What Data for This Category Looks Like
This category of data includes four core document types: advertising review forms, qualification attachments, delivery records, and rectification notices. Data sources are advertising platform backends, customer qualification systems, contract management systems, and public regulatory rule databases. Data updates trigger with individual advertising campaigns or monthly cycles. Each data entry contains fields such as review conclusions, qualification numbers, delivery time windows, rectification items, and more. There is no unified fixed unit. Corresponding metadata must be linked based on document type. Daily tasks include qualification archiving, delivery record retention, and rectification evidence organization. Data retention periods must align with regulatory and business requirements.
Constraints Imposed on Database and Operations Workflows
Data sources for this category are scattered. Multiple source interfaces must be integrated, including advertising platform backends and customer qualification systems. The database must support multi-source data synchronization and heterogeneous document storage. Data updates trigger with individual delivery campaigns, creating peak write scenarios. Connection pools must be properly configured to handle sudden traffic spikes. Each data entry includes structured metadata and unstructured attachments. The system must support both precise query capabilities and large file storage. Data retention periods must align with business and regulatory requirements, and retention durations must support flexible adjustment. Errors may lead to regulatory penalties and customer accountability, so data must be immutable and traceable. Full-link audit logs and regular backup strategies must be configured for operations.
Configuration Settings
This applies to FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 20–30 | Handles peak write requests from monthly or individual delivery campaigns, prevents connection exhaustion that causes synchronization failures |
MONGODB_URI | Dedicated MongoDB instance address | Stores unstructured documents such as qualification attachments and rectification notices, isolates this data from other business data |
PG_URL | Dedicated PostgreSQL instance address | Stores structured metadata for advertising review forms and delivery records, supports complex conditional queries |
REDIS_URL | Dedicated Redis instance address | Caches frequently queried regulatory rules and qualification verification results to reduce database load |
| Data backup cycle | 02:00 daily | Ensures data traceability and meets regulatory and business audit requirements |
| Connection timeout threshold | 600 seconds | Accommodates long connection requirements for multi-source data synchronization, prevents unexpected disconnections |
Three Common Configuration Mistakes
- Symptom: Database connection errors, with logs showing
connection refusedorauth failed. Cause: Account, address, or authentication source forMONGODB_URIorPG_URLis not configured correctly, preventing a valid connection from being established. - Symptom: Complete attachments cannot be retrieved after compliance data synchronization. Cause: The storage path corresponding to
MONGODB_URIis not configured correctly, resulting in failed upload of qualification attachments to the database storage node. - Symptom: Some delivery records are not synchronized to the system after an individual advertising delivery campaign. Cause:
DB_MAX_LINKis set too low, unable to handle peak write requests, leading to timeout failures for some write tasks.
How to Verify Configurations Are Correct
- Execute a database connection test script to validate that configured
MONGODB_URIandPG_URLinstances can establish normal connections and execute basic queries. - Upload a test advertising review form and qualification attachment to confirm normal data storage and successful retrieval of complete metadata and attachment content.
- Simulate batch data writes for a single delivery campaign, observe database load and write success rates, and adjust
DB_MAX_LINKto meet business peak requirements. - Review operation logs to confirm data backup tasks run normally per the configured cycle, with no failed records.
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 2026-10-19.