HBase: The Definitive Guide (Paperback)
暫譯: HBase:權威指南(平裝本)
Lars George
- 出版商: O'Reilly
- 出版日期: 2011-10-18
- 售價: $1,720
- 貴賓價: 9.5 折 $1,634
- 語言: 英文
- 頁數: 556
- 裝訂: Paperback
- ISBN: 1449396100
- ISBN-13: 9781449396107
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相關分類:
Hadoop
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相關翻譯:
HBase 技術手冊 (HBase: The Definitive Guide) (繁中版)
海外代購書籍(需單獨結帳)
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商品描述
If your organization is looking for a storage solution to accommodate a virtually endless amount of data, this book will show you how Apache HBase can fulfill your needs. As the open source implementation of Google's BigTable architecture, HBase scales to billions of rows and millions of columns, while ensuring that write and read performance remain constant. HBase: The Definitive Guide provides the details you require, whether you simply want to evaluate this high-performance, non-relational database, or put it into practice right away.
HBase's adoption rate is beginning to climb, and several IT executives are asking pointed questions about this high-capacity database. This is the only book available to give you meaningful answers.
- Learn how to distribute large datasets across an inexpensive cluster of commodity servers
- Develop HBase clients in many programming languages, including Java, Python, and Ruby
- Get details on HBase's primary storage system, HDFS—Hadoop’s distributed and replicated filesystem
- Learn how HBase's native interface to Hadoop’s MapReduce framework enables easy development and execution of batch jobs that can scan entire tables
- Discover the integration between HBase and other facets of the Apache Hadoop project
商品描述(中文翻譯)
如果您的組織正在尋找一個能夠容納幾乎無限數據的儲存解決方案,本書將向您展示 Apache HBase 如何滿足您的需求。作為 Google 的 BigTable 架構的開源實現,HBase 可以擴展到數十億行和數百萬列,同時確保寫入和讀取性能保持穩定。《HBase: The Definitive Guide》提供了您所需的詳細資訊,無論您是想評估這個高性能的非關聯數據庫,還是立即將其付諸實踐。
HBase 的採用率開始上升,幾位 IT 高管對這個高容量數據庫提出了尖銳的問題。這是唯一一本能夠給您有意義答案的書籍。
- 學習如何在一個廉價的商品伺服器集群中分配大型數據集
- 使用多種程式語言(包括 Java、Python 和 Ruby)開發 HBase 客戶端
- 獲取有關 HBase 主要儲存系統 HDFS 的詳細資訊——Hadoop 的分散式和複製檔案系統
- 學習 HBase 與 Hadoop 的 MapReduce 框架的原生介面如何使批次作業的開發和執行變得簡單,這些作業可以掃描整個表格
- 探索 HBase 與 Apache Hadoop 專案其他方面之間的整合
