Hello,

First time posting here, but an avid reader. I am experiancing slow query times on my database (all tested locally thus far) and not sure how to go about it. The database itself has 44 tables and some of them tables have over 1 Million records (mainly the movies, actresses and actors tables). The table is made via JMDB using the flat files on IMDB. Also the SQL query that I am about to show is from that said program (that too experiances very slow search times). I have tried to include as much information as I can, such as the explain plan etc.

"QUERY PLAN"
"HashAggregate (cost=46492.52..46493.50 rows=98 width=46)"
" Output: public.movies.title, public.movies.movieid, public.movies.year"
" -> Append (cost=39094.17..46491.79 rows=98 width=46)"
" -> HashAggregate (cost=39094.17..39094.87 rows=70 width=46)"
" Output: public.movies.title, public.movies.movieid, public.movies.year"
" -> Seq Scan on movies (cost=0.00..39093.65 rows=70 width=46)"
" Output: public.movies.title, public.movies.movieid, public.movies.year"
" Filter: (((title)::text ~~* '%Babe%'::text) AND ((title)::text !~~* '""%}'::text))"
" -> Nested Loop (cost=0.00..7395.94 rows=28 width=46)"
" Output: public.movies.title, public.movies.movieid, public.movies.year"
" -> Seq Scan on akatitles (cost=0.00..7159.24 rows=28 width=4)"
" Output: akatitles.movieid, akatitles.language, akatitles.title, " Filter: (((title)::text ~~* '%Babe%'::text) AND ((title)::text !~~* '""%}'::text))"
" -> Index Scan using movies_pkey on movies (cost=0.00..8.44 rows=1 width=46)"
" Output: public.movies.movieid, public.movies.title, public.movies.year, public.movies.imdbid" " Index Cond: (public.movies.movieid = akatitles.movieid)"

SELECT * FROM ((SELECT DISTINCT title, movieid, year FROM movies WHERE title ILIKE '%Babe%' AND NOT (title ILIKE '"%}')) UNION (SELECT movies.title, movies.movieid, movies.year FROM movies INNER JOIN akatitles ON movies.movieid=akatitles.movieid WHERE akatitles.title ILIKE '%Babe%' AND NOT (akatitles.title ILIKE '"%}'))) AS union_tmp2;

Returns 612 Rows in 9078ms
Database backup (plain text) is 1.61GB

It's a really complex query and I am not fully cognizant on it, like I said it was spat out by JMDB. Do you have any suggestions on how I can increase the speed ?

Regards
Anthoni