columns
The view columns
contains information about all
table columns (or view columns) in the database. System columns
(ctid
, etc.) are not included. Only those columns are
shown that the current user has access to (by way of being the
owner or having some privilege).
Table 36.15. columns
Columns
Column Type Description |
---|
Name of the database containing the table (always the current database) |
Name of the schema containing the table |
Name of the table |
Name of the column |
Ordinal position of the column within the table (count starts at 1) |
Default expression of the column |
|
Data type of the column, if it is a built-in type, or
|
If |
If |
If |
If |
If |
If |
If |
Applies to a feature not available
in PostgreSQL
(see |
Applies to a feature not available in PostgreSQL |
Applies to a feature not available in PostgreSQL |
Applies to a feature not available in PostgreSQL |
Name of the database containing the collation of the column (always the current database), null if default or the data type of the column is not collatable |
Name of the schema containing the collation of the column, null if default or the data type of the column is not collatable |
Name of the collation of the column, null if default or the data type of the column is not collatable |
If the column has a domain type, the name of the database that the domain is defined in (always the current database), else null. |
If the column has a domain type, the name of the schema that the domain is defined in, else null. |
If the column has a domain type, the name of the domain, else null. |
Name of the database that the column data type (the underlying type of the domain, if applicable) is defined in (always the current database) |
Name of the schema that the column data type (the underlying type of the domain, if applicable) is defined in |
Name of the column data type (the underlying type of the domain, if applicable) |
Applies to a feature not available in PostgreSQL |
Applies to a feature not available in PostgreSQL |
Applies to a feature not available in PostgreSQL |
Always null, because arrays always have unlimited maximum cardinality in PostgreSQL |
An identifier of the data type descriptor of the column, unique among the data type descriptors pertaining to the table. This is mainly useful for joining with other instances of such identifiers. (The specific format of the identifier is not defined and not guaranteed to remain the same in future versions.) |
Applies to a feature not available in PostgreSQL |
If the column is an identity column, then |
If the column is an identity column, then |
If the column is an identity column, then the start value of the internal sequence, else null. |
If the column is an identity column, then the increment of the internal sequence, else null. |
If the column is an identity column, then the maximum value of the internal sequence, else null. |
If the column is an identity column, then the minimum value of the internal sequence, else null. |
If the column is an identity column, then |
If the column is a generated column, then |
If the column is a generated column, then the generation expression, else null. |
|
Since data types can be defined in a variety of ways in SQL, and
PostgreSQL contains additional ways to
define data types, their representation in the information schema
can be somewhat difficult. The column data_type
is supposed to identify the underlying built-in type of the column.
In PostgreSQL, this means that the type
is defined in the system catalog schema
pg_catalog
. This column might be useful if the
application can handle the well-known built-in types specially (for
example, format the numeric types differently or use the data in
the precision columns). The columns udt_name
,
udt_schema
, and udt_catalog
always identify the underlying data type of the column, even if the
column is based on a domain. (Since
PostgreSQL treats built-in types like
user-defined types, built-in types appear here as well. This is an
extension of the SQL standard.) These columns should be used if an
application wants to process data differently according to the
type, because in that case it wouldn't matter if the column is
really based on a domain. If the column is based on a domain, the
identity of the domain is stored in the columns
domain_name
, domain_schema
,
and domain_catalog
. If you want to pair up
columns with their associated data types and treat domains as
separate types, you could write coalesce(domain_name,
udt_name)
, etc.