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IBM is showing its support for Apache Spark in a big way at Spark Summit, a three-day event packed with lectures from leading production users of Spark, Spark SQL, Spark Streaming and related projects. Attendees will learn where project development is going and how to use the Spark stack in a variety of applications.
theCUBE kicked off its first day of interviews with IBM Big Data Evangelist James Kobielus, the senior program director for Product Marketing in Big Data Analytics for IBM. Kobielus also serves as team lead, technical marketing for the IBM Big Data & Analytics Hub.
Kobielus explained for theCUBE viewers that Spark addresses limitations found in “traditional” Hadoop. “Spark is part of the Hadoop distro,” he said. “The Spark community has developed within the Hadoop community. It is a complement for Hadoop; not a replacement.”
Through various product announcements and other internal developments, such as dedicating 3,500 developers and researchers to work on Spark-related projects, IBM makes clear its level of commitment to Spark. Today, Kobielus said that IBM will also announce a new Hack Spark Challenge.
“There is a lot of excitement in the developer community around Spark,” said Kobielus. “IBM understands that Spark is important to the future of Big Data.”
Among other announcements, IBM will open source its IBM SystemML machine learning technology and collaborate with Databricks to advance Spark’s machine learning capabilities. IBM will also build Spark into the core of the company’s analytics and commerce platforms.
“This is a big move for IBM,” said Kobielus. “This is our coming out.”
In an Internet of Things scenario, Kobielus said that Spark engines can bring behavioral data and real-time coordinates together to serve the customer better. “Spark streaming is for close-to-real-time data,” he said.
Day One continues with interviews with key players from IBM, Galvanize, Databricks, Inc., and Lawrence Berkeley National Laboratory.
Watch the full interview below, and be sure to check out more of SiliconANGLE and theCUBE’s coverage of IBM Spark 2015.
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