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Key benefits

You'll learn to write data processing programs in Python that are highly available, reliable, and fault tolerant

Make use of Amazon Web Services along with Python to establish a powerful remote computation system

Train Python to handle data-intensive and resource hungry applications

Description

CPU-intensive data processing tasks have become crucial considering the complexity of the various big data applications that are used today. Reducing the CPU utilization per process is very important to improve the overall speed of applications. This book will teach you how to perform parallel execution of computations by distributing them across multiple processors in a single machine, thus improving the overall performance of a big data processing task. We will cover synchronous and asynchronous models, shared memory and file systems, communication between various processes, synchronization, and more.

What you will learn

Get an introduction to parallel and distributed computing

See synchronous and asynchronous programming

Explore parallelism in Python

Distributed application with Celery

Python in the Cloud

Python on an HPC cluster

Test and debug distributed applications

What do you get with Print?

Instant access to your digital eBook copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Download this book in EPUB and PDF formats

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Frequently bought together

Learning Predictive Analytics with Python

zł221.99

zł157.99

Designing Machine Learning Systems with Python

zł197.99

Total zł 577.97

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Hugo Jun 20, 2021

Es werden die wichtigsten Mechanismen des distributed/parallel computing gut erklärt.

Amazon Verified review

Stefan Mar 23, 2017

I needed a crash course on distributed programming and I got it out of this book. I had a week to learn about concurrency, threading, multiprocessing and how they are implemented in Python and I suceeded with this. I feel confident to jump into harder texts and tutorials and other frameworks now. This book will *not* give you an in-depth coverage of the topics, it is only about 120 pages of content. Perfect for my purpose, thank you.

Phil Dec 18, 2017

This is a very light introduction to distributed computing with Python, which could really do with more information. It introduces important concepts but then moves straight on without getting into any detail. (ie. it mentions two communication methods between processes in the multiprocessing module, pipes and queues, and then ignores pipes altogether). If you've never touched distributing computing this might be a good starting point, but the python docs for the modules give far more detail and are almost as accessible (and free). Additionally there are quite a few errors in the book, at least one of which says the exact opposite of what it should, which might be very confusing for a reader.

Distributed Computing with Python: Harness the power of multiple computers using Python through this fast-paced informative guide

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