On Mon, 31 Jan 2005 14:40:08 -0500, Tom Lane [EMAIL PROTECTED] wrote:
Manfred Koizar [EMAIL PROTECTED] writes:
That's not what I meant. I tried to say that if we have a GROUP BY
several columns and one of these columns alone has more than N/10
distinct values, there's no way to get less than
Manfred Koizar [EMAIL PROTECTED] writes:
On Mon, 31 Jan 2005 14:40:08 -0500, Tom Lane [EMAIL PROTECTED] wrote:
Oh, I see, you want a max calculation in there too. Seems reasonable.
Any objections?
Yes. :-( What I said is only true in the absence of any WHERE clause
(or join). Otherwise
On Fri, 28 Jan 2005 10:53:33 -0500, Tom Lane [EMAIL PROTECTED] wrote:
we should consider
something like clamp to size of table / 10 instead.
... unless a *single* grouping column is estimated to have more than
N/10 distinct values, which should be easy to check.
Servus
Manfred
Manfred Koizar [EMAIL PROTECTED] writes:
On Fri, 28 Jan 2005 10:53:33 -0500, Tom Lane [EMAIL PROTECTED] wrote:
we should consider
something like clamp to size of table / 10 instead.
... unless a *single* grouping column is estimated to have more than
N/10 distinct values, which should be
On Mon, 31 Jan 2005 11:20:31 -0500, Tom Lane [EMAIL PROTECTED] wrote:
Already done that way.
if (relvarcount 1)
clamp *= 0.1;
That's not what I meant. I tried to say that if we have a GROUP BY
several columns and one of these columns alone has more than N/10
distinct
Manfred Koizar [EMAIL PROTECTED] writes:
That's not what I meant. I tried to say that if we have a GROUP BY
several columns and one of these columns alone has more than N/10
distinct values, there's no way to get less than that many groups.
Oh, I see, you want a max calculation in there too.
From: Sailesh Krishnamurthy [EMAIL PROTECTED]
Tom == Tom Lane [EMAIL PROTECTED] writes:
Tom The only real solution, of course, is to acquire cross-column
Tom statistics, but I don't see that happening in the near
Tom future.
Another approach is a hybrid hashing scheme where
Greg Stark [EMAIL PROTECTED] writes:
So why is it any more reasonable for Postgres to assume 0 correlation than any
other value. Perhaps Postgres should calculate these cases assuming some
arbitrary level of correlation.
[ shrug... ] Sure, if you want to do the legwork to develop something
Tom == Tom Lane [EMAIL PROTECTED] writes:
Tom The only real solution, of course, is to acquire cross-column
Tom statistics, but I don't see that happening in the near
Tom future.
Another approach is a hybrid hashing scheme where we use a hash table
until we run out of memory at
Tom Lane [EMAIL PROTECTED] writes:
Greg Stark's thought about a power correction seemed interesting too, though
again far too optimistic to trust without some good math to back it up.
Fwiw, I'm pretty sure good math is not going to back up my off-the-cuff
algorithm. But I did like the answer
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