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Learning Spark: Lightning-Fast Big Data Analysis

Learning Spark: Lightning-Fast Big Data Analysis

Great Research Book in Learning Spark: Lightning-Fast Big Data Analysis

Author(s) Name:  Holden Karau, Andy Konwinski, Patrick Wendell, Matei Zaharia

About the Book:

   This book introduces Spark, an open source cluster computing system that makes data analytics fast to run and fast to write. The readers can learn how to run programs faster, using primitives for in-memory cluster computing. The book will equip the readers with capabilities such as collect, count, reduce, and save Use one programming paradigm instead of mixing and matching tools such as Hive, Hadoop, Mahout, and S4/Storm Learn how to run interactive, iterative, and incremental analyses Integrate with Scala to manipulate distributed datasets like local collections Tackle partitioning issues, data locality, default hash partitioning, user-defined partitioners, and custom serialization Use other languages by means of pipe() to achieve the equivalent of Hadoop streaming

Table of contents

  1. Introduction to Data Analysis with Spark
  2. Downloading Spark and Getting Started
  3. Programming with RDDs
  4. Working with Key/Value Pairs
  5. Loading and Saving Your Data
  6. Advanced Spark Programming
  7. Running on a Cluster
  8. Tuning and Debugging Spark
  9. Spark SQL
  10. Spark Streaming

ISBN:   9781449358624

Publisher:  O‚ÄôReilly Media

Year of Publication:  2015

Book Link:  Home Page Url