GoLLRB is a Left-Leaning Red-Black (LLRB) implementation of 2-3 balanced binary search trees in Go Language.
As of this writing and to the best of the author's knowledge, Go still does not have a balanced binary search tree (BBST) data structure. These data structures are quite useful in a variety of cases. A BBST maintains elements in sorted order under dynamic updates (inserts and deletes) and can support various order-specific queries. Furthermore, in practice one often implements other common data structures like Priority Queues, using BBST's.
2-3 trees (a type of BBST's), as well as the runtime-similar 2-3-4 trees, are the de facto standard BBST algoritms found in implementations of Python, Java, and other libraries. The LLRB method of implementing 2-3 trees is a recent improvement over the traditional implementation. The LLRB approach was discovered relatively recently (in 2008) by Robert Sedgewick of Princeton University.
GoLLRB is a Go implementation of LLRB 2-3 trees.
GoLLRB has been used in some pretty heavy-weight machine learning tasks over many gigabytes of data. I consider it to be in stable, perhaps even production, shape. There are no known bugs.
With a healthy Go Language installed, simply run go get github.com/petar/GoLLRB/llrb
package main
import (
"fmt"
"github.com/petar/GoLLRB/llrb"
)
func lessInt(a, b interface{}) bool { return a.(int) < b.(int) }
func main() {
tree := llrb.New(lessInt)
tree.ReplaceOrInsert(1)
tree.ReplaceOrInsert(2)
tree.ReplaceOrInsert(3)
tree.ReplaceOrInsert(4)
tree.DeleteMin()
tree.Delete(4)
c := tree.IterAscend()
for {
u := <-c
if u == nil {
break
}
fmt.Printf("%d\n", int(u.(int)))
}
}
GoLLRB was written by Petar Maymounkov.
Follow me on Twitter @maymounkov!
