Reputation: 461
Currently my dataset consist of 4 columns, id
, status
, user_id
, created_date
so after a while the data can be like this
(1, 'LOGIN', '2019-07-16 07:06:55', 'Bob')
(2, 'LOGOUT', '2019-07-16 07:29:13', 'Bob')
(3, 'LOGIN', '2019-07-16 07:30:31', 'Bob')
(4, 'LOGOUT', '2019-07-16 07:49:50', 'Bob')
(5, 'LOGIN', '2019-07-16 08:05:55', 'Tom')
(6, 'LOGOUT', '2019-07-16 08:15:13', 'Tom')
(7, 'LOGIN', '2019-07-16 09:13:55', 'John')
(8, 'LOGOUT', '2019-07-16 09:20:13', 'John')
I am trying to make it like this
(1, '2019-07-16 07:06:55', '2019-07-16 07:29:13', 'Bob', 22.5800)
(2, '2019-07-16 07:30:31', '2019-07-16 07:49:50', 'Bob', 19.5800)
(3, '2019-07-16 08:05:55', '2019-07-16 08:15:13', 'Tom', 9.5800)
(4, '2019-07-16 09:13:55', '2019-07-16 09:20:13', 'John', 6.5800)
So this is the query that I came up with so far
SELECT
max(CASE WHEN action = 'LOGOUT'
THEN A.action_date END) AS login_date,
CASE WHEN max(CASE WHEN action = 'LOGOUT'
THEN A.action_date END) < max(CASE WHEN action = 'LOGOUT'
THEN A.action_date END)
THEN max(CASE WHEN action = 'LOGOUT'
THEN A.action_date END)
ELSE max(CASE WHEN action = 'LOGOUT'
THEN A.action_date END) END AS logout_date,
A.full_name,
CASE WHEN timestamp(max(CASE WHEN action = 'LOGOUT'
THEN A.action_date END)) < timestamp(max(CASE WHEN action = 'LOGOUT'
THEN A.action_date END)) OR max(CASE WHEN action = 'LOGOUT'
THEN A.action_date END) IS NULL
THEN 0
ELSE
(timestamp(max(CASE WHEN action = 'LOGOUT'
THEN A.action_date END)) - timestamp(max(CASE WHEN action = 'LOGOUT'
THEN A.action_date END))) / 100 END AS session_time
FROM (
SELECT
timestamp(created_date) AS action_date,
name as full_name,
status as action
FROM `training_ground`.session
WHERE status = 'LOGIN' OR status = 'LOGOUT'
GROUP BY action, cast(action_date AS DATE), name
ORDER BY action_date DESC) AS A
GROUP BY A.full_name
ORDER BY A.action_date DESC;
I have no idea how to differentiate first login-logout to the second login-logout session, with this query, I am only getting
(1, '2019-07-16 07:06:55', '2019-07-16 07:29:13', 'Bob', 22.5800)
(2, '2019-07-16 08:05:55', '2019-07-16 08:15:13', 'Tom', 9.5800)
(3, '2019-07-16 09:13:55', '2019-07-16 09:20:13', 'John', 6.5800)
Is there a way to group login-logout as a set, so that I can differentiate every single pair of login-logout sequentially?
Upvotes: 2
Views: 91
Reputation: 164139
You can do it with a left join and then subtract the 2 dates:
select
t.id,
t.action_date login_date, tt.action_date logout_date,
t.user_id,
(tt.action_date - t.action_date) / 100 session_time
from (
select * from session where status = 'LOGIN'
) t left join (
select * from session where status = 'LOGOUT'
) tt on tt.user_id = t.user_id and
tt.action_date = (
select min(action_date) from session
where status = 'LOGOUT' and user_id = t.user_id and action_date > t.action_date
)
See the demo.
Results:
| id | login_date | user_id | logout_date | session_time |
| --- | ------------------- | ------- | ------------------- | ------------ |
| 1 | 2019-07-16 07:06:55 | Bob | 2019-07-16 07:29:13 | 22.58 |
| 3 | 2019-07-16 07:30:31 | Bob | 2019-07-16 07:49:50 | 19.19 |
| 5 | 2019-07-16 08:05:55 | Tom | 2019-07-16 08:15:13 | 9.58 |
| 7 | 2019-07-16 09:13:55 | John | 2019-07-16 09:20:13 | 6.58 |
Upvotes: 2
Reputation:
Simple implementation over provided inputs. i have data set like:
select id, stat[status],dater[Date], name[Name] from tablelogin
Select t1.id, t1.dater[login], t2.dater[logout], t1.name[name], datediff(day,t1.dater, t2.dater)[days] from tablelogin t1, tablelogin t2 where t1.name=t2.name and t2.id>t1.id and t2.stat='logout'
you need to work on logic and control, when records grows the above query may produce different results.
Upvotes: 0