With CDS 3.2.3 Powered by Apache Spark (CDS 3.2.3), you can run Apache Spark 3 applications locally or distributed across a cluster, either by using an interactive shell or by submitting an application. Running Spark applications interactively is commonly performed during the data-exploration phase and for ad hoc analysis.
With Spark 3, you use slightly different command names than with Spark 2, so that you can run both versions of Spark side-by-side without conflicts:
spark3-submit instead of
spark-submit.
spark3-shell instead of
spark-shell.
pyspark3 instead of pyspark.
For development and test purposes, you can also configure each host so that invoking the Spark 2 command name runs the corresponding Spark 3 executable.
The following example shows a simple pyspark3 session
that refers to the SparkContext, calls the collect()
function which runs a Spark 3 job, and writes data to HDFS. This
sequence of operations helps to check if there are obvious configuration
issues that prevent Spark 3 jobs from working at all. For the HDFS path
for the output directory, substitute a path that exists on your own
system.
$ hdfs dfs -mkdir /user/jdoe/spark
$ pyspark3
...
SparkSession available as 'spark'.
>>> strings = ["one","two","three"]
>>> s2 = sc.parallelize(strings)
>>> s3 = s2.map(lambda word: word.upper())
>>> s3.collect()
['ONE', 'TWO', 'THREE']
>>> s3.saveAsTextFile('hdfs:///user/jdoe/spark/canary_test')
>>> quit()
$ hdfs dfs -ls /user/jdoe/spark
Found 1 items
drwxr-xr-x - jdoe spark-users 0 2016-08-26 14:41 /user/jdoe/spark/canary_test
$ hdfs dfs -ls /user/jdoe/spark/canary_test
Found 3 items
-rw-r--r-- 3 jdoe spark-users 0 2016-08-26 14:41 /user/jdoe/spark/canary_test/_SUCCESS
-rw-r--r-- 3 jdoe spark-users 4 2016-08-26 14:41 /user/jdoe/spark/canary_test/part-00000
-rw-r--r-- 3 jdoe spark-users 10 2016-08-26 14:41 /user/jdoe/spark/canary_test/part-00001
$ hdfs dfs -cat /user/jdoe/spark/canary_test/part-00000
ONE
$ hdfs dfs -cat /user/jdoe/spark/canary_test/part-00001
TWO
THREE
The Maven coordinates are a combination of groupId, artifactId and
version. The groupId and artifactId are the same as for the upstream
Apache Spark project. For example, for spark-core,
groupId is org.apache.spark, and artifactId is
spark-core_2.12, both the same as the upstream
project. The version is different for the Cloudera packaging: see Using the CDS 3 Powered by Apache Spark
Maven Repository for the exact name depending on which release
you are using.
The Spark 3 history server is available on port 18089, rather than port 18088 as with the Spark 2 history server.
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