package tdigest

  1. Overview
  2. Docs
OCaml implementation of the T-Digest algorithm

Install

Dune Dependency

Authors

Maintainers

Sources

2.0.0.tar.gz
md5=5732b60dbdc548f124ffd4acbe1637ba
sha512=c6773bb73c22f03f8ac645e5da444dd7d43ea8600f3982ac94e065857d2bcf69cece01bccced5acb215f362d12b927d6df5916bc0d8e19852108d6cbd4eccfd2

Description

The T-Digest is a data structure and algorithm for constructing an approximate distribution for a collection of real numbers presented as a stream.

The T-Digest can estimate percentiles or quantiles extremely accurately even at the tails, while using a fraction of the space.

Additionally, the T-Digest is concatenable, making it a good fit for distributed systems. The internal state of a T-Digest can be exported as a binary string, and the concatenation of any number of those strings can then be imported to form a new T-Digest.

Published: 28 Nov 2022

README

Tdigest

OCaml implementation of the T-Digest algorithm.

The T-Digest is a data structure and algorithm for constructing an approximate distribution for a collection of real numbers presented as a stream.

The median of a list of medians is not necessarily equal to the median of the whole dataset. The median (p50), p95, and p99 are critical measures that are expensive to compute due to their requirement of having the entire sorted dataset present in one place.

The T-Digest can estimate percentiles or quantiles extremely accurately even at the tails, while using a fraction of the space.

Additionally, the T-Digest is concatenable, making it a good fit for distributed systems. The internal state of a T-Digest can be exported as a binary string, and the concatenation of any number of those strings can then be imported to form a new T-Digest.

Links:

This library started off as a port of Will Welch's JavaScript implementation, down to the unit tests. However some modifications have been made to adapt it to OCaml, the most important one being immutability. As such, almost every function in the Tdigest module return a new Tdigest.t, including "reading" ones since they may trigger expensive intermediate computations worth caching.

Usage

The API is well documented here.

opam install tdigest

Performance

On a 2018 MacBook Pro, it can incorporate 1,000,000 random floating points in just 770ms.

Exporting and importing state (to_string/of_string) is essentially free.

Dependencies (3)

  1. core >= "v0.15.0" & < "v0.16.0"
  2. dune >= "1.9.0"
  3. ocaml >= "4.10.0"

Dev Dependencies (2)

  1. yojson with-test
  2. alcotest with-test

Used by

None

Conflicts

None