I'd like to analyse some data (say, web-service response times) and get various statistical info, mainly percentiles/quantiles and presence of outstanding values.

I know about Statistics::Descriptive, however, I don't want to store all the data in memory. On the other hand, having my results off by a few % would be fine, I only care about huge differences.

So I came up with the following idea: create an array of logarithmic buckets, and count data points landing in each bucket. Having the data spread across 6 orders of magnitude and guaranteed precision of 1% still leaves me with 6 * log 10 / log 1.01 =~ 1400 buckets which is perfectly fine (36 kb of memory, given current Perl's scalar size).

Counting percentiles is simple - just add up bucket counters until $sum exceeds $percentage * $total_count.

However, before I start writing actual code, I would like to ask which memory efficient statistical modules and algorithms already exist (for Perl, of maybe other languages).

Looks like there's a similar Stackoverflow question, and there's similar method proposed in one of the answers. Haven't found a ready-made Perl implementation, though.

In reply to Memory efficient statistical distribution class by Dallaylaen

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