Definition
Batch processing involves aggregating data inputs into a group, or batch, before executing a computation or model inference. This approach contrasts with real-time streaming processing by allowing for higher throughput and better resource utilization through parallel execution. It is commonly used in offline training scenarios, historical data analysis, and scheduled tasks where immediate results are not required, optimizing hardware usage by maximizing GPU/TPU occupancy.
Summary
A computational method where data is collected over time and processed in groups rather than individually.
Key Concepts
- Throughput Optimization
- Resource Utilization
- Offline Computation
- Group Execution
Use Cases
- Training large neural networks on historical datasets
- Scheduled ETL jobs in data warehouses
- Nightly report generation