python中的火花：通过使用numpy.fromfile加载二进制数据来创建rdd
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【中文标题】python中的火花：通过使用numpy.fromfile加载二进制数据来创建rdd【英文标题】：spark in python: creating an rdd by loading binary data with numpy.fromfile 【发布时间】：2015-10-09 11:53:45 【问题描述】：spark python api 目前对加载大型二进制数据文件的支持有限，因此我尝试获取 numpy.fromfile 来帮助我。
我首先得到了一个我想要加载的文件名列表，例如：
In [9] filenames
Out[9]:
['A0000.dat',
'A0001.dat',
'A0002.dat',
'A0003.dat',
'A0004.dat']
我可以通过粗略的迭代联合加载这些文件而不会出现问题，
for i in range(len(filenames)):
rdd = sc.parallelize([np.fromfile(filenames[i], dtype="int16", count=-1, sep='')])
if i==0:
allRdd = rdd;
else:
allRdd = allRdd.union(rdd);
一次将所有文件加载到多个节点中会很棒。我尝试按如下方式执行此操作，
filenameRdd = sc.parallelize(filenames)
allRdd2 = filenameRdd.map(lambda x: np.fromfile(x, dtype="int16", count=-1, sep=''))
但这并没有奏效。我找回了一些 RDD
In [20]: allRdd2
Out[20]: PythonRDD[13] at RDD at PythonRDD.scala:43
如果我试图操纵它，它会不断抛出错误。
我的方法理论上可行吗？ 如果没有，有什么好的选择？
更新：错误消息提示节点找不到原始文件（如下）。当我将所有文件复制到我的主目录时，这种方法确实非常有效。
这里是错误信息的详细信息。
例如，collect() 适用于第一种方法，
allRdd.collect()
[array([87, 52, 82, ..., 96, 25, 20], dtype=int16),
array([20, 72, 13, ..., 53, 41, 99], dtype=int16),
array([97, 63, 17, ..., 38, 89, 13], dtype=int16),
array([88, 66, 97, ..., 22, 93, 93], dtype=int16),
array([99, 14, 42, ..., 33, 34, 20], dtype=int16)]
但不是用第二种方法，
allRdd2.collect()
15/10/09 08:21:58 ERROR Executor: Exception in task 12.0 in stage 4.0 (TID 113)
org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/usr/local/spark-current/python/pyspark/worker.py", line 101, in main
process()
File "/usr/local/spark-current/python/pyspark/worker.py", line 96, in process
serializer.dump_stream(func(split_index, iterator), outfile)
File "/usr/local/spark-current/python/pyspark/serializers.py", line 236, in dump_stream
vs = list(itertools.islice(iterator, batch))
File "<ipython-input-6-58733c66cd22>", line 3, in <lambda>
IOError: [Errno 2] No such file or directory: 'A0003.dat'
at org.apache.spark.api.python.PythonRDD$$anon$1.read(PythonRDD.scala:135)
at org.apache.spark.api.python.PythonRDD$$anon$1.<init>(PythonRDD.scala:176)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:94)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
at org.apache.spark.scheduler.Task.run(Task.scala:64)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
15/10/09 08:21:58 ERROR Executor: Exception in task 9.0 in stage 4.0 (TID 110)
org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/usr/local/spark-current/python/pyspark/worker.py", line 101, in main
process()
File "/usr/local/spark-current/python/pyspark/worker.py", line 96, in process
serializer.dump_stream(func(split_index, iterator), outfile)
File "/usr/local/spark-current/python/pyspark/serializers.py", line 236, in dump_stream
vs = list(itertools.islice(iterator, batch))
File "<ipython-input-6-58733c66cd22>", line 3, in <lambda>
IOError: [Errno 2] No such file or directory: 'A0002.dat'
at org.apache.spark.api.python.PythonRDD$$anon$1.read(PythonRDD.scala:135)
at org.apache.spark.api.python.PythonRDD$$anon$1.<init>(PythonRDD.scala:176)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:94)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
at org.apache.spark.scheduler.Task.run(Task.scala:64)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
15/10/09 08:21:58 ERROR Executor: Exception in task 6.0 in stage 4.0 (TID 107)
org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/usr/local/spark-current/python/pyspark/worker.py", line 101, in main
process()
File "/usr/local/spark-current/python/pyspark/worker.py", line 96, in process
serializer.dump_stream(func(split_index, iterator), outfile)
File "/usr/local/spark-current/python/pyspark/serializers.py", line 236, in dump_stream
vs = list(itertools.islice(iterator, batch))
File "<ipython-input-6-58733c66cd22>", line 3, in <lambda>
IOError: [Errno 2] No such file or directory: 'A0001.dat'
at org.apache.spark.api.python.PythonRDD$$anon$1.read(PythonRDD.scala:135)
at org.apache.spark.api.python.PythonRDD$$anon$1.<init>(PythonRDD.scala:176)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:94)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
at org.apache.spark.scheduler.Task.run(Task.scala:64)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
15/10/09 08:21:58 ERROR TaskSetManager: Task 12 in stage 4.0 failed 1 times; aborting job
---------------------------------------------------------------------------
Py4JJavaError Traceback (most recent call last)
<ipython-input-11-16f16ee2a9b8> in <module>()
----> 1 allRdd2.collect()
/usr/local/spark-current/python/pyspark/rdd.py in collect(self)
711 """
712 with SCCallSiteSync(self.context) as css:
--> 713 port = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
714 return list(_load_from_socket(port, self._jrdd_deserializer))
715
/usr/local/spark-current/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:
/usr/local/spark-current/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 012.\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 12 in stage 4.0 failed 1 times, most recent failure: Lost task 12.0 in stage 4.0 (TID 113, localhost): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/usr/local/spark-current/python/pyspark/worker.py", line 101, in main
process()
File "/usr/local/spark-current/python/pyspark/worker.py", line 96, in process
serializer.dump_stream(func(split_index, iterator), outfile)
File "/usr/local/spark-current/python/pyspark/serializers.py", line 236, in dump_stream
vs = list(itertools.islice(iterator, batch))
File "<ipython-input-6-58733c66cd22>", line 3, in <lambda>
IOError: [Errno 2] No such file or directory: 'A0003.dat'
at org.apache.spark.api.python.PythonRDD$$anon$1.read(PythonRDD.scala:135)
at org.apache.spark.api.python.PythonRDD$$anon$1.<init>(PythonRDD.scala:176)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:94)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
at org.apache.spark.scheduler.Task.run(Task.scala:64)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1204)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1193)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1192)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1192)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:693)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1393)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1354)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
【问题讨论】：
【参考方案1】：解决方案非常简单：当您提供文件名的完整路径时，此方法有效。
fullfilenames = [fullpath + '/' + fname for fname in filenames]
filenameRdd = sc.parallelize(fullfilenames)
allRdd2 = filenameRdd.map(lambda x: np.fromfile(x, dtype="int16", count=-1, sep=''))
【讨论】：
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