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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.

Aliases:

  • Float32 — FLOAT.
  • Float64 — DOUBLE.

When creating tables, numeric parameters for floating point numbers can be set (e.g. FLOAT(12), FLOAT(15, 22), DOUBLE(12), DOUBLE(4, 18)), but ClickHouse ignores them.

Using Floating-point Numbers​

  • Computations with floating-point numbers might produce a rounding error.
SELECT 1 - 0.9
┌───────minus(1, 0.9)─┐
│ 0.09999999999999998 │
└─────────────────────┘
  • 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.
SELECT 0.5 / 0
┌─divide(0.5, 0)─┐
│            inf │
└────────────────┘
  • -Inf — Negative infinity.
SELECT -0.5 / 0
┌─divide(-0.5, 0)─┐
│            -inf │
└─────────────────┘
  • NaN — Not a number.
SELECT 0 / 0
┌─divide(0, 0)─┐
│          nan │
└──────────────┘

See the rules for NaN sorting in the section ORDER BY clause.

Original article