The MySQL FLOAT data type is a numeric data type used to store single-precision floating-point numbers. Floating-point numbers are those that have a decimal point or are expressed in exponential notation. The FLOAT data type is commonly used when precision is not a critical concern, and storage efficiency is important.
Here are some key characteristics of the MySQL FLOAT data type:
Precision and Range
The FLOAT data type in MySQL is a 4-byte single-precision floating-point number.
It can store values ranging from -3.4028235e+38 to -1.17549435e-38, 0, and 1.17549435e-38 to 3.4028235e+38.
Storage Size
The storage size for a FLOAT column is 4 bytes, regardless of the number of digits specified in the declaration.
This makes FLOAT more space-efficient compared to the DOUBLE data type, which is a double-precision floating-point number and requires 8 bytes.
Syntax for Declaration
When defining a column with the FLOAT data type, you can specify the display width, which represents the number of digits to the right of the decimal point. However, this is optional.
CREATE TABLE example_table (
my_float_column FLOAT(4,2)
);
In the example above, 4 is the total number of digits, and 2 is the number of digits to the right of the decimal point.
Floating-Point Precision Issues
Due to the nature of floating-point arithmetic, there may be precision issues when performing calculations with FLOAT numbers. This is important to keep in mind, especially when dealing with financial data or any scenario where precision is crucial.
Usage
FLOAT is suitable for scenarios where a moderate level of precision is acceptable, and there is a need to conserve storage space.
It is commonly used for scientific computations, statistical analysis, and other applications where the precision of floating-point numbers is sufficient.
Comparison
When comparing FLOAT values, it is advisable to use a small tolerance value to account for potential rounding errors introduced by floating-point arithmetic.
In summary, the MySQL FLOAT data type is a space-efficient way to store floating-point numbers with moderate precision. It is suitable for scenarios where the exact precision of the data is not critical, and storage efficiency is a priority. However, developers should be cautious about precision issues inherent in floating-point arithmetic when working with FLOAT data. If higher precision is required, the DOUBLE data type may be more appropriate, despite the increased storage size.