Running Applications with CDS Powered by Apache Spark

With CDS Powered by Apache Spark, you can run Apache Spark 2 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.

The Spark 2 Job Commands

With Spark 2, you use slightly different command names than in Spark 1, so that you can run both versions of Spark side-by-side without conflicts:

  • spark2-submit instead of spark-submit.

  • spark2-shell instead of spark-shell.

  • pyspark2 instead of pyspark.

For development and test purposes, you can also configure each host so that invoking the Spark 1 command name runs the corresponding Spark 2 executable. See Configuring Spark 2 Tools as the Default for details.

Canary Test for pyspark2 Command

The following example shows a simple pyspark2 session that refers to the SparkContext, calls the collect() function which runs a Spark 2 job, and writes data to HDFS. This sequence of operations helps to check if there are obvious configuration issues that prevent Spark 2 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
$ pyspark2
...
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

Fetching Spark 2 Maven Dependencies

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_2.11, both the same as the upstream project. The version is different for the Cloudera packaging: see Using the CDS Powered by Apache Spark Maven Repository for the exact name depending on which release you are using.

Adapting the Spark WordCount App for Spark 2

The following pom fragment shows how to access a CDS Powered by Apache Spark artifact from a Maven POM.

<dependency>
      <groupId>org.apache.spark</groupId>
      <artifactId>spark-core_2.11</artifactId>
      <version>2.3.0.cloudera4</version>
      <scope>provided</scope>
</dependency>

Use this dependency definition to update pom.xml for the example described in Developing and Running a Spark WordCount Application. If you are using a different CDS version, see Using the CDS Powered by Apache Spark Maven Repository.

To account for changes in the Spark 2 API, before building the example, make the following updates to com.cloudera.sparkwordcount.JavaWordCount:
  • Add import java.util.Iterator;
  • Replace all instances of Iterable with Iterator.
  • Perform the following replacements:
    • return Arrays.asList(s.split(" ")); to return Arrays.asList(s.split(" ")).iterator();
    • return chars; to return chars.iterator();

Accessing the Spark 2 History Server

The Spark 2 history server is available on port 18089, rather than port 18088 as with the Spark 1 history server.