CREATE TABLE

CREATE TABLE creates a new table in an existing database.

Tip

Permissions

The role must have the CREATE permission at the schema level.

Syntax

create_table_statement ::=
    CREATE [ OR REPLACE ] TABLE [schema_name.]table_name (
        { column_def [, ...] }
    )
    [ CLUSTER BY { column_name [, ...] } ]
    ;

schema_name ::= identifier

table_name ::= identifier

column_def :: = { column_name type_name [ default ] [ column_constraint ] }

column_name ::= identifier

column_constraint ::=
    { NOT NULL | NULL }

default ::=
    DEFAULT default_value
    | IDENTITY [ ( start_with [ , increment_by ] ) ]

Parameters

Parameter Description
OR REPLACE Create a new table, and overwrite any existing table by the same name. Does not return an error if the table already exists. CREATE OR REPLACE does not check the table contents or structure, only the table name.
schema_name The name of the schema in which to create the table.
table_name The name of the table to create, which must be unique inside the schema.
column_def A comma separated list of column definitions. A minimal column definition includes a name identifier and a datatype. Other column constraints and default values can be added optionally.
CLUSTER BY column_name1 ...

A commma separated list of clustering column keys.

See Data clustering for more information.

Default values

The DEFAULT value constraint specifies a value to use if a value isn’t defined in an INSERT or COPY FROM statement.

The value may be either a literal or GETDATE(), which is s evaluated at the time the row is created.

Note

The DEFAULT constraint only applies if the column does not have a value specified in the INSERT or COPY FROM statement. You can still insert a NULL into an nullable column by explicitly inserting NULL. For example, INSERT INTO cool_animals VALUES (1, 'Gnu', NULL).

Syntax

column_def :: = { column_name type_name [ default ] [ column_constraint ] }

column_constraint ::=
    { NOT NULL | NULL }

default ::=
    DEFAULT default_value
    | IDENTITY [ ( start_with [ , increment_by ] ) ]

check_specification ::=
   CHECK( 'CS compression_spec' )

compression_spec ::=
    { "default" | "p4d" | "dict" | "rle" | "sequence" | "flat" }

Identity (sequence)

Identity columns can be used for generating key values. Some databases call this AUTOINCREMENT.

The identity property on a column guarantees that each new row inserted is generated based on the current seed & increment.

Warning

The identity property on a column does not guarantee uniqueness. The identity value can be bypassed by specifying it in an INSERT command.

Parameter Description
start_with A value that is used for the very first row loaded into the table.
increment_by Incremental value that is added to the identity value of the previous row that was loaded.

Examples

A simple table

CREATE TABLE cool_animals (
   id INT NOT NULL,
   name varchar(30) NOT NULL,
   weight FLOAT,
   is_agressive BOOL
);

A table with default values for some columns

CREATE TABLE cool_animals (
   id INT NOT NULL,
   name varchar(30) NOT NULL,
   weight FLOAT,
   is_agressive BOOL DEFAULT false NOT NULL
);

Note

The nullable/non-nullable constraint appears at the end, after the default option

A table with an identity (autoincrement) column

CREATE TABLE users (
   id BIGINT IDENTITY(0,1) NOT NULL , -- Start with 0, increment by 1
   name VARCHAR(30) NOT NULL,
   country VARCHAR(30) DEFAULT 'Unknown' NOT NULL
);

Note

  • Identity columns are supported on BIGINT columns.
  • Identity does not enforce the uniqueness of values. The identity value can be bypassed by specifying it in an INSERT command.

Creating a table from a SELECT query

Use a CREATE TABLE AS statement to create a new table from the results of a SELECT query.

CREATE TABLE users_uk AS SELECT * FROM users WHERE country = 'United Kingdom';

Creating a table with a clustering key

When data in a table is stored in a sorted order, the sorted columns are considered clustered. Good clustering can have a significant positive impact on performance.

In the following example, we expect the start_date column to be naturally clustered, as new users sign up and get a newer start date.

When the clustering key is set, if the incoming data isn’t naturally clustered, it will be clustered by SQream DB during insert or bulk load.

See Data clustering for more information.

CREATE TABLE users (
   name VARCHAR(30) NOT NULL,
   start_date datetime not null,
   country VARCHAR(30) DEFAULT 'Unknown' NOT NULL
) CLUSTER BY start_date;