🚀 Performance Sprint
For power users with tens of thousands of data records, every minor I/O block is magnified. This week, we challenged the limits of “Instant Response.”
📉 IO Efficiency: Performance Comparison
We refactored the original single-loop operations into an Underlying Batch Processing Solution.
| Scenario | Before (10k records) | After | Boost |
|---|---|---|---|
| Data Batch Cleanup | 58s | 0.28s | 200x 🚀 |
| History Sync | 12s | 0.78s | 15x |
| Status Diff Filtering | 25s | 0.15s | 160x |
💡 Dev Guidelines Updated
“Executing IO operations within a loop is the root of performance disasters.”
Following this fix, we have updated the project’s Code Review Standards.