English 中文(简体)
PostgreSQL Tutorial

Advanced PostgreSQL

PostgreSQL Interfaces

PostgreSQL Useful Resources

Selected Reading

PostgreSQL - Update Query
  • 时间:2024-12-27

PostgreSQL - UPDATE Query


Previous Page Next Page  

The PostgreSQL UPDATE Query is used to modify the existing records in a table. You can use WHERE clause with UPDATE query to update the selected rows. Otherwise, all the rows would be updated.

Syntax

The basic syntax of UPDATE query with WHERE clause is as follows −

UPDATE table_name
SET column1 = value1, column2 = value2...., columnN = valueN
WHERE [condition];

You can combine N number of conditions using AND or OR operators.

Example

Consider the table COMPANY, having records as follows −

testdb# select * from COMPANY;
 id | name  | age | address   | salary
----+-------+-----+-----------+--------
  1 | Paul  |  32 | Capfornia|  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
(7 rows)

The following is an example, which would update ADDRESS for a customer, whose ID is 6 −

testdb=# UPDATE COMPANY SET SALARY = 15000 WHERE ID = 3;

Now, COMPANY table would have the following records −

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

If you want to modify all ADDRESS and SALARY column values in COMPANY table, you do not need to use WHERE clause and UPDATE query would be as follows −

testdb=# UPDATE COMPANY SET ADDRESS =  Texas , SALARY=20000;

Now, COMPANY table will have the following records −

 id | name  | age | address | salary
----+-------+-----+---------+--------
  1 | Paul  |  32 | Texas   |  20000
  2 | Allen |  25 | Texas   |  20000
  4 | Mark  |  25 | Texas   |  20000
  5 | David |  27 | Texas   |  20000
  6 | Kim   |  22 | Texas   |  20000
  7 | James |  24 | Texas   |  20000
  3 | Teddy |  23 | Texas   |  20000
(7 rows)
Advertisements