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GitHub - plar/go-adaptive-radix-tree: Adaptive Radix Trees implemented in Go
Adaptive Radix Trees implemented in Go. Contribute to plar/go-adaptive-radix-tree development by creating an account on GitHub.
Visit SiteGitHub - plar/go-adaptive-radix-tree: Adaptive Radix Trees implemented in Go
Adaptive Radix Trees implemented in Go. Contribute to plar/go-adaptive-radix-tree development by creating an account on GitHub.
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An Adaptive Radix Tree Implementation in Go
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, wherek
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 | 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 qa/benchmarks
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.
GoLang Resources
are all listed below.
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