Reference only; verify against the target FastGPT release and deployment documentation.
What data in this category looks like
Data sources for mine mining and beneficiation ledgers include real-time sensors of mining equipment, PLC control systems for mineral processing, truck scale weighing systems, safety inspection forms, and more. The pace of data updates varies significantly: equipment operating parameters are updated in real time at the second level, truck scale weighing data is uploaded in batches after shifts, and safety inspection ledgers are updated daily. Each ledger document contains fields such as device ID, measurement point name, collection time, value, unit, inspector, and anomaly flag. Units include industry-specific formats such as tons, cubic meters, hours, and percentage. There is no unified fixed field structure, and some unstructured data requires separate storage.
What constraints do these characteristics impose on the database and operations link
High-frequency writes of second-level real-time data require sufficient database connection pool capacity to avoid service interruptions caused by exhausted connections. Heterogeneous formats of multi-source data require the database to support both structured and unstructured storage, balancing query efficiency and write flexibility. Daily updated inspection ledgers require scheduled batch processing, so a stable scheduled task scheduling mechanism must be configured. Specific units attached to fields require validity checks during writes to prevent dirty data from entering the database. Long-term accumulation of data in single ledger tables leads to rapid data growth, so a table sharding strategy must be planned to maintain query performance, and indexes must be created for frequently queried measurement point fields.
How to set the configuration
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Database connection pool size | 20–30 | Matches the dozens of real-time data write requests per second in mine mining and beneficiation, avoiding connection exhaustion |
| MongoDB connection address | mongodb://user:pass@host:27017/mine_collect | Stores unstructured raw sensor data and semi-structured inspection records |
| PostgreSQL connection address | postgresql://user:pass@host:5432/mine_report | Stores structured ledger summary fields, supporting complex statistical queries |
| Redis connection address | redis://:pass@host:6379/0 | Caches frequently queried measurement point data to reduce database query load |
| Scheduled task execution interval | 86400 seconds | Adapts to the daily updated inspection ledger summary workflow |
| Cache expiration time | 300 seconds | Adapts to the update frequency of real-time measurement point data, balancing cache hit rate and data freshness |
Three common mistakes
- Symptom: Unable to create a database after local deployment, with a database connection failure prompt in the interface. Cause: The
MONGODB_URIorPG_URLparameters were not filled correctly, the database service was not started, or the corresponding port was not granted firewall access permissions. - Symptom: When concurrent requests increase, model response latency increases significantly, and logs show that MongoDB write operations take too long. Cause: The database connection pool size configuration is insufficient to support concurrent write and query requests for multi-source data from mine mining and beneficiation.
- Symptom: Returns a 429 status code when concurrency exceeds the threshold, making report generation impossible. Cause: No concurrency current limiting was set in the application configuration, and direct calls to external model interfaces exceeded the service provider's concurrency limits.
How to confirm the configuration is correct
- Log in to the database management tool, enter the connection address corresponding to
MONGODB_URI, and verify that you can successfully connect and view the collections related to mine mining and beneficiation that have been created. - Execute a query statement for structured ledgers to verify that the database corresponding to
PG_URLcan normally return records containing fields such as device ID and collection time. - Initiate 10 concurrent ledger summary requests, check the database connection pool usage, and confirm that the number of connections does not exceed the configured upper limit.
- View the Redis monitoring panel, confirm that the cache hit rate of frequently queried measurement point data meets expectations, and there are no large numbers of repeated database queries.
The values given 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.