• Title Subjects
  • Data

Big Data Using Hadoop and Hive

Paperback
April 2021
9781683926450
More details
  • Publisher
    Mercury Learning and Information
  • Published
    1st April 2021
  • ISBN 9781683926450
  • Language English
  • Pages 192 pp.
  • Size 7" x 9"
  •    Request Exam Copy
$54.95
E-Book

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March 2021
9781683926436
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  • Publisher
    Mercury Learning and Information
  • Published
    24th March 2021
  • ISBN 9781683926436
  • Language English
  • Pages 192 pp.
  • Size 7" x 9"
  •    Request E-Exam Copy
$39.95
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March 2021
9781683926443
More details
  • Publisher
    Mercury Learning and Information
  • Published
    24th March 2021
  • ISBN 9781683926443
  • Language English
  • Pages 192 pp.
  • Size 7" x 9"
$149.95

This book is the basic guide for developers, architects, engineers, and anyone who wants to start leveraging the open-source software Hadoop and Hive to build distributed, scalable concurrent big data applications. Hive will be used for reading, writing, and managing the large, data set files. The book is a concise guide on getting started with an overall understanding on Apache Hadoop and Hive and how they work together to speed up development with minimal effort. It will refer to simple concepts and examples, as they are likely to be the best teaching aids. It will explain the logic, code, and configurations needed to build a successful, distributed, concurrent application, as well as the reason behind those decisions.

FEATURES:

  • Shows how to leverage the open-source software Hadoop and Hive to build distributed, scalable, concurrent big data applications
  • Includes material on Hive architecture with various storage types and the Hive query language
  • Features a chapter on big data and how Hadoop can be used to solve the changes around it
  • Explains the basic Hadoop setup, configuration, and optimization

1: Big Data
2: What Is Apache Hadoop?
3: The Hadoop Distribution File System
4: Getting Started with Hadoop
5: Interfaces to Access HDFS Files
6: Yet Another Resource Negotiator
7: MapReduce
8: Hive
9: Getting Started with Hive
10: File Format
11: Data Compression
Index

Nitin Kumar

Nitin Kumar has 18+ years of overall IT experience with technical specialties in architecture, systems analysis, design, performance tuning, and execution on a Distributed Parallel Processing system. He has published books and papers with special focus on Agile, Big Data, streaming, Java, and re-factoring.

Open Source; Big Data; Distributed Apps