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MySQL for Python

You're reading from   MySQL for Python Integrating MySQL and Python can bring a whole new level of productivity to your applications. This practical tutorial shows you how with examples and explanations that clarify even the most difficult concepts.

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Product type Paperback
Published in Sep 2010
Publisher Packt
ISBN-13 9781849510189
Length 440 pages
Edition 1st Edition
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Author (1):
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Albert Lukaszewski Albert Lukaszewski
Author Profile Icon Albert Lukaszewski
Albert Lukaszewski
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Table of Contents (20) Chapters Close

MySQL for Python
Credits
About the Author
About the Reviewers
Preface
1. Getting Up and Running with MySQL for Python FREE CHAPTER 2. Simple Querying 3. Simple Insertion 4. Exception Handling 5. Results Record-by-Record 6. Inserting Multiple Entries 7. Creating and Dropping 8. Creating Users and Granting Access 9. Date and Time Values 10. Aggregate Functions and Clauses 11. SELECT Alternatives 12. String Functions 13. Showing MySQL Metadata 14. Disaster Recovery Index

Calculations in MySQL


Letting the database server take the burden of calculations can reduce latency across a network. Most web servers, for example, not only serve up web pages, but also perform the processing for any scripts used to form those pages. If the script needs to perform calculations of large amounts of data, the processing time of the server will increase accordingly. Similar bottlenecks can occur on LANs and even desktop systems that are normally optimized for user-based interactions, not heavy data processing.

Note

Computer clusters are another matter altogether. Depending on the size of the cluster, one can lay much heavier loads on individual machines and the cluster will be able to bear the burden. While using a cluster for processing data takes the load off the database server, this can still result in latency as one part of the processing machinery (the database) may operate much slower than the rest of the parts.

MySQL provides several optimized ways of performing calculations...

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