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  • Storm: distributed and fault-tolerant realtime computation

    by Nathan Marz

    Storm makes it easy to write and scale complex realtime computations on a cluster of computers, doing for realtime processing what Hadoop did for batch processing. Storm guarantees that every message will be processed. And it’s fast — you can process millions of messages per second with a small cluster. Best of all, you can write Storm topologies using any programming language. Twitter relies upon Storm for much of its analytics.

    After being open-sourced, Storm instantly attracted a large community. It is by far the most watched JVM project on GitHub and the mailing list is active with over 300 users.

    Storm has a wide range of use cases, from stream processing to continuous computation to distributed RPC. In this talk I’ll introduce Storm and show how easy it is to use for realtime computation.

    At 11:30am to 12:10pm, Thursday 1st March

    In GA J, Santa Clara Convention Center

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