huang
2a7ac3f86e
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- OnCardStatusChanged/Enabled/Disabled 添加 InvalidateCardCache， 解决 Refresh API 更新 DB 后 polling 缓存仍为旧值的 bug - AssetResolveResponse 的 enable_polling/network_status 去掉 omitempty，解决 false/0 时字段从响应中消失的问题 - Scheduler/Initializer/PackageHandler 增加 INFO 级别日志， 可通过日志判断轮询是否工作、处理了哪些卡
306 lines
8.8 KiB
Go
306 lines
8.8 KiB
Go
package polling
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import (
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"context"
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"fmt"
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"sync"
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"sync/atomic"
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"time"
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"github.com/redis/go-redis/v9"
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"go.uber.org/zap"
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"github.com/break/junhong_cmp_fiber/internal/model"
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"github.com/break/junhong_cmp_fiber/internal/store/postgres"
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"github.com/break/junhong_cmp_fiber/pkg/constants"
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)
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// initProgress 初始化进度内部状态（字段通过 GetProgress 快照对外，避免暴露锁）
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type initProgress struct {
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mu sync.RWMutex
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totalCards int64
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loadedCards int64
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startTime time.Time
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lastBatchTime time.Time
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status string
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errorMessage string
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}
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// InitProgress 初始化进度快照（GetProgress 返回的值拷贝，调用方无需加锁）
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type InitProgress struct {
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TotalCards int64 `json:"total_cards"`
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LoadedCards int64 `json:"loaded_cards"`
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StartTime time.Time `json:"start_time"`
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LastBatchTime time.Time `json:"last_batch_time"`
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Status string `json:"status"`
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ErrorMessage string `json:"error_message"`
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}
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// pipelineFlushSize 单次 Pipeline Exec 最大命令数（每张卡最多 6 条）
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// 10000 条约 2MB 内存峰值；千万级卡下约 6000 次 Exec，RTT 总开销可忽略
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const pipelineFlushSize = 10000
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// PollingInitializer 分片渐进式初始化器
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// 启动时从 DB 分批加载全量卡数据到分片 Sorted Set
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// 使用 card_id % shardCount 分片，每 pipelineFlushSize 条命令 flush 一次 Pipeline
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type PollingInitializer struct {
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iotCardStore *postgres.IotCardStore
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redis *redis.Client
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configMgr *PollingConfigManager
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queueMgr *PollingQueueManager
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logger *zap.Logger
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progress initProgress
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initCompleted atomic.Bool
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stopChan chan struct{}
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wg sync.WaitGroup
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}
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// NewPollingInitializer 创建初始化器
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func NewPollingInitializer(
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iotCardStore *postgres.IotCardStore,
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redisClient *redis.Client,
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configMgr *PollingConfigManager,
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queueMgr *PollingQueueManager,
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logger *zap.Logger,
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) *PollingInitializer {
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p := &PollingInitializer{
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iotCardStore: iotCardStore,
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redis: redisClient,
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configMgr: configMgr,
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queueMgr: queueMgr,
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logger: logger,
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stopChan: make(chan struct{}),
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}
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p.progress.status = "pending"
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return p
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}
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// StartBackground 启动后台渐进式初始化（非阻塞）
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func (p *PollingInitializer) StartBackground(ctx context.Context) {
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p.wg.Add(1)
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go p.run(ctx)
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}
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// Stop 停止初始化
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func (p *PollingInitializer) Stop() {
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close(p.stopChan)
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p.wg.Wait()
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}
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// IsCompleted 检查初始化是否完成
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func (p *PollingInitializer) IsCompleted() bool {
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return p.initCompleted.Load()
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}
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// GetProgress 返回当前初始化进度快照（加锁读取，返回值拷贝）
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func (p *PollingInitializer) GetProgress() InitProgress {
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p.progress.mu.RLock()
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defer p.progress.mu.RUnlock()
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return InitProgress{
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TotalCards: p.progress.totalCards,
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LoadedCards: p.progress.loadedCards,
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StartTime: p.progress.startTime,
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LastBatchTime: p.progress.lastBatchTime,
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Status: p.progress.status,
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ErrorMessage: p.progress.errorMessage,
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}
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}
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// run 执行渐进式初始化
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func (p *PollingInitializer) run(ctx context.Context) {
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defer p.wg.Done()
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p.setStatus("running", "")
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p.progress.mu.Lock()
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p.progress.startTime = time.Now()
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p.progress.mu.Unlock()
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p.logger.Info("开始分片渐进式初始化...")
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totalCards, err := p.iotCardStore.CountForPolling(ctx)
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if err != nil {
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p.logger.Error("获取卡总数失败", zap.Error(err))
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p.setStatus("failed", err.Error())
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return
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}
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p.progress.mu.Lock()
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p.progress.totalCards = totalCards
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p.progress.mu.Unlock()
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p.logger.Info("开始加载卡数据", zap.Int64("total_cards", totalCards))
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const batchSize = 100000
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const batchSleep = 500 * time.Millisecond
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var lastID uint
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batchCount := 0
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for {
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select {
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case <-p.stopChan:
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p.logger.Info("渐进式初始化被中断")
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return
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default:
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}
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cards, fetchErr := p.iotCardStore.ListForPollingBatch(ctx, lastID, batchSize)
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if fetchErr != nil {
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p.logger.Error("加载卡数据失败", zap.Error(fetchErr))
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p.setStatus("failed", fetchErr.Error())
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return
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}
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if len(cards) == 0 {
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break
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}
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if initErr := p.initBatch(ctx, cards); initErr != nil {
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p.logger.Warn("批量初始化失败", zap.Error(initErr))
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}
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lastID = cards[len(cards)-1].ID
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batchCount++
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p.progress.mu.Lock()
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p.progress.loadedCards += int64(len(cards))
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p.progress.lastBatchTime = time.Now()
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loaded := p.progress.loadedCards
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p.progress.mu.Unlock()
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if batchCount%10 == 0 || len(cards) < batchSize {
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p.logger.Info("初始化进度",
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zap.Int("batch", batchCount),
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zap.Int64("loaded", loaded),
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zap.Int64("total", totalCards))
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}
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time.Sleep(batchSleep)
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}
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p.setStatus("completed", "")
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p.initCompleted.Store(true)
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snapshot := p.GetProgress()
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p.logger.Info("分片渐进式初始化完成",
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zap.Int64("total_loaded", snapshot.LoadedCards),
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zap.Duration("duration", time.Since(snapshot.StartTime)))
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}
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// initBatch 使用 Pipeline 将一批卡写入分片队列和缓存
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// 每 pipelineFlushSize 条命令 Exec 一次，控制内存峰值并降低单次失败损失
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func (p *PollingInitializer) initBatch(ctx context.Context, cards []*model.IotCard) error {
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if len(cards) == 0 {
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return nil
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}
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now := time.Now()
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cardCacheTTL := 7 * 24 * time.Hour
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pipe := p.redis.Pipeline()
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cmdCount := 0
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enqueuedCards := 0
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skippedCards := 0
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flushPipe := func() {
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if cmdCount == 0 {
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return
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}
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if _, execErr := pipe.Exec(ctx); execErr != nil {
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p.logger.Warn("Pipeline flush 失败，继续下一批", zap.Error(execErr))
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}
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pipe = p.redis.Pipeline()
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cmdCount = 0
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}
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for _, card := range cards {
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cfg := p.configMgr.MatchConfig(card)
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if cfg == nil {
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skippedCards++
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continue
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}
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enqueuedCards++
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shardID := int(card.ID) % p.queueMgr.shardCount
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cardIDStr := fmt.Sprintf("%d", card.ID)
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if cfg.RealnameCheckInterval != nil && *cfg.RealnameCheckInterval > 0 {
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nextCheck := calculateNextCheckTime(card.LastRealNameCheckAt, *cfg.RealnameCheckInterval, now)
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pipe.ZAdd(ctx, constants.RedisPollingShardQueueKey(shardID, constants.TaskTypePollingRealname), redis.Z{
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Score: float64(nextCheck.Unix()), Member: cardIDStr,
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})
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cmdCount++
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}
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if cfg.CarddataCheckInterval != nil && *cfg.CarddataCheckInterval > 0 {
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nextCheck := calculateNextCheckTime(card.LastDataCheckAt, *cfg.CarddataCheckInterval, now)
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pipe.ZAdd(ctx, constants.RedisPollingShardQueueKey(shardID, constants.TaskTypePollingCarddata), redis.Z{
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Score: float64(nextCheck.Unix()), Member: cardIDStr,
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})
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cmdCount++
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}
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if cfg.PackageCheckInterval != nil && *cfg.PackageCheckInterval > 0 {
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nextCheck := calculateNextCheckTime(card.LastDataCheckAt, *cfg.PackageCheckInterval, now)
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pipe.ZAdd(ctx, constants.RedisPollingShardQueueKey(shardID, constants.TaskTypePollingPackage), redis.Z{
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Score: float64(nextCheck.Unix()), Member: cardIDStr,
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})
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cmdCount++
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}
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if cfg.ProtectCheckInterval != nil && *cfg.ProtectCheckInterval > 0 {
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nextCheck := calculateNextCheckTime(card.LastProtectCheckAt, *cfg.ProtectCheckInterval, now)
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pipe.ZAdd(ctx, constants.RedisPollingShardQueueKey(shardID, constants.TaskTypePollingProtect), redis.Z{
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Score: float64(nextCheck.Unix()), Member: cardIDStr,
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})
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cmdCount++
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}
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cacheKey := constants.RedisPollingCardInfoKey(card.ID)
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cacheData := map[string]interface{}{
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"id": card.ID, "iccid": card.ICCID,
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"card_category": card.CardCategory, "real_name_status": card.RealNameStatus,
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"network_status": card.NetworkStatus, "carrier_id": card.CarrierID,
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"current_month_usage_mb": card.CurrentMonthUsageMB,
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"last_gateway_reading_mb": card.LastGatewayReadingMB,
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"data_usage_mb": card.DataUsageMB,
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"stop_reason": card.StopReason, "is_standalone": boolToStr(card.IsStandalone),
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"cached_at": now.Unix(),
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}
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if card.CurrentMonthStartDate != nil {
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cacheData["current_month_start_date"] = card.CurrentMonthStartDate.Unix()
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}
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pipe.HSet(ctx, cacheKey, cacheData)
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pipe.Expire(ctx, cacheKey, cardCacheTTL)
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cmdCount += 2
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if cmdCount >= pipelineFlushSize {
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flushPipe()
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}
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}
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flushPipe()
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p.logger.Info("批量初始化完成",
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zap.Int("total", len(cards)),
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zap.Int("enqueued", enqueuedCards),
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zap.Int("skipped_no_config", skippedCards))
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return nil
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}
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// calculateNextCheckTime 计算下次检查时间
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func calculateNextCheckTime(lastCheckAt *time.Time, intervalSeconds int, now time.Time) time.Time {
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if lastCheckAt == nil {
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jitter := time.Duration(now.UnixNano()%int64(intervalSeconds)) * time.Second / 10
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return now.Add(jitter)
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}
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nextCheck := lastCheckAt.Add(time.Duration(intervalSeconds) * time.Second)
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if nextCheck.Before(now) {
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return now
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}
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return nextCheck
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}
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func (p *PollingInitializer) setStatus(status, errMsg string) {
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p.progress.mu.Lock()
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p.progress.status = status
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p.progress.errorMessage = errMsg
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p.progress.mu.Unlock()
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}
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