Postgresql 中文操作指南
37.17. columns #
columns_视图包含有关数据库中所有表列（或视图列）的信息。不包括系统列（_ctid 等）。只显示当前用户有权访问的列（通过所有者或拥有一些权限进行访问）。
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 37.15. columns Columns
Table 37.15. columns Columns
Column Type Description |
table_catalog sql_identifier Name of the database containing the table (always the current database) |
table_schema sql_identifier Name of the schema containing the table |
table_name sql_identifier Name of the table |
column_name sql_identifier Name of the column |
ordinal_position cardinal_number Ordinal position of the column within the table (count starts at 1) |
column_default character_data Default expression of the column |
is_nullable yes_or_no 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 can be others. |
data_type character_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_length cardinal_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_length cardinal_number If data_type identifies a character type, the maximum possible length in octets (bytes) of a datum; null for all other data types. The maximum octet length depends on the declared character maximum length (see above) and the server encoding. |
numeric_precision cardinal_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 can 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_radix cardinal_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_scale cardinal_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 can 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_precision cardinal_number If data_type identifies a date, time, timestamp, or interval type, this column contains the (declared or implicit) fractional seconds precision of the type for this column, that is, the number of decimal digits maintained following the decimal point in the seconds value. For all other data types, this column is null. |
interval_type character_data If data_type identifies an interval type, this column contains the specification which fields the intervals include for this column, e.g., YEAR TO MONTH, DAY TO SECOND, etc. If no field restrictions were specified (that is, the interval accepts all fields), and for all other data types, this field is null. |
interval_precision cardinal_number Applies to a feature not available in PostgreSQL (see datetime_precision for the fractional seconds precision of interval type columns) |
character_set_catalog sql_identifier Applies to a feature not available in PostgreSQL |
character_set_schema sql_identifier Applies to a feature not available in PostgreSQL |
character_set_name sql_identifier Applies to a feature not available in PostgreSQL |
collation_catalog sql_identifier 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 |
collation_schema sql_identifier Name of the schema containing the collation of the column, null if default or the data type of the column is not collatable |
collation_name sql_identifier Name of the collation of the column, null if default or the data type of the column is not collatable |
domain_catalog sql_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_schema sql_identifier If the column has a domain type, the name of the schema that the domain is defined in, else null. |
domain_name sql_identifier If the column has a domain type, the name of the domain, else null. |
udt_catalog sql_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_schema sql_identifier Name of the schema that the column data type (the underlying type of the domain, if applicable) is defined in |
udt_name sql_identifier Name of the column data type (the underlying type of the domain, if applicable) |
scope_catalog sql_identifier Applies to a feature not available in PostgreSQL |
scope_schema sql_identifier Applies to a feature not available in PostgreSQL |
scope_name sql_identifier Applies to a feature not available in PostgreSQL |
maximum_cardinality cardinal_number Always null, because arrays always have unlimited maximum cardinality in PostgreSQL |
dtd_identifier sql_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_referencing yes_or_no Applies to a feature not available in PostgreSQL |
is_identity yes_or_no If the column is an identity column, then YES, else NO. |
identity_generation character_data If the column is an identity column, then ALWAYS or BY DEFAULT, reflecting the definition of the column. |
identity_start character_data If the column is an identity column, then the start value of the internal sequence, else null. |
identity_increment character_data If the column is an identity column, then the increment of the internal sequence, else null. |
identity_maximum character_data If the column is an identity column, then the maximum value of the internal sequence, else null. |
identity_minimum character_data If the column is an identity column, then the minimum value of the internal sequence, else null. |
identity_cycle yes_or_no If the column is an identity column, then YES if the internal sequence cycles or NO if it does not; otherwise null. |
is_generated character_data If the column is a generated column, then ALWAYS, else NEVER. |
generation_expression character_data If the column is a generated column, then the generation expression, else null. |
is_updatable yes_or_no YES if the column is updatable, NO if not (Columns in base tables are always updatable, columns in views not necessarily) |
由于数据类型可以在 SQL 中通过多种方式定义，并且 PostgreSQL 包含额外的方式来定义数据类型，因此它们在信息架构中的表示可能有点困难。列 data_type 应该用于标识列的基本内置类型。在 PostgreSQL 中，这意味着该类型是在系统目录架构 pg_catalog 中定义的。如果应用程序能专门处理众所周知的内置类型（例如，以不同的格式设置数值类型或在精度列中使用数据），则此列可能有用。列 udt_name、udt_schema 和 udt_catalog 始终标识列的基本数据类型，即使该列基于域也是如此。（由于 PostgreSQL 将内置类型视为用户定义类型，因此内置类型也会显示在这里。这是 SQL 标准的扩展。）如果应用程序想要根据类型以不同的方式处理数据，则应使用这些列，因为在这种情况下，列实际上是否基于域并不重要。如果列基于域，则域标识将存储在列 domain_name、domain_schema 和 domain_catalog 中。如果你想将列与其相关的数据类型配对并把域当作单独的类型处理，你可以编写 coalesce(domain_name, udt_name) 等。
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.