References
Data Types
Float

Reference: Float Type

The types double precision, float, and real are floating-point numbers. Depending on the precision, they are stored in an four or eight-byte IEEE 754 format.

⚠️
The double precision type is not suitable for conducting precise calculations, which are essential, for instance, when handling monetary values.

Usage Example 

create table constants (
    name text,
    value real
);
insert into constants
    values ('pi', 3.141592653589793238462643383279502884),
           ('planck', 6.62607015e-34),
           ('avogadro', 6.02214076e23);
select * from constants;
   name   |    value 
----------+--------------
 pi       |     3.14159
 planck   | 6.62607e-34
 avogadro | 6.02214e+23
(3 rows)

IEEE Special Values

If you need IEEE 754 special values, you need to enter them with explicitly typed literal syntax:

select real 'nan', real 'inf', real '-0';
 ?column? | ?column? | ?column? 
----------+----------+----------
      NaN | Infinity |       -0
(1 row)

Precision

Depending on the type size, the precision varies.

Data TypeApproximate PrecisionStorage SizeNotes
REAL~6 decimal digits4 bytesTypically referred to as float in C
DOUBLE PRECISION~15 decimal digits8 bytesTypically referred to as double in C
FLOAT(p)Depends on p4 or 8 bytesp ≤ 24 => REAL, 24 < p ≤ 53 => DOUBLE PRECISION.

Beware of the limited floating-point precision, where rounding errors can quickly add up, and can lead to subtle errors. Consider, e.g., the following query:

with x(i) as (
    values (0.1), 
           (0.2), 
           (-0.3)
) 
select sum(i::double precision) from x;
         sum          
----------------------
 5.55111512312578e-17
(1 row)

With exact-precision numeric types, the result of the query would be 0. However, with double precision, the result is only close to zero.

The result also is not stable, i.e., can change indeterministically when repeated: CedarDB executes queries in parallel and thus cannot guarantee the order in which the numbers are added. For the above query, an equally valid result would be:

         sum          
----------------------
 2.77555756156289e-17
(1 row)
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