CouchDB in Action

CouchDB in Action

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Managing dynamic, high-capacity systems can be difficult and expensive using databases like MySQL or SQL Server. Until now, web developers have had to principally rely on SQL-based data storage and management. Apache CouchDB, an open source document-oriented database solution, offers a new approach to storing and querying large quantities of data that relies far less on a rigid organizational schema and allows you to store documents and other data objects intact. In CouchDB you create simple schema-less documents and perform operations against the data via an implementation of the MapReduce algorithm. As a result, CouchDB-based data stores are flexible, highly fault-tolerant, and massively scalable. Although CouchDB itself is written in Erlang, its default query language is JavaScript, which means that it's a great choice for most web developers. CouchDB in Action is a guide for developers building high-volume data-driven applications for the web. Designed for web developers familiar with SQL-based database technology, the book presents a series of pragmatic examples that explore CouchDB's features from installation to deployment.
In it, you'll master the techniques you need to manipulate large data sets effectively. Through a series of examples and use cases, you'll develop your understanding by performing examples such as querying views, pagination, sorting, filtering, and data manipulation not easily performed in a traditional SQL paradigm. Along the way, you'll learn how CouchDB leverages the MapReduce-based power that Google and Hadoop are using today. As well, you'll learn integration patterns for using CouchDB with other platforms.
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Product details

  • Paperback | 350 pages
  • New York, United States
  • English
  • 1935182285
  • 9781935182283
  • 3,317,831

Table of contents

Preface PART I - Getting started with CouchDB 1. Enter couchDB - FREE 2. Creating a first database and document 3. Things to know to make CouchDB easier PART II - Couch core ideas 4. Getting more familiar with documents and storing data 5. Map/Reduce Mapping: searching through documents 6. Map/Reduce Reducing: making all those search results meaningful PART III - Advanced CouchDB 7. Key collation or "don't call them joins": combining complex records 8. Paging through data 9. Replicating data for redundancy and parallel processing 10. Reporting style use 11. Example app: converting a paper process to an electronic one 12. Pragmatic CouchDB on the way Appendix A: Installing CouchDB Appendix B: Javascript basics
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About Christopher Chandler

Chris Chandler develops web-based solutions at his company, Flatterline, ranging from small business websites to applications with millions of users. Chris has co-authored several papers on network algorithms and has been a contributor to several open source projects.
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