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Instant Parallel Processing with Gearman电子书

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0人正在读 | 0人评论 9.8

作       者:John Ewart

出  版  社:Packt Publishing

出版时间:2013-07-26

字       数:156.4万

所属分类: 进口书 > 外文原版书 > 电脑/网络

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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.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.
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Instant Parallel Processing with Gearman

Instant Parallel Processing with Gearman

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1. Instant Parallel Processing with Gearman

So, what is Gearman?

Distinguishing features of Gearman

Overview of components

The conversation between the actors

Usecase – image processing

Quick Start – building your first components

Step 1 – running a server

Step 2 – downloading a client library

Your first client

Writing the client

Running your newly created client

Verifying that it was submitted

Step 3 – our first worker

Running your newly created worker

Step 4 – varying priorities

Step 5 – background tasks

And that's it

Top 5 features you need to know about

Job handling

Completed versus successful

Unique identifiers and coalescing

The client

The worker

Making it work

Scaling your system

Running multiple managers

Writing a client that supports multiple managers

Submitting jobs to multiple managers

Handling a manager being terminated

Processing jobs from multiple managers

MapReduce

The shared library

A simple program

The client

The worker

Parallelizing the pipeline

Scaling this solution

Processing a large data file

Providing job updates

Data updates

The worker

The client

Status updates

The worker

The client

Building a processing pipeline

Using multiple languages

Persistence engines

Why is this important?

Persistent versus non-persistent

How safe is safe?

People and places you should get to know

Client libraries

Community

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