Awesome
Skip List implement in Go
What is Skip List
Skip List is a data structure that allows fast search within an ordered sequence of elements. Fast search is made possible by maintaining a linked hierarchy of subsequences, each skipping over fewer elements.
(from wiki)
Install
go get github.com/kkdai/skiplist
Usage
package main
import (
"fmt"
. "github.com/kkdai/skiplist"
)
func main() {
//New a skiplist
sl := skiplist.NewSkipList()
//Insert search key 50, value "5", value could be anything.
sl.Insert(50, "5")
sl.Insert(40, "4")
sl.Insert(70, "7")
sl.Insert(100, "10")
//Search key, which time complexity O(log n)
ret, err := sl.Search(50)
if err == nil {
fmt.Println("key 50: val->", ret)
} else {
fmt.Println("Not found, ", err)
}
//Delete by search key
err = sl.Delete(70)
if err != nil {
fmt.Println("Delete not found")
}
//Display all skip list content.
sl.DisplayAll()
//head->[key:0][val:header]->[key:40][val:4]->[key:50][val:5]->[key:100][val:10]->nil
//---------------------------------------------------------
//[node:0], val:header, level:4 fw[3]:40 fw[2]:40 fw[1]:40 fw[0]:40
//[node:40], val:4, level:4 fw[3]:nil fw[2]:nil fw[1]:50 fw[0]:50
//[node:50], val:5, level:2 fw[1]:100 fw[0]:100
//[node:100], val:10, level:2
}
Inspired By:
- Skip List bookbook
- SkipList Wiki
- 大数据日知录:架构与算法
- https://github.com/surge/skiplist
- https://github.com/huandu/skiplist
- https://github.com/gansidui/skiplist
Benchmark
Here is the benchmark list:
Note: The slice search op base on worst case.
//Slice Operations
BenchmarkSliceInsert-4 100000000 34.4 ns/op
BenchmarkSliceSearch-4 20000 80149.0 ns/op
//Sliplist Operations
BenchmarkSkiplistInsert-4 100000 20881.0 ns/op
BenchmarkSkiplistSearch-4 10000000 137.0 ns/op
It is very obviousily the skiplist search is much faster than slice iterator.
The map operation for reference.
//Map Operations
BenchmarkMapInsert-4 5000000 283.0 ns/op
BenchmarkMapSearch-4 30000000 42.4 ns/op
Project52
It is one of my project 52.
License
This package is licensed under MIT license. See LICENSE for details.