Hi Nitin, It seems to have been filtered out.
> On Nov 5, 2019, at 8:29 AM, Nitin Pawar <nitinpawar...@gmail.com> wrote: > > Hi Charles, > > I have attached git patch. > I was currently doing for lag function only for testing purposes > > Thanks, > Nitin > > On Tue, Nov 5, 2019 at 6:34 PM Charles Givre <cgi...@gmail.com > <mailto:cgi...@gmail.com>> wrote: > Hi Nitin, > Thanks for your question. Could you/did you share your code? If not, could > you please post a draft PR so that we can take a look and offer suggestions? > Thanks, > -- C > > > > On Nov 5, 2019, at 7:27 AM, Nitin Pawar <nitinpawar...@gmail.com > > <mailto:nitinpawar...@gmail.com>> wrote: > > > > Hi Devs, > > > > I had sent request for this almost 2.5 years ago. Trying it again now. > > > > Currently Apache drill window functions LEAD and LAG support offset as 1. > > In another words in a given window these functions can return either > > previous or next row only. > > > > > > I am trying modify the behavior these function and allow offset >=1 in > > query such as > > select employee_id, department_id,salary, lag(salary,*4*) over(partition by > > department_id order by salary asc) from cp.`employee.json`; > > > > I have managed to remove the limitation which fails the query can not have > > offset > 1 and able to pass the offset to actual function implementation. > > > > Currently I am stuck where the record processor is crossing the window > > boundary of department_id and gets row from next/previous window in > > lead/lag function > > > > For eg: If you notice in row 2 for department_id=2, it is getting previous > > windows of department_id=1 > > > > Here is sample output for below query > > apache drill> select employee_id, department_id,salary, lag(salary,4) > > over(partition by department_id order by salary asc) from > > cp.`employee.json` where department_id <=3; > > +-------------+---------------+---------+----------+ > > | employee_id | department_id | salary | EXPR$3 | > > +-------------+---------------+---------+----------+ > > | 20 | 1 | 30000.0 | null | > > | 5 | 1 | 35000.0 | null | > > | 22 | 1 | 35000.0 | null | > > | 21 | 1 | 35000.0 | null | > > | 2 | 1 | 40000.0 | 30000.0 | > > | 4 | 1 | 40000.0 | 35000.0 | > > | 1 | 1 | 80000.0 | 35000.0 | > > | 37 | 2 | 6700.0 | null | > > | 38 | 2 | 8000.0 | 40000.0 | > > | 39 | 2 | 10000.0 | 40000.0 | > > | 40 | 2 | 10000.0 | 80000.0 | > > | 6 | 2 | 25000.0 | 6700.0 | > > | 42 | 3 | 5000.0 | null | > > | 41 | 3 | 8500.0 | 10000.0 | > > | 7 | 3 | 15000.0 | 10000.0 | > > | 36 | 3 | 45000.0 | 25000.0 | > > +-------------+---------------+---------+----------+ > > > > > > Thanks, > > Nitin Pawar > > > > -- > Nitin Pawar
