A fast map-reduce and parallel streaming friendly data-structure for accurate quantile approximation.
This package provides an implementation of Ted Dunning's t-digest data structure in Go.
This project is activelly maintained. There hasn't been a need for new features or bugs in a while, so there isn't much activity but I'm more than willing to cooperate on bugs and/or requests.
The current stable version can be installed via:
go get gopkg.in/caio/go-tdigest.v1
Or if you're planning on contributing or just feeling adventurous:
go get github.com/caio/go-tdigest
package main
import (
"fmt"
"math/rand"
"gopkg.in/caio/go-tdigest.v1"
// Or if you installed the development version:
// "github.com/caio/go-tdigest"
)
func main() {
var t = tdigest.New(100)
for i := 0; i < 10000; i++ {
t.Add(rand.Float64(), 1)
}
fmt.Printf("p(.5) = %.6f\n", t.Quantile(0.5))
}This is a port of the reference implementation with some ideas borrowed from the python version. If you wanna get a quick grasp of how it works and why it's useful, this video and companion article is pretty helpful.