From: | Robert Haas <robertmhaas(at)gmail(dot)com> |
---|---|
To: | Tom Lane <tgl(at)sss(dot)pgh(dot)pa(dot)us> |
Cc: | Greg Stark <gsstark(at)mit(dot)edu>, Pavel Stehule <pavel(dot)stehule(at)gmail(dot)com>, PostgreSQL Hackers <pgsql-hackers(at)postgresql(dot)org>, David Fetter <david(at)fetter(dot)org> |
Subject: | Re: wip: functions median and percentile |
Date: | 2010-08-19 16:49:45 |
Message-ID: | AANLkTi=yam_+-6vMeJVEyutBa3wizxSph0EE2PHddkK2@mail.gmail.com |
Views: | Raw Message | Whole Thread | Download mbox | Resend email |
Thread: | |
Lists: | pgsql-hackers pgsql-rrreviewers |
On Thu, Aug 19, 2010 at 11:33 AM, Tom Lane <tgl(at)sss(dot)pgh(dot)pa(dot)us> wrote:
> Greg Stark <gsstark(at)mit(dot)edu> writes:
>> On Thu, Aug 19, 2010 at 11:59 AM, Pavel Stehule <pavel(dot)stehule(at)gmail(dot)com> wrote:
>>> I am sending a prototype implementation of functions median and
>>> percentile. This implementation is very simple and I moved it to
>>> contrib for this moment - it is more easy maintainable. Later I'll
>>> move it to core.
>
>> So if the entire result set fits in memory it would be nice to use the
>> O(n) Quickselect algorithm -- which would only be a small change to
>> the existing Quicksort code -- instead of sorting the entire set.
>
> That seems like rather a lot of added infrastructure for functions whose
> popularity is at best unknown. I think we should KISS for the first
> implementation.
+1. I think the functions are useful, but the perfect is the enemy of the good.
--
Robert Haas
EnterpriseDB: http://www.enterprisedb.com
The Enterprise Postgres Company
From | Date | Subject | |
---|---|---|---|
Next Message | Tom Lane | 2010-08-19 16:52:49 | Re: PL/pgsSQL EXECUTE USING INTO |
Previous Message | Heikki Linnakangas | 2010-08-19 16:23:23 | Re: CommitFest 2009-07: Yay, Kevin! Thanks, reviewers! |
From | Date | Subject | |
---|---|---|---|
Next Message | David Fetter | 2010-08-19 17:03:20 | Re: wip: functions median and percentile |
Previous Message | Tom Lane | 2010-08-19 15:33:13 | Re: wip: functions median and percentile |