Instant Parallel Processing with Gearman

In DetailMany of today's applications need to be able to process large volumes of data, and vertical scaling has its limits both in terms of prohibitive cost and hardware limits. Gearman is an open source job manager that is well-suited to building horizontally scalable systems, from map-reduce algorithms to simple data processors capable of handling massive amounts of information.
Instant Gearman is a practical, hands-on guide to getting started with building an open source job management server system that is built to grow. Learn the basics of building a distributed application that spans multiple components and learn how Gearman fits into building an application that scales from one to hundreds of components that interact to process data. With Gearman, you can build software that scales horizontally as your need for computation increases.
Instant Gearman has in-depth examples and a step-by-step approach to building distributed systems, helping you to build systems that are scalable and modular in their approach to processing data.
Once you are comfortable with building simple workers and clients, learn how to build a cluster of managers and see how to reduce single-point-of-failure in your architecture. Next, build a simple map-reduce application using Gearman and scale it up from a single instance to multiple parallel processing components.
ApproachGet to grips with a new technology, understand what it is and what it can do for you, and then get to work with the most important features and tasks. This is a quick tutorial allowing you to quickly increase the efficiency of your system by intelligently reducing its workload where possible and learn techniques for designing your solutions to take advantage of Gearman's architecture.
The technology covered in this book is usable by almost any modern programming language and any type of application, be it web, desktop, or mobile applications.
Who this book is forThis book targets developers who are interested in adding distributed data processing to their applications. The examples in this book are written using Ruby, but are documented thoroughly to allow developers comfortable with other languages to understand how to use them in a language of their choice. Intermediate programmers with no previous experience in distributed computing will also be able to easily follow the content.