Root Cause:
- Multiple parallel training tasks (3 at a time) were sharing the same database session
- This caused SQLAlchemy session state conflicts: "Session is already flushing" and "rollback() is already in progress"
- Additionally, duplicate model records were being created by both trainer and training_service
Fixes:
1. Separated model training from database writes:
- Training happens in parallel (CPU-intensive)
- Database writes happen sequentially after training completes
- This eliminates concurrent session access
2. Removed duplicate database writes:
- Trainer now writes all model records sequentially after parallel training
- Training service now retrieves models instead of creating duplicates
- Performance metrics are also created by trainer (no duplicates)
3. Added proper data flow:
- _train_single_product: Only trains models, stores results
- _write_training_results_to_database: Sequential DB writes after training
- _store_trained_models: Changed to retrieve existing models
- _create_performance_metrics: Changed to verify existing metrics
Benefits:
- Eliminates database session conflicts
- Prevents duplicate model records
- Maintains parallel training performance
- Ensures data consistency
Files Modified:
- services/training/app/ml/trainer.py
- services/training/app/services/training_service.py
Resolves: Onboarding training job database session conflicts
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