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Hands-on lab series focused on practical techniques to enhance database performance. Topics include schema design, query optimization, indexing strategies, join tuning, and concurrency control. Inspired by real-world workloads and concepts from database performance literature.

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Database Tuning

Database Tuning course, based on the book:

Database Tuning: Principles, Experiments, and Troubleshooting Techniques
by Dennis Shasha & Philippe Bonnet
(The Morgan Kaufmann Series in Data Management Systems)

This repository contains solutions, experiments, and documentation for 6 lab exercises covering essential techniques for optimizing database performance.


Mainly Used

PostgreSQL Python SQLite Bash


Course Overview

The course focuses on practical techniques to improve database performance through schema design, indexing, query formulation, concurrency handling, and tuning strategies.
The experiments are based on real-world workloads and performance metrics, inspired by the concepts in the book.


Lab Structure

Lab Topic Description
1 Database Creation & Insertion Schema design and efficient data insertion strategies
2 Query Tuning Analyzing and optimizing SQL queries using execution plans
3 Index Tuning Theory Identifying different indexes to improve performance
4 Index Tuning Practice Clustered / Unclustered BTree, Hash Index
5 Join Tuning Join algorithms, reordering joins, and cost estimation
6 Concurrency Tuning Transactions, isolation levels

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Hands-on lab series focused on practical techniques to enhance database performance. Topics include schema design, query optimization, indexing strategies, join tuning, and concurrency control. Inspired by real-world workloads and concepts from database performance literature.

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