1、完全隨機算法
缺點：所有服務器的訪問概率都是相同的。
package com.example.demo.core.random;
import JAVA.util.Arrays;
import java.util.List;
import java.util.Random;
/**
* 負載均衡算法
* 完全隨機算法
*/
public class RandomServer {
public static List<String> list = Arrays.asList("10.180.11.126:8888","10.180.11.128:8888","10.180.11.130:8888");
static Random random = new Random();
public static String getServer() {
int number = random.nextInt(list.size());
return list.get(number);
}
public static void main(String[] args) {
for(int i = 0; i < 15; i++) {
System.out.println(getServer());
}
}
}
2、加權隨機算法
場景：有的服務器性能高，可以讓隨機到此服務器的可能性增大
缺點：權重低的服務器可能很長一段時間都訪問不到3
package com.example.demo.core.random;
import java.util.*;
/**
* 負載均衡算法
*
* 如果某一臺服務器性能比較高，設置訪問的權重高一點
*
* 加權隨機算法
*/
public class WeightRandomServer {
public static Map<String,Integer> map = new HashMap<>();
static {
map.put("10.180.11.126:8888",2);
map.put("10.180.11.128:8888",7);
map.put("10.180.11.130:8888",1);
}
static Random random = new Random();
/**
* 當權重設置過大時，list容易被撐爆
* @return
*/
public static String getServer() {
List<String> list = new ArrayList<>();
for(Map.Entry<String,Integer> entry: map.entrySet()) {
//根據權重，決定向list中添加幾次
for(int i = 0; i < entry.getValue(); i++) {
list.add(entry.getKey());
}
}
//list的大小
int weight = map.values().stream().mapToInt(p -> p).sum();
int number = random.nextInt(weight);
return list.get(number);
}
/**
* 優化后
* @return
*/
public static String getServer1() {
//計算總權值
int weight = map.values().stream().mapToInt(p -> p).sum();
//隨機一個隨機數
int index = random.nextInt(weight);
//遍歷 服務 map
for(Map.Entry<String,Integer> entry : map.entrySet()) {
//如果權重大于 索引
if(entry.getValue() >= index) {
// 返回這個服務
return entry.getKey();
}
//否則，索引 = 當前索引 - 當前服務的權重
index = index - entry.getValue();
}
return "";
}
public static void main(String[] args) {
for(int i = 0; i < 15; i++) {
//System.out.println(getServer());
System.out.println(getServer1());
}
}
}
3、完全輪詢算法
缺點：從頭到尾輪詢一遍，不能根據服務器性能設置權重
package com.example.demo.core.poll;
import java.util.Arrays;
import java.util.List;
/**
* 完全輪詢算法
*/
public class PollServer {
public static List<String> list = Arrays.asList("10.180.11.126:8888","10.180.11.128:8888","10.180.11.130:8888");
static int index;
public static String getServer() {
if(index == list.size()) {
index = 0;
}
return list.get(index++);
}
public static void main(String[] args) {
for(int i = 0; i < 15; i++) {
System.out.println(getServer());
}
}
}
4、加權輪詢算法
有點：可以根據服務器性能設置訪問權重
缺點：可能某個服務器權重大，長時間執行，遇到耗時大的請求，壓力會很大
package com.example.demo.core.poll;
import java.util.HashMap;
import java.util.Map;
/**
* 加權輪詢算法
* 實際中可能遇到某個服務器壓力較大，長時間執行。
*/
public class WeightPollServer {
public static Map<String,Integer> map = new HashMap<>();
static {
map.put("10.180.11.126:8888",2);
map.put("10.180.11.128:8888",7);
map.put("10.180.11.130:8888",5);
}
static int index;
public static String getServer() {
int weight = map.values().stream().mapToInt( p -> p).sum();
int number = (index++) % weight;
for(Map.Entry<String,Integer> entry : map.entrySet()) {
if(entry.getValue() >= number) {
return entry.getKey();
}
number = number - entry.getValue();
}
return "";
}
public static void main(String[] args) {
for(int i = 0; i < 15; i++) {
System.out.println(getServer());
}
}
}
5、平滑加權輪詢算法
優點：根據權重分配服務，同時又保證權重低的服務可以被訪問到
缺點：集群環境下，同一個用戶訪問無法分流到固定一臺機器
package com.example.demo.core.smooth;
/**
* 平滑加權
*/
public class SmoothWeight {
private int weight;
private int currentWeight;
private String address;
public int getWeight() {
return weight;
}
public void setWeight(int weight) {
this.weight = weight;
}
public int getCurrentWeight() {
return currentWeight;
}
public void setCurrentWeight(int currentWeight) {
this.currentWeight = currentWeight;
}
public String getAddress() {
return address;
}
public void setAddress(String address) {
this.address = address;
}
public SmoothWeight(int weight, int currentWeight, String address) {
this.weight = weight;
this.currentWeight = currentWeight;
this.address = address;
}
}
package com.example.demo.core.smooth;
import java.util.HashMap;
import java.util.Map;
/**
* 平滑加權輪詢算法
*/
public class SmoothWeightPollServer {
public static Map<String,SmoothWeight> map = new HashMap<>();
static {
map.put("10.180.11.126:8888",new SmoothWeight(5,5,"10.180.11.126:8888"));
map.put("10.180.11.128:8888",new SmoothWeight(2,2,"10.180.11.128:8888"));
map.put("10.180.11.130:8888",new SmoothWeight(4,4,"10.180.11.130:8888"));
}
public static String getServer() {
SmoothWeight maxSmoothWeight = null;
int weight = map.values().stream().mapToInt(SmoothWeight :: getWeight).sum();
for(Map.Entry<String,SmoothWeight> entry : map.entrySet()) {
SmoothWeight currentSmoothWeight = entry.getValue();
if(maxSmoothWeight == null || currentSmoothWeight.getCurrentWeight() > maxSmoothWeight.getCurrentWeight()) {
maxSmoothWeight = currentSmoothWeight;
}
}
assert maxSmoothWeight != null;
maxSmoothWeight.setCurrentWeight(maxSmoothWeight.getCurrentWeight() - weight);
for(Map.Entry<String,SmoothWeight> entry : map.entrySet()) {
SmoothWeight currentSmoothWeight = entry.getValue();
currentSmoothWeight.setCurrentWeight(currentSmoothWeight.getCurrentWeight() + currentSmoothWeight.getWeight());
}
return maxSmoothWeight.getAddress();
}
public static void main(String[] args) {
for(int i = 0; i < 15; i++) {
System.out.println(getServer());
}
}
}
6、哈希負載算法
package com.example.demo.core.hash;
import java.util.Arrays;
import java.util.List;
import java.util.SortedMap;
import java.util.TreeMap;
/**
* hash負載算法
* 在一個集群環境下，讓同一個用戶的訪問，分流到固定的一臺機器上
*/
public class HashServer {
public static List<String> list = Arrays.asList("10.180.11.126:8888","10.180.11.128:8888","10.180.11.130:8888");
public static String getServer(String client){
int nodeCount = 40;
TreeMap<Integer,String> treeMap = new TreeMap<>();
for(String s : list) {
for(int i = 0; i < nodeCount; i++) {
treeMap.put((s + "address:" + i).hashCode(), s);
}
}
SortedMap<Integer,String> sortedMap = treeMap.tailMap(client.hashCode());
Integer firstHash = (sortedMap.size() > 0) ? sortedMap.firstKey() : treeMap.firstKey();
return treeMap.get(firstHash);
}
public static void main(String[] args) {
for(int i = 0; i < 100; i++) {
System.out.println(getServer("用戶：" + i + "訪問"));
}
}
}
