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From Philippe Mouawad <philippe.moua...@gmail.com>
Subject Re: [GitHub] jmeter issue #296: Bug 61078 - Percentile calculation error
Date Tue, 09 May 2017 11:39:08 GMT
Hi Felix,
Thanks for this precious information.

Maybe we should document what option was taken by JOrphan if you know it.

On another side, do you agree we should make percentiles / median uniform
accross JMeter ?
It seems we have at least those choices:

   - commons-math we already use in BackendListener and Web Report
   - https://github.com/HdrHistogram/HdrHistogram
   - https://github.com/tdunning/t-digest/

I think the 2 latest take more into accound performance and memory usage
than first one.

Regards
Philippe


On Tue, May 9, 2017 at 9:21 AM, Felix Schumacher <
felix.schumacher@internetallee.de> wrote:

> Am 09.05.2017 09:11, schrieb pmouawad:
>
>> Github user pmouawad commented on the issue:
>>
>>     https://github.com/apache/jmeter/pull/296
>>
>>     Hello @abalanonline ,
>>     Thanks for your replies and explanations !
>>
>>     I am not a math expert as you seem to be, so I have few questions
>> you may be able to help on:
>>
>>     1. Thanks to your comment, I see default method is LEGACY, and the
>> one you have created is R_1. Do you have some insights on the
>> different method and their limits / use cases ?
>>
>>     2. Why does the "bug" you report affect all libraries I checked
>> (HdrHistogram, https://github.com/tdunning/t-digest/ and JOrphan ) ?
>> Can't it be due to a different method estimation algorithm ?
>>
>>     Note I share your thoughts on using a dedicated library but
>> commons-math may be overkill in terms of performance compared to
>> HdrHistogram or t-digest.
>>
>
> I have tried to do a bit of research on percentiles, quantiles and median.
>
> It looks to me, that those "points" are more like ranges, and there is no
> exact value.
>
> R and numpy will interpolate the median and the percentiles/quantiles. The
> statistics module
> of python 3 has three different median implementations called median,
> median_high and median_low,
> that interpolate, give the highest possible median and the lowest.
>
> Wikipedia (the german one), gives a definition of an "Empirisches
> Quantile" (empiric quantile),
> where it settles on the lower border of the quantiles (and therefore the
> median).
>
> I wonder if we should change our implementation at all.
>
> Felix
>
>
>
>>     Thanks
>>
>>
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>


-- 
Cordialement.
Philippe Mouawad.

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