Hadoop 2 Essentials: An End-to-End Approach

Dr. Henry H Liu

  • 出版商: CreateSpace Independ
  • 出版日期: 2014-02-09
  • 售價: $2,320
  • 貴賓價: 9.5$2,204
  • 語言: 英文
  • 頁數: 308
  • 裝訂: Paperback
  • ISBN: 1495496120
  • ISBN-13: 9781495496127
  • 相關分類: Hadoop
  • 海外代購書籍(需單獨結帳)

相關主題

商品描述

Updated on Feb 22, 2015: All examples have been updated from 2.2.0 to the latest stable version of 2.6.0 with some very minimal changes. The other major update is that detailed instructions are given for using the free version of VMware Player virtualization software to build your 4-node Linux Yarn cluster on a Windows laptop. A similar procedure is also given on how to build a 4-node Linux Yarn cluster using VMware Fusion virtualization software on a Mac OS X machine.
   
This textbook adopts a unique approach to helping developers and CS students learn Hadoop MapReduce programming fast in an easy-to-setup, virtual 4-node Linux YARN cluster on a Windows or Mac OS X laptop. Rather than filled with disjointed, piecemeal code snippets to show Hadoop MapReduce programming features one at a time, it is designed to place your total Hadoop MapReduce programming learning process in a common application context of mining customer spending patterns ensconced in large volumes of credit card transaction record data. Precise, end-to-end procedures are given to help you set up your Hadoop MapReduce development environment quickly on Eclipse with Maven on Windows. Step-by-step procedures are also given on how to set up a four-node Linux cluster at minimum so that you can run your MapReduce programs not only in local but also in standalone and fully distributed mode on a real cluster. In fact, all MapReduce programs presented in the book have been tested and verified on such a Linux cluster. This textbook mainly focuses on teaching Hadoop MapReduce programming in a scientific, objective, quantitative approach. Rather than heavily relying on subjective, verbose (and sometimes even pompous) textual descriptions with sparse code snippets, this textbook uses Hadoop Java APIs, Hadoop configuration parameters, complete MapReduce programs and their execution logs and outputs to demonstrate how Hadoop MapReduce framework works and how to write MapReduce programs. Specifically, this text covers the following subjects:

  • Introduction to Hadoop
  • Setting up a Linux Hadoop Cluster
  • The Hadoop Distributed FileSystem
  • MapReduce Job Orchestration and Workflows
  • Basic MapReduce Programming
  • Advanced MapReduce Programming
  • Hadoop Streaming
  • Hadoop Administration

No matter what role you play on your team, this text can help you gain truly applicable Hadoop skills in a most effective and efficient manner. The book can also be used as a supplementary textbook for a distributed computing or Hadoop course offered to upper-division CS students.

商品描述(中文翻譯)

更新於2015年2月22日:所有示例已從2.2.0版本更新至最新穩定版本2.6.0,並進行了一些非常小的更改。另一個主要更新是提供了詳細的說明,以使用免費版本的VMware Player虛擬化軟件在Windows筆記本電腦上構建4節點Linux Yarn集群。同樣的步驟也提供了如何使用VMware Fusion虛擬化軟件在Mac OS X機器上構建4節點Linux Yarn集群的方法。

這本教科書採用了一種獨特的方法,幫助開發人員和計算機科學學生在Windows或Mac OS X筆記本電腦上的易於設置的虛擬4節點Linux YARN集群中快速學習Hadoop MapReduce編程。它不是填滿了零散的、零碎的代碼片段,以展示Hadoop MapReduce編程功能,而是設計成將您的整個Hadoop MapReduce編程學習過程置於大量信用卡交易記錄數據中的挖掘客戶消費模式的常見應用程序上下文中。提供了精確的端到端程序,以幫助您在Windows上快速設置您的Hadoop MapReduce開發環境,使用Eclipse和Maven。還提供了逐步程序,以指導您如何最低限度地設置一個四節點Linux集群,以便您不僅可以在本地運行MapReduce程序,還可以在真實集群上以獨立和完全分佈模式運行。事實上,書中介紹的所有MapReduce程序都在這樣的Linux集群上經過測試和驗證。本教科書主要侧重於以科學、客觀、定量的方法教授Hadoop MapReduce編程。本教科書不依賴於主觀、冗長(有時甚至是浮誇的)文本描述和稀疏的代碼片段,而是使用Hadoop Java API、Hadoop配置參數、完整的MapReduce程序及其執行日誌和輸出來演示Hadoop MapReduce框架的工作原理和如何編寫MapReduce程序。具體而言,本文涵蓋以下主題:

- Hadoop介紹
- 設置Linux Hadoop集群
- Hadoop分佈式文件系統
- MapReduce作業協調和工作流程
- 基本的MapReduce編程
- 高級MapReduce編程
- Hadoop Streaming
- Hadoop管理

無論您在團隊中擔任什麼角色,本書都可以幫助您以最有效和高效的方式獲得真正適用的Hadoop技能。該書還可以作為一門面向高年級計算機科學學生的分佈式計算或Hadoop課程的輔助教材。