jupyter 노트북에서 아래 pyspark 변환을 실행하고 있습니다. 내 요구 사항은 469 + 84451 + 903 ...과 같은 요소의 모든 값을 추가하는 것이며 총 개수 만 반환해야합니다.
다음은 변화와 행동입니다.
In [46]: newdispokey1.collect()
[(u'Hello', 469),
(u'is', 84451),
(u'the', 903),
(u'an', 21208),
(u'and', 19903),
(u'route', 185),
(u'bag', 1894),
(u'metal', 315),
(u'bus', 620194),
(u'cloud', 1036)]
예상 결과는 모든 값을 더한 것입니다. 나는 아래의 변형과 행동을 시도하고 있습니다.
In [46]: newdispokey1.reduce( lambda x,y: x[1]+y[1] ).collect()
및 오류가 발생합니다.
---------------------------------------------------------------------------
Py4JJavaError Traceback (most recent call last)
<ipython-input-46-9557bb70b499> in <module>()
----> 1 newdispokey1.reduce( lambda x,y: x[1]+y[1] ).collect()
/home/newuser/spark/python/pyspark/rdd.pyc in reduce(self, f)
797 yield reduce(f, iterator, initial)
798
--> 799 vals = self.mapPartitions(func).collect()
800 if vals:
801 return reduce(f, vals)
/home/newuser/spark/python/pyspark/rdd.pyc in collect(self)
772 with SCCallSiteSync(self.context) as css:
--> 773 port = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
774 return list(_load_from_socket(port, self._jrdd_deserializer))
775
/home/newuser/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py in __call__(self, *args)
536 answer = self.gateway_client.send_command(command)
537 return_value = get_return_value(answer, self.gateway_client,
--> 538 self.target_id, self.name)
539
540 for temp_arg in temp_args:
/home/newuser/spark/python/pyspark/sql/utils.pyc in deco(*a, **kw)
34 def deco(*a, **kw):
35 try:
---> 36 return f(*a, **kw)
37 except py4j.protocol.Py4JJavaError as e:
38 s = e.java_exception.toString()
/home/newuser/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
298 raise Py4JJavaError(
299 'An error occurred while calling {0}{1}{2}.\n'.
--> 300 format(target_id, '.', name), value)
301 else:
302 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 48.0 failed 1 times, most recent failure: Lost task 0.0 in stage 48.0 (TID 167, localhost): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/home/newuser/spark/python/lib/pyspark.zip/pyspark/worker.py", line 111, in main
process()
File "/home/newuser/spark/python/lib/pyspark.zip/pyspark/worker.py", line 106, in process
serializer.dump_stream(func(split_index, iterator), outfile)
File "/home/newuser/spark/python/lib/pyspark.zip/pyspark/serializers.py", line 263, in dump_stream
vs = list(itertools.islice(iterator, batch))
File "/home/newuser/spark/python/pyspark/rdd.py", line 797, in func
yield reduce(f, iterator, initial)
File "<ipython-input-46-9557bb70b499>", line 1, in <lambda>
TypeError: 'int' object has no attribute '__getitem__'
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:166)
at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:300)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:88)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1283)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1271)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1270)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1270)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:697)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:697)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:697)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1496)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1458)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1447)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:567)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1824)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1837)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1850)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1921)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:909)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:310)
at org.apache.spark.rdd.RDD.collect(RDD.scala:908)
at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:405)
at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
at sun.reflect.GeneratedMethodAccessor46.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379)
at py4j.Gateway.invoke(Gateway.java:259)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:207)
at java.lang.Thread.run(Thread.java:745)
Caused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/home/newuser/spark/python/lib/pyspark.zip/pyspark/worker.py", line 111, in main
process()
File "/home/newuser/spark/python/lib/pyspark.zip/pyspark/worker.py", line 106, in process
serializer.dump_stream(func(split_index, iterator), outfile)
File "/home/newuser/spark/python/lib/pyspark.zip/pyspark/serializers.py", line 263, in dump_stream
vs = list(itertools.islice(iterator, batch))
File "/home/newuser/spark/python/pyspark/rdd.py", line 797, in func
yield reduce(f, iterator, initial)
File "<ipython-input-46-9557bb70b499>", line 1, in <lambda>
TypeError: 'int' object has no attribute '__getitem__'
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:166)
at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:300)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:88)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
... 1 more
Apache Spark를 처음 사용하며이 문제를 해결하는 방법은 무엇입니까?
가장 간단한 해결책은
>>> newdispokey1.values().sum()
750558
문제는 reduce메서드 에 대한 매개 변수 유형-감속기 유형에 있습니다. 하나는 이전 결과이거나 첫 번째 요소이고 두 번째는 새 요소입니다. 따라서 다른 요소처럼 보이는 요소를 반환해야합니다. 한 쌍을 반환해야합니다.
>>> newdispokey1.reduce(lambda x, y: ('', x[1] + y[1]))
('', 750558)
또는 더 정교하게 변경하려는 경우 :
>>> newdispokey1.map(lambda x: x[1]).reduce(lambda x, y: x + y)
750558
첫 번째 솔루션과 동일하지만 읽기가 어렵습니다.
이 기사는 인터넷에서 수집됩니다. 재 인쇄 할 때 출처를 알려주십시오.
침해가 발생한 경우 연락 주시기 바랍니다[email protected] 삭제
몇 마디 만하겠습니다