From: | Oleksandr Shulgin <oleksandr(dot)shulgin(at)zalando(dot)de> |
---|---|
To: | Vinicius Segalin <vinisegalin(at)gmail(dot)com> |
Cc: | pgsql general <pgsql-general(at)postgresql(dot)org> |
Subject: | Re: Predicting query runtime |
Date: | 2016-09-12 15:08:14 |
Message-ID: | CACACo5TG-MwUgWH7faFvoS+o=AhUBKDZO-v-gJNw1RBWG=u8PA@mail.gmail.com |
Views: | Raw Message | Whole Thread | Download mbox | Resend email |
Thread: | |
Lists: | pgsql-general |
On Mon, Sep 12, 2016 at 4:03 PM, Vinicius Segalin <vinisegalin(at)gmail(dot)com>
wrote:
> Hi everyone,
>
> I'm trying to find a way to predict query runtime (I don't need to be
> extremely precise). I've been reading some papers about it, and people are
> using machine learning to do so. For the feature vector, they use what the
> DBMS's query planner provide, such as operators and their cost. The thing
> is that I haven't found any work using PostgreSQL, so I'm struggling to
> adapt it.
> My question is if anyone is aware of a work that uses machine learning and
> PostgreSQL to predict query runtime, or maybe some other method to perform
> this.
>
Hi,
I'm not aware of machine-learning techniques to achieve that (and I don't
actually believe it's feasible), but there you might find this extension
particularly useful:
https://www.postgresql.org/docs/9.5/static/pgstatstatements.html
Can you share some links to the papers you are referring to (assuming these
are publicly available)?
Regards,
--
Alex
From | Date | Subject | |
---|---|---|---|
Next Message | Vinicius Segalin | 2016-09-12 15:59:04 | Re: Predicting query runtime |
Previous Message | Adrian Klaver | 2016-09-12 14:03:23 | Re: [SPAM] Re: Question about locking and pg_locks |