golang consistent hash 菜鸟分析

一直找集群的算法,刚好golang上面有一个适合。下面作为菜鸟来分析一下

// Copyright (C) 2012 Numerotron Inc.
// Use of this source code is governed by an MIT-style license
// that can be found in the LICENSE file.
// Package consistent provides a consistent hashing function.
//
// Consistent hashing is often used to distribute requests to a changing set of servers. For example,
// say you have some cache servers cacheA, cacheB, and cacheC. You want to decide which cache server
// to use to look up information on a user.
//
// You could use a typical hash table and hash the user id
// to one of cacheA, cacheB, or cacheC. But with a typical hash table, if you add or remove a server,
// almost all keys will get remapped to different results, which basically could bring your service
// to a grinding halt while the caches get rebuilt.
//
// With a consistent hash, adding or removing a server drastically reduces the number of keys that
// get remapped.
//
// Read more about consistent hashing on wikipedia: http://en.wikipedia.org/wiki/Consistent_hashing
//
package main
import (
	"errors"
	"fmt"
	"hash/crc32"
	"log"
	"sort"
	"strconv"
	"sync"
)
type uints []uint32
// Len returns the length of the uints array.
func (x uints) Len() int { return len(x) }
// Less returns true if element i is less than element j.
func (x uints) Less(i, j int) bool { return x[i] < x[j] }
// Swap exchanges elements i and j.
func (x uints) Swap(i, j int) { x[i], x[j] = x[j], x[i] }
// ErrEmptyCircle is the error returned when trying to get an element when nothing has been added to hash.
var ErrEmptyCircle = errors.New("empty circle")
// Consistent holds the information about the members of the consistent hash circle.
type Consistent struct {
	circle map[uint32]string
	members map[string]bool
	sortedHashes uints // 已经排好序的hashes slice , 主要有力搜索 (存储的内容是全部虚拟hashes值)
	NumberOfReplicas int
	count int64
	scratch [64]byte
	sync.RWMutex
}
// New creates a new Consistent object with a default setting of 20 replicas for each entry.
//
// To change the number of replicas, set NumberOfReplicas before adding entries.
func New() *Consistent {
	c := new(Consistent)
	c.NumberOfReplicas = 20
	c.circle = make(map[uint32]string)
	c.members = make(map[string]bool)
	//log.Printf("%p", c)
	return c
}
// eltKey generates a string key for an element with an index.
func (c *Consistent) eltKey(elt string, idx int) string {
	return elt + "|" + strconv.Itoa(idx)
}
// Add inserts a string element in the consistent hash.
func (c *Consistent) Add(elt string) {
	c.Lock()
	defer c.Unlock()
	for i := 0; i < c.NumberOfReplicas; i++ {
		fmt.Println("i:",i,c.hashKey(c.eltKey(elt, i)))
		c.circle[c.hashKey(c.eltKey(elt, i))] = elt
	}
	//log.Fatal(len(c.circle))
	//log.Println(len(c.members), elt)
	c.members[elt] = true
	c.updateSortedHashes()
	c.count++
}
// Remove removes an element from the hash.
func (c *Consistent) Remove(elt string) {
	c.Lock()
	defer c.Unlock()
	for i := 0; i < c.NumberOfReplicas; i++ {
		delete(c.circle, c.hashKey(c.eltKey(elt, i)))
	}
	delete(c.members, elt)
	c.updateSortedHashes()
	c.count--
}
// Set sets all the elements in the hash. If there are existing elements not present in elts, they will be removed.
func (c *Consistent) Set(elts []string) {
	mems := c.Members()
	for _, k := range mems {
		found := false
		for _, v := range elts {
			if k == v {
				found = true
				break
			}
		}
		if !found {
			c.Remove(k)
		}
	}
	for _, v := range elts {
		c.RLock()
		_, exists := c.members[v]
		c.RUnlock()
		if exists {
			continue
		}
		c.Add(v)
	}
}
func (c *Consistent) Members() []string {
	c.RLock()
	defer c.RUnlock()
	var m []string
	for k := range c.members {
		m = append(m, k)
	}
	return m
}
// Get returns an element close to where name hashes to in the circle.
func (c *Consistent) Get(name string) (string, error) {
	c.RLock()
	defer c.RUnlock()
	if len(c.circle) == 0 {
		return "", ErrEmptyCircle
	}
	key := c.hashKey(name)
	log.Println("need search --> key:",key,"servername:",name)
	i := c.search(key)
	fmt.Println(c.sortedHashes[i],c.circle[c.sortedHashes[i]])
	return c.circle[c.sortedHashes[i]], nil
}
func (c *Consistent) search(key uint32) (i int) {
	f := func(x int) bool {
		log.Println("i",i)
		// 拿不到相等的
		return c.sortedHashes[x] > key
	}
	i = sort.Search(len(c.sortedHashes), f)
	log.Println("I:",i)
	if i >= len(c.sortedHashes) {
		i = 0
	}
	return
}
// GetTwo returns the two closest distinct elements to the name input in the circle.
func (c *Consistent) GetTwo(name string) (string, string, error) {
	c.RLock()
	defer c.RUnlock()
	if len(c.circle) == 0 {
		return "", "", ErrEmptyCircle
	}
	//得到hashesw 值
	key := c.hashKey(name)
	//搜索hashes
	i := c.search(key)
	//获取值
	a := c.circle[c.sortedHashes[i]]
	//如果节点只有一个时,直接返回
	if c.count == 1 {
		return a, "", nil
	}
	start := i
	var b string
	for i = start + 1; i != start; i++ {
		if i >= len(c.sortedHashes) {
			i = 0
		}
		b = c.circle[c.sortedHashes[i]]
		//两个时候否为相同的节点,不是就返回
		if b != a {
			break
		}
	}
	return a, b, nil
}
// GetN returns the N closest distinct elements to the name input in the circle.
func (c *Consistent) GetN(name string, n int) ([]string, error) {
	c.RLock()
	defer c.RUnlock()
	if len(c.circle) == 0 {
		return nil, ErrEmptyCircle
	}
	if c.count < int64(n) {
		n = int(c.count)
	}
	var (
		key = c.hashKey(name)
		i = c.search(key)
		start = i
		res = make([]string, 0, n)
		elem = c.circle[c.sortedHashes[i]]
	)
	res = append(res, elem)
	if len(res) == n {
		return res, nil
	}
	for i = start + 1; i != start; i++ {
		if i >= len(c.sortedHashes) {
			i = 0
		}
		elem = c.circle[c.sortedHashes[i]]
		if !sliceContainsMember(res, elem) {
			res = append(res, elem)
		}
		if len(res) == n {
			break
		}
	}
	return res, nil
}
func (c *Consistent) hashKey(key string) uint32 {
	//
	log.Println("key string:",key)
	if len(key) < 64 {
		var scratch [64]byte
		copy(scratch[:], key)
		//log.Fatal(len(key), scratch)
		return crc32.ChecksumIEEE(scratch[:len(key)])
	}
	return crc32.ChecksumIEEE([]byte(key))
}
// 对hash 进行排序
func (c *Consistent) updateSortedHashes() {
	hashes := c.sortedHashes[:0]
	//reallocate if we're holding on to too much (1/4th)
	//log.Fatal("exit test:",cap(c.sortedHashes))
	if cap(c.sortedHashes)/(c.NumberOfReplicas*4) > len(c.circle) {
		hashes = nil
	}
	for k := range c.circle {
		hashes = append(hashes, k)
		log.Println(k)
	}
	sort.Sort(hashes)
	c.sortedHashes = hashes
	log.Println("tem hashes size :",len(hashes),len(c.sortedHashes))
}
func sliceContainsMember(set []string, member string) bool {
	for _, m := range set {
		if m == member {
			return true
		}
	}
	return false
}
func main() {
	c := New()
	//fmt.Printf("%T", D)
	c.Add("redis-1")
	c.Add("redis-2")
	c.Add("redis-3")
	log.Fatal(c.GetN("redis-2",1))
	v, ok := c.Get("redis-one")
	if ok == nil {
		for i, vv := range v {
			fmt.Println(i, vv)
		}
	}
	log.Println("members size:",len(c.members),"\tcircle size :",len(c.circle),"sortHashes:",len(c.sortedHashes),"scratch:",c.scratch)
	log.Println("sortHashes value:",c.sortedHashes)
	//log.Fatal("...")
}

其中有几点不是很理解,scratch 这个东西好像没用到,还有就是在计算虚拟节点时,他是使用'>'来计算的,假设我们设置一个节点redis,那满默认回事redis|1,redis|2..,这样进行节点分布,如果获取redis时,使用redis|1进行搜索,搜索出来就不是redis|1这个虚拟节点了,可能是其他节点。还有在求近距离节点是它是按升排序进行搜索的,而不考虑左右这个方式找最近节点。

本文来自:CSDN博客

感谢作者:laohan_

查看原文:golang consistent hash 菜鸟分析

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