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Mastering Hadoop 3: Big data processing at scale to unlock unique business insights

발행사항
Birmingham : Packt Publishing, 2019
형태사항
ⅹ, 525p. ; 24cm
서지주기
Includes Index
소장정보
위치등록번호청구기호 / 출력상태반납예정일
이용 가능 (1)
자료실E207433대출가능-
이용 가능 (1)
  • 등록번호
    E207433
    상태/반납예정일
    대출가능
    -
    위치/청구기호(출력)
    자료실
책 소개

A comprehensive guide to mastering the most advanced Hadoop 3 concepts

Key Features

  • Get to grips with the newly introduced features and capabilities of Hadoop 3
  • Crunch and process data using MapReduce, YARN, and a host of tools within the Hadoop ecosystem
  • Sharpen your Hadoop skills with real-world case studies and code

Book Description

Apache Hadoop is one of the most popular big data solutions for distributed storage and for processing large chunks of data. With Hadoop 3, Apache promises to provide a high-performance, more fault-tolerant, and highly efficient big data processing platform, with a focus on improved scalability and increased efficiency.

With this guide, you’ll understand advanced concepts of the Hadoop ecosystem tool. You’ll learn how Hadoop works internally, study advanced concepts of different ecosystem tools, discover solutions to real-world use cases, and understand how to secure your cluster. It will then walk you through HDFS, YARN, MapReduce, and Hadoop 3 concepts. You’ll be able to address common challenges like using Kafka efficiently, designing low latency, reliable message delivery Kafka systems, and handling high data volumes. As you advance, you’ll discover how to address major challenges when building an enterprise-grade messaging system, and how to use different stream processing systems along with Kafka to fulfil your enterprise goals.

By the end of this book, you’ll have a complete understanding of how components in the Hadoop ecosystem are effectively integrated to implement a fast and reliable data pipeline, and you’ll be equipped to tackle a range of real-world problems in data pipelines.

What you will learn

  • Gain an in-depth understanding of distributed computing using Hadoop 3
  • Develop enterprise-grade applications using Apache Spark, Flink, and more
  • Build scalable and high-performance Hadoop data pipelines with security, monitoring, and data governance
  • Explore batch data processing patterns and how to model data in Hadoop
  • Master best practices for enterprises using, or planning to use, Hadoop 3 as a data platform
  • Understand security aspects of Hadoop, including authorization and authentication

Who this book is for

If you want to become a big data professional by mastering the advanced concepts of Hadoop, this book is for you. You’ll also find this book useful if you’re a Hadoop professional looking to strengthen your knowledge of the Hadoop ecosystem. Fundamental knowledge of the Java programming language and basics of Hadoop is necessary to get started with this book.



목차
Section 1: Introduction to Hadoop3 Chapter 1. Journey to Hadoop 3 Chapter 2. Deep Dive into Hadoop Distributed File System Chapter 3. YARN Resource Management in Hadoop Chapter 4. Internals of Map Reduce Section 2: Hadoop Ecosystem Chapter 5. SQL on Hadoop Chapter 6. Real Time Processing Engines Chapter 7. Widely used Hadoop Ecosystem Component Section 3: Hadoop in the Real World Chapter 8. Designing Applications in Hadoop Chapter 9. Real Time/Micro Batch Processing in Hadoop Chapter 10. Machine Learning in Hadoop Chapter 11. Hadoop in Cloud Chapter 12. Hadoop Cluster Profiling Section 4: Securing Hadoop Chapter 13. Who can do What in Hadoop Chapter 14. Network and Data Security Chapter 15. Monitoring Hadoop Index