Sparkling Water 2.0 might come in handy if you are using Apache Spark
Sparkling Water 2.0’s goal is to bring machine learning into the mainstream; this tool from H2O.ai offers an open-source algorithm development platform which helps companies use machine learning algorithms in their data analysis.
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
— Matt Aslett (@maslett) July 1, 2016
What’s under the hood of Sparkling Water 2.0?
This tool offers support for Apache Spark 2.0, as well as backwards compatibility with all previous versions and has the ability to run both Apache Spark and Scala through H2O’s Flow UI. There’s also support for the Apache Zeppelin notebook and visual intelligence for Apache Spark.
H2O.ai CEO Sri Ambati revealed that the company is 100 percent committed to the open source movement and its goal is to “bring visually appealing, and easy to comprehend, AI-driven insights to enterprise users.”