Ugh, never mind. I ran ltrace and it's spending 99% of its time in 
gettimeofday.  

select count(*) from notes;
  count   
---------
 1926207
(1 row)

Time: 213.950 ms

explain analyze select count(*) from notes;
                                                       QUERY PLAN               
                                         
------------------------------------------------------------------------------------------------------------------------
 Aggregate  (cost=99274.59..99274.60 rows=1 width=0) (actual 
time=2889.325..2889.325 rows=1 loops=1)
   ->  Seq Scan on notes  (cost=0.00..94459.07 rows=1926207 width=0) (actual 
time=0.005..1475.218 rows=1926207 loops=1)
 Total runtime: 2889.360 ms
(3 rows)

Time: 2889.842 ms  


On Tuesday, 21 August, 2012 at 3:57 PM, Matt Daw wrote:

> Howdy. I'm curious what besides raw hardware speed determines the performance 
> of a Seq Scan that comes entirely out of shared buffers… I ran the following 
> on the client's server I'm profiling, which is otherwise idle:
>  
> EXPLAIN (ANALYZE ON, BUFFERS ON) SELECT * FROM notes;
>  
> Seq Scan on notes  (cost=0.00..94004.88 rows=1926188 width=862) (actual 
> time=0.009..1673.702 rows=1926207 loops=1)
>    Buffers: shared hit=74743
>  Total runtime: 3110.442 ms
> (3 rows)
>  
>  
> … and that's about 9x slower than what I get on my laptop with the same data. 
> I ran stream-scaling on the machine and the results seem reasonable 
> (8644.1985 MB/s with 1 core -> 25017 MB/s with 12 cores). The box is running 
> 2.6.26.6-49 and postgresql 9.0.6.
>  
> I'm stumped as to why it's so much slower, any ideas on what might explain 
> it… or other benchmarks I could run to try to narrow down the cause?
>  
> Thanks!
>  
> Matt  

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