【sentinel】深入浅出之原理篇FlowSlot

FlowSlot则用于根据预设的限流规则，以及前面 slot 统计的状态，来进行限流。
官方文档：如何使用Sentinel

流控规则

public class FlowSlot extends AbstractLinkedProcessorSlot {

    @Override
    public void entry(Context context, ResourceWrapper resourceWrapper, DefaultNode node, int count,
                      boolean prioritized, Object... args) throws Throwable {
        //流控检查
        checkFlow(resourceWrapper, context, node, count, prioritized);
        fireEntry(context, resourceWrapper, node, count, prioritized, args);
    }

    void checkFlow(ResourceWrapper resource, Context context, DefaultNode node, int count, boolean prioritized) throws BlockException {
        // 获取该Resource对应配置的流控规则 一个resource可以指定多个规则
        Map> flowRules = FlowRuleManager.getFlowRuleMap();
        List rules = flowRules.get(resource.getName());
        if (rules != null) {
            for (FlowRule rule : rules) {
                //规则逐一校验
                if (!canPassCheck(rule, context, node, count, prioritized)) {
                    throw new FlowException(rule.getLimitApp(), rule);
                }
            }
        }
    }

    //检查是否通过
    boolean canPassCheck(FlowRule rule, Context context, DefaultNode node, int count, boolean prioritized) {
        return FlowRuleChecker.passCheck(rule, context, node, count, prioritized);
    }
    @Override
    public void exit(Context context, ResourceWrapper resourceWrapper, int count, Object... args) {
        fireExit(context, resourceWrapper, count, args);
    }
}

在流控检查的时候，判断是否对该Resource有配置规则，如果配置了流控规则，则逐一检查配置规则。在检查规则的时候，又分为集群控流或者单机控流,集群控流或者单机控流具体文档参考：https://www.jianshu.com/p/a52bf4073873
在流控的时候，首先要根据请求的Resource和请求策略(详细见上图)，选择流控节点，再根据不同的流控策略，选择不同的Controller去判断是否通过。

private static boolean passLocalCheck(FlowRule rule, Context context, DefaultNode node, int acquireCount,
                                      boolean prioritized) {
    Node selectedNode = selectNodeByRequesterAndStrategy(rule, context, node);
    if (selectedNode == null) {
        return true;
    }
    //判断是否通过
    return rule.getRater().canPass(selectedNode, acquireCount);
}


//根据请求选择节点
static Node selectNodeByRequesterAndStrategy(/*@NonNull*/ FlowRule rule, Context context, DefaultNode node) {
    // The limit app should not be empty.
    String limitApp = rule.getLimitApp();
    int strategy = rule.getStrategy();
    String origin = context.getOrigin();
    if (limitApp.equals(origin) && filterOrigin(origin)) {
        if (strategy == RuleConstant.STRATEGY_DIRECT) {
            // Matches limit origin, return origin statistic node.
            return context.getOriginNode();
        }
        return selectReferenceNode(rule, context, node);
    } else if (RuleConstant.LIMIT_APP_DEFAULT.equals(limitApp)) {
        if (strategy == RuleConstant.STRATEGY_DIRECT) {
            // Return the cluster node.
            return node.getClusterNode();
        }
        return selectReferenceNode(rule, context, node);
    } else if (RuleConstant.LIMIT_APP_OTHER.equals(limitApp)
        && FlowRuleManager.isOtherOrigin(origin, rule.getResource())) {
        if (strategy == RuleConstant.STRATEGY_DIRECT) {
            return context.getOriginNode();
        }
        return selectReferenceNode(rule, context, node);
    }
    return null;
}

Controller.png

根据配置FlowRule配置的controlBehavior选择不同的Controller
对应关系：

• 1. default(reject directly) DefaultController
• 1. warm up WarmUpController
• 2. rate limiter RateLimiterController
• 3. warm up + rate limiter WarmUpRateLimiter

在默认的Controller中，首先获取当前的线程数，或者QPS数，当当前的线程数或者QPS+申请的数量>配置的总数，则不通过，如果当前线程数或者QPS+申请的数量<=配置的总数，则直接通过。

public class DefaultController implements TrafficShapingController {

    private static final int DEFAULT_AVG_USED_TOKENS = 0;
    private double count;
    private int grade;
    @Override
    public boolean canPass(Node node, int acquireCount) {
        return canPass(node, acquireCount, false);
    }

    @Override
    public boolean canPass(Node node, int acquireCount, boolean prioritized) {
        //获取当前node节点的线程数或者请求的qps总数
        int curCount = avgUsedTokens(node);
        //当前请求数+申请总数是否>该资源配置的总数
        if (curCount + acquireCount > count) {
            return false;
        }
        return true;
    }

    //获取当前node节点的线程数或者请求的qps总数
    private int avgUsedTokens(Node node) {
        if (node == null) {
            return DEFAULT_AVG_USED_TOKENS;
        }
        return grade == RuleConstant.FLOW_GRADE_THREAD ? node.curThreadNum() : (int) node.passQps();
    }

    private void sleep(int timeMillis) {
        try {
            Thread.sleep(timeMillis);
        } catch (InterruptedException e) {
            // Ignore.
        }
    }
}

和其他Slot一样，FlowRule的配置在FlowRuleManager#loadRules (List rules)的，最终更新由FlowPropertyListener来完成。

public static void loadRules(List rules) {
       currentProperty.updateValue(rules);
}

private static final class FlowPropertyListener implements PropertyListener> {

    @Override
    public void configUpdate(List value) {
        Map> rules = FlowRuleUtil.buildFlowRuleMap(value);
        if (rules != null) {
            flowRules.clear();
            flowRules.putAll(rules);
        }
        RecordLog.info("[FlowRuleManager] Flow rules received: " + flowRules);
    }

    @Override
    public void configLoad(List conf) {
        Map> rules = FlowRuleUtil.buildFlowRuleMap(conf);
        if (rules != null) {
            flowRules.clear();
            flowRules.putAll(rules);
        }
        RecordLog.info("[FlowRuleManager] Flow rules loaded: " + flowRules);
    }
}