What This Category of Data Looks Like
The core data of this category falls into two types: project approval text and spatial documents. Daily documents include land pre-examination and site selection opinions, construction land planning permits, construction engineering planning permits, red line drawings, and planning conditions. Fields cover project number, approval document number, land scope coordinates, land scale, control requirements, and more. Data sources include the national land and space planning one-map system, project approval supervision platform, current land use database, and ecological protection red line data. Update frequency is irregular, with no fixed synchronization cycle.
What Constraints Do These Data Characteristics Impose on Database and Operations Maintenance
This category’s data characteristics create three core constraints for the database and operations maintenance stage. First, multi-source and heterogeneous data sources require the database to support hybrid storage and multi-source access, while adapting to both structured ledger data and unstructured spatial documents. Second, the irregular update frequency means fixed full synchronization logic must be abandoned, replaced with on-demand triggered incremental synchronization to avoid resource waste and request timeouts. Third, errors in project approval data will block project approval or construction startup, so strict data verification rules and change logs must be configured to ensure data traceability and auditability.
Configuration Specifications
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://admin:securepass@10.0.1.2:27017/land_approval?authSource=admin | Stores unstructured spatial documents such as red line drawings and planning conditions, as well as full-text indexes, to support spatial data query requirements |
PG_URL | postgresql://admin:securepass@10.0.1.3:5432/land_approval_db | Stores structured project approval ledgers, supports multi-condition combined queries and transactional operations |
DB_MAX_LINK | 8–12 | Matches the concurrent access scale of daily departmental approval work, prevents database connection pool overflow |
REDIS_URL | redis://:securepass@10.0.1.4:6379/1 | Caches frequently queried project ledger summaries, reduces access load on core databases |
Three Common Misconfigurations
- Symptom: Service fails to start after deployment, cannot connect to the specified database, with a
Connection refusederror in logs. Cause: Access address or permission information forMONGODB_URIorPG_URLis misconfigured, or corresponding ports are not open in the database firewall. - Symptom: Task timeout occurs during full historical data pull, leading to failed ledger generation. Cause: On-demand synchronization logic is not configured per the irregular data update pattern, and fixed full pull is still used, causing single request data volume to exceed system timeout thresholds.
- Symptom: Duplicate project entries appear in the generated summary report. Cause: No database unique index is created for the project number field, and no data deduplication verification rule is configured, resulting in duplicate data being stored in the database.
How to Verify Successful Configuration
- Run the built-in database connection test tool to confirm that the addresses and permissions configured for
MONGODB_URIandPG_URLcan establish normal connections. - Trigger a small-scale project ledger synchronization task, check the field integrity and format correctness of synchronized data, and ensure no missing or abnormal fields are present.
- View the Redis cache monitoring panel, confirm that frequently queried project ledger data is cached normally, and no cache penetration or breakdown occurs.
- Simulate concurrent ledger query requests, confirm that the database connection pool is not exhausted, and that the
DB_MAX_LINKconfiguration is active.
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.