Understanding Composite Indexes in SQL

How Composite Indexes Improve Query Performance

When a query filters on multiple columns included in a composite index, the database can use the index to quickly find matching rows without scanning the entire table.

Composite indexes reduce the number of disk reads and CPU cycles needed for complex queries.

• Speeds up WHERE clause conditions involving multiple columns.
• Optimizes ORDER BY and GROUP BY operations on indexed columns.
• Helps in JOIN operations when joining on multiple columns.

Importance of Column Order in Composite Indexes

The order of columns in a composite index matters because the index is sorted first by the first column, then by the second, and so on.

Queries filtering on the leading columns can fully utilize the index, while filtering only on later columns may not use the index efficiently.

• Index on (A, B) can speed up queries filtering on A or on both A and B.
• Queries filtering only on B may not benefit from the index on (A, B).
• Design indexes based on the most common query patterns.

Example of Creating and Using a Composite Index

Consider a table named 'Orders' with columns 'customer_id', 'order_date', and 'status'.

Creating a composite index on (customer_id, order_date) helps queries filtering by customer and date.

SQL Example

Here is how to create a composite index and use it in a query.