Re: How to speed up a time dimension query

[Gaetano Mendola <mendola(at)bigfoot(dot)com>]

Hans de Bruin wrote:

> Hi there,
>
> I like to speed up my homepage and need to do something about a query. A 
> half to one second to get 24 records from a time dimension table a bit 
> long. This is the table:
>
> news2=> \d dim_time
> And here is the query which in my opinion take way to long:
>
> news2=> explain analyze select id,day,hour from dim_time
> news2-> where id between (now()-interval '25 hours')
> news2-> and (now()- interval '1 hour')
> news2-> order by id ;

This is not what I get with a table similiars to your:

test=# select count(*) from user_logs;
  count
---------
 3025880
(1 row)


empdb=# explain analyze
empdb-# select *
empdb-# from user_logs
empdb-# where login_time between (now()-interval '25 hours') and
empdb-#                          (now()-interval '1 hour')
empdb-# order by login_time;
                                                                 QUERY PLAN 

---------------------------------------------------------------------------------------------------------------------------------------------
 Index Scan using idx_user_logs_login_time on user_logs  (cost=0.00..502.67 rows=15130 width=47) 
(actual time=61.433..61.433 rows=0 loops=1)
   Index Cond: ((login_time >= (now() - '1 day 01:00:00'::interval)) AND (login_time <= (now() - 
'01:00:00'::interval)))
 Total runtime: 61.557 ms
(3 rows)

what do you obtain if you disable the sequential scan ?

do it in this way:
set enable_seqscan = off;

if you obtain a cost higher then what you get on your explain:
cost=590.26..590.44
and of course a lower Total runtime, then you have instruct your engine that
is better perform and index scan, you can accoplish this decreasing the
following values ( that values are what I use ).

cpu_index_tuple_cost = 0.0005
cpu_operator_cost    = 0.0025
cpu_tuple_cost       = 0.005


decreasing these value you decrease the cost for the index scans if the Total time
is higher you have to deal with the parameter effective_cache_size in order to
use more ram.


Regards
Gaetano Mendola