Top N earliest punched in Employees across departments in a month

Question

Find two of the earliest punched in Employees across departments in a month The dataset.

Id   EmpName         EmpPunchInTime        EmpDept
1      Dharma        26-JAN-2018 08:45     Engineering
2      Gumpina       26-JAN-2018 08:46     Finance
3      Kumar         26-JAN-2018 08:47     HR
4      Kamal         26-JAN-2018 08:48     Engineering
5      Muruges       26-JAN-2018 08:49     Finance
6      Gumpina       25-JAN-2018 09:01     Finance
7      Kumar         25-JAN-2018 08:42     HR
8      Biju          25-JAN-2018 08:40     Engineering
9      Divya         25-JAN-2018 08:49     HR
10     Vali          24-JAN-2018 08:52     Engineering

The expected output is,

Id   EmpName       EmpPunchInTime        EmpDept
8      Biju          25-JAN-2018 08:40     Engineering
1      Dharma        26-JAN-2018 08:45     Engineering
2      Gumpina       26-JAN-2018 08:46     Finance
5      Muruges       26-JAN-2018 08:49     Finance
7      Kumar         25-JAN-2018 08:42     HR
9      Divya         25-JAN-2018 08:49     HR

FYI I the query which I used

SELECT *
FROM (SELECT *
            ,DENSE_RANK() OVER ( PARTITION BY EmpDept ORDER BY EmpPunchInTime) RANK
      FROM EMPLOYEE_PUNCH) emp_pun
WHERE RANK <= 2

I have tried to solve by using dense rank(partition by EmpDept, order by EmpPunchInTime) but am not seeing desired results.

Note: If the same employee in a department punches early in most of the days(like Kumar of HR dept here in this dataset) then pick the earliest date among his dates and the employee who punches next to him.

Answer 1

It seems to me the specification failed to mention that the ordering should be done using only the hour and minute parts of the date.

The below returns the expected output.

with data as
(
  select 1 as id, 'Dharma' as empname, to_date('26-JAN-2018 08:45', 'DD-MON-YYYY HH24:MI') as emppunchintime, 'Engineering' as empdept from dual union all
  select 2 ,      'Gumpina',           to_date('26-JAN-2018 08:46', 'DD-MON-YYYY HH24:MI'),                   'Finance'                from dual union all
  select 3 ,      'Kumar',             to_date('26-JAN-2018 08:47', 'DD-MON-YYYY HH24:MI'),                   'HR'                     from dual union all
  select 4 ,      'Kamal' ,            to_date('26-JAN-2018 08:48', 'DD-MON-YYYY HH24:MI'),                   'Engineering'            from dual union all
  select 5 ,      'Muruges',           to_date('26-JAN-2018 08:49', 'DD-MON-YYYY HH24:MI'),                   'Finance'                from dual union all
  select 6 ,      'Gumpina',           to_date('25-JAN-2018 09:01', 'DD-MON-YYYY HH24:MI'),                   'Finance'                from dual union all
  select 7 ,      'Kumar',             to_date('25-JAN-2018 08:42', 'DD-MON-YYYY HH24:MI'),                   'HR'                     from dual union all
  select 8 ,      'Biju',              to_date('25-JAN-2018 08:40', 'DD-MON-YYYY HH24:MI'),                   'Engineering'            from dual union all
  select 9 ,      'Divya',             to_date('25-JAN-2018 08:49', 'DD-MON-YYYY HH24:MI'),                   'HR'                     from dual union all
  select 10,      'Vali',              to_date('24-JAN-2018 08:52', 'DD-MON-YYYY HH24:MI'),                   'Engineering'            from dual
)
select f.id, f.empname, f.emppunchintime, f.empdept from 
(
  select e.*, row_number() over (partition by e.empdept order by to_char(e.emppunchintime, 'HH24:MI')) as rn2 from
  (
    select d.*, row_number() over (partition by d.empname order by to_char(d.emppunchintime, 'HH24:MI')) as rn from data d
  ) e
  where e.rn = 1
) f
where f.rn2 <= 2
order by f.empdept, f.emppunchintime;

Output:

        ID EMPNAME EMPPUNCHINTIME    EMPDEPT
---------- ------- ----------------- -----------
         8 Biju    25-JAN-2018 08:40 Engineering
         1 Dharma  26-JAN-2018 08:45 Engineering
         2 Gumpina 26-JAN-2018 08:46 Finance
         5 Muruges 26-JAN-2018 08:49 Finance
         7 Kumar   25-JAN-2018 08:42 HR
         9 Divya   25-JAN-2018 08:49 HR