On 2/17/19 5:09 PM, Tom Lane wrote:
> Fabien COELHO <coelho@cri.ensmp.fr> writes:
>>> I'm trying to use random_zipfian() for benchmarking of skewed data sets,
>>> and I ran head-first into an issue with rather excessive CPU costs.
>
>> If you want skewed but not especially zipfian, use exponential which is
>> quite cheap. Also zipfian with a > 1.0 parameter does not have to compute
>> the harmonic number, so it depends in the parameter.
>
> Maybe we should drop support for parameter values < 1.0, then. The idea
> that pgbench is doing something so expensive as to require caching seems
> flat-out insane from here.
Maybe.
It's not quite clear to me why we support the two modes at all? We use
one algorithm for values < 1.0 and another one for values > 1.0, what's
the difference there? Are those distributions materially different?
Also, I wonder if just dropping support for parameters < 1.0 would be
enough, because the docs say:
The function's performance is poor for parameter values close and
above 1.0 and on a small range.
which seems to suggest it might be slow even for values > 1.0 in some
cases. Not sure.
> That cannot be seen as anything but a foot-gun
> for unwary users. Under what circumstances would an informed user use
> that random distribution rather than another far-cheaper-to-compute one?
>
>> ... This is why I submitted a pseudo-random permutation
>> function, which alas does not get much momentum from committers.
>
> TBH, I think pgbench is now much too complex; it does not need more
> features, especially not ones that need large caveats in the docs.
> (What exactly is the point of having zipfian at all?)
>
I wonder about the growing complexity of pgbench too ...
regards
--
Tomas Vondra http://www.2ndQuadrant.com
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