我从以下站点下载了一个文本文件：http://snap.stanford.edu/data/web-Amazon-links.html，目的是在Pyspark中进行一些文本分析。
所以我设置了我的Spark上下文：
from pyspark import SparkConf, SparkContext
conf = SparkConf().setAppName('app')
sc = SparkContext(conf=conf)
from pyspark.sql import SQLContext
我抓起文件：
Data1 =sc.textFile('/home/john/Downloads/Software.txt.gz').map(lambda line: line.split(','))
数据如下：
[['product/productId: B000068VBQ'],
['product/title: Fisher-Price Rescue Heroes: Lava Landslide'],
['product/price: 8.88'],
['review/userId: unknown'],
['review/profileName: unknown'],
['review/helpfulness: 11/11'],
['review/score: 2.0'],
['review/time: 1042070400'],
['review/summary: Requires too much coordination'],
['review/text: I bought this software for my 5 year old. He has a couple of the other RH software games and he likes them a lot. This game',
' however'
但是我尝试了groupByKey：
sorted(Data1.groupByKey().mapValues(list).collect())
我收到此错误：
Py4JJavaError Traceback (most recent call last)
<ipython-input-15-a3c92709547a> in <module>
----> 1 sorted(Data1.groupByKey().mapValues(list).collect())
~/anaconda3/lib/python3.7/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
~/anaconda3/lib/python3.7/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:
~/anaconda3/lib/python3.7/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 5.0 failed 1 times, most recent failure: Lost task 0.0 in stage 5.0 (TID 4, localhost, executor driver): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/home/john/anaconda3/lib/python3.7/site-packages/pyspark/python/lib/pyspark.zip/pyspark/worker.py", line 372, in main
process()
File "/home/john/anaconda3/lib/python3.7/site-packages/pyspark/python/lib/pyspark.zip/pyspark/worker.py", line 367, in process
serializer.dump_stream(func(split_index, iterator), outfile)
File "/home/john/anaconda3/lib/python3.7/site-packages/pyspark/rdd.py", line 2499, in pipeline_func
return func(split, prev_func(split, iterator))
File "/home/john/anaconda3/lib/python3.7/site-packages/pyspark/rdd.py", line 2499, in pipeline_func
return func(split, prev_func(split, iterator))
File "/home/john/anaconda3/lib/python3.7/site-packages/pyspark/rdd.py", line 352, in func
return f(iterator)
File "/home/john/anaconda3/lib/python3.7/site-packages/pyspark/rdd.py", line 1945, in combine
merger.mergeValues(iterator)
File "/home/john/anaconda3/lib/python3.7/site-packages/pyspark/python/lib/pyspark.zip/pyspark/shuffle.py", line 238, in mergeValues
for k, v in iterator:
ValueError: not enough values to unpack (expected 2, got 1)
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$10.apply(Executor.scala:402)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$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$$failJobAndIndependentStages(DAGScheduler.scala:1887)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1875)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1874)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1874)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:926)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2108)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2057)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2046)
at org.apache.spark.util.EventLoop$$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 "/home/john/anaconda3/lib/python3.7/site-packages/pyspark/python/lib/pyspark.zip/pyspark/worker.py", line 372, in main
process()
File "/home/john/anaconda3/lib/python3.7/site-packages/pyspark/python/lib/pyspark.zip/pyspark/worker.py", line 367, in process
serializer.dump_stream(func(split_index, iterator), outfile)
File "/home/john/anaconda3/lib/python3.7/site-packages/pyspark/rdd.py", line 2499, in pipeline_func
return func(split, prev_func(split, iterator))
File "/home/john/anaconda3/lib/python3.7/site-packages/pyspark/rdd.py", line 2499, in pipeline_func
return func(split, prev_func(split, iterator))
File "/home/john/anaconda3/lib/python3.7/site-packages/pyspark/rdd.py", line 352, in func
return f(iterator)
File "/home/john/anaconda3/lib/python3.7/site-packages/pyspark/rdd.py", line 1945, in combine
merger.mergeValues(iterator)
File "/home/john/anaconda3/lib/python3.7/site-packages/pyspark/python/lib/pyspark.zip/pyspark/shuffle.py", line 238, in mergeValues
for k, v in iterator:
ValueError: not enough values to unpack (expected 2, got 1)
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$10.apply(Executor.scala:402)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more
答案 0 :(得分：1)
问题出在您的数据和使用的地图上。
groupByKey的原理是使用键和值按键分组，并对值数据进行一些汇总。
但是在RDD中，您没有key --> value数据，只是列表列表...这就是导致此错误的原因。
该列表是引起错误消息的1参数。
我不确定您的数据以及您想要实现的目标，但是我认为您可以执行以下操作：
Data1 =sc.textFile('/home/john/Downloads/Software.txt.gz').flatMap(lambda line: line.split("', '"))
Data2 = Data1.map(lambda line : line.split(':')).filter(lambda x : len(x)==2)
sorted(Data2.groupByKey().mapValues(set).collect())