Count values checking if consecutive - sql

Question

This is my table:
Event Order Timestamp
delFailed 281475031393706 2018-07-24T15:48:08.000Z
reopen 281475031393706 2018-07-24T15:54:36.000Z
reopen 281475031393706 2018-07-24T15:54:51.000Z
I need to count the number of event 'delFailed' and 'reopen' to calculate #delFailed - #reopen.
The difficulty is that there cannot be two same consecutives events, so that in this case the result will be "0" not "-1".
This is what i have achieved so far (Which is wrong because it gives me -1 instead of 0 due to the fact there are two consecutive "reopen" events )
with
events as (
select
event as events,
orders,
"timestamp"
from main_source_execevent
where orders = '281475031393706'
and event in ('reopen', 'delFailed')
order by "timestamp"
),
count_events as (
select
count(events) as CEvents,
events,
orders
from events
group by orders, events
)
select (
(select cevents from count_events where events = 'delFailed') - (select cevents from count_events where events = 'reopen')
) as nAttempts,
orders
from count_events
group by orders
How can i count once if there are two same consecutive events?

Answer 1

It is a gaps-and-islands problem, you can use make to row number to check rows are two same consecutive events
Explain
one row number created by normal.
another row number created by Event column
SELECT *
FROM (
SELECT *
,ROW_NUMBER() OVER(ORDER BY Timestamp) grp
,ROW_NUMBER() OVER(PARTITION BY Event ORDER BY Timestamp) rn
FROM T
) t1
| event | Order | timestamp | grp | rn |
|-----------|-----------------|----------------------|-----|----|
| delFailed | 281475031393706 | 2018-07-24T15:48:08Z | 1 | 1 |
| reopen | 281475031393706 | 2018-07-24T15:54:36Z | 2 | 1 |
| reopen | 281475031393706 | 2018-07-24T15:54:51Z | 3 | 2 |
when you create those two row you can get an upper result, then use grp - rn to get calculation the row are or are not same consecutive.
SELECT *,grp-rn
FROM (
SELECT *
,ROW_NUMBER() OVER(ORDER BY Timestamp) grp
,ROW_NUMBER() OVER(PARTITION BY Event ORDER BY Timestamp) rn
FROM T
) t1
| event | Order | timestamp | grp | rn | grp-rn |
|-----------|-----------------|----------------------|-----|----|----------|
| delFailed | 281475031393706 | 2018-07-24T15:48:08Z | 1 | 1 | 0 |
| reopen | 281475031393706 | 2018-07-24T15:54:36Z | 2 | 1 | 1 |
| reopen | 281475031393706 | 2018-07-24T15:54:51Z | 3 | 2 | 1 |
you can see when if there are two same consecutive events grp-rn column will be the same, so we can group by by grp-rn column and get count
Final query.
CREATE TABLE T(
Event VARCHAR(50),
"Order" VARCHAR(50),
Timestamp Timestamp
);
INSERT INTO T VALUES ('delFailed',281475031393706,'2018-07-24T15:48:08.000Z');
INSERT INTO T VALUES ('reopen',281475031393706,'2018-07-24T15:54:36.000Z');
INSERT INTO T VALUES ('reopen',281475031393706,'2018-07-24T15:54:51.000Z');
Query 1:
SELECT
SUM(CASE WHEN event = 'delFailed' THEN 1 END) -
SUM(CASE WHEN event = 'reopen' THEN 1 END) result
FROM (
SELECT Event,COUNT(distinct Event)
FROM (
SELECT *
,ROW_NUMBER() OVER(ORDER BY Timestamp) grp
,ROW_NUMBER() OVER(PARTITION BY Event ORDER BY Timestamp) rn
FROM T
) t1
group by grp - rn,Event
)t1
Results:
| result |
|--------|
| 0 |

Answer 2

I would just use lag() to get the first event in any sequence of similar values. Then do the calculation:
select sum( (event = 'reopen')::int ) as num_reopens,
sum( (event = 'delFailed')::int ) as num_delFailed
from (select mse.*,
lag(event) over (partition by orders order by "timestamp") as prev_event
from main_source_execevent mse
where orders = '281475031393706' and
event in ('reopen', 'delFailed')
) e
where prev_event <> event or prev_event is null;