Hadoop in Practice, 2/e (Paperback)

Alex Holmes

  • 出版商: Manning
  • 出版日期: 2015-02-05
  • 定價: $1,650
  • 售價: 9.5$1,568
  • 貴賓價: 9.0$1,485
  • 語言: 英文
  • 頁數: 512
  • 裝訂: Paperback
  • ISBN: 1617292222
  • ISBN-13: 9781617292224
  • 相關分類: Hadoop
  • 立即出貨 (庫存 < 4)

買這商品的人也買了...

相關主題

商品描述

Summary

Hadoop in Practice, Second Edition provides over 100 tested, instantly useful techniques that will help you conquer big data, using Hadoop. This revised new edition covers changes and new features in the Hadoop core architecture, including MapReduce 2. Brand new chapters cover YARN and integrating Kafka, Impala, and Spark SQL with Hadoop. You'll also get new and updated techniques for Flume, Sqoop, and Mahout, all of which have seen major new versions recently. In short, this is the most practical, up-to-date coverage of Hadoop available anywhere.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

About the Book

It's always a good time to upgrade your Hadoop skills! Hadoop in Practice, Second Edition provides a collection of 104 tested, instantly useful techniques for analyzing real-time streams, moving data securely, machine learning, managing large-scale clusters, and taming big data using Hadoop. This completely revised edition covers changes and new features in Hadoop core, including MapReduce 2 and YARN. You'll pick up hands-on best practices for integrating Spark, Kafka, and Impala with Hadoop, and get new and updated techniques for the latest versions of Flume, Sqoop, and Mahout. In short, this is the most practical, up-to-date coverage of Hadoop available.

Readers need to know a programming language like Java and have basic familiarity with Hadoop.

What's Inside

  • Thoroughly updated for Hadoop 2
  • How to write YARN applications
  • Integrate real-time technologies like Storm, Impala, and Spark
  • Predictive analytics using Mahout and RR
  • Readers need to know a programming language like Java and have basic familiarity with Hadoop.

About the Author

Alex Holmes works on tough big-data problems. He is a software engineer, author, speaker, and blogger specializing in large-scale Hadoop projects.

Table of Contents

    PART 1 BACKGROUND AND FUNDAMENTALS
  1. Hadoop in a heartbeat
  2. Introduction to YARN
  3. PART 2 DATA LOGISTICS
  4. Data serialization—working with text and beyond
  5. Organizing and optimizing data in HDFS
  6. Moving data into and out of Hadoop
  7. PART 3 BIG DATA PATTERNS
  8. Applying MapReduce patterns to big data
  9. Utilizing data structures and algorithms at scale
  10. Tuning, debugging, and testing
  11. PART 4 BEYOND MAPREDUCE
  12. SQL on Hadoop
  13. Writing a YARN application

商品描述(中文翻譯)

《Hadoop實戰,第二版》提供了超過100種經過測試且立即可用的技巧,幫助您使用Hadoop征服大數據。這本修訂的新版涵蓋了Hadoop核心架構的變化和新功能,包括MapReduce 2。全新的章節涵蓋了YARN以及將Kafka、Impala和Spark SQL與Hadoop集成。您還將獲得Flume、Sqoop和Mahout的新的和更新的技巧,這些工具最近都有重大的新版本。簡而言之,這是目前最實用、最新的Hadoop相關資訊。

購買印刷版書籍還包括Manning Publications提供的PDF、Kindle和ePub格式的免費電子書。

關於本書,現在是升級您的Hadoop技能的好時機!《Hadoop實戰,第二版》提供了一系列104種經過測試且立即可用的技巧,用於分析實時數據流、安全移動數據、機器學習、管理大規模集群以及使用Hadoop處理大數據。這本完全修訂的新版涵蓋了Hadoop核心的變化和新功能,包括MapReduce 2和YARN。您將學習到如何將Spark、Kafka和Impala與Hadoop集成的實用最佳實踐,並獲得最新版本的Flume、Sqoop和Mahout的新的和更新的技巧。簡而言之,這是目前最實用、最新的Hadoop相關資訊。

讀者需要了解像Java這樣的編程語言,並對Hadoop有基本的熟悉。

內容包括:
- 適用於Hadoop 2的全面更新
- 如何編寫YARN應用程序
- 將實時技術(如Storm、Impala和Spark)集成到Hadoop中
- 使用Mahout和RR進行預測分析
- 讀者需要了解像Java這樣的編程語言,並對Hadoop有基本的熟悉。

關於作者:
Alex Holmes致力於解決困難的大數據問題。他是一位軟體工程師、作家、演講者和專注於大規模Hadoop項目的部落客。

目錄:
第一部分 背景和基礎知識
1. 心跳中的Hadoop
2. YARN介紹

第二部分 數據物流
3. 數據序列化 - 使用文本和其他格式
4. 在HDFS中組織和優化數據
5. 將數據移入和移出Hadoop

第三部分 大數據模式
6. 將MapReduce模式應用於大數據
7. 在大規模集群中使用數據結構和算法
8. 調試、調優和測試

第四部分 超越MapReduce
9. Hadoop上的SQL
10. 編寫YARN應用程序