First of all, a small note: you really should give some more information. I understand that you probably don't want to show some real columns of your business, but in the way that it becomes a lot more hard to understand what you want to.
But, I am going to give some tips on that subject. I hope that helps you, and whoever has a similar problem.
- You need to be clear what you define as overlaps. That could be a lot of different things to each person.
Look these events:
<--a-->
<---- b ---->
<---- c ---->
<-- d -->
<---- e ---->
<------- f -------->
<--- g --->
If you define overlaps like the google definition: extend over so as to cover partly, then "b","d","e" and "f" overlaps partly the "c" event. If you define overlaps like the full event of covering, then "c" overlaps "d", and "f" overlaps "b" and "c" and "d".
Deleting groups could be a problem. In that previous case, what we should do? Should we delete "b", "c" and "d" and keep just with "f"? Should we sum their values? Take the average maybe? So, this is a decision to be made, column by column. The meaning of each column is very important. So, I can't help you with "bar" and "baz".
So, trying to guess what you really want to, I am creating a similar table of events with id, begin, end and user_id
create table events (
id integer,
user_id integer,
start_time timestamp,
end_time timestamp,
name varchar(100)
);
I am adding the example values
insert into events
( id, user_id, start_time, end_time, name ) values
( 1, 1000, timestamp('2017-10-09 01:00:00'),timestamp('2017-10-09 04:00:00'), 'a' );
insert into events
( id, user_id, start_time, end_time, name ) values
( 2, 1000, timestamp('2017-10-09 03:00:00'),timestamp('2017-10-09 15:00:00'), 'b' );
insert into events
( id, user_id, start_time, end_time, name ) values
( 3, 1000, timestamp('2017-10-09 07:00:00'),timestamp('2017-10-09 19:00:00'), 'c' );
insert into events
( id, user_id, start_time, end_time, name ) values
( 4, 1000, timestamp('2017-10-09 09:00:00'),timestamp('2017-10-09 17:00:00'), 'd' );
insert into events
( id, user_id, start_time, end_time, name ) values
( 5, 1000, timestamp('2017-10-09 17:00:00'),timestamp('2017-10-09 23:00:00'), 'e' );
insert into events
( id, user_id, start_time, end_time, name ) values
( 6, 1000, timestamp('2017-10-09 02:30:00'),timestamp('2017-10-09 22:00:00'), 'f' );
insert into events
( id, user_id, start_time, end_time, name ) values
( 7, 1000, timestamp('2017-10-09 17:30:00'),timestamp('2017-10-10 02:00:00'), 'g' );
Now, we can play with some nice queries:
List all the events that are full overlaps with another event:
select
# EVENT NAME
event_1.name as event_name,
# LIST EVENTS THAT THE EVENT OVERLAPS
GROUP_CONCAT(event_2.name) as overlaps_names
from events as event_1
inner join events as event_2
on
event_1.user_id = event_2.user_id
and
event_1.id != event_2.id
and
(
# START AFTER THE EVENT ONE
event_2.start_time >= event_1.start_time and
# ENDS BEFORE THE EVENT ONE
event_2.end_time <= event_1.end_time
)
group by
event_1.name
Result:
+------------+----------------+
| event_name | overlaps_names |
+------------+----------------+
| c | d |
| f | b,d,c |
+------------+----------------+
To detect the partial overlaps, you will need something like this:
select
# EVENT NAME
event_1.name as event_name,
# LIST EVENTS THAT THE EVENT OVERLAPS
GROUP_CONCAT(event_2.name) as overlaps_names
from events as event_1
inner join events as event_2
on
event_1.user_id = event_2.user_id
and
event_1.id != event_2.id
and
(
(
# START AFTER THE EVENT ONE
event_2.start_time >= event_1.start_time and
# ENDS BEFORE THE EVENT ONE
event_2.start_time <= event_1.end_time
) or
(
# START AFTER THE EVENT ONE
event_2.end_time >= event_1.start_time and
# ENDS BEFORE THE EVENT ONE
event_2.end_time <= event_1.end_time
)
)
group by
event_1.name
Result:
+------------+----------------+
| event_name | overlaps_names |
+------------+----------------+
| a | b,f |
| b | c,d,a |
| c | b,d,e,g |
| d | b,e |
| e | f,g,d,c |
| f | a,g,b,d,c,e |
| g | c,e,f |
+------------+----------------+
Of course, I am using a "group by" to make easier to read. That could be useful too if you want to sum or take the average of the overlaps data to update your parent data before the delete. Maybe that "group_concat" function does not exist into Postgres or have a different name. One "standard SQL" that you could test it is:
select
# EVENT NAME
event_1.name as event_name,
# LIST EVENTS THAT THE EVENT OVERLAPS
event_2.name as overlaps_name
from events as event_1
inner join events as event_2
on
event_1.user_id = event_2.user_id
and
event_1.id != event_2.id
and
(
# START AFTER THE EVENT ONE
event_2.start_time >= event_1.start_time and
# ENDS BEFORE THE EVENT ONE
event_2.end_time <= event_1.end_time
)
Result:
+------------+---------------+
| event_name | overlaps_name |
+------------+---------------+
| f | b |
| f | c |
| c | d |
| f | d |
+------------+---------------+
If you are going to try some math operations, keep in mind the risk of adding the value of the "c" and "d" data on "b" and adding their value again on "f", making the value of "f" wrong.
// should be
new f = old f + b + old c + d
new c = old c + b + d // unecessary if you are going to delete it
// very common mistake
new c = old c + b + d // unecessary but not wrong yet
new f = new c + b + d = ( old c + b + d ) + b + d // wrong!!
You can test all these queries and create your own into the same database online using this URL http://sqlfiddle.com/#!9/1d2455/19. But, keep in mind that it is Mysql, not Postgresql. But it is very good to test standard SQL.
