Data Typesdata typetypedata typePostgreSQL has a rich set of native data
types available to users. Users can add new types to
PostgreSQL using the command.
shows all the 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 are not listed here.
Data TypesNameAliasesDescriptionbigintint8signed eight-byte integerbigserialserial8autoincrementing eight-byte integerbit [ (n) ]fixed-length bit stringbit varying [ (n) ]varbitvariable-length bit stringbooleanboollogical Boolean (true/false)boxrectangular box on a planebyteabinary data (byte array>)character [ (n) ]char [ (n) ]fixed-length character stringcharacter varying [ (n) ]varchar [ (n) ]variable-length character stringcidrIPv4 or IPv6 network addresscirclecircle on a planedatecalendar date (year, month, day)double precisionfloat8double precision floating-point number (8 bytes)inetIPv4 or IPv6 host addressintegerint, int4signed four-byte integerinterval [ fields ] [ (p) ]time spanjsontextual JSON datajsonbbinary JSON data, decomposedlineinfinite line on a planelsegline segment on a planemacaddrMAC (Media Access Control) addressmoneycurrency amountnumeric [ (p,
s) ]decimal [ (p,
s) ]exact numeric of selectable precisionpathgeometric path on a planepg_lsnPostgreSQL Log Sequence Numberpointgeometric point on a planepolygonclosed geometric path on a planerealfloat4single precision floating-point number (4 bytes)smallintint2signed two-byte integersmallserialserial2autoincrementing two-byte integerserialserial4autoincrementing four-byte integertextvariable-length character stringtime [ (p) ] [ without time zone ]time of day (no time zone)time [ (p) ] with time zonetimetztime of day, including time zonetimestamp [ (p) ] [ without time zone ]date and time (no time zone)timestamp [ (p) ] with time zonetimestamptzdate and time, including time zonetsquerytext search querytsvectortext search documenttxid_snapshotuser-level transaction ID snapshotuuiduniversally unique identifierxmlXML data
Compatibility
The following types (or spellings thereof) are specified by
SQL: bigint, 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),
xml.
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 geometric
paths, or have several possible formats, such as the date
and time types.
Some of the input and output functions are not invertible, i.e.,
the result of an output function might lose accuracy when compared to
the original input.
Numeric Typesdata typenumeric
Numeric types consist of two-, four-, and eight-byte integers,
four- and eight-byte floating-point numbers, and selectable-precision
decimals. lists the
available types.
Numeric TypesNameStorage SizeDescriptionRangesmallint>2 bytessmall-range integer-32768 to +32767integer>4 bytestypical choice for integer-2147483648 to +2147483647bigint>8 byteslarge-range integer-9223372036854775808 to +9223372036854775807decimal>variableuser-specified precision, exactup to 131072 digits before the decimal point; up to 16383 digits after the decimal pointnumeric>variableuser-specified precision, exactup to 131072 digits before the decimal point; up to 16383 digits after the decimal pointreal>4 bytesvariable-precision, inexact6 decimal digits precisiondouble precision>8 bytesvariable-precision, inexact15 decimal digits precisionsmallserial2 bytessmall autoincrementing integer1 to 32767serial>4 bytesautoincrementing integer1 to 2147483647bigserial8 byteslarge autoincrementing integer1 to 9223372036854775807
The syntax of constants for the numeric types is described in
. The numeric types have a
full set of corresponding arithmetic operators and
functions. Refer to for more
information. The following sections describe the types in detail.
Integer Typesintegersmallintbigintint4integerint2smallintint8bigint
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 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 type is designed to be
used when the range of the integer type is insufficient.
SQL only specifies the integer types
integer (or int),
smallint, and bigint. The
type names int2, int4, and
int8 are extensions, which are also used by some
other SQL database systems.
Arbitrary Precision Numbersnumeric (data type)arbitrary precision numbersdecimalnumeric
The type numeric can store numbers with a
very large number of digits. It is especially recommended for
storing monetary amounts and other quantities where exactness is
required. Calculations with numeric values yield exact
results where possible, e.g. addition, subtraction, multiplication.
However, calculations on numeric values are very slow
compared to the integer types, or to the floating-point types
described in the next section.
We use the following terms below: 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 maximum precision and the maximum scale of a
numeric column 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.)
The maximum allowed precision when explicitly specified in the
type declaration is 1000; NUMERIC without a specified
precision is subject to the limits described in .
If the scale of a value to be stored is greater than the declared
scale of the column, the system will round the value to the specified
number of fractional digits. Then, if the number of digits to the
left of the decimal point exceeds the declared precision minus the
declared scale, an error is raised.
Numeric values are physically stored without any extra leading or
trailing zeroes. Thus, the declared precision and scale of a column
are maximums, not fixed allocations. (In this sense the numeric>
type is more akin to varchar(n>)
than to char(n>).) The actual storage
requirement is two bytes for each group of four decimal digits,
plus three to eight bytes overhead.
NaNnot a numbernot a numbernumeric (data type)
In addition to ordinary numeric values, the numeric
type allows the special value NaN>, meaning
not-a-number. Any operation on NaN>
yields another NaN>. When writing this value
as a constant in an SQL command, you must put quotes around it,
for example UPDATE table SET x = 'NaN'>. On input,
the string NaN> is recognized in a case-insensitive manner.
In most implementations of the not-a-number> concept,
NaN> is not considered equal to any other numeric
value (including NaN>). In order to allow
numeric> values to be sorted and used in tree-based
indexes, PostgreSQL> treats NaN>
values as equal, and greater than all non-NaN>
values.
The types decimal and numeric are
equivalent. Both types are part of the SQL
standard.
When rounding values, the numeric type rounds ties away
from zero, while (on most machines) the real
and double precision types round ties to the nearest even
number. For example:
SELECT x,
round(x::numeric) AS num_round,
round(x::double precision) AS dbl_round
FROM generate_series(-3.5, 3.5, 1) as x;
x | num_round | dbl_round
------+-----------+-----------
-3.5 | -4 | -4
-2.5 | -3 | -2
-1.5 | -2 | -2
-0.5 | -1 | -0
0.5 | 1 | 0
1.5 | 2 | 2
2.5 | 3 | 2
3.5 | 4 | 4
(8 rows)
Floating-Point Typesrealdouble precisionfloat4realfloat8double precisionfloating point
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 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 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 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 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 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.
The setting controls the
number of extra significant digits included when a floating point
value is converted to text for output. With the default value of
0, the output is the same on every platform
supported by PostgreSQL. Increasing it will produce output that
more accurately represents the stored value, but may be unportable.
not a numberdouble precision
In addition to ordinary numeric values, the floating-point types
have several special values:
Infinity-InfinityNaN
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.
IEEE754 specifies that NaN> should not compare equal
to any other floating-point value (including NaN>).
In order to allow floating-point values to be sorted and used
in tree-based indexes, PostgreSQL> treats
NaN> values as equal, and greater than all
non-NaN> values.
PostgreSQL also supports the SQL-standard
notations float and
float(p) for specifying
inexact numeric types. Here, p specifies
the minimum acceptable precision in binary> digits.
PostgreSQL accepts
float(1) to float(24) as selecting the
real type, while
float(25) to float(53) select
double precision. Values of p
outside the allowed range draw an error.
float with no precision specified is taken to mean
double precision.
The assumption that real and
double precision have exactly 24 and 53 bits in the
mantissa respectively is correct for IEEE-standard floating point
implementations. On non-IEEE platforms it might be off a little, but
for simplicity the same ranges of p are used
on all platforms.
Serial Typessmallserialserialbigserialserial2serial4serial8auto-incrementserialsequenceand serial type
The data types smallserial, serial and
bigserial are not true types, but merely
a notational convenience for creating unique identifier columns
(similar to the AUTO_INCREMENT property
supported by some other databases). In the current
implementation, specifying:
CREATE TABLE tablename (
colname SERIAL
);
is equivalent to specifying:
CREATE SEQUENCE tablename_colname_seq;
CREATE TABLE tablename (
colname integer NOT NULL DEFAULT nextval('tablename_colname_seq')
);
ALTER SEQUENCE tablename_colname_seq OWNED BY tablename.colname;
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
inserted. (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.) Lastly, the sequence is marked as owned by>
the column, so that it will be dropped if the column or table is dropped.
Because smallserial, serial and
bigserial are implemented using sequences, there may
be "holes" or gaps in the sequence of values which appears in the
column, even if no rows are ever deleted. A value allocated
from the sequence is still "used up" even if a row containing that
value is never successfully inserted into the table column. This
may happen, for example, if the inserting transaction rolls back.
See nextval() in
for details.
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
the same way, except that they create a bigint
column. bigserial should be used if you anticipate
the use of more than 231> identifiers over the
lifetime of the table. The type names smallserial and
serial2 also work the same way, except that they
create a smallint column.
The sequence created for a serial column is
automatically dropped when the owning column is dropped.
You can drop the sequence without dropping the column, but this
will force removal of the column default expression.
Monetary Types
The money type stores a currency amount with a fixed
fractional precision; see . The fractional precision is
determined by the database's setting.
The range shown in the table assumes there are two fractional digits.
Input is accepted in a variety of formats, including integer and
floating-point literals, as well as typical
currency formatting, such as '$1,000.00'.
Output is generally in the latter form but depends on the locale.
Monetary TypesNameStorage SizeDescriptionRangemoney8 bytescurrency amount-92233720368547758.08 to +92233720368547758.07
Since the output of this data type is locale-sensitive, it might not
work to load money> data into a database that has a different
setting of lc_monetary>. To avoid problems, before
restoring a dump into a new database make sure lc_monetary> has
the same or equivalent value as in the database that was dumped.
Values of the numeric, int, and
bigint data types can be cast to money.
Conversion from the real and double precision
data types can be done by casting to numeric first, for
example:
SELECT '12.34'::float8::numeric::money;
However, this is not recommended. Floating point numbers should not be
used to handle money due to the potential for rounding errors.
A money value can be cast to numeric without
loss of precision. Conversion to other types could potentially lose
precision, and must also be done in two stages:
SELECT '52093.89'::money::numeric::float8;
When a money value is divided by another money
value, the result is double precision (i.e., a pure number,
not money); the currency units cancel each other out in the division.
Character Typescharacter stringdata typesstringcharacter stringcharactercharacter varyingtextcharvarchar
Character TypesNameDescriptioncharacter varying(n>), varchar(n>)variable-length with limitcharacter(n>), char(n>)fixed-length, blank paddedtextvariable unlimited length
shows the
general-purpose character types available in
PostgreSQL.
SQL defines two primary character types:
character varying(n>) and
character(n>), where n>
is a positive integer. Both of these types can store strings up to
n> characters (not bytes) in length. An attempt to store a
longer string into a column of these types will result in an
error, unless the excess characters are all spaces, in which case
the string will be truncated to the maximum length. (This somewhat
bizarre exception is required by the SQL
standard.) If the string to be stored is shorter than the declared
length, values of type character will be space-padded;
values of type character varying will simply store the
shorter
string.
If one explicitly casts a value to character
varying(n>) or
character(n>), then an over-length
value will be truncated to n> characters without
raising an error. (This too is required by the
SQL standard.)
The notations varchar(n>) and
char(n>) are aliases for character
varying(n>) and
character(n>), respectively.
character without length specifier is equivalent to
character(1). If character varying is used
without length specifier, the type accepts strings of any size. The
latter is a PostgreSQL> extension.
In addition, PostgreSQL provides the
text type, which stores strings of any length.
Although the type text is not in the
SQL standard, several other SQL database
management systems have it as well.
Values of type character are physically padded
with spaces to the specified width n>, and are
stored and displayed that way. However, trailing spaces are treated as
semantically insignificant and disregarded when comparing two values
of type character. In collations where whitespace
is significant, this behavior can produce unexpected results;
for example SELECT 'a '::CHAR(2) collate "C" <
E'a\n'::CHAR(2) returns true, even though C>
locale would consider a space to be greater than a newline.
Trailing spaces are removed when converting a character value
to one of the other string types. Note that trailing spaces
are> semantically significant in
character varying and text values, and
when using pattern matching, that is LIKE> and
regular expressions.
The storage requirement for a short string (up to 126 bytes) is 1 byte
plus the actual string, which includes the space padding in the case of
character. Longer strings have 4 bytes of overhead instead
of 1. Long strings are compressed by the system automatically, so
the physical requirement on disk might be less. Very long values are also
stored in background tables so that they do not interfere with rapid
access to shorter column values. In any case, the longest
possible character string that can be stored is about 1 GB. (The
maximum value that will be allowed for n> in the data
type declaration is less than that. It wouldn't be useful to
change this because with multibyte character encodings the number of
characters and bytes can be quite different. If you desire to
store long strings with no specific upper limit, use
text or character varying without a length
specifier, rather than making up an arbitrary length limit.)
There is no performance difference among these three types,
apart from increased storage space when using the blank-padded
type, and a few extra CPU cycles to check the length when storing into
a length-constrained column. While
character(n>) has performance
advantages in some other database systems, there is no such advantage in
PostgreSQL; in fact
character(n>) is usually the slowest of
the three because of its additional storage costs. In most situations
text or character varying should be used
instead.
Refer to for information about
the syntax of string literals, and to
for information about available operators and functions. The
database character set determines the character set used to store
textual values; for more information on character set support,
refer to .
Using the Character Types
CREATE TABLE test1 (a character(4));
INSERT INTO test1 VALUES ('ok');
SELECT a, char_length(a) FROM test1; --
a | char_length
------+-------------
ok | 2
CREATE TABLE test2 (b varchar(5));
INSERT INTO test2 VALUES ('ok');
INSERT INTO test2 VALUES ('good ');
INSERT INTO test2 VALUES ('too long');
ERROR: value too long for type character varying(5)
INSERT INTO test2 VALUES ('too long'::varchar(5)); -- explicit truncation
SELECT b, char_length(b) FROM test2;
b | char_length
-------+-------------
ok | 2
good | 5
too l | 5
The char_length function is discussed in
.
There are two other fixed-length character types in
PostgreSQL, shown in . The name
type exists only for the storage of identifiers
in the internal system catalogs and is not intended for use by the general user. Its
length is currently defined as 64 bytes (63 usable characters plus
terminator) but should be referenced using the constant
NAMEDATALEN in C> source code.
The length is set at compile time (and
is therefore adjustable for special uses); the default maximum
length might change in a future release. The type "char"
(note the quotes) is different from char(1) in that it
only uses one byte of storage. It is internally used in the system
catalogs as a simplistic enumeration type.
Special Character TypesNameStorage SizeDescription"char"1 bytesingle-byte internal typename64 bytesinternal type for object names
Binary Data Typesbinary databytea
The bytea data type allows storage of binary strings;
see .
Binary Data TypesNameStorage SizeDescriptionbytea1 or 4 bytes plus the actual binary stringvariable-length binary string
A binary string is a sequence of octets (or bytes). Binary
strings are distinguished from character strings in two
ways. First, binary strings specifically allow storing
octets of value zero and other non-printable
octets (usually, octets outside the range 32 to 126).
Character strings disallow zero octets, and also disallow any
other octet values and sequences of octet values that are invalid
according to the database's selected character set encoding.
Second, operations on binary strings process the actual bytes,
whereas the processing of character strings depends on locale settings.
In short, binary strings are appropriate for storing data that the
programmer thinks of as raw bytes>, whereas character
strings are appropriate for storing text.
The bytea type supports two external formats for
input and output: PostgreSQL's historical
escape format, and hex format. Both
of these are always accepted on input. The output format depends
on the configuration parameter ;
the default is hex. (Note that the hex format was introduced in
PostgreSQL 9.0; earlier versions and some
tools don't understand it.)
The SQL standard defines a different binary
string type, called BLOB or BINARY LARGE
OBJECT. The input format is different from
bytea, but the provided functions and operators are
mostly the same.
bytea> Hex Format
The hex> format encodes binary data as 2 hexadecimal digits
per byte, most significant nibble first. The entire string is
preceded by the sequence \x (to distinguish it
from the escape format). In some contexts, the initial backslash may
need to be escaped by doubling it, in the same cases in which backslashes
have to be doubled in escape format; details appear below.
The hexadecimal digits can
be either upper or lower case, and whitespace is permitted between
digit pairs (but not within a digit pair nor in the starting
\x sequence).
The hex format is compatible with a wide
range of external applications and protocols, and it tends to be
faster to convert than the escape format, so its use is preferred.
Example:
SELECT E'\\xDEADBEEF';
bytea> Escape Format
The escape format is the traditional
PostgreSQL format for the bytea
type. It
takes the approach of representing a binary string as a sequence
of ASCII characters, while converting those bytes that cannot be
represented as an ASCII character into special escape sequences.
If, from the point of view of the application, representing bytes
as characters makes sense, then this representation can be
convenient. But in practice it is usually confusing because it
fuzzes up the distinction between binary strings and character
strings, and also the particular escape mechanism that was chosen is
somewhat unwieldy. So this format should probably be avoided
for most new applications.
When entering bytea values in escape format,
octets of certain
values must be escaped, while all octet
values can be escaped. In
general, to escape an octet, convert it into its three-digit
octal value and precede it
by a backslash (or two backslashes, if writing the value as a
literal using escape string syntax).
Backslash itself (octet value 92) can alternatively be represented by
double backslashes.
shows the characters that must be escaped, and gives the alternative
escape sequences where applicable.
bytea> Literal Escaped OctetsDecimal Octet ValueDescriptionEscaped Input RepresentationExampleOutput Representation0zero octetE'\\000'SELECT E'\\000'::bytea;\00039single quote'''' or E'\\047'SELECT E'\''::bytea;'92backslashE'\\\\' or E'\\134'SELECT E'\\\\'::bytea;\\0 to 31 and 127 to 255non-printable octetsE'\\xxx'> (octal value)SELECT E'\\001'::bytea;\001
The requirement to escape non-printable octets
varies depending on locale settings. In some instances you can get away
with leaving them unescaped. Note that the result in each of the examples
in was exactly one octet in
length, even though the output representation is sometimes
more than one character.
The reason multiple backslashes are required, as shown
in , is that an input
string written as a string literal must pass through two parse
phases in the PostgreSQL server.
The first backslash of each pair is interpreted as an escape
character by the string-literal parser (assuming escape string
syntax is used) and is therefore consumed, leaving the second backslash of the
pair. (Dollar-quoted strings can be used to avoid this level
of escaping.) The remaining backslash is then recognized by the
bytea input function as starting either a three
digit octal value or escaping another backslash. For example,
a string literal passed to the server as E'\\001'
becomes \001 after passing through the
escape string parser. The \001 is then sent
to the bytea input function, where it is converted
to a single octet with a decimal value of 1. Note that the
single-quote character is not treated specially by bytea,
so it follows the normal rules for string literals. (See also
.)
Bytea octets are sometimes escaped when output. In general, each
non-printable octet is converted into
its equivalent three-digit octal value and preceded by one backslash.
Most printable octets are represented by their standard
representation in the client character set. The octet with decimal
value 92 (backslash) is doubled in the output.
Details are in .
bytea> Output Escaped OctetsDecimal Octet ValueDescriptionEscaped Output RepresentationExampleOutput Result92backslash\\SELECT E'\\134'::bytea;\\0 to 31 and 127 to 255non-printable octets\xxx> (octal value)SELECT E'\\001'::bytea;\00132 to 126printable octetsclient character set representationSELECT E'\\176'::bytea;~
Depending on the front end to PostgreSQL> you use,
you might have additional work to do in terms of escaping and
unescaping bytea strings. For example, you might also
have to escape line feeds and carriage returns if your interface
automatically translates these.
Date/Time Typesdatetimetime without time zonetime with time zonetimestamptimestamptztimestamp with time zonetimestamp without time zoneintervaltime spanPostgreSQL supports the full set of
SQL date and time types, shown in . The operations available
on these data types are described in
.
Dates are counted according to the Gregorian calendar, even in
years before that calendar was introduced (see for more information).
Date/Time TypesNameStorage SizeDescriptionLow ValueHigh ValueResolutiontimestamp [ (p) ] [ without time zone ]8 bytesboth date and time (no time zone)4713 BC294276 AD1 microsecond / 14 digitstimestamp [ (p) ] with time zone8 bytesboth date and time, with time zone4713 BC294276 AD1 microsecond / 14 digitsdate4 bytesdate (no time of day)4713 BC5874897 AD1 daytime [ (p) ] [ without time zone ]8 bytestime of day (no date)00:00:0024:00:001 microsecond / 14 digitstime [ (p) ] with time zone12 bytestimes of day only, with time zone00:00:00+145924:00:00-14591 microsecond / 14 digitsinterval [ fields ] [ (p) ]16 bytestime interval-178000000 years178000000 years1 microsecond / 14 digits
The SQL standard requires that writing just timestamp
be equivalent to timestamp without time
zone, and PostgreSQL honors that
behavior. timestamptz is accepted as an
abbreviation for timestamp with time zone; this is a
PostgreSQL extension.
time, timestamp, and
interval accept an optional precision value
p which specifies the number of
fractional digits retained in the seconds field. By default, there
is no explicit bound on precision. The allowed range of
p is from 0 to 6 for the
timestamp and interval types.
When timestamp> values are stored as eight-byte integers
(currently the default), microsecond precision is available over
the full range of values. When timestamp> values are
stored as double precision floating-point numbers instead (a
deprecated compile-time option), the effective limit of precision
might be less than 6. timestamp values are stored as
seconds before or after midnight 2000-01-01. When
timestamp values are implemented using floating-point
numbers, microsecond precision is achieved for dates within a few
years of 2000-01-01, but the precision degrades for dates further
away. Note that using floating-point datetimes allows a larger
range of timestamp values to be represented than
shown above: from 4713 BC up to 5874897 AD.
The same compile-time option also determines whether
time and interval values are stored as
floating-point numbers or eight-byte integers. In the
floating-point case, large interval values degrade in
precision as the size of the interval increases.
For the time types, the allowed range of
p is from 0 to 6 when eight-byte integer
storage is used, or from 0 to 10 when floating-point storage is used.
The interval type has an additional option, which is
to restrict the set of stored fields by writing one of these phrases:
YEAR
MONTH
DAY
HOUR
MINUTE
SECOND
YEAR TO MONTH
DAY TO HOUR
DAY TO MINUTE
DAY TO SECOND
HOUR TO MINUTE
HOUR TO SECOND
MINUTE TO SECOND
Note that if both fields and
p are specified, the
fields must include SECOND>,
since the precision applies only to the seconds.
The type time with time zone is defined by the SQL
standard, but the definition exhibits properties which lead to
questionable usefulness. In most cases, a combination of
date, time, timestamp without time
zone, and timestamp with time zone should
provide a complete range of date/time functionality required by
any application.
The types abstime
and reltime are lower precision types which are used internally.
You are discouraged from using these types in
applications; these internal types
might disappear in a future release.
Date/Time Input
Date and time input is accepted in almost any reasonable format, including
ISO 8601, SQL-compatible,
traditional POSTGRES, and others.
For some formats, ordering of day, month, and year in date input is
ambiguous and there is support for specifying the expected
ordering of these fields. Set the parameter
to MDY> to select month-day-year interpretation,
DMY> to select day-month-year interpretation, or
YMD> to select year-month-day interpretation.
PostgreSQL is more flexible in
handling date/time input than the
SQL standard requires.
See
for the exact parsing rules of date/time input and for the
recognized text fields including months, days of the week, and
time zones.
Remember that any date or time literal input needs to be enclosed
in single quotes, like text strings. Refer to
for more
information.
SQL requires the following syntax
type [ (p) ] 'value'
where p is an optional precision
specification giving the number of
fractional digits in the seconds field. Precision can be
specified for time, timestamp, and
interval types. The allowed values are mentioned
above. If no precision is specified in a constant specification,
it defaults to the precision of the literal value.
Datesdate shows some possible
inputs for the date type.
Date InputExampleDescription1999-01-08ISO 8601; January 8 in any mode
(recommended format)January 8, 1999unambiguous in any datestyle input mode1/8/1999January 8 in MDY> mode;
August 1 in DMY> mode1/18/1999January 18 in MDY> mode;
rejected in other modes01/02/03January 2, 2003 in MDY> mode;
February 1, 2003 in DMY> mode;
February 3, 2001 in YMD> mode
1999-Jan-08January 8 in any modeJan-08-1999January 8 in any mode08-Jan-1999January 8 in any mode99-Jan-08January 8 in YMD> mode, else error08-Jan-99January 8, except error in YMD> modeJan-08-99January 8, except error in YMD> mode19990108ISO 8601; January 8, 1999 in any mode990108ISO 8601; January 8, 1999 in any mode1999.008year and day of yearJ2451187Julian dateJanuary 8, 99 BCyear 99 BC
Timestimetime without time zonetime with time zone
The time-of-day types are time [
(p) ] without time zone and
time [ (p) ] with time
zone. time alone is equivalent to
time without time zone.
Valid input for these types consists of a time of day followed
by an optional time zone. (See
and .) If a time zone is
specified in the input for time without time zone,
it is silently ignored. You can also specify a date but it will
be ignored, except when you use a time zone name that involves a
daylight-savings rule, such as
America/New_York. In this case specifying the date
is required in order to determine whether standard or daylight-savings
time applies. The appropriate time zone offset is recorded in the
time with time zone value.
Time InputExampleDescription04:05:06.789ISO 860104:05:06ISO 860104:05ISO 8601040506ISO 860104:05 AMsame as 04:05; AM does not affect value04:05 PMsame as 16:05; input hour must be <= 1204:05:06.789-8ISO 860104:05:06-08:00ISO 860104:05-08:00ISO 8601040506-08ISO 860104:05:06 PSTtime zone specified by abbreviation2003-04-12 04:05:06 America/New_Yorktime zone specified by full name
Time Zone InputExampleDescriptionPSTAbbreviation (for Pacific Standard Time)America/New_YorkFull time zone namePST8PDTPOSIX-style time zone specification-8:00ISO-8601 offset for PST-800ISO-8601 offset for PST-8ISO-8601 offset for PSTzuluMilitary abbreviation for UTCzShort form of zulu
Refer to for more information on how
to specify time zones.
Time Stampstimestamptimestamp with time zonetimestamp without time zone
Valid input for the time stamp types consists of the concatenation
of a date and a time, followed by an optional time zone,
followed by an optional AD or BC.
(Alternatively, AD/BC can appear
before the time zone, but this is not the preferred ordering.)
Thus:
1999-01-08 04:05:06
and:
1999-01-08 04:05:06 -8:00
are valid values, which follow the ISO 8601
standard. In addition, the common format:
January 8 04:05:06 1999 PST
is supported.
The SQL standard differentiates
timestamp without time zone
and timestamp with time zone literals by the presence of a
+ or - symbol and time zone offset after
the time. Hence, according to the standard,
TIMESTAMP '2004-10-19 10:23:54'
is a timestamp without time zone, while
TIMESTAMP '2004-10-19 10:23:54+02'
is a timestamp with time zone.
PostgreSQL never examines the content of a
literal string before determining its type, and therefore will treat
both of the above as timestamp without time zone. To
ensure that a literal is treated as timestamp with time
zone, give it the correct explicit type:
TIMESTAMP WITH TIME ZONE '2004-10-19 10:23:54+02'
In a literal that has been determined to be timestamp without time
zone, PostgreSQL will silently ignore
any time zone indication.
That is, the resulting value is derived from the date/time
fields in the input value, and is not adjusted for time zone.
For timestamp with time zone, the internally stored
value is always in UTC (Universal
Coordinated Time, traditionally known as Greenwich Mean Time,
GMT>). An input value that has an explicit
time zone specified is converted to UTC using the appropriate offset
for that time zone. If no time zone is stated in the input string,
then it is assumed to be in the time zone indicated by the system's
parameter, and is converted to UTC using the
offset for the timezone> zone.
When a timestamp with time
zone value is output, it is always converted from UTC to the
current timezone> zone, and displayed as local time in that
zone. To see the time in another time zone, either change
timezone> or use the AT TIME ZONE> construct
(see ).
Conversions between timestamp without time zone and
timestamp with time zone normally assume that the
timestamp without time zone value should be taken or given
as timezone> local time. A different time zone can
be specified for the conversion using AT TIME ZONE>.
Special ValuestimeconstantsdateconstantsPostgreSQL supports several
special date/time input values for convenience, as shown in . The values
infinity and -infinity
are specially represented inside the system and will be displayed
unchanged; but the others are simply notational shorthands
that will be converted to ordinary date/time values when read.
(In particular, now> and related strings are converted
to a specific time value as soon as they are read.)
All of these values need to be enclosed in single quotes when used
as constants in SQL commands.
Special Date/Time InputsInput StringValid TypesDescriptionepochdate, timestamp1970-01-01 00:00:00+00 (Unix system time zero)infinitydate, timestamplater than all other time stamps-infinitydate, timestampearlier than all other time stampsnowdate, time, timestampcurrent transaction's start timetodaydate, timestampmidnight todaytomorrowdate, timestampmidnight tomorrowyesterdaydate, timestampmidnight yesterdayallballstime00:00:00.00 UTC
The following SQL-compatible functions can also
be used to obtain the current time value for the corresponding data
type:
CURRENT_DATE, CURRENT_TIME,
CURRENT_TIMESTAMP, LOCALTIME,
LOCALTIMESTAMP. The latter four accept an
optional subsecond precision specification. (See .) Note that these are
SQL functions and are not> recognized in data input strings.
Date/Time Outputdateoutput formatformattingtimeoutput formatformatting
The output format of the date/time types can be set to one of the four
styles ISO 8601,
SQL (Ingres), traditional POSTGRES>
(Unix date> format), or
German. The default
is the ISO format. (The
SQL standard requires the use of the ISO 8601
format. The name of the SQL output format is a
historical accident.) shows examples of each
output style. The output of the date and
time types is generally only the date or time part
in accordance with the given examples. However, the
POSTGRES> style outputs date-only values in
ISO format.
ISO 8601 specifies the use of uppercase letter T> to separate
the date and time. PostgreSQL> accepts that format on
input, but on output it uses a space rather than T>, as shown
above. This is for readability and for consistency with RFC 3339 as
well as some other database systems.
In the SQL and POSTGRES styles, day appears before
month if DMY field ordering has been specified, otherwise month appears
before day.
(See
for how this setting also affects interpretation of input values.)
shows examples.
Date Order Conventionsdatestyle SettingInput OrderingExample OutputSQL, DMY>day/month/year17/12/1997 15:37:16.00 CETSQL, MDY>month/day/year12/17/1997 07:37:16.00 PSTPostgres, DMY>day/month/yearWed 17 Dec 07:37:16 1997 PST
The date/time style can be selected by the user using the
SET datestyle command, the parameter in the
postgresql.conf configuration file, or the
PGDATESTYLE environment variable on the server or
client.
The formatting function to_char
(see ) is also available as
a more flexible way to format date/time output.
Time Zonestime zone
Time zones, and time-zone conventions, are influenced by
political decisions, not just earth geometry. Time zones around the
world became somewhat standardized during the 1900s,
but continue to be prone to arbitrary changes, particularly with
respect to daylight-savings rules.
PostgreSQL uses the widely-used
IANA (Olson) time zone database for information about
historical time zone rules. For times in the future, the assumption
is that the latest known rules for a given time zone will
continue to be observed indefinitely far into the future.
PostgreSQL endeavors to be compatible with
the SQL standard definitions for typical usage.
However, the SQL standard has an odd mix of date and
time types and capabilities. Two obvious problems are:
Although the date type
cannot have an associated time zone, the
time type can.
Time zones in the real world have little meaning unless
associated with a date as well as a time,
since the offset can vary through the year with daylight-saving
time boundaries.
The default time zone is specified as a constant numeric offset
from UTC>. It is therefore impossible to adapt to
daylight-saving time when doing date/time arithmetic across
DST boundaries.
To address these difficulties, we recommend using date/time types
that contain both date and time when using time zones. We
do not> recommend using the type time with
time zone (though it is supported by
PostgreSQL for legacy applications and
for compliance with the SQL standard).
PostgreSQL assumes
your local time zone for any type containing only date or time.
All timezone-aware dates and times are stored internally in
UTC. They are converted to local time
in the zone specified by the configuration
parameter before being displayed to the client.
PostgreSQL allows you to specify time zones in
three different forms:
A full time zone name, for example America/New_York>.
The recognized time zone names are listed in the
pg_timezone_names view (see ).
PostgreSQL uses the widely-used IANA
time zone data for this purpose, so the same time zone
names are also recognized by much other software.
A time zone abbreviation, for example PST>. Such a
specification merely defines a particular offset from UTC, in
contrast to full time zone names which can imply a set of daylight
savings transition-date rules as well. The recognized abbreviations
are listed in the pg_timezone_abbrevs> view (see ). You cannot set the
configuration parameters or
to a time
zone abbreviation, but you can use abbreviations in
date/time input values and with the AT TIME ZONE>
operator.
In addition to the timezone names and abbreviations,
PostgreSQL will accept POSIX-style time zone
specifications of the form STD>offset> or
STD>offset>DST>, where
STD> is a zone abbreviation, offset> is a
numeric offset in hours west from UTC, and DST> is an
optional daylight-savings zone abbreviation, assumed to stand for one
hour ahead of the given offset. For example, if EST5EDT>
were not already a recognized zone name, it would be accepted and would
be functionally equivalent to United States East Coast time. In this
syntax, a zone abbreviation can be a string of letters, or an
arbitrary string surrounded by angle brackets (<>>).
When a daylight-savings zone abbreviation is present,
it is assumed to be used
according to the same daylight-savings transition rules used in the
IANA time zone database's posixrules> entry.
In a standard PostgreSQL installation,
posixrules> is the same as US/Eastern>, so
that POSIX-style time zone specifications follow USA daylight-savings
rules. If needed, you can adjust this behavior by replacing the
posixrules> file.
In short, this is the difference between abbreviations
and full names: abbreviations represent a specific offset from UTC,
whereas many of the full names imply a local daylight-savings time
rule, and so have two possible UTC offsets. As an example,
2014-06-04 12:00 America/New_York> represents noon local
time in New York, which for this particular date was Eastern Daylight
Time (UTC-4). So 2014-06-04 12:00 EDT> specifies that
same time instant. But 2014-06-04 12:00 EST> specifies
noon Eastern Standard Time (UTC-5), regardless of whether daylight
savings was nominally in effect on that date.
To complicate matters, some jurisdictions have used the same timezone
abbreviation to mean different UTC offsets at different times; for
example, in Moscow MSK> has meant UTC+3 in some years and
UTC+4 in others. PostgreSQL> interprets such
abbreviations according to whatever they meant (or had most recently
meant) on the specified date; but, as with the EST> example
above, this is not necessarily the same as local civil time on that date.
One should be wary that the POSIX-style time zone feature can
lead to silently accepting bogus input, since there is no check on the
reasonableness of the zone abbreviations. For example, SET
TIMEZONE TO FOOBAR0> will work, leaving the system effectively using
a rather peculiar abbreviation for UTC.
Another issue to keep in mind is that in POSIX time zone names,
positive offsets are used for locations west> of Greenwich.
Everywhere else, PostgreSQL follows the
ISO-8601 convention that positive timezone offsets are east>
of Greenwich.
In all cases, timezone names and abbreviations are recognized
case-insensitively. (This is a change from PostgreSQL>
versions prior to 8.2, which were case-sensitive in some contexts but
not others.)
Neither timezone names nor abbreviations are hard-wired into the server;
they are obtained from configuration files stored under
.../share/timezone/> and .../share/timezonesets/>
of the installation directory
(see ).
The configuration parameter can
be set in the file postgresql.conf>, or in any of the
other standard ways described in .
There are also some special ways to set it:
The SQL command SET TIME ZONE
sets the time zone for the session. This is an alternative spelling
of SET TIMEZONE TO> with a more SQL-spec-compatible syntax.
The PGTZ environment variable is used by
libpq clients
to send a SET TIME ZONE
command to the server upon connection.
Interval Inputintervalinterval values can be written using the following
verbose syntax:
@> quantity> unit> quantity> unit>...> direction>
where quantity> is a number (possibly signed);
unit> is microsecond,
millisecond, second,
minute, hour, day,
week, month, year,
decade, century, millennium,
or abbreviations or plurals of these units;
direction> can be ago or
empty. The at sign (@>) is optional noise. The amounts
of the different units are implicitly added with appropriate
sign accounting. ago negates all the fields.
This syntax is also used for interval output, if
is set to
postgres_verbose>.
Quantities of days, hours, minutes, and seconds can be specified without
explicit unit markings. For example, '1 12:59:10'> is read
the same as '1 day 12 hours 59 min 10 sec'>. Also,
a combination of years and months can be specified with a dash;
for example '200-10'> is read the same as '200 years
10 months'>. (These shorter forms are in fact the only ones allowed
by the SQL standard, and are used for output when
IntervalStyle> is set to sql_standard.)
Interval values can also be written as ISO 8601 time intervals, using
either the format with designators> of the standard's section
4.4.3.2 or the alternative format> of section 4.4.3.3. The
format with designators looks like this:
P quantity> unit> quantity> unit> ... T quantity> unit> ...
The string must start with a P>, and may include a
T> that introduces the time-of-day units. The
available unit abbreviations are given in . Units may be
omitted, and may be specified in any order, but units smaller than
a day must appear after T>. In particular, the meaning of
M> depends on whether it is before or after
T>.
ISO 8601 Interval Unit AbbreviationsAbbreviationMeaningYYearsMMonths (in the date part)WWeeksDDaysHHoursMMinutes (in the time part)SSeconds
In the alternative format:
P years>-months>-days> T hours>:minutes>:seconds>
the string must begin with P, and a
T> separates the date and time parts of the interval.
The values are given as numbers similar to ISO 8601 dates.
When writing an interval constant with a fields>
specification, or when assigning a string to an interval column that was
defined with a fields> specification, the interpretation of
unmarked quantities depends on the fields>. For
example INTERVAL '1' YEAR> is read as 1 year, whereas
INTERVAL '1'> means 1 second. Also, field values
to the right> of the least significant field allowed by the
fields> specification are silently discarded. For
example, writing INTERVAL '1 day 2:03:04' HOUR TO MINUTE>
results in dropping the seconds field, but not the day field.
According to the SQL> standard all fields of an interval
value must have the same sign, so a leading negative sign applies to all
fields; for example the negative sign in the interval literal
'-1 2:03:04'> applies to both the days and hour/minute/second
parts. PostgreSQL> allows the fields to have different
signs, and traditionally treats each field in the textual representation
as independently signed, so that the hour/minute/second part is
considered positive in this example. If IntervalStyle> is
set to sql_standard then a leading sign is considered
to apply to all fields (but only if no additional signs appear).
Otherwise the traditional PostgreSQL> interpretation is
used. To avoid ambiguity, it's recommended to attach an explicit sign
to each field if any field is negative.
Internally interval> values are stored as months, days,
and seconds. This is done because the number of days in a month
varies, and a day can have 23 or 25 hours if a daylight savings
time adjustment is involved. The months and days fields are integers
while the seconds field can store fractions. Because intervals are
usually created from constant strings or timestamp> subtraction,
this storage method works well in most cases. Functions
justify_days> and justify_hours> are
available for adjusting days and hours that overflow their normal
ranges.
In the verbose input format, and in some fields of the more compact
input formats, field values can have fractional parts; for example
'1.5 week'> or '01:02:03.45'>. Such input is
converted to the appropriate number of months, days, and seconds
for storage. When this would result in a fractional number of
months or days, the fraction is added to the lower-order fields
using the conversion factors 1 month = 30 days and 1 day = 24 hours.
For example, '1.5 month'> becomes 1 month and 15 days.
Only seconds will ever be shown as fractional on output.
shows some examples
of valid interval> input.
Interval InputExampleDescription1-2SQL standard format: 1 year 2 months3 4:05:06SQL standard format: 3 days 4 hours 5 minutes 6 seconds1 year 2 months 3 days 4 hours 5 minutes 6 secondsTraditional Postgres format: 1 year 2 months 3 days 4 hours 5 minutes 6 secondsP1Y2M3DT4H5M6SISO 8601 format with designators>: same meaning as aboveP0001-02-03T04:05:06ISO 8601 alternative format>: same meaning as above
Interval Outputintervaloutput formatformatting
The output format of the interval type can be set to one of the
four styles sql_standard>, postgres>,
postgres_verbose>, or iso_8601>,
using the command SET intervalstyle.
The default is the postgres> format.
shows examples of each
output style.
The sql_standard> style produces output that conforms to
the SQL standard's specification for interval literal strings, if
the interval value meets the standard's restrictions (either year-month
only or day-time only, with no mixing of positive
and negative components). Otherwise the output looks like a standard
year-month literal string followed by a day-time literal string,
with explicit signs added to disambiguate mixed-sign intervals.
The output of the postgres> style matches the output of
PostgreSQL> releases prior to 8.4 when the
parameter was set to ISO>.
The output of the postgres_verbose> style matches the output of
PostgreSQL> releases prior to 8.4 when the
DateStyle> parameter was set to non-ISO> output.
The output of the iso_8601> style matches the format
with designators> described in section 4.4.3.2 of the
ISO 8601 standard.
Interval Output Style ExamplesStyle SpecificationYear-Month IntervalDay-Time IntervalMixed Intervalsql_standard>1-23 4:05:06-1-2 +3 -4:05:06postgres>1 year 2 mons3 days 04:05:06-1 year -2 mons +3 days -04:05:06postgres_verbose>@ 1 year 2 mons@ 3 days 4 hours 5 mins 6 secs@ 1 year 2 mons -3 days 4 hours 5 mins 6 secs agoiso_8601>P1Y2MP3DT4H5M6SP-1Y-2M3DT-4H-5M-6S
Boolean TypeBooleandata typetruefalsePostgreSQL provides the
standard SQL type boolean;
see .
The boolean type can have several states:
true, false, and a third state,
unknown, which is represented by the
SQL null value.
Boolean Data TypeNameStorage SizeDescriptionboolean1 bytestate of true or false
Valid literal values for the true state are:
TRUE't''true''y''yes''on''1'
For the false state, the following values can be
used:
FALSE'f''false''n''no''off''0'
Leading or trailing whitespace is ignored, and case does not matter.
The key words
TRUE and FALSE are the preferred
(SQL-compliant) usage.
shows that
boolean values are output using the letters
t and f.
Using the boolean Type
CREATE TABLE test1 (a boolean, b text);
INSERT INTO test1 VALUES (TRUE, 'sic est');
INSERT INTO test1 VALUES (FALSE, 'non est');
SELECT * FROM test1;
a | b
---+---------
t | sic est
f | non est
SELECT * FROM test1 WHERE a;
a | b
---+---------
t | sic est
Enumerated Typesdata typeenumerated (enum)enumerated types
Enumerated (enum) types are data types that
comprise a static, ordered set of values.
They are equivalent to the enum
types supported in a number of programming languages. An example of an enum
type might be the days of the week, or a set of status values for
a piece of data.
Declaration of Enumerated Types
Enum types are created using the command,
for example:
CREATE TYPE mood AS ENUM ('sad', 'ok', 'happy');
Once created, the enum type can be used in table and function
definitions much like any other type:
CREATE TYPE mood AS ENUM ('sad', 'ok', 'happy');
CREATE TABLE person (
name text,
current_mood mood
);
INSERT INTO person VALUES ('Moe', 'happy');
SELECT * FROM person WHERE current_mood = 'happy';
name | current_mood
------+--------------
Moe | happy
(1 row)
Ordering
The ordering of the values in an enum type is the
order in which the values were listed when the type was created.
All standard comparison operators and related
aggregate functions are supported for enums. For example:
INSERT INTO person VALUES ('Larry', 'sad');
INSERT INTO person VALUES ('Curly', 'ok');
SELECT * FROM person WHERE current_mood > 'sad';
name | current_mood
-------+--------------
Moe | happy
Curly | ok
(2 rows)
SELECT * FROM person WHERE current_mood > 'sad' ORDER BY current_mood;
name | current_mood
-------+--------------
Curly | ok
Moe | happy
(2 rows)
SELECT name
FROM person
WHERE current_mood = (SELECT MIN(current_mood) FROM person);
name
-------
Larry
(1 row)
Type Safety
Each enumerated data type is separate and cannot
be compared with other enumerated types. See this example:
CREATE TYPE happiness AS ENUM ('happy', 'very happy', 'ecstatic');
CREATE TABLE holidays (
num_weeks integer,
happiness happiness
);
INSERT INTO holidays(num_weeks,happiness) VALUES (4, 'happy');
INSERT INTO holidays(num_weeks,happiness) VALUES (6, 'very happy');
INSERT INTO holidays(num_weeks,happiness) VALUES (8, 'ecstatic');
INSERT INTO holidays(num_weeks,happiness) VALUES (2, 'sad');
ERROR: invalid input value for enum happiness: "sad"
SELECT person.name, holidays.num_weeks FROM person, holidays
WHERE person.current_mood = holidays.happiness;
ERROR: operator does not exist: mood = happiness
If you really need to do something like that, you can either
write a custom operator or add explicit casts to your query:
SELECT person.name, holidays.num_weeks FROM person, holidays
WHERE person.current_mood::text = holidays.happiness::text;
name | num_weeks
------+-----------
Moe | 4
(1 row)
Implementation Details
An enum value occupies four bytes on disk. The length of an enum
value's textual label is limited by the NAMEDATALEN
setting compiled into PostgreSQL; in standard
builds this means at most 63 bytes.
Enum labels are case sensitive, so
'happy' is not the same as 'HAPPY'.
White space in the labels is significant too.
The translations from internal enum values to textual labels are
kept in the system catalog
pg_enum.
Querying this catalog directly can be useful.
Geometric Types
Geometric data types represent two-dimensional spatial
objects. shows the geometric
types available in PostgreSQL.
Geometric TypesNameStorage SizeDescriptionRepresentationpoint16 bytesPoint on a plane(x,y)line32 bytesInfinite line{A,B,C}lseg32 bytesFinite line segment((x1,y1),(x2,y2))box32 bytesRectangular box((x1,y1),(x2,y2))path16+16n bytesClosed path (similar to polygon)((x1,y1),...)path16+16n bytesOpen path[(x1,y1),...]polygon40+16n bytesPolygon (similar to closed path)((x1,y1),...)circle24 bytesCircle<(x,y),r> (center point and radius)
A rich set of functions and operators is available to perform various geometric
operations such as scaling, translation, rotation, and determining
intersections. They are explained in .
Pointspoint
Points are the fundamental two-dimensional building block for geometric
types. Values of type point are specified using either of
the following syntaxes:
( x , y )
x , y
where x> and y> are the respective
coordinates, as floating-point numbers.
Points are output using the first syntax.
Linesline
Lines are represented by the linear
equation A>x + B>y + C> = 0,
where A> and B> are not both zero. Values
of type line are input and output in the following form:
{ A, B, C }
Alternatively, any of the following forms can be used for input:
[ ( x1 , y1 ) , ( x2 , y2 ) ]
( ( x1 , y1 ) , ( x2 , y2 ) )
( x1 , y1 ) , ( x2 , y2 )
x1 , y1 , x2 , y2
where
(x1,y1)
and
(x2,y2)
are two different points on the line.
Line Segmentslsegline segment
Line segments are represented by pairs of points that are the endpoints
of the segment. Values of type lseg are specified using any
of the following syntaxes:
[ ( x1 , y1 ) , ( x2 , y2 ) ]
( ( x1 , y1 ) , ( x2 , y2 ) )
( x1 , y1 ) , ( x2 , y2 )
x1 , y1 , x2 , y2
where
(x1,y1)
and
(x2,y2)
are the end points of the line segment.
Line segments are output using the first syntax.
Boxesbox (data type)rectangle
Boxes are represented by pairs of points that are opposite
corners of the box.
Values of type box are specified using any of the following
syntaxes:
( ( x1 , y1 ) , ( x2 , y2 ) )
( x1 , y1 ) , ( x2 , y2 )
x1 , y1 , x2 , y2
where
(x1,y1)
and
(x2,y2)
are any two opposite corners of the box.
Boxes are output using the second syntax.
Any two opposite corners can be supplied on input, but the values
will be reordered as needed to store the
upper right and lower left corners, in that order.
Pathspath (data type)
Paths are represented by lists of connected points. Paths can be
open, where
the first and last points in the list are considered not connected, or
closed,
where the first and last points are considered connected.
Values of type path are specified using any of the following
syntaxes:
[ ( x1 , y1 ) , ... , ( xn , yn ) ]
( ( x1 , y1 ) , ... , ( xn , yn ) )
( x1 , y1 ) , ... , ( xn , yn )
( x1 , y1 , ... , xn , yn )
x1 , y1 , ... , xn , yn
where the points are the end points of the line segments
comprising the path. Square brackets ([]>) indicate
an open path, while parentheses (()>) indicate a
closed path. When the outermost parentheses are omitted, as
in the third through fifth syntaxes, a closed path is assumed.
Paths are output using the first or second syntax, as appropriate.
Polygonspolygon
Polygons are represented by lists of points (the vertexes of the
polygon). Polygons are very similar to closed paths, but are
stored differently and have their own set of support routines.
Values of type polygon are specified using any of the
following syntaxes:
( ( x1 , y1 ) , ... , ( xn , yn ) )
( x1 , y1 ) , ... , ( xn , yn )
( x1 , y1 , ... , xn , yn )
x1 , y1 , ... , xn , yn
where the points are the end points of the line segments
comprising the boundary of the polygon.
Polygons are output using the first syntax.
Circlescircle
Circles are represented by a center point and radius.
Values of type circle are specified using any of the
following syntaxes:
< ( x , y ) , r >
( ( x , y ) , r )
( x , y ) , rx , y , r
where
(x,y)>
is the center point and r is the radius of the
circle.
Circles are output using the first syntax.
Network Address Typesnetworkdata typesPostgreSQL> offers data types to store IPv4, IPv6, and MAC
addresses, as shown in . It
is better to use these types instead of plain text types to store
network addresses, because
these types offer input error checking and specialized
operators and functions (see ).
Network Address TypesNameStorage SizeDescriptioncidr7 or 19 bytesIPv4 and IPv6 networksinet7 or 19 bytesIPv4 and IPv6 hosts and networksmacaddr6 bytesMAC addresses
When sorting inet or cidr data types,
IPv4 addresses will always sort before IPv6 addresses, including
IPv4 addresses encapsulated or mapped to IPv6 addresses, such as
::10.2.3.4 or ::ffff:10.4.3.2.
inetinet (data type)
The inet type holds an IPv4 or IPv6 host address, and
optionally its subnet, all in one field.
The subnet is represented by the number of network address bits
present in the host address (the
netmask). If the netmask is 32 and the address is IPv4,
then the value does not indicate a subnet, only a single host.
In IPv6, the address length is 128 bits, so 128 bits specify a
unique host address. Note that if you
want to accept only networks, you should use the
cidr type rather than inet.
The input format for this type is
address/y
where
address
is an IPv4 or IPv6 address and
y
is the number of bits in the netmask. If the
/y
portion is missing, the
netmask is 32 for IPv4 and 128 for IPv6, so the value represents
just a single host. On display, the
/y
portion is suppressed if the netmask specifies a single host.
cidr>cidr
The cidr type holds an IPv4 or IPv6 network specification.
Input and output formats follow Classless Internet Domain Routing
conventions.
The format for specifying networks is address/y> where address> is the network represented as an
IPv4 or IPv6 address, and y> is the number of bits in the netmask. If
y> is omitted, it is calculated
using assumptions from the older classful network numbering system, except
it will be at least large enough to include all of the octets
written in the input. It is an error to specify a network address
that has bits set to the right of the specified netmask.
shows some examples.
cidr> Type Input Examplescidr Inputcidr Outputabbrev(cidr)192.168.100.128/25192.168.100.128/25192.168.100.128/25192.168/24192.168.0.0/24192.168.0/24192.168/25192.168.0.0/25192.168.0.0/25192.168.1192.168.1.0/24192.168.1/24192.168192.168.0.0/24192.168.0/24128.1128.1.0.0/16128.1/16128128.0.0.0/16128.0/16128.1.2128.1.2.0/24128.1.2/2410.1.210.1.2.0/2410.1.2/2410.110.1.0.0/1610.1/161010.0.0.0/810/810.1.2.3/3210.1.2.3/3210.1.2.3/322001:4f8:3:ba::/642001:4f8:3:ba::/642001:4f8:3:ba::/642001:4f8:3:ba:2e0:81ff:fe22:d1f1/1282001:4f8:3:ba:2e0:81ff:fe22:d1f1/1282001:4f8:3:ba:2e0:81ff:fe22:d1f1::ffff:1.2.3.0/120::ffff:1.2.3.0/120::ffff:1.2.3/120::ffff:1.2.3.0/128::ffff:1.2.3.0/128::ffff:1.2.3.0/128
inet vs. cidr
The essential difference between inet and cidr
data types is that inet accepts values with nonzero bits to
the right of the netmask, whereas cidr does not.
If you do not like the output format for inet or
cidr values, try the functions host>,
text>, and abbrev>.
macaddrmacaddr (data type)MAC addressmacaddr
The macaddr> type stores MAC addresses, known for example
from Ethernet card hardware addresses (although MAC addresses are
used for other purposes as well). Input is accepted in the
following formats:
'08:00:2b:01:02:03'>'08-00-2b-01-02-03'>'08002b:010203'>'08002b-010203'>'0800.2b01.0203'>'0800-2b01-0203'>'08002b010203'>
These examples would all specify the same address. Upper and
lower case is accepted for the digits
a> through f>. Output is always in the
first of the forms shown.
IEEE Std 802-2001 specifies the second shown form (with hyphens)
as the canonical form for MAC addresses, and specifies the first
form (with colons) as the bit-reversed notation, so that
08-00-2b-01-02-03 = 01:00:4D:08:04:0C. This convention is widely
ignored nowadays, and it is relevant only for obsolete network
protocols (such as Token Ring). PostgreSQL makes no provisions
for bit reversal, and all accepted formats use the canonical LSB
order.
The remaining five input formats are not part of any standard.
Bit String Typesbit stringdata type
Bit strings are strings of 1's and 0's. They can be used to store
or visualize bit masks. There are two SQL bit types:
bit(n) and bit
varying(n), where
n is a positive integer.
bit type data must match the length
n exactly; it is an error to attempt to
store shorter or longer bit strings. bit varying data is
of variable length up to the maximum length
n; longer strings will be rejected.
Writing bit without a length is equivalent to
bit(1), while bit varying without a length
specification means unlimited length.
If one explicitly casts a bit-string value to
bit(n>), it will be truncated or
zero-padded on the right to be exactly n> bits,
without raising an error. Similarly,
if one explicitly casts a bit-string value to
bit varying(n>), it will be truncated
on the right if it is more than n> bits.
Refer to for information about the syntax
of bit string constants. Bit-logical operators and string
manipulation functions are available; see .
Using the Bit String Types
CREATE TABLE test (a BIT(3), b BIT VARYING(5));
INSERT INTO test VALUES (B'101', B'00');
INSERT INTO test VALUES (B'10', B'101');
ERROR: bit string length 2 does not match type bit(3)
INSERT INTO test VALUES (B'10'::bit(3), B'101');
SELECT * FROM test;
a | b
-----+-----
101 | 00
100 | 101
A bit string value requires 1 byte for each group of 8 bits, plus
5 or 8 bytes overhead depending on the length of the string
(but long values may be compressed or moved out-of-line, as explained
in for character strings).
Text Search Typesfull text searchdata typestext searchdata typesPostgreSQL provides two data types that
are designed to support full text search, which is the activity of
searching through a collection of natural-language documents>
to locate those that best match a query>.
The tsvector type represents a document in a form optimized
for text search; the tsquery type similarly represents
a text query.
provides a detailed explanation of this
facility, and summarizes the
related functions and operators.
tsvectortsvector (data type)
A tsvector value is a sorted list of distinct
lexemes>, which are words that have been
normalized> to merge different variants of the same word
(see for details). Sorting and
duplicate-elimination are done automatically during input, as shown in
this example:
SELECT 'a fat cat sat on a mat and ate a fat rat'::tsvector;
tsvector
----------------------------------------------------
'a' 'and' 'ate' 'cat' 'fat' 'mat' 'on' 'rat' 'sat'
To represent
lexemes containing whitespace or punctuation, surround them with quotes:
SELECT $$the lexeme ' ' contains spaces$$::tsvector;
tsvector
-------------------------------------------
' ' 'contains' 'lexeme' 'spaces' 'the'
(We use dollar-quoted string literals in this example and the next one
to avoid the confusion of having to double quote marks within the
literals.) Embedded quotes and backslashes must be doubled:
SELECT $$the lexeme 'Joe''s' contains a quote$$::tsvector;
tsvector
------------------------------------------------
'Joe''s' 'a' 'contains' 'lexeme' 'quote' 'the'
Optionally, integer positions>
can be attached to lexemes:
SELECT 'a:1 fat:2 cat:3 sat:4 on:5 a:6 mat:7 and:8 ate:9 a:10 fat:11 rat:12'::tsvector;
tsvector
-------------------------------------------------------------------------------
'a':1,6,10 'and':8 'ate':9 'cat':3 'fat':2,11 'mat':7 'on':5 'rat':12 'sat':4
A position normally indicates the source word's location in the
document. Positional information can be used for
proximity ranking. Position values can
range from 1 to 16383; larger numbers are silently set to 16383.
Duplicate positions for the same lexeme are discarded.
Lexemes that have positions can further be labeled with a
weight>, which can be A,
B, C, or D.
D is the default and hence is not shown on output:
SELECT 'a:1A fat:2B,4C cat:5D'::tsvector;
tsvector
----------------------------
'a':1A 'cat':5 'fat':2B,4C
Weights are typically used to reflect document structure, for example
by marking title words differently from body words. Text search
ranking functions can assign different priorities to the different
weight markers.
It is important to understand that the
tsvector type itself does not perform any normalization;
it assumes the words it is given are normalized appropriately
for the application. For example,
select 'The Fat Rats'::tsvector;
tsvector
--------------------
'Fat' 'Rats' 'The'
For most English-text-searching applications the above words would
be considered non-normalized, but tsvector doesn't care.
Raw document text should usually be passed through
to_tsvector> to normalize the words appropriately
for searching:
SELECT to_tsvector('english', 'The Fat Rats');
to_tsvector
-----------------
'fat':2 'rat':3
Again, see for more detail.
tsquerytsquery (data type)
A tsquery value stores lexemes that are to be
searched for, and combines them honoring the Boolean operators
& (AND), | (OR), and
!> (NOT). Parentheses can be used to enforce grouping
of the operators:
SELECT 'fat & rat'::tsquery;
tsquery
---------------
'fat' & 'rat'
SELECT 'fat & (rat | cat)'::tsquery;
tsquery
---------------------------
'fat' & ( 'rat' | 'cat' )
SELECT 'fat & rat & ! cat'::tsquery;
tsquery
------------------------
'fat' & 'rat' & !'cat'
In the absence of parentheses, !> (NOT) binds most tightly,
and & (AND) binds more tightly than
| (OR).
Optionally, lexemes in a tsquery can be labeled with
one or more weight letters, which restricts them to match only
tsvector> lexemes with matching weights:
SELECT 'fat:ab & cat'::tsquery;
tsquery
------------------
'fat':AB & 'cat'
Also, lexemes in a tsquery can be labeled with *>
to specify prefix matching:
SELECT 'super:*'::tsquery;
tsquery
-----------
'super':*
This query will match any word in a tsvector> that begins
with super>. Note that prefixes are first processed by
text search configurations, which means this comparison returns
true:
SELECT to_tsvector( 'postgraduate' ) @@ to_tsquery( 'postgres:*' );
?column?
----------
t
(1 row)
because postgres> gets stemmed to postgr>:
SELECT to_tsquery('postgres:*');
to_tsquery
------------
'postgr':*
(1 row)
which then matches postgraduate>.
Quoting rules for lexemes are the same as described previously for
lexemes in tsvector>; and, as with tsvector>,
any required normalization of words must be done before converting
to the tsquery> type. The to_tsquery>
function is convenient for performing such normalization:
SELECT to_tsquery('Fat:ab & Cats');
to_tsquery
------------------
'fat':AB & 'cat'
UUID TypeUUID
The data type uuid stores Universally Unique Identifiers
(UUID) as defined by RFC 4122, ISO/IEC 9834-8:2005, and related standards.
(Some systems refer to this data type as a globally unique identifier, or
GUID,GUID instead.) This
identifier is a 128-bit quantity that is generated by an algorithm chosen
to make it very unlikely that the same identifier will be generated by
anyone else in the known universe using the same algorithm. Therefore,
for distributed systems, these identifiers provide a better uniqueness
guarantee than sequence generators, which
are only unique within a single database.
A UUID is written as a sequence of lower-case hexadecimal digits,
in several groups separated by hyphens, specifically a group of 8
digits followed by three groups of 4 digits followed by a group of
12 digits, for a total of 32 digits representing the 128 bits. An
example of a UUID in this standard form is:
a0eebc99-9c0b-4ef8-bb6d-6bb9bd380a11
PostgreSQL also accepts the following
alternative forms for input:
use of upper-case digits, the standard format surrounded by
braces, omitting some or all hyphens, adding a hyphen after any
group of four digits. Examples are:
A0EEBC99-9C0B-4EF8-BB6D-6BB9BD380A11
{a0eebc99-9c0b-4ef8-bb6d-6bb9bd380a11}
a0eebc999c0b4ef8bb6d6bb9bd380a11
a0ee-bc99-9c0b-4ef8-bb6d-6bb9-bd38-0a11
{a0eebc99-9c0b4ef8-bb6d6bb9-bd380a11}
Output is always in the standard form.
PostgreSQL provides storage and comparison
functions for UUIDs, but the core database does not include any
function for generating UUIDs, because no single algorithm is well
suited for every application. The module
provides functions that implement several standard algorithms.
The module also provides a generation
function for random UUIDs.
Alternatively, UUIDs could be generated by client applications or
other libraries invoked through a server-side function.
XML> TypeXML
The xml data type can be used to store XML data. Its
advantage over storing XML data in a text field is that it
checks the input values for well-formedness, and there are support
functions to perform type-safe operations on it; see . Use of this data type requires the
installation to have been built with configure
--with-libxml>.
The xml type can store well-formed
documents, as defined by the XML standard, as well
as content fragments, which are defined by the
production XMLDecl? content in the XML
standard. Roughly, this means that content fragments can have
more than one top-level element or character node. The expression
xmlvalue IS DOCUMENT
can be used to evaluate whether a particular xml
value is a full document or only a content fragment.
Creating XML Values
To produce a value of type xml from character data,
use the function
xmlparse:xmlparse
XMLPARSE ( { DOCUMENT | CONTENT } value)
Examples:
Manual...')
XMLPARSE (CONTENT 'abcbarfoo')
]]>
While this is the only way to convert character strings into XML
values according to the SQL standard, the PostgreSQL-specific
syntaxes:
bar'
'bar'::xml
]]>
can also be used.
The xml type does not validate input values
against a document type declaration
(DTD),DTD
even when the input value specifies a DTD.
There is also currently no built-in support for validating against
other XML schema languages such as XML Schema.
The inverse operation, producing a character string value from
xml, uses the function
xmlserialize:xmlserialize
XMLSERIALIZE ( { DOCUMENT | CONTENT } value AS type )
type can be
character, character varying, or
text (or an alias for one of those). Again, according
to the SQL standard, this is the only way to convert between type
xml and character types, but PostgreSQL also allows
you to simply cast the value.
When a character string value is cast to or from type
xml without going through XMLPARSE or
XMLSERIALIZE, respectively, the choice of
DOCUMENT versus CONTENT is
determined by the XML optionXML option
session configuration parameter, which can be set using the
standard command:
SET XML OPTION { DOCUMENT | CONTENT };
or the more PostgreSQL-like syntax
SET xmloption TO { DOCUMENT | CONTENT };
The default is CONTENT, so all forms of XML
data are allowed.
With the default XML option setting, you cannot directly cast
character strings to type xml if they contain a
document type declaration, because the definition of XML content
fragment does not accept them. If you need to do that, either
use XMLPARSE or change the XML option.
Encoding Handling
Care must be taken when dealing with multiple character encodings
on the client, server, and in the XML data passed through them.
When using the text mode to pass queries to the server and query
results to the client (which is the normal mode), PostgreSQL
converts all character data passed between the client and the
server and vice versa to the character encoding of the respective
end; see . This includes string
representations of XML values, such as in the above examples.
This would ordinarily mean that encoding declarations contained in
XML data can become invalid as the character data is converted
to other encodings while traveling between client and server,
because the embedded encoding declaration is not changed. To cope
with this behavior, encoding declarations contained in
character strings presented for input to the xml type
are ignored, and content is assumed
to be in the current server encoding. Consequently, for correct
processing, character strings of XML data must be sent
from the client in the current client encoding. It is the
responsibility of the client to either convert documents to the
current client encoding before sending them to the server, or to
adjust the client encoding appropriately. On output, values of
type xml will not have an encoding declaration, and
clients should assume all data is in the current client
encoding.
When using binary mode to pass query parameters to the server
and query results back to the client, no character set conversion
is performed, so the situation is different. In this case, an
encoding declaration in the XML data will be observed, and if it
is absent, the data will be assumed to be in UTF-8 (as required by
the XML standard; note that PostgreSQL does not support UTF-16).
On output, data will have an encoding declaration
specifying the client encoding, unless the client encoding is
UTF-8, in which case it will be omitted.
Needless to say, processing XML data with PostgreSQL will be less
error-prone and more efficient if the XML data encoding, client encoding,
and server encoding are the same. Since XML data is internally
processed in UTF-8, computations will be most efficient if the
server encoding is also UTF-8.
Some XML-related functions may not work at all on non-ASCII data
when the server encoding is not UTF-8. This is known to be an
issue for xpath()> in particular.
Accessing XML Values
The xml data type is unusual in that it does not
provide any comparison operators. This is because there is no
well-defined and universally useful comparison algorithm for XML
data. One consequence of this is that you cannot retrieve rows by
comparing an xml column against a search value. XML
values should therefore typically be accompanied by a separate key
field such as an ID. An alternative solution for comparing XML
values is to convert them to character strings first, but note
that character string comparison has little to do with a useful
XML comparison method.
Since there are no comparison operators for the xml
data type, it is not possible to create an index directly on a
column of this type. If speedy searches in XML data are desired,
possible workarounds include casting the expression to a
character string type and indexing that, or indexing an XPath
expression. Of course, the actual query would have to be adjusted
to search by the indexed expression.
The text-search functionality in PostgreSQL can also be used to speed
up full-document searches of XML data. The necessary
preprocessing support is, however, not yet available in the PostgreSQL
distribution.
&json;
&array;
&rowtypes;
&rangetypes;
Object Identifier Typesobject identifierdata typeoidregprocregprocedureregoperregoperatorregclassregtyperegconfigregdictionaryxidcidtid
Object identifiers (OIDs) are used internally by
PostgreSQL as primary keys for various
system tables. OIDs are not added to user-created tables, unless
WITH OIDS is specified when the table is
created, or the
configuration variable is enabled. Type oid> represents
an object identifier. There are also several alias types for
oid>: regproc>, regprocedure>,
regoper>, regoperator>, regclass>,
regtype>, regrole>, regnamespace>,
regconfig>, and regdictionary>.
shows an overview.
The oid> type is currently implemented as an unsigned
four-byte integer. Therefore, it is not large enough to provide
database-wide uniqueness in large databases, or even in large
individual tables. So, using a user-created table's OID column as
a primary key is discouraged. OIDs are best used only for
references to system tables.
The oid> type itself has few operations beyond comparison.
It can be cast to integer, however, and then manipulated using the
standard integer operators. (Beware of possible
signed-versus-unsigned confusion if you do this.)
The OID alias types have no operations of their own except
for specialized input and output routines. These routines are able
to accept and display symbolic names for system objects, rather than
the raw numeric value that type oid> would use. The alias
types allow simplified lookup of OID values for objects. For example,
to examine the pg_attribute> rows related to a table
mytable>, one could write:
SELECT * FROM pg_attribute WHERE attrelid = 'mytable'::regclass;
rather than:
SELECT * FROM pg_attribute
WHERE attrelid = (SELECT oid FROM pg_class WHERE relname = 'mytable');
While that doesn't look all that bad by itself, it's still oversimplified.
A far more complicated sub-select would be needed to
select the right OID if there are multiple tables named
mytable> in different schemas.
The regclass> input converter handles the table lookup according
to the schema path setting, and so it does the right thing>
automatically. Similarly, casting a table's OID to
regclass> is handy for symbolic display of a numeric OID.
Object Identifier TypesNameReferencesDescriptionValue Exampleoid>anynumeric object identifier564182>regproc>pg_proc>function namesum>regprocedure>pg_proc>function with argument typessum(int4)>regoper>pg_operator>operator name+>regoperator>pg_operator>operator with argument types*(integer,integer)> or -(NONE,integer)>regclass>pg_class>relation namepg_type>regtype>pg_type>data type nameinteger>regrole>pg_authid>role namesmithee>regnamespace>pg_namespace>namespace namepg_catalog>regconfig>pg_ts_config>text search configurationenglish>regdictionary>pg_ts_dict>text search dictionarysimple>
All of the OID alias types for objects grouped by namespace accept
schema-qualified names, and will
display schema-qualified names on output if the object would not
be found in the current search path without being qualified.
The regproc> and regoper> alias types will only
accept input names that are unique (not overloaded), so they are
of limited use; for most uses regprocedure> or
regoperator> are more appropriate. For regoperator>,
unary operators are identified by writing NONE> for the unused
operand.
An additional property of most of the OID alias types is the creation of
dependencies. If a
constant of one of these types appears in a stored expression
(such as a column default expression or view), it creates a dependency
on the referenced object. For example, if a column has a default
expression nextval('my_seq'::regclass)>,
PostgreSQL
understands that the default expression depends on the sequence
my_seq>; the system will not let the sequence be dropped
without first removing the default expression.
regrole> is the only exception for the property. Constants of this
type are not allowed in such expressions.
The OID alias types do not completely follow transaction isolation
rules. The planner also treats them as simple constants, which may
result in sub-optimal planning.
Another identifier type used by the system is xid>, or transaction
(abbreviated xact>) identifier. This is the data type of the system columns
xmin> and xmax>. Transaction identifiers are 32-bit quantities.
A third identifier type used by the system is cid>, or
command identifier. This is the data type of the system columns
cmin> and cmax>. Command identifiers are also 32-bit quantities.
A final identifier type used by the system is tid>, or tuple
identifier (row identifier). This is the data type of the system column
ctid>. A tuple ID is a pair
(block number, tuple index within block) that identifies the
physical location of the row within its table.
(The system columns are further explained in .)
pg_lsn Typepg_lsn
The pg_lsn data type can be used to store LSN (Log Sequence
Number) data which is a pointer to a location in the XLOG. This type is a
representation of XLogRecPtr and an internal system type of
PostgreSQL.
Internally, an LSN is a 64-bit integer, representing a byte position in
the write-ahead log stream. It is printed as two hexadecimal numbers of
up to 8 digits each, separated by a slash; for example,
16/B374D848>. The pg_lsn type supports the
standard comparison operators, like = and
>. Two LSNs can be subtracted using the
- operator; the result is the number of bytes separating
those write-ahead log positions.
Pseudo-Typesrecordanyanyelementanyarrayanynonarrayanyenumanyrangevoidtriggerevent_triggerpg_ddl_commandlanguage_handlerfdw_handlerindex_am_handlertsm_handlercstringinternalopaque
The PostgreSQL type system contains a
number of special-purpose entries that are collectively called
pseudo-types>. A pseudo-type cannot be used as a
column data type, but it can be used to declare a function's
argument or result type. Each of the available pseudo-types is
useful in situations where a function's behavior does not
correspond to simply taking or returning a value of a specific
SQL data type. lists the existing
pseudo-types.
Pseudo-TypesNameDescriptionany>Indicates that a function accepts any input data type.anyelement>Indicates that a function accepts any data type
(see ).anyarray>Indicates that a function accepts any array data type
(see ).anynonarray>Indicates that a function accepts any non-array data type
(see ).anyenum>Indicates that a function accepts any enum data type
(see and
).anyrange>Indicates that a function accepts any range data type
(see and
).cstring>Indicates that a function accepts or returns a null-terminated C string.internal>Indicates that a function accepts or returns a server-internal
data type.language_handler>A procedural language call handler is declared to return language_handler>.fdw_handler>A foreign-data wrapper handler is declared to return fdw_handler>.index_am_handler>An index access method handler is declared to return index_am_handler>.tsm_handler>A tablesample method handler is declared to return tsm_handler>.record>Identifies a function taking or returning an unspecified row type.trigger>A trigger function is declared to return trigger.>event_trigger>An event trigger function is declared to return event_trigger.>pg_ddl_command>Identifies a representation of DDL commands that is available to event triggers.void>Indicates that a function returns no value.opaque>An obsolete type name that formerly served all the above purposes.
Functions coded in C (whether built-in or dynamically loaded) can be
declared to accept or return any of these pseudo data types. It is up to
the function author to ensure that the function will behave safely
when a pseudo-type is used as an argument type.
Functions coded in procedural languages can use pseudo-types only as
allowed by their implementation languages. At present most procedural
languages forbid use of a pseudo-type as an argument type, and allow
only void> and record> as a result type (plus
trigger> or event_trigger> when the function is used
as a trigger or event trigger). Some also
support polymorphic functions using the types anyelement>,
anyarray>, anynonarray>, anyenum>, and
anyrange>.
The internal> pseudo-type is used to declare functions
that are meant only to be called internally by the database
system, and not by direct invocation in an SQL
query. If a function has at least one internal>-type
argument then it cannot be called from SQL. To
preserve the type safety of this restriction it is important to
follow this coding rule: do not create any function that is
declared to return internal> unless it has at least one
internal> argument.