What the data for this category looks like
Data comes from grain depot IoT weighing equipment, inventory management terminals, and quality inspection laboratory records. Update rhythm follows three patterns: real-time synchronization for inbound and outbound operations, full updates for monthly inventory checks, and fixed-cycle consolidated documents generated quarterly. Each document includes grain category, storage bin number, inbound batch, inbound weight, outbound weight, remaining stock weight, quality inspection result, and storage period. Units are tons and days.
Constraints Imposed on Database and Operations Workflows
Real-time inbound and outbound operations create high-frequency write requirements. The database connection pool must maintain stable concurrent connection counts. This avoids write timeouts or data loss. Full monthly inventory checks involve bulk data synchronization. The database must support large transaction commits. This prevents table locking caused by overly long transactions. Quarterly summary reports require association of ledger data across multiple bins and batches. The database must have efficient multi-table join query capabilities. Ledger fields vary slightly across different grain depots. The database must support dynamic field expansion to adapt to personalized requirements. Data must comply with public service domain compliance rules. Database audit logs must be enabled to retain records of all data read and write operations.
How to Configure
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://[privileged account]:[encrypted password]@[grain depot internal IP]:27017/granary_stock?authSource=admin | Adapts to the semi-structured storage needs of ledger data, supports flexible expansion of personalized fields for different grain depots |
PG_URL | postgresql://[operations account]:[encrypted password]@[consolidation server internal IP]:5432/report_db?sslmode=require | Used to store structured data for quarterly summary reports, supports complex query logic with multi-table joins |
DB_MAX_LINK | 15–25 | Balances concurrent connection counts for real-time writes and bulk inventory checks, prevents database resource exhaustion |
REDIS_URL | redis://[cache server internal IP]:6379/0 | Caches frequently accessed basic data for grain categories and bin numbers, reduces access pressure on the primary database |
Three Common Misconfigurations
- Symptom: The Oracle option does not appear in the database connection configuration interface. Oracle cannot be selected as a data source. Cause: The default integrated database drivers in the current FastGPT v4.17.0 version only cover MongoDB, PostgreSQL, and Redis. No Oracle driver package is included.
- Symptom: After deployment on a Linux server, an error
Connection refusedorAuthentication failedoccurs when attempting a MongoDB connection. Cause: The Linux system firewall has not opened the default MongoDB port 27017. Or the configured database account has not been granted read and write permissions for the ledger database. - Symptom: When generating a quarterly summary report, the remaining stock weight field is empty for some grain categories. The number of results is less than the actual number of ledgers. Cause: The
DB_MAX_LINKparameter is not set appropriately. Concurrent write requests exceed the connection pool limit. Some database requests are rejected.
How to Verify Successful Configuration
- Connect to a database management client. Perform write, query, and update operations for a single ledger entry. Confirm functionality is normal. Adjust the connection pool configuration based on business concurrent volume.
- Trigger a bulk inventory check data synchronization task. Check the database monitoring panel to confirm no transaction timeouts or table locking occur. Adjust batch submission rules based on the synchronization task's duration.
- Generate a quarterly summary report. Verify that all associated fields in the report are displayed correctly. Adjust the caching strategy based on the report's query complexity.
- View the database audit logs. Confirm all data read and write operations are fully recorded. This meets compliance requirements.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.