How to figure out size of Indexes in MySQL

In MySQL, calculating the size of an index requires understanding the database's storage structure and index types. MySQL commonly uses storage engines such as InnoDB and MyISAM, which have slightly different index storage methods. I will focus on how to calculate index size in the InnoDB storage engine.

Step 1: Understanding Index Types

In InnoDB, there are two main types of indexes: primary key indexes and secondary indexes (also known as auxiliary indexes). Primary key indexes are clustered indexes, where data records are stored directly in the leaf nodes of the B+ tree. Secondary indexes store the primary key values in their leaf nodes.

Step 2: Determining Index Composition

The size of an index depends on the data types and number of columns in the index. For example, an index consisting of one INT and one VARCHAR(100) will differ in size from an index containing only two INT columns.

Step 3: Calculating Index Size

Method 1: Using MySQL Queries

For InnoDB tables, you can directly query the size of tables and indexes using the TABLES and STATISTICS tables in the information_schema database. Here is an example:

sql
SELECT 
    table_name AS `Table`,
    index_name AS `Index`,
    round((stat_value*@@innodb_page_size)/1024/1024,2) AS `Size in MB`
FROM mysql.innodb_index_stats 
WHERE database_name='your_database_name' AND table_name='your_table_name' AND stat_name='size';

This SQL query will display the approximate size of each index for the specified table (in MB).

Method 2: Manual Estimation

1. Estimating Row Size: Determine the size of each row based on the data types of the columns in the index. For example, INT is typically 4 bytes, and VARCHAR is calculated based on the character count.
2. Calculating Row Count: Query the number of rows in the table.
3. Estimating Total Size: Multiply the row size by the row count, and add extra space required to maintain the B+ tree structure (typically adding 20-30% as redundancy).

Example

Assume a table named users has an index idx_user_email consisting of two fields: user_id (INT) and email (VARCHAR(100)). You can estimate the approximate size of this index as follows:

• INT occupies 4 bytes, and VARCHAR(100) occupies up to 100 bytes (assuming UTF-8 encoding, which may be larger).
• Assume the table has 10,000 rows of data.
• The index size is approximately: (4 + 100) * 10,000 = 1,040,000 bytes ≈ 0.99 MB
• Adding extra space for maintaining the B+ tree structure: 0.99 MB * 1.25 ≈ 1.2375 MB

This is a simple estimate; the actual size may vary due to factors such as encoding, handling of NULL values, and index fill factor. In practice, directly querying information_schema is more accurate and convenient.