1、oracle函数大全(分析函数, 聚合函数 ,转换函数,日期型函数, 字符型函数,数值型函数,其他函数)oracle 函数大全 .1oracle 分析函数-SQL*PLUS 环境 .1oracle 10g 函数大全-聚合函数 .19oracle 10g 函数大全-转换函数 .23oracle 10g 函数大全-日期型函数 .40oracle 10g 函数大全-字符型函数 .45oracle 10g 函数大全-数值型函数 .55oracle 10g 函数大全-其他函数 .58oracle分析函数-SQL*PLUS 环境一、总体介绍1.1. 分析函数如何工作语法 FUNCTION_NAME(,)
2、OVER ( ) PARTITION子句 ORDER BY子句 WINDOWING子句 缺省时相当于 RANGE UNBOUNDED PRECEDING 1. 值域窗 (RANGE WINDOW) RANGE N PRECEDING 仅对数值或日期类型有效 ,选定窗为排序后当前行之前,某列( 即排序列) 值大于 /小于 (当前行该列值 /+ N)的所有行,因此与 ORDER BY子句有关系。 2. 行窗 (ROW WINDOW) ROWS N PRECEDING 选定窗为当前行及之前 N行。 还可以加上 BETWEEN AND 形式 ,例如 RANGE BETWEEN m PRECEDING
3、AND n FOLLOWING 函数 AVG( eXPr) 一组或选定窗中表达式的平均值 CORR(expr, expr) 即 COVAR_POP(exp1,exp2) / (STDDEV_POP(expr1) * STDDEV_POP(expr2),两个表达式的互相关,-1(反相关) 1(正相关 ),0表示不相关 COUNT( ) 计数 COVAR_POP(expr, expr) 总体协方差 COVAR_SAMP(expr, expr) 样本协方差 CUME_DIST 累积分布,即行在组中的相对位置 ,返回 0 1 DENSE_RANK 行的相对排序 (与 ORDER BY搭配), 相同的值
4、具有一样的序数(NULL 计为相同),并不留空序数 FIRST_VALUE 一个组的第一个值 LAG(expr, , ) 访问之前的行,OFFSET 是缺省为 1 的正数,表示相对行数,DEFAULT 是当超出选定窗范围时的返回值 (如第一行不存在之前行) LAST_VALUE 一个组的最后一个值 LEAD(expr, , ) 访问之后的行,OFFSET 是缺省为 1 的正数,表示相对行数,DEFAULT 是当超出选定窗范围时的返回值 (如最后行不存在之前行) MAX(expr) 最大值 MIN(expr) 最小值 NTILE(expr) 按表达式的值和行在组中的位置编号,如表达式为 4,则组
5、分 4份,分别为 1 4的值,而不能等分则多出的部分在值最小的那组 PERCENT_RANK 类似 CUME_DIST,1/(行的序数 - 1) RANK 相对序数 ,答应并列,并空出随后序号 RATIO_TO_REPORT(expr) 表达式值 / SUM(表达式值) ROW_NUMBER 排序的组中行的偏移 STDDEV(expr) 标准差 STDDEV_POP(expr) 总体标准差 STDDEV_SAMP(expr) 样本标准差 SUM(expr) 合计 VAR_POP(expr) 总体方差 VAR_SAMP(expr) 样本方差 VARIANCE(expr) 方差 REGR_ xxx
6、x(expr, expr) 线性回归函数 REGR_SLOPE：返回斜率，等于 COVAR_POP(expr1, expr2) / VAR_POP(expr2)REGR_INTERCEPT：返回回归线的 y截距，等于AVG(expr1) - REGR_SLOPE(expr1, expr2) * AVG(expr2)REGR_COUNT：返回用于填充回归线的非空数字对的数目REGR_R2：返回回归线的决定系数，计算式为：If VAR_POP(expr2) = 0 then return NULLIf VAR_POP(expr1) = 0 and VAR_POP(expr2) != 0 then
7、return 1If VAR_POP(expr1) 0 and VAR_POP(expr2 != 0 then return POWER(CORR(expr1,expr),2)REGR_AVGX：计算回归线的自变量(expr2)的平均值，去掉了空对 (expr1, expr2)后，等于 AVG(expr2)REGR_AVGY：计算回归线的应变量(expr1)的平均值，去掉了空对 (expr1, expr2)后，等于 AVG(expr1)REGR_SXX： 返回值等于 REGR_COUNT(expr1, expr2) * VAR_POP(expr2)REGR_SYY： 返回值等于 REGR_CO
8、UNT(expr1, expr2) * VAR_POP(expr1)REGR_SXY: 返回值等于 REGR_COUNT(expr1, expr2) * COVAR_POP(expr1, expr2)首先：创建表及接入测试数据create table students(id number(15,0),area varchar2(10),stu_type varchar2(2),score number(20,2);insert into students values(1, 111, g, 80 );insert into students values(1, 111, j, 80 );ins
9、ert into students values(1, 222, g, 89 );insert into students values(1, 222, g, 68 );insert into students values(2, 111, g, 80 );insert into students values(2, 111, j, 70 );insert into students values(2, 222, g, 60 );insert into students values(2, 222, j, 65 );insert into students values(3, 111, g,
10、75 );insert into students values(3, 111, j, 58 );insert into students values(3, 222, g, 58 );insert into students values(3, 222, j, 90 );insert into students values(4, 111, g, 89 );insert into students values(4, 111, j, 90 );insert into students values(4, 222, g, 90 );insert into students values(4,
11、222, j, 89 );commit;二、具体应用：1、分组求和：1.2. GROUP BY 子句 1.2.1. GROUPING SETSselect id,area,stu_type,sum(score) score from studentsgroup by grouping sets(id,area,stu_type),(id,area),id)order by id,area,stu_type;/*-理解 grouping setsselect a, b, c, sum( d ) from tgroup by grouping sets ( a, b, c )等效于select *
12、 from (select a, null, null, sum( d ) from t group by aunion allselect null, b, null, sum( d ) from t group by b union allselect null, null, c, sum( d ) from t group by c )*/1.2.2. ROLLUPselect id,area,stu_type,sum(score) score from studentsgroup by rollup(id,area,stu_type)order by id,area,stu_type;
13、1.2.3. rollupselect a, b, c, sum( d )from tgroup by rollup(a, b, c);等效于select * from (select a, b, c, sum( d ) from t group by a, b, c union allselect a, b, null, sum( d ) from t group by a, bunion allselect a, null, null, sum( d ) from t group by aunion allselect null, null, null, sum( d ) from t)*
14、/1.2.4. CUBEselect id,area,stu_type,sum(score) score from studentsgroup by cube(id,area,stu_type)order by id,area,stu_type;/*-理解 cubeselect a, b, c, sum( d ) from tgroup by cube( a, b, c)等效于select a, b, c, sum( d ) from tgroup by grouping sets( ( a, b, c ), ( a, b ), ( a ), ( b, c ), ( b ), ( a, c )
15、, ( c ), () )*/1.2.5. GROUPING/*从上面的结果中我们很容易发现,每个统计数据所对应的行都会出现 null,如何来区分到底是根据那个字段做的汇总呢,grouping 函数判断是否合计列!*/select decode(grouping(id),1,all id,id) id,decode(grouping(area),1,all area,to_char(area) area,decode(grouping(stu_type),1,all_stu_type,stu_type) stu_type,sum(score) scorefrom studentsgroup b
16、y cube(id,area,stu_type)order by id,area,stu_type; 1.3. OVER()函数的使用1.3.1. 统计名次1.3.1.1.DENSE_RANK()，允许并列名次、名次不间断，如 122344456将 score按 ID分组排名：dense_rank() over(partition by id order by score desc)将 score不分组排名： dense_rank() over(order by score desc)select id,area,score,dense_rank() over(partition by id
17、order by score desc) 分组 id排序,dense_rank() over(order by score desc) 不分组排序from students order by id,area;1.3.1.2.ROW_NUMBER()，不允许并列名次、相同值名次不重复，结果如 123456将 score按 ID分组排名：row_number() over(partition by id order by score desc)将 score不分组排名： row_number() over(order by score desc)select id,area,score,row_n
18、umber() over(partition by id order by score desc) 分组 id排序,row_number() over(order by score desc) 不分组排序from students order by id,area;1.3.1.3.rank()，允许并列名次、复制名次自动空缺，结果如12245558将 score按 ID分组排名：rank() over(partition by id order by score desc)将 score不分组排名： rank() over(order by score desc)select id,area,
19、score,rank() over(partition by id order by score desc) 分组 id排序,rank() over(order by score desc) 不分组排序from students order by id,area;1.3.1.4.cume_dist()，名次分析-最大排名/总个数 函数：cume_dist() over(order by id)select id,area,score,cume_dist() over(order by id) a, -按 ID最大排名/总个数 cume_dist() over(partition by id o
20、rder by score desc) b, -ID分组中，scroe最大排名值/本组总个数row_number() over (order by id) 记录号from students order by id,area;1.3.1.5.cume_dist()，允许并列名次、复制名次自动空缺，取并列后较大名次，结果如 22355778将 score按 ID分组排名：cume_dist() over(partition by id order by score desc)*sum(1) over(partition by id)将 score不分组排名： cume_dist() over(or
21、der by score desc)*sum(1) over()select id,area,score,sum(1) over() as 总数,sum(1) over(partition by id) as 分组个数,(cume_dist() over(partition by id order by score desc)*(sum(1) over(partition by id) 分组 id排序,(cume_dist() over(order by score desc)*(sum(1) over() 不分组排序from students order by id,area1.3.1.6.
22、sum(),max(),avg(),RATIO_TO_REPORT()分组统计select id,area,sum(1) over() as 总记录数, sum(1) over(partition by id) as 分组记录数,sum(score) over() as 总计 , sum(score) over(partition by id) as 分组求和,sum(score) over(order by id) as 分组连续求和,sum(score) over(partition by id,area) as 分组 ID和 area求和,sum(score) over(partitio
23、n by id order by area) as 分组 ID并连续按 area求和,max(score) over() as 最大值,max(score) over(partition by id) as 分组最大值 ,max(score) over(order by id) as 分组连续最大值,max(score) over(partition by id,area) as 分组 ID和 area求最大值,max(score) over(partition by id order by area) as 分组 ID并连续按 area求最大值,avg(score) over() as 所有
24、平均,avg(score) over(partition by id) as 分组平均,avg(score) over(order by id) as 分组连续平均,avg(score) over(partition by id,area) as 分组 ID和 area平均,avg(score) over(partition by id order by area) as 分组 ID并连续按 area平均,RATIO_TO_REPORT(score) over() as “占所有%“,RATIO_TO_REPORT(score) over(partition by id) as “占分组%“,
25、score from students;3、 LAG(COL,n,default)、LEAD(OL,n,default) -取前后边 N条数据取前面记录的值：lag(score,n,x) over(order by id)取后面记录的值：lead(score,n,x) over(order by id) 参数：n 表示移动 N条记录， X表示不存在时填充值，iD 表示排序列select id,lag(score,1,0) over(order by id) lg,score from students;select id,lead(score,1,0) over(order by id) lg
26、,score from students;4、 FIRST_VALUE()、LAST_VALUE()取第起始 1行值： first_value(score,n) over(order by id)取第最后 1行值： LAST_value(score,n) over(order by id)select id,first_value(score) over(order by id) fv,score from students;select id,last_value(score) over(order by id) fv,score from students;sum(.) over .【功能
27、】连续求和分析函数【参数】具体参示例【说明】Oracle 分析函数NC示例：select bdcode,sum(1) over(order by bdcode) aa from bd_bdinfo 【示例】1.原表信息： SQL break on deptno skip 1 - 为效果更明显，把不同部门的数据隔段显示。SQL select deptno,ename,sal2 from emp3 order by deptno;DEPTNO ENAME SAL- - -10 CLARK 2450KING 5000MILLER 130020 SMITH 800ADAMS 1100FORD 3000
28、SCOTT 3000JONES 297530 ALLEN 1600BLAKE 2850MARTIN 1250JAMES 950TURNER 1500WARD 12502.先来一个简单的，注意 over(.)条件的不同，使用 sum(sal) over (order by ename). 查询员工的薪水“连续” 求和,注意 over (order by ename)如果没有 order by 子句，求和就不是 “连续”的，放在一起，体会一下不同之处：SQL select deptno,ename,sal,2 sum(sal) over (order by ename) 连续求和,3 sum(sa
29、l) over () 总和, - 此处 sum(sal) over () 等同于sum(sal)4 100*round(sal/sum(sal) over (),4) “份额(%)“5 from emp6 /DEPTNO ENAME SAL 连续求和 总和 份额(%)- - - - - -20 ADAMS 1100 1100 29025 3.7930 ALLEN 1600 2700 29025 5.5130 BLAKE 2850 5550 29025 9.8210 CLARK 2450 8000 29025 8.4420 FORD 3000 11000 29025 10.3430 JAMES
30、950 11950 29025 3.2720 JONES 2975 14925 29025 10.2510 KING 5000 19925 29025 17.2330 MARTIN 1250 21175 29025 4.3110 MILLER 1300 22475 29025 4.4820 SCOTT 3000 25475 29025 10.3420 SMITH 800 26275 29025 2.7630 TURNER 1500 27775 29025 5.1730 WARD 1250 29025 29025 4.313.使用子分区查出各部门薪水连续的总和。注意按部门分区。注意 over(.
31、)条件的不同，sum(sal) over (partition by deptno order by ename) 按部门“连续”求总和sum(sal) over (partition by deptno) 按部门求总和sum(sal) over (order by deptno，ename) 不按部门“连续” 求总和sum(sal) over () 不按部门，求所有员工总和，效果等同于 sum(sal)。SQL select deptno,ename,sal,2 sum(sal) over (partition by deptno order by ename) 部门连续求和,-各部门的薪水
32、“连续“ 求和3 sum(sal) over (partition by deptno) 部门总和, - 部门统计的总和，同一部门总和不变4 100*round(sal/sum(sal) over (partition by deptno),4) “部门份额(%)“,5 sum(sal) over (order by deptno,ename) 连续求和, -所有部门的薪水“连续“ 求和6 sum(sal) over () 总和, - 此处 sum(sal) over () 等同于 sum(sal)，所有员工的薪水总和7 100*round(sal/sum(sal) over (),4) “总
33、份额(%)“8 from emp9 /DEPTNO ENAME SAL 部门连续求和 部门总和 部门份额(%) 连续求和 总和 总份额(%)- - - - - - - - -10 CLARK 2450 2450 8750 28 2450 29025 8.44KING 5000 7450 8750 57.14 7450 29025 17.23MILLER 1300 8750 8750 14.86 8750 29025 4.4820 ADAMS 1100 1100 10875 10.11 9850 29025 3.79FORD 3000 4100 10875 27.59 12850 29025 1
34、0.34JONES 2975 7075 10875 27.36 15825 29025 10.25SCOTT 3000 10075 10875 27.59 18825 29025 10.34SMITH 800 10875 10875 7.36 19625 29025 2.7630 ALLEN 1600 1600 9400 17.02 21225 29025 5.51BLAKE 2850 4450 9400 30.32 24075 29025 9.82JAMES 950 5400 9400 10.11 25025 29025 3.27MARTIN 1250 6650 9400 13.3 26275 29025 4.31TURNER 1500 8150 9400 15.96 27775 29025 5.17WARD 1250 9400 9400 13.3 29025 29025 4.31
