Pyspark reduce 将接受某些功能，而不是其他功能
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【中文标题】Pyspark reduce 将接受某些功能，而不是其他功能【英文标题】：Pyspark reduce will take in some functions, not others 【发布时间】：2016-11-02 18:55:30 【问题描述】：我在 jupyter notebook 上运行 Python 2.7。我有以下 pyspark RDD 对象：
file_rdd.collect()
[(u'Jane', 2),
(u'Jane', 1),
(u'Pete', 20),
(u'Tyler', 3),
(u'Duncan', 4),
(u'Yuki', 5),
(u'Duncan', 6),
(u'Duncan', 4),
(u'Duncan', 5)]
当我运行file_rdd.values().reduce(max) 时，我得到20。然而，当我运行file_rdd.values().reduce(sum) 时，我得到一个错误：
---------------------------------------------------------------------------
Py4JJavaError Traceback (most recent call last)
<ipython-input-61-eb9dd2b679d4> in <module>()
----> 1 file_rdd.values().reduce(sum)
/usr/local/Cellar/apache-spark/2.0.1/libexec/python/pyspark/rdd.pyc in reduce(self, f)
800 yield reduce(f, iterator, initial)
801
--> 802 vals = self.mapPartitions(func).collect()
803 if vals:
804 return reduce(f, vals)
/usr/local/Cellar/apache-spark/2.0.1/libexec/python/pyspark/rdd.pyc in collect(self)
774 """
775 with SCCallSiteSync(self.context) as css:
--> 776 port = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
777 return list(_load_from_socket(port, self._jrdd_deserializer))
778
/Users/zacharythomas/anaconda/lib/python2.7/site-packages/py4j/java_gateway.pyc 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:
/Users/zacharythomas/anaconda/lib/python2.7/site-packages/py4j/protocol.pyc in get_return_value(answer, gateway_client, target_id, name)
317 raise Py4JJavaError(
318 "An error occurred while calling 012.\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 1 in stage 30.0 failed 1 times, most recent failure: Lost task 1.0 in stage 30.0 (TID 59, localhost): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/usr/local/Cellar/apache-spark/2.0.1/libexec/python/lib/pyspark.zip/pyspark/worker.py", line 172, in main
process()
File "/usr/local/Cellar/apache-spark/2.0.1/libexec/python/lib/pyspark.zip/pyspark/worker.py", line 167, in process
serializer.dump_stream(func(split_index, iterator), outfile)
File "/usr/local/Cellar/apache-spark/2.0.1/libexec/python/lib/pyspark.zip/pyspark/serializers.py", line 263, in dump_stream
vs = list(itertools.islice(iterator, batch))
File "/usr/local/Cellar/apache-spark/2.0.1/libexec/python/pyspark/rdd.py", line 800, in func
yield reduce(f, iterator, initial)
TypeError: 'int' object is not iterable
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:193)
at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:234)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:152)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:63)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
at org.apache.spark.scheduler.Task.run(Task.scala:86)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
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$$failJobAndIndependentStages(DAGScheduler.scala:1454)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1442)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1441)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1441)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:811)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1667)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1622)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1611)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:632)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1890)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1903)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1916)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1930)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:912)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:358)
at org.apache.spark.rdd.RDD.collect(RDD.scala:911)
at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:453)
at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
at sun.reflect.GeneratedMethodAccessor42.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:237)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:280)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:214)
at java.lang.Thread.run(Thread.java:745)
Caused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/usr/local/Cellar/apache-spark/2.0.1/libexec/python/lib/pyspark.zip/pyspark/worker.py", line 172, in main
process()
File "/usr/local/Cellar/apache-spark/2.0.1/libexec/python/lib/pyspark.zip/pyspark/worker.py", line 167, in process
serializer.dump_stream(func(split_index, iterator), outfile)
File "/usr/local/Cellar/apache-spark/2.0.1/libexec/python/lib/pyspark.zip/pyspark/serializers.py", line 263, in dump_stream
vs = list(itertools.islice(iterator, batch))
File "/usr/local/Cellar/apache-spark/2.0.1/libexec/python/pyspark/rdd.py", line 800, in func
yield reduce(f, iterator, initial)
TypeError: 'int' object is not iterable
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:193)
at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:234)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:152)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:63)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
at org.apache.spark.scheduler.Task.run(Task.scala:86)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
... 1 more
这是为什么呢？当我运行file_rdd.values().reduce(lambda x, y: x+y) 时，我得到了想要的结果50。
有人向我建议这是因为 sum 需要一个可迭代对象，而 .reduce 需要二进制操作。这并不能解释为什么 max 有效，对吧？
【问题讨论】：
【参考方案1】：实际上，最后一段中的“某人”是完全正确的;-)
reduce 想要二进制操作，max 就是其中之一：
>>> max(1,2)
2
但sum 不是：
>>> sum(1,2)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: 'int' object is not iterable
通过查看operator module documentation，您可以找到add 二元运算符：
>>> from operator import add
>>> add(1,2)
3
>>> file_rdd.values().reduce(add)
50
【讨论】：
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