- Author: shasha
- Description: 该文简单介绍微服务技术栈有哪些分别用来做什么
如何使用负载均衡算法
随机算法
- 随机算法,就是从可用服务节点随机挑选一个节点来访问
- 实现:随机算法通过生成随机数来实现,例如服务有10个节点,随机生成数字2,就访问2的这个节点
package com.weibo.api.motan.cluster.loadbalance;
import java.util.List;
import java.util.concurrent.ThreadLocalRandom;
import com.weibo.api.motan.core.extension.SpiMeta;
import com.weibo.api.motan.rpc.Referer;
import com.weibo.api.motan.rpc.Request;
@SpiMeta(name = "random")
public class RandomLoadBalance<T> extends AbstractLoadBalance<T> {
@Override
protected Referer<T> doSelect(Request request) {
List<Referer<T>> referers = getReferers();
int idx = (int) (ThreadLocalRandom.current().nextDouble() * referers.size());
for (int i = 0; i < referers.size(); i++) {
Referer<T> ref = referers.get((i + idx) % referers.size());
if (ref.isAvailable()) {
return ref;
}
}
return null;
}
@Override
protected void doSelectToHolder(Request request, List<Referer<T>> refersHolder) {
List<Referer<T>> referers = getReferers();
int idx = (int) (ThreadLocalRandom.current().nextDouble() * referers.size());
for (int i = 0; i < referers.size(); i++) {
Referer<T> referer = referers.get((i + idx) % referers.size());
if (referer.isAvailable()) {
refersHolder.add(referer);
}
}
}
}
轮询算法
- 轮询算法,就是按照指定的顺序,把可用的服务节点挨个访问一次
- 轮询算法通常是吧可用节点放到一个数组里面,然后按照数组编号,挨个访问。
package com.weibo.api.motan.cluster.loadbalance;
import java.util.List;
import java.util.concurrent.atomic.AtomicInteger;
import com.weibo.api.motan.core.extension.SpiMeta;
import com.weibo.api.motan.rpc.Referer;
import com.weibo.api.motan.rpc.Request;
import com.weibo.api.motan.util.MathUtil;
@SpiMeta(name = "roundrobin")
public class RoundRobinLoadBalance<T> extends AbstractLoadBalance<T> {
private AtomicInteger idx = new AtomicInteger(0);
@Override
protected Referer<T> doSelect(Request request) {
List<Referer<T>> referers = getReferers();
int index = getNextNonNegative();
for (int i = 0; i < referers.size(); i++) {
Referer<T> ref = referers.get((i + index) % referers.size());
if (ref.isAvailable()) {
return ref;
}
idx.incrementAndGet();
}
return null;
}
@Override
protected void doSelectToHolder(Request request, List<Referer<T>> refersHolder) {
List<Referer<T>> referers = getReferers();
int index = getNextNonNegative();
for (int i = 0, count = 0; i < referers.size() && count < MAX_REFERER_COUNT; i++) {
Referer<T> referer = referers.get((i + index) % referers.size());
if (referer.isAvailable()) {
refersHolder.add(referer);
count++;
}
}
}
private int getNextNonNegative() {
return MathUtil.getNonNegative(idx.incrementAndGet());
}
}
加权轮询算法
- 加权轮询就是给每个节点赋予一个权重,从而使每个节点被访问的概率不同,权重大的节点被访问的概率就高,权重小的节点被访问的概率就小。
- 实现:加权轮询就是生成一个随机序列,该序列里有n个节点,n是所有节点的权重之和,在这个序列中,每个节点出现的次数就是它的权重值,例如a,b,c三个权重值分别是3,2,1,那么它生成的序列就是{a,b,c,a,a,b}
package com.weibo.api.motan.cluster.loadbalance;
import com.weibo.api.motan.core.extension.SpiMeta;
import com.weibo.api.motan.rpc.Referer;
import com.weibo.api.motan.rpc.Request;
import com.weibo.api.motan.util.CollectionUtil;
import com.weibo.api.motan.util.LoggerUtil;
import com.weibo.api.motan.util.MathUtil;
import org.apache.commons.lang3.StringUtils;
import java.util.*;
import java.util.concurrent.ThreadLocalRandom;
import java.util.concurrent.atomic.AtomicInteger;
@SpiMeta(name = "configurableWeight")
public class ConfigurableWeightLoadBalance<T> extends ActiveWeightLoadBalance<T> {
@SuppressWarnings("rawtypes")
private static final RefererListCacheHolder emptyHolder = new EmptyHolder();
@SuppressWarnings("unchecked")
private volatile RefererListCacheHolder<T> holder = emptyHolder;
private String weightString;
@SuppressWarnings("unchecked")
@Override
public void onRefresh(List<Referer<T>> referers) {
super.onRefresh(referers);
if (CollectionUtil.isEmpty(referers)) {
holder = emptyHolder;
} else if (StringUtils.isEmpty(weightString)) {
holder = new SingleGroupHolder<T>(referers);
} else {
holder = new MultiGroupHolder<T>(weightString, referers);
}
}
@Override
protected Referer<T> doSelect(Request request) {
if (holder == emptyHolder) {
return null;
}
RefererListCacheHolder<T> h = this.holder;
Referer<T> r = h.next();
if (!r.isAvailable()) {
int retryTimes = getReferers().size() - 1;
for (int i = 0; i < retryTimes; i++) {
r = h.next();
if (r.isAvailable()) {
break;
}
}
}
if (r.isAvailable()) {
return r;
} else {
noAvailableReferer();
return null;
}
}
@Override
protected void doSelectToHolder(Request request, List<Referer<T>> refersHolder) {
if (holder == emptyHolder) {
return;
}
RefererListCacheHolder<T> h = this.holder;
int i = 0, j = 0;
while (i++ < getReferers().size()) {
Referer<T> r = h.next();
if (r.isAvailable()) {
refersHolder.add(r);
if (++j == MAX_REFERER_COUNT) {
return;
}
}
}
if (refersHolder.isEmpty()) {
noAvailableReferer();
}
}
private void noAvailableReferer() {
LoggerUtil.error(this.getClass().getSimpleName() + " 当前没有可用连接, pool.size=" + getReferers().size());
}
@Override
public void setWeightString(String weightString) {
this.weightString = weightString;
}
static abstract class RefererListCacheHolder<T> {
abstract Referer<T> next();
}
static class EmptyHolder<T> extends RefererListCacheHolder<T> {
@Override
Referer<T> next() {
return null;
}
}
@SuppressWarnings("hiding")
class SingleGroupHolder<T> extends RefererListCacheHolder<T> {
private int size;
private List<Referer<T>> cache;
SingleGroupHolder(List<Referer<T>> list) {
cache = list;
size = list.size();
LoggerUtil.info("ConfigurableWeightLoadBalance build new SingleGroupHolder.");
}
@Override
Referer<T> next() {
return cache.get(ThreadLocalRandom.current().nextInt(size));
}
}
@SuppressWarnings("hiding")
class MultiGroupHolder<T> extends RefererListCacheHolder<T> {
private int randomKeySize = 0;
private List<String> randomKeyList = new ArrayList<String>();
private Map<String, AtomicInteger> cursors = new HashMap<String, AtomicInteger>();
private Map<String, List<Referer<T>>> groupReferers = new HashMap<String, List<Referer<T>>>();
MultiGroupHolder(String weights, List<Referer<T>> list) {
LoggerUtil.info("ConfigurableWeightLoadBalance build new MultiGroupHolder. weights:" + weights);
String[] groupsAndWeights = weights.split(",");
int[] weightsArr = new int[groupsAndWeights.length];
Map<String, Integer> weightsMap = new HashMap<String, Integer>(groupsAndWeights.length);
int i = 0;
for (String groupAndWeight : groupsAndWeights) {
String[] gw = groupAndWeight.split(":");
if (gw.length == 2) {
Integer w = Integer.valueOf(gw[1]);
weightsMap.put(gw[0], w);
groupReferers.put(gw[0], new ArrayList<Referer<T>>());
weightsArr[i++] = w;
}
}
int weightGcd = findGcd(weightsArr);
if (weightGcd != 1) {
for(Map.Entry<String,Integer> entry: weightsMap.entrySet()) {
weightsMap.put(entry.getKey(),entry.getValue()/weightGcd);
}
}
for (Map.Entry<String, Integer> entry : weightsMap.entrySet()) {
for (int j = 0; j < entry.getValue(); j++) {
randomKeyList.add(entry.getKey());
}
}
Collections.shuffle(randomKeyList);
randomKeySize = randomKeyList.size();
for (String key : weightsMap.keySet()) {
cursors.put(key, new AtomicInteger(0));
}
for (Referer<T> referer : list) {
groupReferers.get(referer.getServiceUrl().getGroup()).add(referer);
}
}
@Override
Referer<T> next() {
String group = randomKeyList.get(ThreadLocalRandom.current().nextInt(randomKeySize));
AtomicInteger ai = cursors.get(group);
List<Referer<T>> referers = groupReferers.get(group);
return referers.get(MathUtil.getNonNegative(ai.getAndIncrement()) % referers.size());
}
private int findGcd(int n, int m) {
return (n == 0 || m == 0) ? n + m : findGcd(m, n % m);
}
private int findGcd(int[] arr) {
int i = 0;
for (; i < arr.length - 1; i++) {
arr[i + 1] = findGcd(arr[i], arr[i + 1]);
}
return findGcd(arr[i], arr[i - 1]);
}
}
}
最少活跃连接算法
- 最少活跃度算法,每一次访问都选择连接数最少的节点。连接数大的可以认为是处理请求慢,连接数小的可以认为是处理请求魁岸。
package com.weibo.api.motan.cluster.loadbalance;
import java.util.Collections;
import java.util.Comparator;
import java.util.List;
import java.util.Random;
import java.util.concurrent.ThreadLocalRandom;
import com.weibo.api.motan.core.extension.SpiMeta;
import com.weibo.api.motan.rpc.Referer;
import com.weibo.api.motan.rpc.Request;
@SpiMeta(name = "activeWeight")
public class ActiveWeightLoadBalance<T> extends AbstractLoadBalance<T> {
@Override
protected Referer<T> doSelect(Request request) {
List<Referer<T>> referers = getReferers();
int refererSize = referers.size();
int startIndex = ThreadLocalRandom.current().nextInt(refererSize);
int currentCursor = 0;
int currentAvailableCursor = 0;
Referer<T> referer = null;
while (currentAvailableCursor < MAX_REFERER_COUNT && currentCursor < refererSize) {
Referer<T> temp = referers.get((startIndex + currentCursor) % refererSize);
currentCursor++;
if (!temp.isAvailable()) {
continue;
}
currentAvailableCursor++;
if (referer == null) {
referer = temp;
} else {
if (compare(referer, temp) > 0) {
referer = temp;
}
}
}
return referer;
}
@Override
protected void doSelectToHolder(Request request, List<Referer<T>> refersHolder) {
List<Referer<T>> referers = getReferers();
int refererSize = referers.size();
int startIndex = ThreadLocalRandom.current().nextInt(refererSize);
int currentCursor = 0;
int currentAvailableCursor = 0;
while (currentAvailableCursor < MAX_REFERER_COUNT && currentCursor < refererSize) {
Referer<T> temp = referers.get((startIndex + currentCursor) % refererSize);
currentCursor++;
if (!temp.isAvailable()) {
continue;
}
currentAvailableCursor++;
refersHolder.add(temp);
}
Collections.sort(refersHolder, new LowActivePriorityComparator<T>());
}
private int compare(Referer<T> referer1, Referer<T> referer2) {
return referer1.activeRefererCount() - referer2.activeRefererCount();
}
static class LowActivePriorityComparator<T> implements Comparator<Referer<T>> {
@Override
public int compare(Referer<T> referer1, Referer<T> referer2) {
return referer1.activeRefererCount() - referer2.activeRefererCount();
}
}
}
一致hash算法
- 一致性hash算法,是通过某个hash函数,把同一个来源的请求都映射到同一个节点上。
package com.weibo.api.motan.cluster.loadbalance;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collections;
import java.util.List;
import com.weibo.api.motan.common.MotanConstants;
import com.weibo.api.motan.core.extension.SpiMeta;
import com.weibo.api.motan.rpc.Referer;
import com.weibo.api.motan.rpc.Request;
import com.weibo.api.motan.util.MathUtil;
@SpiMeta(name = "consistent")
public class ConsistentHashLoadBalance<T> extends AbstractLoadBalance<T> {
private List<Referer<T>> consistentHashReferers;
@Override
public void onRefresh(List<Referer<T>> referers) {
super.onRefresh(referers);
List<Referer<T>> copyReferers = new ArrayList<Referer<T>>(referers);
List<Referer<T>> tempRefers = new ArrayList<Referer<T>>();
for (int i = 0; i < MotanConstants.DEFAULT_CONSISTENT_HASH_BASE_LOOP; i++) {
Collections.shuffle(copyReferers);
for (Referer<T> ref : copyReferers) {
tempRefers.add(ref);
}
}
consistentHashReferers = tempRefers;
}
@Override
protected Referer<T> doSelect(Request request) {
int hash = getHash(request);
Referer<T> ref;
for (int i = 0; i < getReferers().size(); i++) {
ref = consistentHashReferers.get((hash + i) % consistentHashReferers.size());
if (ref.isAvailable()) {
return ref;
}
}
return null;
}
@Override
protected void doSelectToHolder(Request request, List<Referer<T>> refersHolder) {
List<Referer<T>> referers = getReferers();
int hash = getHash(request);
for (int i = 0; i < referers.size(); i++) {
Referer<T> ref = consistentHashReferers.get((hash + i) % consistentHashReferers.size());
if (ref.isAvailable()) {
refersHolder.add(ref);
}
}
}
private int getHash(Request request) {
int hashcode;
if (request.getArguments() == null || request.getArguments().length == 0) {
hashcode = request.hashCode();
} else {
hashcode = Arrays.hashCode(request.getArguments());
}
return MathUtil.getNonNegative(hashcode);
}
}
`