Instant Parallel Processing with Gearman

Learn how to use Gearman to build scalable distributed applications Key Features Learn something new in an Instant! A short, fast, focused guide delivering immediate results Build a cluster of managers, workers, and clients using Gearman to scale your application Understand how to reduce single-points-of-failure in your distributed applications Build clients and workers to process data in the background and provide real-time updates to your frontend Book DescriptionMany of today's applications need to be able to process ... Read More

Learn how to use Gearman to build scalable distributed applications Key Features Learn something new in an Instant! A short, fast, focused guide delivering immediate results Build a cluster of managers, workers, and clients using Gearman to scale your application Understand how to reduce single-points-of-failure in your distributed applications Build clients and workers to process data in the background and provide real-time updates to your frontend Book DescriptionMany 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.What you will learn Develop clients and workers to process data Use Gearman to implement a map-reduce cluster Take existing libraries and use them with Gearman Learn how Gearman stores jobs and available persistence options Build a cluster of managers, workers, and clients to scale your application Discover ways to use Gearman to avoid single-point-of-failure in your system 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. Read Less