Instant Parallel Processing with Gearman

John Ewart

• Publisher: Packt Publishing
• Year: 2013
• ISBN:
  9781783284078
• Edition: 1
• Topic: Informatica
• Subtopic: Programmazione open source

In Detail

Many 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.

Approach

Get 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 for

This 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.

Instant Parallel Processing with Gearman

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Instant Parallel Processing with Gearman

Copyright © 2013 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

First published: July 2013

Production Reference: 1230713

Published by Packt Publishing Ltd.

Livery Place

35 Livery Street

Birmingham B3 2PB, UK.

ISBN 978-1-78328-407-8

www.packtpub.com

Credits

Author

John Ewart

Reviewer

Josh Black

Acquisition Editor

Vinay Argekar

Commissioning Editor

Priyanka Shah

Technical Editor

Mausam Kothari

Project Coordinator

Michelle Quadros

Proofreader

Bernadette Watkins

Graphics

Ronak Dhruv

Production Coordinator

Prachali Bhiwandkar

Cover Work

Prachali Bhiwandkar

Cover Image

Prachali Bhiwandkar

About the Author

John Ewart is a systems architect, software developer, and lecturer. He has designed and taught courses at a variety of institutions including the University of California, California State University and local community colleges covering a wide range of computer science topics including Java, data structures and algorithms, operating systems fundamentals, UNIX and Linux systems administration, and web application development. In addition to working and teaching, he maintains and contributes to a number of open source projects. He currently resides in Redmond, Washington with his wife, Mary, and their two children.

About the Reviewer

Josh Black has been working with computers professionally for 20 years. He has a broad range of experience and expertise including systems and network administration, mobile app development, and production web applications. Josh earned a BS in computer science with a minor in math from California State University, Chico, in 2005. He currently resides in Chico, California, with his wife Rachel, and their four children.

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Chapter 1. Instant Parallel Processing with Gearman

Welcome to the Instant Parallel Processing with Gearman. This book has been written to show you all you need to know to get started using Gearman. You will learn the history of Gearman, how to run your own servers, write some scripts to process data, and learn some of the more advanced features of Gearman.

This book contains the following sections:

So, what is Gearman? finds out what Gearman is, why it exists, and what you can do with it.

Quick start – building your first components shows you how to set up your own server and interacts with it with some quick examples in Ruby. This section of the book will cover the core concepts of Gearman to get you on your way as quickly as possible to processing jobs using Gearman.

Top 5 features you need to know about helps you learn how to use Gearman beyond simple job submissions. By the end of this section, you will be able to use Gearman and MapReduce methodologies to process large amounts of data, build a pipeline of complex loosely coupled processes that work together to process data using different languages and libraries, offload long-running and complex data analysis and provide real-time feedback to a frontend application, and utilize job coalescing to distribute results to multiple clients while processing the data only one time.

People and places you should get to know tells us that Gearman, like many other open source projects, has a wealth of online resources available. This section will get you started with a number of links to these resources including code examples, libraries, server implementations, mailing lists, and more.

So, what is Gearman?

Gearman is a network-based job-queuing system that was initially developed by Danga Interactive in order to process large volumes of jobs. Its primary design goals were low-latency remote function execution, being able to run code remotely and in parallel, load balancing of job distribution, and supporting writing components in multiple languages.

Although originally written in Perl it is comprised of, at its core, a network protocol that is designed to allow the various components to communicate the lifecycle of a unit of work. Because of this design, there are both servers and client libraries written in multiple languages including Ruby, Perl, PHP, Python, C, C++, and Java.

What this translates into is the ability to design and develop the various components of your architecture in whatever language makes the most sense and have those components communicate easily with one another.

Gearman goes one step further than simply defining a message bus; it formalizes its architecture to focus on units of work. This means that everything in a system using Gearman operates in terms of submitting or working on jobs. To follow this paradigm, Gearman has three main actors: clients who request that work be completed by somebody, the managers (servers) that are responsible for accepting jobs from clients, and then handing those jobs out to workers that ultimately complete the tasks.

Distinguishin...