• This Setup involves activation of RStudio on bda Gateways and uses of the following libraries for R :

• Setup in rstudio_sparklyr , run in this order :

• • $ bash -x install_rstudio.sh
• • $ bash -x install_additional_packages.sh
• • $ bash -x install_sparklyr_2.1.sh

• Using sparklyr (Apache Spark) , DBI (Apache Hive SQL) , H2O (Machine Learning)

• • Sample use case : https://blog.rstudio.com/2016/09/27/sparklyr-r-interface-for-apache-spark/

• Using H2O with SparklyR : https://spark.rstudio.com/h2o.html

• • Productionizing an H2O sparklir model : http://docs.h2o.ai/h2o/latest-stable/h2o-docs/productionizing.html
• • Usage of H2O Models as Hive UDF POJO/MOJO : https://github.com/h2oai/h2o-tutorials/tree/master/tutorials/hive_udf_template/hive_udf_pojo_template

• Using SparkliR with conda R zio in the driver for spark containers :

• • From Cloudera Workbench option2 : https://blog.cloudera.com/blog/2017/09/how-to-distribute-your-r-code-with-sparklyr-and-cdsw/

Enjoy :)