Task Batch Partitioning Algorithm & ThreadPoolExecutor Concurrency Throttling
Decrypting batch_runner.py task distribution, dynamic thread pool scaling & exception recovery
📊 Fig 12-1-1: Batch data slicing, thread pool allocation & task channel concurrency limiting structure diagram
⚡ 1. Batch Task Partitioning Algorithm
In batch_runner.py, when facing hundreds or thousands of parallel tasks, the system implements an efficient partitioning algorithm that distributes tasks across concurrent queues based on workload and available hardware threads.
📊 Fig 12-1-2: Batch concurrent API error capture, backoff delay calculation & task channel retry sequence diagram
🚦 2. Thread Pool Concurrency Throttling & Exception Fault Tolerance
The system controls the number of active ThreadPoolExecutor threads via configured concurrency limits, preventing excessive parallelism from overwhelming the LLM server, while automatically spawning new threads to take over remaining batches when a thread crashes.