title: What does the below error mean in PySpark?
body: <p>I am using this tutorial: <a href="http://spark.apache.org/docs/latest/quick-start.html" rel="nofollow">http://spark.apache.org/docs/latest/quick-start.html</a> to no avail.</p>
  
  <p>I have tried the following:</p>
  
  <pre><code>textFile=sc.textFile("README.md")
  textFile.count()
  </code></pre>
  
  <p>Below is the output that I receive instead of the desired result, 126.</p>
  
  <pre><code>&gt; textFile=sc.textFile("README.md")
  15/11/18 13:19:49 INFO MemoryStore: ensureFreeSpace(182712) called with curMem=2
  54076, maxMem=556038881
  15/11/18 13:19:49 INFO MemoryStore: Block broadcast_2 stored as values in memory
   (estimated size 178.4 KB, free 529.9 MB)
  15/11/18 13:19:49 INFO MemoryStore: ensureFreeSpace(17179) called with curMem=43
  6788, maxMem=556038881
  15/11/18 13:19:49 INFO MemoryStore: Block broadcast_2_piece0 stored as bytes in
  memory (estimated size 16.8 KB, free 529.8 MB)
  15/11/18 13:19:49 INFO BlockManagerInfo: Added broadcast_2_piece0 in memory on l
  ocalhost:61916 (size: 16.8 KB, free: 530.2 MB)
  15/11/18 13:19:49 INFO SparkContext: Created broadcast 2 from textFile at null:-
  2
  
  &gt; textFile.count()
  
  Traceback (most recent call last):
    File "&lt;stdin&gt;", line 1, in &lt;module&gt;
    File "C:\Users\Administrator\Downloads\spark-1.5.2-bin-hadoop2.4\spark-1.5.2-b
  in-hadoop2.4\spark-1.5.2-bin-hadoop2.4\python\pyspark\rdd.py", line 1006, in cou
  nt
      return self.mapPartitions(lambda i: [sum(1 for _ in i)]).sum()
    File "C:\Users\Administrator\Downloads\spark-1.5.2-bin-hadoop2.4\spark-1.5.2-b
  in-hadoop2.4\spark-1.5.2-bin-hadoop2.4\python\pyspark\rdd.py", line 997, in sum
      return self.mapPartitions(lambda x: [sum(x)]).fold(0, operator.add)
    File "C:\Users\Administrator\Downloads\spark-1.5.2-bin-hadoop2.4\spark-1.5.2-b
  in-hadoop2.4\spark-1.5.2-bin-hadoop2.4\python\pyspark\rdd.py", line 871, in fold
  
      vals = self.mapPartitions(func).collect()
    File "C:\Users\Administrator\Downloads\spark-1.5.2-bin-hadoop2.4\spark-1.5.2-b
  in-hadoop2.4\spark-1.5.2-bin-hadoop2.4\python\pyspark\rdd.py", line 773, in coll
  ect
      port = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
    File "C:\Users\Administrator\Downloads\spark-1.5.2-bin-hadoop2.4\spark-1.5.2-b
  in-hadoop2.4\spark-1.5.2-bin-hadoop2.4\python\lib\py4j-0.8.2.1-src.zip\py4j\java
  _gateway.py", line 538, in __call__
    File "C:\Users\Administrator\Downloads\spark-1.5.2-bin-hadoop2.4\spark-1.5.2-b
  in-hadoop2.4\spark-1.5.2-bin-hadoop2.4\python\pyspark\sql\utils.py", line 36, in
   deco
      return f(*a, **kw)
    File "C:\Users\Administrator\Downloads\spark-1.5.2-bin-hadoop2.4\spark-1.5.2-b
  in-hadoop2.4\spark-1.5.2-bin-hadoop2.4\python\lib\py4j-0.8.2.1-src.zip\py4j\prot
  ocol.py", line 300, in get_return_value
  py4j.protocol.Py4JJavaError: An error occurred while calling z:org.apache.spark.
  api.python.PythonRDD.collectAndServe.
  : org.apache.hadoop.mapred.InvalidInputException: Input path does not exist: fil
  e:/C:/Users/Administrator/Downloads/spark-1.5.2-bin-hadoop2.4/spark-1.5.2-bin-ha
  doop2.4/spark-1.5.2-bin-hadoop2.4/bin/README.md
          at org.apache.hadoop.mapred.FileInputFormat.singleThreadedListStatus(Fil
  eInputFormat.java:285)
          at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.j
  ava:228)
          at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.ja
  va:304)
          at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:207)
          at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
          at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
          at scala.Option.getOrElse(Option.scala:120)
          at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
          at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.
  scala:35)
          at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
          at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
          at scala.Option.getOrElse(Option.scala:120)
          at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
          at org.apache.spark.api.python.PythonRDD.getPartitions(PythonRDD.scala:5
  8)
          at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
          at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
          at scala.Option.getOrElse(Option.scala:120)
          at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
          at org.apache.spark.SparkContext.runJob(SparkContext.scala:1921)
          at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:909)
          at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.s
  cala:147)
          at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.s
  cala:108)
          at org.apache.spark.rdd.RDD.withScope(RDD.scala:310)
          at org.apache.spark.rdd.RDD.collect(RDD.scala:908)
          at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scal
  a:405)
          at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala
  )
          at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
          at sun.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)
          at sun.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
          at java.lang.reflect.Method.invoke(Unknown Source)
          at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
          at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379)
          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:207)
          at java.lang.Thread.run(Unknown Source)
  </code></pre>