Spark和Python试图使用gensim解析维基百科

Question

基于我之前的问题Spark和Python使用自定义文件格式/生成器作为RDD的输入，我认为我应该能够通过sc.textFile（）解析基本上任何输入，然后使用我的或来自一些库的自定义函数。

现在我特别尝试使用gensim框架解析维基百科转储。我已经在我的主节点和所有工作节点上安装了gensim，现在我想使用gensim内置函数来解析维基百科页面，灵感来自MAP（PySpark）返回的元组的问题列表（或迭代器）。

我的代码如下：

import sys
import gensim
from pyspark import SparkContext

if __name__ == "__main__":
    if len(sys.argv) != 2:
        print >> sys.stderr, "Usage: wordcount <file>"
        exit(-1)
    sc = SparkContext(appName="Process wiki - distributed RDD")
    distData = sc.textFile(sys.argv[1])
    #take 10 only to see how the output would look like
    processed_data = distData.flatMap(gensim.corpora.wikicorpus.extract_pages).take(10)
    print processed_data
    sc.stop()

extract_pages的源代码可在https://github.com/piskvorky/gensim/blob/develop/gensim/corpora/wikicorpus.py根据我的经历，它似乎应该与Spark合作。

但不幸的是，当我运行代码时，我得到了以下错误日志：

14/10/05 13:21:11 WARN scheduler.TaskSetManager: Lost task 0.0 in stage 0.0 (TID 0, <ip address>.ec2.internal): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/root/spark/python/pyspark/worker.py", line 79, in main
serializer.dump_stream(func(split_index, iterator), outfile)
File "/root/spark/python/pyspark/serializers.py", line 196, in dump_stream
self.serializer.dump_stream(self._batched(iterator), stream)
File "/root/spark/python/pyspark/serializers.py", line 127, in dump_stream
for obj in iterator:
File "/root/spark/python/pyspark/serializers.py", line 185, in _batched
for item in iterator:
File "/root/spark/python/pyspark/rdd.py", line 1148, in takeUpToNumLeft
yield next(iterator)
File "/usr/lib64/python2.6/site-packages/gensim/corpora/wikicorpus.py", line 190, in extract_pages
elems = (elem for _, elem in iterparse(f, events=("end",)))
File "<string>", line 52, in __init__
IOError: [Errno 2] No such file or directory: u'<mediawiki xmlns="http://www.mediawiki.org/xml/export-0.9/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.mediawiki.org/xml/export-0.9/ http://www.mediawiki.org/xml/export-0.9.xsd" version="0.9" xml:lang="en">'
    org.apache.spark.api.python.PythonRDD$$anon$1.read(PythonRDD.scala:124)
    org.apache.spark.api.python.PythonRDD$$anon$1.<init>(PythonRDD.scala:154)
    org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:87)
    org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
    org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
    org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:62)
    org.apache.spark.scheduler.Task.run(Task.scala:54)
    org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:177)
    java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
    java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
    java.lang.Thread.run(Thread.java:745)

然后可能是Spark日志：

14/10/05 13:21:12 ERROR scheduler.TaskSetManager: Task 0 in stage 0.0 failed 4 times; aborting job
14/10/05 13:21:12 INFO scheduler.TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool 
14/10/05 13:21:12 INFO scheduler.TaskSchedulerImpl: Cancelling stage 0
14/10/05 13:21:12 INFO scheduler.DAGScheduler: Failed to run runJob at PythonRDD.scala:296

和

at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1185)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1174)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1173)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1173)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:688)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:688)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:688)
at org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1391)
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
at akka.actor.ActorCell.invoke(ActorCell.scala:456)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
at akka.dispatch.Mailbox.run(Mailbox.scala:219)
at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)

我在没有Spark的情况下成功地尝试了这一点，所以问题应该是Spark和gensim的结合，但我不太理解我遇到的错误。在gensimwikicorpus.py.的第190行中，我没有看到任何文件在读取

编辑：

添加了更多来自Spark:的日志

第2版：

gensim使用了来自xml.etree.cElementTree import iterparse的文档，这可能会导致问题。它实际上需要文件名或包含xml数据的文件。RDD是否可以被视为包含xml数据的文件？

Answer 1

我通常在Scala中使用Spark。然而，以下是我的想法：

当您通过sc.textFile加载一个文件时，它是分布在您的sparkWorkers中的某种行迭代器。我认为，考虑到维基百科的xml格式，其中一行不一定对应于可解析的xml项，因此您会遇到这个问题。

即：

 Line 1 :  <item>
 Line 2 :  <title> blabla </title> <subitem>
 Line 3 : </subItem>
 Line 4 : </item>

如果您尝试单独解析每一行，它会抛出与您得到的异常类似的异常。

我通常不得不处理维基百科转储，所以我要做的第一件事就是把它转换成一个"可编辑版本"，Spark很容易消化它。即：每个条目一行。一旦你有了它，你就可以很容易地把它激发出来，并进行各种处理。转换不需要太多资源

看看ReadableWiki：https://github.com/idio/wiki2vec