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Mastering matplotlib

You're reading from  Mastering matplotlib

Product type Book
Published in Jun 2015
Publisher
ISBN-13 9781783987542
Pages 292 pages
Edition 1st Edition
Languages
Authors (2):
Duncan M. McGreggor Duncan M. McGreggor
Profile icon Duncan M. McGreggor
Duncan M McGreggor Duncan M McGreggor
Profile icon Duncan M McGreggor
View More author details

Table of Contents (16) Chapters

Mastering matplotlib
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Getting Up to Speed 2. The matplotlib Architecture 3. matplotlib APIs and Integrations 4. Event Handling and Interactive Plots 5. High-level Plotting and Data Analysis 6. Customization and Configuration 7. Deploying matplotlib in Cloud Environments 8. matplotlib and Big Data 9. Clustering for matplotlib Index

The custom ZeroMQ cluster


In this section, we will create a task pipeline, which is a messaging pattern that we mentioned briefly when discussing the Disco project's answer to MapReduce. Task pipelines can be viewed as a generalization of MapReduce in that they support data flows through a sequence of steps, where each step provides the results from its processing to the next step in the flow. We will accomplish this by using ZeroMQ to create a messaging topology that is suitable for the execution of embarrassingly parallel code in a number of worker processes.

Note

The descriptive term embarrassingly parallel was adopted in online parallelization discussions after its use in an article named Matrix Computation on Distributed Memory Multiprocessors that was written by Cleve Moler. The parallelizing of serially biased code is notoriously difficult, and problems that were obviously or easily parallelizable were described by using this phrase.

ZeroMQ is an asynchronous messaging framework, which...

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