Float32 | Float64 | BFloat16 Types

Documentation for floating-point data types in ClickHouse: Float32, Float64, and BFloat16

If you need accurate calculations, in particular if you work with financial or business data requiring a high precision, you should consider using Decimal instead.

Floating Point Numbers might lead to inaccurate results as illustrated below:

CREATE TABLE IF NOT EXISTS float_vs_decimal
(
   my_float Float64,
   my_decimal Decimal64(3)
)
ENGINE=MergeTree
ORDER BY tuple();

# Generate 1 000 000 random numbers with 2 decimal places and store them as a float and as a decimal
INSERT INTO float_vs_decimal SELECT round(randCanonical(), 3) AS res, res FROM system.numbers LIMIT 1000000;

SELECT sum(my_float), sum(my_decimal) FROM float_vs_decimal;

┌──────sum(my_float)─┬─sum(my_decimal)─┐
│ 499693.60500000004 │      499693.605 │
└────────────────────┴─────────────────┘

SELECT sumKahan(my_float), sumKahan(my_decimal) FROM float_vs_decimal;

┌─sumKahan(my_float)─┬─sumKahan(my_decimal)─┐
│         499693.605 │           499693.605 │
└────────────────────┴──────────────────────┘

The equivalent types in ClickHouse and in C are given below:

• Float32 — float.
• Float64 — double.

Float types in ClickHouse have the following aliases:

• Float32 — FLOAT, REAL, SINGLE.
• Float64 — DOUBLE, DOUBLE PRECISION.

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.

BFloat16

BFloat16 is a 16-bit floating point data type with 8-bit exponent, sign, and 7-bit mantissa. It is useful for machine learning and AI applications.

ClickHouse supports conversions between Float32 and BFloat16 which can be done using the toFloat32() or toBFloat16 functions.

Most other operations are not supported.