feat: 轮询系统重构(分片队列 + 停复机统一 + Handler 拆分)
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【核心变更】

1. 停复机逻辑统一(StopResumeService)
   - 新增 EvaluateAndAct 统一入口,封装三条件停复机判断
   - 停机条件:无套餐(no_package) / 流量耗尽(traffic_exhausted) / 未实名(not_realname)
   - 复机条件:stop_reason 合规 + 有套餐且未耗尽 + 已实名或行业卡
   - 修复设备套餐 Bug:hasValidPackage 按 device_id 查套餐,而非仅 iot_card_id
   - 设备维度停复机加幂等锁(Redis SetNX,TTL 30s),防止多卡并发重复调 Gateway

2. Redis 分片队列(PollingQueueManager)
   - 新建 queue_manager.go,封装所有轮询 Redis 操作
   - 16 分片 Sorted Set,Key 格式:polling:shard:{shardID}:queue:{taskType}
   - Lua 脚本原子出队(ZRANGEBYSCORE + 分批 ZREM),消除竞态窗口
   - 新增背压检测:队列深度超 50 万时 Scheduler 跳过该分片
   - RemoveFromAllQueues 覆盖 4 种任务类型(含 protect)

3. Handler 拆分(polling_handler.go 1360行 → 5个专注文件)
   - polling_base.go:共享基类(并发控制/卡缓存/重入队)
   - polling_realname_handler.go:实名采集,实名 0→1 时立即触发复机
   - polling_carddata_handler.go:流量采集,保留跨月边界检测逻辑
   - polling_package_handler.go:套餐采集,委托 EvaluateAndAct 决策
   - polling_protect_handler.go:保护期一致性检查,保护期内强制修正

4. 配置管理(PollingConfigManager)
   - 新建 config_manager.go,从 scheduler.go 提取配置职责
   - 内存缓存 + 5 分钟定时刷新,刷新失败保留原缓存
   - 修复 getCardCondition:停机卡返回 suspended,不再错配 activated 配置

5. 渐进式初始化(CardInitializer)
   - 新建 initializer.go,分批加载(每批 10 万),批次间 sleep 500ms
   - 过滤 enable_polling=false 的卡,初始化完成前 Scheduler 不出队

6. 卡生命周期服务(PollingLifecycleService)
   - 新建 lifecycle_service.go,替代已删除的 callbacks.go 和 api_callback.go
   - OnCardCreated/OnCardEnabled/OnCardStatusChanged 入队前检查 enable_polling

7. Scheduler 精简(1000+行 → 227行)
   - 保留纯调度循环:scheduleLoop + processShardSchedule + enqueueBatch
   - 保留每 10 秒触发套餐过期检测和流量重置
   - 移除所有 DB 操作、配置加载、卡初始化逻辑

8. 轮询管控 API(enable_polling)
   - 新增 PUT /api/admin/assets/:id/polling-status 接口
   - 支持对设备/卡维度开关轮询,关闭后从所有分片队列移除

9. 数据库迁移
   - 000103:tb_device 新增 enable_polling 字段(boolean, NOT NULL, DEFAULT true)
   - 000104:新增 suspended 轮询配置,为 activated 配置补全 protect_check_interval

【文件统计】
- 新增:19 个文件(handler × 5、polling 组件 × 4、迁移 × 3 等)
- 修改:20 个文件(bootstrap 注入、store 接口、monitoring 适配分片等)
- 删除:3 个文件(polling_handler.go、callbacks.go、api_callback.go)

Ultraworked with [Sisyphus](https://github.com/code-yeongyu/oh-my-openagent)

Co-authored-by: Sisyphus <clio-agent@sisyphuslabs.ai>
This commit is contained in:
2026-04-07 12:27:04 +08:00
parent 10fcc0b3c9
commit 434a8b0349
62 changed files with 7496 additions and 3023 deletions

View File

@@ -0,0 +1,297 @@
package polling
import (
"context"
"fmt"
"sync"
"sync/atomic"
"time"
"github.com/redis/go-redis/v9"
"go.uber.org/zap"
"github.com/break/junhong_cmp_fiber/internal/model"
"github.com/break/junhong_cmp_fiber/internal/store/postgres"
"github.com/break/junhong_cmp_fiber/pkg/constants"
)
// initProgress 初始化进度内部状态(字段通过 GetProgress 快照对外,避免暴露锁)
type initProgress struct {
mu sync.RWMutex
totalCards int64
loadedCards int64
startTime time.Time
lastBatchTime time.Time
status string
errorMessage string
}
// InitProgress 初始化进度快照GetProgress 返回的值拷贝,调用方无需加锁)
type InitProgress struct {
TotalCards int64 `json:"total_cards"`
LoadedCards int64 `json:"loaded_cards"`
StartTime time.Time `json:"start_time"`
LastBatchTime time.Time `json:"last_batch_time"`
Status string `json:"status"`
ErrorMessage string `json:"error_message"`
}
// pipelineFlushSize 单次 Pipeline Exec 最大命令数(每张卡最多 6 条)
// 10000 条约 2MB 内存峰值;千万级卡下约 6000 次 ExecRTT 总开销可忽略
const pipelineFlushSize = 10000
// PollingInitializer 分片渐进式初始化器
// 启动时从 DB 分批加载全量卡数据到分片 Sorted Set
// 使用 card_id % shardCount 分片,每 pipelineFlushSize 条命令 flush 一次 Pipeline
type PollingInitializer struct {
iotCardStore *postgres.IotCardStore
redis *redis.Client
configMgr *PollingConfigManager
queueMgr *PollingQueueManager
logger *zap.Logger
progress initProgress
initCompleted atomic.Bool
stopChan chan struct{}
wg sync.WaitGroup
}
// NewPollingInitializer 创建初始化器
func NewPollingInitializer(
iotCardStore *postgres.IotCardStore,
redisClient *redis.Client,
configMgr *PollingConfigManager,
queueMgr *PollingQueueManager,
logger *zap.Logger,
) *PollingInitializer {
p := &PollingInitializer{
iotCardStore: iotCardStore,
redis: redisClient,
configMgr: configMgr,
queueMgr: queueMgr,
logger: logger,
stopChan: make(chan struct{}),
}
p.progress.status = "pending"
return p
}
// StartBackground 启动后台渐进式初始化(非阻塞)
func (p *PollingInitializer) StartBackground(ctx context.Context) {
p.wg.Add(1)
go p.run(ctx)
}
// Stop 停止初始化
func (p *PollingInitializer) Stop() {
close(p.stopChan)
p.wg.Wait()
}
// IsCompleted 检查初始化是否完成
func (p *PollingInitializer) IsCompleted() bool {
return p.initCompleted.Load()
}
// GetProgress 返回当前初始化进度快照(加锁读取,返回值拷贝)
func (p *PollingInitializer) GetProgress() InitProgress {
p.progress.mu.RLock()
defer p.progress.mu.RUnlock()
return InitProgress{
TotalCards: p.progress.totalCards,
LoadedCards: p.progress.loadedCards,
StartTime: p.progress.startTime,
LastBatchTime: p.progress.lastBatchTime,
Status: p.progress.status,
ErrorMessage: p.progress.errorMessage,
}
}
// run 执行渐进式初始化
func (p *PollingInitializer) run(ctx context.Context) {
defer p.wg.Done()
p.setStatus("running", "")
p.progress.mu.Lock()
p.progress.startTime = time.Now()
p.progress.mu.Unlock()
p.logger.Info("开始分片渐进式初始化...")
totalCards, err := p.iotCardStore.CountForPolling(ctx)
if err != nil {
p.logger.Error("获取卡总数失败", zap.Error(err))
p.setStatus("failed", err.Error())
return
}
p.progress.mu.Lock()
p.progress.totalCards = totalCards
p.progress.mu.Unlock()
p.logger.Info("开始加载卡数据", zap.Int64("total_cards", totalCards))
const batchSize = 100000
const batchSleep = 500 * time.Millisecond
var lastID uint
batchCount := 0
for {
select {
case <-p.stopChan:
p.logger.Info("渐进式初始化被中断")
return
default:
}
cards, fetchErr := p.iotCardStore.ListForPollingBatch(ctx, lastID, batchSize)
if fetchErr != nil {
p.logger.Error("加载卡数据失败", zap.Error(fetchErr))
p.setStatus("failed", fetchErr.Error())
return
}
if len(cards) == 0 {
break
}
if initErr := p.initBatch(ctx, cards); initErr != nil {
p.logger.Warn("批量初始化失败", zap.Error(initErr))
}
lastID = cards[len(cards)-1].ID
batchCount++
p.progress.mu.Lock()
p.progress.loadedCards += int64(len(cards))
p.progress.lastBatchTime = time.Now()
loaded := p.progress.loadedCards
p.progress.mu.Unlock()
if batchCount%10 == 0 || len(cards) < batchSize {
p.logger.Info("初始化进度",
zap.Int("batch", batchCount),
zap.Int64("loaded", loaded),
zap.Int64("total", totalCards))
}
time.Sleep(batchSleep)
}
p.setStatus("completed", "")
p.initCompleted.Store(true)
snapshot := p.GetProgress()
p.logger.Info("分片渐进式初始化完成",
zap.Int64("total_loaded", snapshot.LoadedCards),
zap.Duration("duration", time.Since(snapshot.StartTime)))
}
// initBatch 使用 Pipeline 将一批卡写入分片队列和缓存
// 每 pipelineFlushSize 条命令 Exec 一次,控制内存峰值并降低单次失败损失
func (p *PollingInitializer) initBatch(ctx context.Context, cards []*model.IotCard) error {
if len(cards) == 0 {
return nil
}
now := time.Now()
cardCacheTTL := 7 * 24 * time.Hour
pipe := p.redis.Pipeline()
cmdCount := 0
flushPipe := func() {
if cmdCount == 0 {
return
}
if _, execErr := pipe.Exec(ctx); execErr != nil {
p.logger.Warn("Pipeline flush 失败,继续下一批", zap.Error(execErr))
}
pipe = p.redis.Pipeline()
cmdCount = 0
}
for _, card := range cards {
cfg := p.configMgr.MatchConfig(card)
if cfg == nil {
continue
}
shardID := int(card.ID) % p.queueMgr.shardCount
cardIDStr := fmt.Sprintf("%d", card.ID)
if cfg.RealnameCheckInterval != nil && *cfg.RealnameCheckInterval > 0 {
nextCheck := calculateNextCheckTime(card.LastRealNameCheckAt, *cfg.RealnameCheckInterval, now)
pipe.ZAdd(ctx, constants.RedisPollingShardQueueKey(shardID, constants.TaskTypePollingRealname), redis.Z{
Score: float64(nextCheck.Unix()), Member: cardIDStr,
})
cmdCount++
}
if cfg.CarddataCheckInterval != nil && *cfg.CarddataCheckInterval > 0 {
nextCheck := calculateNextCheckTime(card.LastDataCheckAt, *cfg.CarddataCheckInterval, now)
pipe.ZAdd(ctx, constants.RedisPollingShardQueueKey(shardID, constants.TaskTypePollingCarddata), redis.Z{
Score: float64(nextCheck.Unix()), Member: cardIDStr,
})
cmdCount++
}
if cfg.PackageCheckInterval != nil && *cfg.PackageCheckInterval > 0 {
nextCheck := calculateNextCheckTime(card.LastDataCheckAt, *cfg.PackageCheckInterval, now)
pipe.ZAdd(ctx, constants.RedisPollingShardQueueKey(shardID, constants.TaskTypePollingPackage), redis.Z{
Score: float64(nextCheck.Unix()), Member: cardIDStr,
})
cmdCount++
}
if cfg.ProtectCheckInterval != nil && *cfg.ProtectCheckInterval > 0 {
nextCheck := calculateNextCheckTime(card.LastProtectCheckAt, *cfg.ProtectCheckInterval, now)
pipe.ZAdd(ctx, constants.RedisPollingShardQueueKey(shardID, constants.TaskTypePollingProtect), redis.Z{
Score: float64(nextCheck.Unix()), Member: cardIDStr,
})
cmdCount++
}
cacheKey := constants.RedisPollingCardInfoKey(card.ID)
cacheData := map[string]interface{}{
"id": card.ID, "iccid": card.ICCID,
"card_category": card.CardCategory, "real_name_status": card.RealNameStatus,
"network_status": card.NetworkStatus, "carrier_id": card.CarrierID,
"current_month_usage_mb": card.CurrentMonthUsageMB,
"last_gateway_reading_mb": card.LastGatewayReadingMB,
"data_usage_mb": card.DataUsageMB,
"stop_reason": card.StopReason, "is_standalone": boolToStr(card.IsStandalone),
"cached_at": now.Unix(),
}
if card.CurrentMonthStartDate != nil {
cacheData["current_month_start_date"] = card.CurrentMonthStartDate.Unix()
}
pipe.HSet(ctx, cacheKey, cacheData)
pipe.Expire(ctx, cacheKey, cardCacheTTL)
cmdCount += 2
if cmdCount >= pipelineFlushSize {
flushPipe()
}
}
flushPipe()
return nil
}
// calculateNextCheckTime 计算下次检查时间
func calculateNextCheckTime(lastCheckAt *time.Time, intervalSeconds int, now time.Time) time.Time {
if lastCheckAt == nil {
jitter := time.Duration(now.UnixNano()%int64(intervalSeconds)) * time.Second / 10
return now.Add(jitter)
}
nextCheck := lastCheckAt.Add(time.Duration(intervalSeconds) * time.Second)
if nextCheck.Before(now) {
return now
}
return nextCheck
}
func (p *PollingInitializer) setStatus(status, errMsg string) {
p.progress.mu.Lock()
p.progress.status = status
p.progress.errorMessage = errMsg
p.progress.mu.Unlock()
}