
Lesson 36 of the SQL Optimization Course: Time-Based Partitioning Case Study
Time-based partitioning in MySQL optimizes query performance for large datasets by enabling partition pruning and automated data lifecycle management.

Time-based partitioning in MySQL optimizes query performance for large datasets by enabling partition pruning and automated data lifecycle management.

Explore MySQL's native horizontal sharding methods using MERGE tables. Learn benefits, limitations, and practical use cases for optimizing large-scale databases.

Explore how MySQL’s multi-valued indexes revolutionize query optimization by enabling efficient array-based searches, surpassing traditional index limits, and streamlining complex schema designs.

This article explores MySQL composite index unsuitable scenarios and optimization strategies through detailed SQL execution plan analyses.

Learn when and how to use composite indexes in SQL Server for optimized query performance.

Discover how MySQL functional indexes optimize query performance and simplify complex data retrieval.

Explore how MySQL prefix indexes optimize query performance and storage efficiency.

Explore hash tables and MySQL hash indexes to optimize database performance and improve query efficiency.

Explore MySQL primary key design best practices, including space efficiency, ordering, data types, and alternatives to UUIDs for optimal performance.

Adjusting MERGE_THRESHOLD optimizes data page merging and splitting in MySQL InnoDB, enhancing performance.