Sparkling Water 2.0 works wonders with Apache Spark

According to the official statement, "Sparkling Water was designed to allow users to get the best of Apache Spark -- its elegant APIs, RDDs and multi-tenant Context -- along with H2O's speed, columnar-compression and fully-featured machine learning algorithms." Plus, this newly updated tool empowers enterprise customers to use H2O algorithms in conjunction with, or instead of, MLlib algorithms on Apache Spark. Matt Aslett, Research Director, Data Platforms and Analytics at 451 Research forecasted that Sparkling Water could attract both Spark and H2O users, helping them to mix and match algorithms as needed. Enterprises are looking to take advantage of a variety of machine learning algorithms to address an increasingly complex set of use cases when determining how to best serve their customers. H2O.ai updates Sparkling Water machine learning API for Apache Spark https://t.co/ZWEYFoi4a6