一、基础数据准备
Sql代码
create table earnings -- 打工挣钱表
(
earnmonth varchar2(6), -- 打工月份
area varchar2(20), -- 打工地区
snovarchar2(10), -- 打工者编号
sname varchar2(20), -- 打工者姓名
times int, -- 本月打工次数
singleincome number(10,2), -- 每次赚多少钱
personincome number(10,2) -- 当月总收入
)
然后插入实验数据：
insert into earnings values('200912','北平','511601','大魁',11,30,11*30);
insert into earnings values('200912','北平','511602','大凯',8,25,8*25);
insert into earnings values('200912','北平','511603','小东',30,6.25,30*6.25);
insert into earnings values('200912','北平','511604','大亮',16,8.25,16*8.25);
insert into earnings values('200912','北平','511605','贱敬',30,11,30*11);
insert into earnings values('200912','金陵','511301','小玉',15,12.25,15*12.25);
insert into earnings values('200912','金陵','511302','小凡',27,16.67,27*16.67);
insert into earnings values('200912','金陵','511303','小妮',7,33.33,7*33.33);
insert into earnings values('200912','金陵','511304','小俐',0,18,0);
insert into earnings values('200912','金陵','511305','雪儿',11,9.88,11*9.88);
insert into earnings values('201001','北平','511601','大魁',0,30,0);
insert into earnings values('201001','北平','511602','大凯',10,25,10*25);
insert into earnings values('201001','北平','511603','小东',19,6.25,19*6.25);
insert into earnings values('201001','北平','511604','大亮',7,8.25,7*8.25);
insert into earnings values('201001','北平','511605','贱敬',21,11,21*11);
insert into earnings values('201001','金陵','511301','小玉',6,12.25,6*12.25);
insert into earnings values('201001','金陵','511302','小凡',14,16.67,14*16.67);
insert into earnings values('201001','金陵','511303','小妮',27,33.33,27*33.33);
insert into earnings values('201001','金陵','511304','小俐',16,18,16*18);
insert into earnings values('201001','金陵','511305','雪儿',11,9.88,11*9.88);
insert into earnings values('201002','北平','511601','大魁',0,30,0);
insert into earnings values('201002','北平','511602','大凯',14,25,14*25);
insert into earnings values('201002','北平','511603','小东',19,6.25,19*6.25);
insert into earnings values('201002','北平','511604','大亮',9,8.25,9*8.25);
insert into earnings values('201002','北平','511605','贱敬',21,11,21*11);
insert into earnings values('201002','金陵','511301','小玉',6,12.25,6*12.25);
insert into earnings values('201002','金陵','511302','小凡',17,16.67,17*16.67);
insert into earnings values('201002','金陵','511303','小妮',27,33.33,27*33.33);
insert into earnings values('201002','金陵','511304','小俐',16,18,16*18);
insert into earnings values('201002','金陵','511305','雪儿',19,9.88,19*9.88);
insert into earnings values('201003','北平','511601','大魁',0,30,0);
insert into earnings values('201003','北平','511602','大凯',14,25,14*25);
insert into earnings values('201003','北平','511603','小东',19,6.25,19*6.25);
insert into earnings values('201003','北平','511604','大亮',22,8.25,22*8.25);
insert into earnings values('201003','北平','511605','贱敬',21,11,21*11);
insert into earnings values('201003','金陵','511301','小玉',6,12.25,6*12.25);
insert into earnings values('201003','金陵','511302','小凡',17,16.67,17*16.67);
insert into earnings values('201003','金陵','511303','小妮',27,33.33,27*33.33);
insert into earnings values('201003','金陵','511304','小俐',16,18,16*18);
insert into earnings values('201003','金陵','511305','雪儿',11,9.88,11*9.88);
insert into earnings values('201004','北平','511601','大魁',0,30,0);
insert into earnings values('201004','北平','511602','大凯',14,25,14*25);
insert into earnings values('201004','北平','511603','小东',19,6.25,19*6.25);
insert into earnings values('201004','北平','511604','大亮',7,8.25,7*8.25);
insert into earnings values('201004','北平','511605','贱敬',21,11,21*11);
insert into earnings values('201004','金陵','511301','小玉',6,12.25,6*12.25);
insert into earnings values('201004','金陵','511302','小凡',17,16.67,17*16.67);
insert into earnings values('201004','金陵','511303','小妮',23,33.33,23*33.33);
insert into earnings values('201004','金陵','511304','小俐',16,18,16*18);
insert into earnings values('201004','金陵','511305','雪儿',12,9.88,12*9.88);
然后看看刚刚建好的库：
select * from earnings;
(1)sum函数，统计总合
按照月份，统计每個地区的总收入
select earnmonth, area, sum(personincome)
from earnings
group by earnmonth,area
order by earnmonth,area
查看结果如下：
(2)rollup函数
按照月份，地区统计收入
Sql代码
select earnmonth, area, sum(personincome)
from earnings
group by rollup(earnmonth,area);
查看结果如下：
(3)cube函数
按照月份，地区进行收入总汇总
Sql代码
select earnmonth, area, sum(personincome)
from earnings
group by cube(earnmonth,area)
order by earnmonth,area nulls last;
结果如下：
小结：sum是统计求和的函数。
group by 是分组函数，按照earnmonth和area先后次序分组。
以上三例都是先按照earnmonth分组，在earnmonth内部再按area分组，并在area组内统计personincome总合。
group by 后面什么也不接就是直接分组。
group by 后面接 rollup 是在纯粹的 group by 分组上再加上对earnmonth的汇总统计。
group by 后面接 cube 是对earnmonth汇总统计基础上对area再统计。
另外那个 nulls last 是把空值放在最后。
rollup和cube区别：
如果是ROLLUP(A, B, C)的话，GROUP BY顺序
(A、B、C)
(A、B)
(A)
最后对全表进行GROUP BY操作。
如果是GROUP BY CUBE(A, B, C)，GROUP BY顺序
(A、B、C)
(A、B)
(A、C)
(A)，
(B、C)
(B)
(C)，
最后对全表进行GROUP BY操作。
(4)grouping函数
在以上例子中，是用rollup和cube函数都会对结果集产生null，这时候可用grouping函数来确认
该记录是由哪个字段得出来的
grouping函数用法，带一个参数，参数为字段名，结果是根据该字段得出来的就返回1，反之返回0
Sql代码
select decode(grouping(earnmonth),1,'所有月份',earnmonth) 月份,
decode(grouping(area),1,'全部地区',area) 地区, sum(personincome) 总金额
from earnings
group by cube(earnmonth,area)
order by earnmonth,area nulls last;
查看结果如下：
(5)rank() over开窗函数
按照月份、地区，求打工收入排序
Sql代码
select earnmonth 月份,area 地区,sname 打工者, personincome 收入,
rank() over (partition by earnmonth,area order by personincome desc) 排名
from earnings;
查看结果：
(6)dense_rank() over开窗函数
按照月份、地区，求打工收入排序2
Sql代码
select earnmonth 月份,area 地区,sname 打工者, personincome 收入,
dense_rank() over (partition by earnmonth,area order by personincome desc) 排名
from earnings;
结果如下：
(7)row_number() over开窗函数
按照月份、地区，求打工收入排序3
Sql代码
select earnmonth 月份,area 地区,sname 打工者, personincome 收入,
row_number() over (partition by earnmonth,area order by personincome desc) 排名
from earnings;
结果如下：
通过(5)(6)(7)发现rank,dense_rank,row_number的区别：
结果集中如果出现两个相同的数据，那么rank会进行跳跃式的排名，
比如两个第二，那么没有第三接下来就是第四；
但是dense_rank不会跳跃式的排名，两个第二接下来还是第三；
row_number最牛，即使两个数据相同，排名也不一样。
(8)sum累计求和
根据月份求出各个打工者收入总和，按照收入由少到多排序
Sql代码
select earnmonth 月份,area 地区,sname 打工者,
sum(personincome) over (partition by earnmonth,area order by personincome) 总收入
from earnings;
查看结果如下：
(9)max，min，avg和sum函数综合运用
按照月份和地区求打工收入最高值，最低值，平均值和总额
Sql代码
select distinct earnmonth 月份, area 地区,
max(personincome) over(partition by earnmonth,area) 最高值,
min(personincome) over(partition by earnmonth,area) 最低值,
avg(personincome) over(partition by earnmonth,area) 平均值,
sum(personincome) over(partition by earnmonth,area) 总额
from earnings;
结果如下：
(10)lag和lead函数
求出每个打工者上个月和下个月有没有赚钱(personincome大于零即为赚钱)
Sql代码
select earnmonth 本月,sname 打工者,
lag(decode(nvl(personincome,0),0,'没赚','赚了'),1,0) over(partition by sname order by earnmonth) 上月,
lead(decode(nvl(personincome,0),0,'没赚','赚了'),1,0) over(partition by sname order by earnmonth) 下月
from earnings;
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