What this category's data looks like
Small home appliance profit margin and market trend data comes from three main sources: e-commerce platform public sales data, brand inventory and sales systems, and industry retail monitoring databases. Data is fully aggregated for the previous day every early morning. Each data record covers the daily operating status of one SKU. Files use standardized CSV or JSON format, with fields including single product code, product name, sales channel, daily terminal selling price, daily purchase cost, daily profit amount, market average price, daily sales volume, and month-over-month sales change. Selling price, purchase cost, and profit amount use yuan per unit as their unit. Sales volume uses units as its unit. Month-over-month change uses units as its unit.
Constraints on Deployment and Upgrade
The large number of small home appliance SKUs and fixed data update frequency create specific deployment requirements. Deployments must support multi-source data pulling and batch synchronization configuration. Fixed daily synchronization tasks need matching timing rules to avoid conflicts with business peak periods. Full data volumes are large, so synchronization timeout and file upload parameters must be adjusted to prevent synchronization timeouts or file upload failures. During upgrades, user-defined field mapping rules must be retained. This avoids data display errors caused by mismatches between the new version's default configuration and the small home appliance data structure. An automatic backup mechanism must also be configured to prevent historical data loss from upgrade failures.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
DATA_SYNC_INTERVAL | 1:00 AM daily | Matches the daily update rhythm of small home appliance profit margin daily reports, and avoids conflicts with peak e-commerce platform data periods |
BATCH_SYNC_SIZE | 800-1200 items per sync | Adapts to the batch synchronization needs of tens of thousands of small home appliance SKUs, balancing synchronization efficiency and database load |
SYNC_TIMEOUT_SECONDS | 600 seconds | Full synchronization of all category SKU data requires a long processing duration, and the default timeout duration cannot cover the synchronization cycle |
FIELD_MAPPING_MODE | Strict matching + custom mapping | Compatibility with field differences across brand small home appliance data, retaining standardized fields while supporting custom extensions |
UPLOAD_DATA_MAX_SIZE | 1000 MB | Small home appliance full market trend daily report CSV files typically have large volumes, so upload limits must be relaxed |
AUTO_BACKUP_ENABLED | Enabled | Retains historical configuration and data during upgrades, preventing business interruptions from upgrade failures |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require targeted analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Configuration Mistakes
- When running
docker build -f ./projects/app/Dockerfile -t registry.c, the error "dependency package pull failed" or "build timeout" occurs. The cause is that small home appliance data files have large volumes, the build process needs to pull additional industry data dependency packages, and the defaultBUILD_TIMEOUTparameter is set too short. - After upgrading to version 4.9.0, profit margin data fields display as empty. The cause is that custom
FIELD_MAPPING_RULEconfiguration was not retained during the upgrade, and the new version's default field mapping does not match the original small home appliance data structure. - When using an Ollama-deployed large model calling tool, a "400 Bad Request" error is returned. The cause is that the Ollama interface address and model name were not correctly configured in
OPENAI_COMPATIBLE_API_CONFIG, causing the tool call link to interrupt.
How to Confirm Proper Configuration
- Run a manual data synchronization task, verify that the number of synced SKUs matches the source data file, and confirm that the scheduled task execution time meets business requirements.
- View the configuration details of
FIELD_MAPPING_RULE, confirm that each field of the small home appliance data has been correctly mapped to the system's standard fields, with no missing or incorrect mappings. - Trigger a profit margin reporting tool call test, confirm that the returned result contains correct fields and values, with no abnormal errors.
- Check the automatic backup task logs, confirm that the pre-upgrade configuration and data have been successfully backed up, and that there are no abnormal records during the upgrade process.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.