| From: | Greg Stark <gsstark(at)mit(dot)edu> | 
|---|---|
| To: | Tom Lane <tgl(at)sss(dot)pgh(dot)pa(dot)us> | 
| Cc: | PFC <lists(at)peufeu(dot)com>, pgsql-performance(at)postgresql(dot)org | 
| Subject: | Re: Bad plan on a view | 
| Date: | 2006-03-01 16:04:47 | 
| Message-ID: | 87r75mup5s.fsf@stark.xeocode.com | 
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| Lists: | pgsql-performance | 
Tom Lane <tgl(at)sss(dot)pgh(dot)pa(dot)us> writes:
> PFC <lists(at)peufeu(dot)com> writes:
> > So, in order to speed up requests which need a full table scan, I wanted  
> > to put the text fields in another table, and use a view to make it look  
> > like nothing happened. Also, the small table used for searching is a lot  
> > more likely to fit in RAM than the big table with all the text which is  
> > only used for display.
> 
> Aren't you going to a lot of work to reinvent something that TOAST
> already does for you?  (At least, in the cases where the text fields
> are wide enough that it really matters.)
I think this is a fairly common data modelling trick actually. And it's not a
terribly large amount of work either.
While TOAST has a similar goal I don't think it has enough AI to completely
replace this manual process. It suffers in a number of use cases:
1) When you have a large number of moderate sized text fields instead of a
   single very large text field. This is probably the case here.
2) When you know exactly which fields you'll be searching on and which you
   won't be. Often many speed-sensitive queries don't need to access the
   extended information at all.
   Instead of making the decision on a per-record basis you can *always* move
   the data to the other table saving even more space even in cases where
   you're gaining very little per record. In total across the entire scan you
   still gain a lot being able to scan just the dense integer fields.
Also, is the optimizer capable of coming up with merge join type plans for
TOAST tables when necessary?
-- 
greg
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