GROUP BY consecutive dates delimited by gaps

aggregate, postgresql, sql, window-functions

Solution

create table t ("date" date, "value" int);
insert into t ("date", "value") values
    ('2011-10-31', 2),
    ('2011-11-01', 8),
    ('2011-11-02', 10),
    ('2012-09-13', 1),
    ('2012-09-14', 4),
    ('2012-09-15', 5),
    ('2012-09-16', 20),
    ('2012-10-30', 10);

Simpler and cheaper version:

select min("date"), max("date"), sum(value)
from (
    select
        "date", value,
        "date" - (dense_rank() over(order by "date"))::int g
    from t
) s
group by s.g
order by 1

My first try was more complex and expensive:

create temporary sequence s;
select min("date"), max("date"), sum(value)
from (
    select 
        "date", value, d,
        case 
            when lag("date", 1, null) over(order by s.d) is null and "date" is not null 
                then nextval('s')
            when lag("date", 1, null) over(order by s.d) is not null and "date" is not null 
                then lastval()
            else 0 
        end g
    from 
        t
        right join
        generate_series(
            (select min("date") from t)::date, 
            (select max("date") from t)::date + 1, 
            '1 day'
        ) s(d) on s.d::date = t."date"
) q
where g != 0
group by g
order by 1
;
drop sequence s;

The output:

    min     |    max     | sum 
------------+------------+-----
 2011-10-31 | 2011-11-02 |  20
 2012-09-13 | 2012-09-16 |  30
 2012-10-30 | 2012-10-30 |  10
(3 rows)

Problem

Assume you have (in Postgres 9.1 ) a table like this: ``` date | value ``` which have some gaps in it (I mean: not every possible date between min(date) and max(date) has it's row). My problem is how to aggregate this data so that each consistent group (without gaps) is treated separately, like this: ``` min_date | max_date | [some aggregate of "value" column] ``` Any ideas how to do it? I believe it is possible with window functions but after a while trying with `lag()` and `lead()` I'm a little stuck. For instance if the data are like this: ``` date | value ---------------+------- 2011-10-31 | 2 2011-11-01 | 8 2011-11-02 | 10 2012-09-13 | 1 2012-09-14 | 4 2012-09-15 | 5 2012-09-16 | 20 2012-10-30 | 10 ``` the output (for `sum` as the aggregate) would be: ``` min | max | sum -----------+------------+------- 2011-10-31 | 2011-11-02 | 20 2012-09-13 | 2012-09-16 | 30 2012-10-30 | 2012-10-30 | 10 ```

Original source

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