添加新分片后KCL Lease表未更新，导致Worker闲置问题求助

我正在使用版本为2.1.3的amazon-kclpy（基于MultiLangDaemon的Python库）。根据AWS文档，当为流添加新分片或启动新Worker（我这边是Kubernetes中的Pod）时，应触发分片重分配事件，之后Lease表中应出现新记录。但实际在这两种场景下，Lease表都未生成新记录，导致新增的Worker处于闲置状态并进入睡眠循环，相关日志如下：

2023-12-24 17:46:34,750 [multi-lang-daemon-0000] INFO  s.a.kinesis.coordinator.Scheduler [NONE] - Initializing LeaseCoordinator attempt 1 
2023-12-24 17:46:37,860 [multi-lang-daemon-0000] INFO  s.a.k.leases.LeaseCleanupManager [NONE] - Starting lease cleanup thread. 
2023-12-24 17:46:37,861 [multi-lang-daemon-0000] INFO  s.a.kinesis.coordinator.Scheduler [NONE] - Starting LeaseCoordinator 
2023-12-24 17:46:37,861 [pool-15-thread-1] INFO  s.a.k.leases.LeaseCleanupManager [NONE] - Number of pending leases to clean before the scan : 0 
2023-12-24 17:46:37,926 [multi-lang-daemon-0000] INFO  s.a.kinesis.coordinator.Scheduler [NONE] - Scheduling periodicShardSync 
2023-12-24 17:46:37,928 [multi-lang-daemon-0000] INFO  s.a.kinesis.coordinator.Scheduler [NONE] - Initialization complete. Starting worker loop. 
2023-12-24 17:46:38,026 [multi-lang-daemon-0000] INFO  s.a.k.c.DeterministicShuffleShardSyncLeaderDecider [NONE] - Elected leaders: fe86945c-96d7-423e-a157-97c5c6ad6f79 
2023-12-24 17:47:05,036 [multi-lang-daemon-0000] INFO  s.a.k.c.DiagnosticEventLogger [NONE] - Current thread pool executor state: ExecutorStateEvent(executorName=SchedulerThreadPoolExecutor, currentQueueSize=0, activeThreads=0, coreThreads=0, leasesOwned=0, largestPoolSize=0, maximumPoolSize=2147483647) 
2023-12-24 17:47:35,044 [multi-lang-daemon-0000] INFO  s.a.kinesis.coordinator.Scheduler [NONE] - No activities assigned 
2023-12-24 17:47:35,045 [multi-lang-daemon-0000] INFO  s.a.k.c.DiagnosticEventLogger [NONE] - Current thread pool executor state: ExecutorStateEvent(executorName=SchedulerThreadPoolExecutor, currentQueueSize=0, activeThreads=0, coreThreads=0, leasesOwned=0, largestPoolSize=0, maximumPoolSize=2147483647) 
2023-12-24 17:47:35,045 [multi-lang-daemon-0000] INFO  s.a.kinesis.coordinator.Scheduler [NONE] - Sleeping ... 

请问这是权限问题还是Python代码存在问题？

1. 权限问题 #

• 检查Pod绑定的IAM角色是否包含以下必要权限：
  • kinesis:DescribeStream/kinesis:DescribeStreamSummary：Worker需要获取Kinesis流的分片元数据
  • dynamodb:PutItem、dynamodb:GetItem、dynamodb:UpdateItem、dynamodb:Scan：对Lease表的读写及扫描权限
  • 确认权限策略中的资源ARN是否正确，比如Lease表的ARN是否完整匹配，没有限制特定条目

2. 分片同步配置问题 #

• 检查periodicShardSyncIntervalMillis参数：默认5分钟，若配置过大，新分片/Worker的同步会延迟
• 确保所有Worker使用同一个Lease表：不同表会导致分片分配逻辑隔离，新Worker无法感知已有分片
• 验证Leader节点状态：日志显示已选举Leader，但需确认该Leader节点能正常访问Kinesis流和Lease表，未被资源限制或网络隔离

3. Amazon-KCLPy配置校验 #

• 确认所有Worker的applicationName配置一致：这个参数是Lease表关联的核心标识，不一致会导致无法共享分片信息
• 检查shardSyncEnabled是否启用：默认开启，若被禁用会直接阻止分片同步逻辑执行
• 核对kinesisStreamName/kinesisStreamArn配置：确保流名称/ARN拼写正确，没有环境差异导致的配置错误

4. 代码逻辑问题 #

• 检查自定义RecordProcessor的initialize、shardEnded方法：若存在阻塞、未正确处理异常等情况，会导致Lease更新失败，影响分片分配
• 确认未手动修改Lease表记录：手动删除或修改分片对应的Lease条目会破坏KCL的自动分配机制，导致新分片无法被识别

内容的提问来源于stack exchange，提问作者omer bar lev