Add missing data from previous month or year cumulatively - sql

Question

Say I have the following data:
select 1 id, 'A' name, '2007' year, '04' month, 5 sales from dual union all
select 2 id, 'A' name, '2007' year, '05' month, 2 sales from dual union all
select 3 id, 'B' name, '2008' year, '12' month, 3 sales from dual union all
select 4 id, 'B' name, '2009' year, '12' month, 56 sales from dual union all
select 5 id, 'C' name, '2009' year, '08' month, 89 sales from dual union all
select 13 id,'B' name, '2016' year, '01' month, 10 sales from dual union all
select 14 id,'A' name, '2016' year, '02' month, 8 sales from dual union all
select 15 id,'D' name, '2016' year, '03' month, 12 sales from dual union all
select 16 id,'E' name, '2016' year, '04' month, 34 sales from dual
I want to cumulatively add up all the sales across all years and their respective periods (months). The output should look like the following:
name year month sale opening bal closing bal
A 2007 04 5 0 5
A 2007 05 2 5 7
B 2008 12 3 12 15
A 2008 04 0 5 5 -- to be generated
A 2008 05 0 7 7 -- to be generated
B 2009 12 56 15 71
C 2009 08 89 71 160
A 2009 04 0 5 5 -- to be generated
A 2009 05 0 7 7 -- to be generated
B 2016 01 10 278 288
B 2016 12 0 71 71 -- to be generated
A 2016 02 8 288 296
A 2016 04 0 5 5 -- to be generated
A 2016 05 0 7 7 -- to be generated
D 2016 03 12 296 308
E 2016 04 34 308 342
C 2016 08 0 160 160 -- to be generated
The Opening balance is the closing balance of previous month, and if it goes into next year than the opening balance for next year is the closing balance of the previous year. It should be able to work like this for subsequent years. I've got this part working. However, I don't know how to get around ths missing in say 2009 that exists in 2008. For instance the key A,2008,04 and also A,2008,05 does not exist in 2009 and the code should be able to add it in 2009 like above. Same applies for other years and months.
I'm working on Oracle 12c.
Thanks in advance.

Answer 1

A variation on #boneists approach, starting with your sample data in a CTE:
with t as (
select 1 id, 'A' name, '2007' year, '04' month, 5 sales from dual union all
select 2 id, 'A' name, '2007' year, '05' month, 2 sales from dual union all
select 3 id, 'B' name, '2008' year, '12' month, 3 sales from dual union all
select 4 id, 'B' name, '2009' year, '12' month, 56 sales from dual union all
select 5 id, 'C' name, '2009' year, '08' month, 89 sales from dual union all
select 13 id,'B' name, '2016' year, '01' month, 10 sales from dual union all
select 14 id,'A' name, '2016' year, '02' month, 8 sales from dual union all
select 15 id,'D' name, '2016' year, '03' month, 12 sales from dual union all
select 16 id,'E' name, '2016' year, '04' month, 34 sales from dual
),
y (year, rnk) as (
select year, dense_rank() over (order by year)
from (select distinct year from t)
),
r (name, year, month, sales, rnk) as (
select t.name, t.year, t.month, t.sales, y.rnk
from t
join y on y.year = t.year
union all
select r.name, y.year, r.month, 0, y.rnk
from y
join r on r.rnk = y.rnk - 1
where not exists (
select 1 from t where t.year = y.year and t.month = r.month and t.name = r.name
)
)
select name, year, month, sales,
nvl(sum(sales) over (partition by name order by year, month
rows between unbounded preceding and 1 preceding), 0) as opening_bal,
nvl(sum(sales) over (partition by name order by year, month
rows between unbounded preceding and current row), 0) as closing_bal
from r
order by year, month, name;
Which gets the same result too, though it also doesn't match the expected results in the question:
NAME YEAR MONTH SALES OPENING_BAL CLOSING_BAL
---- ---- ----- ---------- ----------- -----------
A 2007 04 5 0 5
A 2007 05 2 5 7
A 2008 04 0 7 7
A 2008 05 0 7 7
B 2008 12 3 0 3
A 2009 04 0 7 7
A 2009 05 0 7 7
C 2009 08 89 0 89
B 2009 12 56 3 59
B 2016 01 10 59 69
A 2016 02 8 7 15
D 2016 03 12 0 12
A 2016 04 0 15 15
E 2016 04 34 0 34
A 2016 05 0 15 15
C 2016 08 0 89 89
B 2016 12 0 69 69
The y CTE (feel free to use more meaningful names!) generates all the distinct years from your original data, and also adds a ranking, so 2007 is 1, 2008 is 2, 2009 is 3, and 2016 is 4.
The r recursive CTE combines your actual data with dummy rows with zero sales, based on the name/month data from previous years.
From what that recursive CTE produces you can do your analytic cumulative sum to add the opening/closing balances. This is using windowing clauses to decide which sales values to include - essentially the opening and closing balances are the sum of all values up to this point, but opening doesn't include the current row.

Answer 2

This is the closest I can get to your result, although I realise it's not an exact match. For example, your opening balances don't look correct (where did the opening balance of 12 come from for the output row for id = 3?). Anyway, hopefully the following will enable you to amend as appropriate:
with sample_data as (select 1 id, 'A' name, '2007' year, '04' month, 5 sales from dual union all
select 2 id, 'A' name, '2007' year, '05' month, 2 sales from dual union all
select 3 id, 'B' name, '2008' year, '12' month, 3 sales from dual union all
select 4 id, 'B' name, '2009' year, '12' month, 56 sales from dual union all
select 5 id, 'C' name, '2009' year, '08' month, 89 sales from dual union all
select 13 id, 'B' name, '2016' year, '01' month, 10 sales from dual union all
select 14 id, 'A' name, '2016' year, '02' month, 8 sales from dual union all
select 15 id, 'D' name, '2016' year, '03' month, 12 sales from dual union all
select 16 id, 'E' name, '2016' year, '04' month, 34 sales from dual),
dts as (select distinct year
from sample_data),
res as (select sd.name,
dts.year,
sd.month,
nvl(sd.sales, 0) sales,
min(sd.year) over (partition by sd.name, sd.month) min_year_per_name_month,
sum(nvl(sd.sales, 0)) over (partition by name order by to_date(dts.year||'-'||sd.month, 'yyyy-mm')) - nvl(sd.sales, 0) as opening,
sum(nvl(sd.sales, 0)) over (partition by name order by to_date(dts.year||'-'||sd.month, 'yyyy-mm')) as closing
from dts
left outer join sample_data sd partition by (sd.name, sd.month) on (sd.year = dts.year))
select name,
year,
month,
sales,
opening,
closing
from res
where (opening != 0 or closing != 0)
and year >= min_year_per_name_month
order by to_date(year||'-'||month, 'yyyy-mm'),
name;
NAME YEAR MONTH SALES OPENING CLOSING
---- ---- ----- ---------- ---------- ----------
A 2007 04 5 0 5
A 2007 05 2 5 7
A 2008 04 0 7 7
A 2008 05 0 7 7
B 2008 12 3 0 3
A 2009 04 0 7 7
A 2009 05 0 7 7
C 2009 08 89 0 89
B 2009 12 56 3 59
B 2016 01 10 59 69
A 2016 02 8 7 15
D 2016 03 12 0 12
A 2016 04 0 15 15
E 2016 04 34 0 34
A 2016 05 0 15 15
C 2016 08 0 89 89
B 2016 12 0 69 69
I've used Partition Outer Join to link any month and name combination in the table (in my query, the sample_data subquery - you wouldn't need that subquery, you'd just use your table instead!) to any year in the same table, and then working out the opening / closing balances. I then discard any rows that have an opening and closing balance of 0.