[Sqlite] Sqlite的基本日常SQL操作语句汇总

原文地址:[Sqlite] Sqlite的基本日常SQL操作语句汇总 作者:mchdba

原博客地址:http://blog.itpub.net/26230597/abstract/1/
原作者:黄杉 (mchdba)


序言:

    嵌入式数据库Sqlite的基本sql使用汇总,使用测试起来,与关系型数据库mysql在语法上有很多的相似之处,先准备测试数据:

CREATE TABLE COMPANY(ID INT NOT NULL, NAME VARCHAR(20),AGE INT,ADDRESS VARCHAR(20),SALARY DECIMAL(7,2));

INSERT INTO "COMPANY" VALUES(1,'Paul',32,'California',20000);

INSERT INTO "COMPANY" VALUES(2,'Allen',25,'Texas',15000);

INSERT INTO "COMPANY" VALUES(3,'Teddy',23,'Norway',20000);

INSERT INTO "COMPANY" VALUES(4,'Mark',25,'Rich-Mond',65000);

INSERT INTO "COMPANY" VALUES(5,'David',27,'Texas',85000);

INSERT INTO "COMPANY" VALUES(6,'Kim',22,'South-Hall',45000);

INSERT INTO "COMPANY" VALUES(7,'James',24,NULL,10000);

INSERT INTO "COMPANY" VALUES(8,'Xiaoteng',29,NULL,NULL);

1,分组统计排序

GROUP BY 进行分组统计数据,命令如下:

sqlite> SELECT NAME, SUM(SALARY) SALARY_SUM, COUNT(1) COUNT_NUM FROM COMPANY GROUP BY NAME;

 

ORDER BY 进行排序,命令如下:

sqlite> SELECT NAME, SUM(SALARY) SALARY_SUM, COUNT(1) COUNT_NUM FROM COMPANY GROUP BY NAME ORDER BY SALARY_SUM ASC;

 

HAVING 字句过滤数据记录,命令如下:

SELECT c.*,COUNT(1) COUNT_NUM FROM COMPANY c GROUP BY c.NAME HAVING (COUNT_NUM) > 1 ORDER BY COUNT_NUM ;

PS:在一个查询中,HAVING 子句必须放在 GROUP BY 子句之后,必须放在 ORDER BY 子句之前。下面是包含 HAVING 子句的 SELECT 语句的语法:

 

2Limit分页统计语句

SQLite 的 LIMIT 子句用于限制由 SELECT 语句返回的数据数量。

第一页取值SQL: SELECT * FROM COMPANY ORDER BY ID LIMIT 0,3;  也可以从一个特定的偏移开始提取记录,从第四位开始提取 3 个记录,使用OFFSET关键字,SELECT * FROM COMPANY ORDER BY ID LIMIT 3 OFFSET 0;PS:首页从0开始取值。

第二页取值SQL: SELECT * FROM COMPANY ORDER BY ID LIMIT 3,3;  也可以从一个特定的偏移开始提取记录,从第四位开始提取 3 个记录,使用OFFSET关键字,SELECT * FROM COMPANY ORDER BY ID LIMIT 3 OFFSET 3;如下图所示:

 

3Glob匹配字句

SQLite 的 GLOB 运算符是用来匹配通配符指定模式的文本值。如果搜索表达式与模式表达式匹配,GLOB 运算符将返回真(true),也就是 1。与 LIKE 运算符不同的是,GLOB 是大小写敏感的,对于下面的通配符,它遵循 UNIX 的语法。

星号 (*)

问号 (?)

星号(*)代表零个、一个或多个数字或字符。问号(?)代表一个单一的数字或字符。这些符号可以被组合使用。

下面一些实例演示了 带有 '*' 和 '?' 运算符的 GLOB 子句不同的地方:

 

下面是一个实例,它显示 COMPANY 表中 AGE 以 2 开头的所有记录,如下所示:

 

 

下面是一个实例,它显示 COMPANY 表中 ADDRESS 文本里包含一个连字符(-)的所有记录:

 

4Distinct关键字过滤重复记录

SQLite 的 DISTINCT 关键字与 SELECT 语句一起使用,来消除所有重复的记录,并只获取唯一一次记录。

有可能出现一种情况,在一个表中有多个重复的记录。当提取这样的记录时,DISTINCT 关键字就显得特别有意义,它只获取唯一一次记录,而不是获取重复记录。

 

 

5,字符串连接操作

问题地址:http://bbs.csdn.net/topics/390886865

sqlite> CREATE TABLE t1(id int, name varchar(60));

sqlite> INSERT INTO "t1" VALUES(4,'[email protected]');

sqlite> select * from t1;

id          name     

----------  ----------

4           [email protected]

sqlite> update t1 set name=(id/2)||substr(name,instr(name,'@'),length(name)-instr(name,'@')+1)  where id=4;

sqlite> select * from t1;

id          name     

----------  ----------

4           [email protected]

sqlite>

 

6,对Null值的处理

往表里面录入Null

sqlite> INSERT INTO COMPANY(ID,NAME,AGE,ADDRESS,SALARY) VALUES(8,'Xiaoteng',29,NULL,18000);

sqlite>

修改某个字段为null

sqlite> UPDATE COMPANY SET SALARY = NULL WHERE ID=8;

sqlite>

查询为null的记录

sqlite> SELECT * FROM COMPANY WHERE ADDRESS IS NULL;

ID          NAME        AGE         ADDRESS     SALARY   

----------  ----------  ----------  ----------  ----------

7           James       24                      10000    

8           Xiaoteng    29                               

sqlite>

查询不为null的记录

sqlite> SELECT * FROM COMPANY WHERE ADDRESS IS NOT NULL;

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    

sqlite>


7,子查询

SELECt中的基本语法如下:

SELECT column_name [, column_name ]

FROM   table1 [, table2 ]

WHERE  column_name OPERATOR

      (SELECT column_name [, column_name ]

      FROM table1 [, table2 ]

      [WHERE])

实例如下:

sqlite> SELECT * FROM COMPANY WHERE ID IN (SELECT ID FROM COMPANY WHERE SALARY > 45000);

 

INSERT语句中的子查询使用,基本语法:

INSERT INTO table_name [ (column1 [, column2 ]) ]

           SELECT [ *|column1 [, column2 ]

           FROM table1 [, table2 ]

           [ WHERE VALUE OPERATOR ]

实例如下:

sqlite> INSERT INTO COMPANY_BKP

SELECT * FROM COMPANY

     WHERE ID IN (SELECT ID

                  FROM COMPANY) ;

UPDATE语句中的子查询使用,基本语法如下:

UPDATE table

SET column_name = new_value

[ WHERE OPERATOR [ VALUE ]

   (SELECT COLUMN_NAME

   FROM TABLE_NAME)

   [ WHERE) ]

实例如下:

 sqlite> UPDATE COMPANY

     SET SALARY = SALARY * 0.50

     WHERE AGE IN (SELECT AGE FROM COMPANY_BKP

                   WHERE AGE >= 27 );

DELETE语句中的子查询使用,语法如下:

DELETE FROM TABLE_NAME

[ WHERE OPERATOR [ VALUE ]

   (SELECT COLUMN_NAME

   FROM TABLE_NAME)

   [ WHERE) ]

实例如下:

sqlite> DELETE FROM COMPANY

     WHERE AGE IN (SELECT AGE FROM COMPANY_BKP

                   WHERE AGE > 27 );

 

8EXPLAIN分析

没有建立索引之前,分析都是表扫描:

sqlite> EXPLAIN SELECT *  FROM COMPANY  WHERE Salary < 20000;

addr        opcode      p1          p2          p3          p4          p5          comment  

----------  ----------  ----------  ----------  ----------  ----------  ----------  ----------

0           Trace       0           0           0                       00                   

1           Integer     20000       1           0                       00                   

2           Goto        0           16          0                       00                   

3           OpenRead    0           2           0           5           00                   

4           Rewind      0           14          0                       00                   

5           Column      0           4           2                       00                   

6           Ge          1           13          2           collseq(BI  6b                   

7           Column      0           0           4                       00                   

8           Column      0           1           5                       00                   

9           Column      0           2           6                       00                   

10          Column      0           3           7                       00                   

11          Column      0           4           8                       00                   

12          ResultRow   4           5           0                       00                   

13          Next        0           5           0                       01                   

14          Close       0           0           0                       00                   

15          Halt        0           0           0                       00                   

16          Transactio  0           0           0                       00                   

17          VerifyCook  0           1           0                       00                   

18          TableLock   0           2           0           COMPANY     00                    

19          Goto        0           3           0                       00                   

sqlite> EXPLAIN QUERY PLAN SELECT * FROM COMPANY WHERE Salary < 20000;

order       from        detail      

----------  ----------  -------------

0           0           TABLE COMPANY

sqlite>

 

建立索引,再进行EXPLAIN分析查看结果,走了idx_sal索引扫描:

sqlite> CREATE INDEX idx_sal ON COMPANY(SALARY);

sqlite> EXPLAIN SELECT *  FROM COMPANY  WHERE Salary < 20000;

addr        opcode      p1          p2          p3          p4          p5          comment  

----------  ----------  ----------  ----------  ----------  ----------  ----------  ----------

0           Trace       0           0           0                       00                   

1           Integer     20000       1           0                       00                   

2           Goto        0           25          0                       00                   

3           OpenRead    0           2           0           5           00                   

4           OpenRead    1           3           0           keyinfo(1,  00                   

5           Affinity    2           0           0           cb          00                   

6           Rewind      1           22          2           0           00                   

7           SCopy       1           2           0                       00                   

8           IsNull      2           22          0                       00                   

9           Affinity    2           1           0           cb          00                   

10          IdxGE       1           22          2           1           00                   

11          Column      1           0           3                       00                   

12          IsNull      3           21          0                       00                   

13          IdxRowid    1           3           0                       00                   

14          Seek        0           3           0                       00                   

15          Column      0           0           4                       00                   

16          Column      0           1           5                       00                   

17          Column      0           2           6                       00                    

18          Column      0           3           7                       00                   

19          Column      1           0           8                       00                   

20          ResultRow   4           5           0                       00                   

21          Next        1           10          0                       00                   

22          Close       0           0           0                       00                   

23          Close       1           0           0                       00                   

24          Halt        0           0           0                       00                   

25          Transactio  0           0           0                       00                    

26          VerifyCook  0           2           0                       00                   

27          TableLock   0           2           0           COMPANY     00                   

28          Goto        0           3           0                       00                   

sqlite> EXPLAIN QUERY PLAN SELECT * FROM COMPANY WHERE Salary < 20000;

order       from        detail                         

----------  ----------  --------------------------------

0           0           TABLE COMPANY WITH INDEX idx_sal

sqlite>


9,删除重复数据但是一条记录

录入测试数据

sqlite> .dump

PRAGMA foreign_keys=OFF;

BEGIN TRANSACTION;

CREATE TABLE COMPANY(ID INT NOT NULL, NAME VARCHAR(20),AGE INT,ADDRESS VARCHAR(20),SALARY DECIMAL(7,2));

INSERT INTO "COMPANY" VALUES(2,'Allen',25,'Texas',15000);

INSERT INTO "COMPANY" VALUES(3,'Teddy',23,'Norway',20000);

INSERT INTO "COMPANY" VALUES(4,'Mark',25,'Rich-Mond',65000);

INSERT INTO "COMPANY" VALUES(5,'David',27,'Texas',85000);

INSERT INTO "COMPANY" VALUES(6,'Kim',22,'South-Hall',45000);

INSERT INTO "COMPANY" VALUES(7,'James',24,'Houston',10000);

INSERT INTO "COMPANY" VALUES(7,'James',28,'Houston',20000);

INSERT INTO "COMPANY" VALUES(4,'Mark',29,'Rich-Mond',95000);

COMMIT;

sqlite>

 

查看重复记录数

sqlite> select * from company order by name;

ID          NAME        AGE         ADDRESS     SALARY     

----------  ----------  ----------  ----------  ---------- 

2           Allen       25          Texas       15000      

5           David       27          Texas       85000      

7           James       24          Houston     10000      

7           James       28          Houston     20000      

6           Kim         22          South-Hall  45000      

4           Mark        25          Rich-Mond   65000      

4           Mark        29          Rich-Mond   95000      

3           Teddy       23          Norway      20000      

sqlite>

 

通过rowid来删除重复记录

sqlite> DELETE FROM COMPANY WHERE rowid NOT IN(SELECT MAX(rowid) rowid FROM COMPANY GROUP BY NAME);

sqlite>

 

再查看最新的数据记录,已经删除了重复NAME的记录

sqlite> select * from company;

ID          NAME        AGE         ADDRESS     SALARY     

----------  ----------  ----------  ----------  ---------- 

2           Allen       25          Texas       15000      

3           Teddy       23          Norway      20000      

5           David       27          Texas       85000      

6           Kim         22          South-Hall  45000      

7           James       28          Houston     20000      

4           Mark        29          Rich-Mond   95000      

sqlite>


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