我有一个包含列的表员工：
两者都与员工有关，因此同一公司的员工之间存在差异。
我希望选择opted_out_on月等于opt_out_window_starts_on月份的员工人数，按公司规模分组。
我写了下面的查询，但数字不对。
源数据如下：
company_id | employee_id | opt_out_on | opt_out_window_starts_on
-----------+-------------+------------+-------------------------
23101 | 920190500 | 20/01/2017 | 09/01/2017
12264 | 920190508 | 02/03/2017 | 04/02/2017
12039 | 920190513 | 07/11/2017 | 31/10/2017
12039 | 920190516 | 13/02/2017 | 11/02/2017
23109 | 920190520 | 06/01/2017 | 06/01/2017
21875 | 920190529 | 22/05/2017 | 15/05/2017
21875 | 920190532 | 19/05/2017 | 15/05/2017
21875 | 920190533 | 22/05/2017 | 15/05/2017
21875 | 920190534 | 15/05/2017 | 15/05/2017
21875 | 920190535 | 22/05/2017 | 15/05/2017
21875 | 920190536 | 19/05/2017 | 15/05/2017
18112 | 920190545 | 11/01/2017 | 05/01/2017
9764 | 920190546 | 02/05/2017 | 02/05/2017
18365 | 920190665 | 30/03/2017 | 28/03/2017
18365 | 920190668 | 28/03/2017 | 28/03/2017
18365 | 920190678 | 28/03/2017 | 28/03/2017
20928 | 920190699 | 14/06/2017 | 13/06/2017
20928 | 920190705 | 20/06/2017 | 13/06/2017
16860 | 920190717 | 17/01/2017 | 16/01/2017
16860 | 920190718 | 16/01/2017 | 16/01/2017
此数据可在SQL Fiddle上找到。
我的代码是：
with size as
(
select distinct company_id
, date_trunc('month', opt_out_window_starts_on) :: date months
, case
when count(id) over (partition by company_id ) = 1 then
count(id)
filter
(
where opt_state = 'opted_out'
and
(
date_trunc('month', opt_out_on) = date_trunc('month', opt_out_window_starts_on)
)
)
else 0
end as "one"
, case
when count(id) over (partition by company_id ) = 2 then
count(id)
filter
(
where opt_state = 'opted_out'
and
(
date_trunc('month', opt_out_on) = date_trunc('month', opt_out_window_starts_on)
)
)
else 0
end as "two"
, case
when
count(id) over (partition by company_id ) >= 3
and count(id) over (partition by company_id ) <= 4
then
count(id) filter
(
where opt_state = 'opted_out'
and
(
date_trunc('month', opt_out_on) = date_trunc('month', opt_out_window_starts_on)
)
)
else 0
end as "3-4"
, case
when
count(id) over (partition by company_id ) >= 5
and count(id) over (partition by company_id ) <= 9
then
count(id)
filter
(
where opt_state = 'opted_out'
and
(
date_trunc('month', opt_out_on) = date_trunc('month', opt_out_window_starts_on)
)
)
else 0
end as "5-9"
, case
when
count(id) over (partition by company_id ) >= 10
and count(id) over (partition by company_id ) <= 29
then
count(id)
filter
(
where opt_state = 'opted_out'
and
(
date_trunc('month', opt_out_on) = date_trunc('month', opt_out_window_starts_on)
)
)
else 0
end as "10-29"
, case
when
count(id) over (partition by company_id ) >= 30
and count(id) over (partition by company_id ) <= 49
then
count(id)
filter (
where opt_state = 'opted_out'
and
(
date_trunc('month', opt_out_on) = date_trunc('month', opt_out_window_starts_on)
)
)
else 0
end as "30-49"
, case
when
count(id) over (partition by company_id) >= 50
and count(id) over (partition by company_id) <= 249
then
count(id)
filter
(
where opt_state = 'opted_out'
and
(
date_trunc('month', opt_out_on) = date_trunc('month', opt_out_window_starts_on)
)
)
else 0
end as "50-249"
, case
when
count(id) over (partition by company_id ) >= 250
then
count(id)
filter
(
where opt_state = 'opted_out'
and
(
date_trunc('month', opt_out_on) = date_trunc('month', opt_out_window_starts_on)
)
)
else 0
end as "250+"
from employees
group by company_id
, id
)
select to_char(date_trunc('month', months),'YYYY MON')
, sum(one)
, sum(two)
, sum("3-4")
, sum("5-9")
, sum("10-29")
, sum("30-49")
, sum("50-249")
, sum("250+")
from size
where to_char(date_trunc('month', months),'YYYY MON') is not null
group by date_trunc('month', months)
order by date_trunc('month', months) asc
;
错误结果的样本：
to_char | sum | sum | sum | sum | sum | sum | sum | sum
---------+-----+-----+-----+-----+-----+-----+-----+----
2017 JAN | 35 | 37 | 85 | 119 | 131 | 39 | 19 | 3
2017 FEB | 49 | 53 | 112 | 165 | 170 | 41 | 23 | 2
2017 MAR | 29 | 33 | 62 | 85 | 104 | 24 | 23 | 1
2017 APR | 37 | 50 | 117 | 150 | 159 | 33 | 28 | 3
2017 MAY | 71 | 84 | 150 | 182 | 208 | 51 | 44 | 4
2017 JUN | 35 | 51 | 80 | 90 | 128 | 26 | 43 | 7
2017 JUL | 69 | 84 | 146 | 177 | 173 | 51 | 45 | 5
2017 AUG | 93 | 137 | 168 | 194 | 234 | 63 | 51 | 5
2017 SEP | 75 | 60 | 97 | 127 | 136 | 44 | 44 | 6
2017 OCT | 91 | 113 | 132 | 157 | 126 | 38 | 49 | 6
2017 NOV | 125 | 158 | 168 | 198 | 162 | 36 | 58 | 11
2017 DEC | 49 | 81 | 83 | 103 | 91 | 27 | 40 | 10
2018 JAN | 134 | 132 | 119 | 158 | 132 | 37 | 41 | 12
2018 FEB | 127 | 111 | 155 | 142 | 121 | 37 | 45 | 15
2018 MAR | 112 | 92 | 119 | 115 | 116 | 35 | 37 | 15
2018 APR | 37 | 51 | 64 | 57 | 56 | 14 | 26 | 10
2018 MAY | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
如果以2017年1月为例，选择退出的员工总数为1404，而我的查询显示为468（35 + 37 + 85 + 119 + 131 + 39 + 19 + 3）。
我检查了数字：
select count(id)
, date_trunc('month', opt_out_window_starts_on)
from employees
where opt_state = 'opted_out'
and date_trunc('month', opt_out_window_starts_on) = date_trunc('month', opt_out_on)
group by date_trunc('month', opt_out_window_starts_on)
答案 0 :(得分：1)
如果我想要正确理解你的问题：
此代码解决了这个问题的第一部分;获取公司名单，他们的规模和离职人数：
select company_id
, date_trunc('month', opt_out_window_starts_on) optOutMonth
, count(employee_id) as companySize
, count(case
when opt_state = 'opted_out'
and date_trunc('month', opt_out_on) = date_trunc('month', opt_out_window_starts_on)
then employee_id
else null
end)
as leaversInOptOutWindow
from employee
group by company_id, date_trunc('month', opt_out_window_starts_on)
然后，您可以将此连接到另一个表中，在该表中定义范围以将公司分组为大小，并对结果执行调整。
可悲的是Postgres不支持数据透视表，但似乎可以通过crosstab函数实现相同：PostgreSQL Crosstab Query
我没有在SQL Fiddle中使用它;不确定我的代码是否存在问题，或者缺乏对此功能的支持（因为我对Postgres不够熟悉）......但我相信这应该属于什么你之后：
SELECT * FROM crosstab(
'
select e.optOutMonth
, s.name
, sum(e.leaversInOptOutWindow) LeaverCount
from
(
select company_id
, date_trunc(''month'', opt_out_window_starts_on) optOutMonth
, count(employee_id) as companySize
, count(case
when opt_state = ''opted_out''
and date_trunc(''month'', opt_out_on) = date_trunc(''month'', opt_out_window_starts_on)
then employee_id
else null
end) as leaversInOptOutWindow
from employee
group by company_id
, date_trunc(''month'', opt_out_window_starts_on)
) e
left outer join companySizeRange s
on s.minSize <= e.companySize
and (s.maxSize is null or s.maxSize >= e.companySize)
group by e.optOutMonth, s.name
order by e.optOutMonth, s.name
'
, 'select name from companySizeRange order by minSize'
) as x(
optOutMonth date, "1" int, "2" int, "3-4" int, "5-9" int, "10-29" int, "30-49" int, "50-249" int, "250+" int
);
这是一个不需要crosstab / pivot的版本：
select e.optOutMonth
, sum(case when s.companySize = 1 then e.leaversInOptOutWindow else 0 end) "1"
, sum(case when s.companySize = 2 then e.leaversInOptOutWindow else 0 end) "2"
, sum(case when s.companySize between 3 and 4 then e.leaversInOptOutWindow else 0 end) "3-4"
, sum(case when s.companySize between 5 and 9 then e.leaversInOptOutWindow else 0 end) "5-9"
, sum(case when s.companySize between 10 and 29 then e.leaversInOptOutWindow else 0 end) "10-29"
, sum(case when s.companySize between 30 and 49 then e.leaversInOptOutWindow else 0 end) "30-49"
, sum(case when s.companySize between 50 and 249 then e.leaversInOptOutWindow else 0 end) "50-249"
, sum(case when s.companySize >= 250 then e.leaversInOptOutWindow else 0 end) "250+"
from
(
select company_id
, count(employee_id) as companySize
from employee
group by company_id
) s
inner join
(
select company_id
, date_trunc('month', opt_out_window_starts_on) optOutMonth
, count(employee_id) as leaversInOptOutWindow
from employee
where opt_state = 'opted_out'
and date_trunc('month', opt_out_on) = date_trunc('month', opt_out_window_starts_on)
group by company_id
, date_trunc('month', opt_out_window_starts_on)
) e
on e.company_id = s.company_id
group by e.optOutMonth
order by e.optOutMonth