Merge Overlapping Intervals and Track Maximum Value in BigQuery SQL - sql

Question

I am trying to solve a problem where i want to merge overlapping intervals for a given column id, but i also want to track the maximum value for each overlapped interval. I have start_time and stop_time for each interval and each interval has a hierarchy/priority associated with it.
These are the following columns in the table:
id, start_time, stop_time, some_value
example input:
example output:

Answer 1

Below is for BigQuery Standard SQL and I assume you stll working on the same use-case as in previous question, so I wanted to keep it inline with that solution - and you can extend it for when you also want to account for priorities for example
So, anyway:
#standardSQL
WITH check_times AS (
SELECT id, start_time AS TIME FROM `project.dataset.table` UNION DISTINCT
SELECT id, stop_time AS TIME FROM `project.dataset.table`
), distinct_intervals AS (
SELECT id, TIME AS start_time, LEAD(TIME) OVER(PARTITION BY id ORDER BY TIME) stop_time
FROM check_times
), deduped_intervals AS (
SELECT a.id, a.start_time, a.stop_time, MAX(some_value) some_value
FROM distinct_intervals a
JOIN `project.dataset.table` b
ON a.id = b.id
AND a.start_time BETWEEN b.start_time AND b.stop_time
AND a.stop_time BETWEEN b.start_time AND b.stop_time
GROUP BY a.id, a.start_time, a.stop_time
), combined_intervals AS (
SELECT id, MIN(start_time) start_time, MAX(stop_time) stop_time, MAX(some_value) some_value
FROM (
SELECT id, start_time, stop_time, some_value, COUNTIF(flag) OVER(PARTITION BY id ORDER BY start_time) grp
FROM (
SELECT id, start_time, stop_time, some_value,
start_time != IFNULL(LAG(stop_time) OVER(PARTITION BY id ORDER BY start_time), start_time) flag
FROM deduped_intervals
)
)
GROUP BY id, grp
)
SELECT *
FROM combined_intervals
-- ORDER BY id, start_time
If to apply to your sample data - result is
Row id start_time stop_time some_value
1 1 0 36 50
2 1 41 47 23
Is it possible to add one more column to the result which will show number of events during that time period
#standardSQL
WITH check_times AS (
SELECT id, start_time AS TIME FROM `project.dataset.table` UNION DISTINCT
SELECT id, stop_time AS TIME FROM `project.dataset.table`
), distinct_intervals AS (
SELECT id, TIME AS start_time, LEAD(TIME) OVER(PARTITION BY id ORDER BY TIME) stop_time
FROM check_times
), deduped_intervals AS (
SELECT a.id, a.start_time, a.stop_time, MAX(some_value) some_value, ANY_VALUE(To_JSON_STRING(b)) event_hash
FROM distinct_intervals a
JOIN `project.dataset.table` b
ON a.id = b.id
AND a.start_time BETWEEN b.start_time AND b.stop_time
AND a.stop_time BETWEEN b.start_time AND b.stop_time
GROUP BY a.id, a.start_time, a.stop_time
), combined_intervals AS (
SELECT id, MIN(start_time) start_time, MAX(stop_time) stop_time, MAX(some_value) some_value, COUNT(DISTINCT event_hash) events
FROM (
SELECT *, COUNTIF(flag) OVER(PARTITION BY id ORDER BY start_time) grp
FROM (
SELECT *,
start_time != IFNULL(LAG(stop_time) OVER(PARTITION BY id ORDER BY start_time), start_time) flag
FROM deduped_intervals
)
)
GROUP BY id, grp
)
SELECT *
FROM combined_intervals
-- ORDER BY id, start_time
with result
Row id start_time stop_time some_value events
1 1 0 36 50 8
2 1 41 47 23 1

Answer 2

You can determine when a new grouping starts using a cumulative max(). Then a cumulative conditional count() to identify the groups . . . and finally aggregation:
select min(start_time), max(stop_time), max(some_value)
from (select t.*,
countif(prev_stop_time is null or prev_stop_time < start_time) over (partition by id order by start_time) as grp
from (select t.*,
max(stop_time) over (partition by id order by start_time rows between unbounded preceding and 1 preceding) as prev_stop_time
from t
) t
) t
group by item_id, grp;