Re: Optimising "in" queries

array processing???

There are no arrays. What made you think there might be?

The table definition is:

benparts=# \d reading
Table "public.reading"
Column | Type |
Modifiers
-----------+-----------------------------+-----------------------------------------------------------
id | integer | not null default
nextval(('reading_seq'::text)::regclass)
sensor_id | integer |
rdate | timestamp without time zone |
rval | numeric(7,3) |
Indexes:
"reading_pkey" PRIMARY KEY, btree (id)
"unique_sensor_date" UNIQUE, btree (sensor_id, rdate)
"date" btree (rdate)
"reading_sensor" btree (sensor_id)
Foreign-key constraints:
"$1" FOREIGN KEY (sensor_id) REFERENCES sensor(id)

Cheers,
Stephen

On Wednesday 22 August 2007 20:28, Russell Smith wrote:
> Stephen Davies wrote:
> > I have a PostgreSQL 8.2.4 table with some seven million rows.
> >
> > The psql query:
> >
> > select count(rdate),rdate from reading where sensor_id in
> > (1137,1138,1139) group by rdate order by rdate desc limit 1;
> >
> > takes a few seconds but:
> >
> > select count(rdate),rdate from reading where sensor_id in
> > (1137,1138,1139,1140) group by rdate order by rdate desc limit 1;
>
> It would have been helpful to see the table definition here. I can
> say up front that array processing in postgres is SLOW.
>
> > (anything with four or more values in the "in" list) takes several
> > minutes.
> >
> > Is there any way to make the "larger" queries more efficient?
> >
> > Both rdate and sensor_id are indexed and the database is vacuumed
> > every night.
> >
> > The values in the "in" list are seldom as "neat" as in the above
> > examples. Actual values can range from 1 to about 2000. The number
> > of values ranges from 2 to about 10.
> >
> > Explain outputs are:
> >
> > benparts=# explain select count(rdate),rdate from reading where
> > sensor_id in (1137,1138,1139,1140) group by rdate order by rdate
> > desc limit 1;
> > QUERY PLAN
> > -------------------------------------------------------------------
> >-------------------------------- Limit (cost=0.00..39890.96 rows=1
> > width=8)
> > -> GroupAggregate (cost=0.00..7938300.21 rows=199 width=8)
> > -> Index Scan Backward using date on reading
> > (cost=0.00..7937884.59 rows=82625 width=8)
> > Filter: (sensor_id = ANY
> > ('{1137,1138,1139,1140}'::integer[]))
> > (4 rows)
>
> I'm unsure of how you produced a plan like this without the benefit
> of seeing the table definition.
>
> > benparts=# explain select count(rdate),rdate from reading where
> > sensor_id in (1137,1138,1139) group by rdate order by rdate desc
> > limit 1;
> > QUERY PLAN
> > -------------------------------------------------------------------
> >---------------------------------- Limit (cost=48364.32..48364.32
> > rows=1 width=8)
> > -> Sort (cost=48364.32..48364.49 rows=69 width=8)
> > Sort Key: rdate
> > -> HashAggregate (cost=48361.35..48362.21 rows=69
> > width=8) -> Bitmap Heap Scan on reading (cost=535.53..48218.10
> > rows=28650 width=8)
> > Recheck Cond: (sensor_id = ANY
> > ('{1137,1138,1139}'::integer[]))
> > -> Bitmap Index Scan on reading_sensor
> > (cost=0.00..528.37 rows=28650 width=0)
> > Index Cond: (sensor_id = ANY
> > ('{1137,1138,1139}'::integer[]))
> > (8 rows)
>
> As mentioned already, you need explain analyze.
>
> However I again will say that array processing is postgres is SLOW.
> It would strongly recommend redesigning your schema to use a table
> with sensor_id's that correspond to the primary key in the reading
> table.
>
> Rethinking the way you are going about this will probably be the most
> effective solution, but we will need more information if you are not
> comfortable doing that yourself.
>
> Regards
>
> Russell Smith

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