Re: quickly getting the top N rows

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On Thu, 4 Oct 2007, Tom Lane wrote:

You're being about as clear as mud here, except that you obviously lied
about what you were doing in your first message.  If you have a planner
problem, show us the *exact* query, the *exact* table definition, and
unfaked EXPLAIN ANALYZE output.

I didn't realize that simplification was viewed as so sinister, but thanks, I'll remember that in the future.

The table:
                         Table "public.log"
     Column     |            Type             |      Modifiers
----------------+-----------------------------+---------------------
 clientkey      | character(30)               | not null
 premiseskey    | character(30)               | not null
 logkey         | character(30)               | not null
 logicaldel     | character(1)                | default 'N'::bpchar
 lockey         | character(30)               |
 devlockey      | character(30)               |
 eventkey       | character(30)               |
 logshorttext   | character varying(255)      |
 logdesc        | character varying(255)      |
 loguserkey     | character(30)               |
 logassetkey    | character(30)               |
 logresourcekey | character(30)               |
 logtime        | timestamp without time zone |
 logip          | character varying(50)       |
 logarchived    | character(1)                |
 logarchivedate | timestamp without time zone |
 loghasvideo    | character(1)                |
 loghasaudio    | character(1)                |
 resvehiclekey  | character(30)               |
 synccreated    | character(1)                |
 logtypekey     | character(30)               |
Indexes:
    "log_pkey" PRIMARY KEY, btree (clientkey, premiseskey, logkey)
    "eventkey_idx" btree (eventkey),
    "log_ak1" btree (clientkey, premiseskey, logtime, logkey)


The original, slow query:

explain analyze SELECT * FROM log WHERE clientkey in ('000000004500000000010000000001') AND premiseskey in ('000000004500000000010000000001') and logicaldel = 'N'
ORDER BY logtime desc, logkey desc, clientkey desc, premiseskey desc LIMIT 20 offset 0;

QUERY PLAN
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------
 Limit  (cost=356402.58..356402.63 rows=20 width=563) (actual time=215858.481..215858.527 rows=20 loops=1)
   ->  Sort  (cost=356402.58..357598.25 rows=478267 width=563) (actual time=215858.478..215858.498 rows=20 loops=1)
         Sort Key: logtime, logkey, clientkey, premiseskey
         ->  Seq Scan on log  (cost=0.00..52061.67 rows=478267 width=563) (actual time=29.340..100043.313 rows=475669 loops=1)
               Filter: ((clientkey = '000000004500000000010000000001'::bpchar) AND (premiseskey = '000000004500000000010000000001'::bpchar) AND (logicaldel = 'N'::bpchar))
 Total runtime: 262462.582 ms
(6 rows)


Every row in log has identical clientkey and premiseskey values, so if I just remove those columns from the order by clause, I get this far superior plan:

explain analyze SELECT * FROM log WHERE clientkey in ('000000004500000000010000000001') AND premiseskey in
('000000004500000000010000000001') and logicaldel = 'N'
ORDER BY logtime desc, logkey desc LIMIT 20 offset 0;
                                                                QUERY PLAN
-------------------------------------------------------------------------------------------------------------------------------------------
 Limit  (cost=0.00..12.33 rows=20 width=563) (actual time=0.047..0.105 rows=20 loops=1)
   ->  Index Scan Backward using log_ak1 on log  (cost=0.00..294735.70 rows=478267 width=563) (actual time=0.044..0.076 rows=20 loops=1)
         Index Cond: ((clientkey = '000000004500000000010000000001'::bpchar) AND (premiseskey = '000000004500000000010000000001'::bpchar))
         Filter: (logicaldel = 'N'::bpchar)
 Total runtime: 0.165 ms
(5 rows)


...which made me to think that maybe postgres is not using log_ak1 in the former case because two of the columns in the order by match every row.

Unfortunately, in this case it's not an option to alter the query. I'm just trying to figure out an explaination.

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