What the Data for This Category Looks Like
Data for this category originates from slab or billet batches, heating furnaces, mill automation control systems, online thickness and width measurement equipment, surface inspection devices, and MES systems. Daily generated documents include rolling plans, heating schedules, rolling specifications, shape and thickness records, surface quality reports, and quality certificates.
Data is updated per coil or per billet. Some process parameters and test results are synced in real time. Coil-level traceability logic links batch information, process parameters, test results, and quality judgment results. Fields include batch number, thickness deviation, surface defect type, heating temperature, and more.
What Constraints Do These Characteristics Impose on Database and Operations Maintenance Work
Multi-source data access creates high-frequency concurrent write pressure. Mixed storage of real-time test data and batch documents requires databases with flexible schema adaptation capabilities.
The core coil-level traceability requirement requires databases to support multi-table join queries to restore the full process chain. High-frequency update cycles impose clear constraints on database connection pool configuration. Connection exhaustion must be avoided to maintain business continuity.
Data formats vary across different production processes. Operations teams must unify data validation rules to filter dirty data and ensure traceability accuracy. Cross-process data consistency must also be maintained to prevent breaks in the traceability chain that would affect defect analysis results.
How to Configure the System
This configuration is adapted for FastGPT v4.17.0. Specific parameters are listed below:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
MONGODB_URI | mongodb://<user>:<pass>@<host>:27017/steel_roll_trace?replicaSet=rs0 | Supports replica set high-availability deployment, adapts to high-frequency writes of real-time test data, and persists full coil-level traceability data |
PG_URL | postgresql://<user>:<pass>@<host>:5432/steel_quality?search_path=quality_analysis | Supports complex multi-table join queries, stores structured data such as rolling plans, thickness records, and surface quality reports |
DB_MAX_LINK | 80–120 connections | Adapts to high-frequency concurrent writes per coil or real-time, balances database memory usage and concurrent processing capabilities, and avoids connection exhaustion |
REDIS_URL | redis://:<pass>@<host>:6379/0 | Caches basic rolling batch information and temporary online test data to reduce query pressure on core databases |
| Data Validation Rules | Calibrated based on actual measurements | Adapts to differences in field formats across processes, filters dirty data that does not meet process requirements |
| Backup Strategy | Daily full backup + hourly incremental backup | Matches the update frequency of coil-level data, enabling rapid recovery when data anomalies occur |
Three Common Configuration Errors
- Phenomenon: A
connection refusederror occurs during deployment, or database connection pool initialization fails. Cause: Configuration items for different types of databases are incorrectly mixed, and relational database parameters are bound to non-corresponding containers, resulting in a mismatch between the configuration file and the actual deployment environment. - Phenomenon: Real-time test data write delay exceeds the business tolerance range, or some coil-level data is lost. Cause: Replica set mode is not configured for MongoDB. A single-point database cannot handle high-frequency real-time write pressure, making rapid data recovery impossible after an exception.
- Phenomenon: After the MongoDB replica set primary node drifts, the service disconnects and cannot automatically reconnect. Cause: The replica set name is not configured in
MONGODB_URI. The database driver cannot identify the new primary node address, resulting in failure to automatically recover after a connection interruption.
How to Verify That the Configuration Is Correct
- Run database connectivity tests to verify the connection status of
MONGODB_URI,PG_URL, andREDIS_URL, and confirm that the parameter configuration is correct. - Simulate the write and multi-table join query process for a single coil of data, check the completeness of the coil-level data association relationship, and verify that the query performance meets business expectations.
- Adjust the
DB_MAX_LINKparameter, observe the real-time occupancy of the database connection pool, and confirm that the configuration can cover daily concurrent peaks. - Trigger a MongoDB replica set primary node switch, verify whether the service can automatically reconnect, and confirm that the high-availability configuration takes effect.
The values listed here are common starting points and should be evaluated against the reader's own samples.