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Big Data Processing with Apache Spark

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Paperback / softback
13 March 2018
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Apache Spark is a popular open-source big-data processing framework that's built around speed, ease of use, and unified distributed computing architecture. Not only it supports developing applications in different languages like Java, Scala, Python, and R, it's also hundred times faster in memory and ten times faster even when running on disk compared to traditional data processing frameworks. Whether you are currently working on a big data project or interested in learning more about topics like machine learning, streaming data processing, and graph data analytics, this book is for you. You can learn about Apache Spark and develop Spark programs for various use cases in big data analytics using the code examples provided.This book covers all the libraries in Spark ecosystem: Spark Core, Spark SQL, Spark Streaming, Spark ML, and Spark GraphX.

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    Product Details
    ISBN-13
    9781387659951
    Author
    Srini Penchikala
    Publisher
    Lulu Press
    Published
    13 March 2018
    Format
    Paperback / softback

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    $36.49
    Ships in 3-5 business days

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    Hurry up! Current stock:

    Big Data Processing with Apache Spark

    $36.49

    Description

    Apache Spark is a popular open-source big-data processing framework that's built around speed, ease of use, and unified distributed computing architecture. Not only it supports developing applications in different languages like Java, Scala, Python, and R, it's also hundred times faster in memory and ten times faster even when running on disk compared to traditional data processing frameworks. Whether you are currently working on a big data project or interested in learning more about topics like machine learning, streaming data processing, and graph data analytics, this book is for you. You can learn about Apache Spark and develop Spark programs for various use cases in big data analytics using the code examples provided.This book covers all the libraries in Spark ecosystem: Spark Core, Spark SQL, Spark Streaming, Spark ML, and Spark GraphX.

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