pyspark - 使用 pySpark reduceByKey 的词袋

Question

我正在尝试使用 pySpark 执行一些文本挖掘任务。我是 Spark 新手，我一直在关注这个示例 http://mccarroll.net/blog/pyspark2/index.html为我的数据构建词袋。

最初我的数据看起来像这样

df.show(5)
+------------+---------+----------------+--------------------+
|Title       |Month    |     Author     |            Document|
+------------+---------+----------------+--------------------+
|      a     |      Jan|     John       |This is a document  |
|      b     |      Feb|     Mary       |A book by Mary      |
|      c     |      Mar|     Luke       |Newspaper article   |
+------------+---------+----------------+--------------------+

到目前为止，我已经提取了每个文档的条款

bow0 = df.rdd\
    .map( lambda x: x.Document.replace(',',' ').replace('.',' ').replace('-',' ').lower())\
    .flatMap(lambda x: x.split())\
    .map(lambda x: (x, 1))

这给了我

[('This', 1),
 ('is', 1),
 ('a', 1),
 ('document', 1)]

但是当我尝试使用reduceByKey计算频率并尝试查看结果时

bow0.reduceByKey(lambda x,y:x+y).take(50)

我收到此错误:

---------------------------------------------------------------------------
Py4JJavaError                             Traceback (most recent call last)
<ipython-input-53-966f90775397> in <module>()
----> 1 bow0.reduceByKey(lambda x,y:x+y).take(50)

/usr/local/spark/python/pyspark/rdd.py in take(self, num)
   1341 
   1342             p = range(partsScanned, min(partsScanned + numPartsToTry, totalParts))
-> 1343             res = self.context.runJob(self, takeUpToNumLeft, p)
   1344 
   1345             items += res

/usr/local/spark/python/pyspark/context.py in runJob(self, rdd, partitionFunc, partitions, allowLocal)
    990         # SparkContext#runJob.
    991         mappedRDD = rdd.mapPartitions(partitionFunc)
--> 992         port = self._jvm.PythonRDD.runJob(self._jsc.sc(), mappedRDD._jrdd, partitions)
    993         return list(_load_from_socket(port, mappedRDD._jrdd_deserializer))
    994 

/usr/local/spark/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py 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:

/usr/local/spark/python/pyspark/sql/utils.py in deco(*a, **kw)
     61     def deco(*a, **kw):
     62         try:
---> 63             return f(*a, **kw)
     64         except py4j.protocol.Py4JJavaError as e:
     65             s = e.java_exception.toString()

/usr/local/spark/python/lib/py4j-0.10.4-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
    317                 raise Py4JJavaError(
    318                     "An error occurred while calling {0}{1}{2}.\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.runJob.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 1 in stage 31.0 failed 4 times, most recent failure: Lost task 1.3 in stage 31.0 (TID 84, 9.242.64.15, executor 7): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/worker.py", line 177, in main
    process()
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/worker.py", line 172, in process
    serializer.dump_stream(func(split_index, iterator), outfile)
  File "/usr/local/spark/python/pyspark/rdd.py", line 2423, in pipeline_func
    return func(split, prev_func(split, iterator))
  File "/usr/local/spark/python/pyspark/rdd.py", line 2423, in pipeline_func
    return func(split, prev_func(split, iterator))
  File "/usr/local/spark/python/pyspark/rdd.py", line 346, in func
    return f(iterator)
  File "/usr/local/spark/python/pyspark/rdd.py", line 1842, in combineLocally
    merger.mergeValues(iterator)
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/shuffle.py", line 236, in mergeValues
    for k, v in iterator:
  File "<ipython-input-48-5c0753c6b152>", line 1, in <lambda>
AttributeError: 'NoneType' object has no attribute 'replace'

    at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:193)
    at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:234)
    at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:152)
    at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:63)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
    at org.apache.spark.api.python.PairwiseRDD.compute(PythonRDD.scala:404)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
    at org.apache.spark.scheduler.Task.run(Task.scala:108)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:338)
    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$$failJobAndIndependentStages(DAGScheduler.scala:1517)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1505)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1504)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1504)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
    at scala.Option.foreach(Option.scala:257)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:814)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1732)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1687)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1676)
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:630)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2029)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2050)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2069)
    at org.apache.spark.api.python.PythonRDD$.runJob(PythonRDD.scala:455)
    at org.apache.spark.api.python.PythonRDD.runJob(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: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:748)
Caused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last):
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/worker.py", line 177, in main
    process()
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/worker.py", line 172, in process
    serializer.dump_stream(func(split_index, iterator), outfile)
  File "/usr/local/spark/python/pyspark/rdd.py", line 2423, in pipeline_func
    return func(split, prev_func(split, iterator))
  File "/usr/local/spark/python/pyspark/rdd.py", line 2423, in pipeline_func
    return func(split, prev_func(split, iterator))
  File "/usr/local/spark/python/pyspark/rdd.py", line 346, in func
    return f(iterator)
  File "/usr/local/spark/python/pyspark/rdd.py", line 1842, in combineLocally
    merger.mergeValues(iterator)
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/shuffle.py", line 236, in mergeValues
    for k, v in iterator:
  File "<ipython-input-48-5c0753c6b152>", line 1, in <lambda>
AttributeError: 'NoneType' object has no attribute 'replace'

    at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:193)
    at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:234)
    at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:152)
    at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:63)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
    at org.apache.spark.api.python.PairwiseRDD.compute(PythonRDD.scala:404)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
    at org.apache.spark.scheduler.Task.run(Task.scala:108)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:338)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    ... 1 more

Answer 1

扩展my comment ，您收到的错误是由于您的文档列中存在 null 值造成的。这是一个小例子来演示:

data = [
    ['a', 'Jan', 'John', 'This is a document'],
    ['b', 'Feb', 'Mary', 'A book by Mary'],
    ['c', 'Mar', 'Luke', 'Newspaper article'],
    ['d', 'Apr', 'Mark', None]
]
columns = ['Title', 'Month', 'Author', 'Document']
df = spark.createDataFrame(data, columns)
df.show()
#+-----+-----+------+------------------+
#|Title|Month|Author|          Document|
#+-----+-----+------+------------------+
#|    a|  Jan|  John|This is a document|
#|    b|  Feb|  Mary|    A book by Mary|
#|    c|  Mar|  Luke| Newspaper article|
#|    d|  Apr|  Mark|              null|
#+-----+-----+------+------------------+

对于最后一行，Document 列中的值为 null。当您按照问题计算 bow0 时，当 map 函数对该行进行操作时，它会尝试调用 x.Document.replace 其中 x 是无。这会导致 AttributeError: 'NoneType' object has no attribute 'replace'。

解决这个问题的一种方法是在调用 map 之前过滤掉坏值:

bow0 = df.rdd\
    .filter(lambda x: x.Document)\
    .map( lambda x: x.Document.replace(',',' ').replace('.',' ').replace('-',' ').lower())\
    .flatMap(lambda x: x.split())\
    .map(lambda x: (x, 1))
bow0.reduceByKey(lambda x,y:x+y).take(50)
#[(u'a', 2),
# (u'this', 1),
# (u'is', 1),
# (u'newspaper', 1),
# (u'article', 1),
# (u'by', 1),
# (u'book', 1),
# (u'mary', 1),
# (u'document', 1)]

或者您可以在 map 函数内构建对 None 条件的检查。一般来说，让您的 map 函数对错误输入具有鲁棒性是一种很好的做法。

<小时/>

顺便说一句，您可以使用 DataFrame API 函数执行相同的操作。在这种情况下:

from pyspark.sql.functions import explode, split, regexp_replace, col, lower
df.select(explode(split(regexp_replace("Document", "[,.-]", " "), "\s+")).alias("word"))\
    .groupby(lower(col("word")).alias("lower"))\
    .count()\
    .show()
#+---------+-----+
#|    lower|count|
#+---------+-----+
#| document|    1|
#|       by|    1|
#|newspaper|    1|
#|  article|    1|
#|     mary|    1|
#|       is|    1|
#|        a|    2|
#|     this|    1|
#|     book|    1|
#+---------+-----+