Spring Cloud Alibaba——Nacos AP一致性策略 Distro

Eureka 一致性策略

Eureka是一个AP模式的服务发现框架，在Eureka集群模式下，Eureka采取的是Server之间互相广播各自的数据进行数据复制、更新操作；并且Eureka在客户端与注册中心出现网络故障时，依然能够获取服务注册信息——Eureka实现了客户端对于服务注册信息的缓存

@Singleton
public class DiscoveryClient implements EurekaClient {

private boolean fetchRegistryFromBackup() {
        try {
            @SuppressWarnings("deprecation")
            BackupRegistry backupRegistryInstance = newBackupRegistryInstance();
            if (null == backupRegistryInstance) { // backward compatibility with the old protected method, in case it is being used.
                backupRegistryInstance = backupRegistryProvider.get();
            }

            if (null != backupRegistryInstance) {
                Applications apps = null;
                if (isFetchingRemoteRegionRegistries()) {
                    String remoteRegionsStr = remoteRegionsToFetch.get();
                    if (null != remoteRegionsStr) {
                        apps = backupRegistryInstance.fetchRegistry(remoteRegionsStr.split(","));
                    }
                } else {
                    apps = backupRegistryInstance.fetchRegistry();
                }
                if (apps != null) {
                    final Applications applications = this.filterAndShuffle(apps);
                    applications.setAppsHashCode(applications.getReconcileHashCode());
                    localRegionApps.set(applications);
                    logTotalInstances();
                    logger.info("Fetched registry successfully from the backup");
                    return true;
                }
            } else {
                logger.warn("No backup registry instance defined & unable to find any discovery servers.");
            }
        } catch (Throwable e) {
            logger.warn("Cannot fetch applications from apps although backup registry was specified", e);
        }
        return false;
    }
}

正因为Eureka为了能够在Eureka集群无法工作时不影响消费者调用服务提供者而设置的客户端缓存，因此Eureka无法保证服务注册信息的强一致性（CP模式），只能满足数据的最终一致性（AP模式）

Nacos AP一致性策略——Distro

Nacos在AP模式下的一致性策略就类似于Eureka，采用Server之间互相的数据同步来实现数据在集群中的同步、复制操作。

触发数据广播

@DependsOn("ProtocolManager")
@org.springframework.stereotype.Service("distroConsistencyService")
public class DistroConsistencyServiceImpl implements EphemeralConsistencyService, DistroDataProcessor {

    private final GlobalConfig globalConfig;
    
    private final DistroProtocol distroProtocol;

    @Override
    public void put(String key, Record value) throws NacosException {
        onPut(key, value);
        distroProtocol.sync(new DistroKey(key, KeyBuilder.INSTANCE_LIST_KEY_PREFIX), DataOperation.CHANGE,
                globalConfig.getTaskDispatchPeriod() / 2);
    }
}

当服务注册和注销实例，即InstanceController的register和deregister方法被调用时，ServiceManager类中addInstance或removeInstance方法调用ConsistencyService接口定义的put、remove方法时，涉及到了Server端数据的变更，此时会创建一个任务DistroDelayTask，将数据的key封装到DistroDelayTask中。

@Component
public class DistroProtocol {

    public void sync(DistroKey distroKey, DataOperation action, long delay) {
        for (Member each : memberManager.allMembersWithoutSelf()) {
            //遍历所有服务ip。进行数据同步
            DistroKey distroKeyWithTarget = new DistroKey(distroKey.getResourceKey(), distroKey.getResourceType(),
                    each.getAddress());
            //创建延迟任务
            DistroDelayTask distroDelayTask = new DistroDelayTask(distroKeyWithTarget, action, delay);
            //其实也是一个定时任务
            distroTaskEngineHolder.getDelayTaskExecuteEngine().addTask(distroKeyWithTarget, distroDelayTask);
            if (Loggers.DISTRO.isDebugEnabled()) {
                Loggers.DISTRO.debug("[DISTRO-SCHEDULE] {} to {}", distroKey, each.getAddress());
            }
        }
    }
}

然后将DistroDelayTask提交到Nacos的延时任务执行引擎NacosDelayTaskExecuteEngine中的ConcurrentHashMap tasks中存储，并且NacosDelayTaskExecuteEngine在其构造方法中初始化ScheduledExecutorService线程池并提交一个ProcessRunnable任务去取出tasks中的AbstractDelayTask任务进行处理。

public class NacosDelayTaskExecuteEngine extends AbstractNacosTaskExecuteEngine {
    
    private final ScheduledExecutorService processingExecutor;
    
    protected final ConcurrentHashMap tasks;
    
    protected final ReentrantLock lock = new ReentrantLock();
    
    //NacosDelayTaskExecuteEngine实例化
    public NacosDelayTaskExecuteEngine(String name, int initCapacity, Logger logger, long processInterval) {
        super(logger);
        //初始化tasks
        tasks = new ConcurrentHashMap(initCapacity);
        //创建定时任务线程池
        processingExecutor = ExecutorFactory.newSingleScheduledExecutorService(new NameThreadFactory(name));
        //每间隔一段时间定时执行任务ProcessRunnable
        processingExecutor
                .scheduleWithFixedDelay(new ProcessRunnable(), processInterval, processInterval, TimeUnit.MILLISECONDS);
    }   

    @Override
    public void addTask(Object key, AbstractDelayTask newTask) {
        lock.lock();
        try {
            AbstractDelayTask existTask = tasks.get(key);
            //存在相同任务则合并
            if (null != existTask) {
                newTask.merge(existTask);
            }
            //将AbstractDelayTask存入tasks中
            tasks.put(key, newTask);
        } finally {
            lock.unlock();
        }
    }

ProcessRunnable线程处理存入延时任务执行引擎NacosDelayTaskExecuteEngine中的ConcurrentHashMap tasks中的任务

public class NacosDelayTaskExecuteEngine extends AbstractNacosTaskExecuteEngine {
    
    private final ScheduledExecutorService processingExecutor;
    
    protected final ConcurrentHashMap tasks;
    
    /**
     * process tasks in execute engine.
     */
    protected void processTasks() {
        //获取tasks中的所有key
        Collection