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Big Data Processing with Apache Spark
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  • Title Big Data Processing with Apache Spark
  • Author(s) Srini Penchikala
  • Publisher: InfoQ (2018)
  • Paperback: N/A
  • eBook PDF (104 pages)
  • Language: English
  • ISBN-10: N/A
  • ISBN-13: N/A
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Book Description

Apache Spark is an open-source big-data processing framework built around speed, ease of use, and sophisticated analytics.

Spark has several advantages compared to other big-data and MapReduce technologies like Hadoop and Storm. It provides a comprehensive, unified framework with which to manage big-data processing requirements for datasets that are diverse in nature (text data, graph data, etc.) and that come from a variety of sources (batch versus real-time streaming data).

Spark enables applications in HDFS clusters to run up to a hundred times faster in memory and ten times faster even when running on disk.

In this mini-book, the reader will learn about the Apache Spark framework and will develop Spark programs for use cases in big-data analysis. The book covers all the libraries that are part of Spark ecosystem, which includes Spark Core, Spark SQL, Spark Streaming, Spark MLlib, and Spark GraphX.

About the Authors
  • Srini Penchikala currently works as Software Architect at a financial services organization in Austin, Texas. He has over 20 years of experience in software architecture, design and development.
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