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0.10 (stable)
Numeric Types

Integer Types

The types TINYINT, SMALLINT, INTEGER, BIGINT and HUGEINT store whole numbers, that is, numbers without fractional components, of various ranges. Attempts to store values outside of the allowed range will result in an error. The types UTINYINT, USMALLINT, UINTEGER, UBIGINT and UHUGEINT store whole unsigned numbers. Attempts to store negative numbers or values outside of the allowed range will result in an error

Name Aliases Min Max
TINYINT INT1 -128 127
SMALLINT INT2, SHORT -32768 32767
INTEGER INT4, INT, SIGNED -2147483648 2147483647
BIGINT INT8, LONG -9223372036854775808 9223372036854775807
HUGEINT - -170141183460469231731687303715884105728 170141183460469231731687303715884105727
UTINYINT - 0 255
USMALLINT - 0 65535
UINTEGER - 0 4294967295
UBIGINT - 0 18446744073709551615
UHUGEINT - 0 340282366920938463463374607431768211455

The type integer is the common choice, as it offers the best balance between range, storage size, and performance. The SMALLINT type is generally only used if disk space is at a premium. The BIGINT and HUGEINT types are designed to be used when the range of the integer type is insufficient.

Fixed-Point Decimals

The data type DECIMAL(WIDTH, SCALE) (also available under the alias NUMERIC(WIDTH, SCALE)) represents an exact fixed-point decimal value. When creating a value of type DECIMAL, the WIDTH and SCALE can be specified to define which size of decimal values can be held in the field. The WIDTH field determines how many digits can be held, and the scale determines the amount of digits after the decimal point. For example, the type DECIMAL(3, 2) can fit the value 1.23, but cannot fit the value 12.3 or the value 1.234. The default WIDTH and SCALE is DECIMAL(18, 3), if none are specified.

Internally, decimals are represented as integers depending on their specified width.

Width Internal Size (Bytes)
1-4 INT16 2
5-9 INT32 4
10-18 INT64 8
19-38 INT128 16

Performance can be impacted by using too large decimals when not required. In particular decimal values with a width above 19 are slow, as arithmetic involving the INT128 type is much more expensive than operations involving the INT32 or INT64 types. It is therefore recommended to stick with a width of 18 or below, unless there is a good reason for why this is insufficient.

Floating-Point Types

The data types REAL and DOUBLE precision are inexact, variable-precision numeric types. In practice, these types are usually implementations of IEEE Standard 754 for Binary Floating-Point Arithmetic (single and double precision, respectively), to the extent that the underlying processor, operating system, and compiler support it.

Name Aliases Description
REAL FLOAT4, FLOAT single precision floating-point number (4 bytes)
DOUBLE FLOAT8 double precision floating-point number (8 bytes)

Inexact means that some values cannot be converted exactly to the internal format and are stored as approximations, so that storing and retrieving a value might show slight discrepancies. Managing these errors and how they propagate through calculations is the subject of an entire branch of mathematics and computer science and will not be discussed here, except for the following points:

  • If you require exact storage and calculations (such as for monetary amounts), use the DECIMAL data type or its NUMERIC alias instead.
  • If you want to do complicated calculations with these types for anything important, especially if you rely on certain behavior in boundary cases (infinity, underflow), you should evaluate the implementation carefully.
  • Comparing two floating-point values for equality might not always work as expected.

On most platforms, the REAL type has a range of at least 1E-37 to 1E+37 with a precision of at least 6 decimal digits. The DOUBLE type typically has a range of around 1E-307 to 1E+308 with a precision of at least 15 digits. Values that are too large or too small will cause an error. Rounding might take place if the precision of an input number is too high. Numbers too close to zero that are not representable as distinct from zero will cause an underflow error.

In addition to ordinary numeric values, the floating-point types have several special values:

  • Infinity
  • -Infinity
  • NaN

These represent the IEEE 754 special values “infinity”, “negative infinity”, and “not-a-number”, respectively. (On a machine whose floating-point arithmetic does not follow IEEE 754, these values will probably not work as expected.) When writing these values as constants in an SQL command, you must put quotes around them, for example: UPDATE table SET x = '-Infinity'. On input, these strings are recognized in a case-insensitive manner.

Universally Unique Identifiers (UUIDs)

DuckDB supports universally unique identifiers (UUIDs) through the UUID type. These use 128 bits and are represented internally as HUGEINT values. When printed, they are shown with hexadecimal characters, separated by dashes as follows: ⟨8 characters⟩-⟨4 characters⟩-⟨4 characters⟩-⟨4 characters⟩-⟨12 characters⟩ (using 36 characters in total). For example, 4ac7a9e9-607c-4c8a-84f3-843f0191e3fd is a valid UUID.

To generate a new UUID, use the uuid() utility function.

Functions

See Numeric Functions and Operators.

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Last modified: 2024-03-19