我正在尝试从表格中的数据计算一些计数和平均时间间隔：
+---------+--------+------+-----------+----------+
| STATS_I | TASK_I | TYPE | CREATE_TS | END_TS |
+---------+--------+------+-----------+----------+
| 1 | 111 | A | 30-05-16 | 30-05-16 |
+---------+--------+------+-----------+----------+
| 2 | 111 | A | 30-05-16 | |
+---------+--------+------+-----------+----------+
| 3 | 111 | B | 30-05-16 | 30-05-16 |
+---------+--------+------+-----------+----------+
| 4 | 111 | B | 30-05-16 | |
+---------+--------+------+-----------+----------+
| 5 | 111 | C | 30-05-16 | 30-05-16 |
+---------+--------+------+-----------+----------+
| 6 | 222 | D | 30-05-16 | |
+---------+--------+------+-----------+----------+
| 7 | 222 | D | 30-05-16 | 30-05-16 |
+---------+--------+------+-----------+----------+
| 8 | 222 | C | 30-05-16 | 30-05-16 |
+---------+--------+------+-----------+----------+
| 9 | 222 | C | 30-05-16 | 30-05-16 |
+---------+--------+------+-----------+----------+
| 10 | 222 | C | 30-05-16 | |
+---------+--------+------+-----------+----------+
| 11 | 333 | A | 30-05-16 | 30-05-16 |
+---------+--------+------+-----------+----------+
| 12 | 333 | B | 30-05-16 | 30-05-16 |
+---------+--------+------+-----------+----------+
| 13 | 333 | B | 30-05-16 | 31-05-16 |
+---------+--------+------+-----------+----------+
| 14 | 333 | D | 30-05-16 | 30-05-16 |
+---------+--------+------+-----------+----------+
| 15 | 333 | D | 30-05-16 | 31-05-16 |
+---------+--------+------+-----------+----------+
| 16 | 444 | D | 30-05-16 | 30-05-16 |
+---------+--------+------+-----------+----------+
| 17 | 444 | D | 30-05-16 | 31-05-16 |
+---------+--------+------+-----------+----------+
| 18 | 444 | C | 30-05-16 | 30-05-16 |
+---------+--------+------+-----------+----------+
| 19 | 444 | B | 30-05-16 | 30-05-16 |
+---------+--------+------+-----------+----------+
| 20 | 444 | A | 30-05-16 | 30-05-16 |
+---------+--------+------+-----------+----------+
样本表可以填充：
CREATE TABLE "STATS" ("STATS_I" NUMBER(10,0), "TASK_I" NUMBER(10,0), "TYPE" VARCHAR2(30), "CREATE_TS" DATE, "END_TS" DATE);
Insert into STATS (STATS_I,TASK_I,TYPE,CREATE_TS,END_TS) values (1,111,'A',to_date('30-05-16','DD-MM-RR'),to_date('30-05-16','DD-MM-RR'));
Insert into STATS (STATS_I,TASK_I,TYPE,CREATE_TS,END_TS) values (2,111,'A',to_date('30-05-16','DD-MM-RR'),null);
Insert into STATS (STATS_I,TASK_I,TYPE,CREATE_TS,END_TS) values (3,111,'B',to_date('30-05-16','DD-MM-RR'),to_date('30-05-16','DD-MM-RR'));
Insert into STATS (STATS_I,TASK_I,TYPE,CREATE_TS,END_TS) values (4,111,'B',to_date('30-05-16','DD-MM-RR'),null);
Insert into STATS (STATS_I,TASK_I,TYPE,CREATE_TS,END_TS) values (5,111,'C',to_date('30-05-16','DD-MM-RR'),to_date('30-05-16','DD-MM-RR'));
Insert into STATS (STATS_I,TASK_I,TYPE,CREATE_TS,END_TS) values (6,222,'D',to_date('30-05-16','DD-MM-RR'),null);
Insert into STATS (STATS_I,TASK_I,TYPE,CREATE_TS,END_TS) values (7,222,'D',to_date('30-05-16','DD-MM-RR'),to_date('30-05-16','DD-MM-RR'));
Insert into STATS (STATS_I,TASK_I,TYPE,CREATE_TS,END_TS) values (8,222,'C',to_date('30-05-16','DD-MM-RR'),to_date('30-05-16','DD-MM-RR'));
Insert into STATS (STATS_I,TASK_I,TYPE,CREATE_TS,END_TS) values (9,222,'C',to_date('30-05-16','DD-MM-RR'),to_date('30-05-16','DD-MM-RR'));
Insert into STATS (STATS_I,TASK_I,TYPE,CREATE_TS,END_TS) values (10,222,'C',to_date('30-05-16','DD-MM-RR'),null);
Insert into STATS (STATS_I,TASK_I,TYPE,CREATE_TS,END_TS) values (11,333,'A',to_date('30-05-16','DD-MM-RR'),to_date('30-05-16','DD-MM-RR'));
Insert into STATS (STATS_I,TASK_I,TYPE,CREATE_TS,END_TS) values (12,333,'B',to_date('30-05-16','DD-MM-RR'),to_date('30-05-16','DD-MM-RR'));
Insert into STATS (STATS_I,TASK_I,TYPE,CREATE_TS,END_TS) values (13,333,'B',to_date('30-05-16','DD-MM-RR'),null);
Insert into STATS (STATS_I,TASK_I,TYPE,CREATE_TS,END_TS) values (14,333,'D',to_date('30-05-16','DD-MM-RR'),to_date('30-05-16','DD-MM-RR'));
Insert into STATS (STATS_I,TASK_I,TYPE,CREATE_TS,END_TS) values (15,333,'D',to_date('30-05-16','DD-MM-RR'),null);
Insert into STATS (STATS_I,TASK_I,TYPE,CREATE_TS,END_TS) values (16,444,'D',to_date('30-05-16','DD-MM-RR'),to_date('30-05-16','DD-MM-RR'));
Insert into STATS (STATS_I,TASK_I,TYPE,CREATE_TS,END_TS) values (17,444,'D',to_date('30-05-16','DD-MM-RR'),null);
Insert into STATS (STATS_I,TASK_I,TYPE,CREATE_TS,END_TS) values (18,444,'C',to_date('30-05-16','DD-MM-RR'),to_date('30-05-16','DD-MM-RR'));
Insert into STATS (STATS_I,TASK_I,TYPE,CREATE_TS,END_TS) values (19,444,'B',to_date('30-05-16','DD-MM-RR'),to_date('30-05-16','DD-MM-RR'));
Insert into STATS (STATS_I,TASK_I,TYPE,CREATE_TS,END_TS) values (20,444,'A',to_date('30-05-16','DD-MM-RR'),to_date('31-05-16','DD-MM-RR'));
- end_ts和create_ts保持10分钟差异
我想要获得的输出是：
+--------+--------------+-------------------+-------------------+-------+
| Task_i | A | B | C | D |
+ +--------------+-------------------+-------------------+-------+
| | Count | Read | Count | Avg. Time | Count | Avg. Time | Count |
| | | | | to Read | | to Read | |
+--------+-------+------+-------+-----------+-------+-----------+-------+
| 111 | 2 | 1 | 2 | 10 min | 1 | 10 min | 0 |
+--------+-------+------+-------+-----------+-------+-----------+-------+
| 222 | 0 | 0 | 0 | 0 min | 3 | 10 min | 2 |
+--------+-------+------+-------+-----------+-------+-----------+-------+
| 333 | 1 | 1 | 2 | 10 min | 0 | 0 min | 2 |
+--------+-------+------+-------+-----------+-------+-----------+-------+
| 444 | 1 | 1 | 1 | 10 min | 1 | 10 min | 2 |
+--------+-------+------+-------+-----------+-------+-----------+-------+
每个task_i的位置：
end_ts不为空的类型的行数(end_ts - create_ts )/count of type计算，忽略end_ts为空的行到目前为止，我尝试创建了四个表，每个表对应一种类型，然后在task_i上加入它们：
(((select count(*) as A from stats s where s.type='A' group by s.TYPE UNION ALL
select count(*) as B from stats s where s.type='B' group by s.TYPE ) UNION ALL
select count(*) as C from stats s where s.type='C' group by s.TYPE ) UNION ALL
select count(*) as D from stats s where s.type='D' group by s.TYPE ) ;
但这并不能产生我需要的东西：
A
----------
4
5
4
7
我做错了什么，如何生成所需的输出？
答案 0 :(得分：0)
计数是您尝试的部分，可以通过条件计数找到 - 在案例表达式中 - 而不是使用union：
select task_i,
count(case when type = 'A' then 1 end) as a_count,
count(case when type = 'B' then 1 end) as b_count,
count(case when type = 'C' then 1 end) as c_count,
count(case when type = 'D' then 1 end) as d_count
from stats
group by task_i
order by task_i;
TASK_I A_COUNT B_COUNT C_COUNT D_COUNT
---------- ---------- ---------- ---------- ----------
111 2 2 1 0
222 0 0 2 3
333 1 2 0 2
444 1 1 1 2
通过修改案例表达式可以找到＆＃39;读取＆＃39;的数量，其中end_ts is not null：
select task_i,
count(case when type = 'A' then 1 end) as a_count,
count(case when type = 'A' and end_ts is not null then 1 end) as a_read,
count(case when type = 'B' then 1 end) as b_count,
count(case when type = 'B' and end_ts is not null then 1 end) as b_read,
count(case when type = 'C' then 1 end) as c_count,
count(case when type = 'C' and end_ts is not null then 1 end) as c_read,
count(case when type = 'D' then 1 end) as d_count
from stats
group by task_i
order by task_i;
TASK_I A_COUNT A_READ B_COUNT B_READ C_COUNT C_READ D_COUNT
---------- ---------- ---------- ---------- ---------- ---------- ---------- ----------
111 2 1 2 1 1 1 0
222 0 0 0 0 2 1 3
333 1 1 2 1 0 0 2
444 1 1 1 1 1 1 2
可以通过相同的方式找到过去的时间，但使用avg()代替count()：
select task_i,
count(case when type = 'A' then 1 end) as a_count,
count(case when type = 'A' and end_ts is not null then 1 end) as a_read,
avg(case when type = 'A' and end_ts is not null then end_ts - create_ts end) as a_readtime,
count(case when type = 'B' then 1 end) as b_count,
count(case when type = 'B' and end_ts is not null then 1 end) as b_read,
avg(case when type = 'B' and end_ts is not null then end_ts - create_ts end) as b_readtime,
count(case when type = 'C' then 1 end) as c_count,
count(case when type = 'C' and end_ts is not null then 1 end) as c_read,
avg(case when type = 'C' and end_ts is not null then end_ts - create_ts end) as c_readtime,
count(case when type = 'D' then 1 end) as d_count
from stats
group by task_i
order by task_i;
TASK_I A_COUNT A_READ A_READTIME B_COUNT B_READ B_READTIME C_COUNT C_READ C_READTIME D_COUNT
---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ----------
111 2 1 1.0035 2 1 1.0035 1 1 1.0035 0
222 0 0 0 0 2 1 1.0035 3
333 1 1 1.0035 2 1 1.0035 0 0 2
444 1 1 1.0035 1 1 1.0035 1 1 1.0035 2
日期算术意味着那些以一天的分数显示;我稍微修改了您的数据，每次结束时间增加五分钟，以便更接近原始结果。要获得字符串输出，您需要稍微操作一下，如果使用内联视图进行计算，那么重复性要小一些：
select task_i,
a_count,
a_read,
case when a_readtime > 1 then trunc(24 * a_readtime) || ' hrs ' end
|| round(60 * mod(24 * nvl(a_readtime, 0), 1)) || ' min'
as a_readtime
from (
select task_i,
count(case when type = 'A' then 1 end) as a_count,
count(case when type = 'A' and end_ts is not null then 1 end) as a_read,
avg(case when type = 'A' and end_ts is not null then end_ts - create_ts end) as a_readtime,
count(case when type = 'B' then 1 end) as b_count,
count(case when type = 'B' and end_ts is not null then 1 end) as b_read,
avg(case when type = 'B' and end_ts is not null then end_ts - create_ts end) as b_readtime,
count(case when type = 'C' then 1 end) as c_count,
count(case when type = 'C' and end_ts is not null then 1 end) as c_read,
avg(case when type = 'C' and end_ts is not null then end_ts - create_ts end) as c_readtime,
count(case when type = 'D' then 1 end) as d_count
from stats
group by task_i
)
order by task_i;
TASK_I A_COUNT A_READ A_READTIME
---------- ---------- ---------- ---------------
111 2 1 24 hrs 5 min
222 0 0 0 min
333 1 1 24 hrs 5 min
444 1 1 24 hrs 5 min
...并为B，C和D的相同数据重复外部查询选择列表项。
如果您使用的是11g或更高版本，则可以使用pivot来避免重复将时差转换为字符串：
select * from (
select task_i, type, type_count, type_read,
case when type_readtime > 1 then trunc(24 * type_readtime) || ' hrs ' end
|| round(60 * mod(24 * type_readtime, 1)) || ' min'
as type_readtime
from (
select task_i,
type,
count(*) as type_count,
count(case when end_ts is not null then 1 end) as type_read,
avg(case when end_ts is not null then end_ts - create_ts end) as type_readtime
from stats
group by task_i, type
)
)
pivot (max(type_count) as count, max(type_read) as read, max(type_readtime) as readtime
for (type) in ('A' as a, 'B' as b, 'C' as c, 'D' as d))
order by task_i;
TASK_I A_COUNT A_READ A_READTIME B_COUNT B_READ B_READTIME C_COUNT C_READ C_READTIME D_COUNT D_READ D_READTIME
---------- ---------- ---------- --------------- ---------- ---------- --------------- ---------- ---------- --------------- ---------- ---------- ---------------
111 2 1 24 hrs 5 min 2 1 24 hrs 5 min 1 1 24 hrs 5 min
222 2 1 24 hrs 5 min 3 2 24 hrs 5 min
333 1 1 24 hrs 5 min 2 1 24 hrs 5 min 2 1 24 hrs 5 min
444 1 1 24 hrs 5 min 1 1 24 hrs 5 min 1 1 24 hrs 5 min 2 1 24 hrs 5 min
...但如果您不想要空值，则需要在最终选择列表中使用nvl()次调用替换它们，这会使其再次变得更加混乱。