aggregating log data - min/max time until another session, PostgreSQL

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drop table if exists my_log;
create table my_log(id int primary key, timestamp time, username text, job integer, action text);
insert into my_log values
(1, '7:00', 'bob', 22, 'did x'),
(2, '7:15', 'bob', 22, 'did q'),
(3, '7:30', 'joe', 22, 'did z'),
(4, '8:00', 'bob', 22, 'did y'),
(5, '8:10', 'bob', 56, 'did x'),
(6, '8:11', 'joe', 22, 'did a'),
(7, '8:12', 'bob', 56, 'did e'),
(8, '8:15', 'joe', 45, 'did u'),
(9, '8:24', 'bob', 22, 'BACK to do w'),
(10, '8:32', 'bob', 22, 'did p'),
(11, '8:45', 'joe', 45, 'did n'),
(12, '8:47', 'joe', 56, 'fixed bobs z');

-- find change points
        select 
            timestamp, username, job, 
            (job is distinct from lag(job) over w)::int as switch
        from my_log
        window w as (partition by username order by timestamp);

-- find series
    select timestamp, username, job, sum(switch) over w as series
    from (
        select 
            timestamp, username, job, 
            (job is distinct from lag(job) over w)::int as switch
        from my_log
        window w as (partition by username order by timestamp)
        ) s
    window w as (order by username, timestamp);

-- find min/max of series
select 
    min(timestamp) as start,
    max(timestamp) as stop,
    job, username
from (	
    select timestamp, username, job, sum(switch) over w as series
    from (
        select 
            timestamp, username, job, 
            (job is distinct from lag(job) over w)::int as switch
        from my_log
        window w as (partition by username order by timestamp)
        ) s
    window w as (order by username, timestamp)
    ) s
group by username, job, series
order by 1;


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