Deep Dive into Apache SeaTunnel Metadata Cache: Running Tens of Thousands of Sync Jobs in Parallel

In large-scale data integration, the throughput bottleneck is often not the data pipeline itself, but the “metadata path”: loading connector JARs during startup, managing state and recovery during runtime, and fetching schemas/partitions from external systems (databases, Hive Metastore, etc.) while initializing jobs. Once job concurrency reaches thousands (or more), these seemingly small operations can easily turn into cluster-wide pressure.