Float32, Float64

Floating point numbers.

Types are equivalent to types of C:

  • Float32 - float
  • Float64 - double

We recommend that you store data in integer form whenever possible. For example, convert fixed precision numbers to integer values, such as monetary amounts or page load times in milliseconds.

Using Floating-point Numbers

  • Computations with floating-point numbers might produce a rounding error.
  1. SELECT 1 - 0.9
  1. ┌───────minus(1, 0.9)─┐
  2. │ 0.09999999999999998 │
  3. └─────────────────────┘
  • The result of the calculation depends on the calculation method (the processor type and architecture of the computer system).
  • Floating-point calculations might result in numbers such as infinity (Inf) and “not-a-number” (NaN). This should be taken into account when processing the results of calculations.
  • When parsing floating-point numbers from text, the result might not be the nearest machine-representable number.

NaN and Inf

In contrast to standard SQL, ClickHouse supports the following categories of floating-point numbers:

  • Inf – Infinity.
  1. SELECT 0.5 / 0
  1. ┌─divide(0.5, 0)─┐
  2. │            inf │
  3. └────────────────┘
  • -Inf – Negative infinity.
  1. SELECT -0.5 / 0
  1. ┌─divide(-0.5, 0)─┐
  2. │            -inf │
  3. └─────────────────┘
  • NaN – Not a number.
  1. SELECT 0 / 0
  1. ┌─divide(0, 0)─┐
  2. │          nan │
  3. └──────────────┘
  1. See the rules for `NaN` sorting in the section [ORDER BY clause](../sql_reference/statements/select/order-by.md).

Original article