Re: Critical performance problems on large databases

On Wed, 10 Apr 2002, Gunther Schadow wrote:

> Off the bat, this indicates to me that there is something
> sub-obtimal about PostgreSQL handling simple queries. From
> a database that should perform well in online user transactions
> one would want the query processing to be streamed as much
> as possible, i.e., since in a SELECT * FROM Bigtable; there is
> no work needed other than to retrieve the tuples out of
> physical storage, the response should be immediate and resource
> usage low. There should not be large buffer allocations.
>
> Conversely it looks as if PostgreSQL will always read a sizeable
> piece (if not all?) of the result set into some buffer area before
> returning a single row. This would explain the slow startup on
> the SELECT * FROM Bigtable; query as well as the fact that
> COUNT(smallcolumn) behaves much faster than COUNT(*).

IIRC, the entire result set is sent across in the select
* from bigtable case, possibly to allow random access to
the result set?  Not sure really.

The usual way to deal with these cases is to use limit/offset
or a cursor to fetch pieces of the data as you want them (ie:
begin;
DECLARE foo CURSOR FOR SELECT * FROM Bigtable;
FETCH 100 from foo;
FETCH 100 from foo;
...
end;
)

> Again, count should be streamed as well such as to use no
> significant memory resources other than the counter. Apparently
> a COUNT(*) in postgres is executed as
>
> SELECT * FROM Bigtable INTO $somebuffer
> COUNT(tuples in $somebuffer)

I believe the thing that takes a long time here is that it has to do a
sequential scan of Bigtable, which for large tables is rather time
consuming.  I generally haven't seen large growth of backends
on moderate sized tables for such queries, although due to the
sequential scan I try to avoid count() whenever possible.