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Book details
Format: pdf
File Size: 7.67 MB
Print Length: 170 pages
Publisher: Packt Publishing; 1 edition (12 April 2016)
Sold by: Amazon Asia-Pacific Holdings Private Limited
Language: English
ASIN: B01AXR8JAC

Key Features

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
Book 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
Table of Contents

An Introduction to Parallel and Distributed Computing
Asynchronous Programming
Parallelism in Python
Distributed Applications – with Celery
Python in the Cloud
Python on an HPC Cluster
Testing and Debugging Distributed Applications
The Road Ahead