复杂/算法 SQL 查询

Question

我想知道是否有可能实现一个 SQL 查询，它会像一种算法一样根据下表为我计算某个数字：

这是初始查询，

SELECT Activity, TimeOfAction, Requestor
FROM EventLog
WHERE Requestor = 0
ORDER BY Requestor, TimeOfAction;

以及返回的数据样本，

Login   2010-05-28 15:52:50.590 0

Login   2010-05-28 15:52:50.873 0

Logout  2010-05-28 15:52:50.890 0

Logout  2010-05-28 16:22:57.983 0

Login   2010-05-29 11:29:36.967 0

Logout  2010-05-29 11:29:37.640 0

如您所见，此数据集中有重复的登录和注销。当有重复时，我需要通过第一次登录和最后一次注销来计算会话的长度。因此，给出上述数据的第一个会话将来自，

5-28 15:52:50.590 to 5-28 16:22:57.983

算法大致，

1) 按用户名排序登录/注销列表，然后按操作时间排序

2) 如果条目是登录，则搜索下一个登出，紧接着是一个登录（以确认它是所有重复项中的最后一个登出）

3) 使用第一次登录和最后一次注销创建一个新会话（长度为注销时间-登录时间）

4) 重复

目前我只是在代码中实现它，但想知道它是否可以在 SQL 中实现（我对 SQL 不太熟悉）。

Answer 1

当然……试试这样的。

select e1.Requestor, 
       e1.TimeOfAction as LoginTime, 
       (select min(ActivityTime)
        from EventLog where TimeOfAction > e1.TimeOfAction 
        and Activity = 'Logout') as LogoutTime
from EventLog e1
where e1.ActivityType = 'Login'
order by Requestor, LoginTime

第二个解决方案...看看这是否更适合你。

select requestor,
    (select min(activitytime)
     from eventlog 
     where activitytime < e.activitytime
     and activity = 'Login' and e.activity = 'Logout') as LoginTime, 
    (select max(activitytime)
     from eventlog 
     where activitytime > e.activitytime
     and activity = 'Logout' and e.activity = 'Login') as LogoutTime, 
from eventlog e
order by requestor, logintime

Answer 2

select min(TimeOfAction) Login, null Logout, Requestor
  from EventLog
 where Activity = 'Login'
 group by Requestor
union
select null Login, max(TimeOfAction) Logout, Requestor
  from EventLog
 where Activity = 'Logout'
 group by Requestor

Answer 3

这里有一个选项供您使用一些 CTE 和 row_numbers。基本上，它为每个用户对事件进行排序，然后查找在注销后或不执行任何操作的登录列表，然后查找执行登录或不执行任何操作的注销列表，然后将它们关联成对。

;with events as (
  select *,
         row_number() over(partition by Requestor order by TimeOfAction) row
  from EventLog
), logins as (
  select e1.Activity, e1.TimeOfAction, e1.Requestor,
         row_number() over(partition by e1.Requestor order by e1.TimeOfAction) row
  from events e1
    left join events e2 on e1.Requestor=e2.Requestor
                       and e1.row=e2.row+1
  where e1.Activity='Login'
    and e1.Activity!=isnull(e2.Activity, 'Logout')
), logouts as (
  select e1.Activity, e1.TimeOfAction, e1.Requestor,
         row_number() over(partition by e1.Requestor order by e1.TimeOfAction) row
  from events e1
    left join events e2 on e1.Requestor=e2.Requestor
                       and e1.row=e2.row-1
  where e1.Activity='Logout'
    and e1.Activity!=isnull(e2.Activity, 'Login')
)
select i.Requestor, i.TimeOfAction as loginTime, o.TimeOfAction as logoutTime
from logins i
  left join logouts o on i.Requestor=o.Requestor
                     and i.row=o.row

注意：通过将部分或全部 CTE 查询拆分到临时表中，可以（大幅？）提高查询性能。即类似于以下内容：

select *,
       row_number() over(partition by Requestor order by TimeOfAction) row
into #events
from EventLog

select e1.Activity, e1.TimeOfAction, e1.Requestor,
       row_number() over(partition by e1.Requestor order by e1.TimeOfAction) row
into #logins
from #events e1
  left join #events e2 on e1.Requestor=e2.Requestor
                     and e1.row=e2.row+1
where e1.Activity='Login'
  and e1.Activity!=isnull(e2.Activity, 'Logout')

select e1.Activity, e1.TimeOfAction, e1.Requestor,
       row_number() over(partition by e1.Requestor order by e1.TimeOfAction) row
into #logouts
from #events e1
  left join #events e2 on e1.Requestor=e2.Requestor
                     and e1.row=e2.row-1
where e1.Activity='Logout'
  and e1.Activity!=isnull(e2.Activity, 'Login')

select i.Requestor, i.TimeOfAction as loginTime, o.TimeOfAction as logoutTime
from #logins i
  left join #logouts o on i.Requestor=o.Requestor
                      and i.row=o.row

drop table #logouts
drop table #logins
drop table #events