32.9. columns

The view columns contains information about all table columns (or view columns) in the database. System columns (oid, 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 32-7. columns Columns

NameData TypeDescription
table_catalogsql_identifierName of the database containing the table (always the current database)
table_schemasql_identifierName of the schema containing the table
table_namesql_identifierName of the table
column_namesql_identifierName of the column
ordinal_positioncardinal_numberOrdinal position of the column within the table (count starts at 1)
column_defaultcharacter_data Default expression of the column (null if the current user is not the owner of the table containing the column)
is_nullablecharacter_data YES if the column is possibly nullable, NO if it is known not nullable. A not-null constraint is one way a column can be known not nullable, but there may be others.
data_typecharacter_data Data type of the column, if it is a built-in type, or ARRAY if it is some array (in that case, see the view element_types), else USER-DEFINED (in that case, the type is identified in udt_name and associated columns). If the column is based on a domain, this column refers to the type underlying the domain (and the domain is identified in domain_name and associated columns).
character_maximum_lengthcardinal_number If data_type identifies a character or bit string type, the declared maximum length; null for all other data types or if no maximum length was declared.
character_octet_lengthcardinal_number If data_type identifies a character type, the maximum possible length in octets (bytes) of a datum (this should not be of concern to PostgreSQL users); null for all other data types.
numeric_precisioncardinal_number If data_type identifies a numeric type, this column contains the (declared or implicit) precision of the type for this column. The precision indicates the number of significant digits. It may be expressed in decimal (base 10) or binary (base 2) terms, as specified in the column numeric_precision_radix. For all other data types, this column is null.
numeric_precision_radixcardinal_number If data_type identifies a numeric type, this column indicates in which base the values in the columns numeric_precision and numeric_scale are expressed. The value is either 2 or 10. For all other data types, this column is null.
numeric_scalecardinal_number If data_type identifies an exact numeric type, this column contains the (declared or implicit) scale of the type for this column. The scale indicates the number of significant digits to the right of the decimal point. It may be expressed in decimal (base 10) or binary (base 2) terms, as specified in the column numeric_precision_radix. For all other data types, this column is null.
datetime_precisioncardinal_number If data_type identifies a date, time, or interval type, the declared precision; null for all other data types or if no precision was declared.
interval_typecharacter_dataNot yet implemented
interval_precisioncharacter_dataNot yet implemented
character_set_catalogsql_identifierApplies to a feature not available in PostgreSQL
character_set_schemasql_identifierApplies to a feature not available in PostgreSQL
character_set_namesql_identifierApplies to a feature not available in PostgreSQL
collation_catalogsql_identifierApplies to a feature not available in PostgreSQL
collation_schemasql_identifierApplies to a feature not available in PostgreSQL
collation_namesql_identifierApplies to a feature not available in PostgreSQL
domain_catalogsql_identifier If the column has a domain type, the name of the database that the domain is defined in (always the current database), else null.
domain_schemasql_identifier If the column has a domain type, the name of the schema that the domain is defined in, else null.
domain_namesql_identifierIf the column has a domain type, the name of the domain, else null.
udt_catalogsql_identifier Name of the database that the column data type (the underlying type of the domain, if applicable) is defined in (always the current database)
udt_schemasql_identifier Name of the schema that the column data type (the underlying type of the domain, if applicable) is defined in
udt_namesql_identifier Name of the column data type (the underlying type of the domain, if applicable)
scope_catalogsql_identifierApplies to a feature not available in PostgreSQL
scope_schemasql_identifierApplies to a feature not available in PostgreSQL
scope_namesql_identifierApplies to a feature not available in PostgreSQL
maximum_cardinalitycardinal_numberAlways null, because arrays always have unlimited maximum cardinality in PostgreSQL
dtd_identifiersql_identifier 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.)
is_self_referencingcharacter_dataApplies to a feature not available in PostgreSQL

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 may 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.

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