SQLite Update function


  Translation results:

sqlite

Database; use; embedded relational database

update

英[ˌʌpˈdeɪt] US[ʌpˈdet ]

vt. Update, modernize; correct, amend

n. Modernize; updated information; updated behavior or instances

SQLite Update functionsyntax

Function: SQLite's UPDATE query is used to modify existing records in the table. You can use an UPDATE query with a WHERE clause to update selected rows, otherwise all rows will be updated.

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

SQLite Update functionexample

COMPANY 表有以下记录:

ID          NAME        AGE         ADDRESS     SALARY
----------  ----------  ----------  ----------  ----------
1           Paul        32          California  20000.0
2           Allen       25          Texas       15000.0
3           Teddy       23          Norway      20000.0
4           Mark        25          Rich-Mond   65000.0
5           David       27          Texas       85000.0
6           Kim         22          South-Hall  45000.0
7           James       24          Houston     10000.0
下面是一个实例,它会更新 ID 为 6 的客户地址:

sqlite> UPDATE COMPANY SET ADDRESS = 'Texas' WHERE ID = 6;
现在,COMPANY 表有以下记录:

ID          NAME        AGE         ADDRESS     SALARY
----------  ----------  ----------  ----------  ----------
1           Paul        32          California  20000.0
2           Allen       25          Texas       15000.0
3           Teddy       23          Norway      20000.0
4           Mark        25          Rich-Mond   65000.0
5           David       27          Texas       85000.0
6           Kim         22          Texas       45000.0
7           James       24          Houston     10000.0
如果您想修改 COMPANY 表中 ADDRESS 和 SALARY 列的所有值,则不需要使用 WHERE 子句,UPDATE 查询如下:

sqlite> UPDATE COMPANY SET ADDRESS = 'Texas', SALARY = 20000.00;
现在,COMPANY 表有以下记录:

ID          NAME        AGE         ADDRESS     SALARY
----------  ----------  ----------  ----------  ----------
1           Paul        32          Texas       20000.0
2           Allen       25          Texas       20000.0
3           Teddy       23          Texas       20000.0
4           Mark        25          Texas       20000.0
5           David       27          Texas       20000.0
6           Kim         22          Texas       20000.0
7           James       24          Texas       20000.0

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