PySpark Error: Input path does not exist - apache-spark

Question

I am trying to perform data transformations using PySpark.
I have a text file with data(CHANGES.txt)
I am able to execute the command:
RDDread = sc.textFile("file:///home/test/desktop/CHANGES.txt")
but when I run:
RDDread.first()
then I get the error:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/srv/spark/python/pyspark/rdd.py", line 1328, in first
rs = self.take(1)
File "/srv/spark/python/pyspark/rdd.py", line 1280, in take
totalParts = self.getNumPartitions()
File "/srv/spark/python/pyspark/rdd.py", line 356, in getNumPartitions
return self._jrdd.partitions().size()
File "/srv/spark/python/lib/py4j-0.10.3-src.zip/py4j/java_gateway.py", line 1133, in __call__
File "/srv/spark/python/pyspark/sql/utils.py", line 63, in deco
return f(*a, **kw)
File "/srv/spark/python/lib/py4j-0.10.3-src.zip/py4j/protocol.py", line 319, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o256.partitions.
: org.apache.hadoop.mapred.InvalidInputException: Input path does not exist: file:/home/test/desktop/CHANGES.txt
at org.apache.hadoop.mapred.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:287)
at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:229)
at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:315)
at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:199)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:248)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:246)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:246)
at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:248)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:246)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:246)
at org.apache.spark.api.java.JavaRDDLike$class.partitions(JavaRDDLike.scala:60)
at org.apache.spark.api.java.AbstractJavaRDDLike.partitions(JavaRDDLike.scala:45)
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:237)
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:745)
It seems that is mentions the file path does not exist. How can I resolve this. I have python, Java, and spark installed on my linux machine.

Answer 1

If your running in a clustered mode you need to copy the file across all the nodes of same shared file system. Then spark reads that file otherwise you should use HDFS
I copied txt file into HDFS and spark takes file from HDFS.
I copied txt file on the shared filesystem of all nodes then spark read that file.
Both worked for me