What the data for this category looks like
Livestock and poultry farming profitability data comes from three main sources: daily monitoring reports from local livestock authorities, internal production logs from large-scale farms, and public market data from third-party agricultural data platforms. Full production and transaction data from the previous day is synced at fixed daily times. Each data entry uses breeding batches as the core dimension, and includes fields such as barn ID, inventory headcount, slaughter volume, total feed consumption, epidemic prevention and labor costs, unit transaction price, and breeding cycle duration. Field units include head, ton, yuan, yuan/kg, day, and others.
What constraints these characteristics impose on deployment and upgrade
The multi-source, heterogeneous nature of livestock farming data requires configuring multi-format data access adapters during deployment, to adapt to field mapping rules for different data sources. The fixed daily full update schedule requires pre-setting trigger parameters for scheduled sync tasks during deployment, to avoid conflicts with business peaks. The multi-field dimensions of single-batch data require compatible parsing logic for new fields during upgrades, to prevent old configuration versions from failing to read new breeding cost fields. Large daily data volume from large-scale farms requires adjusting the maximum connection count of the database connection pool during deployment. Upgrades require verifying compatibility of the data cleaning module, to avoid calculation deviations in profitability caused by field parsing errors.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
SYNC_DATA_DAILY_TRIGGER_TIME | 06:00 | Matches the daily pre-dawn update rhythm of livestock data, ensures latest data is available for morning reports |
FIELD_MAPPING_PRECISION | 0.01 | Adapts to precision requirements for monetary and weight fields in livestock farming data, avoids calculation deviations |
PARSE_BATCH_DATA_TIMEOUT | 300 seconds | Addresses parsing time for multi-batch data from large-scale farms, prevents sync task interruptions |
UPLOAD_LOCAL_DATA_MAX_SIZE | 2000 MB | Accommodates file size of full single-batch breeding logs, meets data import needs of large-scale farms |
GRAYSCALE_UPGRADE_PERCENT | 20% | Controls upgrade traffic, prevents service interruptions from full upgrades that impact daily report broadcasts |
ROLLBACK_ON_FAILURE | Enabled | Automatically rolls back to previous version if upgrade fails, ensures stability of profitability broadcast services |
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 individual analysis. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Issue: A
permission deniederror appears during local deployment, and connection to the local data storage directory fails. Cause: The FastGPT runtime user’s permissions are not configured for read/write access to the breeding data log storage path, causing data sync tasks to fail to read source files. - Issue: After upgrading to version 4.8.7, the 360 Extreme Browser cannot load the broadcast page normally. Cause: The new version’s compilation target is set to
es2020, which is not compatible with JS syntax features of older browsers, causing page rendering failures. - Issue: After uploading breeding log files, all parsed fields are empty. Cause: The
FIELD_MAPPING_RULESparameter is not configured, and no mapping relationship is established between data source fields and internal system fields, causing the parsing module to fail to recognize valid data.
How to confirm configuration is complete
- Manually trigger a data sync task, check system logs for successful data sync records, confirm trigger timing matches preset sync rules.
- Upload single-batch breeding test data, verify parsed fields are complete with no missing or abnormal formats, confirm
FIELD_MAPPING_RULESconfiguration takes effect. - Perform a small-scale upgrade operation, observe running status of service nodes, complete full upgrade after confirming no errors, verify availability of the rollback mechanism in abnormal scenarios.
- Check permissions of the local deployment storage path, confirm the runtime account has read/write access, to avoid access failures in subsequent sync tasks.
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.