insert 语句

SQLite 的 INSERT INTO 语句用于向数据库的某个表中添加新的数据行。

语法

-- 语法一

INSERT INTO TABLE_NAME [(column1, column2, column3,...columnN)]  
VALUES (value1, value2, value3,...valueN);

-- column1, column2,...columnN 是要插入数据的表中的列的名称。

-- 语法二

-- 如果要为表中的所有列添加值，您也可以不需要在 SQLite 查询中指定列名称。但要确保值的顺序与列在表中的顺序一致。
INSERT INTO TABLE_NAME VALUES (value1,value2,value3,...valueN);

实例

-- 环境准备
sqlite> CREATE TABLE COMPANY(
   ...>    ID INT PRIMARY KEY     NOT NULL,
   ...>    NAME           TEXT    NOT NULL,
   ...>    AGE            INT     NOT NULL,
   ...>    ADDRESS        CHAR(50),
   ...>    SALARY         REAL
   ...> );

-- 添加数据行
sqlite> INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)
VALUES (2, 'Allen', 25, 'Texas', 15000.00 );

INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)
VALUES (3, 'Teddy', 23, 'Norway', 20000.00 );

INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)
   ...> VALUES (1, 'Paul', 32, 'California', 20000.00 );
VALUES (6, 'Kim', 22, 'South-Hall', 45000.00 );sqlite>
sqlite> INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)
   ...> VALUES (2, 'Allen', 25, 'Texas', 15000.00 );
sqlite>
sqlite> INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)
   ...> VALUES (3, 'Teddy', 23, 'Norway', 20000.00 );
sqlite>
sqlite> INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)
   ...> VALUES (4, 'Mark', 25, 'Rich-Mond ', 65000.00 );
sqlite>
sqlite> INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)
   ...> VALUES (5, 'David', 27, 'Texas', 85000.00 );
sqlite>
sqlite> INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)
   ...> VALUES (6, 'Kim', 22, 'South-Hall', 45000.00 );

-- 使用第二种语法在 COMPANY 表中添加数据行
sqlite> INSERT INTO COMPANY VALUES (7, 'James', 24, 'Houston', 10000.00 );

-- 显示记录
sqlite> .headers on
sqlite> .mode column
sqlite>
sqlite> select * from company;
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