Group by bursts of occurences in TimescaleDB/PostgreSQL - sql

Question

this is my first question in stackoverflow, any advice on how to ask a well structured question will be welcomed.
So, I have a TimescaleDB database, which is time-series databases built over Postgres. It has most of its functionalities, so if any of you don't know about Timescale it won't be an issue.
I have a select statement which returns:
time | num_issues | actor_login
------------------------+------------+------------------
2015-11-10 01:00:00+01 | 2 | nifl
2015-12-10 01:00:00+01 | 1 | anandtrex
2016-01-09 01:00:00+01 | 1 | isaacrg
2016-02-08 01:00:00+01 | 1 | timbarclay
2016-06-07 02:00:00+02 | 1 | kcalmes
2016-07-07 02:00:00+02 | 1 | cassiozen
2016-08-06 02:00:00+02 | 13 | phae
2016-09-05 02:00:00+02 | 2 | phae
2016-10-05 02:00:00+02 | 13 | cassiozen
2016-11-04 01:00:00+01 | 6 | cassiozen
2016-12-04 01:00:00+01 | 4 | cassiozen
2017-01-03 01:00:00+01 | 5 | cassiozen
2017-02-02 01:00:00+01 | 8 | cassandraoid
2017-03-04 01:00:00+01 | 16 | erquhart
2017-04-03 02:00:00+02 | 3 | erquhart
2017-05-03 02:00:00+02 | 9 | erquhart
2017-06-02 02:00:00+02 | 5 | erquhart
2017-07-02 02:00:00+02 | 2 | greatwarlive
2017-08-01 02:00:00+02 | 8 | tech4him1
2017-08-31 02:00:00+02 | 7 | tech4him1
2017-09-30 02:00:00+02 | 17 | erquhart
2017-10-30 01:00:00+01 | 7 | erquhart
2017-11-29 01:00:00+01 | 12 | erquhart
2017-12-29 01:00:00+01 | 8 | tech4him1
2018-01-28 01:00:00+01 | 6 | ragasirtahk
And it follows. Basically it returns a username in a bucket of time, in this case 30 days.
The SQL query is:
SELECT DISTINCT ON(time_bucket('30 days', created_at))
time_bucket('30 days', created_at) as time,
count(id) as num_issues,
actor_login
FROM
issues_event
WHERE action = 'opened' AND repo_name='netlify/netlify-cms'
group by time, actor_login
order by time, num_issues DESC
My question is, how can i detect or group the rows which have equal actor_login and are consecutive.
For example, I would like to group the cassiozen from 2016-10-05 to 2017-01-03, but not with the other cassiozen of the column.
I have tried with auxiliar columns, with window functions such as LAG, but without a function or a do statement I don't think it is possible.
I also tried with functions but I can't find a way.
Any approach, idea or solution will be fully appreciated.
Edit: I show my desired output.
time | num_issues | actor_login | actor_group_id
------------------------+------------+------------------+----------------
2015-11-10 01:00:00+01 | 2 | nifl | 0
2015-12-10 01:00:00+01 | 1 | anandtrex | 1
2016-01-09 01:00:00+01 | 1 | isaacrg | 2
2016-02-08 01:00:00+01 | 1 | timbarclay | 3
2016-06-07 02:00:00+02 | 1 | kcalmes | 4
2016-07-07 02:00:00+02 | 1 | cassiozen | 5
2016-08-06 02:00:00+02 | 13 | phae | 6
2016-09-05 02:00:00+02 | 2 | phae | 6
2016-10-05 02:00:00+02 | 13 | cassiozen | 7
2016-11-04 01:00:00+01 | 6 | cassiozen | 7
2016-12-04 01:00:00+01 | 4 | cassiozen | 7
2017-01-03 01:00:00+01 | 5 | cassiozen | 7
2017-02-02 01:00:00+01 | 8 | cassandraoid | 12
2017-03-04 01:00:00+01 | 16 | erquhart | 13
2017-04-03 02:00:00+02 | 3 | erquhart | 13
2017-05-03 02:00:00+02 | 9 | erquhart | 13
2017-06-02 02:00:00+02 | 5 | erquhart | 13
2017-07-02 02:00:00+02 | 2 | greatwarlive | 17
2017-08-01 02:00:00+02 | 8 | tech4him1 | 18
2017-08-31 02:00:00+02 | 7 | tech4him1 | 18
2017-09-30 02:00:00+02 | 17 | erquhart | 16
2017-10-30 01:00:00+01 | 7 | erquhart | 16
2017-11-29 01:00:00+01 | 12 | erquhart | 16
2017-12-29 01:00:00+01 | 8 | tech4him1 | 21
2018-01-28 01:00:00+01 | 6 | ragasirtahk | 24
The solution of MatBaille is almost perfect.
I just wanted to group the consecutive actors like this so I could extract a bunch of metrics with other attributes of the table.

Answer 1

You could use a so-called "gaps-and-islands" approach
WITH
sorted AS
(
SELECT
*,
ROW_NUMBER() OVER ( ORDER BY time) AS rn,
ROW_NUMBER() OVER (PARTITION BY actor_login ORDER BY time) AS rn_actor
FROM
your_results
)
SELECT
*,
rn - rn_actor AS actor_group_id
FROM
sorted
Then the combination of (actor_login, actor_group_id) will group consecutive rows together.
db<>fiddle demo