Tuning queries on large database

The result is that for "short queries" (Q1 and Q2) it runs in a few
seconds on both Oracle and PG. The difference becomes important with
Q3 : 8 seconds with oracle
80 sec with PG
and too much with Q4 : 28s with oracle
17m20s with PG !

Of course when I run 100 or 1000 parallel queries such as Q3 or Q4,
it becomes a disaster !
I can't understand these results. The way to execute queries is the
same I think. I've read recommended articles on the PG site.
I tried with a table containing 30 millions rows, results are similar.

I don't trust the Oracle #s. Lets look at Q4: returns 3 million rows.
Using your #s of 160 fields and 256 bytes, your are asking for a result
set of 160 * 256 * 3M = 12 GB! This data has to be gathered by the
disk, assembled, and sent over the network.

I don't know Oracle, but it probably has some 'smart' result set that
uses a cursor behind the scenes to do the fetching.

With a 3M row result set, you need to strongly consider using cursors.
Try experimenting with the same query (Q4), declared as a cursor, and
fetch the data in 10k blocks in a loop (fetch 10000), and watch the #s
fly.

Merlin

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i74D9IO19408

The result is that for "short queries" (Q1 and Q2) it runs in a few
seconds on both Oracle and PG. The difference becomes important with
Q3 : 8 seconds with oracle
80 sec with PG
and too much with Q4 : 28s with oracle
17m20s with PG !

Of course when I run 100 or 1000 parallel queries such as Q3 or Q4,
it becomes a disaster !
I can't understand these results. The way to execute queries is the
same I think. I've read recommended articles on the PG site.
I tried with a table containing 30 millions rows, results are similar.

I don't trust the Oracle #s. Lets look at Q4: returns 3 million rows.
Using your #s of 160 fields and 256 bytes, your are asking for a result
set of 160 * 256 * 3M = 12 GB! This data has to be gathered by the
disk, assembled, and sent over the network.

Yes, but queries such as Q3 or Q4 look like :

select 'Q3',sum(rr1),count(ff)
from data
where num_poste in (:p1,:p1 + 2)
;

select 'Q4',count(*)
from data
where t<td
and num_poste between :p1 and :p1 + 25
;

I need to declare a cursor also in this case (group functions) ?

I don't know Oracle, but it probably has some 'smart' result set that
uses a cursor behind the scenes to do the fetching.

With a 3M row result set, you need to strongly consider using cursors.
Try experimenting with the same query (Q4), declared as a cursor, and
fetch the data in 10k blocks in a loop (fetch 10000), and watch the #s
fly.

Merlin

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sort_mem = 50000

That is way, way too large. Try more like 5000 or lower.

num_poste | numeric(9,0) | not null

For starters numerics are really, really slow compared to integers. Why
aren't you using an integer for this field since youhave '0' decimal
places.

schema | relfilenode | table | index | reltuples | size
--------+-------------+------------------+------------+-------------+----------
public | 125615917 | data | | 1.25113e+08 | 72312040
public | 251139049 | data | i_data_dat | 1.25113e+08 | 2744400
public | 250870177 | data | pk_data | 1.25113e+08 | 4395480

My first remark is that the table takes a lot of place on disk, about
70 Gb, instead of 35 Gb with oracle.

Integers will take a lot less space than numerics.

The different queries of the bench are "simple" queries (no join,
sub-query, ...) and are using indexes (I "explained" each one to
be sure) :
Q1 select_court : access to about 700 rows : 1 "num_poste" and 1 month
(using PK : num_poste=p1 and dat between p2 and p3)
Q2 select_moy : access to about 7000 rows : 10 "num_poste" and 1 month
(using PK : num_poste between p1 and p1+10 and dat between p2 and p3)
Q3 select_long : about 250 000 rows : 2 "num_poste"
(using PK : num_poste in (p1,p1+2))
Q4 select_tres_long : about 3 millions rows : 25 "num_poste"
(using PK : num_poste between p1 and p1 + 25)

The result is that for "short queries" (Q1 and Q2) it runs in a few
seconds on both Oracle and PG. The difference becomes important with
Q3 : 8 seconds with oracle
80 sec with PG
and too much with Q4 : 28s with oracle
17m20s with PG !

Of course when I run 100 or 1000 parallel queries such as Q3 or Q4,
it becomes a disaster !

Please reply with the EXPLAIN ANALYZE output of these queries so we can
have some idea of how to help you.

Chris

On Wed, 2004-08-04 at 08:44, Valerie Schneider DSI/DEV wrote:

Hi,

I have some problem of performance on a PG database, and I don't
know how to improve. I Have two questions : one about the storage
of data, one about tuning queries. If possible !

My job is to compare Oracle and Postgres. All our operational databases
have been running under Oracle for about fifteen years. Now I try to replace
Oracle by Postgres.

You may assume some additional hardware may be required -- this would be
purchased out of the Oracle License budget :)

My first remark is that the table takes a lot of place on disk, about
70 Gb, instead of 35 Gb with oracle.
125 000 000 rows x 256 b = about 32 Gb. This calculation gives an idea
not so bad for oracle. What about for PG ? How data is stored ?

This is due to the datatype you've selected. PostgreSQL does not convert
NUMERIC into a more appropriate integer format behind the scenes, nor
will it use the faster routines for the math when it is an integer.
Currently it makes the assumption that if you've asked for numeric
rather than integer or float that you are dealing with either large
numbers or require high precision math.

Changing most of your columns to integer + Check constraint (where
necessary) will give you a large speed boost and reduce disk
requirements a little.

The different queries of the bench are "simple" queries (no join,
sub-query, ...) and are using indexes (I "explained" each one to
be sure) :

Care to send us the EXPLAIN ANALYZE output for each of the 4 queries
after you've improved the datatype selection?

--
Rod Taylor <rbt [at] rbt [dot] ca>

Build A Brighter Lamp :: Linux Apache {middleware} PostgreSQL
PGP Key: http://www.rbt.ca/signature.asc

Valerie Schneider DSI/DEV wrote:

Hi,

I have some problem of performance on a PG database, and I don't
know how to improve. I Have two questions : one about the storage
of data, one about tuning queries. If possible !

My job is to compare Oracle and Postgres. All our operational databases
have been running under Oracle for about fifteen years. Now I try to replace
Oracle by Postgres.

Show us the explain analyze on your queries.

Regards
Gaetano Mendola

not so bad for oracle. What about for PG ? How data is stored

I agree with the datatype issue. Smallint, bigint, integer... add a
constraint...

Also the way order of the records in the database is very important. As
you seem to have a very large static population in your table, you should
insert it, ordered by your favourite selection index (looks like it's
poste).

Also, you have a lot of static data which pollutes your table. Why not
create two tables, one for the current year, and one for all the past
years. Use a view to present a merged view.