mirror of
https://github.com/woodchen-ink/proxy-go.git
synced 2025-07-18 08:31:55 +08:00
refactor(metrics): remove historical data handling and streamline collector logic
- Eliminated the historical data storage and related functions from the metrics collector to simplify the codebase. - Removed the historical data display section from the metrics template, enhancing clarity and focus on current metrics. - Updated the CheckDataConsistency method to implement a simpler validation check for total errors against total requests. These changes improve the maintainability of the metrics system by removing outdated features and ensuring a more straightforward data validation process.
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@ -568,22 +568,6 @@ var metricsTemplate = `
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</table>
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</div>
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<div class="card">
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<h2>历史数据</h2>
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<div class="controls" style="margin-bottom: 20px;">
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<label>
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<input type="checkbox" id="autoRefresh" checked>
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自动刷新
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</label>
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<select id="refreshInterval">
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<option value="5000">5秒</option>
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<option value="10000">10秒</option>
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<option value="30000">30秒</option>
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<option value="60000">1分钟</option>
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</select>
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</div>
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</div>
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<span id="lastUpdate"></span>
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<button class="refresh" onclick="refreshMetrics()">刷新</button>
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@ -38,22 +38,10 @@ type Collector struct {
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cache *cache.Cache
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monitor *monitor.Monitor
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statsPool sync.Pool
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// 添加历史数据存储
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historicalData struct {
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sync.RWMutex
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items []models.HistoricalMetrics
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}
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}
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var globalCollector *Collector
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const (
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// 数据变化率阈值
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highThreshold = 0.8 // 高变化率阈值
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lowThreshold = 0.2 // 低变化率阈值
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)
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func InitCollector(config *config.Config) error {
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globalCollector = &Collector{
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startTime: time.Now(),
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@ -86,15 +74,6 @@ func InitCollector(config *config.Config) error {
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// 设置最后保存时间
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lastSaveTime = time.Now()
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// 初始化历史数据存储
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globalCollector.historicalData.items = make([]models.HistoricalMetrics, 0, 1000)
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// 启动定期保存历史数据的goroutine
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go globalCollector.recordHistoricalData()
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// 启动定期清理历史数据的goroutine
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go globalCollector.cleanHistoricalData()
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return nil
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}
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@ -425,81 +404,6 @@ func formatAvgLatency(latencySum, requests int64) string {
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return FormatDuration(time.Duration(latencySum / requests))
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}
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// calculateChangeRate 计算数据变化率
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func calculateChangeRate(stats map[string]interface{}) float64 {
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// 获取当前值
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currentReqs, _ := stats["total_requests"].(int64)
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currentErrs, _ := stats["total_errors"].(int64)
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currentBytes, _ := stats["total_bytes"].(int64)
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// 计算变化率 (可以根据实际需求调整计算方法)
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var changeRate float64
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if currentReqs > 0 {
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// 计算请求数的变化率
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reqRate := float64(currentReqs) / float64(constants.MaxRequestsPerMinute)
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// 计算错误率的变化
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errRate := float64(currentErrs) / float64(currentReqs)
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// 计算流量的变化率
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bytesRate := float64(currentBytes) / float64(constants.MaxBytesPerMinute)
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// 综合评分
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changeRate = (reqRate + errRate + bytesRate) / 3
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}
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return changeRate
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}
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// CheckDataConsistency 检查数据一致性
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func (c *Collector) CheckDataConsistency() error {
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totalReqs := atomic.LoadInt64(&c.totalRequests)
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// 检查状态码统计
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var statusTotal int64
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for i := range c.statusStats {
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count := c.statusStats[i].Load()
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if count < 0 {
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return fmt.Errorf("invalid status code count: %d", count)
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}
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statusTotal += count
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}
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// 检查路径统计
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var pathTotal int64
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c.pathStats.Range(func(_, value interface{}) bool {
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stats := value.(*models.PathStats)
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count := stats.Requests.Load()
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if count < 0 {
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return false
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}
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pathTotal += count
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return true
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})
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// 修改一致性检查的逻辑
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// 1. 如果总数为0，不进行告警
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// 2. 增加容差范围到5%
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if totalReqs > 0 {
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tolerance := totalReqs / 20 // 5% 的容差
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if statusTotal > 0 && abs(statusTotal-totalReqs) > tolerance {
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log.Printf("Warning: Status code total (%d) differs from total requests (%d) by more than 5%%",
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statusTotal, totalReqs)
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}
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if pathTotal > 0 && abs(pathTotal-totalReqs) > tolerance {
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log.Printf("Warning: Path total (%d) differs from total requests (%d) by more than 5%%",
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pathTotal, totalReqs)
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}
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}
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return nil
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}
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func abs(x int64) int64 {
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if x < 0 {
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return -x
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}
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return x
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}
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// SaveBackup 保存数据备份
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func (c *Collector) SaveBackup() error {
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stats := c.GetStats()
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@ -563,81 +467,11 @@ func (c *Collector) GetLastSaveTime() time.Time {
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return lastSaveTime
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}
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// 定期记录历史数据
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func (c *Collector) recordHistoricalData() {
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ticker := time.NewTicker(5 * time.Minute)
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for range ticker.C {
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stats := c.GetStats()
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metric := models.HistoricalMetrics{
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Timestamp: time.Now().Format("2006-01-02 15:04:05"),
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TotalRequests: stats["total_requests"].(int64),
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TotalErrors: stats["total_errors"].(int64),
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TotalBytes: stats["total_bytes"].(int64),
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ErrorRate: stats["error_rate"].(float64),
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}
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if avgLatencyStr, ok := stats["avg_response_time"].(string); ok {
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if d, err := parseLatency(avgLatencyStr); err == nil {
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metric.AvgLatency = d
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}
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}
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c.historicalData.Lock()
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c.historicalData.items = append(c.historicalData.items, metric)
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c.historicalData.Unlock()
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// CheckDataConsistency 实现 interfaces.MetricsCollector 接口
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func (c *Collector) CheckDataConsistency() error {
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// 简单的数据验证
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if atomic.LoadInt64(&c.totalErrors) > atomic.LoadInt64(&c.totalRequests) {
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return fmt.Errorf("total errors exceeds total requests")
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}
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}
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// 定期清理30天前的数据
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func (c *Collector) cleanHistoricalData() {
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ticker := time.NewTicker(1 * time.Hour)
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for range ticker.C {
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threshold := time.Now().Add(-30 * 24 * time.Hour)
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c.historicalData.Lock()
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newItems := make([]models.HistoricalMetrics, 0)
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for _, item := range c.historicalData.items {
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timestamp, err := time.Parse("2006-01-02 15:04:05", item.Timestamp)
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if err == nil && timestamp.After(threshold) {
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newItems = append(newItems, item)
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}
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}
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c.historicalData.items = newItems
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c.historicalData.Unlock()
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}
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}
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// GetHistoricalData 获取历史数据
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func (c *Collector) GetHistoricalData() []models.HistoricalMetrics {
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c.historicalData.RLock()
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defer c.historicalData.RUnlock()
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result := make([]models.HistoricalMetrics, len(c.historicalData.items))
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copy(result, c.historicalData.items)
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return result
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}
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// parseLatency 解析延迟字符串
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func parseLatency(latency string) (float64, error) {
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var value float64
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var unit string
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_, err := fmt.Sscanf(latency, "%f %s", &value, &unit)
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if err != nil {
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return 0, err
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}
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// 根据单位转换为毫秒
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switch unit {
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case "μs":
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value = value / 1000 // 微秒转毫秒
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case "ms":
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// 已经是毫秒
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case "s":
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value = value * 1000 // 秒转毫秒
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default:
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return 0, fmt.Errorf("unknown unit: %s", unit)
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}
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return value, nil
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return nil
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}
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