title: Running a Windows Batch File through Piping in Apache Spark
body: <p>I have a requirement in which I have to run a Windows batch file using Apache Spark on multiple nodes of the Spark cluster.</p>
  
  <p>So is it possible to do the same using Piping concept of Apache Spark?</p>
  
  <p>I have before run a shell file using Piping in Spark on a Ubuntu machine. My below code doing the same runs fine:</p>
  
  <pre><code>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()
  </code></pre>
  
  <p>I tried to adapt the same code to run a Windows batch file on a Windows machine having Spark (1.6 prebuilt for Hadoop 2.6) installed. But it gives me the error on the <code>sc.addFile</code> step. Code is below:</p>
  
  <pre><code>batchFile = "D:/spark-1.6.2-bin-hadoop2.6/data/OpenCV/runOpenCv"
  batchFileName = "runOpenCv"
  sc.addFile(batchFile)
  </code></pre>
  
  <p>Error thrown by Spark is below:</p>
  
  <pre><code>Py4JJavaError                             Traceback (most recent call last)
  &lt;ipython-input-11-9e13c265cbae&gt; in &lt;module&gt;()
  ----&gt; 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)
  </code></pre>
  
  <p>Although the batch file exists at the given location.       </p>
  
  <p><strong>UPDATE</strong>:<br>
  Added <code>.bat</code> as extension in the <code>batchFile</code> &amp; <code>batchFileName</code> &amp; <code>file:///</code> in the starting of the file path. The modified code is:     </p>
  
  <pre><code>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()
  </code></pre>
  
  <p>Now it doesn't give error in the <code>addFile</code> step, and <code>print SparkFiles.get("runOpenCv.bat")</code> prints the path<br>
  <code>C:\Users\abhilash.awasthi\AppData\Local\Temp\spark-c0f383b1-8365-4840-bd0f-e7eb46cc6794\userFiles-69051066-f18c-45dc-9610-59cbde0d77fe\runOpenCv.bat</code><br>
  So file is added. But in the last step of the code it throws the below error:     </p>
  
  <pre><code>    Py4JJavaError                             Traceback (most recent call last)
  &lt;ipython-input-6-bf2b8aea3ef0&gt; in &lt;module&gt;()
  ----&gt; 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:
  --&gt; 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(
  --&gt; 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:
  ---&gt; 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".
  --&gt; 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$1.&lt;init&gt;(PythonRDD.scala:207)
      at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
      at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
      at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
      at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
      at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
      at org.apache.spark.scheduler.Task.run(Task.scala:89)
      at org.apache.spark.executor.Executor$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$1.&lt;init&gt;(PythonRDD.scala:207)
      at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
      at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
      at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
      at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
      at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
      at org.apache.spark.scheduler.Task.run(Task.scala:89)
      at org.apache.spark.executor.Executor$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
  </code></pre>