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