Cassandra權威指南（第2版 影印版） [Cassandra the Definitive Guide] 下載 mobi epub pdf 電子書 2024

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內容簡介

　　如果不用考慮可伸縮性，想象一下你能做些什麼？在這本實踐指南中，你將會瞭解到Cassandra數據庫管理係統是如何在為多個數據中心提供高可用服務的同時處理上百TB的數據。擴充後的第二版已經更新到瞭Cassandra 3.0，書中給齣瞭各種技術細節以及實例，當你將Cassandra投入實際生産環境時，這些內容都是必不可少的。
　　作者Jeff Carpenter和Eben Hewitt闡述瞭Cassandra非關係型設計的優勢，著重介紹瞭其數據模型。
　　《Cassandra**指南（第2版 影印版）》嚮開發者、DBA、正在尋找數據庫的可擴展性解決方案的應用架構師展示瞭Cassandra的速度和靈活性。

作者簡介

　　Jeff Carpenter，精品國際酒店集團（Choice Hotels International）的一名係統架構師，在服務業和國防工業有著20年的從業經驗。他的興趣包括SOA/微服務、大規模係統架構設計以及數據架構。
　　EbenHewitt是精品國際酒店集團（世界大酒店之一）的首席技術官。
　　他還是好幾本書籍的作者，題材涉及係統架構、分布式係統以及編程。

內頁插圖

目錄

Foreword
Foreword
Preface

1．Beyond Relational Databases
What's Wrong with Relational Databases?
A Quick Review of Relational Databases
RDBMSs： The Awesome and the Not-So-Much
Web Scale
The Rise of NoSQL
Summary

2．Introducing Cassandra
The Cassandra Elevator Pitch
Cassandra in 50 Words or Less
Distributed and Decentralized
Elastic Scalability
High Availability and Fault Tolerance
Tuneable Consistency
Brewer's CAP Theorem
Row-Oriented
High Performance
Where Did Cassandra Come From?
Release History
Is Cassandra a Good Fit for My Project?
Large Deployments
Lots of Writes， Statistics， and Analysis
Geographical Distribution
Evolving Applications
Getting Involved
Summary

3．Installing Cassandra
Installing the Apache Distribution
Extracting the Download
What's In There?
Building from Source
Additional Build Targets
Running Cassandra
On Windows
On Linux
Starting the Server
Stopping Cassandra
Other Cassandra Distributioaas
Running the CQL Shell
Basic cqlsh Commands
cqlsh Help
Describing the Environment in cqlsh
Creating a Keyspace and Table in cqlsh
Writing and Reading Data in cqlsh
Summary

4．The Cassandra Query Language
The Relational Data Model
Cassandra's Data Model
Clusters
Keyspaces
Tables
Columns
CQL Types
Numeric Data Types
Textual Data Types
Time and Identity Data Types
Other Simple Data Types
Collections
User-Defined Types
Secondary Indexes
Summary
……

前言/序言

　　Cassandra was open-sourced by Facebook in July 2008. This original version of Cassandra was written primarily by an ex-employee from Amazon and one from Microsoft. It was strongly influenceyd by Dynamo， Amazon's pioneering distributed key/value database. Cassandra implements a Dynamo-style replication model with no single point of failure， but adds a more powerful "column family" data model.
　　I became involved in December of that year， when Rackspace asked me to build them a scalable database. This was good timing， because all of today's important open source scalable databases were available for evaluation， Despite initially having only a single major use case， Cassandra's underlying architecture was the strongest， and I
　　directed my efforts toward improving the code and building a community.
　　Cassandra was accepted into the Apache Incubator， and by the time it graduated in March 2010， it had become a true open source success story， with committers from Rackspace， Digg， Twitter， and other companies that wouldn't have written their own
　　database from scratch， but together built something important.
　　Today's Cassandra is much more than the early system that powered （and still powers） Facebook's inbox search; it has become "the hands-down winner for transaction
　　processing performance：' to quote Tony Bain， with a deserved reputation for reliability and performance at scale.
　　As Cassandra matured and began attracting more mainstream users， it became clear that there was a need for commeraal support; thus， Matt Pfeil and I cofounded Riptano in April 2010. Helping drive Cassandra adoption has been very rewarding， espeaally seeing the uses that don't get discussed in public.
　　Another need has been a book like this one. Like many open source projects， Cassandra's documentation has historically been weak. And even when the documentation
　　ultimately improves， a book-length treatment like this will remain useful.
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