PostgreSQL 7.4 Documentation | ||||
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**Table of Contents**- 8.1. Numeric Types
- 8.1.1. Integer Types
- 8.1.2. Arbitrary Precision Numbers
- 8.1.3. Floating-Point Types
- 8.1.4. Serial Types

- 8.2. Monetary Types
- 8.3. Character Types
- 8.4. Binary Data Types
- 8.5. Date/Time Types
- 8.5.1. Date/Time Input
- 8.5.2. Date/Time Output
- 8.5.3. Time Zones
- 8.5.4. Internals

- 8.6. Boolean Type
- 8.7. Geometric Types
- 8.8. Network Address Types
- 8.8.1.
`inet` - 8.8.2.
`cidr` - 8.8.3.
`inet`vs.`cidr` - 8.8.4.
`macaddr`

- 8.8.1.
- 8.9. Bit String Types
- 8.10. Arrays
- 8.10.1. Declaration of Array Types
- 8.10.2. Array Value Input
- 8.10.3. Accessing Arrays
- 8.10.4. Modifying Arrays
- 8.10.5. Searching in Arrays
- 8.10.6. Array Input and Output Syntax

- 8.11. Object Identifier Types
- 8.12. Pseudo-Types

PostgreSQL has a rich set of native data
types available to users.
Users may add new types to PostgreSQL using the
`CREATE TYPE` command.

Table 8-1 shows all built-in general-purpose data types. Most of the alternative names listed in the "Aliases" column are the names used internally by PostgreSQL for historical reasons. In addition, some internally used or deprecated types are available, but they are not listed here.

**Table 8-1. Data Types**

Name | Aliases | Description |
---|---|---|

bigint | int8 | signed eight-byte integer |

bigserial | serial8 | autoincrementing eight-byte integer |

bit | fixed-length bit string | |

bit varying(n) | varbit(n) | variable-length bit string |

boolean | bool | logical Boolean (true/false) |

box | rectangular box in the plane | |

bytea | binary data | |

character varying(n) | varchar(n) | variable-length character string |

character(n) | char(n) | fixed-length character string |

cidr | IPv4 or IPv6 network address | |

circle | circle in the plane | |

date | calendar date (year, month, day) | |

double precision | float8 | double precision floating-point number |

inet | IPv4 or IPv6 host address | |

integer | int, int4 | signed four-byte integer |

interval(p) | time span | |

line | infinite line in the plane (not fully implemented) | |

lseg | line segment in the plane | |

macaddr | MAC address | |

money | currency amount | |

numeric [ (p,
s) ] | decimal [ (p,
s) ] | exact numeric with selectable precision |

path | open and closed geometric path in the plane | |

point | geometric point in the plane | |

polygon | closed geometric path in the plane | |

real | float4 | single precision floating-point number |

smallint | int2 | signed two-byte integer |

serial | serial4 | autoincrementing four-byte integer |

text | variable-length character string | |

time [ (p) ] [ without time zone ] | time of day | |

time [ (p) ] with time zone | timetz | time of day, including time zone |

timestamp [ (p) ] without time zone | timestamp | date and time |

timestamp [ (p) ] [ with time zone ] | timestamptz | date and time, including time zone |

Compatibility:The following types (or spellings thereof) are specified by SQL:bit,bit varying,boolean,char,character varying,character,varchar,date,double precision,integer,interval,numeric,decimal,real,smallint,time(with or without time zone),timestamp(with or without time zone).

Each data type has an external representation determined by its input and output functions. Many of the built-in types have obvious external formats. However, several types are either unique to PostgreSQL, such as open and closed paths, or have several possibilities for formats, such as the date and time types. Some of the input and output functions are not invertible. That is, the result of an output function may lose accuracy when compared to the original input.

Some of the operators and functions (e.g., addition and multiplication) do not perform run-time error-checking in the interests of improving execution speed. On some systems, for example, the numeric operators for some data types may silently cause underflow or overflow.

Numeric types consist of two-, four-, and eight-byte integers, four- and eight-byte floating-point numbers, and fixed-precision decimals. Table 8-2 lists the available types.

**Table 8-2. Numeric Types**

Name | Storage Size | Description | Range |
---|---|---|---|

smallint | 2 bytes | small-range integer | -32768 to +32767 |

integer | 4 bytes | usual choice for integer | -2147483648 to +2147483647 |

bigint | 8 bytes | large-range integer | -9223372036854775808 to 9223372036854775807 |

decimal | variable | user-specified precision, exact | no limit |

numeric | variable | user-specified precision, exact | no limit |

real | 4 bytes | variable-precision, inexact | 6 decimal digits precision |

double precision | 8 bytes | variable-precision, inexact | 15 decimal digits precision |

serial | 4 bytes | autoincrementing integer | 1 to 2147483647 |

bigserial | 8 bytes | large autoincrementing integer | 1 to 9223372036854775807 |

The syntax of constants for the numeric types is described in Section 4.1.2. The numeric types have a full set of corresponding arithmetic operators and functions. Refer to Chapter 9 for more information. The following sections describe the types in detail.

The types `smallint`, `integer`, and
`bigint` 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 type `integer` is the usual 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` type should only
be used if the `integer` range is not sufficient,
because the latter is definitely faster.

The `bigint` type may not function correctly on all
platforms, since it relies on compiler support for eight-byte
integers. On a machine without such support, `bigint`
acts the same as `integer` (but still takes up eight
bytes of storage). However, we are not aware of any reasonable
platform where this is actually the case.

SQL only specifies the integer types
`integer` (or `int`) and
`smallint`. The type `bigint`, and the
type names `int2`, `int4`, and
`int8` are extensions, which are shared with various
other SQL database systems.

Note:If you have a column of typesmallintorbigintwith an index, you may encounter problems getting the system to use that index. For instance, a clause of the form... WHERE smallint_column = 42will not use an index, because the system assigns type

integerto the constant 42, and PostgreSQL currently cannot use an index when two different data types are involved. A workaround is to single-quote the constant, thus:... WHERE smallint_column = '42'This will cause the system to delay type resolution and will assign the right type to the constant.

The type `numeric` can store numbers with up to 1000
digits of precision and perform calculations exactly. It is
especially recommended for storing monetary amounts and other
quantities where exactness is required. However, the
`numeric` type is very slow compared to the
floating-point types described in the next section.

In what follows we use these terms: The
*scale* of a `numeric` is the
count of decimal digits in the fractional part, to the right of
the decimal point. The *precision* of a
`numeric` is the total count of significant digits in
the whole number, that is, the number of digits to both sides of
the decimal point. So the number 23.5141 has a precision of 6
and a scale of 4. Integers can be considered to have a scale of
zero.

Both the precision and the scale of the numeric type can be
configured. To declare a column of type `numeric` use
the syntax

NUMERIC(precision,scale)

The precision must be positive, the scale zero or positive. Alternatively,

NUMERIC(precision)

selects a scale of 0. Specifying

NUMERIC

without any precision or scale creates a column in which numeric
values of any precision and scale can be stored, up to the
implementation limit on precision. A column of this kind will
not coerce input values to any particular scale, whereas
`numeric` columns with a declared scale will coerce
input values to that scale. (The SQL standard
requires a default scale of 0, i.e., coercion to integer
precision. We find this a bit useless. If you're concerned
about portability, always specify the precision and scale
explicitly.)

If the precision or scale of a value is greater than the declared precision or scale of a column, the system will attempt to round the value. If the value cannot be rounded so as to satisfy the declared limits, an error is raised.

The types `decimal` and `numeric` are
equivalent. Both types are part of the SQL
standard.

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.

Inexact means that some values cannot be converted exactly to the internal format and are stored as approximations, so that storing and printing back out a value may 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 further here, except for the following points:

If you require exact storage and calculations (such as for monetary amounts), use the

`numeric`type 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 may or may not 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 precision` 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 may
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.

PostgreSQL also supports the SQL-standard
notations `float` and
`float( p)` for specifying
inexact numeric types. Here,

Note:Prior to PostgreSQL 7.4, the precision infloat(was taken to mean so many decimal digits. This has been corrected to match the SQL standard, which specifies that the precision is measured in binary digits. The assumption thatp)realanddouble precisionhave exactly 24 and 53 bits in the mantissa respectively is correct for IEEE-standard floating point implementations. On non-IEEE platforms it may be off a little, but for simplicity the same ranges ofpare used on all platforms.

The data types `serial` and `bigserial`
are not true types, but merely
a notational convenience for setting up unique identifier columns
(similar to the `AUTO_INCREMENT` property
supported by some other databases). In the current
implementation, specifying

CREATE TABLEtablename(colnameSERIAL );

is equivalent to specifying:

CREATE SEQUENCEtablename_colname_seq; CREATE TABLEtablename(colnameinteger DEFAULT nextval('tablename_colname_seq') NOT NULL );

Thus, we have created an integer column and arranged for its default
values to be assigned from a sequence generator. A `NOT NULL`
constraint is applied to ensure that a null value cannot be explicitly
inserted, either. In most cases you would also want to attach a
`UNIQUE` or `PRIMARY KEY` constraint to prevent
duplicate values from being inserted by accident, but this is
not automatic.

Note:Prior to PostgreSQL 7.3,serialimpliedUNIQUE. This is no longer automatic. If you wish a serial column to be in a unique constraint or a primary key, it must now be specified, same as with any other data type.

To insert the next value of the sequence into the `serial`
column, specify that the `serial`
column should be assigned its default value. This can be done
either by excluding the column from the list of columns in
the `INSERT` statement, or through the use of
the `DEFAULT` key word.

The type names `serial` and `serial4` are
equivalent: both create `integer` columns. The type
names `bigserial` and `serial8` work just
the same way, except that they create a `bigint`
column. `bigserial` should be used if you anticipate
the use of more than 2^{31} identifiers over the
lifetime of the table.

The sequence created for a `serial` column is
automatically dropped when the owning column is dropped, and
cannot be dropped otherwise. (This was not true in
PostgreSQL releases before 7.3. Note
that this automatic drop linkage will not occur for a sequence
created by reloading a dump from a pre-7.3 database; the dump
file does not contain the information needed to establish the
dependency link.) Furthermore, this dependency between sequence
and column is made only for the `serial` column itself; if
any other columns reference the sequence (perhaps by manually
calling the `nextval`

function), they will be broken
if the sequence is removed. Using a `serial` column's sequence
in such a fashion is considered bad form; if you wish to feed several
columns from the same sequence generator, create the sequence as an
independent object.