field note
Solving Memory Pressure in a Python Data Pipeline
After a vectorized rewrite cut processing time from 30 minutes to 10 seconds, concurrent load under limited server memory exposed a completely different constraint, and the solution required batching, job queues, and polling to solve without giving back the performance gains.
pythonpandasmemory-managementbatch-processingqueuespollingscalabilitydata-processing
