Re: Question about postmaster's CPU usage

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Thanks a lot for replies from Kevin, Ken, and Ants Aasma. I really aappreciate your suggestions and comments.
 
My server configuration is two physical quad-core CPUs with hyper-threading enabled. 
Each CPU is Intel(R) Xeon(R) CPU E5620@2.40GHz. Physical memory is 16GB.
I set shared_buffers as 4GB, effective_cache_size as 10GB and inventory table is around 500MB.
 
From the information provided by top command, although the row for postmaster shows that postmaster is using 100%CPU, 
the total CPU user time for the whole server never goes beyond 6.6%us.
I guess it is because postgres only uses a single thread to read
the data or “pushing the data around in RAM” according to Kevin’s statement.
Then my question is actually why postgres can not use the remaining 93.4%CPU.

 
Btw, I also tried the command suggested by Ants Aasma, but got an error:
explain (analyze on, timing off) select * from inventory;
ERROR:  syntax error at or near "analyze"
LINE 1: explain (analyze on, timing off) select * from inventory;
                 ^
Thanks!

Best regards
Kelphet Xiong

On Thu, Mar 28, 2013 at 2:03 PM, Kevin Grittner <kgrittn@xxxxxxxxx> wrote:
kelphet xiong <kelphet@xxxxxxxxx> wrote:

> When I use postgres and issue a simple sequential scan for a
> table inventory using query "select * from inventory;", I can see
> from "top" that postmaster is using 100% CPU, which limits the
> query execution time. My question is that, why CPU is the
> bottleneck here and what is postmaster doing? Is there any way to
> improve the performance? Thanks!

> explain analyze select * from inventory;
>
> Seq Scan on inventory  (cost=0.00..180937.00 rows=11745000 width=16) (actual time=0.005..1030.403 rows=11745000 loops=1)
>  Total runtime: 1750.889 ms

So it is reading and returning 11.7 million rows in about 1 second,
or about 88 nanoseconds (billionths of a second) per row.  You
can't be waiting for a hard drive for many of those reads, or it
would take a lot longer, so the bottleneck is the CPU pushing the
data around in RAM.  I'm not sure why 100% CPU usage would surprise
you.  Are you wondering why the CPU works on the query straight
through until it is done, rather than taking a break periodically
and letting the unfinished work sit there?

--
Kevin Grittner
EnterpriseDB: http://www.enterprisedb.com
The Enterprise PostgreSQL Company


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