-c 10 means 10 clients so that should take advantage of all your cores (see bellow)
%Cpu0 : 39.3 us, 21.1 sy, 0.0 ni, 38.7 id, 0.9 wa, 0.0 hi, 0.0 si, 0.0 st %Cpu1 : 38.0 us, 25.0 sy, 0.0 ni, 26.0 id, 4.2 wa, 0.0 hi, 6.8 si, 0.0 st %Cpu2 : 39.3 us, 20.4 sy, 0.0 ni, 39.0 id, 1.3 wa, 0.0 hi, 0.0 si, 0.0 st %Cpu3 : 40.0 us, 18.7 sy, 0.0 ni, 40.0 id, 1.3 wa, 0.0 hi, 0.0 si, 0.0 st %Cpu4 : 13.9 us, 7.1 sy, 0.0 ni, 79.1 id, 0.0 wa, 0.0 hi, 0.0 si, 0.0 st %Cpu5 : 13.1 us, 8.4 sy, 0.0 ni, 78.5 id, 0.0 wa, 0.0 hi, 0.0 si, 0.0 st %Cpu6 : 14.8 us, 6.4 sy, 0.0 ni, 78.8 id, 0.0 wa, 0.0 hi, 0.0 si, 0.0 st %Cpu7 : 15.7 us, 6.7 sy, 0.0 ni, 77.7 id, 0.0 wa, 0.0 hi, 0.0 si, 0.0 st i am pasting you the results of the same test on a i7-2600 16gb with a sata3 SSD and the results from a VM with 2 cores and a normal 7200 rpm hdd -- DESKTOP vasilis@Disorder ~ $ pgbench -c 10 -t 10000 bench starting vacuum...end. transaction type: TPC-B (sort of) scaling factor: 1 query mode: simple number of clients: 10 number of threads: 1 number of transactions per client: 10000 number of transactions actually processed: 100000/100000 tps = 1713.338111 (including connections establishing) tps = 1713.948478 (excluding connections establishing) -- VM postgres@pglab1:~/postgresql-9.2.4/contrib/pgbench$ ./pgbench -c 10 -t 10000 bench starting vacuum...end. transaction type: TPC-B (sort of) scaling factor: 1 query mode: simple number of clients: 10 number of threads: 1 number of transactions per client: 10000 number of transactions actually processed: 100000/100000 tps = 1118.976496 (including connections establishing) tps = 1119.180126 (excluding connections establishing) i am assuming that you didn't populate your pgbench db with the default values , if you tell me how you did i will be happy to re run the test and see the differences. On Mon, Apr 8, 2013 at 10:31 PM, Mark Davidson <m...@4each.co.uk> wrote: > Thanks for your response Vasillis. I've run pgbench on both machines > `./pgbench -c 10 -t 10000 pgbench` getting 99.800650 tps on my local > machine and 23.825332 tps on the server so quite a significant difference. > Could this purely be down to the CPU clock speed or is it likely something > else causing the issue? > I have run ANALYZE on both databases and tried the queries a number of > times on each to make sure the results are consistent, this is the case. > > > On 8 April 2013 18:19, Vasilis Ventirozos <v.ventiro...@gmail.com> wrote: > >> >> Hello Mark, >> PostgreSQL currently doesn't support parallel query so a faster cpu even >> if it has less cores would be faster for a single query, about benchmarking >> you can try pgbench that you will find in the contrib, >> the execution plan may be different because of different statistics, have >> you analyzed both databases when you compared the execution plans ? >> >> Vasilis Ventirozos >> >> >> Been trying to progress with this today. Decided to setup the database >>> on my local machine to try a few things and I'm getting much more sensible >>> results and a totally different query plan >>> http://explain.depesz.com/s/KGd in this case the query took about a >>> minute but does sometimes take around 80 seconds. >>> >>> The config is exactly the same between the two database. The databases >>> them selves are identical with all indexes the same on the tables. >>> >>> The server has an 2 x Intel Xeon E5420 running at 2.5Ghz each, 16GB RAM >>> and the database is just on a SATA HDD which is a Western Digital >>> WD5000AAKS. >>> My desktop has a single i5-3570K running at 3.4Ghz, 16GB RAM and the >>> database is running on a SATA HDD which is a Western Digital WD1002FAEX-0 >>> >>> Could anyone offer any reasoning as to why the plan would be so >>> different across the two machines? I would have thought that the server >>> would perform a lot better since it has more cores or is postgres more >>> affected by the CPU speed? Could anyone suggest a way to bench mark the >>> machines for their postgres performance? >>> >>> Thanks again for everyones input, >>> >>> Mark >>> >>> >>> On 7 April 2013 23:22, Mark Davidson <m...@4each.co.uk> wrote: >>> >>>> Takes a little longer with the INNER join unfortunately. Takes about >>>> ~3.5 minutes, here is the query plan http://explain.depesz.com/s/EgBl. >>>> >>>> With the JOIN there might not be a match if the data does not fall >>>> within one of the areas that is selected in the IN query. >>>> >>>> So if we have data id (10) that might fall in areas ( 1, 5, 8, 167 ) >>>> but the user might be querying areas ( 200 ... 500 ) so no match in area >>>> would be found just to be absolutely clear. >>>> >>>> Is it worth considering adding additional statistics on any of the >>>> columns? And / Or additional INDEXES or different types INDEX? Would it be >>>> worth restructuring the query starting with areas and working to join data >>>> to that? >>>> >>>> >>>> On 7 April 2013 16:15, Kevin Grittner <kgri...@ymail.com> wrote: >>>> >>>>> Greg Williamson <gwilliamso...@yahoo.com> wrote: >>>>> >>>>> >> Thanks for your response. I tried doing what you suggested so >>>>> >> that table now has a primary key of >>>>> >> ' CONSTRAINT data_area_pkey PRIMARY KEY(area_id , data_id ); ' >>>>> >> and I've added the INDEX of >>>>> >> 'CREATE INDEX data_area_data_id_index ON data_area USING btree >>>>> (data_id );' >>>>> >>>>> Yeah, that is what I was suggesting. >>>>> >>>>> >> unfortunately it hasn't resulted in an improvement of the query >>>>> >> performance. >>>>> >>>>> > Did you run analyze on the table after creating the index ? >>>>> >>>>> That probably isn't necessary. Statistics are normally on relations >>>>> and columns; there are only certain special cases where an ANALYZE >>>>> is needed after an index build, like if the index is on an >>>>> expression rather than a list of columns. >>>>> >>>>> Mark, what happens if you change that left join to a normal (inner) >>>>> join? Since you're doing an inner join to data_area and that has a >>>>> foreign key to area, there should always be a match anyway, right? >>>>> The optimizer doesn't recognize that, so it can't start from the >>>>> area and just match to the appropriate points. >>>>> >>>>> -- >>>>> Kevin Grittner >>>>> EnterpriseDB: http://www.enterprisedb.com >>>>> The Enterprise PostgreSQL Company >>>>> >>>> >>>> >>> >> >
