Hello,
Thanks for this clear explanation !
Then I have a sub-question :
Supposed I have 3600 materialised views say 600 mat views from 6 main table. (A,B,C,D,E,F are repetead 600 times with some differences)
Is it faster to :
1) parallel refresh 600 time A, then 600 time B etc,
1) parallel refresh 600 time A, then 600 time B etc,
OR
2) parallel refresh 600 time A,B,C,D,E,F
I guess 1) is faster because they are 600 access to same table loaded in memory ? But do parallel access to the same table implies concurency
and bad performance ?
Thanks
Nicolas PARIS
2014-04-07 12:29 GMT+02:00 Graeme B. Bell <grb@xxxxxxxxxxxxxxxxx>:
Hi Nick,On 04 Apr 2014, at 18:29, Nicolas Paris <niparisco@xxxxxxxxx> wrote:
> Hello,
>
> My question is about multiprocess and materialized View.
> http://www.postgresql.org/docs/9.3/static/sql-creatematerializedview.html
> I (will) have something like 3600 materialised views, and I would like to know the way to refresh them in a multithread way
> (anderstand 8 cpu cores -> 8 refresh process in the same time)
out of DB solution:
1. Produce a text file which contains the 3600 refresh commands you want to run in parallel. You can do that with select and format() if you don't have a list already.
2. I'm going to simulate your 3600 'refresh' commands here with some select and sleep statements that finish at unknown times.
(In BASH):
for i in {1..3600} ; do echo "echo \"select pg_sleep(1+random()::int*10); select $i\" | psql mydb" ; done > 3600commands
3. Install Gnu Parallel and type:
parallel < 3600commands
4. Parallel will automatically work out the appropriate number of cores/threads for your CPUs, or you can control it manually with -j.
It will also give you a live progress report if you use --progress.
e.g. this command balances 8 jobs at a time, prints a dynamic progress report and dumps stdout to /dev/null
parallel -j 8 --progress < 3600commands > /dev/null
5. If you want to make debugging easier use the parameter --tag to tag output for each command.
Of course it would be much more elegant if someone implemented something like Gnu Parallel inside postgres or psql ... :-)
Hope this helps & have a nice day,
Graeme.
