Hello,
Thank you for your comments.
On Thu, Mar 01, 2018 at 08:31:49PM -0800, Andres Freund wrote:
> Hi,
>
> On 2018-02-07 19:28:29 +0300, Arthur Zakirov wrote:
> > + {
> > + {"max_shared_dictionaries_size", PGC_POSTMASTER, RESOURCES_MEM,
> > + gettext_noop("Sets the maximum size of all text search
> > dictionaries loaded into shared memory."),
> > + gettext_noop("Currently controls only loading of Ispell
> > dictionaries. "
> > + "If total size of
> > simultaneously loaded dictionaries "
> > + "reaches the maximum allowed
> > size then a new dictionary "
> > + "will be loaded into local
> > memory of a backend."),
> > + GUC_UNIT_KB,
> > + },
> > + &max_shared_dictionaries_size,
> > + 100 * 1024, 0, MAX_KILOBYTES,
> > + NULL, NULL, NULL
> > + },
>
> So this uses shared memory, allocated at server start? That doesn't
> seem right. Wouldn't it make more sense to have a
> 'num_shared_dictionaries' GUC, and then allocate them with dsm? Or even
> better not have any such limit and us a dshash table to point to
> individual loaded tables?
The patch uses dsm and dshash table already.
'max_shared_dictionaries_size' GUC was introduced after discussion with
Tomas [1]. To limit amount of memory consumed by loaded dictionaries and to
prevent possible memory bloating. Its default value is 100MB.
There was 'shared_dictionaries' GUC before, it was introduced because
usual hash tables was used before, not dshash. I replaced usual hash
tables by dshash, removed 'shared_dictionaries' and added
'max_shared_dictionaries_size'.
> Is there any chance we can instead can convert dictionaries into a form
> we can just mmap() into memory? That'd scale a lot higher and more
> dynamicallly?
I think new IspellDictData structure (in
0003-Store-ispell-structures-in-shmem-v5.patch)
can be stored in a binary file and mapped into memory already. But
mmap() is not used in this patch yet.
I can do some experiments and make a prototype.
1 -
https://www.postgresql.org/message-id/d12d9395-922c-64c9-c87d-dd0e1d31440e%402ndquadrant.com
--
Arthur Zakirov
Postgres Professional: http://www.postgrespro.com
Russian Postgres Company
