Data Overview for This Category
Data sources include engineering orders, sand, cement and admixture inspection records, aggregate moisture content test results, mixing plant control system data, and laboratory test reports. Update frequency aligns with per-vehicle production records, per-batch raw material test results, and daily aggregated ledgers. Daily documents include mix proportion notices, batch opening identification forms, production and transport orders, raw material inspection records, test block retention records, and strength test reports. Data fields cover project number, raw material batch, mixing parameters, transport vehicle information, test block number, strength test results, and additional relevant fields. Units used include cubic meters, tons, and hours.
Constraints for Database and Operations Workflows
Per-vehicle high-frequency production write requests require databases to support high concurrent connections, to prevent data loss or synchronization delays. Heterogeneous data from multiple sources requires unified format validation, to avoid data anomalies caused by field conflicts. Daily ledger aggregation needs scheduled synchronization tasks, to ensure consistency of cross-department data. Test block records and strength reports require long-term storage, so databases must have reliable backup and expansion capabilities. Production data anomalies may trigger engineering quality issues, so data validation and real-time alert mechanisms must be configured.
Configuration Recommendations
These recommendations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://[username]:[password]@host:port/dbname?authSource=admin | Supports storage of unstructured document data such as test records and transport orders |
PG_URL | postgresql://[username]:[password]@host:port/dbname | Supports complex queries for strongly associated structured data such as production ledgers and engineering orders |
DB_MAX_LINK | 20–30 | Matches the concurrent demand of per-vehicle high-frequency writes, to avoid connection pool exhaustion |
REDIS_URL | redis://[password]@host:port/0 | Caches frequently queried mix proportion parameters and real-time production status, to reduce database load |
Three Common Configuration Errors
- Symptom: When connecting to the database via
MONGODB_URI, an "Authentication failed" or "connection refused" error is returned. Cause: The username, password, host, or port in the connection string is not configured correctly, or database access permissions for the mixing plant server are not enabled. - Symptom: SQL queries occasionally fail, returning "query timeout" or empty results. Cause:
DB_MAX_LINKis not set appropriately, leading to connection pool exhaustion and failure of some requests to obtain database connections. - Symptom: Formula code data cannot be retrieved normally after storage. Cause: An unstructured database was incorrectly selected to store structured formula code data, instead of a relational database that supports efficient indexing.
How to Verify Successful Configuration
The built-in FastGPT database connectivity test tool is executed to verify that the databases corresponding to MONGODB_URI and PG_URL can establish normal connections and complete read and write operations. Per-vehicle production data writes and daily batch aggregation queries are simulated, connection pool usage is observed, and no connection exhaustion is confirmed to occur. A batch of test block records and transport order data is imported, and all fields are checked to be fully written without missing or format anomalies. Real-time production status data cached in Redis is reviewed, and the cache update frequency is confirmed to meet the per-vehicle synchronization requirement.
The values provided are common starting points and should be measured against the reader's own samples.