Wich hardware suits best for large full-text indexed databases

-----Original Message-----
From: Diogo Biazus [mailto:diogo@ikono.com.br]
Sent: Tuesday, March 30, 2004 1:55 PM
To: pgsql-general@postgresql.org
Subject: [GENERAL] Wich hardware suits best for large
full-text indexed databases

Hi folks,

I have a database using tsearch2 to index 300 000 documents.
I've already have optimized the queries, and the database is
vacuumed on
a daily basis.
The stat function tells me that my index has aprox. 460 000
unique words
(I'm using stemmer and a nice stopword list).
The problem is performance, some queries take more than 10 seconds to
execute, and I'm not sure if my bottleneck is memory or io.
The server is a Athlon XP 2000, HD ATA133, 1.5 GB RAM running
postgresql
7.4.3 over freebsd 5.0 with lots of shared buffers and sort_mem...

Does anyone has an idea of a more cost eficient solution?
How to get a better performance without having to invest some
astronomicaly high amount of money?

What does the EXPLAIN command say about the slowest queries?

Dann Corbit wrote:

What does the EXPLAIN command say about the slowest queries?

explain SELECT qrydocumentos.coddocumento, qrydocumentos.nomedocumento,
qrydocumentos.conteudo, qrydocumentos.tamanho, qrydocumentos.hora,
qrydocumentos.data, qrydocumentos.codfonte, qrydocumentos.nomefonte,
qrydocumentos.numeroimagens as "numeroImagens", qrydocumentos.subtitulo,
qrydocumentos.codtipodocumento, qrydocumentos.codformato, numeroacessos
AS acessos FROM qrydocumentos WHERE qrydocumentos.codgrupousuario = 1
AND (qrydocumentos.conteudo_stem_ix @@ to_tsquery('default_portuguese',
'brasil')) ORDER BY ajustadata(qrydocumentos.datapublicacao) DESC,
ajustahora(qrydocumentos.horapublicacao) DESC,
qrydocumentos.coddocumento DESC;

QUERY PLAN
---------------------------------------------------------------------------------------------------------------------------------------------------------------------
Sort (cost=1270.87..1271.60 rows=293 width=880)
Sort Key: ajustadata(documentos.datapublicacao),
ajustahora(documentos.horapublicacao), documentos.coddocumento
-> Hash Join (cost=1246.88..1258.87 rows=293 width=880)
Hash Cond: ("outer".codfonte = "inner".codfonte)
-> Merge Join (cost=1245.38..1252.25 rows=293 width=861)
Merge Cond: (("outer".codfonte = "inner".codfonte) AND
("outer".codtipodocumento = "inner".codtipodocumento))
-> Sort (cost=1195.00..1195.73 rows=291 width=845)
Sort Key: documentos.codfonte,
documentos.codtipodocumento
-> Index Scan using documentos_conteudo_stem_ix_ix
on documentos (cost=0.00..1183.08 rows=291 width=845)
Index Cond: (conteudo_stem_ix @@
'\'brasil\''::tsquery)
Filter: (conteudo_stem_ix @@
'\'brasil\''::tsquery)
-> Sort (cost=50.38..50.89 rows=204 width=16)
Sort Key: fontes_gruposusuario.codfonte,
tiposdocumento_gruposusuario.codtipodocumento
-> Merge Join (cost=0.00..42.57 rows=204 width=16)
Merge Cond: ("outer".codgrupousuario =
"inner".codgrupousuario)
-> Index Scan using
fontes_gruposusuario_codgrupousuario_ix on fontes_gruposusuario
(cost=0.00..24.75 rows=28 width=8)
Index Cond: (codgrupousuario = 1)
-> Index Scan using
tiposdocumento_gruposusuario_codgrupousuario_ix on
tiposdocumento_gruposusuario (cost=0.00..13.85 rows=542 width=8)
-> Hash (cost=1.40..1.40 rows=40 width=19)
-> Seq Scan on fontes (cost=0.00..1.40 rows=40 width=19)

--
Diogo Biazus
diogo@ikono.com.br
http://www.ikono.com.br

Can we see the schema for the table qrydocumentos ?

-----Original Message-----
From: Diogo Biazus [mailto:diogo@ikono.com.br]
Sent: Tuesday, March 30, 2004 2:32 PM
To: Dann Corbit
Cc: pgsql-general@postgresql.org
Subject: Re: [GENERAL] Wich hardware suits best for large full-text
indexed databases

Dann Corbit wrote:
What does the EXPLAIN command say about the slowest queries?

explain SELECT qrydocumentos.coddocumento, qrydocumentos.nomedocumento,
qrydocumentos.conteudo, qrydocumentos.tamanho, qrydocumentos.hora,
qrydocumentos.data, qrydocumentos.codfonte, qrydocumentos.nomefonte,
qrydocumentos.numeroimagens as "numeroImagens", qrydocumentos.subtitulo,
qrydocumentos.codtipodocumento, qrydocumentos.codformato, numeroacessos
AS acessos FROM qrydocumentos WHERE qrydocumentos.codgrupousuario = 1
AND (qrydocumentos.conteudo_stem_ix @@ to_tsquery('default_portuguese',
'brasil')) ORDER BY ajustadata(qrydocumentos.datapublicacao) DESC,
ajustahora(qrydocumentos.horapublicacao) DESC,
qrydocumentos.coddocumento DESC;

QUERY PLAN
------------------------------------------------------------------------
------------------------------------------------------------------------
---------------------
Sort (cost=1270.87..1271.60 rows=293 width=880)
Sort Key: ajustadata(documentos.datapublicacao),
ajustahora(documentos.horapublicacao), documentos.coddocumento
-> Hash Join (cost=1246.88..1258.87 rows=293 width=880)
Hash Cond: ("outer".codfonte = "inner".codfonte)
-> Merge Join (cost=1245.38..1252.25 rows=293 width=861)
Merge Cond: (("outer".codfonte = "inner".codfonte) AND
("outer".codtipodocumento = "inner".codtipodocumento))
-> Sort (cost=1195.00..1195.73 rows=291 width=845)
Sort Key: documentos.codfonte,
documentos.codtipodocumento
-> Index Scan using documentos_conteudo_stem_ix_ix
on documentos (cost=0.00..1183.08 rows=291 width=845)
Index Cond: (conteudo_stem_ix @@
'\'brasil\''::tsquery)
Filter: (conteudo_stem_ix @@
'\'brasil\''::tsquery)
-> Sort (cost=50.38..50.89 rows=204 width=16)
Sort Key: fontes_gruposusuario.codfonte,
tiposdocumento_gruposusuario.codtipodocumento
-> Merge Join (cost=0.00..42.57 rows=204
width=16)
Merge Cond: ("outer".codgrupousuario =
"inner".codgrupousuario)
-> Index Scan using
fontes_gruposusuario_codgrupousuario_ix on fontes_gruposusuario
(cost=0.00..24.75 rows=28 width=8)
Index Cond: (codgrupousuario = 1)
-> Index Scan using
tiposdocumento_gruposusuario_codgrupousuario_ix on
tiposdocumento_gruposusuario (cost=0.00..13.85 rows=542 width=8)
-> Hash (cost=1.40..1.40 rows=40 width=19)
-> Seq Scan on fontes (cost=0.00..1.40 rows=40
width=19)

--
Diogo Biazus
diogo@ikono.com.br
http://www.ikono.com.br

Diogo Biazus wrote:

Hi folks,

I have a database using tsearch2 to index 300 000 documents.
I've already have optimized the queries, and the database is vacuumed on
a daily basis.
The stat function tells me that my index has aprox. 460 000 unique words
(I'm using stemmer and a nice stopword list).
The problem is performance, some queries take more than 10 seconds to
execute, and I'm not sure if my bottleneck is memory or io.
The server is a Athlon XP 2000, HD ATA133, 1.5 GB RAM running postgresql
7.4.3 over freebsd 5.0 with lots of shared buffers and sort_mem...

Does anyone has an idea of a more cost eficient solution?
How to get a better performance without having to invest some
astronomicaly high amount of money?

This isn't hardware related, but FreeBSD 5 is not a particularly impressive
performer. Especially 5.0 ... 5.2.1 would be better, but if you're shooting
for performance, 4.9 will probably outperform both of them at this stage of
the game.

Something to consider if the query tuning that others are helping with doesn't
solve the problem. Follow through with that _first_ though.

However, if you insist on running 5, make sure your kernel is compiled without
WITNESS ... it speeds things up noticably.

--
Bill Moran
Potential Technologies
http://www.potentialtech.com

I have a database using tsearch2 to index 300 000 documents.
I've already have optimized the queries, and the database is vacuumed on

a daily basis.
The stat function tells me that my index has aprox. 460 000 unique words
(I'm using stemmer and a nice stopword list).
The problem is performance, some queries take more than 10 seconds to
execute, and I'm not sure if my bottleneck is memory or io.
The server is a Athlon XP 2000, HD ATA133, 1.5 GB RAM running postgresql
7.4.3 over freebsd 5.0 with lots of shared buffers and sort_mem...

Does anyone has an idea of a more cost eficient solution?
How to get a better performance without having to invest some
astronomicaly high amount of money?

Can you identify a bottleneck during the 10 sec? CPU at 100%, memory
swapping like crazy, HDD access non-stop?

I assume you're running cpu FSB & memory at 266. Moving to an Athlon 2600
or faster with faster synchronous memory (DDR333 or 400) should give at
least a 20% boost if cpu is an issue, 4Gb of RAM will be a boost if you
are swapping or using all the memory, make sure the HDD is a 7200RPM 8mb
cache model, or even adding a second drive & RAIDing them if HDD access is
the problem. The high performance WD Raptor drive on a suitable SATA
controller may give a boost, as would moving to a fast SCSI drive.

There are also a few hardware tweaks possible, if you are running your cpu
at FSB 266 and memory at 333, you MAY get better performance dropping
memory to 266, as the speed loss may be more than offset by the
gains due to having synchronous memory.

Run a benchmark (bonnie or hdparm) & see that the hard drive is performing
OK, you should be getting up around 40-50Mb/sec on a good ATA hard drive.

It all really depends where the bottleneck is....

Cheers,

Brent Wood

Look into running Swish-e instead:
http://www.swish-e.org

Great speed, nice engine, excellent boolean searches. We run it on
several sites each with over 500,000 documents. Performance is
consistently sub-second response time, and we also integrate it within
PHP, Perl and Postgresql too.

I know, it is nice to use tsearch2, but we also found the performance
lacking for those big indices. Maybe Oleg and the tsearch2 gang have
some extra tips?

- Ericson

Bill Moran wrote:

explain SELECT qrydocumentos.coddocumento, qrydocumentos.nomedocumento,
qrydocumentos.conteudo, qrydocumentos.tamanho, qrydocumentos.hora,
qrydocumentos.data, qrydocumentos.codfonte, qrydocumentos.nomefonte,
qrydocumentos.numeroimagens as "numeroImagens", qrydocumentos.subtitulo,
qrydocumentos.codtipodocumento, qrydocumentos.codformato, numeroacessos
AS acessos FROM qrydocumentos WHERE qrydocumentos.codgrupousuario = 1
AND (qrydocumentos.conteudo_stem_ix @@ to_tsquery('default_portuguese',
'brasil')) ORDER BY ajustadata(qrydocumentos.datapublicacao) DESC,
ajustahora(qrydocumentos.horapublicacao) DESC,
qrydocumentos.coddocumento DESC;

What is distribution of records by codgrupousuario field?
You can use multi-column index (with contrib/btree_gist):
create index fti on qrydocumentos using gist (codgrupousuario, conteudo_stem_ix);
or partial index
create index fti on qrydocumentos using gist (conteudo_stem_ix) where
codgrupousuario = 1;

One more. Let you use ispell dictionary ( I suppose, for Portuguese language,
http://fmg-www.cs.ucla.edu/geoff/ispell-dictionaries.html#Portuguese-dicts )

--
Teodor Sigaev E-mail: teodor@sigaev.ru

On Tue, 30 Mar 2004, Diogo Biazus wrote:

Hi folks,

I have a database using tsearch2 to index 300 000 documents.
I've already have optimized the queries, and the database is vacuumed on
a daily basis.
The stat function tells me that my index has aprox. 460 000 unique words
(I'm using stemmer and a nice stopword list).

460 000 unique words is a lot ! Have you seen on them ? Sometimes it's
very useful to analyze what did you indexed and do you want all of them.
I suggest you to use ispell dictionary and, if you index numbers
(look statistics), use special dictionaries for integer and decimal numbers
http://www.sai.msu.su/~megera/postgres/gist/tsearch/V2/dicts/README.intdict

The problem is performance, some queries take more than 10 seconds to
execute, and I'm not sure if my bottleneck is memory or io.
The server is a Athlon XP 2000, HD ATA133, 1.5 GB RAM running postgresql
7.4.3 over freebsd 5.0 with lots of shared buffers and sort_mem...

Does anyone has an idea of a more cost eficient solution?
How to get a better performance without having to invest some
astronomicaly high amount of money?

TIA,

Regards,
Oleg
_____________________________________________________________
Oleg Bartunov, sci.researcher, hostmaster of AstroNet,
Sternberg Astronomical Institute, Moscow University (Russia)
Internet: oleg@sai.msu.su, http://www.sai.msu.su/~megera/
phone: +007(095)939-16-83, +007(095)939-23-83

Diogo,

could you send us 'explain analyze' for fts-specific part of your
query ? For example,

www=# explain analyze select title from s_pages where to_tsquery('regression') @@ fts_index;
QUERY PLAN
-----------------------------------------------------------------------------------------------------------------------
Index Scan using s_gist_key on s_pages (cost=0.00..5.95 rows=1 width=29) (actual time=0.781..11.403 rows=62 loops=1)
Index Cond: ('\'regress\''::tsquery @@ fts_index)
Filter: ('\'regress\''::tsquery @@ fts_index)
Total runtime: 11.554 ms
(4 rows)

Frankly, I don't understand your query :) Could you explain what do you
want to find ?

qrydocumentos.conteudo_stem_ix @@ to_tsquery('default_portuguese', 'brasil')

Oleg

On Tue, 30 Mar 2004, Diogo Biazus wrote:

Dann Corbit wrote:

What does the EXPLAIN command say about the slowest queries?

explain SELECT qrydocumentos.coddocumento, qrydocumentos.nomedocumento,
qrydocumentos.conteudo, qrydocumentos.tamanho, qrydocumentos.hora,
qrydocumentos.data, qrydocumentos.codfonte, qrydocumentos.nomefonte,
qrydocumentos.numeroimagens as "numeroImagens", qrydocumentos.subtitulo,
qrydocumentos.codtipodocumento, qrydocumentos.codformato, numeroacessos
AS acessos FROM qrydocumentos WHERE qrydocumentos.codgrupousuario = 1
AND (qrydocumentos.conteudo_stem_ix @@ to_tsquery('default_portuguese',
'brasil')) ORDER BY ajustadata(qrydocumentos.datapublicacao) DESC,
ajustahora(qrydocumentos.horapublicacao) DESC,
qrydocumentos.coddocumento DESC;

QUERY PLAN
---------------------------------------------------------------------------------------------------------------------------------------------------------------------
Sort (cost=1270.87..1271.60 rows=293 width=880)
Sort Key: ajustadata(documentos.datapublicacao),
ajustahora(documentos.horapublicacao), documentos.coddocumento
-> Hash Join (cost=1246.88..1258.87 rows=293 width=880)
Hash Cond: ("outer".codfonte = "inner".codfonte)
-> Merge Join (cost=1245.38..1252.25 rows=293 width=861)
Merge Cond: (("outer".codfonte = "inner".codfonte) AND
("outer".codtipodocumento = "inner".codtipodocumento))
-> Sort (cost=1195.00..1195.73 rows=291 width=845)
Sort Key: documentos.codfonte,
documentos.codtipodocumento
-> Index Scan using documentos_conteudo_stem_ix_ix
on documentos (cost=0.00..1183.08 rows=291 width=845)
Index Cond: (conteudo_stem_ix @@
'\'brasil\''::tsquery)
Filter: (conteudo_stem_ix @@
'\'brasil\''::tsquery)
-> Sort (cost=50.38..50.89 rows=204 width=16)
Sort Key: fontes_gruposusuario.codfonte,
tiposdocumento_gruposusuario.codtipodocumento
-> Merge Join (cost=0.00..42.57 rows=204 width=16)
Merge Cond: ("outer".codgrupousuario =
"inner".codgrupousuario)
-> Index Scan using
fontes_gruposusuario_codgrupousuario_ix on fontes_gruposusuario
(cost=0.00..24.75 rows=28 width=8)
Index Cond: (codgrupousuario = 1)
-> Index Scan using
tiposdocumento_gruposusuario_codgrupousuario_ix on
tiposdocumento_gruposusuario (cost=0.00..13.85 rows=542 width=8)
-> Hash (cost=1.40..1.40 rows=40 width=19)
-> Seq Scan on fontes (cost=0.00..1.40 rows=40 width=19)

Regards,
Oleg
_____________________________________________________________
Oleg Bartunov, sci.researcher, hostmaster of AstroNet,
Sternberg Astronomical Institute, Moscow University (Russia)
Internet: oleg@sai.msu.su, http://www.sai.msu.su/~megera/
phone: +007(095)939-16-83, +007(095)939-23-83

On Wed, 31 Mar 2004, Ericson Smith wrote:

Look into running Swish-e instead:
http://www.swish-e.org

Great speed, nice engine, excellent boolean searches. We run it on
several sites each with over 500,000 documents. Performance is
consistently sub-second response time, and we also integrate it within
PHP, Perl and Postgresql too.

it's very different story ! There are hundreds *standalone* search engine
based on inverted indices, but you don't have *native* access to metadata
stored in database, so your search collection isn't consistent.
tsearch2 was developed specially for online update and consistency
(think about access control to documents). If you're not care about that
you don't need tsearch2. btw, tsearch2 scaled much better with long
queries.

I know, it is nice to use tsearch2, but we also found the performance
lacking for those big indices. Maybe Oleg and the tsearch2 gang have
some extra tips?

Not very much, most of them are written in documentation. Other tips are
general to databases, like use multi-key indices, use dictionaries, stop words,
check words statistics.

One interesting option we have - is standalone archive search based
on OpenFTS. The main idea is to have separate searches -
online search (fresh documents) and archive (static documents) search.
Online search is performed using as usual (tsearch2), while archive search
uses inverted indices ) like swish-e, google,...... The nice thing is that
results from both searches could be easily merged because they use the
same ranking function ! So, you may have online index for month's news and
archive part for older news and I bet you could manage millions documents.

- Ericson

Bill Moran wrote:

Diogo Biazus wrote:

Hi folks,

I have a database using tsearch2 to index 300 000 documents.
I've already have optimized the queries, and the database is vacuumed
on a daily basis.
The stat function tells me that my index has aprox. 460 000 unique
words (I'm using stemmer and a nice stopword list).
The problem is performance, some queries take more than 10 seconds to
execute, and I'm not sure if my bottleneck is memory or io.
The server is a Athlon XP 2000, HD ATA133, 1.5 GB RAM running
postgresql 7.4.3 over freebsd 5.0 with lots of shared buffers and
sort_mem...

Does anyone has an idea of a more cost eficient solution?
How to get a better performance without having to invest some
astronomicaly high amount of money?

This isn't hardware related, but FreeBSD 5 is not a particularly
impressive
performer. Especially 5.0 ... 5.2.1 would be better, but if you're
shooting
for performance, 4.9 will probably outperform both of them at this
stage of
the game.

Something to consider if the query tuning that others are helping with
doesn't
solve the problem. Follow through with that _first_ though.

However, if you insist on running 5, make sure your kernel is compiled
without
WITNESS ... it speeds things up noticably.

---------------------------(end of broadcast)---------------------------
TIP 6: Have you searched our list archives?

http://archives.postgresql.org

Regards,
Oleg
_____________________________________________________________
Oleg Bartunov, sci.researcher, hostmaster of AstroNet,
Sternberg Astronomical Institute, Moscow University (Russia)
Internet: oleg@sai.msu.su, http://www.sai.msu.su/~megera/
phone: +007(095)939-16-83, +007(095)939-23-83

Oleg Bartunov wrote:

it's very different story ! There are hundreds *standalone* search engine
based on inverted indices, but you don't have *native* access to metadata
stored in database, so your search collection isn't consistent.
tsearch2 was developed specially for online update and consistency
(think about access control to documents). If you're not care about that
you don't need tsearch2. btw, tsearch2 scaled much better with long
queries.

Actually swish-e has excellent support for metadata. This allows you to
nicely partition your indices, or to search only user-defined parts
based on as much custom meta-data as you'd care to define. Granted
tsearch2 allows you to have *live* updates to the index. But we usually
reindex nightly and that tends to be good enough for most cases.

- Ericson Smith

Dann Corbit wrote:

Can we see the schema for the table qrydocumentos ?

Sure:

CREATE OR REPLACE VIEW public.qrydocumentos AS

SELECT documentos.coddocumento, documentos.codfonte,
documentos.codsecao, documentos.codusuario, documentos.codposicaopagina,
documentos.codinterno, documentos.nomedocumento, documentos.subtitulo,
documentos.resumohumano, documentos.resumoautomatico,
documentos.conteudo, documentos.datapublicacao, documentos.localorigem,
documentos.horapublicacao, documentos.pagina, documentos.anoedicao,
documentos.numeroedicao_old, documentos.nomeautor,
documentos.datainsercao, documentos.url, documentos.codtipoinsercao,
documentos.codbusca, documentos.codtipodocumento, documentos.codformato,
documentos.analisado, documentos.numeroedicao,
documentos.conteudo_stem_ix, documentos.conteudo_ix,
documentos.numeroimagens, documentos.numeroacessos, fontes.nomefonte,
fontes.codtipofonte, fontes_gruposusuario.codgrupousuario,
character_length(documentos.conteudo ) AS tamanho,
to_char((documentos.horapublicacao )::interval, 'HH24:MI'::text ) AS
hora, to_char((documentos.datapublicacao )::timestamp with time zone,
'dd/mm/yyyy'::text ) AS data
FROM (((fontes_gruposusuario
JOIN tiposdocumento_gruposusuario ON
((tiposdocumento_gruposusuario.codgrupousuario =
fontes_gruposusuario.codgrupousuario )))
JOIN documentos ON (((documentos.codtipodocumento =
tiposdocumento_gruposusuario.codtipodocumento ) AND (documentos.codfonte
= fontes_gruposusuario.codfonte ))))
JOIN fontes ON ((fontes.codfonte = documentos.codfonte )));

--
Diogo Biazus
diogo@ikono.com.br
http://www.ikono.com.br

Bill Moran wrote:

Diogo Biazus wrote:

Hi folks,

I have a database using tsearch2 to index 300 000 documents.
I've already have optimized the queries, and the database is vacuumed
on a daily basis.
The stat function tells me that my index has aprox. 460 000 unique
words (I'm using stemmer and a nice stopword list).
The problem is performance, some queries take more than 10 seconds to
execute, and I'm not sure if my bottleneck is memory or io.
The server is a Athlon XP 2000, HD ATA133, 1.5 GB RAM running
postgresql 7.4.3 over freebsd 5.0 with lots of shared buffers and
sort_mem...

Does anyone has an idea of a more cost eficient solution?
How to get a better performance without having to invest some
astronomicaly high amount of money?

This isn't hardware related, but FreeBSD 5 is not a particularly
impressive
performer. Especially 5.0 ... 5.2.1 would be better, but if you're
shooting
for performance, 4.9 will probably outperform both of them at this
stage of
the game.

Something to consider if the query tuning that others are helping with
doesn't
solve the problem. Follow through with that _first_ though.

However, if you insist on running 5, make sure your kernel is compiled
without
WITNESS ... it speeds things up noticably.

Thanks for the advice, I'll try recompiling the kernel. Does the freebsd
version make a noticeable diference?

Regards,

--
Diogo Biazus
diogo@ikono.com.br
http://www.ikono.com.br

Teodor Sigaev wrote:

What is distribution of records by codgrupousuario field?

There are lots of documents in common between diferent user groups
(codgrupousuario = user group id), but each user groups can access a
subset of documents based on the types of document and data sources
(fontes) they are allowed to use.

You can use multi-column index (with contrib/btree_gist):
create index fti on qrydocumentos using gist (codgrupousuario,
conteudo_stem_ix);
or partial index
create index fti on qrydocumentos using gist (conteudo_stem_ix) where
codgrupousuario = 1;

I�d rather not create partial index (I would have to create a trigger
that creates an index each time a row is inserted on codgrupousuario).
But I'll try it to see how it performs.
The multi-column index seems a good idea.

One more. Let you use ispell dictionary ( I suppose, for Portuguese
language,
http://fmg-www.cs.ucla.edu/geoff/ispell-dictionaries.html#Portuguese-dicts
)

I'll make some tests with ispell, thanks for the advices.

My Regards,

--
Diogo Biazus
diogo@ikono.com.br
http://www.ikono.com.br

Oleg Bartunov wrote:

On Tue, 30 Mar 2004, Diogo Biazus wrote:

Hi folks,

I have a database using tsearch2 to index 300 000 documents.
I've already have optimized the queries, and the database is vacuumed on
a daily basis.
The stat function tells me that my index has aprox. 460 000 unique words
(I'm using stemmer and a nice stopword list).

460 000 unique words is a lot ! Have you seen on them ? Sometimes it's
very useful to analyze what did you indexed and do you want all of them.
I suggest you to use ispell dictionary and, if you index numbers
(look statistics), use special dictionaries for integer and decimal numbers
http://www.sai.msu.su/~megera/postgres/gist/tsearch/V2/dicts/README.intdict

I 'll try the ispell dictionaries and dicts for numbers too ;)
Could the synonym dictionary help me on this (reducing unique words)?

thanks,

--
Diogo Biazus
diogo@ikono.com.br
http://www.ikono.com.br

Oleg Bartunov wrote:

Diogo,

could you send us 'explain analyze' for fts-specific part of your
query ? For example,

Alright, here it goes:

eyeknow=# explain analyze select * from documentos where
conteudo_stem_ix @@ to_tsquery('default_portuguese', 'brasil');

QUERY PLAN
-----------------------------------------------------------------------------------------------------------------------------------------------------------
Index Scan using documentos_conteudo_stem_ix_ix on documentos
(cost=0.00..1183.08 rows=291 width=1156) (actual time=26.33..840039.40
rows=70686 loops=1)
Index Cond: (conteudo_stem_ix @@ '\'brasil\''::tsquery)
Filter: (conteudo_stem_ix @@ '\'brasil\''::tsquery)
Total runtime: 840248.91 msec
(4 rows)

Frankly, I don't understand your query :) Could you explain what do you
want to find ?

qrydocumentos.conteudo_stem_ix @@ to_tsquery('default_portuguese', 'brasil')

I'm trying to find documents which contain the word 'brasil' (stemmed).
This is just an example, because the user can input any query to the
database.
The rest of the query is used to make sure that the user is accessing
only documents he has permission to.

Regards,

--
Diogo Biazus
diogo@ikono.com.br
http://www.ikono.com.br

Can we see the underlying tables also?

Dann Corbit wrote:

Can we see the underlying tables also?

CREATE TABLE public.documentos
(
coddocumento serial NOT NULL,
codfonte int4 NOT NULL,
codsecao int4,
codusuario int4,
codposicaopagina int4,
codinterno varchar(255),
nomedocumento text NOT NULL,
subtitulo text,
resumohumano text,
resumoautomatico text,
conteudo text,
datapublicacao date,
localorigem varchar(255),
horapublicacao time,
pagina varchar(5),
anoedicao varchar(5),
numeroedicao_old varchar(10),
nomeautor varchar(255),
datainsercao timestamp NOT NULL DEFAULT ('now'::text)::timestamp(6)
with time zone,
url text,
codtipoinsercao varchar(1) NOT NULL,
codbusca int4,
codtipodocumento int4 NOT NULL,
codformato int4 NOT NULL,
analisado bool NOT NULL DEFAULT false,
numeroedicao varchar(120),
conteudo_stem_ix public.tsvector,
conteudo_ix public.tsvector,
numeroimagens int4 DEFAULT 0,
numeroacessos int4 DEFAULT 0,
codtarefa int8,
md5arquivo varchar(32),
CONSTRAINT documentos_pkey PRIMARY KEY (coddocumento),
CONSTRAINT arquivos_documentos_fk FOREIGN KEY (md5arquivo) REFERENCES
public.arquivos (md5arquivo) ON UPDATE CASCADE ON DELETE CASCADE,
CONSTRAINT buscas_documentos FOREIGN KEY (codbusca) REFERENCES
public.buscas (codbusca) ON UPDATE CASCADE ON DELETE CASCADE,
CONSTRAINT fontes_documentos FOREIGN KEY (codfonte) REFERENCES
public.fontes (codfonte) ON UPDATE NO ACTION ON DELETE NO ACTION,
CONSTRAINT secoes_documentos FOREIGN KEY (codsecao) REFERENCES
public.secoes (codsecao) ON UPDATE NO ACTION ON DELETE NO ACTION,
CONSTRAINT tiposdocumento_documentos FOREIGN KEY (codtipodocumento)
REFERENCES public.tiposdocumento (codtipodocumento) ON UPDATE CASCADE ON
DELETE NO ACTION,
CONSTRAINT tiposinsercao_documentos FOREIGN KEY (codtipoinsercao)
REFERENCES public.tiposinsercao (codtipoinsercao) ON UPDATE NO ACTION ON
DELETE NO ACTION,
CONSTRAINT usuarios_documentos FOREIGN KEY (codusuario) REFERENCES
public.usuarios (codusuario) ON UPDATE NO ACTION ON DELETE NO ACTION
) WITH OIDS;

CREATE INDEX documentos_ajustaautor_ix
ON public.documentos
USING btree
(public.ajustaautor(nomeautor) text_ops);

CREATE INDEX documentos_ajustadata_ix
ON public.documentos
USING btree
(public.ajustadata(datapublicacao) date_ops);

CREATE INDEX documentos_ajustahora_ix
ON public.documentos
USING btree
(public.ajustahora(horapublicacao) time_ops);

CREATE INDEX documentos_codtipodocumento_ix
ON public.documentos
USING btree
(codtipodocumento);

CREATE UNIQUE INDEX documentos_codfonte_codinterno_ix
ON public.documentos
USING btree
(codinterno, codfonte);

CREATE INDEX documentos_codfonte_ix
ON public.documentos
USING btree
(codfonte);

CREATE INDEX documentos_codformato_ix
ON public.documentos
USING btree
(codformato);

CREATE INDEX documentos_conteudo_stem_ix_ix
ON public.documentos
USING gist
(conteudo_stem_ix);

CREATE INDEX documentos_conteudo_ix_ix
ON public.documentos
USING gist
(conteudo_ix);

CREATE TABLE public.fontes
(
codfonte serial NOT NULL,
codtipofonte int4 NOT NULL,
nomefonte varchar(50) NOT NULL,
ativo bool NOT NULL DEFAULT true,
periodicidade varchar(1),
codagente int4,
CONSTRAINT fontes_pkey PRIMARY KEY (codfonte),
CONSTRAINT tiposfonte_fontes FOREIGN KEY (codtipofonte) REFERENCES
public.tiposfonte (codtipofonte) ON UPDATE NO ACTION ON DELETE NO ACTION
) WITH OIDS;

CREATE INDEX fontes_codtipofonte_ix
ON public.fontes
USING btree
(codtipofonte);

CREATE INDEX fontes_nomefonte_ix
ON public.fontes
USING btree
(nomefonte);

CREATE TABLE public.fontes_gruposusuario
(
codfonte int4 NOT NULL,
codgrupousuario int4 NOT NULL,
CONSTRAINT fontes_gruposusuario_pkey PRIMARY KEY (codfonte,
codgrupousuario),
CONSTRAINT fontes_gruposusuario_codfonte_fk FOREIGN KEY (codfonte)
REFERENCES public.fontes (codfonte) ON UPDATE CASCADE ON DELETE CASCADE,
CONSTRAINT fontes_gruposusuario_codgrupousuario_fk FOREIGN KEY
(codgrupousuario) REFERENCES public.gruposusuario (codgrupousuario) ON
UPDATE CASCADE ON DELETE CASCADE
) WITH OIDS;

CREATE INDEX fontes_gruposusuario_codfonte_ix
ON public.fontes_gruposusuario
USING btree
(codfonte);

CREATE INDEX fontes_gruposusuario_codgrupousuario_ix
ON public.fontes_gruposusuario
USING btree
(codgrupousuario);

CREATE TABLE public.tiposdocumento_gruposusuario
(
codtipodocumento int4 NOT NULL,
codgrupousuario int4 NOT NULL,
CONSTRAINT tiposdocumento_gruposusuario_pkey PRIMARY KEY
(codtipodocumento, codgrupousuario),
CONSTRAINT tiposdocumento_gruposusuario_codtipodocumento_fk FOREIGN
KEY (codtipodocumento) REFERENCES public.tiposdocumento
(codtipodocumento) ON UPDATE CASCADE ON DELETE CASCADE,
CONSTRAINT tiposdocumentos_gruposusuario_codgrupousuario_fk FOREIGN
KEY (codgrupousuario) REFERENCES public.gruposusuario (codgrupousuario)
ON UPDATE CASCADE ON DELETE CASCADE
) WITHOUT OIDS;

CREATE INDEX tiposdocumento_gruposusuario_codgrupousuario_ix
ON public.tiposdocumento_gruposusuario
USING btree
(codgrupousuario);

CREATE INDEX tiposdocumento_gruposusuario_codtipodocumento_ix
ON public.tiposdocumento_gruposusuario
USING btree
(codtipodocumento);

--
Diogo Biazus
diogo@ikono.com.br
http://www.ikono.com.br

I see that only table documentos has a unique index. Is it really so
that none of the other tables has a key to uniquely identify a record?
Perhaps the others have a unique attribute but it was never declared
when forming the index?

I do not remember which version of PostgreSQL you are using, but there
is now a CLUSTER command. Now, I am speaking with my experience in
other database systems, and so perhaps the PostgreSQL group may find it
necessary to correct me. I have only recently began working with
PostgreSQL versions beyond 7.1.3 which had no cluster command (or at
least I was not aware of one). In other database systems, a clustered
index is incredibly valuable. In fact, a unique, clustered index is
always a silver bullet to marvelous performance. Perhaps some of the
experts can give measurements as to the effectiveness of clustering in
PostgreSQL. Here is the link for the cluster documentation:
http://www.postgresql.org/docs/current/static/sql-cluster.html

From the description, clustering is expensive and your tables are large.
So it should be an infrequent operation.