Christopher Smith wrote:
>my mistakes, zips_max should be zips_300.>and>in my zip code table there are 120 million rows, example of the
records >are>>origin destination>===================>>90210 90222>90210 90234>90210
96753
1.try to create index on both fields on zips_300 - origin and destination
zips_300_ind(origin,destination)
2.if you have only unique pairs in zips_300, this query should noticable
speed up you example:
select userid from user_login UL join user_details_p UD using (userid) join user_match_details UM using
(userid) join zips_300 Z on (Z.destination=UM.zipcode and Z.origin='90210')
where UD.gender ='W' AND UD.seekgender ='M' AND UD.age between 18 and 50 and UMD.min_age <= 30 AND
UMD.max_age>= 30 AND UD.ethnictype = 'Caucasian (White)' AND strpos(UMD.ethnicity,'Asian') !=0 order by
user_login.last_logindesc;
Next step to speed up your query is answering such question:
- How many values do I get if I ask one question.
Example:
gender='W' - 50% rows
seekgender='M' - 50% rows
ethnictype='Caucasian (White)' - 5%
Start indexing your tables on smallest values - in this situation -
ethnictype. Consider using multi-column indexes.
Regards,
Tomasz Myrta
