Re: cube operations slower than geo_distance() on production server

Mark Stosberg <mark@summersault.com>

From: Mark Stosberg <mark@summersault.com>
To: pgsql-performance@postgresql.org
Date: 2007-02-12T16:11:19Z
Lists: pgsql-performance

Attachments

Merlin Moncure wrote:
> On 2/10/07, Mark Stosberg <mark@summersault.com> wrote:
>>
>> With the help of some of this list, I was able to successfully  set up
>> and benchmark a cube-based replacement for geo_distance() calculations.
>>
>> On a development box, the cube-based variations benchmarked consistently
>> running in about 1/3 of the time of the gel_distance() equivalents.
>>
>> After setting up the same columns and indexes on a production
>> database, it's a different story. All the cube operations show
>> themselves to be about the same as, or noticeably slower than, the same
>> operations done with geo_distance().
>>
>> I've stared at the EXPLAIN ANALYZE output as much I can to figure what's
>> gone. Could you help?
>>
>> Here's the plan on the production server, which seems too slow. Below
>> is the plan I get in
>> on the development server, which is much faster.
>>
>> I tried "set enable_nestloop = off", which did change the plan, but
>> the performance.
>>
>> The production DB has much more data in it, but I still expected
>> comparable results relative
>> to using geo_distance() calculations.
>
> any objection to posting the query (any maybe tables, keys, indexes, etc)?

Here the basic query I'm using:
SELECT
 -- 1609.344 is a constant for "meters per mile"
 cube_distance( (SELECT earth_coords from zipcodes WHERE zipcode =
'90210') , earth_coords)/1609.344
   AS RADIUS
   FROM pets
   -- "shelters_active" is a view where "shelter_state = 'active'"
   JOIN shelters_active as shelters USING (shelter_id)
   -- The zipcode fields here are varchars
   JOIN zipcodes ON (
        shelters.postal_code_for_joining = zipcodes.zipcode )
   -- search for just 'dogs'
   WHERE species_id = 1
       AND pet_state='available'
      AND earth_box(
        (SELECT earth_coords from zipcodes WHERE zipcode = '90210') ,
10*1609.344
      ) @ earth_coords
   ORDER BY RADIUS;

All the related columns are indexed:
   pets.species_id
   pets.shelter_id
   pets.pet_state

   shelters.shelter_id (pk)
   shelters.postal_code_for_joining
   shelters.active

   zipcodes.zipcode (pk)
   zipcodes.earth_coords

The pets table has about 300,000 rows, but only about 10% are
"available". It sees regular updates and is "vacuum analyzed" every
couple of hours now. the rest of the tables get "vacuum analyzed
nightly".  The shelters table is about 99% "shelter_state = active".
It's updated infrequently.

The zipcodes table has about 40,000 rows in it and doesn't change.

I tried a partial index on the pets table "WHERE pet_state =
'available'. I could see the index was used, but the performance was
unaffected.

The "EXPLAIN ANALYZE" output is attached, to try to avoid mail-client
wrapping. The query is running 10 times slower today than on Friday,
perhaps because of server load, or because we are at the end of a VACUUM
cycle.

Thanks for any help!

    Mark