You can use Spark to process data that is destined for HBase. See Importing Data Into HBase Using Spark .

You can also use Spark in conjunction with Apache Kafka to stream data from Spark to HBase. See Importing Data Into HBase Using Spark and Kafka .

The host from which the Spark application is submitted or on which spark-shell or pyspark runs must have an HBase gateway role defined in Cloudera Manager and client configurations deployed.

  Note: Spark 2 on HBase is not supported with CDH.

spark-shell --jars MySparkHbaseApp.jar --principal ME@DOMAIN.COM --keytab /path/to/local/keytab ...

spark-submit --class com.example.SparkHbaseApp --principal ME@DOMAIN.COM --keytab /path/to/local/keytab
SparkHBaseApp.jar [ application parameters....]"

The host from which the Spark application is submitted or on which spark-shell or pyspark runs must have a Hive gateway role defined in Cloudera Manager and client configurations deployed.

When a Spark job accesses a Hive view, Spark must have privileges to read the data files in the underlying Hive tables. Currently, Spark cannot use fine-grained privileges based on the columns or the WHERE clause in the view definition. If Spark does not have the required privileges on the underlying data files, a SparkSQL query against the view returns an empty result set, rather than an error.

For CDH 5.4 and higher you can invoke Spark jobs from Oozie using the Spark action. For information on the Spark action, see Oozie Spark Action Extension.

In CDH 5.4, to enable dynamic allocation when running the action, specify the following in the Oozie workflow:

<spark-opts>--conf spark.dynamicAllocation.enabled=true
--conf spark.shuffle.service.enabled=true
--conf spark.dynamicAllocation.minExecutors=1
</spark-opts>

If you have enabled the shuffle service in Cloudera Manager, you do not need to specify spark.shuffle.service.enabled.