What Data for This Category Looks Like
Business data for this category comes primarily from the level editor, art resource library, player test data, and defect system. Daily produced documents include level design drafts, resource requirement lists, test feedback sheets, and version submission records. Level design drafts contain scene coordinates, resource mount points, and trigger logic fields. Resource requirement lists mark resource IDs and usage quantities. Test feedback sheets record defect severity levels and reproduction steps. Version submission records include submitters, timestamps, and change details. Data updates occur weekly or with each version iteration. The volume of updated documents fluctuates based on the scale of the target level.
What Constraints These Characteristics Impose on Database and Operations Workflows
Multiple data sources introduce heterogeneous data formats. Unified parsing is required for JSON files exported from the level editor, resource lists from the art library, structured feedback from player tests, and ticket data from the defect system. Weekly or version-level bulk updates require databases to support high-throughput bulk writes and incremental synchronization. Level data includes strongly correlated fields such as scene coordinates and trigger logic. Composite indexes must be created to maintain query efficiency. Data anomalies directly cause level freezes or launch delays. Atomicity and consistency must be guaranteed for data writes. This avoids level logic breaks caused by failed partial updates. Logical isolation must be implemented for data from different levels. This prevents mixing of test data and production data.
How to Configure Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
MONGODB_URI | mongodb://level_user:secure_pass@node1:27017,node2:27017/?replicaSet=rs_level&retryWrites=true | Adapts to hierarchical storage requirements for level data. Replica set configuration and retry parameters ensure service availability during primary node failover, and meet data source connection requirements for FastGPT v4.17.0 |
DB_MAX_LINK | 30–60 connections | Balances single-instance connection count and concurrent write capacity. Adapts to mixed workloads of weekly bulk updates and daily queries |
REDIS_URL | redis://cache_user:secure_pass@cache-host:6379/1 | Caches frequently accessed level configuration data and player test feedback tags. Reduces query pressure on the core database |
PG_URL | postgresql://ops_user:secure_pass@pg-host:5432/level_ops_db | Stores structured test feedback sheets and version submission records. Ensures consistency of transactional writes |
| Bulk Write Threshold | 500 items per batch | Adapts to bulk data submissions during version iterations. Reduces network overhead and database load per write operation |
| Connection Timeout | 240 seconds | Adapts to bulk import scenarios for large level data. Prevents long-running tasks from being forcibly terminated |
Three Common Misconfigurations
- Console repeatedly displays "Database connection disconnected, automatic reconnection failed" errors. Version submission records have missing fields. This occurs because the automatic reconnection parameter for the replica set is not configured in
MONGODB_URI. Connections cannot be restored after primary node failover. - Bulk import tasks for large levels fail with 504 timeout status code. This occurs because the bulk write threshold is set too high. It exceeds the database's single-operation processing capacity, and does not adapt to differences in level scale.
- Level resources associated with test feedback sheets are misaligned. They display art assets from other levels. This occurs because cache keys are not isolated by level ID. Configuration data for different levels is overwritten, causing data consistency issues.
How to Verify Correct Configuration
- Manually trigger a version submission for a small level. Check that database write logs are complete, with no missing fields or error messages.
- Simulate a MongoDB replica set primary node failover. Use operations tools to switch the primary node. Confirm that the service automatically restores connections, with no persistent errors.
- View the key list in the cache service. Confirm that each key name includes a unique level ID prefix. No data mixing occurs.
- Run a weekly bulk update task. Confirm that all associated test feedback sheets and version submission records are fully synchronized, with no missing data.
The values listed here are common starting points. They should be evaluated against specific deployment 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.