Count rows in partition with Order By

The "why" has already been explained by others. Sometimes you have an ordered window, and you have to do a count over the whole partition despite having an ORDER BY.

To do so, use an unbounded range with RANGE BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING

create table search_log
(
    id bigint not null primary key,
    query varchar(255) not null,
    stemmed_query varchar(255) not null,
    created timestamp not null,
);

SELECT query,
       created as seen_on,
       first_value(created) OVER query_window as last_seen,
       row_number() OVER query_window AS rn,
       count(*) OVER query_window AS occurence
FROM search_log l
     WINDOW query_window AS (PARTITION BY stemmed_query ORDER BY created DESC 
         RANGE BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING)

When you add an order by to an aggregate used as a window function that aggregate turns into a "running count" (or whatever aggregate you use).

The count(*) will return the number of rows up until the "current one" based on the order specified.

The following query shows the different results for aggregates used with an order by. With sum() instead of count() it's a bit easier to see (in my opinion).

with test (id, num, x) as (
  values 
    (1, 4, 1),
    (2, 4, 1),
    (3, 5, 2),
    (4, 6, 2)
)
select id, 
       num,
       x,
       count(*) over () as total_rows, 
       count(*) over (order by id) as rows_upto,
       count(*) over (partition by x order by id) as rows_per_x,
       sum(num) over (partition by x) as total_for_x,
       sum(num) over (order by id) as sum_upto,
       sum(num) over (partition by x order by id) as sum_for_x_upto
from test;

will result in:

id | num | x | total_rows | rows_upto | rows_per_x | total_for_x | sum_upto | sum_for_x_upto
---+-----+---+------------+-----------+------------+-------------+----------+---------------
 1 |   4 | 1 |          4 |         1 |          1 |           8 |        4 |              4
 2 |   4 | 1 |          4 |         2 |          2 |           8 |        8 |              8
 3 |   5 | 2 |          4 |         3 |          1 |          11 |       13 |              5
 4 |   6 | 2 |          4 |         4 |          2 |          11 |       19 |             11

There are more examples in the Postgres manual

Your two expressions are:

COUNT(id) OVER (PARTITION BY num)

COUNT(id) OVER (PARTITION BY num ORDER BY id)

Why would you expect these to return the same values? The syntax is different for a reason.

The first returns the overall count for each num -- essentially joining back the aggregated value.

The second does a cumulative count. It does the COUNT() for each row of id, for all values up to that ids value.

Note that such cumulative counts would normally be implemented using RANK() (or related functions). The cumulative count is subtly different from RANK(). The cumulative count implements:

COUNT(id) OVER (PARTITION BY num ORDER BY id RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW)

RANK() is slightly different. The difference only matters when the ORDER BY keys have ties.