What this category of data looks like
This category of data originates from the engineering quality and safety supervision system, on-site construction real-name platform, supervision logs, and test reports. Data updates occur weekly. The following documents are processed daily: supervision plans, supervision inspection records, hidden danger rectification notices, quality problem handling forms, and completion acceptance supervision reports. Data fields cover project number, participating unit information, inspection time, hidden danger level, rectification closed-loop status, and additional relevant items. Units include project duration (days), rectification time limit (days), and test values such as MPa and m. The data volume of a single document fluctuates with project scale.
What constraints these characteristics impose on the database and operations maintenance link
Weekly batch data updates require databases to support efficient batch writing and reading, avoiding performance bottlenecks from single-item processing. Heterogeneous documents from multiple sources, such as structured data from the supervision system and unstructured text from supervision logs, require a hybrid architecture that supports both structured and unstructured storage. Data covers the full project lifecycle, and fields adjust dynamically with project phases. Databases must support flexible schema changes. Data links multi-dimensional information such as participating units and hidden danger rectification status, requiring optimization of associated query performance. At the same time, data is linked to quality and safety responsibilities. Real-time backup and abnormal verification mechanisms must be configured to prevent data loss or errors from affecting subsequent acceptance and accident traceability.
How to set the configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
MONGODB_URI | mongodb://admin:securepass@db-host:27017/fastgpt_qc | Stores unstructured documents such as supervision logs and test reports, as well as vectorization results. Supports large text storage and flexible field expansion |
PG_URL | postgresql://admin:securepass@db-host:5432/fastgpt_struct | Stores structured business data such as supervision plans and hidden danger rectification notices. Supports multi-table associated queries |
DB_MAX_LINK | 20–30 | Adapts to concurrent write requirements for weekly batch data imports, avoiding database connection exhaustion |
REDIS_URL | redis://:securepass@cache-host:6379/1 | Caches frequently accessed basic project information and rectification status statistics, reducing database query pressure |
| Batch data import concurrency limit | 5–10 items/second | Matches the weekly updated data scale, avoiding overloading the business system from a single import operation |
Three common mistakes
- Symptom: A MongoDB connection failure error pop-up appears after starting the service. The log shows
connection timed out. Cause: The vulnerablemongo:5.0.18version is used, and no update to a compliant version has been applied. This causes the database service to fail to respond to connection requests normally. - Symptom: Task execution times out when generating completion acceptance supervision reports in batch. A 504 status code is returned. Cause: The
DB_MAX_LINKparameter is not configured properly. The connection pool is filled by batch write requests, and new database requests cannot be established. - Symptom: The closed-loop status of some hidden danger rectification records in the generated account book is empty. Cause: The latest rectification data is not synchronized at the weekly update frequency, and some late-submitted records are not written to the database.
How to confirm the configuration is complete
- Run the built-in database connection test tool to verify that the connections configured via
MONGODB_URIandPG_URLwork normally, with no authentication or address errors. - Import structured and unstructured data for a small number of test projects, and check that the
DB_MAX_LINKparameter supports concurrent writes, with no connection timeouts or rejections. - View the Redis cache monitoring panel to confirm that frequently accessed basic project information hits the cache, and database query times meet expected levels.
- Trigger a small batch data synchronization task, and check that the fields in the synchronized account book are complete, with no missing or incorrectly linked information.
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 2026-09-28.