cumulative using case statement in Oracle's SQL - sql

Question

I have a simple data
Date Count by english count by chinese
08-Mar-19 12 54
09-Mar-19 15 66
10-Mar-19 45 32
11-Mar-19 21 70
12-Mar-19 57 64
29-Mar-19 43 53
30-Mar-19 67 21
I want to group this data by week and the sum should be cumulative.The date starts from 8 march so the week should be calculated that way only. So the result should be
count by english count by chinese
08-MAR-19-14-MAR-19 150 286
15-MAR-19-22-MAR-19 150 286 (no data so same as above)
23-MAR-19-30-MAR-19 260 360
Tried using cumulative and sum but not able to achieve it

Answer 1

You can generate your week ranges, then use an outer join to see which data fits in each week, and use an analytic sum to get the result you want;
with week_ranges (date_from, date_to) as (
select min_date + ((level - 1) * 7), min_date + (level * 7)
from (
select min(some_date) as min_date, ceil((max(some_date) - min(some_date)) / 7) as weeks
from your_table
)
connect by level <= weeks
)
select distinct wr.date_from, wr.date_to - 1 as date_to,
sum(count_english) over (order by wr.date_from) as count_english,
sum(count_chinese) over (order by wr.date_from) as count_chinese
from week_ranges wr
left join your_table yt
on yt.some_date >= wr.date_from
and yt.some_date < wr.date_to
order by date_from;
which with your sample data gets:
DATE_FROM DATE_TO COUNT_ENGLISH COUNT_CHINESE
---------- ---------- ------------- -------------
2019-03-08 2019-03-14 150 286
2019-03-15 2019-03-21 150 286
2019-03-22 2019-03-28 150 286
2019-03-29 2019-04-04 260 360
Note this is splitting it up into four 7-days weeks, rather than one of 7 days and two of 8 days...
db<>fiddle

Answer 2

Here's one option; note that "my weeks" are different than yours because - your data is somewhat inconsistent as they vary from 6 to 7 days. That's also why the final result is different, but the general idea should be OK.
SQL> alter session set nls_date_format = 'dd.mm.yyyy';
Session altered.
SQL> with test (datum, cbe) as
2 -- sample data
3 (select date '2019-03-08', 12 from dual union all
4 select date '2019-03-09', 15 from dual union all
5 select date '2019-03-10', 45 from dual union all
6 select date '2019-03-11', 21 from dual union all
7 select date '2019-03-12', 57 from dual union all
8 select date '2019-03-29', 43 from dual union all
9 select date '2019-03-30', 67 from dual
10 ),
11 span as
12 -- min and max date value, so that we could create a "calendar"
13 (select min(datum) mindat,
14 max(datum) maxdat
15 from test
16 ),
17 periods as
18 -- "calendar" whose periods are weeks
19 (select s.mindat + (level - 1) * 7 datum_from,
20 (s.mindat + level * 7) - 1 datum_to
21 from span s
22 connect by level <= (s.maxdat - s.mindat) / 7 + 1
23 )
24 -- running sum per weeks
25 select distinct
26 p.datum_from,
27 p.datum_to,
28 sum(t.cbe) over (order by p.datum_from) sum_cbe
29 from test t full outer join periods p on t.datum between p.datum_from and p.datum_to
30 order by p.datum_from;
DATUM_FROM DATUM_TO SUM_CBE
---------- ---------- ----------
08.03.2019 14.03.2019 150
15.03.2019 21.03.2019 150
22.03.2019 28.03.2019 150
29.03.2019 04.04.2019 260
SQL>