[OracleCode SF] In-memory Analytics with Spark and Hazelcast

[OracleCode SF] In-memory Analytics with Spark and Hazelcast

Apache Spark is a distributed computation framework optimized to work in-memory, and heavily influenced by concepts from functional programming languages.

Hazelcast - open source in-memory data grid capable of amazing feats of scale - provides wide range of distributed computing primitives computation, including ExecutorService, M/R and Aggregations frameworks.

The nature of data exploration and analysis requires data scientists be able to ask questions that weren't planned to be asked—and get an answer fast!

In this talk, Viktor will explore Spark and see how it works together with Hazelcast to provide a robust in-memory open-source big data analytics solution!

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Viktor Gamov

March 01, 2017
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