I don't know exactly is it your case, but sometimes

SET enable_sort = off;

speeds up some queries by the factor of hundred. But in some cases this
command slows down operations, so I TEMPORARILY switch enable_sort on and
off for some queries. It affects the query plan greatly.

On 3/20/07, Alban Hertroys <[EMAIL PROTECTED]> wrote:

Tom Lane wrote:
> Alban Hertroys <[EMAIL PROTECTED]> writes:
>> It seems pretty obvious that the planner underestimates the cost of
>> nestloops here, is there some way to tweak this?
>
> The real problem is the factor-of-a-thousand underestimate of the size
> of this join:

Good observation, I missed that one. Thanks.

>>    ->  Nested Loop  (cost=0.00..281.74 rows=2 width=14) (actual time=
0.068..14.000 rows=1683 loops=1)
>>          ->  Index Scan using fewo_location_ancestry_full_idx on
fewo_location_ancestry ancestor  (cost=0.00..49.34 rows=9 width=4) (actual
time=0.024..0.172 rows=41 loops=1)
>>                Index Cond: ((ancestor_id = 309) AND (ancestor_type_id =
12) AND (child_type_id = 10))
>>          ->  Index Scan using
fewo_property_location_country_location_idx on fewo_property_location
property_location  (cost=0.00..25.80 rows=2 width=18) (actual time=
0.009..0.169 rows=41 loops=41)
>>                Index Cond: ((property_location.country_id = 300) AND
("outer".child_id = property_location.location_id))
>>                Filter: (property_state_id = 3)
>
> Have you got up-to-date ANALYZE stats for both of these tables?
> Maybe increasing the statistics targets for them would help.

Yes. This is as of this moment a mostly static development database that
has been vacuumed and analyzed quite recently.

> You may be kind of stuck because of the lack of cross-column statistics
> --- I suppose these columns are probably rather highly correlated ---
> but you should at least try pulling the levers you've got.
>
> One thought is that country_id is probably entirely determined by
> location_id, and possibly ancestor_type_id is determined by ancestor_id.

Actually property.location_id refers to cities, which is the deepest
level in the represented data. Country_id is the top level.

Ancestry id, type and child id, type are indeed closely related. I
changed their representation based on your suggestions.

> If so you should be leaving them out of the queries and indexes;
> they're not doing anything for you except fooling the planner about the
> net selectivity of the conditions.

I tried a few things, but it seems I am quite successful at fooling the
planner...

I changed the indices on our ancestry table to not combine id and type
on the same half of the join; which is something we're in fact never
interested in anyway. This seems to have helped some indeed.

I tried removing country_id from the equation, but I haven't had the
patience to wait for the explain analyzes to complete that way - they
take long.
I implemented it this way as an optimization; I decided to join
property_location with both period_type_property and
property_availability_month using (country_id, property_id) as FK.
That quickly narrows down the number of matching records in those
tables, which an index on property_id only somehow didn't accomplish.

The good news is that I get results under 1s without having to
explicitly sort my subquery results.
The bad news is that the estimated row counts are still quite a bit off.
I analyzed the DB just before generating the attached result.

--
Alban Hertroys
[EMAIL PROTECTED]

magproductions b.v.

T: ++31(0)534346874
F: ++31(0)534346876
M:
I: www.magproductions.nl
A: Postbus 416
   7500 AK Enschede

// Integrate Your World //

                                                                                
                                        QUERY
PLAN

----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Aggregate  (cost=6780.04..6780.42 rows=1 width=182) (actual time=
629.652..629.653 rows=1 loops=1)
   ->  Nested Loop  (cost=1053.78..6779.62 rows=1 width=182) (actual time=
160.662..595.059 rows=969 loops=1)
         ->  Hash Join  (cost=1053.78..6688.46 rows=21 width=186) (actual
time=160.493..545.222 rows=3522 loops=1)
               Hash Cond: ("outer".property_id = "inner".property_id)
               ->  GroupAggregate  (cost=0.00..5581.97 rows=3500 width=12)
(actual time=0.159..363.108 rows=3522 loops=1)
                     ->  Index Scan using
fewo_property_availability_month_country_property_idx on
fewo_property_availability_month property_availability_month  (cost=
0.00..3893.52 rows=34992 width=12) (actual time=0.023..147.269 rows=37316
loops=1)
                           Index Cond: (300 = country_id)
               ->  Hash  (cost=1053.16..1053.16 rows=250 width=86) (actual
time=160.277..160.277 rows=3522 loops=1)
                     ->  Hash Join  (cost=825.03..1053.16 rows=250
width=86) (actual time=115.767..147.429 rows=3522 loops=1)
                           Hash Cond: ("outer".property_id =
"inner".property_id)
                           ->  HashAggregate  (cost=338.96..488.83rows=2141 
width=12) (actual time=
64.207..77.280 rows=3522 loops=1)
                                 ->  Bitmap Heap Scan on
fewo_period_type_property period_type_property  (cost=23.03..253.01rows=3438 
width=12) (actual time=
0.625..27.199 rows=3522 loops=1)
                                       Recheck Cond: (300 = country_id)
                                       ->  Bitmap Index Scan on
fewo_period_type_property_country_property_idx  (cost=0.00..23.03rows=3438 
width=0) (actual time=
0.605..0.605 rows=3522 loops=1)
                                             Index Cond: (300 =
country_id)
                           ->  Hash  (cost=473.87..473.87 rows=4881
width=18) (actual time=51.496..51.496 rows=4873 loops=1)
                                 ->  Bitmap Heap Scan on
fewo_property_location property_location  (cost=50.19..473.87 rows=4881
width=18) (actual time=0.974..24.530 rows=4873 loops=1)
                                       Recheck Cond: (country_id = 300)
                                       Filter: (property_state_id = 3)
                                       ->  Bitmap Index Scan on
fewo_property_location_country_property_idx  (cost=0.00..50.19 rows=4912
width=0) (actual time=0.939..0.939 rows=4873 loops=1)
                                             Index Cond: (country_id =
300)
         ->  Index Scan using fewo_location_ancestry_ancestor_child_idx on
fewo_location_ancestry ancestor  (cost=0.00..4.33 rows=1 width=4) (actual
time=0.007..0.008 rows=0 loops=3522)
               Index Cond: ((ancestor.ancestor_id = 309) AND (
ancestor.child_id = "outer".location_id))
Total runtime: 631.858 ms
(24 rows)



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