我有一个需求,需要在Spark集群的多个节点上使用Apache Spark运行Windows批处理文件。
那么,是否可以使用Apache Spark的管道概念来实现相同的操作呢?
我之前在Ubuntu机器上使用Spark的管道功能运行过shell文件,下面的代码可以成功运行:
data = ["hi","hello","how","are","you"]
distScript = "/home/aawasthi/echo.sh"
distScriptName = "echo.sh"
sc.addFile(distScript)
RDDdata = sc.parallelize(data)
print RDDdata.pipe(SparkFiles.get(distScriptName)).collect()
我尝试着将同样的代码应用于在安装有Spark(1.6预构建版本,适用于Hadoop 2.6)的Windows机器上运行Windows批处理文件。但是在sc.addFile
步骤时出现错误。以下是代码:
batchFile = "D:/spark-1.6.2-bin-hadoop2.6/data/OpenCV/runOpenCv"
batchFileName = "runOpenCv"
sc.addFile(batchFile)
Spark抛出的错误如下:
Py4JJavaError Traceback (most recent call last)
<ipython-input-11-9e13c265cbae> in <module>()
----> 1 sc.addFile(batchFile)`
Py4JJavaError: An error occurred while calling o160.addFile.
: java.io.FileNotFoundException: Added file D:/spark-1.6.2-bin-hadoop2.6/data/OpenCV/runOpenCv does not exist.
at org.apache.spark.SparkContext.addFile(SparkContext.scala:1364)
at org.apache.spark.SparkContext.addFile(SparkContext.scala:1340)
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:231)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
at py4j.Gateway.invoke(Gateway.java:259)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:209)
at java.lang.Thread.run(Thread.java:745)
尽管批处理文件存在于给定的位置。 更新:
在
batchFile
和batchFileName
中添加了扩展名.bat
,并在文件路径开头添加了file:///
。修改后的代码如下:from pyspark import SparkFiles
from pyspark import SparkContext
sc
batchFile = "file:///D:/spark-1.6.2-bin-hadoop2.6/data/OpenCV/runOpenCv.bat"
batchFileName = "runOpenCv.bat"
sc.addFile(batchFile)
RDDdata = sc.parallelize(["hi","hello"])
print SparkFiles.get("runOpenCv.bat")
print RDDdata.pipe(SparkFiles.get(batchFileName)).collect()
现在在
addFile
步骤中不再报错,而print SparkFiles.get("runOpenCv.bat")
会打印路径C:\Users\abhilash.awasthi\AppData\Local\Temp\spark-c0f383b1-8365-4840-bd0f-e7eb46cc6794\userFiles-69051066-f18c-45dc-9610-59cbde0d77fe\runOpenCv.bat
所以文件已添加。但在代码的最后一步中,它抛出以下错误:
Py4JJavaError Traceback (most recent call last)
<ipython-input-6-bf2b8aea3ef0> in <module>()
----> 1 print RDDdata.pipe(SparkFiles.get(batchFileName)).collect()
D:\spark-1.6.2-bin-hadoop2.6\python\pyspark\rdd.pyc in collect(self)
769 """
770 with SCCallSiteSync(self.context) as css:
--> 771 port = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
772 return list(_load_from_socket(port, self._jrdd_deserializer))
773
D:\spark-1.6.2-bin-hadoop2.6\python\lib\py4j-0.9-src.zip\py4j\java_gateway.py in __call__(self, *args)
811 answer = self.gateway_client.send_command(command)
812 return_value = get_return_value(
--> 813 answer, self.gateway_client, self.target_id, self.name)
814
815 for temp_arg in temp_args:
D:\spark-1.6.2-bin-hadoop2.6\python\pyspark\sql\utils.pyc in deco(*a, **kw)
43 def deco(*a, **kw):
44 try:
---> 45 return f(*a, **kw)
46 except py4j.protocol.Py4JJavaError as e:
47 s = e.java_exception.toString()
D:\spark-1.6.2-bin-hadoop2.6\python\lib\py4j-0.9-src.zip\py4j\protocol.py in get_return_value(answer, gateway_client, target_id, name)
306 raise Py4JJavaError(
307 "An error occurred while calling {0}{1}{2}.\n".
--> 308 format(target_id, ".", name), value)
309 else:
310 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 0.0 failed 1 times, most recent failure: Lost task 1.0 in stage 0.0 (TID 1, localhost): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "D:\spark-1.6.2-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\worker.py", line 111, in main
File "D:\spark-1.6.2-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\worker.py", line 106, in process
File "D:\spark-1.6.2-bin-hadoop2.6\python\pyspark\rdd.py", line 317, in func
return f(iterator)
File "D:\spark-1.6.2-bin-hadoop2.6\python\pyspark\rdd.py", line 715, in func
shlex.split(command), env=env, stdin=PIPE, stdout=PIPE)
File "C:\Anaconda2\lib\subprocess.py", line 710, in __init__
errread, errwrite)
File "C:\Anaconda2\lib\subprocess.py", line 958, in _execute_child
startupinfo)
WindowsError: [Error 2] The system cannot find the file specified
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:166)
at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:227)
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$$failJobAndIndependentStages(DAGScheduler.scala:1431)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1419)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1418)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1418)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:799)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1640)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1599)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1588)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:620)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1832)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1845)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1858)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1929)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:927)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
at org.apache.spark.rdd.RDD.collect(RDD.scala:926)
at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:405)
at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
at py4j.Gateway.invoke(Gateway.java:259)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:209)
at java.lang.Thread.run(Thread.java:745)
Caused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "D:\spark-1.6.2-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\worker.py", line 111, in main
File "D:\spark-1.6.2-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\worker.py", line 106, in process
File "D:\spark-1.6.2-bin-hadoop2.6\python\pyspark\rdd.py", line 317, in func
return f(iterator)
File "D:\spark-1.6.2-bin-hadoop2.6\python\pyspark\rdd.py", line 715, in func
shlex.split(command), env=env, stdin=PIPE, stdout=PIPE)
File "C:\Anaconda2\lib\subprocess.py", line 710, in __init__
errread, errwrite)
File "C:\Anaconda2\lib\subprocess.py", line 958, in _execute_child
startupinfo)
WindowsError: [Error 2] The system cannot find the file specified
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:166)
at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:227)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
... 1 more
.cmd
或.bat
。您尝试过将其包含吗? - MC NDbatchFile
和batchFileName
中添加了.bat
之后,我不再收到文件不存在的错误。但是,我得到了更新答案中显示的不同错误。 - Abhilash Awasthi