Scaling Big Data with Hadoop and Solr, 2/e (Paperback)
暫譯: 使用 Hadoop 和 Solr 擴展大數據,第二版 (平裝本)
Hrishikesh Vijay Karambelkar
- 出版商: Packt Publishing
- 出版日期: 2015-04-30
- 售價: $2,010
- 貴賓價: 9.5 折 $1,910
- 語言: 英文
- 頁數: 156
- 裝訂: Paperback
- ISBN: 1783553391
- ISBN-13: 9781783553396
-
相關分類:
Hadoop、全文搜尋引擎 Full-text-search、大數據 Big-data
海外代購書籍(需單獨結帳)
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商品描述
Understand, design, build, and optimize your big data search engine with Hadoop and Apache Solr
About This Book
- Explore different approaches to making Solr work on big data ecosystems besides Apache Hadoop
- Improve search performance while working with big data
- A practical guide that covers interesting, real-life use cases for big data search along with sample code
Who This Book Is For
This book is aimed at developers, designers, and architects who would like to build big data enterprise search solutions for their customers or organizations. No prior knowledge of Apache Hadoop and Apache Solr/Lucene technologies is required.
What You Will Learn
- Understand Apache Hadoop, its ecosystem, and Apache Solr
- Explore industry-based architectures by designing a big data enterprise search with their applicability and benefits
- Integrate Apache Solr with big data technologies such as Cassandra to enable better scalability and high availability for big data
- Optimize the performance of your big data search platform with scaling data
- Write MapReduce tasks to index your data
- Configure your Hadoop instance to handle real-world big data problems
- Work with Hadoop and Solr using real-world examples to benefit from their practical usage
- Use Apache Solr as a NoSQL database
In Detail
Together, Apache Hadoop and Apache Solr help organizations resolve the problem of information extraction from big data by providing excellent distributed faceted search capabilities.
This book will help you learn everything you need to know to build a distributed enterprise search platform as well as optimize this search to a greater extent, resulting in the maximum utilization of available resources. Starting with the basics of Apache Hadoop and Solr, the book covers advanced topics of optimizing search with some interesting real-world use cases and sample Java code.
This is a step-by-step guide that will teach you how to build a high performance enterprise search while scaling data with Hadoop and Solr in an effortless manner.
商品描述(中文翻譯)
**了解、設計、建構並優化您的大數據搜尋引擎,使用 Hadoop 和 Apache Solr**
## 本書介紹
- 探索在大數據生態系統中使 Solr 運作的不同方法,除了 Apache Hadoop
- 在處理大數據時提升搜尋效能
- 一本實用指南,涵蓋有趣的真實案例以及範例程式碼
## 本書適合誰閱讀
本書針對希望為其客戶或組織建構大數據企業搜尋解決方案的開發人員、設計師和架構師。無需具備 Apache Hadoop 和 Apache Solr/Lucene 技術的先前知識。
## 您將學到什麼
- 了解 Apache Hadoop、其生態系統及 Apache Solr
- 通過設計大數據企業搜尋,探索基於行業的架構及其適用性和優點
- 將 Apache Solr 與大數據技術(如 Cassandra)整合,以實現更好的可擴展性和高可用性
- 通過擴展數據來優化您的大數據搜尋平台性能
- 編寫 MapReduce 任務以索引您的數據
- 配置您的 Hadoop 實例以處理現實世界的大數據問題
- 使用現實世界的範例與 Hadoop 和 Solr 進行操作,以獲得其實用性
- 將 Apache Solr 作為 NoSQL 數據庫使用
## 詳細內容
Apache Hadoop 和 Apache Solr 共同幫助組織解決從大數據中提取信息的問題,提供卓越的分散式多面搜尋能力。
本書將幫助您學習建構分散式企業搜尋平台所需的所有知識,並進一步優化此搜尋,以實現可用資源的最大化利用。從 Apache Hadoop 和 Solr 的基礎開始,本書涵蓋了優化搜尋的進階主題,並提供一些有趣的真實案例和範例 Java 程式碼。
這是一本逐步指南,將教您如何在輕鬆的方式下,使用 Hadoop 和 Solr 建構高效能的企業搜尋,同時擴展數據。