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Bad performance with large objects: msg#00038

db.postgresql.odbc

Subject: Bad performance with large objects

Hi,

I'm using psqlodbc (latest from CVS) together with PostgreSQL 7.4.3 in
a project. In it, I have a table that uses large objects (type
"lo"). Functions for lo was imported from the contrib/lo-script.

The table looks like this:

timestamp | bigint | not null
jobid | bigint | not null
objectid | bigint | not null
class | integer | not null
field | character varying | not null
data | lo |

The idea is that each object consists of a number of fields with
corresponding lo-data. The program is responsible for putting together
the fields to full objects. There is also a timestamp, to be able to
have history of changes of objects.

To this, I have a statement that picks out the latest timestamp for
each field of each object:

SELECT objectid,class,field,data
FROM cjm_object t1
WHERE EXISTS (SELECT MAX(timestamp) FROM cjm_object
WHERE objectid=t1.objectid AND class=t1.class
AND field=t1.field
GROUP BY objectid,class,field
HAVING t1.timestamp=MAX(timestamp))
AND data IS NOT NULL
ORDER BY objectid,class,field;

So far so good, this works well. With about 2300 rows (about 2200
active, and 100 old changes), explain analyze in psql says that this
query takes about 300ms on my machine. I've also made a view that
picks out the lo-data as bytea (from pg_largeobject) instead, and this
takes about 700ms.

Now, when I run this query from my program through ODBC, using
SQLFetch (or SQLFetchScroll) to get the data, some 100 rows at a time,
it all takes about 6 seconds instead. I've tried to set different
rowset sizes, only use FETCH_NEXT, tried to optimize for sequential
fetching, but it won't get under at least 5 seconds for the whole
operation.

So, why does it take so much longer from ODBC, than from psql (even if
I pick out the bytea-data)? The program and postgresql both run on the
same machine, so there is no network delay. I've measured that it's
not my program that is slow, it's the ODBC calls.

I'm very thankful for any help to speed this up.


Greetings,

Tomas


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