Book Image

PHP and MongoDB Web Development Beginner's Guide

Book Image

PHP and MongoDB Web Development Beginner's Guide

Overview of this book

With the rise of Web 2.0, the need for a highly scalable database, capable of storing diverse user-generated content is increasing. MongoDB, an open-source, non-relational database has stepped up to meet this demand and is being used in some of the most popular websites in the world. MongoDB is one of the NoSQL databases which is gaining popularity for developing PHP Web 2.0 applications.PHP and MongoDB Web Development Beginner’s Guide is a fast-paced, hands-on guide to get started with web application development using PHP and MongoDB. The book follows a “Code first, explain later” approach, using practical examples in PHP to demonstrate unique features of MongoDB. It does not overwhelm you with information (or starve you of it), but gives you enough to get a solid practical grasp on the concepts.The book starts by introducing the underlying concepts of MongoDB. Each chapter contains practical examples in PHP that teache specific features of the database.The book teaches you to build a blogging application, handle user sessions and authentication, and perform aggregation with MapReduce. You will learn unique MongoDB features and solve interesting problems like real-time analytics, location-aware web apps etc. You will be guided to use MongoDB alongside MySQL to build a diverse data back-end. With its concise coverage of concepts and numerous practical examples, PHP and MongoDB Web Development Beginner’s Guide is the right choice for the PHP developer to get started with learning MongoDB.
Table of Contents (17 chapters)
PHP and MongoDB Web Development
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface

Extracting analytics data with MapReduce


The log contains raw data about page visits, but we need to extract some meaningful information out of it. For example, it might be useful to know how many times a page has been viewed over a certain time period, or what is the average response time for a page. It is possible to do so by applying MapReduce on the log. In the next example, we are going to do just that.