Popularity
5.0
-
Activity
1.7
-
138
7
19

Programming language: Go
Tags: Data Structures    
Latest version: v1.0.1

go-adaptive-radix-tree alternatives and similar packages

Based on the "Data Structures" category

Do you think we are missing an alternative of go-adaptive-radix-tree or a related project?

Add another 'Data Structures' Package

README

An Adaptive Radix Tree Implementation in Go

Build Status Coverage Status Go Report Card GoDoc

This library provides a Go implementation of the Adaptive Radix Tree (ART).

Features:

  • Lookup performance surpasses highly tuned alternatives
  • Support for highly efficient insertions and deletions
  • Space efficient
  • Performance is comparable to hash tables
  • Maintains the data in sorted order, which enables additional operations like range scan and prefix lookup
  • O(k) search/insert/delete operations, where k is the length of the key
  • Minimum / Maximum value lookups
  • Ordered iteration
  • Prefix-based iteration
  • Support for keys with null bytes, any byte array could be a key

Usage

package main

import (
    "fmt"
    "github.com/plar/go-adaptive-radix-tree"
)

func main() {

    tree := art.New()

    tree.Insert(art.Key("Hi, I'm Key"), "Nice to meet you, I'm Value")
    value, found := tree.Search(art.Key("Hi, I'm Key"))
    if found {
        fmt.Printf("Search value=%v\n", value)
    }

    tree.ForEach(func(node art.Node) bool {
        fmt.Printf("Callback value=%v\n", node.Value())
        return true
    })

    for it := tree.Iterator(); it.HasNext(); {
        value, _ := it.Next()
        fmt.Printf("Iterator value=%v\n", value.Value())
    }
}

// Output:
// Search value=Nice to meet you, I'm Value
// Callback value=Nice to meet you, I'm Value
// Iterator value=Nice to meet you, I'm Value

Documentation

Check out the documentation on godoc.org

Performance

plar/go-adaptive-radix-tree outperforms kellydunn/go-art by avoiding memory allocations during search operations. It also provides prefix based iteration over the tree.

Benchmarks were performed on datasets extracted from different projects:

  • The "Words" dataset contains a list of 235,886 english words. [2]
  • The "UUIDs" dataset contains 100,000 uuids. [2]
  • The "HSK Words" dataset contains 4,995 words. [4]
go-adaptive-radix-tree # Average time Bytes per operation Allocs per operation
Tree Insert Words 10 146,326,506 ns/op 41,299,883 B/op 1,326,167 allocs/op
Tree Search Words 30 44,075,933 ns/op 0 B/op 0 allocs/op
Tree Insert UUIDs 20 86,062,471 ns/op 19,638,904 B/op 547,648 allocs/op
Tree Search UUIDs 50 35,808,749 ns/op 0 B/op 0 allocs/op
go-art
Tree Insert Words 5 272,047,975 ns/op 81,628,987 B/op 2,547,316 allocs/op
Tree Search Words 10 129,011,177 ns/op 13,272,278 B/op 1,659,033 allocs/op
Tree Insert UUIDs 10 140,309,246 ns/op 33,678,160 B/op 874,561 allocs/op
Tree Search UUIDs 20 82,120,943 ns/op 3,883,131 B/op 485,391 allocs/op

To see more benchmarks just run

$ make benchmark

References

[1] The Adaptive Radix Tree: ARTful Indexing for Main-Memory Databases (Specification)

[2] C99 implementation of the Adaptive Radix Tree

[3] Another Adaptive Radix Tree implementation in Go

[4] HSK Words. HSK(Hanyu Shuiping Kaoshi) - Standardized test of Standard Mandarin Chinese proficiency.