DSS can be configured to use a (already existing ) Hadoop and spark cluster .
Hadoop and spark are effective when they consume external resources and their use is dedicated to fairly big datasets ( multi hundred gigabytes or multi terabytes datasets) .
If your use case implies such requirements you will need to additional vm (mimum 32 GB of RAM ) on wihich you can install a hadoop distribution . Four on premise installations you can chose among these 3 distributions :
If your DSS is hosted on cloud you can also try to use Azure HDinsight (which provisions a DSS for you along with the cluster ) and EMR if you are on amazon (but you might need a very clear understanding of Hadoop integration to connect to EMR) .
You can also choose to run a spark standalone cluster but every one of these options (maybe exect HDInsight preprovisioned DSS instance requires a decent Linux system knowledge and a clear understanding of Hadoop and Spark concepts.
Once it is done you can check the documentation of DSS hadoop and spark integration .