What the data for this category looks like
Data for this category comes from safety production supervision systems, enterprise hazard self-inspection systems, law enforcement inspection records, and accident statistics systems. The update frequency is daily. Daily documents include hazard inspection lists, hazard governance ledgers, rectification notices, review records, and major hazard suspension and supervision orders. Each entry contains fields such as hazard ID, inspection subject, inspection date, hazard level, rectification measures, responsible unit, rectification deadline, review date, review conclusion, and supervision status. Rectification deadlines are measured in calendar days, and inspection dates use the YYYY-MM-DD format.
What constraints these characteristics impose on the database and operations link
The daily high-frequency update requirement means the database must support stable concurrent writes and queries, to avoid data delays caused by connection exhaustion. Multi-source heterogeneous data sources require the database to support structured and semi-structured data storage, to ensure uniform formatting of hazard data imported from different systems. Full-process hazard-related data requires the database to support associated queries, to quickly summarize ledgers and generate reports. Data errors can lead to serious consequences, so reliable backup and disaster recovery mechanisms must be configured. Data field standardization checks are also needed to avoid missing fields that disrupt subsequent report generation and rectification tracking.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Database connection pool size | 20–30 connections | Adapts to daily high-frequency hazard data writes and queries, avoids connection resource exhaustion |
MONGODB_URI | mongodb://[account]:[password]@host address:port/admin?authSource=admin | Stores unstructured documents such as rectification notices and review records, supports flexible field expansion |
PG_URL | postgresql://[account]:[password]@host address:5432/hazard governance database | Stores structured hazard ledger, rectification deadline, supervision status and other associated data, ensures transaction consistency |
DB_MAX_LINK | 20–30 | Same as database connection pool size configuration, adapts to concurrent write requirements for multi-source data synchronization |
REDIS_URL | redis://:[password]@host address:6379/0 | Caches daily summarized hazard statistics data, reduces query pressure on the primary database |
| Data backup frequency | 1 time per day | Ensures recoverability of hazard data, avoids rectification process interruptions caused by data loss |
Three common mistakes
- Symptom: After upgrading to FastGPT v4.17.0, modifying the MongoDB configuration file and restarting the service results in connection timeout errors or failure to load the login interface. Cause: The authentication method or connection parameters for the new MongoDB version were not correctly matched, preventing the service from establishing a valid connection to the database.
- Symptom: When batch importing hazard inspection data, some core fields are empty, or the number of query results does not match the actual imported volume. Cause: Database mapping relationships were not configured according to the hazard data field specifications, leading to loss of key information during data writing.
- Symptom: Slow database responses or request timeouts occur in high-concurrency scenarios. Cause: The database connection pool configuration is too small, unable to support daily high-frequency hazard data writes and ledger query requests.
How to confirm the configuration is complete
- Run a database connection test command to verify that the connections configured via
MONGODB_URIandPG_URLare normal, with no authentication or address errors. - Import a standard hazard data entry, check that core fields such as hazard ID, rectification deadline, and review results are fully stored in the database.
- Simulate high-concurrency query requests, observe whether the database connection count stays within the configured
DB_MAX_LINKrange, with no connection exhaustion. - Trigger the daily data synchronization task, check that the cached statistics data matches the source data, with no update delays.
The values given 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.