using Spark on my local machine - apache-spark

Question

I downloaded Spark and it looks like it works. Now I would like to try work with a txt file, for example, hamlet.txt. As I understand, to work in Spark I need to open spark-1.6.1/bin/pyspark
I put hamlet.txt in spark-1.6.1/bin/
Now I type:
raw_hamlet = sc.textFile("hamlet.txt")
raw_hamlet.take(5)
But the output is:
Traceback (most recent call last):
File "", line 1, in
File "/Applications/spark-1.6.1/python/pyspark/rdd.py", line 1267, in take
totalParts = self.getNumPartitions()
File "/Applications/spark-1.6.1/python/pyspark/rdd.py", line 356, in getNumPartitions
return self._jrdd.partitions().size()
File "/Applications/spark-1.6.1/python/lib/py4j-0.9-src.zip/py4j/java_gateway.py", line 813, in call
File "/Applications/spark-1.6.1/python/pyspark/sql/utils.py", line 45, in deco
return f(*a, **kw)
File "/Applications/spark-1.6.1/python/lib/py4j-0.9-src.zip/py4j/protocol.py", line 308, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o50.partitions.
: org.apache.hadoop.mapred.InvalidInputException: Input path does not exist: file:/Users/kate/hamlet.txt
at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:251)
at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:270)
at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:199)
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$2.apply(RDD.scala:237)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
at org.apache.spark.api.java.JavaRDDLike$class.partitions(JavaRDDLike.scala:64)
at org.apache.spark.api.java.AbstractJavaRDDLike.partitions(JavaRDDLike.scala:46)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
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)

Answer 1

1 - Add your "spark-1.6.1/bin/" to your .bashrc
2 - source .bashrc
3 - go to the directory where you have your dataset
4 - run your pyspark or spark-submit from there.