Calc aggregates across continuous groups of values in Redshift - sql

Question

This is something that would probably be pretty easy to code a solution, but harder to accomplish in straight SQL. I may have to give up and code a routine that scans through the table.
I have a table of user status values with start and end dates that is like this:
create table #t (userid int4, status varchar(15), start_time date, end_time date);
insert into #t values
(1, 'Active', '2019-08-15', '2019-08-20'),
(1, 'Active', '2019-08-20', '2019-08-22'),
(1, 'Active', '2019-08-22', '2019-09-22'),
(1, 'Inactive', '2019-09-22', '2019-10-22'),
(1, 'At Risk', '2019-10-22', '2019-11-22'),
(1, 'Lapsed', '2019-11-22', '2019-12-08'),
(1, 'Active', '2019-12-08', '2019-12-18'),
(1, 'Active', '2019-12-18', '2020-01-11'),
(1, 'Active', '2020-01-11', '2020-01-15'),
(1, 'Active', '2020-01-15', '2020-02-15'),
(1, 'Inactive', '2020-02-15', '2020-03-15')
;
I'm trying to summarized to min/max dates for each continuous group of status values (when sorted by start_time), as shown below:
I've been trying to get there by using window functions in Redshift, but I cannot partition based on status as that seems to group the statuses together and I end up with "Active" from 2019-08-15 to 2020-02-15.

Answer 1

This is a so-called gaps-and-islands approach. Written on my phone so untested. But you should be able to search SO for that key-phrase.
WITH
sorted AS
(
SELECT
*,
ROW_NUMBER()
OVER (
PARTITION BY userid
ORDER BY start
)
AS row_userid_start,
ROW_NUMBER()
OVER (
PARTITION BY userid, status
ORDER BY start
)
AS row_userid_status_start
FROM
#t
)
SELECT
userid,
status,
MIN(start) AS start,
MAX(end) AS end
FROM
sorted
GROUP BY
userid,
status,
row_userid_status_start - row_userid_start