What this category of data looks like
Core data for this category originates from local public data disclosure platforms, integrated big data platforms, departmental business databases, and electronic credential repositories. It includes public data resource catalogs, data disclosure lists, data item descriptions, anonymization rules, interface documentation, and update frequency descriptions. Data updates occur monthly. Required processes include sorting departmental open data items, cleaning data, converting anonymized formats, and marking open conditions and update frequencies. Most data uses structured fields, such as data item codes, affiliated departments, disclosure scope, anonymization methods, and interface addresses. Consistency between stored data and actually disclosed data must be maintained.
Constraints during deployment and upgrade
The monthly update frequency requires configuring scheduled synchronization tasks during deployment to ensure timeliness between catalog data and actually disclosed data. Multiple data sources require adaptation to different databases and storage connection parameters. Support for multiple storage types such as PostgreSQL and Redis must be included. Multiple document structures require configuring multi-format parsing rules to support import of different formats including catalogs, lists, and interface documentation. The complexity of anonymization rules and authorization boundaries requires configuring associated logic for permission verification and data anonymization during deployment to avoid data leakage risks. Failure consequences include data leakage, inconsistencies between catalogs and actual data, and unavailable open interfaces. Thus, failure retry and alert mechanisms must be configured during deployment.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PG_URL | postgresql://username:password@internal database address:5432/public data catalog database | Standard PostgreSQL connection format for storing structured catalog data, adapted for internal deployment scenarios |
REDIS_URL | redis://:cache password@internal cache address:6379/1 | Caches catalog update status and interface call tokens, uses database 1 to isolate cached data for public data services |
DB_MAX_LINK | 20–30 concurrent connections | Adapts to concurrent volume of monthly batch data imports, prevents database connection exhaustion |
STORAGE_S3_ENDPOINT | http://internal object storage address:9000 | Stores anonymized interface documentation and anonymization rule files, adapted for internal deployment environments without public network access |
FILE_TOKEN_KEY | custom 32-character random string | Used to generate temporary access tokens for catalog document downloads, ensuring secure data access |
Three Common Misconfigurations
- Symptom: A 500 error is returned when calling the catalog synchronization interface, and curl tests show interface anomalies. Cause:
PG_URLorREDIS_URLparameters are not configured correctly, database connection timeout occurs, or cache token verification fails. - Symptom: Ledger reports that meet expectations cannot be generated after offline deployment. Cause: The number of documents imported per batch is not limited based on local storage capacity, and resource upper limit verification is not configured for offline environments.
- Symptom: Some data items have empty open condition fields after monthly ledger generation. Cause: Field integrity after data cleaning is not verified, and alert logic for missing fields is not configured.
How to Verify Successful Configuration
- Run
docker psto check the running status of FastGPT v4.17.0 related containers, and confirm that the database and cache services corresponding toPG_URLandREDIS_URLare properly connected. - Upload a standard public data resource catalog template document, trigger the ledger summary task, and check that the task logs contain no database connection or storage error messages.
- Access the frontend address corresponding to
FE_DOMAIN, test the monthly report generation function, and confirm that the report includes complete fields such as data item codes, affiliated departments, and disclosure scope. - Trigger a manual synchronization task, wait for the task to complete, check the consistency between the open list and catalog data, and confirm that updated information has been synchronized.
Final Note
The values listed are common starting points and should be evaluated 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.