On Fri, Sep 26, 2014 at 3:06 AM, Simon Riggs <simon@2ndquadrant.com> wrote:
> The problem, as I see it, is different. We assume that if there are
> 100 distinct values and you use LIMIT 1 that you would only need to
> scan 1% of rows. We assume that the data is arranged in the table in a
> very homogenous layout. When data is not, and it seldom is, we get
> problems.
Hm, good point -- 'data proximity'. At least in theory, can't this be
measured and quantified? For example, given a number of distinct
values, you could estimate the % of pages read (or maybe non
sequential seeks relative to the number of pages) you'd need to read
all instances of a particular value in the average (or perhaps the
worst) case. One way of trying to calculate that would be to look at
proximity of values in sampled pages (and maybe a penalty assigned for
high update activity relative to table size). Data proximity would
then become a cost coefficient to the benefits of LIMIT.
merlin
