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Distributed Computing with Python
Key FeaturesYou'll learn to write data processing programs in Python that are highly available, reliable, and fault tolerantMake use of Amazon Web Services along with Python to establish a powerful remote computation systemTrain Python to handle data-intensive and resource hungry applicationsBook DescriptionCPU-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 LearnGet an introduction to parallel and distributed computingSee synchronous and asynchronous programmingExplore parallelism in PythonDistributed application with CeleryPython in the CloudPython on an HPC clusterTest and debug distributed applicationsAbout the AuthorFrancesco Pierfederici is a software engineer who loves Python. He has been working in the fields of astronomy, biology, and numerical weather forecasting for the last 20 years.
He has built large distributed systems that make use of tens of thousands of cores at a time and run on some of the fastest supercomputers in the world. He has also written a lot of applications of dubious usefulness but that are great fun. Mostly, he just likes to build things.
Table of ContentsAn Introduction to Parallel and Distributed ComputingAsynchronous ProgrammingParallelism in PythonDistributed Applications – with CeleryPython in the CloudPython on an HPC ClusterTesting and Debugging Distributed ApplicationsThe Road Ahead
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 LearnGet an introduction to parallel and distributed computingSee synchronous and asynchronous programmingExplore parallelism in PythonDistributed application with CeleryPython in the CloudPython on an HPC clusterTest and debug distributed applicationsAbout the AuthorFrancesco Pierfederici is a software engineer who loves Python. He has been working in the fields of astronomy, biology, and numerical weather forecasting for the last 20 years.
He has built large distributed systems that make use of tens of thousands of cores at a time and run on some of the fastest supercomputers in the world. He has also written a lot of applications of dubious usefulness but that are great fun. Mostly, he just likes to build things.
Table of ContentsAn Introduction to Parallel and Distributed ComputingAsynchronous ProgrammingParallelism in PythonDistributed Applications – with CeleryPython in the CloudPython on an HPC ClusterTesting and Debugging Distributed ApplicationsThe Road Ahead
- GenresNonfiction
267 pages, Kindle Edition
Published April 12, 2016
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11 people want to read
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Displaying 1 of 1 review
December 2, 2016
Very short and very shallow. If I had to pay for this book I would ask for the refund, since you can get pretty much the same information from just reading few blog posts and Celery documentation.
In fact, after thinking about it - my biggest gripe with books like this is not necessarily their length or their level of deepness/shallowness. It is fine to be concise and there's nothing wrong in providing a high-level overview. The problem in my opinion is a contrast between very high-level chapters describing general approach to the distributed computing and very detailed chapters instructing you how to setup, for example, an account with AWS. Those two things are just not good together.
In fact, after thinking about it - my biggest gripe with books like this is not necessarily their length or their level of deepness/shallowness. It is fine to be concise and there's nothing wrong in providing a high-level overview. The problem in my opinion is a contrast between very high-level chapters describing general approach to the distributed computing and very detailed chapters instructing you how to setup, for example, an account with AWS. Those two things are just not good together.
Displaying 1 of 1 review