What Data for This Category Looks Like
This category of data is generated around the full publication declaration process for a single game. Sources include the National Press and Publication Administration’s service portal, copyright registration documents, game packages, and materials submitted by operating institutions. Daily documents include declaration request files, game application forms, copyright certificates, review reports, and more. Teams archive data for each single game, with updates triggered irregularly based on declaration progress. Data fields cover approval node status, material numbers, submission deadlines, and more. No unified batch update rhythm exists.
Constraints on Database and Operations Linked to These Characteristics
The data traits of this category impose multiple constraints on database and operations workflows. First, decentralized multi-source data requires the database to support mixed storage of unstructured and structured data, to adapt to different formats of declaration materials. Second, irregular update cycles require the database to have flexible field expansion capabilities, to avoid hard-coded structures limiting iterative modifications to declaration materials. Third, the archive isolation requirement for individual projects demands strict access controls, to prevent data mixing across different declaration projects. Fourth, frequent material consistency checks during approval processes require the database to build efficient indexes for fields like approval nodes and material types, to speed up retrieval. Additionally, the high-stakes nature of errors requires the operations workflow to strengthen data backup and consistency verification mechanisms, to prevent data loss from delaying approval progress.
How to Configure Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://admin:securepass@db-host:27017/game_approval?retryWrites=true&w=majority | Stores unstructured documents such as declaration requests and review reports. Supports flexible document structures to adapt to material formats across different declaration stages, and is compatible with FastGPT v4.17.0 storage architecture |
PG_URL | postgresql://admin:securepass@pg-host:5432/game_metadata?sslmode=require | Stores structured data such as approval node status, copyright numbers, and package hashes. Supports multi-condition joint queries for material consistency checks |
DB_MAX_LINK | 15–25 | Adapts to concurrent query demands for team collaboration, and prevents excessive connections from occupying database resources and delaying approval workflows |
REDIS_URL | redis://:securepass@redis-host:6379/1 | Caches frequently retrieved approval status and material metadata, to reduce repeated query load on the database |
Three Common Configuration Mistakes
- Symptom: Backup operations fail to restore complete declaration data, with some review reports missing. Cause: Backup parameters for
MONGODB_URIare not configured correctly. Only structured metadata is backed up, not unstructured documents. - Symptom: Containers fail to start with the error
column vector does not exist, and the declaration data page cannot load. Cause: The PostgreSQL vector extension was deleted, and the FastGPT initialization script was not re-run. This leads to missing fields for storing metadata. - Symptom: Database connections fail after deploying a Docker image, and the frontend displays a 503 status code. Cause: The
PG_URLconfigured inside the container does not match the host machine’s database address, or network policies restrict communication ports between the container and database.
How to Verify Proper Configuration
- Run a database connection test command to verify that the addresses, ports, and authentication information configured for
PG_URLandMONGODB_URIcan connect normally. - Check the running status of the Redis service, and confirm that the instance configured with
REDIS_URLcan read and write cached data normally. - Submit a test declaration data entry, and check whether corresponding documents and metadata are generated in the database to verify that the storage structure meets expectations.
- Simulate multi-user concurrent queries, and confirm that the number of database connections does not exceed the configured
DB_MAX_LINKthreshold, with no connection errors.
The values provided here 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 2026-10-19.