Tom Lane wrote:
Kouber Saparev <kouber@xxxxxxxxxxx> writes:
Now the planner believes there're 910 rows, which is a bit closer to the
real data:
swing=# select avg(length) from (select username, count(*) as length
from login_attempt group by username) as freq;
avg
----------------------
491.6087310427555479
(1 row)
Hmph, that's still not real good. Ideally it should be estimating
*less* than the average frequency, because the estimate is made after
excluding all the most-common-values, which evidently 'kouber' is not
one of. I suppose there's quite a large number of infrequently-seen
usernames and the ndistinct estimate is much less than reality? (Look
at the pg_stats row for this column.) It might be worth going all the
way to stats target 1000 for this column.
I altered the statistics for that column to 1000, so now the planner
assumes exactly 492 rows for the fore-mentioned query, which is indeed
the average. It never went *less* than that value, it was always higher,
i.e. for a statistics value of 600, it was 588, for 800, it became 540.
The current value of n_distinct (given statistics=1000) is:
db=# SELECT n_distinct FROM pg_stats WHERE tablename='login_attempt' AND
attname='username';
n_distinct
------------
5605
(1 row)
db=# SELECT COUNT(DISTINCT username) FROM login_attempt;
count
-------
23391
(1 row)
In fact, what is n_distinct standing for, apart the famous formula:
n*d / (n - f1 + f1*n/N)
;-)
Regards,
--
Kouber Saparev
http://kouber.saparev.com
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