Re: [HACKERS] Real-life range datasets

2012-01-10 Thread Stefan Keller
Hi

I'm proposing OpenStreetMap which is of variable size up to 250 GB
XML Data for whole world.
It's downloadable from CloudMade.com or Geofabrik.de and can be
imported into PostgreSQL using osm2pgsql.
It's a key/value schema literally of the real world. I'm using hstore
option of osm2pgsql and hstore index is based on GIST.

I'm running a database instance called PostGIS Terminal which is a
daily extract of Switzerland:
http://labs.geometa.info/postgisterminal/?xapi=node%5Bname%3DHochschule%20Rapperswil%5D

This is a typical query which extracts 'real' highways (being of
geometry linestring, aka line/way) with a speed limit =  100 km/h:

SELECT ST_AsText(way) geom
FROM osm_line
WHERE tags @ 'highway=motorway'
AND coalesce(substring((tags-'maxspeed') FROM E'[0-9]+')::int,0) = 100

Yours, Stefan

2011/12/23 Alexander Korotkov aekorot...@gmail.com:
 Hello,

 On Thu, Dec 22, 2011 at 12:51 PM, Benedikt Grundmann
 bgrundm...@janestreet.com wrote:

 I should be able to give you a table with the same characteristics as
 the instruments table but bogus data by replacing all entries in the
 table with random strings of the same length or something like that.
 I can probably take a little bit of time during this or the next week
 to generate such fake real world data ;-)   Is there an ftp site to
 upload the gzipped pg_dump file to?


 Thank you very much for your response! I'm going to send you accessories for
 upload soon.

 -
 With best regards,
 Alexander Korotkov.

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Re: [HACKERS] Real-life range datasets

2011-12-23 Thread Alexander Korotkov
Hello,

On Thu, Dec 22, 2011 at 12:51 PM, Benedikt Grundmann 
bgrundm...@janestreet.com wrote:

 I should be able to give you a table with the same characteristics as
 the instruments table but bogus data by replacing all entries in the
 table with random strings of the same length or something like that.
 I can probably take a little bit of time during this or the next week
 to generate such fake real world data ;-)   Is there an ftp site to
 upload the gzipped pg_dump file to?


Thank you very much for your response! I'm going to send you accessories
for upload soon.

-
With best regards,
Alexander Korotkov.


Re: [HACKERS] Real-life range datasets

2011-12-22 Thread Benedikt Grundmann
Hello,

We have a table in a postgres 8.4 database that would make use of date
ranges and exclusion constraints if they were available.  Sadly I cannot
give you the data as it is based on data we are paying for and as part
of the relevant licenses we are obliqued to not give the data to third
parties.

Basically the tables keep meta data about financial instruments on
a given day.  Thanks to corporate actions (companies merging, splitting
up, etc...) that meta data can be different from one day to the next.

One way to model such a table is:

identifier, date, payload columns...


unique index on (date, identifier)

(and in fact some of the payload columns are unique per day indices
as well).

But because there are a large number of rows per day and most don't
change this is a very wasteful representation.

Instead we use this

identifier, effective_from, effective_until, payload columns...

And we have some clever plpgsql functions that merge a days snapshot
into that representation.  That happens only a few times per day and
is currently quite slow mostly because a lot of time is spend in 
validation triggers to check that there are no overlapping entries
for effective_from,effective_until for jane_symbol and a few other
identifiers.

The most common operations are: 

  Get all or most rows of a given day 

(select ... from instruments where :date between effective_from and 
effective_until)

left join of the instruments (again in the normal case constrained to
one day but in same cases periods of a week or a few month)

select ... from t left join instruments on 
  t.jane_symbol = instruments.jane_symbol
  t.date between instruments.effective_from and t.effective_until
  where t.date = X
and additional constraint on the number of rows from t

With t a huge table clustered on date with roughly 500,000 to 2,000,000 
entries per day.  The left join would work most of the time (my guess is
more than 90%).  But there are entries in t where the jane_symbol would
not be in instruments (sadly).

Current size (immediately after a cluster):

  table toast(all indices)   total 
| 1268 MB | 900 MB | 693 MB| 2861 MB

= select min(effective_from), max(effective_from) from instruments;
min |max 
+
 2011-05-30 | 2011-12-21
(1 row)

b= select count(*) from instruments where current_date - 1 between 
effective_from and effective_until ;
 count  

 358741
(1 row)

I should be able to give you a table with the same characteristics as
the instruments table but bogus data by replacing all entries in the
table with random strings of the same length or something like that.
I can probably take a little bit of time during this or the next week
to generate such fake real world data ;-)   Is there an ftp site to
upload the gzipped pg_dump file to?

Cheers,

Bene

On 20/12/11 16:48, Alexander Korotkov wrote:
 Hackers,
 
 For better GiST indexing of range types it's important to have real-life
 datasets for testing on. Real-life range datasets would help to proof (or
 reject) some concepts and get more realistic benchmarks. Also, it would be
 nice to know what queries you expect to run fast on that datasets. Ideally
 it should be real-life set of queries, but it also could be your
 presentation of what are typical queries  for such datasets.
 Thanks!
 
 -
 With best regards,
 Alexander Korotkov.

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Re: [HACKERS] Real-life range datasets

2011-12-22 Thread Oleg Bartunov

Bene,

we have pgfoundry project http://pgfoundry.org/projects/dbsamples/.
Since your sample database is very important (for me also), I suggest to use
this site.

Oleg
On Thu, 22 Dec 2011, Benedikt Grundmann wrote:


Hello,

We have a table in a postgres 8.4 database that would make use of date
ranges and exclusion constraints if they were available.  Sadly I cannot
give you the data as it is based on data we are paying for and as part
of the relevant licenses we are obliqued to not give the data to third
parties.

Basically the tables keep meta data about financial instruments on
a given day.  Thanks to corporate actions (companies merging, splitting
up, etc...) that meta data can be different from one day to the next.

One way to model such a table is:

identifier, date, payload columns...


unique index on (date, identifier)

(and in fact some of the payload columns are unique per day indices
as well).

But because there are a large number of rows per day and most don't
change this is a very wasteful representation.

Instead we use this

identifier, effective_from, effective_until, payload columns...

And we have some clever plpgsql functions that merge a days snapshot
into that representation.  That happens only a few times per day and
is currently quite slow mostly because a lot of time is spend in
validation triggers to check that there are no overlapping entries
for effective_from,effective_until for jane_symbol and a few other
identifiers.

The most common operations are:

 Get all or most rows of a given day

(select ... from instruments where :date between effective_from and 
effective_until)

left join of the instruments (again in the normal case constrained to
one day but in same cases periods of a week or a few month)

select ... from t left join instruments on
 t.jane_symbol = instruments.jane_symbol
 t.date between instruments.effective_from and t.effective_until
 where t.date = X
   and additional constraint on the number of rows from t

With t a huge table clustered on date with roughly 500,000 to 2,000,000
entries per day.  The left join would work most of the time (my guess is
more than 90%).  But there are entries in t where the jane_symbol would
not be in instruments (sadly).

Current size (immediately after a cluster):

 table toast(all indices)   total
| 1268 MB | 900 MB | 693 MB| 2861 MB

= select min(effective_from), max(effective_from) from instruments;
   min |max
+
2011-05-30 | 2011-12-21
(1 row)

b= select count(*) from instruments where current_date - 1 between 
effective_from and effective_until ;
count

358741
(1 row)

I should be able to give you a table with the same characteristics as
the instruments table but bogus data by replacing all entries in the
table with random strings of the same length or something like that.
I can probably take a little bit of time during this or the next week
to generate such fake real world data ;-)   Is there an ftp site to
upload the gzipped pg_dump file to?

Cheers,

Bene

On 20/12/11 16:48, Alexander Korotkov wrote:

Hackers,

For better GiST indexing of range types it's important to have real-life
datasets for testing on. Real-life range datasets would help to proof (or
reject) some concepts and get more realistic benchmarks. Also, it would be
nice to know what queries you expect to run fast on that datasets. Ideally
it should be real-life set of queries, but it also could be your
presentation of what are typical queries  for such datasets.
Thanks!

-
With best regards,
Alexander Korotkov.





Regards,
Oleg
_
Oleg Bartunov, Research Scientist, Head of AstroNet (www.astronet.ru),
Sternberg Astronomical Institute, Moscow University, Russia
Internet: o...@sai.msu.su, http://www.sai.msu.su/~megera/
phone: +007(495)939-16-83, +007(495)939-23-83

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Re: [HACKERS] Real-life range datasets

2011-12-22 Thread David E. Wheeler
On Dec 22, 2011, at 7:48 AM, Oleg Bartunov wrote:

 we have pgfoundry project http://pgfoundry.org/projects/dbsamples/.
 Since your sample database is very important (for me also), I suggest to use
 this site.

Or PGXN.

  http://pgxn.org/

You can register an account to upload extensions like you describe here:

  http://manager.pgxn.org/account/register

Details on what’s required to distribute on PGXN are here:

  http://manager.pgxn.org/howto

Best,

David


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[HACKERS] Real-life range datasets

2011-12-20 Thread Alexander Korotkov
Hackers,

For better GiST indexing of range types it's important to have real-life
datasets for testing on. Real-life range datasets would help to proof (or
reject) some concepts and get more realistic benchmarks. Also, it would be
nice to know what queries you expect to run fast on that datasets. Ideally
it should be real-life set of queries, but it also could be your
presentation of what are typical queries  for such datasets.
Thanks!

-
With best regards,
Alexander Korotkov.