I have the following data:
Key Stage CreateDate
AAF 0 01-Jan-2018
AAF 0 02-Jan-2018
AAF 0 10-Jan-2018
AAF 20 20-Jan-2018
AAF 40 20-Mar-2018
AAF 0 01-May-2018
AAF 0 10-May-2018
AAF 0 20-May-2018
AAF 30 20-Jun-2018
AAF 0 20-Jul-2018
AAF 100 20-Jul-2018
I am basically trying to calculate the days spent at each stage.. I am currently taking the minimum date within each stage, and find the difference between the minimum date of the next stage:
select
key,
stage,
cast(extract (day from max(next_dt) - min(createddate)) as number) as interval_days
from
(
select
key,
stage,
createddate
lead(createddate,1) over (partition by key order by createddate) next_dt
from oppstages
)
group by key,stage
As it can be seen, sometimes, the stage progresses from 0-40, but again goes back to 0. So the above logic doesn't work correctly and I am seeing a necessity to group the 0-40 as one category, and anything after 40 as next category and so on (if the stage decreases and restarts with new lesser stage number). The below query gives me the point where probability goes down, but I am not able flag to group the rows further.
select key,
stage,
createddate,
next_dt,
next_prob,
case when next_prob < stage then 1 else 0 end as valid_flag,
from
(
select
key,
stage,
createddate,
lead(createddate,1) over (partition by key order by createddate) next_dt,
coalesce(lead(stage,1) over (partition by key order by createddate),101) next_prob,
from oppstages
) a
I expect this output so that I could group using flag to calculate the days spent at each instance:
Key Stage CreateDate Flag
AAF 0 01-Jan-2018 1
AAF 0 02-Jan-2018 1
AAF 0 10-Jan-2018 1
AAF 20 20-Jan-2018 1
AAF 40 20-Mar-2018 1
AAF 0 01-May-2018 2
AAF 0 10-May-2018 2
AAF 0 20-May-2018 2
AAF 30 20-Jun-2018 2
AAF 10 20-Jul-2018 3
AAF 100 20-Jul-2018 3
thanks.
You can try to use lag
window function get the Stage
previous value.
Then use CASE WHEN
check PREVAL > STAGE
do increase 1
.
CREATE TABLE T(
Key varchar(50),
Stage int,
CreateDate date
);
INSERT INTO T VALUES ('AAF',0,TO_DATE('01-01-2018','dd-mm-yyyy'));
INSERT INTO T VALUES ('AAF',0,TO_DATE('02-01-2018','dd-mm-yyyy'));
INSERT INTO T VALUES ('AAF',0,TO_DATE('10-01-2018','dd-mm-yyyy'));
INSERT INTO T VALUES ('AAF',20,TO_DATE('20-01-2018','dd-mm-yyyy'));
INSERT INTO T VALUES ('AAF',40,TO_DATE('20-03-2018','dd-mm-yyyy'));
INSERT INTO T VALUES ('AAF',0,TO_DATE('01-05-2018','dd-mm-yyyy'));
INSERT INTO T VALUES ('AAF',0,TO_DATE('10-05-2018','dd-mm-yyyy'));
INSERT INTO T VALUES ('AAF',0,TO_DATE('20-05-2018','dd-mm-yyyy'));
INSERT INTO T VALUES ('AAF',30,TO_DATE('20-06-2018','dd-mm-yyyy'));
INSERT INTO T VALUES ('AAF',10,TO_DATE('20-07-2018','dd-mm-yyyy'));
INSERT INTO T VALUES ('AAF',100,TO_DATE('20-07-2018','dd-mm-yyyy'));
Query 1:
SELECT t1.KEY,
t1.STAGE,
(SUM(CASE WHEN PREVAL > STAGE THEN 1 ELSE 0 END) over (partition by Key order by CreateDate) + 1) Flag
FROM (
SELECT T.*,lag(Stage) over (partition by Key order by CreateDate) preVAL
FROM T
)t1
| KEY | STAGE | FLAG |
|-----|-------|------|
| AAF | 0 | 1 |
| AAF | 0 | 1 |
| AAF | 0 | 1 |
| AAF | 20 | 1 |
| AAF | 40 | 1 |
| AAF | 0 | 2 |
| AAF | 0 | 2 |
| AAF | 0 | 2 |
| AAF | 30 | 2 |
| AAF | 10 | 3 |
| AAF | 100 | 3 |