To add a compression library to Spark, you can use the --jars option. For an example, see Adding Libraries to Spark.

To save a Spark RDD to HDFS in compressed format, use code similar to the following (the example uses the GZip algorithm):

rdd.saveAsHadoopFile("/tmp/spark_compressed",
                     "org.apache.hadoop.mapred.TextOutputFormat",
                     compressionCodecClass="org.apache.hadoop.io.compress.GzipCodec")

For more information about supported compression algorithms, see Configuring HDFS Compression in the HDFS Administration Guide.

When accessing an HDFS file from PySpark, you must set HADOOP_CONF_DIR in an environment variable, as in the following example:

export HADOOP_CONF_DIR=/etc/hadoop/conf
[hrt_qa@ip-172-31-42-188 spark]$ pyspark
[hrt_qa@ip-172-31-42-188 spark]$ >>>lines = sc.textFile("hdfs://ip-172-31-42-188.ec2.internal:8020/tmp/PySparkTest/file-01")
.......

If HADOOP_CONF_DIR is not set properly, you might see the following error:

Error from secure cluster

2016-08-22 00:27:06,046|t1.machine|INFO|1580|140672245782272|MainThread|Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.
2016-08-22 00:27:06,047|t1.machine|INFO|1580|140672245782272|MainThread|: org.apache.hadoop.security.AccessControlException: SIMPLE authentication is not enabled.  Available:[TOKEN, KERBEROS]
2016-08-22 00:27:06,047|t1.machine|INFO|1580|140672245782272|MainThread|at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
2016-08-22 00:27:06,047|t1.machine|INFO|1580|140672245782272|MainThread|at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:57)
2016-08-22 00:27:06,048|t1.machine|INFO|1580|140672245782272|MainThread|at
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