RapidMiner Announces Support for SparkR and PySpark with the Latest Version of RapidMiner Radoop
The RapidMiner Predictive Analytics Platform is the industry's first and only visual predictive analytics solution to support SparkR and PySpark
CAMBRIDGE, Mass., Sept. 29, 2015 /PRNewswire/ -- Strata + Hadoop World New York 2015 -- RapidMiner™, the industry's #1 open source predictive analytics platform, today announced the general availability of RapidMiner Radoop v2.6, making it easy to incorporate SparkR and PySpark scripts within a single, unified analytics workflow. Radoop, a core component of the RapidMiner platform, extends predictive analytics to Hadoop and Spark, giving organizations complete and holistic insight across all their data by leveraging the computation power of their Hadoop clusters.
By adding SparkR and PySpark support, RapidMiner becomes the first and only visual predictive analytics solution to combine data preparation on Spark, predictive analytics using Spark's Machine Learning library (MLlib), and the ability to incorporate custom-built R and Python scripts. RapidMiner's visual building block "language" makes the process of creating predictive analytics incredibly fast. Using Spark's computation power makes analytics execution extremely efficient, empowering organizations to quickly and easily extract and operationalize the immense value deeply hidden within their Hadoop clusters.
"Hadoop is a very powerful technology, yet also a complicated environment, making it a challenge to tap its wealth of buried insights," said Dr. Ingo Mierswa, Founder & CTO at RapidMiner. "Today's announcement of Radoop v2.6 adding SparkR and PySpark support brings together customized data science scripts with powerful and standardized visual workflows, allowing businesses to create the most competitive predictive analytics."
In addition to RapidMiner Radoop 2.6 with SparkR and PySpark support, at Strata + Hadoop World, RapidMiner will showcase:
- RapidMiner's code-free software that data scientists and business analysts use to quickly create predictive analytics processes to run within Hadoop and Spark.
- How to incorporate R, Python and SQL scripts within a code-free predictive analytics process.
- RapidMiner Radoop, which uses built-in intelligence that automatically translates predictive analytics processes into the native languages of Hadoop and Spark.
- A new Hadoop connector that allows users to extract data from Hadoop for in-memory rapid-prototyping of predictive analytic models.
- How to take advantage of Spark's Machine Learning Library (MLlib) to create and execute competitive predictive analytics and leverage Big Data.
- Its joint offering with Cloudera, which enables end users to effortlessly mine and model data—no coding required—mashup all data for a holistic business view, rapidly build predictive models to uncover opportunities and risks and operationalize predictive models by embedding them within business processes.
Visit RapidMiner at booth #419 at Strata + Hadoop World 2015 at the Javits Convention Center in NYC. For more information about RapidMiner Radoop, please visit: https://rapidminer.com/products/radoop/.
About RapidMiner
RapidMiner, the industry's #1 open source predictive analytics platform, is disrupting the industry by empowering enterprises to include predictive analytics in any business process—closing the loop between insight and action. RapidMiner's effortless solution makes predictive analytics lightning-fast for today's modern analysts, radically reducing the time to unearth opportunities and risks. RapidMiner delivers game-changing expertise from the largest worldwide predictive analytics community. For more information, visit www.rapidminer.com.
Media Contact:
Payal Patel Cudia, RapidMiner
[email protected]
+1 (617) 401-7708
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SOURCE RapidMiner
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