How does a bitmap index improve query performance?

A bitmap index improves query performance by allowing rapid searching, sorting and retrieval of records in a database.

A bitmap index is a special kind of database index that uses bitmaps and can be used to speed up data retrieval in databases. It is particularly effective when dealing with data that has a limited number of distinct values, such as gender, age groups, or yes/no fields. This is because it uses a binary representation (0s and 1s) to denote the presence or absence of a value in a record, which can be processed very quickly by computers.

The way a bitmap index works is by creating a separate bitmap for each distinct value in the indexed column. Each bit in the bitmap corresponds to a single record in the database table. If the record has the indexed value, the bit is set to 1; otherwise, it is set to 0. For example, if we have a 'gender' column in a table with 1000 records, we would have two bitmaps of 1000 bits each, one for 'male' and one for 'female'. Each bit in the 'male' bitmap would be set to 1 if the corresponding record is for a male, and 0 otherwise. The same applies to the 'female' bitmap.

This binary representation allows for very efficient Boolean operations, such as AND, OR and NOT, which are often used in database queries. For instance, if we want to find all records that are for males AND are in a certain age group, the database system can simply perform a bitwise AND operation on the corresponding bitmaps. This is much faster than scanning through all the records in the table.

Moreover, bitmap indexes are highly compressible, which means they can take up less storage space than other types of indexes. This can further improve query performance by reducing the amount of data that needs to be read from disk.

However, it's worth noting that bitmap indexes are not suitable for all situations. They work best with low-cardinality data, i.e., data with few distinct values. For high-cardinality data, such as unique IDs, other types of indexes, like B-trees, are usually more efficient. Also, bitmap indexes can be slow to update, so they are not ideal for tables that are frequently modified.