CREATE TABLE

Defines a new table.

Note

Greenplum Database accepts, but does not enforce, referential integrity syntax (foreign key constraints).

Synopsis

CREATE [ [GLOBAL | LOCAL] {TEMPORARY | TEMP} | UNLOGGED ] TABLE [IF NOT EXISTS] <table_name> ( 
  [ { <column_name> <data_type> [ COLLATE <collation> ] [ ENCODING ( <storage_directive> [, ...] ) ] [<column_constraint> [ ... ] ]
    | <table_constraint>
    | LIKE <source_table> [ <like_option> ... ]
    | COLUMN <column_name> ENCODING ( <storage_directive> [, ...] ) [, ...] }
] )
[ INHERITS ( <parent_table> [, ... ] ) ]
[ PARTITION BY { RANGE | LIST | HASH } ( { <column_name> | ( <expression> ) } [ COLLATE <collation> ] [ <opclass> ] [, ... ] ) ]
[ USING ( <access_method> ) ]
[ WITH ( <storage_parameter> [=<value>] [, ... ] ) ]
[ ON COMMIT { PRESERVE ROWS | DELETE ROWS | DROP } ]
[ TABLESPACE <tablespace_name> ]
[ DISTRIBUTED BY ( <column> [<opclass>] [, ... ] ) 
    | DISTRIBUTED RANDOMLY
    | DISTRIBUTED REPLICATED ]

CREATE [ [GLOBAL | LOCAL] {TEMPORARY | TEMP} | UNLOGGED ] TABLE [IF NOT EXISTS] <table_name>
  OF <type_name> [ (
  { <column_name> [WITH OPTIONS] [ <column_constraint> [ ... ] ]
    | <table_constraint> }
    [, ... ]
) ]
[ PARTITION BY { RANGE | LIST | HASH } ( { <column_name> | ( <expression> ) } [ COLLATE <collation> ] [ <opclass> ] [, ... ] ) ]
[ USING <access_method> ]
[ WITH ( <storage_parameter> [=<value>] [, ... ] ) ]
[ ON COMMIT { PRESERVE ROWS | DELETE ROWS | DROP } ]
[ TABLESPACE <tablespace_name> ]
[ DISTRIBUTED BY ( <column> [<opclass>] [, ... ] ) 
    | DISTRIBUTED RANDOMLY
    | DISTRIBUTED REPLICATED ]

CREATE [ [GLOBAL | LOCAL] { TEMPORARY | TEMP } | UNLOGGED ] TABLE [ IF NOT EXISTS ] <table_name>
  PARTITION OF <parent_table> [ (
  { <column_name [ WITH OPTIONS ] [ <column_constraint> [ ... ] ]
    | <table_constraint> }
    [, ... ]
) ] { FOR VALUES <partition_bound_spec> | DEFAULT }
[ PARTITION BY { RANGE | LIST | HASH } ( { <column_name> | ( <expression> ) } [ COLLATE <collation> ] [ <opclass> ] [, ... ] ) ]
[ USING <access_method> ]
[ WITH ( <storage_parameter> [=<value>] [, ... ] ) ]
[ ON COMMIT { PRESERVE ROWS | DELETE ROWS | DROP } ]
[ TABLESPACE <tablespace_name> ]

where <column_constraint> is:

  [ CONSTRAINT <constraint_name>]
  { NOT NULL 
    | NULL 
    | CHECK  ( <expression> ) [ NO INHERIT ]
    | DEFAULT <default_expr>
    | GENERATED ALWAYS AS ( <generation_expr> ) STORED
    | GENERATED { ALWAYS | BY DEFAULT } AS IDENTITY [ ( <sequence_options> ) ]
    | UNIQUE <index_parameters>
    | PRIMARY KEY <index_parameters>
    | REFERENCES <reftable> [ ( refcolumn ) ] 
        [ MATCH FULL | MATCH PARTIAL | MATCH SIMPLE ]  
        [ ON DELETE <referential_action> ] [ ON UPDATE <referential_action> ] }
  [ DEFERRABLE | NOT DEFERRABLE ] [ INITIALLY DEFERRED | INITIALLY IMMEDIATE ]

and <table_constraint> is:

  [ CONSTRAINT <constraint_name> ]
  { CHECK ( <expression> ) [ NO INHERIT ]
    | UNIQUE ( <column_name> [, ... ] ) <index_parameters>
    | PRIMARY KEY ( <column_name> [, ... ] ) <index_parameters>
    | EXCLUDE [ USING <index_method> ] ( <exclude_element> WITH <operator> [, ... ] )
        <index_parameters> [ WHERE ( <predicate> ) ]
    | FOREIGN KEY ( <column_name> [, ... ] ) REFERENCES <reftable> [ ( <refcolumn> [, ... ] ) ]
        [ MATCH FULL | MATCH PARTIAL | MATCH SIMPLE ] 
        [ ON DELETE <referential_action> ] [ ON UPDATE <referential_action> ] }
  [ DEFERRABLE | NOT DEFERRABLE ] [ INITIALLY DEFERRED | INITIALLY IMMEDIATE ]

and <like_option> is:

  { INCLUDING | EXCLUDING }
  { AM | COMMENTS | CONSTRAINTS | DEFAULTS | ENCODING | GENERATED | IDENTITY
       | INDEXES | RELOPT | STATISTICS | STORAGE | ALL }

and <partition_bound_spec> is:

  IN ( <partition_bound_expr> [, ...] ) |
  FROM ( { <partition_bound_expr> | MINVALUE | MAXVALUE } [, ...] )
    TO ( { <partition_bound_expr> | MINVALUE | MAXVALUE } [, ...] ) |
  WITH ( MODULUS <numeric_literal>, REMAINDER <numeric_literal> )

and <index_parameters> in UNIQUE, PRIMARY KEY, and EXCLUDE constraints are:

  [ INCLUDE ( <column_name> [, ... ] ) ]
  [ WITH ( <storage_parameter> [=<value>] [, ... ] ) ]
  [ USING INDEX TABLESPACE <tablespace_name> ] 

and <exclude_element> in an EXCLUDE constraint is:

  { <column_name> | ( <expression> ) } [ <opclass> ] [ ASC | DESC ] [ NULLS { FIRST | LAST } ]

Classic partitioning syntax elements include:

CREATE [ [GLOBAL | LOCAL] {TEMPORARY | TEMP} | UNLOGGED ] TABLE [IF NOT EXISTS] <table_name> (
  [ { <column_name> <data_type> [ COLLATE <collation> ] [ ENCODING ( <storage_directive> [, ...] ) ] [<column_constraint> [ ... ] ]
    | <table_constraint>
    | LIKE <source_table> [ <like_option> ... ]
    | COLUMN <column_name> ENCODING ( <storage_directive> [, ...] ) [, ...] }
] )
[ INHERITS ( <parent_table> [, ... ] ) ]
[ USING ( <access_method> ) ]
[ WITH ( <storage_parameter> [=<value>] [, ... ] ) ]
[ ON COMMIT { PRESERVE ROWS | DELETE ROWS | DROP } ]
[ TABLESPACE <tablespace_name> ]
[ DISTRIBUTED BY ( <column> [<opclass>] [, ... ] )
    | DISTRIBUTED RANDOMLY
    | DISTRIBUTED REPLICATED ]

{ --partitioned table using SUBPARTITION TEMPLATE
[ PARTITION BY { RANGE | LIST } (<column>) 
  {  [ SUBPARTITION BY { RANGE | LIST } (<column1>) 
       SUBPARTITION TEMPLATE ( <template_spec> ) ]
          [ SUBPARTITION BY { RANGE | LIST } (<column2>) 
            SUBPARTITION TEMPLATE ( <template_spec> ) ]
              [...]  }
  ( <classic_partition_spec> ) ]
} 

|

{ -- partitioned table without SUBPARTITION TEMPLATE
[ PARTITION BY { RANGE | LIST } (<column>)
   [ SUBPARTITION BY { RANGE | LIST } (<column1>) ]
      [ SUBPARTITION BY { RANGE | LIST } (<column2>) ]
         [...]
  ( <classic_partition_spec>
     [ ( <subpartition_spec_column1>
          [ ( <subpartition_spec_column2>
               [...] ) ] ) ],
  [ <classic_partition_spec>
     [ ( <subpartition_spec_column1>
        [ ( <subpartition_spec_column2>
             [...] ) ] ) ], ]
    [...]
  ) ]
}

where <classic_partition_spec> is:

  <partition_element> [, ...]

and <partition_element> is:

   DEFAULT PARTITION <name>
  | [PARTITION <name>] VALUES (<list_value> [,...] )
  | [PARTITION <name>] 
     START ([<datatype>] '<start_value>') [INCLUSIVE | EXCLUSIVE]
     [ END ([<datatype>] '<end_value>') [INCLUSIVE | EXCLUSIVE] ]
     [ EVERY ([<datatype>] [<number> | INTERVAL] '<interval_value>') ]
  | [PARTITION <name>] 
     END ([<datatype>] '<end_value>') [INCLUSIVE | EXCLUSIVE]
     [ EVERY ([<datatype>] [<number> | INTERVAL] '<interval_value>') ]
[ WITH ( <storage_parameter> = <value> [ , ... ] ) ]
[ <storage_directive> [ , ... ] ]
[ TABLESPACE <tablespace> ]

and <subpartition_spec> or <template_spec> is:

  <subpartition_element> [, ...]

and <subpartition_element> is:

  DEFAULT SUBPARTITION <name>
  | [SUBPARTITION <name>] VALUES (<list_value> [,...] )
  | [SUBPARTITION <name>] 
     START ([<datatype>] '<start_value>') [INCLUSIVE | EXCLUSIVE]
     [ END ([<datatype>] '<end_value>') [INCLUSIVE | EXCLUSIVE] ]
     [ EVERY ([<datatype>] [<number> | INTERVAL] '<interval_value>') ]
  | [SUBPARTITION <name>] 
     END ([<datatype>] '<end_value>') [INCLUSIVE | EXCLUSIVE]
     [ EVERY ([<datatype>] [<number> | INTERVAL] '<interval_value>') ]
[ WITH ( <storage_parameter> = <value> [ , ... ] ) ]
[ <storage_directive> [, ...] ]
[ TABLESPACE <tablespace> ]

Description

CREATE TABLE creates a new, initially empty table in the current database. The user who issues the command owns the table.

To create a table, you must have USAGE privilege on all column types or the type in the OF clause, respectively.

If you specify a schema name, Greenplum creates the table in the specified schema. Otherwise Greenplum creates the table in the current schema. Temporary tables exist in a special schema, so you cannot specify a schema name when creating a temporary table. The name of the table must be distinct from the name of any other table, external table, sequence, index, view, or foreign table in the same schema.

CREATE TABLE also automatically creates a data type that represents the composite type corresponding to one row of the table. Therefore, tables cannot have the same name as any existing data type in the same schema.

The optional constraint clauses specify conditions that new or updated rows must satisfy for an insert or update operation to succeed. A constraint is an SQL object that helps define the set of valid values in the table in various ways.

Greenplum Database accepts, but does not enforce, referential integrity (foreign key) constraints. The information is retained in the system catalogs but is otherwise ignored.

You can define two types of constraints: table constraints and column constraints. A column constraint is defined as part of a column definition. A table constraint definition is not tied to a particular column, and it can encompass more than one column. Every column constraint can also be written as a table constraint; a column constraint is only a notational convenience for use when the constraint only affects one column.

When creating a table, you specify an additional clause to declare the Greenplum Database distribution policy. If a DISTRIBUTED BY, DISTRIBUTED RANDOMLY, or DISTRIBUTED REPLICATED clause is not supplied, then Greenplum Database assigns a hash distribution policy to the table using either the PRIMARY KEY (if the table has one) or the first column of the table as the distribution key. Columns of geometric or user-defined data types are not eligible to be a Greenplum distribution key column. If a table does not have a column of an eligible data type, the rows are distributed based on a random distribution. To ensure an even distribution of data in your Greenplum Database system, you want to choose a distribution key that is unique for each record, or if that is not possible, then choose DISTRIBUTED RANDOMLY.

If you supply the DISTRIBUTED REPLICATED clause, Greenplum Database distributes all rows of the table to all segments in the Greenplum Database system. You can use this option in cases where user-defined functions must run on the segments, and the functions require access to all rows of the table. Replicated functions can also be used to improve query performance by preventing broadcast motions for the table. The DISTRIBUTED REPLICATED clause cannot be used with the PARTITION clauses or the INHERITS clause. A replicated table also cannot be inherited by another table. The hidden system columns (ctid, cmin, cmax, xmin, xmax, and gp_segment_id) cannot be referenced in user queries on replicated tables because they have no single, unambiguous value. Greenplum Database returns a column does not exist error for the query.

The PARTITION BY and PARTITION OF clauses allow you to divide the table into multiple sub-tables (or parts) that, taken together, make up the parent table and share its schema.

Note

Greenplum Database supports both classic and modern partitioning syntaxes. Refer to Choosing the Partitioning Syntax for more information, including guidance on selecting the appropriate syntax for a partitioned table.

Parameters

GLOBAL | LOCAL

These keywords are present for SQL standard compatibility, but have no effect in Greenplum Database and are deprecated.

TEMPORARY | TEMP

If specified, the table is created as a temporary table. Temporary tables are automatically dropped at the end of a session, or optionally at the end of the current transaction (see ON COMMIT). Existing permanent tables with the same name are not visible to the current session while the temporary table exists, unless they are referenced with schema-qualified names. Any indexes created on a temporary table are automatically temporary as well.

Be sure to perform appropriate vacuum and analyze operations on temporary tables via session SQL commands. For example, if you are going to use a temporary table in complex queries, run ANALYZE on the temporary table after it is populated.

UNLOGGED

If specified, the table is created as an unlogged table. Data written to unlogged tables is not written to the write-ahead (WAL) log, which makes them considerably faster than ordinary tables. However, the contents of an unlogged table are not replicated to mirror segment instances. Also an unlogged table is not crash-safe: Greenplum Database automatically truncates an unlogged table after a crash or unclean shutdown. Any indexes created on an unlogged table are automatically unlogged as well.

IF NOT EXISTS

Do not throw an error if a relation with the same name already exists. Greenplum Database issues a notice in this case. Note that there is no guarantee that the existing relation is anything like the one that would have been created.

table_name

The name (optionally schema-qualified) of the table to be created.

OF type_name

Creates a typed table, which takes its structure from the specified composite type (name optionally schema-qualified). A typed table is tied to its type; for example, the table will be dropped if the type is dropped with DROP TYPE ... CASCADE.

When a typed table is created, the data types of the columns are determined by the underlying composite type and are not specified by the CREATE TABLE command. But the CREATE TABLE command can add defaults and constraints to the table and can specify storage parameters.

column_name

The name of a column to be created in the new table.

data_type

The data type of the column. This may include array specifiers. For more information on the data types supported by Greenplum Database, refer to the Data Types documentation.

For table columns that contain textual data, Specify the data type VARCHAR or TEXT. Specifying the data type CHAR is not recommended. In Greenplum Database, the data types VARCHAR or TEXT handle padding added to the data (space characters added after the last non-space character) as significant characters, the data type CHAR does not. See Notes.

COLLATE collation

The COLLATE clause assigns a collation to the column (which must be of a collatable data type). If not specified, the column data type's default collation is used.

Note

The Greenplum query optimizer (GPORCA) supports collation only when all columns in the query use the same collation. If columns in the query use different collations, then Greenplum uses the Postgres-based planner.

ENCODING ( storage_directive [, ...] )

For a column, the optional ENCODING clause specifies the type of compression and block size for the column data. Valid column storage_directives are compresstype, compresslevel, and blocksize.

This clause is valid only for append-optimized, column-oriented tables.

Column compression settings are inherited from the table level to the partition level to the sub-partition level. The lowest-level settings have priority.

For more information about using column compression, refer to Adding Column-Level Compression.

blocksize

Set to the size, in bytes, for each block in a table. The blocksize must be between 8192 and 2097152 bytes, and be a multiple of 8192. The default is 32768.

compresslevel

For Zstd compression of append-optimized tables, set to an integer value from 1 (fastest compression) to 19 (highest compression ratio). For zlib compression, the valid range is from 1 to 9. For RLE_TYPE, the compression level can be an integer value from 1 (fastest compression) to 4 (highest compression ratio).

compresstype

Set to ZLIB (the default), ZSTD, or RLE_TYPE, to specify the type of compression used. The value NONE deactivates compression. Zstd provides for both speed or a good compression ratio, tunable with the compresslevel option. zlib is provided for backwards-compatibility. Zstd outperforms these compression types on usual workloads.

The value RLE_TYPE, which is supported only for append-optimized, column-oriented tables, enables the run-length encoding (RLE) compression algorithm. RLE compresses data better than the Zstd or zlib compression algorithms when the same data value occurs in many consecutive rows.

For columns of type BIGINT, INTEGER, DATE, TIME, or TIMESTAMP, delta compression is also applied if the compresstype option is set to RLE_TYPE compression. The delta compression algorithm is based on the delta between column values in consecutive rows and is designed to improve compression when data is loaded in sorted order or the compression is applied to column data that is in sorted order.

INHERITS ( parent_table [, …])

The optional INHERITS clause specifies a list of tables from which the new table automatically inherits all columns. Parent tables can be plain tables or foreign tables.

Use of INHERITS creates a persistent relationship between the new child table and its parent table(s). Schema modifications to the parent(s) normally propagate to children as well, and by default the data of the child table is included in scans of the parent(s).

If the same column name exists in more than one parent table, an error is reported unless the data types of the columns match in each of the parent tables. If there is no conflict, then the duplicate columns are merged to form a single column in the new table. If the column name list of the new table contains a column name that is also inherited, the data type must likewise match the inherited column(s), and the column definitions are merged into one. If the new table explicitly specifies a default value for the column, this default overrides any defaults from inherited declarations of the column. Otherwise, any parents that specify default values for the column must all specify the same default, or Greenplum reports an error.

CHECK constraints are merged in essentially the same way as columns: if multiple parent tables or the new table definition contain identically-named CHECK constraints, these constraints must all have the same check expression, or an error will be reported. Constraints having the same name and expression will be merged into one copy. A constraint marked NO INHERIT in a parent will not be considered. Notice that an unnamed CHECK constraint in the new table will never be merged, since a unique name will always be chosen for it.

Column STORAGE settings are also copied from parent tables.

If a column in the parent table is an identity column, that property is not inherited. You can declare a column in the child table an identity column if desired.

PARTITION BY { RANGE | LIST | HASH } ( { column_name | ( expression ) } [ opclass ] [, ...] )

The optional PARTITION BY clause of the modern partitioning syntax specifies a strategy of partitioning the table. The table thus created is referred to as a partitioned table. The parenthesized list of columns or expressions forms the partition key for the table. When using range or hash partitioning, the partition key can include multiple columns or expressions (up to 32), but for list partitioning, the partition key must consist of a single column or expression.

Range and list partitioning require a btree operator class, while hash partitioning requires a hash operator class. If no operator class is specified explicitly, the default operator class of the appropriate type will be used; if no default operator class exists, Greenplum raises an error. When hash partitioning is used, the operator class used must implement support function 2 (see Index Method Support Routines in the PostgreSQL documentation for details).

Note

Only the modern partitioning syntax supports hash partitions.

A partitioned table is divided into sub-tables (called partitions), which are typically created using separate CREATE TABLE commands. The partitioned table is itself empty. A data row inserted into the table is routed to a partition based on the value of columns or expressions in the partition key. If no existing partition matches the values in the new row, Greenplum Database reports an error.

Partitioned tables do not support EXCLUDE constraints; however, you can define these constraints on individual partitions.

Refer to Partitioning Large Tables for further discussion on table partitioning.

PARTITION OF parent_table { FOR VALUES partition_bound_spec | DEFAULT }

The PARTITION OF clause of the modern partitioning syntax creates the table as a partition of the specified parent table. You can create the table either as a partition for specific values using FOR VALUES or as a default partition using DEFAULT. Any indexes and constraints that exist in the parent table are cloned on the new partition.

The partition_bound_spec must correspond to the partitioning method and partition key of the parent table, and must not overlap with any existing partition of that parent. The form with IN is used for list partitioning, the form with FROM and TO is used for range partitioning, and the form with WITH is used for hash partitioning.

partition_bound_expr is any variable-free expression (subqueries, window functions, aggregate functions, and set-returning functions are not allowed). Its data type must match the data type of the corresponding partition key column. The expression is evaluated once at table creation time, so it can even contain volatile expressions such as CURRENT_TIMESTAMP.

When creating a list partition, you can specify NULL to signify that the partition allows the partition key column to be null. However, there cannot be more than one such list partition for a given parent table. NULL cannot be specified for range partitions.

When creating a range partition, the lower bound specified with FROM is an inclusive bound, whereas the upper bound specified with TO is an exclusive bound. That is, the values specified in the FROM list are valid values of the corresponding partition key columns for this partition, whereas those in the TO list are not. Note that this statement must be understood according to the rules of row-wise comparison (see Row Constructor Comparison in the PostgreSQL documentation for more information.). For example, given PARTITION BY RANGE (x, y), a partition bound FROM (1, 2) TO (3, 4) allows x=1 with any y>=2, x=2 with any non-null y, and x=3 with any y<4.

The special values MINVALUE and MAXVALUE may be used when creating a range partition to indicate that there is no lower or upper bound on the column's value. For example, a partition defined using FROM (MINVALUE) TO (10) allows any values less than 10, and a partition defined using FROM (10) TO (MAXVALUE) allows any values greater than or equal to 10.

When creating a range partition involving more than one column, it can also make sense to use MAXVALUE as part of the lower bound, and MINVALUE as part of the upper bound. For example, a partition defined using FROM (0, MAXVALUE) TO (10, MAXVALUE) allows any rows where the first partition key column is greater than 0 and less than or equal to 10. Similarly, a partition defined using FROM ('a', MINVALUE) TO ('b', MINVALUE) allows any rows where the first partition key column starts with "a".

Note that if MINVALUE or MAXVALUE is used for one column of a partitioning bound, the same value must be used for all subsequent columns. For example, (10, MINVALUE, 0) is not a valid bound; you must specify (10, MINVALUE, MINVALUE).

Also note that some element types, such as timestamp, have a notion of "infinity", which is just another value that can be stored. This is different from MINVALUE and MAXVALUE, which are not real values that can be stored, but rather they are ways of saying that the value is unbounded. MAXVALUE can be thought of as being greater than any other value, including "infinity" and MINVALUE as being less than any other value, including "minus infinity". Thus the range FROM ('infinity') TO (MAXVALUE) is not an empty range; it allows precisely one value to be stored — "infinity".

If DEFAULT is specified, the table will be created as the default partition of the parent table. This option is not available for hash-partitioned tables. Greenplum routes a partition key value not fitting into any other partition of the given parent to the default partition.

When a table has an existing DEFAULT partition and a new partition is added to it, the default partition must be scanned to verify that it does not contain any rows which properly belong in the new partition. If the default partition contains a large number of rows, this may be a slow operation. Greenplum skips the scan if the default partition is a foreign table or if it has a constraint which proves that it cannot contain rows which should be placed in the new partition.

When creating a hash partition, you must specify a modulus and a remainder. The modulus must be a positive integer, and the remainder must be a non-negative integer less than the modulus. Typically, when initially setting up a hash-partitioned table, you should choose a modulus equal to the number of partitions and assign every table the same modulus and a different remainder (see examples below). However, it is not required that every partition have the same modulus, only that every modulus which occurs among the partitions of a hash-partitioned table is a factor of the next larger modulus. This allows the number of partitions to be increased incrementally without needing to move all the data at once. For example, suppose you have a hash-partitioned table with 8 partitions, each of which has modulus 8, but find it necessary to increase the number of partitions to 16. You can detach one of the modulus-8 partitions, create two new modulus-16 partitions covering the same portion of the key space (one with a remainder equal to the remainder of the detached partition, and the other with a remainder equal to that value plus 8), and repopulate them with data. You can then repeat this -- perhaps at a later time -- for each modulus-8 partition until none remain. While this may still involve a large amount of data movement at each step, it is still preferable to having to create a whole new table and move all the data at once.

A partition must have the same column names and types as the partitioned table to which it belongs. Modifications to the column names or types of a partitioned table automatically propagate to all partitions. CHECK constraints are inherited automatically by every partition, but an individual partition may specify additional CHECK constraints; additional constraints with the same name and condition as in the parent will be merged with the parent constraint. Defaults may be specified separately for each partition. But note that a partition's default value is not applied when inserting a tuple through a partitioned table.

Greenplum automatically routes rows inserted into a partitioned table to the correct partition. If no suitable partition exists, Greenplum Database returns an error.

Operations such as TRUNCATE which normally affect a table and all of its inheritance children will cascade to all partitions, but may also be performed on an individual partition. Note that dropping a partition with DROP TABLE requires taking an ACCESS EXCLUSIVE lock on the parent table.

LIKE source_table [like_option ...]

The LIKE clause specifies a table from which the new table automatically copies all column names, their data types, not-null constraints, and distribution policy.

Note

Storage properties and the partition structure are not copied to the new table.

Unlike INHERITS, the new table and original table are completely decoupled after creation is complete. Changes to the original table will not be applied to the new table, and it is not possible to include data of the new table in scans of the original table.

Also unlike INHERITS, columns and constraints copied by LIKE are not merged with similarly named columns and constraints. If the same name is specified explicitly or in another LIKE clause, Greenplum Database signals an error.

The optional like_option clauses specify which additional properties of the original table to copy. Specifying INCLUDING copies the property, specifying EXCLUDING omits the property. EXCLUDING is the default. If multiple specifications are made for the same kind of object, the last one is used. The available options are:

INCLUDING AM

The access method of the original table will be copied.

When you include AM, you must not explicitly specify the access method of the new table using the WITH or the USING clauses.

INCLUDING COMMENTS

Comments for the copied columns, constraints, and indexes will be copied. The default behavior is to exclude comments, resulting in the copied columns and constraints in the new table having no comments.

INCLUDING CONSTRAINTS

CHECK constraints will be copied. No distinction is made between column constraints and table constraints. Not-null constraints are always copied to the new table.

INCLUDING DEFAULTS

Default expressions for the copied column definitions will be copied. Otherwise, default expressions are not copied, resulting in the copied columns in the new table having null defaults. Note that copying defaults that call database-modification functions, such as nextval, may create a functional linkage between the original and new tables.

INCLUDING ENCODING

For an append-optimized, column-oriented original table, copies the per-column encodings.

INCLUDING GENERATED

Any generation expressions of copied column definitions will be copied. By default, new columns will be regular base columns.

INCLUDING IDENTITY

Any identity specifications of copied column definitions will be copied. A new sequence is created for each identity column of the new table, separate from the sequences associated with the old table.

INCLUDING INDEXES

Indexes, PRIMARY KEY, UNIQUE, and EXCLUDE constraints on the original table will be created on the new table. Names for the new indexes and constraints are chosen according to the default rules, regardless of how the originals were named. (This behavior avoids possible duplicate-name failures for the new indexes.)

INCLUDING RELOPT

Copies relation storage options from the original table. For append-optimized and append-optimized, column-oriented tables, copies the blocksize, compresslevel, and compresstype. For heap tables, copies the fillfactor. You can also specify relation storage parameters. When you include RELOPT options, you must not explicitly specify relation storage options for the new table using the WITH clause.

INCLUDING STATISTICS

Extended statistics are copied to the new table.

INCLUDING STORAGE

STORAGE settings for the copied column definitions will be copied. The default behavior is to exclude STORAGE settings, resulting in the copied columns in the new table having type-specific default settings.

INCLUDING ALL

INCLUDING ALL is an abbreviated form of all available options (It may be useful to specify individual EXCLUDING clauses after INCLUDING ALL to select all but some specific options.)

You can also use the LIKE clause to copy column definitions from views, foreign tables, or composite types. Greenplum Database ignores inapplicable options (for example, INCLUDING INDEXES from a view).

CONSTRAINT constraint_name

An optional name for a column or table constraint. If the constraint is violated, the constraint name is present in error messages, so constraint names like column must be positive can be used to communicate helpful constraint information to client applications. (Use double-quotes to specify constraint names that contain spaces.) If a constraint name is not specified, the system generates a name.

Note

The specified constraint_name is used for the constraint, but a system-generated unique name is used for the index name. In some prior releases, the provided name was used for both the constraint name and the index name.

NOT NULL

The column is not allowed to contain null values.

NULL

The column is allowed to contain null values. This is the default.

This clause is only provided for compatibility with non-standard SQL databases. Its use is discouraged in new applications.

CHECK (expression) [ NO INHERIT ]

The CHECK clause specifies an expression producing a Boolean result which new or updated rows must satisfy for an insert or update operation to succeed. Expressions evaluating to TRUE or UNKNOWN succeed. Should any row of an insert or update operation produce a FALSE result, Greenplum raises an error exception, and the insert or update does not alter the database. A check constraint specified as a column constraint should reference that column's value only, while an expression appearing in a table constraint can reference multiple columns.

Currently, CHECK expressions cannot contain subqueries nor refer to variables other than columns of the current row. You can reference the system column tableoid, but not any other system column.

A constraint marked with NO INHERIT will not propagate to child tables.

When a table has multiple CHECK constraints, they will be tested for each row in alphabetical order by name, after checking NOT NULL constraints. (Previous Greenplum Database versions did not honor any particular firing order for CHECK constraints.)

DEFAULT default_expr

The DEFAULT clause assigns a default data value for the column whose column definition it appears within. The value is any variable-free expression (in particular, cross-references to other columns in the current table are not allowed). Subqueries are not allowed either. The data type of the default expression must match the data type of the column. The default expression will be used in any insert operation that does not specify a value for the column. If there is no default for a column, then the default is null.

GENERATED ALWAYS AS ( generation_expr ) STORED

This clause creates the column as a generated column. The column cannot be written to, and when read the result of the specified expression will be returned.

The keyword STORED is required to signify that the column will be computed on write and will be stored on disk.

The generation expression can refer to other columns in the table, but not other generated columns. Any functions and operators used must be immutable. References to other tables are not allowed.

GENERATED { ALWAYS | BY DEFAULT } AS IDENTITY [ ( sequence_options ) ]

This clause creates the column as an identity column. Greenplum Database attaches an implicit sequence to it, and automatically assigns a value from the sequence to the column in new rows. Such a column is implicitly NOT NULL.

The clauses ALWAYS and BY DEFAULT determine how the sequence value is given precedence over a user-specified value in an INSERT statement. If ALWAYS is specified, a user-specified value is only accepted if the INSERT statement specifies OVERRIDING SYSTEM VALUE. If BY DEFAULT is specified, then the user-specified value takes precedence. See INSERT for details. (In the COPY command, ueser-specified values are always used regardless of this setting.)

You can use the optional sequence_options clause to override the options of the sequence. See CREATE SEQUENCE for details.

UNIQUE ( column_constraint )

UNIQUE ( column_name [, ... ] ) [ INCLUDE ( column_name [, ...]) ] ( table_constraint )

The UNIQUE constraint specifies that a group of one or more columns of a table may contain only unique values. The behavior of a unique table constraint is the same as that of a unique column constraint, with the additional capability to span multiple columns. The constraint therefore enforces that any two rows must differ in at least one of these columns.

For the purpose of a unique constraint, null values are not considered equal. The column(s) that are unique must contain all the columns of the Greenplum distribution key. In addition, the <key> must contain all the columns in the partition key if the table is partitioned. Note that a <key> constraint in a partitioned table is not the same as a simple UNIQUE INDEX.

Each unique constraint should name a set of columns that is different from the set of columns named by any other unique or primary key constraint defined for the table. (Otherwise, Greenplum discards redundant unique constraints.)

When establishing a unique constraint for a multi-level partition hierarchy, all of the columns in the partition key of the target partitioned table, as well as those of all its descendant partitioned tables, must be included in the constraint definition.

Adding a unique constraint automatically creates a unique btree index on the column or group of columns used in the constraint.

The optional INCLUDE clause adds to that index one or more columns that are simply "payload": uniqueness is not enforced on them, and the index cannot be searched on the basis of those columns. However they can be retrieved by an index-only scan. Note that although the constraint is not enforced on included columns, it still depends on them. Consequently, some operations on such columns (for example, DROP COLUMN) can cause cascaded constraint and index deletion.

PRIMARY KEY ( column constraint )

PRIMARY KEY ( column_name [, ... ] ) [ INCLUDE ( column_name [, ...]) ] ( table constraint )

The PRIMARY KEY constraint specifies that a column or columns of a table may contain only unique (non-duplicate), non-null values. You can specify only one primary key for a table, whether as a column constraint or a table constraint.

The primary key constraint should name a set of columns that is different from the set of columns named by any unique constraint defined for the same table. (Otherwise, the unique constraint is redundant and will be discarded.)

PRIMARY KEY enforces the same data constraints as a combination of UNIQUE and NOT NULL, but identifying a set of columns as the primary key also provides metadata about the design of the schema, since a primary key implies that other tables can rely on this set of columns as a unique identifier for rows.

When placed on a partitioned table, PRIMARY KEY constraints share the restrictions previously described for UNIQUE constraints.

Adding a PRIMARY KEY constraint will automatically create a unique btree index on the column or group of columns used in the constraint.

The optional INCLUDE clause adds to that index one or more columns that are simply "payload": uniqueness is not enforced on them, and the index cannot be searched on the basis of those columns. However they can be retrieved by an index-only scan. Note that although the constraint is not enforced on included columns, it still depends on them. Consequently, some operations on such columns (for example, DROP COLUMN) can cause cascaded constraint and index deletion.

EXCLUDE [ USING index_method ] ( exclude_element WITH operator [, ... ] ) index_parameters [ WHERE ( predicate ) ]

The EXCLUDE clause defines an exclusion constraint, which guarantees that if any two rows are compared on the specified column(s) or expression(s) using the specified operator(s), not all of these comparisons will return TRUE. If all of the specified operators test for equality, this is equivalent to a UNIQUE constraint, although an ordinary unique constraint will be faster. However, exclusion constraints can specify constraints that are more general than simple equality. For example, you can specify a constraint that no two rows in the table contain overlapping circles by using the && operator.

Greenplum Database does not support specifying an exclusion constraint on a randomly-distributed table.

Exclusion constraints are implemented using an index, so each specified operator must be associated with an appropriate operator class for the index access method index_method. The operators are required to be commutative. Each exclude_element can optionally specify an operator class and/or ordering options; these are described fully under CREATE INDEX.

The access method must support amgettuple; at present this means GIN cannot be used. Although it's allowed, there is little point in using B-tree or hash indexes with an exclusion constraint, because this does nothing that an ordinary unique constraint doesn't do better. So in practice the access method will always be GiST or SP-GiST.

The predicate allows you to specify an exclusion constraint on a subset of the table; internally this creates a partial index. Note that parentheses are required around the predicate.

REFERENCES reftable [ ( refcolumn ) ]

[ MATCH matchtype ] [ON DELETE key_action] [ON UPDATE key_action] (column constraint)

FOREIGN KEY (column_name [, ...]) REFERENCES reftable [ ( refcolumn [, ... ] ) ]

[ MATCH matchtype ] [ ON DELETE referential_action ] [ ON UPDATE referential_action ] (table constraint)

The REFERENCES and FOREIGN KEY clauses specify referential integrity constraints (foreign key constraints). Greenplum accepts referential integrity constraints but does not enforce them.

DEFERRABLE

NOT DEFERRABLE

The [NOT] DEFERRABLE clause controls whether the constraint can be deferred. A constraint that is not deferrable will be checked immediately after every command. Checking of constraints that are deferrable can be postponed until the end of the transaction (using the SET CONSTRAINTS command). NOT DEFERRABLE is the default. Currently, only UNIQUE, PRIMARY KEY, and EXCLUDE constraints accept this clause. NOT NULL and CHECK constraints are not deferrable. REFERENCES (foreign key) constraints accept this clause but are not enforced. Note that deferrable constraints cannot be used as conflict arbitrators in an INSERT statement that includes an ON CONFLICT DO UPDATE clause.

Note that deferrable constraints cannot be used as conflict arbitrators in an INSERT statement that includes an ON CONFLICT DO UPDATE clause.

INITIALLY IMMEDIATE

INITIALLY DEFERRED

If a constraint is deferrable, this clause specifies the default time to check the constraint. If the constraint is INITIALLY IMMEDIATE, it is checked after each statement. This is the default. If the constraint is INITIALLY DEFERRED, it is checked only at the end of the transaction. You can alter the constraint check time with the SET CONSTRAINTS command.

USING access_method

The optional USING clause specifies the table access method to use to store the contents for the new table you are creating; the method must be an access method of type TABLE. Set to heap to access the table as a heap-storage table, ao_row to access the table as an append-optimized table with row-oriented storage (AO), or ao_column to access the table as an append-optimized table with column-oriented storage (AO/CO). The default access method is determined by the value of the default_table_access_method server configuration parameter.

Note: Although you can specify the table's access method using WITH (appendoptimized=true|false, orientation=row|column) VMware recommends that you use USING instead.

WITH ( storage_parameter=value )

The WITH clause specifies optional storage parameters for a table or index; see Storage Parameters below for details. For backward-compatibility the WITH clause for a table can also include OIDS=FALSE to specify that rows of the new table should not contain OIDs (object identifiers), OIDS=TRUE. is no longer supported.

ON COMMIT

You can control the behavior of temporary tables at the end of a transaction block using ON COMMIT. The three options are:

PRESERVE ROWS - No special action is taken at the ends of transactions for temporary tables. This is the default behavior.

DELETE ROWS - All rows in the temporary table will be deleted at the end of each transaction block. Essentially, Greenplum Database performs an automatic TRUNCATE at each commit. When used on a partitioned table, this operation is not cascaded to its partitions.

DROP - The temporary table will be dropped at the end of the current transaction block. When used on a partitioned table, this action drops its partitions and when used on tables with inheritance children, it drops the dependent children.

TABLESPACE tablespace

The name of the tablespace in which the new table is to be created. If not specified, the database's default_tablespace is consulted, or temp_tablespaces if the table is temporary. For partitioned tables, since no storage is required for the table itself, the tablespace specified overrides default_tablespace as the default tablespace to use for any newly created partitions when no other tablespace is explicitly specified.

USING INDEX TABLESPACE tablespace

This clause allows selection of the tablespace in which the index associated with a UNIQUE, PRIMARY KEY, or EXCLUDE constraint will be created. If not specified, the database's default_tablespace is used, or temp_tablespaces if the table is temporary.

DISTRIBUTED BY ( column [opclass] [, ... ] )

DISTRIBUTED RANDOMLY

DISTRIBUTED REPLICATED

Used to declare the Greenplum Database distribution policy for the table. DISTRIBUTED BY uses hash distribution with one or more columns declared as the distribution key. For the most even data distribution, the distribution key should be the primary key of the table or a unique column (or set of columns). If that is not possible, then you may choose DISTRIBUTED RANDOMLY, which will send the data randomly to the segment instances. Additionally, an operator class, opclass, can be specified, to use a non-default hash function.

The Greenplum Database server configuration parameter gp_create_table_random_default_distribution controls the default table distribution policy if the DISTRIBUTED BY clause is not specified when you create a table. Greenplum Database follows these rules to create a table if a distribution policy is not specified.

If the value of the parameter is off (the default), Greenplum Database chooses the table distribution key based on the command:

• If a LIKE or INHERITS clause is specified, then Greenplum copies the distribution key from the source or parent table.
• If PRIMARY KEY, UNIQUE, or EXCLUDE constraints are specified, then Greenplum chooses the largest subset of all the key columns as the distribution key.
• If no constraints nor a LIKE or INHERITS clause is specified, then Greenplum chooses the first suitable column as the distribution key. (Columns with geometric or user-defined data types are not eligible as Greenplum distribution key columns.)

If the value of the parameter is set to on, Greenplum Database follows these rules:

• If PRIMARY KEY, UNIQUE, or EXCLUDE columns are not specified, the distribution of the table is random (DISTRIBUTED RANDOMLY). Table distribution is random even if the table creation command contains the LIKE or INHERITS clause.
• If PRIMARY KEY, UNIQUE, or EXCLUDE columns are specified, you must also specify a DISTRIBUTED BY clause If a DISTRIBUTED BY clause is not specified as part of the table creation command, the command fails.

The DISTRIBUTED REPLICATED clause replicates the entire table to all Greenplum Database segment instances. It can be used when it is necessary to run user-defined functions on segments when the functions require access to all rows in the table, or to improve query performance by preventing broadcast motions.

Classic Partitioning Syntax Parameters

Descriptions of additional parameters that are specific to the classic partitioning syntax follow.

Note

VMware recommends that you use the modern partitioning syntax.

CREATE TABLE table_name ... PARTITION BY

When creating a partitioned table using the classic syntax, Greenplum Database creates the root partitioned table with the specified table name. Greenplum also creates a hierarchy of tables, child tables, that are the sub-partitions based on the partitioning options that you specify. The pg_partitioned_table system catalog contains information about the sub-partition tables.

classic_partition_spec

Declares the individual partitions to create. Each partition can be defined individually or, for range partitions, you can use the EVERY clause (with a START and optional END clause) to define an increment pattern to use to create the individual partitions.

DEFAULT PARTITION name

Declares a default partition. When data does not match the bouds of an existing partition, Greenplum inserts it into the default partition. Partition designs that do not identify a default partition will reject incoming rows that do not match an existing partition.

PARTITION name

Declares a name to use for the partition. Partitions are created using the following naming convention: <table_name>_<level#>_prt_<given_name>.

VALUES

For list partitions, defines the value(s) that the partition will contain.

START

For range partitions, defines the starting range value for the partition. By default, start values are INCLUSIVE. For example, if you declared a start date of ' 2016-01-01', then the partition would contain all dates greater than or equal to ' 2016-01-01'. The data type of the START expression must support a suitable + operator, for example timestamp or integer (not float or text) if it is defined with the EXCLUSIVE keyword. Typically the data type of the START expression is the same type as the partition key column. If that is not the case, then you must explicitly cast to the intended data type.

END

For range partitions, defines the ending range value for the partition. By default, end values are EXCLUSIVE. For example, if you declared an end date of ' 2016-02-01', then the partition would contain all dates less than but not equal to ' 2016-02-01'. The data type of the END expression must support a suitable + operator, for example timestamp or integer (not float or text) if it is defined with the INCLUSIVE keyword. The data type of the END expression is typically the same type as the partition key column. If that is not the case, then you must explicitly cast to the intended data type.

EVERY

For range partitions, defines how to increment the values from START to END to create individual partitions. The data type of the EVERY expression is typically the same type as the partition key column. If that is not the case, then you must explicitly cast to the intended data type.

WITH

Sets the table storage options for a partition. For example, you may want older partitions to be append-optimized tables and newer partitions to be regular heap tables. See Storage Parameters, below.

TABLESPACE

The name of the tablespace in which the partition is to be created.

SUBPARTITION BY

Declares one or more columns by which to sub-partition the first-level partitions of the table. For LIST partitioning, the partition key must consist of a single column or expression. The format of the sub-partition specification is similar to that of a partition specification described above.

SUBPARTITION TEMPLATE

Instead of declaring each sub-partition definition individually for each partition, you can optionally declare a sub-partition template to be used to create the sub-partitions (lower level child tables). This sub-partition specification would then apply to all parent partitions.

Storage Parameters

The WITH clause can specify storage parameters for tables, and for indexes associated with a UNIQUE, PRIMARY KEY, or EXCLUDE constraint. Storage parameters for indexes are documented on the CREATE INDEX reference page. The storage parameters currently available for tables are listed below. For many of these parameters, as shown, there is an additional parameter with the same name prefixed with toast., which controls the behavior of the table's secondary TOAST table, if any. If a table parameter value is set and the equivalent toast. parameter is not, the TOAST table will use the table's parameter value. Specifying these parameters for partitioned tables is not supported, but you may specify them for individual leaf partitions.

Note that you can also set storage parameters for a particular partition or sub-partition by declaring the WITH clause in the classic syntax partition specification. The lowest-level partition's settings have priority.

You can specify the defaults for some of the table storage options with the server configuration parameter gp_default_storage_options. For information about setting default storage options, see Notes.

Note

Because Greenplum Database does not permit autovacuuming user tables, it accepts, but does not apply, certain per-table parameter settings as noted below.

The following table storage parameters are available:

analyze_hll_non_part_table

Set this storage parameter to true to force collection of HLL statistics even if the table is not part of a partitioned table. This is useful if the table will be exchanged or added to a partitioned table, so that the table does not need to be re-analyzed. The default is false.

appendoptimized

Set to TRUE to create the table as an append-optimized table. If FALSE or not declared, the table will be created as a regular heap-storage table.

blocksize

Set to the size, in bytes, for each block in a table. The blocksize must be between 8192 and 2097152 bytes, and be a multiple of 8192. The default is 32768. The blocksize option is valid only if the table is append-optimized.

checksum

This option is valid only for append-optimized tables. The value TRUE is the default and enables CRC checksum validation for append-optimized tables. The checksum is calculated during block creation and is stored on disk. Checksum validation is performed during block reads. If the checksum calculated during the read does not match the stored checksum, the transaction is cancelled. If you set the value to FALSE to deactivate checksum validation, checking the table data for on-disk corruption will not be performed.

compresslevel

For Zstd compression of append-optimized tables, set to an integer value from 1 (fastest compression) to 19 (highest compression ratio). For zlib compression, the valid range is from 1 to 9. If not declared, the default is 1. For RLE_TYPE, the compression level can be an integer value from 1 (fastest compression) to 4 (highest compression ratio).

The compresslevel option is valid only if the table is append-optimized.

compresstype

Set to ZLIB (the default), ZSTD, or RLE_TYPE to specify the type of compression used. The value NONE deactivates compression. Zstd provides for both speed and a good compression ratio, tunable with the compresslevel option. zlib is provided for backward compatibility. Zstd outperforms these compression types on usual workloads. The compresstype option is only valid if the table is append-optimized.

The value RLE_TYPE, which is supported only for append-optimized, column-oriented tables, enables the run-length encoding (RLE) compression algorithm. RLE compresses data better than the Zstd or zlib compression algorithms when the same data value occurs in many consecutive rows.

For columns of type BIGINT, INTEGER, DATE, TIME, or TIMESTAMP, delta compression is also applied if the compresstype option is set to RLE_TYPE compression. The delta compression algorithm is based on the delta between column values in consecutive rows and is designed to improve compression when data is loaded in sorted order or the compression is applied to column data that is in sorted order.

For information about using table compression, see Choosing the Table Storage Model in the Greenplum Database Administrator Guide.

fillfactor

The fillfactor for a table is a percentage between 10 and 100. 100 (complete packing) is the default. When a smaller fillfactor is specified, INSERT operations pack table pages only to the indicated percentage; the remaining space on each page is reserved for updating rows on that page. This gives UPDATE a chance to place the updated copy of a row on the same page as the original, which is more efficient than placing it on a different page. For a table whose entries are never updated, complete packing is the best choice, but in heavily updated tables smaller fillfactors are appropriate. This parameter cannot be set for TOAST tables.

The fillfactor option is valid only for heap tables (tables that specify the heap access method or the appendoptimized=FALSE storage parameter).

orientation

Set to column for column-oriented storage, or row (the default) for row-oriented storage. This option is only valid if the table is append-optimized. Heap-storage tables can only be row-oriented.

The following parameters are supported for heap tables only:

toast_tuple_target (integer)

The toast_tuple_target specifies the minimum tuple length required before Greenplum attempts to compress and/or move long column values into TOAST tables, and is also the target length Greenplum tries to reduce the length below once toasting begins. This affects columns marked as External (for move), Main (for compression), or Extended (for both) and applies only to new tuples. There is no effect on existing rows. By default this parameter is set to allow at least 4 tuples per block, which with the default blocksize will be 8184 bytes. Valid values are between 128 bytes and the (blocksize - header), by default 8160 bytes. Changing this value may not be useful for very short or very long rows. Note that the default setting is often close to optimal, and it is possible that setting this parameter could have negative effects in some cases. You can not set this parameter for TOAST tables.

parallel_workers (integer)

Sets the number of workers that should be used to assist a parallel scan of this table. If not set, Greenplum determines a value based on the relation size. The actual number of workers chosen by the planner or by utility statements that use parallel scans may be less, for example due to the setting of max_worker_processes.

autovacuum_enabled, toast.autovacuum_enabled (boolean)

Enables or disables the autovacuum daemon for a particular table. If true, the autovacuum daemon will perform automatic VACUUM and/or ANALYZE operations on this table following the rules discussed in The Autovacuum Daemon in the PostgreSQL documentation. If false, Greenplum does not autovacuum the table, except to prevent transaction ID wraparound. Note that the autovacuum daemon does not run at all (except to prevent transaction ID wraparound) if the autovacuum parameter is false; setting individual tables' storage parameters does not override that. So there is seldom much point in explicitly setting this storage parameter to true, only to false.

vacuum_index_cleanup, toast.vacuum_index_cleanup (boolean)

Enables or disables index cleanup when VACUUM is run on this table. The default value is true. Disabling index cleanup can speed up VACUUM very significantly, but may also lead to severely bloated indexes if table modifications are frequent. The INDEX_CLEANUP parameter of VACUUM, if specified, overrides the value of this option.

Setting this to false may be useful when you need to run VACUUM as quickly as possible, for example to prevent imminent transaction ID wraparound. However, if you do not perform index cleanup regularly, performance may suffer, because as the table is modified, indexes accumulate dead tuples and the table itself accumulates dead line pointers that cannot be removed until index cleanup completes.

vacuum_truncate, toast.vacuum_truncate (boolean)

Enables or disables vacuum to attempt to truncate any empty pages at the end of this table. The default value is true. If true, VACUUM and autovacuum truncate the empty pages, and the disk space for the truncated pages is returned to the operating system. Note that the truncation requires an ACCESS EXCLUSIVE lock on the table. The TRUNCATE parameter of VACUUM, if specified, overrides the value of this option.

autovacuum_vacuum_threshold, toast.autovacuum_vacuum_threshold (integer)

Per-table value for the autovacuum_vacuum_threshold server configuration parameter.

Note

Greenplum accepts, but does not apply, values for these storage parameters.

autovacuum_vacuum_scale_factor, toast.autovacuum_vacuum_scale_factor (floating point)

Per-table value for the autovacuum_vacuum_scale_factor server configuration parameter.

Note

Greenplum accepts, but does not apply, values for these storage parameters.

autovacuum_analyze_threshold (integer)

Per-table value for the autovacuum_analyze_threshold server configuration parameter.

autovacuum_analyze_scale_factor (floating point)

Per-table value for the autovacuum_analyze_scale_factor server configuration parameter.

autovacuum_vacuum_cost_delay, toast.autovacuum_vacuum_cost_delay (floating point)

Per-table value for the autovacuum_vacuum_cost_delay server configuration parameter.

Note

Greenplum accepts, but does not apply, values for these storage parameters.

autovacuum_vacuum_cost_limit, toast.autovacuum_vacuum_cost_limit (integer)

Per-table value for the autovacuum_vacuum_cost_limit server configuration parameter.

Note

Greenplum accepts, but does not apply, values for these storage parameters.

autovacuum_freeze_min_age, toast.autovacuum_freeze_min_age (integer)

Per-table value for the vacuum_freeze_min_age parameter. Note that autovacuum will ignore per-table autovacuum_freeze_min_age parameters that are larger than half of the system-wide autovacuum_freeze_max_age setting.

Note

Greenplum accepts, but does not apply, values for these storage parameters.

autovacuum_freeze_max_age, toast.autovacuum_freeze_max_age (integer)

Per-table value for the autovacuum_freeze_max_age server configuration parameter. Note that autovacuum will ignore per-table autovacuum_freeze_max_age parameters that are larger than the system-wide setting (it can only be set smaller).

Note

Greenplum accepts, but does not apply, values for these storage parameters.

autovacuum_freeze_table_age, toast.autovacuum_freeze_table_age (integer)

Per-table value for the vacuum_freeze_table_age server configuration parameter.

Note

Greenplum accepts, but does not apply, values for these storage parameters.

autovacuum_multixact_freeze_min_age, toast.autovacuum_multixact_freeze_min_age (integer)

Per-table value for the vacuum_multixact_freeze_min_age server configuration parameter. Note that autovacuum will ignore per-table autovacuum_multixact_freeze_min_age parameters that are larger than half of the system-wide autovacuum_multixact_freeze_max_age setting.

Note

Greenplum accepts, but does not apply, values for these storage parameters.

autovacuum_multixact_freeze_max_age, toast.autovacuum_multixact_freeze_max_age (integer)

Per-table value for the autovacuum_multixact_freeze_max_age server configuration parameter. Note that autovacuum will ignore per-table autovacuum_multixact_freeze_max_age parameters that are larger than the system-wide setting (it can only be set smaller).

Note

Greenplum accepts, but does not apply, values for these storage parameters.

autovacuum_multixact_freeze_table_age, toast.autovacuum_multixact_freeze_table_age (integer)

Per-table value for the vacuum_multixact_freeze_table_age server configuration parameter.

Note

Greenplum accepts, but does not apply, values for these storage parameters.

log_autovacuum_min_duration, toast.log_autovacuum_min_duration (integer)

Per-table value for the log_autovacuum_min_duration server configuration parameter.

Note

Greenplum accepts, but does not apply, values for these storage parameters.

Notes

Greenplum Database automatically creates an index for each unique constraint and primary key constraint to enforce uniqueness, so it is not necessary to create an index explicitly for primary key columns. (See CREATE INDEX for more information.)

Unique constraints and primary keys are not inherited.

You cannot define a table with more than 1600 columns. (In practice, the effective limit is usually lower because of tuple-length constraints.)

The Greenplum Database data types VARCHAR or TEXT handle padding added to the textual data (space characters added after the last non-space character) as significant characters; the data type CHAR does not.

In Greenplum Database, values of type CHAR(<n>) are padded with trailing spaces to the specified width <n>. The values are stored and displayed with the spaces. However, the padding spaces are treated as semantically insignificant. When the values are distributed, the trailing spaces are disregarded. The trailing spaces are also treated as semantically insignificant when comparing two values of data type CHAR, and the trailing spaces are removed when converting a character value to one of the other string types.

Greenplum Database requires certain special conditions for primary key and unique constraints with regards to columns that are the distribution key in a Greenplum table. For a unique constraint to be enforced in Greenplum Database, the table must be hash-distributed (not DISTRIBUTED RANDOMLY), and the constraint columns must be the same as, or a superset of, the table's distribution key columns.

Replicated tables (DISTRIBUTED REPLICATED) can have both PRIMARY KEY and UNIQUE column constraints.

A primary key constraint is simply a combination of a unique constraint and a not-null constraint.

Foreign key constraints are not supported in Greenplum Database.

For inherited tables, unique constraints, primary key constraints, indexes and table privileges are not inherited in the current implementation.

For append-optimized tables, UPDATE and DELETE are not allowed in a repeatable read or serializable transaction and will cause the transaction to end prematurely.

DECLARE...FOR UPDATE, and triggers are not supported with append-optimized tables.

CLUSTER on append-optimized tables is only supported over B-tree indexes.

GPORCA does not support list partitions with multi-column (composite) partition keys.

Examples

Create a table named rank in the schema named baby and distribute the data using the columns rank and year:

CREATE TABLE baby.rank (id int, rank int, year smallint, count int )
DISTRIBUTED BY (rank, year);

Create tables named films and distributors (the primary key will be used as the Greenplum distribution key by default):

CREATE TABLE films (
    code        char(5) CONSTRAINT firstkey PRIMARY KEY,
    title       varchar(40) NOT NULL,
    did         integer NOT NULL,
    date_prod   date,
    kind        varchar(10),
    len         interval hour to minute
);

CREATE TABLE distributors (
    did    integer PRIMARY KEY GENERATED BY DEFAULT AS IDENTITY,
    name   varchar(40) NOT NULL CHECK (name <> '')
);

Create a gzip-compressed, append-optimized table:

CREATE TABLE sales (txn_id int, qty int, date date) 
WITH (appendoptimized=true, compresslevel=5) 
DISTRIBUTED BY (txn_id);

Create a table with a 2-dimensional array:

CREATE TABLE array_int (
    vector  int[][]
);

Define a unique table constraint for the table films. Unique table constraints can be defined on one or more columns of the table:

CREATE TABLE films (
    code        char(5),
    title       varchar(40),
    did         integer,
    date_prod   date,
    kind        varchar(10),
    len         interval hour to minute,
    CONSTRAINT production UNIQUE(date_prod)
);

Define a check column constraint:

CREATE TABLE distributors (
    did     integer CHECK (did > 100),
    name    varchar(40)
);

Define a check table constraint:

CREATE TABLE distributors (
    did     integer,
    name    varchar(40),
    CONSTRAINT con1 CHECK (did > 100 AND name <> '')
);

Define a primary key table constraint for the table films:

CREATE TABLE films (
    code        char(5),
    title       varchar(40),
    did         integer,
    date_prod   date,
    kind        varchar(10),
    len         interval hour to minute,
    CONSTRAINT code_title PRIMARY KEY(code,title)
);

Define a primary key constraint for table distributors. The following two examples are equivalent, the first using the table constraint syntax, the second the column constraint syntax:

CREATE TABLE distributors (
    did     integer,
    name    varchar(40),
    PRIMARY KEY(did)
);

CREATE TABLE distributors (
    did     integer PRIMARY KEY,
    name    varchar(40)
);

Assign a literal constant default value for the column name, arrange for the default value of column did to be generated by selecting the next value of a sequence object, and make the default value of modtime be the time at which the row is inserted:

CREATE TABLE distributors (
    name      varchar(40) DEFAULT 'Luso Films',
    did       integer DEFAULT nextval('distributors_serial'),
    modtime   timestamp DEFAULT current_timestamp
);

Define two NOT NULL column constraints on the table distributors, one of which is explicitly given a name:

CREATE TABLE distributors (
    did     integer CONSTRAINT no_null NOT NULL,
    name    varchar(40) NOT NULL
);

Define a unique constraint for the name column:

CREATE TABLE distributors (
    did     integer,
    name    varchar(40) UNIQUE
);

The same, specified as a table constraint:

CREATE TABLE distributors (
    did     integer,
    name    varchar(40),
    UNIQUE(name)
);

Create the same table, specifying 70% fill factor for both the table and its unique index:

CREATE TABLE distributors (
    did     integer,
    name    varchar(40),
    UNIQUE(name) WITH (fillfactor=70)
)
WITH (fillfactor=70);

Create table cinemas in tablespace diskvol1`:

CREATE TABLE cinemas (
        id serial,
        name text,
        location text
) TABLESPACE diskvol1;

Create a composite type and a typed table:

CREATE TYPE employee_type AS (name text, salary numeric);

CREATE TABLE employees OF employee_type (
    PRIMARY KEY (name),
    salary WITH OPTIONS DEFAULT 1000
);

Modern Partitioning Syntax Examples

Create a range partitioned table:

CREATE TABLE measurement (
    logdate         date not null,
    peaktemp        int,
    unitsales       int
) PARTITION BY RANGE (logdate);

Create a range partitioned table with multiple columns in the partition key:

CREATE TABLE measurement_year_month (
    logdate         date not null,
    peaktemp        int,
    unitsales       int
) PARTITION BY RANGE (EXTRACT(YEAR FROM logdate), EXTRACT(MONTH FROM logdate));

Create a list partitioned table:

CREATE TABLE cities (
    city_id      bigserial not null,
    name         text not null,
    population   bigint
) PARTITION BY LIST (left(lower(name), 1));

Create a hash partitioned table:

CREATE TABLE orders (
    order_id     bigint not null,
    cust_id      bigint not null,
    status       text
) PARTITION BY HASH (order_id);

Create partition of a range partitioned table:

CREATE TABLE measurement_y2016m07
    PARTITION OF measurement (
    unitsales DEFAULT 0
) FOR VALUES FROM ('2016-07-01') TO ('2016-08-01');

Create a few partitions of a range partitioned table with multiple columns in the partition key:

CREATE TABLE measurement_ym_older
    PARTITION OF measurement_year_month
    FOR VALUES FROM (MINVALUE, MINVALUE) TO (2016, 11);

CREATE TABLE measurement_ym_y2016m11
    PARTITION OF measurement_year_month
    FOR VALUES FROM (2016, 11) TO (2016, 12);

CREATE TABLE measurement_ym_y2016m12
    PARTITION OF measurement_year_month
    FOR VALUES FROM (2016, 12) TO (2017, 01);

CREATE TABLE measurement_ym_y2017m01
    PARTITION OF measurement_year_month
    FOR VALUES FROM (2017, 01) TO (2017, 02);

Create partition of a list partitioned table:

CREATE TABLE cities_ab
    PARTITION OF cities (
    CONSTRAINT city_id_nonzero CHECK (city_id != 0)
) FOR VALUES IN ('a', 'b');

Create partition of a list partitioned table that is itself further partitioned and then add a partition to it:

CREATE TABLE cities_ab
    PARTITION OF cities (
    CONSTRAINT city_id_nonzero CHECK (city_id != 0)
) FOR VALUES IN ('a', 'b') PARTITION BY RANGE (population);

CREATE TABLE cities_ab_10000_to_100000
    PARTITION OF cities_ab FOR VALUES FROM (10000) TO (100000);

Create partitions of a hash partitioned table:

CREATE TABLE orders_p1 PARTITION OF orders
    FOR VALUES WITH (MODULUS 4, REMAINDER 0);
CREATE TABLE orders_p2 PARTITION OF orders
    FOR VALUES WITH (MODULUS 4, REMAINDER 1);
CREATE TABLE orders_p3 PARTITION OF orders
    FOR VALUES WITH (MODULUS 4, REMAINDER 2);
CREATE TABLE orders_p4 PARTITION OF orders
    FOR VALUES WITH (MODULUS 4, REMAINDER 3);

Create a default partition:

CREATE TABLE cities_partdef
    PARTITION OF cities DEFAULT;

Classic Partitioning Syntax Examples

Create a simple, single level partitioned table:

CREATE TABLE sales (id int, year int, qtr int, c_rank int, code char(1), region text)
DISTRIBUTED BY (id)
PARTITION BY LIST (code)
( PARTITION sales VALUES ('S'),
  PARTITION returns VALUES ('R')
);

Create a three level partitioned table that defines sub-partitions without the SUBPARTITION TEMPLATE clause:

CREATE TABLE sales (id int, year int, qtr int, c_rank int, code char(1), region text)
DISTRIBUTED BY (id)
PARTITION BY LIST (code)
  SUBPARTITION BY RANGE (c_rank)
    SUBPARTITION by LIST (region)

( PARTITION sales VALUES ('S')
   ( SUBPARTITION cr1 START (1) END (2)
      ( SUBPARTITION ca VALUES ('CA') ), 
      SUBPARTITION cr2 START (3) END (4)
        ( SUBPARTITION ca VALUES ('CA') ) ),

 PARTITION returns VALUES ('R')
   ( SUBPARTITION cr1 START (1) END (2)
      ( SUBPARTITION ca VALUES ('CA') ), 
     SUBPARTITION cr2 START (3) END (4)
        ( SUBPARTITION ca VALUES ('CA') ) )
);

Create the same partitioned table as the previous table using the SUBPARTITION TEMPLATE clause:

CREATE TABLE sales1 (id int, year int, qtr int, c_rank int, code char(1), region text)
DISTRIBUTED BY (id)
PARTITION BY LIST (code)

   SUBPARTITION BY RANGE (c_rank)
     SUBPARTITION TEMPLATE (
     SUBPARTITION cr1 START (1) END (2),
     SUBPARTITION cr2 START (3) END (4) )

     SUBPARTITION BY LIST (region)
       SUBPARTITION TEMPLATE (
       SUBPARTITION ca VALUES ('CA') )

( PARTITION sales VALUES ('S'),
  PARTITION  returns VALUES ('R')
);

Create a three level partitioned table using sub-partition templates and default partitions at each level:

CREATE TABLE sales (id int, year int, qtr int, c_rank int, code char(1), region text)
DISTRIBUTED BY (id)
PARTITION BY RANGE (year)

  SUBPARTITION BY RANGE (qtr)
    SUBPARTITION TEMPLATE (
    START (1) END (5) EVERY (1), 
    DEFAULT SUBPARTITION bad_qtr )

    SUBPARTITION BY LIST (region)
      SUBPARTITION TEMPLATE (
      SUBPARTITION usa VALUES ('usa'),
      SUBPARTITION europe VALUES ('europe'),
      SUBPARTITION asia VALUES ('asia'),
      DEFAULT SUBPARTITION other_regions)

( START (2009) END (2011) EVERY (1),
  DEFAULT PARTITION outlying_years);

Compatibility

CREATE TABLE command conforms to the SQL standard, with the following exceptions:

Temporary Tables

In the SQL standard, temporary tables are defined just once and automatically exist (starting with empty contents) in every session that needs them. Greenplum Database instead requires each session to issue its own CREATE TEMPORARY TABLE command for each temporary table to be used. This allows different sessions to use the same temporary table name for different purposes, whereas the standard's approach constrains all instances of a given temporary table name to have the same table structure.

The standard's distinction between global and local temporary tables is not in Greenplum Database. Greenplum Database will accept the GLOBAL and LOCAL keywords in a temporary table declaration, but they have no effect and are deprecated.

If the ON COMMIT clause is omitted, the SQL standard specifies that the default behavior as ON COMMIT DELETE ROWS. However, the default behavior in Greenplum Database is ON COMMIT PRESERVE ROWS. The ON COMMIT DROP option does not exist in the SQL standard.

Non-Deferred Uniqueness Constraints

When a UNIQUE or PRIMARY KEY constraint is not deferrable, Greeplum Database checks for uniqueness immediately whenever a row is inserted or modified. The SQL standard states that uniqueness should be enforced only at the end of the statement; this makes a difference when, for example, a single command updates multiple key values. To obtain standard-compliant behavior, declare the constraint as DEFERRABLE but not deferred (for example, INITIALLY IMMEDIATE). Note that this can be significantly slower than immediate uniqueness checking.

Column Check Constraints

Column Check Constraints — The SQL standard states that CHECK column constraints may only refer to the column they apply to; only CHECK table constraints may refer to multiple columns. Greenplum Database does not enforce this restriction; it treats column and table check constraints alike.

Exclude Constraint — The EXCLUDE constraint type is a Greenplum Database extension.

NULL Constraint — The NULL constraint is a Greenplum Database extension to the SQL standard that is included for compatibility with some other database systems (and for symmetry with the NOT NULL constraint). Since it is the default for any column, its presence is not required.

Constraint Naming

The SQL standard states that table and domain constraints must have names that are unique across the schema containing the table or domain. Greenplum is laxer: it only requires constraint names to be unique across the constraints attached to a particular table or domain. However, this extra freedom does not exist for index-based constraints (UNIQUE, PRIMARY KEY, and EXCLUDE constraints), because the associated index is named the same as the constraint, and index names must be unique across all relations within the same schema.

Greenplum Database does not currently record names for NOT NULL constraints at all, so they are not subject to the uniqueness restriction.

Inheritance

Multiple inheritance via the INHERITS clause is a Greenplum Database language extension. SQL:1999 and later define single inheritance using a different syntax and different semantics. SQL:1999-style inheritance is not yet supported by Greenplum Database.

Zero-Column Tables

Greenplum Database allows a table of no columns to be created (for example, CREATE TABLE foo();). This is an extension from the SQL standard, which does not allow zero-column tables. Because zero-column tables are not in themselves very useful, disallowing them creates odd special cases for ALTER TABLE DROP COLUMN, so Greenplum ignores this spec restriction.

Multiple Identity Columns

Greenplum allows a table to have more than one identity column. The standard specifies that a table can have at most one identity column. Greenplum relaxes this restriction to provide more flexibility for schema changes or migrations. Note that the INSERT command supports only one override clause that applies to the entire statement, so having multiple identity columns with different behaviors is not well supported.

Generated Columns

The option STORED is not standard but is also used by other SQL implementations. The SQL standard does not specify the storage of generated columns.

LIKE Clause

While a LIKE clause exists in the SQL standard, many of the options that Greenplum Database accepts for it are not in the standard, and some of the standard's options are not implemented by Greenplum Database.

WITH Clause

The WITH clause is a Greenplum Database extension; storage parameters are in the standard.

Tablespaces

The Greenplum Database concept of tablespaces is not part of the SQL standard. The clauses TABLESPACE and USING INDEX TABLESPACE are extensions.

Typed Tables

Typed tables implement a subset of the SQL standard. According to the standard, a typed table has columns corresponding to the underlying composite type as well as one other column that is the "self-referencing column". Greenplum Database does not support self-referencing columns explicitly.

PARTITION BY Clause

Table partitioning via the PARTITION BY clause is a Greenplum Database extension.

PARTITION OF Clause

Table partitioning via the PARTITION OF clause is a Greenplum Database extension.

Data Distribution

The Greenplum Database concept of a parallel or distributed database is not part of the SQL standard. The DISTRIBUTED clauses are extensions.

See Also

ALTER TABLE, DROP TABLE, CREATE EXTERNAL TABLE, CREATE TABLE AS, CREATE TABLESPACE, CREATE TYPE

Parent topic: SQL Commands