MySQL Floating-Point Comparison Challenges

MySQL users often encounter inaccuracies when comparing floating-point values. Consider the following example:

CREATE TABLE users (points float);

INSERT INTO users VALUES (50.12);
INSERT INTO users VALUES (34.57);
INSERT INTO users VALUES (12.75);

The query SELECT COUNT(*) FROM users WHERE points > "12.75" returns 3, despite expecting a count of 2.

The Issue with Floating-Point Arithmetic

MySQL uses floating-point arithmetic to store and manipulate float type values. This system represents numbers using a combination of a significand (the actual number) and an exponent, resulting in potential precision issues. For instance, the value 12.75 may be stored as 12.75000005722 when entered into MySQL due to the binary representation of floating-point numbers.

Exact Decimal Representation

To avoid such inaccuracies, it's recommended to use the DECIMAL data type in MySQL for precise decimal representation. Unlike float, DECIMAL stores values as fixed-point numbers, ensuring exact precision.

Converting to DECIMAL

To convert an existing float column to DECIMAL, use the ALTER TABLE statement:

ALTER TABLE users MODIFY points DECIMAL(6,2);

This will convert points to a decimal column with 6 total digits and 2 decimal places. You can adjust the precision and scale as needed.

Conclusion

While float may seem convenient, the inherent inaccuracies in floating-point arithmetic can lead to unexpected results when comparing values. For precise decimal representation and accurate comparisons, it's strongly recommended to use the DECIMAL data type in MySQL. By using DECIMAL, you can avoid the potential pitfalls of floating-point comparisons and ensure the reliability of your data.