- B-tree indexes: These are the most common type of index used in MariaDB. They use a balanced tree data structure to store the index keys and their corresponding row IDs. B-tree indexes can be used to optimize queries that involve range conditions, such as WHERE clauses with inequality operators (<, >, <=, >=) or BETWEEN conditions.
Example:
CREATE INDEX my_index ON mytable (column1, column2);
2. Hash indexes: These indexes use a hash function to map index keys to their corresponding row IDs. Hash indexes are particularly useful for equality-based lookups, such as WHERE clauses with the = operator. However, they do not work well with range queries.
Example:
CREATE INDEX my_index ON mytable (column) USING HASH;
- Full-text indexes: These indexes are used for full-text searches. They allow for fast searching of text fields using natural language queries. Full-text indexes use a variation of the inverted index data structure, where the index keys are the words in the text and the corresponding row IDs are the documents that contain those words.
Example:
CREATE FULLTEXT INDEX my_index ON mytable (column);
- Spatial indexes: These indexes are used for spatial data, such as geographic coordinates. They use a variant of the R-tree data structure to store the index keys and their corresponding row IDs. Spatial indexes can be used to optimize queries that involve spatial relationships, such as finding points within a certain distance of a given location.
Example:
CREATE SPATIAL INDEX my_index ON mytable (column);
- Prefix indexes: These indexes are a type of B-tree index that indexes only the first few characters of a column. Prefix indexes can be useful for optimizing queries that involve LIKE conditions with a wildcard at the end of the string.
Example:
CREATE INDEX my_index ON mytable (column(10));
In summary, indexes are an important tool for optimizing database performance, and MariaDB offers several different types of indexes to choose from, depending on the specific requirements of your application. It’s important to choose the right type of index for each use case to ensure the best possible performance.
