package com.mytest;
import java.io.Serializable;
import java.math.BigDecimal;
import java.util.ArrayList;
import java.util.Collections;
import java.util.Comparator;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Random;
import org.apache.commons.lang3.StringUtils;
class MsgChannel implements Serializable{
private static final long serialVersionUID = 1895082597124213342L;
private String id;
private String name;
private String signName;
private int status;//状态
private int priority;//权重
private Map<String,String> paramMap = new HashMap<>();
public String getId() {
return id;
}
public void setId(String id) {
this.id = id;
}
public String getName() {
return name;
}
public void setName(String name) {
this.name = name;
}
public String getSignName() {
return signName;
}
public void setSignName(String signName) {
this.signName = signName;
}
public int getStatus() {
return status;
}
public void setStatus(int status) {
this.status = status;
}
public void addParam(String key,String value){
paramMap.put(key,value);
}
public String getParam(String key){
String s= paramMap.get(key);
return s==null?"":s;
}
public int getParamInt(String key){
String v = paramMap.get(key);
if(StringUtils.isBlank(v)){
return 0;
}
try{
return Integer.parseInt(v);
}catch(Exception e){
return 0;
}
}
public Map<String, String> getParamMap() {
return paramMap;
}
public void setParamMap(Map<String, String> paramMap) {
this.paramMap = paramMap;
}
/**
* @return the priority
*/
public int getPriority() {
return priority;
}
/**
* @param priority the priority to set
*/
public void setPriority(int priority) {
this.priority = priority;
}
}
/**
* @author coolboyysy [coolboyysy @126.com]
* @since 15-3-6
*/
public class RandomAverageUtil {
/**
* 通过权值来获取渠道id
* 算法: 例如权值为1,2,3,5 则总权值为11 ，分为4档，[1][2-3][4-6][7-11]随机抽取11内自然数，落在哪个区间内就只该权值的值,随机命中率为1/11,2/11,3/11,5/11。
* 即便是权值均等，此方法也一样适用。
* 特点：时间复杂度为T(n) = O(n)
* 使用累计方法获取对应的channel,例如：11的总权值，我随机抽到7，则比对，0+1，0+1+2，0+1+2+3，0+1+2+3+5四次，在第四次获取到的即为选中的channel
* @param channels
* @return
*/
public static MsgChannel getSpecialChannel(List<MsgChannel> channels){
MsgChannel luckChannel = null;
if(null!=channels&&channels.size()>0){
int totalrate = 0;
for (MsgChannel channel:channels) {
totalrate = totalrate+channel.getPriority();
}
if(totalrate==0){
int index = (int) (Math.random() * channels.size());
luckChannel = channels.get(index);
return luckChannel;
}
int hitnumber = new Random().nextInt(totalrate);
int tmp_total = 0;
for (MsgChannel channel:channels) {
tmp_total += channel.getPriority();
if (tmp_total >= hitnumber) {
luckChannel = channel;
break;
}
}
}
return luckChannel;
}
/**
* 通过权值来获取渠道id
* 算法: 例如权值为1,2,3,5 则总权值为11 ，分为11档，填入[0-11)内自然数，随机取值,随机命中率为1/11,2/11,3/11,5/11。
* 即便是权值均等，此方法也一样适用。
* 特点：时间复杂度为T(n) = O(n^2)
* 使用累计方法获取对应的channel,例如：11的总权值，我随机抽到7，则直接取得7对应的channel
* @param channels
* @return
*/
public static MsgChannel getLuckyChannel(List<MsgChannel> channels){
MsgChannel luckChannel = null;
if(null!=channels&&channels.size()>0){
int totalrate = 0;
Map<Integer,MsgChannel> map = new HashMap<>();
for (MsgChannel channel:channels) {
for (int j = totalrate; j < totalrate+channel.getPriority(); j++) {
map.put(j, channel);
}
totalrate += channel.getPriority();
}
if(totalrate==0){
int index = (int) (Math.random() * channels.size());
luckChannel = channels.get(index);
return luckChannel;
}
int hitnumber = new Random().nextInt(totalrate);
luckChannel = map.get(hitnumber);
}
return luckChannel;
}
/**
* 通过权值来获取渠道id
* 算法: 例如权值为1,2,3,5 则总权值为11 ，分为11档，在数组内填入[0-11)内自然数，map 中填入对应id的channel，随机取值,随机命中率为1/11,2/11,3/11,5/11。
* 即便是权值均等，此方法也一样适用。
* 特点：时间复杂度为T(n) = O(n^2+1)
* 使用累计方法获取对应的channel,例如：11的总权值，我随机抽到7，则直接取得index为7对应的map中的channel
* @param channels
* @return
*/
public static MsgChannel getLuckChannel(List<MsgChannel> channels){
MsgChannel luckChannel = null;
if(null!=channels&&channels.size()>0){
int totalrate = 0;
int sum = 0;
for (MsgChannel channel:channels) {
sum += channel.getPriority();
}
if(sum==0){
int index = (int) (Math.random() * channels.size());
luckChannel = channels.get(index);
return luckChannel;
}
int[] temp = new int[sum];
Map<Integer,MsgChannel> map = new HashMap<>();
for (MsgChannel channel:channels) {
for (int j = totalrate; j < totalrate+channel.getPriority(); j++) {
temp[j]=j;
map.put(j, channel);
}
totalrate += channel.getPriority();
}
int index = (int) (Math.random() * temp.length);
luckChannel = map.get(index);
}
return luckChannel;
}
/**
* 通过权值来获取渠道id
* 算法: 例如权值为1,2,3,5 则总权值为11 ，分为11档，填入[0-11)内自然数为key的map中，随机取值,随机命中率为1/11,2/11,3/11,5/11。
* 即便是权值均等，此方法也一样适用。
* 特点：时间复杂度为T(n) = O(n^2)
* 使用累计方法获取对应的channel,例如：11的总权值，我随机抽到7，则直接取得index为7对应的map中的channel
* 但随机抽取方法是按时间来做，因此，随着系统时间的不同，会有不同的几率表现，在瞬时大规模时候，偏向其中几个。适合随着时间长度增加而进行的随机平均算法
* @param channels
* @return
*/
public static MsgChannel getTimeLuckChannel(List<MsgChannel> channels){
MsgChannel luckChannel = null;
if(null!=channels&&channels.size()>0){
int totalrate = 0;
Map<Integer,MsgChannel> map = new HashMap<>();
for (MsgChannel channel:channels) {
for (int j = totalrate; j < totalrate+channel.getPriority(); j++) {
map.put(j, channel);
}
totalrate += channel.getPriority();
}
if(totalrate>0){
int index = (int) (System.currentTimeMillis()%totalrate)+1;
luckChannel = map.get(index);
}else{
int index = (int) (Math.random() * channels.size());
luckChannel = channels.get(index);
}
}
return luckChannel;
}
/**
* 算术除法运算
* @param a
* @param b
* @return
*/
public static String devideNum(int a,int b){
if(b==0){
return String.valueOf(a);
}
BigDecimal bda = new BigDecimal(String.valueOf(a));
BigDecimal bdb = new BigDecimal(String.valueOf(b));
bda.setScale(5,BigDecimal.ROUND_HALF_UP);
bdb.setScale(5,BigDecimal.ROUND_HALF_UP);
BigDecimal res = bda.divide(bdb,5,BigDecimal.ROUND_HALF_UP);
double f =res.setScale(5,BigDecimal.ROUND_HALF_UP).doubleValue();
return String.format("%.2f", f);
}
/**
* Map排序算法
* @param map
*/
public static void sortMap(Map<MsgChannel, Integer> map){
List<Map.Entry<MsgChannel, Integer>> infoIds = new ArrayList<Map.Entry<MsgChannel, Integer>>(map.entrySet());
// 排序
Collections.sort(infoIds, new Comparator<Map.Entry<MsgChannel, Integer>>() {
public int compare(Map.Entry<MsgChannel, Integer> o1,Map.Entry<MsgChannel, Integer> o2) {
return (o1.getValue()-o2.getValue());
}
});
}
public static void main(String[] args) {
long startTime = System.currentTimeMillis();
int total = 0;
List<MsgChannel> channels = new ArrayList<MsgChannel>();
int channelNum = 5;
for (int i = 1; i <=channelNum; i++) {
MsgChannel channel = new MsgChannel();
channel.setId(String.valueOf(i));
channel.setName("第"+i+"个");
channel.setSignName("hello"+i);
channel.setParamMap(new HashMap<String,String>(i));
channel.setPriority( new Random().nextInt(200));
channels.add(channel);
}
for (MsgChannel channel: channels) {
total +=channel.getPriority();
System.out.println("channelid: "+channel.getId()+" 权值: "+channel.getPriority());
}
int loopnum = 1000;
Map<MsgChannel,Integer> hitmap1 = new HashMap<MsgChannel,Integer>();
Map<MsgChannel,Integer> hitmap2 = new HashMap<MsgChannel,Integer>();
Map<MsgChannel,Integer> hitmap3 = new HashMap<MsgChannel,Integer>();
Map<MsgChannel,Integer> hitmap4 = new HashMap<MsgChannel,Integer>();
long start1Time = System.currentTimeMillis();
for (int i = 0; i < loopnum; i++) {
MsgChannel channel1 = getSpecialChannel(channels);
if(null!=hitmap1.get(channel1)){
int num = hitmap1.get(channel1);
num =num+1;
hitmap1.put(channel1, num);
}else{
int num =1;
hitmap1.put(channel1, num);
}
}
System.out.println("第一个方法耗时:"+(System.currentTimeMillis()-start1Time)+"毫秒");
long start2Time = System.currentTimeMillis();
for (int i = 0; i < loopnum; i++) {
MsgChannel channel2 = getLuckyChannel(channels);
if(null!=hitmap2.get(channel2)){
int num = hitmap2.get(channel2);
num =num+1;
hitmap2.put(channel2, num);
}else{
int num =1;
hitmap2.put(channel2, num);
}
}
System.out.println("第二个方法耗时:"+(System.currentTimeMillis()-start2Time)+"毫秒");
long start3Time = System.currentTimeMillis();
for (int i = 0; i < loopnum; i++) {
MsgChannel channel3 = getLuckChannel(channels);
if(null!=hitmap3.get(channel3)){
int num = hitmap3.get(channel3);
num =num+1;
hitmap3.put(channel3, num);
}else{
int num =1;
hitmap3.put(channel3, num);
}
}
System.out.println("第三个方法耗时:"+(System.currentTimeMillis()-start3Time)+"毫秒");
long start4Time = System.currentTimeMillis();
for (int i = 0; i < loopnum; i++) {
try {
Thread.sleep(1);
} catch (InterruptedException e) {
e.printStackTrace();
}
MsgChannel channel4 = getTimeLuckChannel(channels);
if(null!=hitmap4.get(channel4)){
int num = hitmap4.get(channel4);
num =num+1;
hitmap4.put(channel4, num);
}else{
int num =1;
hitmap4.put(channel4, num);
}
}
System.out.println("第四个方法耗时:"+(System.currentTimeMillis()-start4Time)+"毫秒");
sortMap(hitmap1);
sortMap(hitmap2);
sortMap(hitmap3);
sortMap(hitmap4);
long endTime = System.currentTimeMillis();
System.out.println("总循环次数"+loopnum+" 总共耗时："+(endTime-startTime)+"毫秒");
System.out.println("总权值数目:"+total);
for (MsgChannel channel: channels) {
System.out.println("channelid: "+channel.getId()+" 算术平均几率: "+devideNum(channel.getPriority()*100,total)+"% 权值: "+channel.getPriority());
}
for (MsgChannel channel:hitmap1.keySet()) {
if(null!=channel&&null!=hitmap3.get(channel)){
System.out.println("第一个方法： channelid: "+channel.getId()+" 几率: "+devideNum(hitmap1.get(channel)*100,loopnum)+"% 权值: "+channel.getPriority());
}
}
for (MsgChannel channel:hitmap2.keySet()) {
if(null!=channel&&null!=hitmap3.get(channel)){
System.out.println("第二个方法： channelid: "+channel.getId()+" 几率: "+devideNum(hitmap2.get(channel)*100,loopnum)+"% 权值: "+channel.getPriority());
}
}
for (MsgChannel channel:hitmap3.keySet()) {
if(null!=channel&&null!=hitmap3.get(channel)){
System.out.println("第三个方法： channelid: "+channel.getId()+" 几率: "+devideNum(hitmap3.get(channel)*100,loopnum)+"% 权值: "+channel.getPriority());
}
}
for (MsgChannel channel:hitmap4.keySet()) {
if(null!=channel&&null!=hitmap4.get(channel)){
System.out.println("第四个方法： channelid: "+channel.getId()+" 几率: "+devideNum(hitmap4.get(channel)*100,loopnum)+"% 权值: "+channel.getPriority());
}
}
}
}
通过权值来获取渠道的平均算法
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转载自coolboyysy.iteye.com/blog/2189814
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