)
        at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2074)
        at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2074)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
        at org.apache.spark.scheduler.Task.run(Task.scala:109)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
        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$$failJobAndIndependentStages(DAGScheduler.scala:1602)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1590)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1589)
        at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
        at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
        at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1589)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
        at scala.Option.foreach(Option.scala:257)
        at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:831)
        at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1823)
        at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1772)
        at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1761)
        at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
        at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642)
        at org.apache.spark.SparkContext.runJob(SparkContext.scala:2034)
        at org.apache.spark.SparkContext.runJob(SparkContext.scala:2055)
        at org.apache.spark.SparkContext.runJob(SparkContext.scala:2074)
        at org.apache.spark.SparkContext.runJob(SparkContext.scala:2099)
        at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:939)
        at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
        at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
        at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
        at org.apache.spark.rdd.RDD.collect(RDD.scala:938)
        at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:162)
        at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
        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 py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
        at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
        at py4j.Gateway.invoke(Gateway.java:282)
        at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
        at py4j.commands.CallCommand.execute(CallCommand.java:79)
        at py4j.GatewayConnection.run(GatewayConnection.java:238)
        at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last):
  File "C:\spark-2.3.1-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\worker.py", line 230, in main
  File "C:\spark-2.3.1-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\worker.py", line 225, in process
  File "C:\spark-2.3.1-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\serializers.py", line 372, in dump_stream
    vs = list(itertools.islice(iterator, batch))
  File "C:\spark-2.3.1-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\util.py", line 55, in wrapper
    return f(*args, **kwargs)
  File "C:\spark-2.3.1-bin-hadoop2.7\python\pyspark\rdd.py", line 690, in <lambda>
    samples = self.sample(False, fraction, 1).map(lambda kv: kv[0]).collect()
TypeError: 'int' object has no attribute '__getitem__'

        at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:298)
        at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:438)
        at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:421)
        at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:252)
        at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
        at scala.collection.Iterator$class.foreach(Iterator.scala:893)
        at org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28)
        at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
        at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
        at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
        at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
        at org.apache.spark.InterruptibleIterator.to(InterruptibleIterator.scala:28)
        at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)
        at org.apache.spark.InterruptibleIterator.toBuffer(InterruptibleIterator.scala:28)
        at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)
        at org.apache.spark.InterruptibleIterator.toArray(InterruptibleIterator.scala:28)
        at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)
        at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)
        at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2074)
        at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2074)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
        at org.apache.spark.scheduler.Task.run(Task.scala:109)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        ... 1 more

>>> 2018-09-02 10:39:42 WARN  TaskSetManager:66 - Lost task 0.0 in stage 1.0 (TID 4, localhost, executor driver): TaskKilled (Stage cancelled)
2018-09-02 10:39:42 WARN  TaskSetManager:66 - Lost task 3.0 in stage 1.0 (TID 7, localhost, executor driver): TaskKilled (Stage cancelled)
2018-09-02 10:39:43 WARN  TaskSetManager:66 - Lost task 1.0 in stage 1.0 (TID 5, localhost, executor driver): TaskKilled (Stage cancelled)

如何使用Apache Spark并行处理整数列表？

  

我正在使用Windows 10，Java SE Development Kit 8和Python 2.7.15

2 个答案:

答案 0 :(得分：1)

您要查找的方法是sortBy而不是sortByKey：

rdd.sortBy(lambda x: x)

答案 1 :(得分：0)

您不能在这里真正使用 sortByKey ，因为它是仅在 PairRDD 上实现的方法。 R，您的RDD不是PairRDD，即不是键/值对的分布式集合。

您可以改用 sortBy（function），您必须在其中提供排序条件。适合您的情况，您应该尝试：

rdd.sortBy(lambda x => x)

我希望这对您有帮助

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