15_python.md

Documentation

PySpark with Data Frames - Experimental

With the inclusion of the Cassandra Data Source, PySpark can now be used with the Connector to access Cassandra data. This does not require DataStax Enterprise but you are limited to DataFrame only operations.

Setup

To enable Cassandra access the Spark Cassandra Connector assembly jar must be included on both the driver and executor classpath for the PySpark Java Gateway. This can be done by starting the PySpark shell similarlly to how the spark shell is started.

./bin/pyspark \
  --driver-class-path spark-cassandra-connector-assembly-1.4.0-M1-SNAPSHOT.jar \
  --jars spark-cassandra-connector-assembly-1.4.0-M1-SNAPSHOT.jar

Loading a DataFrame in Python

A DataFrame can be created which links to cassandra by using the the org.apache.spark.sql.cassandra source and by specifying keyword arguements for keyspace and table.

 sqlContext.read\
    .format("org.apache.spark.sql.cassandra")\
    .options(table="kv", keyspace="test")\
    .load().show()

+-+-+
|k|v|
+-+-+
|5|5|
|1|1|
|2|2|
|4|4|
|3|3|
+-+-+

The options and parameters are identical to the Scala Data Frames Api so please see Data Frames for more information.