Re: workaround for expensive KNN? - Mailing list pgsql-hackers

Hans,

what if you create index (price,title) ?


On Fri, 8 Apr 2011, PostgreSQL - Hans-J?rgen Sch?nig wrote:

> hello ...
>
> i got that one ...
>
>    "idx_product_t_product_titleprice" gist (to_tsvector('german'::regconfig, title), int_price)
>
> so, i have a combined index on text + number.
> to me the plan seems fine ... it looks like a prober KNN traversal.
> the difference between my plan and your plan seems to be the fact that i have, say, 1 mio rows which have "handy" or
soin it (1 mio out of 11 mio or so). you are moving out from one specific place.
 
>
> my maths is like that:
>     11 mio in total
>     1 mio matching "iphone"
>     cheapest / most expensive 10 out of this mio needed.
>
> operator classes are all nice and in place:
>
> SELECT 10 <-> 4 as distance;
> distance
> ----------
>        6
> (1 row)
>
> what does "buffers true" in your case say?
>
> many thanks,
>
>     hans
>
>
> On Apr 8, 2011, at 3:22 PM, Oleg Bartunov wrote:
>
>> Probably, you miss two-columnt index. From my early post:
>> http://www.sai.msu.su/~megera/wiki/knngist
>>
>> =# CREATE INDEX spots_idx ON spots USING knngist (coordinates, to_tsvector('french',address));
>> =# SELECT id, address,  (coordinates <-> '(2.29470491409302,48.858263472125)'::point) AS dist FROM spots WHERE
coordinates>< '(2.29470491409302,48.858263472125)'::point AND to_tsvector('french',address) @@
to_tsquery('french','mars') LIMIT 10;
 
>>   id    |                           address                           |         dist
---------+-------------------------------------------------------------+---------------------
>>  366096 | 1st Floor Tour Eiffel | Champs de Mars, Paris 75007, France | 2.32488941293945e-05
>> 4356328 | r Champ de Mars 75007 PARIS                                 |  0.00421854756964406
>> 5200167 | Champ De Mars 75007 Paris                                   |  0.00453564562587288
>> 9301676 | Champ de Mars, 75007 Paris,                                 |  0.00453564562587288
>> 2152213 | 16, ave Rapp, Champ de Mars, Tour Eiffel, Paris, France     |  0.00624152097590896
>> 1923818 | Champ de Mars Paris, France                                 |  0.00838214733539654
>> 5165953 | 39 Rue Champ De Mars Paris, France                          |  0.00874410234569529
>> 7395870 | 39 Rue Champ De Mars Paris, France                          |  0.00874410234569529
>> 4358671 | 32 Rue Champ De Mars Paris, France                          |  0.00876089659276339
>> 1923742 | 12 rue du Champ de Mars Paris, France                       |  0.00876764731845995
>> (10 rows)
>>
>> Time: 7.859 ms
>>
>> =# EXPLAIN (COSTS OFF) SELECT id, address FROM spots WHERE coordinates ><
'(2.29470491409302,48.858263472125)'::point
>> AND to_tsvector('french',address) @@ to_tsquery('french','mars')  LIMIT 10;
>>
>>                            QUERY PLAN
>>
--------------------------------------------------------------------------------------------------------------------------------------
>> Limit
>>   ->  Index Scan using spots_idx on spots
>>         Index Cond: ((coordinates >< '(2.29470491409302,48.858263472125)'::point) AND
(to_tsvector('french'::regconfig,address) @@ '''mar'''::tsquery))
 
>> (3 rows)
>>
>>
>> On Fri, 8 Apr 2011, PostgreSQL - Hans-J?rgen Sch?nig wrote:
>>
>>> hello all ...
>>>
>>> given oleg's posting before i also wanted to fire up some KNN related question.
>>> let us consider a simple example. i got some million lines and i want all rows matching a tsquery sorted by price.
>>> i did some tests:
>>>
>>> test=# explain (analyze true, buffers true, costs true) SELECT id FROM product.t_product WHERE
to_tsvector('german',title) @@ to_tsquery('german', 'iphone') ORDER BY int_price <-> 0 LIMIT 10;
 
>>>                                                                           QUERY PLAN
>>>
>>>
-----------------------------------------------------------------------------------------------------------------------------
>>> --------------------------------------
>>> Limit  (cost=0.00..41.11 rows=10 width=16) (actual time=36391.717..45542.590 rows=10 loops=1)
>>>  Buffers: shared hit=9 read=5004
>>>  ->  Index Scan using idx_product_t_product_titleprice on t_product  (cost=0.00..13251.91 rows=3224 width=16)
(actualtime=
 
>>> 36391.715..45542.573 rows=10 loops=1)
>>>        Index Cond: (to_tsvector('german'::regconfig, title) @@ '''iphon'''::tsquery)
>>>        Order By: (int_price <-> 0::bigint)
>>>        Buffers: shared hit=9 read=5004
>>> Total runtime: 45542.676 ms
>>> (7 rows)
>>>
>>> test=# explain (analyze true, buffers true, costs true) SELECT id FROM product.t_product WHERE
to_tsvector('german',title) @@ to_tsquery('german', 'handy') ORDER BY int_price <-> 0 LIMIT 10;
 
>>>                                                                           QUERY PLAN
>>>
>>>
-----------------------------------------------------------------------------------------------------------------------------
>>> -------------------------------------
>>> Limit  (cost=0.00..41.03 rows=10 width=16) (actual time=7243.526..10935.227 rows=10 loops=1)
>>>  Buffers: shared hit=3 read=2316
>>>  ->  Index Scan using idx_product_t_product_titleprice on t_product  (cost=0.00..29762.61 rows=7255 width=16)
(actualtime=
 
>>> 7243.524..10935.217 rows=10 loops=1)
>>>        Index Cond: (to_tsvector('german'::regconfig, title) @@ '''handy'''::tsquery)
>>>        Order By: (int_price <-> 0::bigint)
>>>        Buffers: shared hit=3 read=2316
>>> Total runtime: 10935.265 ms
>>> (7 rows)
>>>
>>> test=# explain (analyze true, buffers true, costs true) SELECT id FROM product.t_product WHERE
to_tsvector('german',title) @@ to_tsquery('german', 'handy') ORDER BY int_price <-> 0 LIMIT 1;
 
>>>                                                                        QUERY PLAN
>>>
>>>
-----------------------------------------------------------------------------------------------------------------------------
>>> -------------------------------
>>> Limit  (cost=0.00..4.10 rows=1 width=16) (actual time=28.527..28.528 rows=1 loops=1)
>>>  Buffers: shared hit=1 read=1577
>>>  ->  Index Scan using idx_product_t_product_titleprice on t_product  (cost=0.00..29762.61 rows=7255 width=16)
(actualtime=
 
>>> 28.525..28.525 rows=1 loops=1)
>>>        Index Cond: (to_tsvector('german'::regconfig, title) @@ '''handy'''::tsquery)
>>>        Order By: (int_price <-> 0::bigint)
>>>        Buffers: shared hit=1 read=1577
>>> Total runtime: 28.558 ms
>>> (7 rows)
>>>
>>>
>>> under any circumstances - there is no way to reduce the number of buffers needed for a query like that.
>>> if everything is cached this is still ok but as soon as you have to take a single block from disk you will die a
painfulrandom I/O death.
 
>>> is there any alternative which does not simply die when i try to achieve what i want?
>>>
>>> the use case is quite simple: all products with a certain word (10 cheapest or so).
>>>
>>> is there any alternative approach to this?
>>> i was putting some hope into KNN but it seems it needs too much random I/O :(.
>>>
>>>     many thanks,
>>>
>>>         hans
>>>
>>> --
>>> Cybertec Sch?nig & Sch?nig GmbH
>>> Gr?hrm?hlgasse 26
>>> A-2700 Wiener Neustadt, Austria
>>> Web: http://www.postgresql-support.de
>>>
>>>
>>>
>>
>>     Regards,
>>         Oleg
>> _____________________________________________________________
>> Oleg Bartunov, Research Scientist, Head of AstroNet (www.astronet.ru),
>> Sternberg Astronomical Institute, Moscow University, Russia
>> Internet: oleg@sai.msu.su, http://www.sai.msu.su/~megera/
>> phone: +007(495)939-16-83, +007(495)939-23-83
>>
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>
> --
> Cybertec Sch?nig & Sch?nig GmbH
> Gr?hrm?hlgasse 26
> A-2700 Wiener Neustadt, Austria
> Web: http://www.postgresql-support.de
>
    Regards,        Oleg
_____________________________________________________________
Oleg Bartunov, Research Scientist, Head of AstroNet (www.astronet.ru),
Sternberg Astronomical Institute, Moscow University, Russia
Internet: oleg@sai.msu.su, http://www.sai.msu.su/~megera/
phone: +007(495)939-16-83, +007(495)939-23-83