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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
- Hadoop in a heartbeat
- Introduction to YARN
- Data serialization—working with text and beyond
- Organizing and optimizing data in HDFS
- Moving data into and out of Hadoop
- Applying MapReduce patterns to big data
- Utilizing data structures and algorithms at scale
- Tuning, debugging, and testing
- SQL on Hadoop
- Writing a YARN application
PART 1 BACKGROUND AND FUNDAMENTALS
PART 2 DATA LOGISTICS
PART 3 BIG DATA PATTERNS
PART 4 BEYOND MAPREDUCE
商品描述(中文翻譯)
**摘要**
《Hadoop 實務應用(第二版)》提供了超過 100 種經過測試、立即可用的技術,幫助您使用 Hadoop 征服大數據。這一修訂版涵蓋了 Hadoop 核心架構中的變更和新功能,包括 MapReduce 2。全新章節涵蓋了 YARN 以及如何將 Kafka、Impala 和 Spark SQL 與 Hadoop 整合。您還將獲得 Flume、Sqoop 和 Mahout 的新技術和更新技術,這些工具最近都推出了重大新版本。簡而言之,這是目前最實用、最新的 Hadoop 覆蓋內容。
購買印刷版書籍可免費獲得 Manning Publications 提供的 PDF、Kindle 和 ePub 格式的電子書。
**關於本書**
升級您的 Hadoop 技能永遠是個好時機!《Hadoop 實務應用(第二版)》提供了一系列 104 種經過測試、立即可用的技術,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 駕馭大數據。這一完全修訂的版本涵蓋了 Hadoop 核心中的變更和新功能,包括 MapReduce 2 和 YARN。您將學到將 Spark、Kafka 和 Impala 與 Hadoop 整合的最佳實踐,並獲得 Flume、Sqoop 和 Mahout 最新版本的新技術和更新技術。簡而言之,這是目前最實用、最新的 Hadoop 覆蓋內容。
讀者需要了解像 Java 這樣的程式語言,並對 Hadoop 有基本的熟悉度。
**內容概覽**
- 完全更新至 Hadoop 2
- 如何撰寫 YARN 應用程式
- 整合實時技術,如 Storm、Impala 和 Spark
- 使用 Mahout 和 RR 進行預測分析
- 讀者需要了解像 Java 這樣的程式語言,並對 Hadoop 有基本的熟悉度。
**關於作者**
**Alex Holmes** 專注於解決困難的大數據問題。他是一名軟體工程師、作家、演講者和部落客,專門從事大規模 Hadoop 專案。
**目錄**
**第一部分 背景與基礎**
1. Hadoop 一瞥
2. YARN 介紹
**第二部分 數據物流**
1. 數據序列化—處理文本及其他
2. 在 HDFS 中組織和優化數據
3. 將數據移入和移出 Hadoop
**第三部分 大數據模式**
1. 將 MapReduce 模式應用於大數據
2. 在大規模下利用數據結構和算法
3. 調整、除錯和測試
**第四部分 超越 MapReduce**
1. 在 Hadoop 上使用 SQL
2. 撰寫 YARN 應用程式