fix(metrics): 优化延迟统计和分布数据处理

- 修复延迟统计分布数据获取逻辑,增加更健壮的类型转换
- 确保延迟分布桶始终存在,即使没有数据
- 在处理器中为空分布数据添加默认初始化
- 优化指标收集器中的延迟桶初始化和数据获取方法
This commit is contained in:
wood chen 2025-03-09 11:33:47 +08:00
parent b6b77b03ed
commit 2cb88a4f5e
2 changed files with 40 additions and 16 deletions

View File

@ -161,14 +161,31 @@ func (h *ProxyHandler) MetricsHandler(w http.ResponseWriter, r *http.Request) {
metrics.LatencyStats.Max = utils.SafeString(latencyStats["max"], "0ms") metrics.LatencyStats.Max = utils.SafeString(latencyStats["max"], "0ms")
// 处理分布数据 // 处理分布数据
if distribution, ok := latencyStats["distribution"].(map[string]interface{}); ok { if stats["latency_stats"] != nil {
if distribution, ok := stats["latency_stats"].(map[string]interface{})["distribution"]; ok && distribution != nil {
if distributionMap, ok := distribution.(map[string]interface{}); ok {
metrics.LatencyStats.Distribution = make(map[string]int64) metrics.LatencyStats.Distribution = make(map[string]int64)
for k, v := range distribution { for k, v := range distributionMap {
if intValue, ok := v.(float64); ok { if intValue, ok := v.(float64); ok {
metrics.LatencyStats.Distribution[k] = int64(intValue) metrics.LatencyStats.Distribution[k] = int64(intValue)
} else if intValue, ok := v.(int64); ok {
metrics.LatencyStats.Distribution[k] = intValue
} }
} }
} }
}
}
// 如果分布数据为空,初始化一个空的分布
if metrics.LatencyStats.Distribution == nil {
metrics.LatencyStats.Distribution = make(map[string]int64)
// 添加默认的延迟桶
metrics.LatencyStats.Distribution["<10ms"] = 0
metrics.LatencyStats.Distribution["10-50ms"] = 0
metrics.LatencyStats.Distribution["50-200ms"] = 0
metrics.LatencyStats.Distribution["200-1000ms"] = 0
metrics.LatencyStats.Distribution[">1s"] = 0
}
// 填充错误统计数据 // 填充错误统计数据
metrics.ErrorStats.ClientErrors = clientErrors metrics.ErrorStats.ClientErrors = clientErrors

View File

@ -61,11 +61,12 @@ func InitCollector(cfg *config.Config) error {
instance.bandwidthStats.history = make(map[string]int64) instance.bandwidthStats.history = make(map[string]int64)
// 初始化延迟分布桶 // 初始化延迟分布桶
instance.latencyBuckets.Store("<10ms", new(int64)) buckets := []string{"<10ms", "10-50ms", "50-200ms", "200-1000ms", ">1s"}
instance.latencyBuckets.Store("10-50ms", new(int64)) for _, bucket := range buckets {
instance.latencyBuckets.Store("50-200ms", new(int64)) counter := new(int64)
instance.latencyBuckets.Store("200-1000ms", new(int64)) *counter = 0
instance.latencyBuckets.Store(">1s", new(int64)) instance.latencyBuckets.Store(bucket, counter)
}
// 启动数据一致性检查器 // 启动数据一致性检查器
instance.startConsistencyChecker() instance.startConsistencyChecker()
@ -344,14 +345,20 @@ func (c *Collector) GetStats() map[string]interface{} {
// 收集延迟分布 // 收集延迟分布
latencyDistribution := make(map[string]int64) latencyDistribution := make(map[string]int64)
c.latencyBuckets.Range(func(key, value interface{}) bool {
if counter, ok := value.(*int64); ok { // 确保所有桶都存在即使计数为0
latencyDistribution[key.(string)] = atomic.LoadInt64(counter) buckets := []string{"<10ms", "10-50ms", "50-200ms", "200-1000ms", ">1s"}
for _, bucket := range buckets {
if counter, ok := c.latencyBuckets.Load(bucket); ok {
if counter != nil {
latencyDistribution[bucket] = atomic.LoadInt64(counter.(*int64))
} else { } else {
latencyDistribution[key.(string)] = value.(int64) latencyDistribution[bucket] = 0
}
} else {
latencyDistribution[bucket] = 0
}
} }
return true
})
// 获取最近请求记录(使用读锁) // 获取最近请求记录(使用读锁)
recentRequests := c.recentRequests.GetAll() recentRequests := c.recentRequests.GetAll()