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2019 | OriginalPaper | Chapter

16. Understand SQL Performance with Algorithm Analysis

Author : Jon Heller

Published in: Pro Oracle SQL Development

Publisher: Apress

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Abstract

Solving Oracle SQL performance issues is the pinnacle of SQL development. Performance tuning requires a combination of all the skills previously discussed in this book. We need to understand the development process (to know why problems happened and weren’t caught sooner), advanced features (to find alternative ways to implement code), and programming styles (in order to understand the code and rewrite it into something better).

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Footnotes
1
This book uses the word “steps” to refer to the work performed by algorithms. Traditionally, that value is named “operations.” But Oracle execution plans already prominently use the word “operation,” so it would be confusing if I used the standard name. This chapter isn’t a mathematical proof, so it doesn’t matter if our terminology is nonstandard.
 
2
See this Stack Overflow answer, where I try and fail to create a useful constant-time index using hash clusters: https://stackoverflow.com/questions/32071259/constant-time-index-for-string-column-on-oracle-database
 
3
Amdahl’s law is not a worst-case run time complexity. But the function is important for understanding performance and worth discussing here.
 
4
If we set the SQL_ID parameter to the top-level PL/SQL statement, DBMS_SQLTUNE.REPORT_SQL_MONITOR will generate an activity graph for all child SQL statements.
 
5
See my Stack Overflow answer here for more details: https://stackoverflow.com/q/43131204/409172 .
 
6
See my answer here for tests comparing sort-merge with hash: https://stackoverflow.com/a/8548454/409172 . When available, hash joins are always faster.
 
7
Oracle uses an algorithm called HyperLogLog for distinct count approximations.
 
Metadata
Title
Understand SQL Performance with Algorithm Analysis
Author
Jon Heller
Copyright Year
2019
Publisher
Apress
DOI
https://doi.org/10.1007/978-1-4842-4517-0_16

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