Performance Implications of Indexing Boolean Fields

In database systems, indexing fields improves query performance by allowing the database engine to quickly locate data without scanning the entire table. However, the performance gain of indexing boolean fields has been a topic of debate.

Does Indexing Boolean Fields Improve Performance?

When performing queries with clauses like WHERE boolean_field=true, indexing the boolean field can indeed enhance performance. Database engines like InnoDB utilize a special technique called bitmap indexing for boolean fields. This technique divides the table into partitions based on the field values (true/false).

How Bitmap Indexing Works

Bitmap indexing allocates a bit for each row in the table. If the bit is set to 1, it indicates that the corresponding row has the value true for the boolean field. The engine then creates an index containing these bitmaps.

When executing queries like WHERE boolean_field=true, the engine locates the partition corresponding to the value true. It then scans the bitmap to identify the rows that match the criterion, skipping the remaining rows in other partitions. This significantly reduces the number of rows that need to be checked compared to scanning the entire table.

Empirical Example

As mentioned in the answer provided, the addition of an index on a boolean field accelerated queries by orders of magnitude in a table with 4 million rows. The initial execution time of 9 seconds plummeted to a fraction of a second. This demonstrates the potential performance boost that bitmap indexing can provide.

Conclusion

Contrary to the notion that indexing boolean fields is futile, it can offer substantial performance gains in cases where the query specifically filters on the boolean field and the data distribution allows for effective use of bitmap indexing. Therefore, consider indexing boolean fields when the dataset exhibits a significant bias towards specific values or when the query workload frequently involves filtering on those fields.