Bigquery extracting sequences from timeseries data - sql

Question

I have a timeseries in BQ, with additional data, and based on some of the data I want to extract sequences from the timeseries for further processing.
The following demonstrates the source table:
with dataset as (
select
timestamp('2023-01-25 00:00:00') as last_seen, 1 as vehicle_id, 1 as mode, 0 as activity
union all select timestamp('2023-01-25 00:00:02'), 1, 1, 0
union all select timestamp('2023-01-25 00:00:04'), 1, 1, 0
union all select timestamp('2023-01-25 00:00:00'), 2, 1, 0
union all select timestamp('2023-01-25 00:00:02'), 2, 1, 0
union all select timestamp('2023-01-25 00:00:04'), 2, 1, 0
union all select timestamp('2023-01-25 00:00:06'), 1, 2, 1
union all select timestamp('2023-01-25 00:00:08'), 1, 2, 1
union all select timestamp('2023-01-25 00:00:10'), 1, 2, 1
union all select timestamp('2023-01-25 00:00:12'), 1, 1, 0
union all select timestamp('2023-01-25 00:00:14'), 1, 1, 0
union all select timestamp('2023-01-25 00:00:16'), 1, 1, 0
union all select timestamp('2023-01-25 00:00:12'), 2, 1, 1
union all select timestamp('2023-01-25 00:00:14'), 2, 1, 1
union all select timestamp('2023-01-25 00:00:17'), 2, 1, 1
)
What I want is to have a result that for every time the mode and/or activity changes for each vehicle_id which includes the start and end timestamps. Eg like this:
vehicle_id
mode
activity
start
end
1
1
0
2023-01-25 00:00:00
2023-01-25 00:00:04
1
2
1
2023-01-25 00:00:06
2023-01-25 00:00:10
1
1
0
2023-01-25 00:00:12
2023-01-25 00:00:16
2
1
0
2023-01-25 00:00:00
2023-01-25 00:00:04
2
1
1
2023-01-25 00:00:12
2023-01-25 00:00:17
I have tried:
select * from dataset where true
qualify ifnull(mode != lag(mode) over win or activity != lag(activity) over win or mode != lead(mode) over win or activity != lead(activity) over win, true)
window win as (partition by vehicle_id order by last_seen)
But that gives start and end on separate rows, so it feels like a dead end as it might cause issues if a sequence does not have an end.
Thanks

Answer 1

You might consider below.
SELECT vehicle_id,
ANY_VALUE(mode) mode, ANY_VALUE(activity) activity,
MIN(last_seen) AS start, MAX(last_seen) AS `end`
FROM (
SELECT *, COUNTIF(flag) OVER w1 AS part FROM (
SELECT *, mode <> LAG(mode) OVER w0 OR activity <> LAG(activity) OVER w0 AS flag
FROM dataset
WINDOW w0 AS (PARTITION BY vehicle_id ORDER BY last_seen)
) WINDOW w1 AS (PARTITION BY vehicle_id ORDER BY last_seen)
) GROUP BY vehicle_id, part;
Query results