Help optimizing a slow index scan

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explain analyze
select distinct eventmain.incidentid, eventmain.entrydate, eventgeo.long, eventgeo.lat, eventgeo.geox, eventgeo.geoy
from eventmain, eventgeo
where
   eventmain.incidentid = eventgeo.incidentid and
   ( long > -104.998027962962 and long < -104.985957781349 ) and
   ( lat > 39.7075542720006 and lat < 39.7186195832938 ) and
   eventmain.entrydate > '2006-1-1 00:00' and
   eventmain.entrydate <= '2006-3-17 00:00'
order by
   eventmain.entrydate;

QUERY PLAN
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Unique (cost=121313.81..121330.72 rows=451 width=178) (actual time=723719.761..723726.875 rows=1408 loops=1) -> Sort (cost=121313.81..121314.94 rows=451 width=178) (actual time=723719.755..723721.807 rows=1408 loops=1) Sort Key: eventmain.entrydate, eventmain.disposition, eventmain.incidentid, eventgeo.reportingarea, eventgeo.beatid, eventmain.finaltype, eventmain.casenumber, eventgeo.eventlocation, eventmain.insertdate, eventmain.priority, eventgeo.long, eventgeo.lat, eventgeo.geox, eventgeo.geoy -> Nested Loop (cost=0.00..121293.93 rows=451 width=178) (actual time=1916.230..723712.900 rows=1408 loops=1) -> Index Scan using eventgeo_lat_idx on eventgeo (cost=0.00..85488.05 rows=10149 width=76) (actual time=0.402..393376.129 rows=22937 loops=1) Index Cond: ((lat > 39.7075542720006::double precision) AND (lat < 39.7186195832938::double precision)) Filter: ((long > -104.998027962962::double precision) AND (long < -104.985957781349::double precision)) -> Index Scan using eventmain_incidentid_idx on eventmain (cost=0.00..3.52 rows=1 width=119) (actual time=14.384..14.392 rows=0 loops=22937) Index Cond: ((eventmain.incidentid)::text = ("outer".incidentid)::text) Filter: ((entrydate > '2006-01-01 00:00:00'::timestamp without time zone) AND (entrydate <= '2006-03-17 00:00:00'::timestamp without time zone))

Total runtime:  >>> 723729.238 ms(!) <<<



I'm trying to figure out why it's consuming so much time on the index scan for eventgeo_lat_idx. Also, I have an index on "long" that the planner does not appear to find helpful.

There are 3.3 million records in eventmain and eventgeo. The server has a reasonably fast RAID10 setup with 16x 15k RPM drives and 12GB of RAM ( 11GB listed as "cache" by vmstat ). Running version 8.0.2 on linux kernel 2.6.12.

I have just vacuum analyze'd both tables, rebuilt the eventgeo_lat_idx index and reran the query multiple times to see if caching helped ( it didn't help much ). The server seems to be fine utilizing other fields from this table but using "long" and "lat" seem to drag it down significantly.

Is it because there's such slight differences between the records, since they are all within a few hundredths of a degree from each other?

Thanks for your time and ideas.

-Dan


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