PostgreSQL – Auto Increment


PostgreSQL – AUTO INCREMENT


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PostgreSQL has the data types smallserial, serial and bigserial; these are not true types, but merely a notational convenience for creating unique identifier columns. These are similar to AUTO_INCREMENT property supported by some other databases.

If you wish a serial column to have a unique constraint or be a primary key, it must now be specified, just like any other data type.

The type name serial creates an integer columns. The type name bigserial creates a bigint column. bigserial should be used if you anticipate the use of more than 231 identifiers over the lifetime of the table. The type name smallserial creates a smallint column.

Syntax

The basic usage of SERIAL dataype is as follows −

CREATE TABLE tablename (
   colname SERIAL
);

Example

Consider the COMPANY table to be created as follows −

testdb=# CREATE TABLE COMPANY(
   ID  SERIAL PRIMARY KEY,
   NAME           TEXT      NOT NULL,
   AGE            INT       NOT NULL,
   ADDRESS        CHAR(50),
   SALARY         REAL
);

Now, insert the following records into table COMPANY −

INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)
VALUES ( ''Paul'', 32, ''California'', 20000.00 );

INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)
VALUES (''Allen'', 25, ''Texas'', 15000.00 );

INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)
VALUES (''Teddy'', 23, ''Norway'', 20000.00 );

INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)
VALUES ( ''Mark'', 25, ''Rich-Mond '', 65000.00 );

INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)
VALUES ( ''David'', 27, ''Texas'', 85000.00 );


INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)
VALUES ( ''Kim'', 22, ''South-Hall'', 45000.00 );

INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)
VALUES ( ''James'', 24, ''Houston'', 10000.00 );

This will insert seven tuples into the table COMPANY and COMPANY will have the following records −

 id | name  | age | address    | salary
----+-------+-----+------------+--------
  1 | Paul  |  32 | California |  20000
  2 | Allen |  25 | Texas      |  15000
  3 | Teddy |  23 | Norway     |  20000
  4 | Mark  |  25 | Rich-Mond  |  65000
  5 | David |  27 | Texas      |  85000
  6 | Kim   |  22 | South-Hall |  45000
  7 | James |  24 | Houston    |  10000

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