group orders based on crossing date ranges - oracle

Question

I need to group order together with crossing their date ranges only
scenario A.
order 1, 1.3.2020-30.6.2020
order 2, 1.5.2020-31.8.2020
order 3, 31.7.2020-31.10.2020
order 4, 31.7.2020-31.12.2020
so the output should be
order 1, order 2
order 2, order 3, order 4
order1,3,4 are not grouped because their ranges don't cross at all
scenario B.
same as above plus another order
order 5, 1.1.2020-31.12.2020
so output will be
order 1, order 2, order 5
order 2, order 3, order 4, order 5
I tried Self Join to check which start date falls in that range.
so in the range of order 1 falls only the start date of order 2 -> we have one group
then in the range of order 2 fall both start dates of order 3 and 4 -> we have second group
but then for order 3 falls start date of order 4 and opposite -> that will give another 2 groups but they are invalid because order 2 is crossing their date ranges as well and shoul be included as well and becuase there will be 3 douplicates we should display it just once as in the desired output but this approach will fail.
Thanks

Answer 1

the result of MATCH_RECOGNIZE solution is incorrent because order 5 should be in both groups
I use some analitycal functions to solve this:
-- create table
Create table cross_dates (order_id number, start_date date , end_date date);
-- insert dates
insert into cross_dates values( 1, to_date('01.03.2020', 'dd.mm.yyyy'), to_date('30.06.2020', 'dd.mm.yyyy'));
insert into cross_dates values( 2, to_date('01.05.2020', 'dd.mm.yyyy'), to_date( '31.08.2020', 'dd.mm.yyyy'));
insert into cross_dates values( 3, to_date('31.07.2020', 'dd.mm.yyyy'), to_date( '31.08.2020', 'dd.mm.yyyy'));
insert into cross_dates values( 4, to_date('31.07.2020', 'dd.mm.yyyy'), to_date( '31.10.2020', 'dd.mm.yyyy'));
insert into cross_dates values( 5, to_date('01.01.2020', 'dd.mm.yyyy'), to_date( '31.12.2020', 'dd.mm.yyyy'));
-- SQL
select 'Order '|| min_order_id ||': ', listagg( order_id, ',') within group (order by order_id) list
from (
select distinct min_order_id, order_id from (
with dates (cur_date, end_date, order_id, start_date) as (
select start_date, end_date, order_id, start_date
from cross_Dates
union all
select cur_date + 1, end_date, order_id,start_date
from dates
where cur_date < end_date )
select d.order_id,
min(d.order_id) over(partition by greatest(d.start_date, cd.start_date)) min_order_id
from dates d, cross_Dates cd
where d.cur_date between cd.start_date and cd.end_date ))
group by min_order_id
having count(*) > 1;
Result:
Order 1: 1,2,5
Order 2: 2,3,4,5
-- add new column and update old records
alter table cross_dates add (item varchar2(1));
update cross_dates set item = 'A';
-- insert new records B
insert into cross_dates values( 1, to_date('01.01.2020', 'dd.mm.yyyy'), to_date( '30.06.2020', 'dd.mm.yyyy'), 'B');
insert into cross_dates values( 1, to_date('01.07.2020', 'dd.mm.yyyy'), to_date( '31.12.2020', 'dd.mm.yyyy'), 'B');
My assumption:
A and B are separate orders, not going in same groups even when crossing
order 1 B - has two records as a continuations - in my understanding counts like one order : order 1 B 01.01.2020 - 21.12.2020
If my assumption are correct the SQL could look like this:
select distinct min_order_id, order_id, item from (
with dates (cur_date, end_date, order_id, start_date, item) as (
select start_date, end_date, order_id, start_date, item
from cross_Dates
union all
select cur_date + 1, end_date, order_id,start_date, item
from dates
where cur_date < end_date )
select d.order_id, d.item,
min(d.order_id) over(partition by greatest(d.start_date, cd.start_date),d.item) min_order_id
from dates d, cross_Dates cd
where d.cur_date between cd.start_date and cd.end_date and d.item = cd.item )
order by item, min_order_id;
Result:
MIN_ORDER_ID ORDER_ID I
1 1 A
1 2 A
1 5 A
2 2 A
2 3 A
2 4 A
2 5 A
5 5 A
1 1 B
If my assumption are not ok please provide me what result should look like i this case.
:)

Answer 2

You can use MATCH_RECOGNIZE to find groups where the next value's start date is before, or equal to, the end date of all the previous values in the group. Then you can aggregate and exclude groups that would be entirely contained in another group:
WITH groups ( id, ids, start_date, end_date ) AS (
SELECT id,
LISTAGG( grp_id, ',' ) WITHIN GROUP ( ORDER BY start_date ),
MIN( start_date ),
MIN( end_date )
FROM (
SELECT t.id,
x.id AS grp_id,
x.start_date,
x.end_date
FROM table_name t
INNER JOIN table_name x
ON (
x.start_date >= t.start_date
AND x.start_date <= t.end_date
)
)
MATCH_RECOGNIZE (
PARTITION BY id
ORDER BY start_date
MEASURES
MATCH_NUMBER() AS mno
ALL ROWS PER MATCH
PATTERN ( FIRST_ROW GROUPED_ROWS* )
DEFINE GROUPED_ROWS AS (
GROUPED_ROWS.start_date <= MIN( end_date )
)
)
WHERE mno = 1
GROUP BY id
)
SELECT id,
ids
FROM groups g
WHERE NOT EXISTS (
SELECT 1
FROM groups x
WHERE g.ID <> x.ID
AND x.start_date <= g.start_date
AND g.end_date <= x.end_date
)
Which for the sample data:
CREATE TABLE table_name ( id, start_date, end_date ) AS
SELECT 'order 1', DATE '2020-03-01', DATE '2020-06-30' FROM DUAL UNION ALL
SELECT 'order 2', DATE '2020-05-01', DATE '2020-08-31' FROM DUAL UNION ALL
SELECT 'order 3', DATE '2020-07-31', DATE '2020-10-31' FROM DUAL UNION ALL
SELECT 'order 4', DATE '2020-07-31', DATE '2020-12-31' FROM DUAL;
Outputs:
ID | IDS
:------ | :----------------------
order 2 | order 2,order 3,order 4
order 1 | order 1,order 2
I you then:
INSERT INTO table_name ( id, start_date, end_date )
VALUES ( 'order 5', DATE '2020-01-01', DATE '2020-12-31' );
The output would be:
ID | IDS
:------ | :----------------------
order 2 | order 2,order 3,order 4
order 5 | order 5,order 1,order 2
db<>fiddle here