常用的分析函数如下所列:
row_number() over(partition by ... order by ...)
rank() over(partition by ... order by ...)
dense_rank() over(partition by ... order by ...)
count() over(partition by ... order by ...)
max() over(partition by ... order by ...)
min() over(partition by ... order by ...)
sum() over(partition by ... order by ...)
avg() over(partition by ... order by ...)
first_value() over(partition by ... order by ...)
last_value() over(partition by ... order by ...)
lag() over(partition by ... order by ...)
lead() over(partition by ... order by ...)

常用的分析函数如下所列:
row_number() over(partition by ... order by ...)
rank() over(partition by ... order by ...)
dense_rank() over(partition by ... order by ...)
count() over(partition by ... order by ...)
max() over(partition by ... order by ...)
min() over(partition by ... order by ...)
sum() over(partition by ... order by ...)
avg() over(partition by ... order by ...)
first_value() over(partition by ... order by ...)
last_value() over(partition by ... order by ...)
lag() over(partition by ... order by ...)
lead() over(partition by ... order by ...)

示例：
14:33:29 SQL> select type,qty from test;
TYPE QTY
---------- ----------
1 3
1 6
2 5
2 9
2 7

14:33:36 SQL> select type,qty,to_char(row_number() over(partition by type order by qty))||'/'||to_char(count(*) over(partition by type)) as cnt2 from test;
TYPE QTY CNT2
---------- ---------- ------------
1 3 1/2
1 6 2/2
2 5 1/3
2 7 2/3
2 9 3/3

SQL> select * from test;

ID MC
---------- --------------------------------------------------
1 11111
2 22222
3 33333
4 44444

SQL>
SQL> select t.id,mc,to_char(b.rn)||'/'||t.id
2 from test t,
3 (select rownum rn from (select max(to_number(id)) mid from test) connect by rownum <=mid ) b
4 where b.rn<=to_number(t.id)
5 order by id,3
6 /

ID MC TO_CHAR(B.RN)||'/'||T.ID
---------- -------------------------------------------------- ---------------------------------------------------
1 11111 1/1
2 22222 1/2
2 22222 2/2
3 33333 1/3
3 33333 2/3
3 33333 3/3
4 44444 1/4
4 44444 2/4
4 44444 3/4
4 44444 4/4

10 rows selected