What Data Looks Like for Precast Concrete Components
Data related to precast concrete components comes from BIM detailed design documents, steel bar and concrete batch ledgers, mold table and curing kiln operation logs, laboratory test reports, and product QR code traceability systems. Daily documents include component detailed drawings, steel bar cutting lists, mold inspection records, pouring and vibration records, curing records, demolding and factory inspection reports. Data is updated per individual component, each batch of raw materials, and each curing kiln unit. Fields include component number, steel bar specification, concrete strength grade, curing duration, demolding strength, and others. Units include millimeters, megapascals, hours, and additional standard units.
Constraints Imposed by These Characteristics on the Database and Operations & Maintenance Link
Data for this category is updated frequently per individual component, batch, and kiln run. Each single data entry is linked to multi-dimensional documents and ledgers, requiring support for complex multi-table join queries. Large-scale engineering files such as component detailed drawings coexist with lightweight inspection records. The database must balance structured data storage and unstructured document indexing. The volume of individual piece data linked via QR code traceability fluctuates with orders, requiring dynamic scaling to support peak load. Data formats from different sources vary, so unified field mapping rules must be implemented to avoid data redundancy or missing entries. Data association errors can lead to serious consequences such as on-site installation deviations and component scrapping. Read-write consistency must be ensured, and the operations & maintenance link must regularly verify the integrity of the data link.
How to Configure Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PG_URL | postgresql://user:pass@host:5432/pc_component_db?charset=utf8mb4 | Stores structured associated data such as component ledgers and batch information, supports complex multi-table queries and transaction operations |
MONGODB_URI | mongodb://user:pass@host:27017/pc_component_files?retryWrites=true&w=majority | Stores unstructured documents such as detailed drawings and curing records, supports large file indexing and flexible queries |
DB_MAX_LINK | 20–30 | Adapts to concurrent requirements of frequent individual piece updates and multi-dimensional queries, prevents database connection exhaustion |
REDIS_URL | redis://:authpass@host:6379/0 | Caches individual piece data linked via QR codes and frequently queried component information, reduces direct database query load |
Three Common Configuration Mistakes
- Symptom: After deploying via Docker image, the console reports "connection refused" error, and database connection fails. Cause: The host database address was not written to the environment variables during image construction. The default localhost points to the container's internal network, making external database services inaccessible.
- Symptom: Chinese inspection records or component names stored in the database display garbled characters. Cause: The database connection configuration does not specify the correct character set parameter, or the system character set settings are not synchronized within the container.
- Symptom: Some data is lost or fails to write when importing multiple batches of component data in bulk. Cause: The
DB_MAX_LINKsetting value is too small. Concurrent write requests exceed the database connection limit, causing some requests to be rejected.
How to Confirm Configurations Are Correct
- Use the database connectivity test tool built into FastGPT v4.17.0 to verify the configurations of
PG_URL,MONGODB_URI, andREDIS_URLseparately, confirming no connection errors. - Import a single component inspection record containing Chinese content, then query to confirm that Chinese fields display normally with no garbled characters.
- Simulate bulk data write operations, check database connection usage, and confirm that the
DB_MAX_LINKsetting covers concurrent request peaks. - View cache logs to confirm that frequently queried component data has been correctly cached, reducing the number of direct database queries.
The values provided are common starting points and should be measured against the reader's own samples.