.. _supported_platforms: Supported Platforms ------------------- Sparkling Water can run on top of Spark in various ways; however, starting Sparkling Water requires different configurations on different environments: Local ~~~~~ In this case, Sparkling Water runs as a local cluster (Spark master variable points to one of the values ``local``, ``local[*]`` or additional local modes available at `Spark Master URLs `__). Standalone Spark Cluster ~~~~~~~~~~~~~~~~~~~~~~~~ Spark documentation: `Spark Standalone Mode `__ YARN ~~~~ Spark documentation: `Running Spark on YARN `__ When submitting a Sparkling Water application to a CHD or Apache Hadoop cluster, the command to submit may look like: .. code:: bash ./spark-submit --master=yarn --deploy-mode=client --class ai.h2o.sparkling.SparklingWaterDriver --driver-memory=8G --num-executors=3 --executor-memory=3G --conf "spark.executor.extraClassPath=-Dhdp.version=current" sparkling-water-assembly-SUBST_SW_VERSION-all.jar When submitting a Sparkling Water application to an HDP Cluster, the command to submit may look like: .. code:: bash ./spark-submit --master=yarn --deploy-mode=client --class ai.h2o.sparkling.SparklingWaterDriver --conf "spark.yarn.am.extraJavaOptions=-Dhdp.version=current" --driver-memory=8G --num-executors=3 --executor-memory=3G --conf "spark.executor.extraClassPath=-Dhdp.version=current" sparkling-water-assembly-SUBST_SW_VERSION-all.jar The only difference between the HDP cluster and the CDH and Apache Hadoop clusters is that we need to add ``-Dhdp.version=current`` to both the ``spark.executor.extraClassPath`` and ``spark.yarn.am.extraJavaOptions`` (resp., ``spark.driver.extraJavaOptions``) configuration properties in the HDP case. Mesos ~~~~~ Spark documentation: `Running Spark on Mesos `__