SQL queries can be fast and highly efficient, but they can also be slow and demand excessive CPU and memory resources. For many SQL programmers, occasional bouts with long-running queries and poor performance are simply par for the course. But by gaining a better understanding of how databases translate SQL queries into execution plans, you can take steps to avoid these issues. In this course, Dan Sullivan shows developers how to analyze query execution plans and use data modeling strategies to boost query performance. Dan describes how SQL queries are executed; highlights different types of indexes and how they factor in query tuning; covers several methods for performing joins; and discusses how to use partitioning and materialized views to improve performance.

Topics include:

How SQL executes queries

Working with PostgreSQL tools for tuning

Bitmap and hash indexes

Using different types of indexes to improve performance

Challenges with joining tables

When to use partitioning to improve performance

Collecting statistics about data in tables

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