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https://github.com/plar/Go-adaptive-radix-tree
Adaptive Radix Trees implemented in Go
https://github.com/plar/Go-adaptive-radix-tree
go trie
Last synced: 20 days ago
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Adaptive Radix Trees implemented in Go
- Host: GitHub
- URL: https://github.com/plar/Go-adaptive-radix-tree
- Owner: plar
- License: mit
- Created: 2016-04-01T01:40:40.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2024-04-09T12:39:33.000Z (7 months ago)
- Last Synced: 2024-07-31T01:23:12.661Z (4 months ago)
- Topics: go, trie
- Language: Go
- Homepage:
- Size: 2.81 MB
- Stars: 347
- Watchers: 9
- Forks: 51
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
An Adaptive Radix Tree Implementation in Go
====
[](https://travis-ci.org/plar/go-adaptive-radix-tree) [](https://coveralls.io/github/plar/go-adaptive-radix-tree?branch=master) [](https://goreportcard.com/report/github.com/plar/go-adaptive-radix-tree) [](http://godoc.org/github.com/plar/go-adaptive-radix-tree)
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
```go
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](http://godoc.org/github.com/plar/go-adaptive-radix-tree)
# Performance
[plar/go-adaptive-radix-tree](https://github.com/plar/go-adaptive-radix-tree) outperforms [kellydunn/go-art](https://github.com/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 | 9 | 117,888,698 ns/op | 37,942,744 B/op | 1,214,541 allocs/op |
| Tree Search Words | 26 | 44,555,608 ns/op | 0 B/op | 0 allocs/op |
| Tree Insert UUIDs | 18 | 59,360,135 ns/op | 18,375,723 B/op | 485,057 allocs/op |
| Tree Search UUIDs | 54 | 21,265,931 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)](http://www-db.in.tum.de/~leis/papers/ART.pdf)
[2] [C99 implementation of the Adaptive Radix Tree](https://github.com/armon/libart)
[3] [Another Adaptive Radix Tree implementation in Go](https://github.com/kellydunn/go-art)
[4] [HSK Words](http://hskhsk.pythonanywhere.com/hskwords). HSK(Hanyu Shuiping Kaoshi) - Standardized test of Standard Mandarin Chinese proficiency.