Pyspark 具有多个值的reduceByKey

我的rdd中的每个值都是一个元组：

temp = clustering.map(lambda x: (x[0][0], (1,1)))
temp.take(10)

[(0, (1, 1)),
 (0, (1, 1)),
 (6, (1, 1)),
 (0, (1, 1)),
 (0, (1, 1)),
 (0, (1, 1)),
 (0, (1, 1)),
 (0, (1, 1)),
 (7, (1, 1)),
 (0, (1, 1))]

然后尝试按键减少它：

temp.reduceByKey(lambda a,b: (a[1]+b[1])).collect()

得到了这个错误：

    ---------------------------------------------------------------------------
Py4JJavaError                             Traceback (most recent call last)
<ipython-input-33-237802845981> in <module>
----> 1 temp.reduceByKey(lambda a,b: (a[1]+b[1])).collect()

~\AppData\Local\Continuum\anaconda3\lib\site-packages\pyspark\rdd.py in collect(self)
    814         """
    815         with SCCallSiteSync(self.context) as css:
--> 816             sock_info = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
    817         return list(_load_from_socket(sock_info, self._jrdd_deserializer))
    818 

~\AppData\Local\Continuum\anaconda3\lib\site-packages\py4j\java_gateway.py in __call__(self, *args)
   1255         answer = self.gateway_client.send_command(command)
   1256         return_value = get_return_value(
-> 1257             answer, self.gateway_client, self.target_id, self.name)
   1258 
   1259         for temp_arg in temp_args:

~\AppData\Local\Continuum\anaconda3\lib\site-packages\py4j\protocol.py in get_return_value(answer, gateway_client, target_id, name)
    326                 raise Py4JJavaError(
    327                     "An error occurred while calling {0}{1}{2}.\n".
--> 328                     format(target_id, ".", name), value)
    329             else:
    330                 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 0 in stage 35.0 failed 1 times, most recent failure: Lost task 0.0 in stage 35.0 (TID 28, localhost, executor driver): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
  File "C:\Users\helmis\AppData\Local\Continuum\anaconda3\Lib\site-packages\pyspark\python\lib\pyspark.zip\pyspark\worker.py", line 377, in main
  File "C:\Users\helmis\AppData\Local\Continuum\anaconda3\Lib\site-packages\pyspark\python\lib\pyspark.zip\pyspark\worker.py", line 372, in process
  File "C:\Users\helmis\AppData\Local\Continuum\anaconda3\lib\site-packages\pyspark\rdd.py", line 2499, in pipeline_func
    return func(split, prev_func(split, iterator))
  File "C:\Users\helmis\AppData\Local\Continuum\anaconda3\lib\site-packages\pyspark\rdd.py", line 2499, in pipeline_func
    return func(split, prev_func(split, iterator))
  File "C:\Users\helmis\AppData\Local\Continuum\anaconda3\lib\site-packages\pyspark\rdd.py", line 352, in func
    return f(iterator)
  File "C:\Users\helmis\AppData\Local\Continuum\anaconda3\lib\site-packages\pyspark\rdd.py", line 1861, in combineLocally
    merger.mergeValues(iterator)
  File "C:\Users\helmis\AppData\Local\Continuum\anaconda3\Lib\site-packages\pyspark\python\lib\pyspark.zip\pyspark\shuffle.py", line 240, in mergeValues
    d[k] = comb(d[k], v) if k in d else creator(v)
  File "C:\Users\helmis\AppData\Local\Continuum\anaconda3\lib\site-packages\pyspark\util.py", line 99, in wrapper
    return f(*args, **kwargs)
  File "<ipython-input-33-237802845981>", line 1, in <lambda>
TypeError: 'int' object is not subscriptable

    at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:452)
    at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:588)
    at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:571)
    at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:406)
    at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
    at scala.collection.Iterator$GroupedIterator.fill(Iterator.scala:1124)
    at scala.collection.Iterator$GroupedIterator.hasNext(Iterator.scala:1130)
    at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
    at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:55)
    at org.apache.spark.scheduler.Task.run(Task.scala:121)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$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$$failJobAndIndependentStages(DAGScheduler.scala:1889)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1877)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1876)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1876)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
    at scala.Option.foreach(Option.scala:257)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:926)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2110)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2059)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2048)
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:737)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2082)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2101)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2126)
    at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:945)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
    at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
    at org.apache.spark.rdd.RDD.collect(RDD.scala:944)
    at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:166)
    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:\Users\helmis\AppData\Local\Continuum\anaconda3\Lib\site-packages\pyspark\python\lib\pyspark.zip\pyspark\worker.py", line 377, in main
  File "C:\Users\helmis\AppData\Local\Continuum\anaconda3\Lib\site-packages\pyspark\python\lib\pyspark.zip\pyspark\worker.py", line 372, in process
  File "C:\Users\helmis\AppData\Local\Continuum\anaconda3\lib\site-packages\pyspark\rdd.py", line 2499, in pipeline_func
    return func(split, prev_func(split, iterator))
  File "C:\Users\helmis\AppData\Local\Continuum\anaconda3\lib\site-packages\pyspark\rdd.py", line 2499, in pipeline_func
    return func(split, prev_func(split, iterator))
  File "C:\Users\helmis\AppData\Local\Continuum\anaconda3\lib\site-packages\pyspark\rdd.py", line 352, in func
    return f(iterator)
  File "C:\Users\helmis\AppData\Local\Continuum\anaconda3\lib\site-packages\pyspark\rdd.py", line 1861, in combineLocally
    merger.mergeValues(iterator)
  File "C:\Users\helmis\AppData\Local\Continuum\anaconda3\Lib\site-packages\pyspark\python\lib\pyspark.zip\pyspark\shuffle.py", line 240, in mergeValues
    d[k] = comb(d[k], v) if k in d else creator(v)
  File "C:\Users\helmis\AppData\Local\Continuum\anaconda3\lib\site-packages\pyspark\util.py", line 99, in wrapper
    return f(*args, **kwargs)
  File "<ipython-input-33-237802845981>", line 1, in <lambda>
TypeError: 'int' object is not subscriptable

    at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:452)
    at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:588)
    at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:571)
    at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:406)
    at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
    at scala.collection.Iterator$GroupedIterator.fill(Iterator.scala:1124)
    at scala.collection.Iterator$GroupedIterator.hasNext(Iterator.scala:1130)
    at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
    at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:55)
    at org.apache.spark.scheduler.Task.run(Task.scala:121)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    ... 1 more

得到：

[(0, None),
 (6, None),
 (7, None),
 (8, None),
 (5, None),
 (3, None),
 (9, None),
 (1, (1, 1)),
 (2, (1, 1)),
 (4, None)]

所以，我不知道怎么了！谢谢你的帮助

我想最终得到的是：

---

temp.reduceByKey（lambda a，b:（a[0]+b[0]，a[1]+b[1]）。collect（）

在您的代码中有两个值，但您希望单独聚合值-2。因此，您的代码编写如下：

温度还原基（λa，b:（a[1]+b[1]）。收集（）

错误原因： 由于代码中缺少值-1的位置，因此抛出错误。您必须在代码中指定值-1（a[0]），即如下所示：

---

温度还原键（λa，b:（a[0]，a[1]+b[1]）。取（20）

谢谢你的回复。我认为值1隐式地是键，a和b都指向第二个值，在本例中，哪个值是元组？

[(0, None),
 (6, None),
 (7, None),
 (8, None),
 (5, None),
 (3, None),
 (9, None),
 (1, (1, 1)),
 (2, (1, 1)),
 (4, None)]