Question

i have a table of resumes – names, resume text, zipcode, firstname, lastname, longitude, latitude, zip … 500,000+ rows

i query it too ways:

by location, example:

1) SELECT * FROM resumes 
WHERE ((latitude BETWEEN 44.3523845787 AND 45.6809474213) 
AND (longitude BETWEEN -110.873064254 AND -108.993603746)) 
GROUP BY lastname,longitude 
LIMIT 0, 50 
by name

2) SELECT * from resumes 
   (MATCH(resume) AGAINST ('donald')) AS relevance 
    FROM resumes 
    WHERE (MATCH(resume) AGAINST ('donald')) 
    GROUP BY lastname,longitude 
    ORDER BY relevance DESC 
    LIMIT 0, 50

queries on this table are very slow at first, but same query afterwards is faster, i think it’s caching it …

how can i speed up these queries? thanks

Answer 1

1) SELECT * FROM resumes 
WHERE ((latitude BETWEEN 44.3523845787 AND 45.6809474213) 
AND (longitude BETWEEN -110.873064254 AND -108.993603746)) 
GROUP BY lastname,longitude 
LIMIT 0, 50 
by name

This one can make little use of btree indexes. At best, it would grab all locations that fit for the latitude, or the longitude, and investigate potential rows along the other dimension. What you want is for it to only investigate rows that fit in a smaller box.

For this, you need a spacial index.

2) SELECT * from resumes 
   (MATCH(resume) AGAINST ('donald')) AS relevance 
    FROM resumes 
    WHERE (MATCH(resume) AGAINST ('donald')) 
    GROUP BY lastname,longitude 
    ORDER BY relevance DESC 
    LIMIT 0, 50

Likewise, this also needs a special kind of index which is not btree — a full text index to be specific.