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Distributed Computing with Python

You're reading from   Distributed Computing with Python Harness the power of multiple computers using Python through this fast-paced informative guide

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Product type Paperback
Published in Apr 2016
Publisher
ISBN-13 9781785889691
Length 170 pages
Edition 1st Edition
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Author (1):
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Rasheedh B Rasheedh B
Author Profile Icon Rasheedh B
Rasheedh B
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Table of Contents (10) Chapters Close

Preface 1. An Introduction to Parallel and Distributed Computing 2. Asynchronous Programming FREE CHAPTER 3. Parallelism in Python 4. Distributed Applications – with Celery 5. Python in the Cloud 6. Python on an HPC Cluster 7. Testing and Debugging Distributed Applications 8. The Road Ahead Index

Common problems – clocks and time


Time is a handy variable for use. For instance, using timestamps is very natural when we want to join different streams of data, sort database records, and in general, reconstruct the timeline for a series of events, which we oftentimes observe out of order. In addition, some tools (for example, GNU make) rely solely on file modification time and are easily confused by a clock skew between machines.

For these reasons, clock synchronization among all computers and systems we use is very important. If our computers are in different time zones, we might want to not only synchronize their clocks but also set them to Coordinated Universal Time (UTC) for simplicity. In all the cases, when changing clocks to UTC is not possible, a good piece of advice is to always process time in UTC within our code and to only convert to local time for display purposes.

In general, clock synchronization in distributed systems is a fascinating and complex topic, and it is out of...

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