What the data for this category looks like
This category of data primarily originates from the community reporting system, reported content detail pages, reporter historical behavior records, and the audit rule library. Daily generated documents include report tickets, report processing records, user appeal forms, and violation disposal notification templates. Systems update data in two rhythms: real-time (when a user submits a report) and daily batch aggregation (when operation reports are generated). A single data entry contains fields such as unique report identifier, reported content ID, reporter account, report reason, processing progress, and disposal result. Most fields are string or timestamp types, and some associated fields must match the internal community account system.
What constraints these characteristics impose on the database and operations link
Database connection pools must support high-concurrency access for real-time submitted report data to avoid blocking business processes due to connection exhaustion. Targeted indexing for associated data from multiple sources speeds up query efficiency for report status and disposal results. Schedule daily batch-generated operation reports via timed tasks to avoid peak business hours. Configure data validation rules for fields associated with the community account system to prevent cross-table data inconsistency. Retain complete operation logs to facilitate root cause analysis for issues such as retained violating content and user complaints.
How to configure the settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 100–200 connections | Addresses concurrent access demands from real-time report submissions and batch operation reports, avoiding connection pool overflow |
MONGODB_URI | Cluster address with read-write separation suffix | Stores unstructured data such as reported content details and appeal form attachments; read-write separation reduces load on single nodes |
PG_URL | Connection address prioritizing read replicas | Stores structured data such as report tickets and processing records; batch queries use read replicas to avoid occupying primary database resources |
REDIS_URL | 600-second cache expiration time | Caches frequently queried audit rules and user historical report records, reducing repeated database query frequency |
| Database backup scheduling cycle | 0 2 * * * | Avoids daily peak business hours to complete full data backups and ensure fault recovery capabilities |
This page applies to FastGPT v4.17.0
Three common configuration mistakes
- Symptom: Executing an SQL query returns empty results after configuring the database connection address. Cause: The database access whitelist is not configured, or the connection address parameter is filled incorrectly, preventing connection to the target database instance.
- Symptom: Connection timeout errors occur when submitting batch report tickets. Cause: The
DB_MAX_LINKsetting is too low, failing to support concurrent report submission requests, and the connection pool is exhausted and cannot allocate new connections. - Symptom: After updating an audit rule, the system still uses the old rule to process reports. Cause: The cache expiration time configured in
REDIS_URLis too long, and the rule data in the cache is not refreshed in a timely manner.
How to verify the configuration is correct
- Submit a small number of test report requests, check the database connection pool monitoring metrics, and confirm that the number of connections does not reach the configured
DB_MAX_LINKupper limit. - Manually trigger an operation report generation task, confirm that the latest report ticket data can be pulled from the database.
- Modify an audit rule, wait for the cache to expire, then query and confirm that the system uses the updated rule to process reports.
- Check the database backup logs to confirm that the daily backup task has executed normally according to the configured scheduling cycle.
The configuration values provided here are common starting points, and should be evaluated against your own specific samples and workloads.
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.