What this type of data looks like
Data sources include construction machinery factory certificates, equipment maintenance ledgers, construction project filing files, and procurement declaration forms. Update cadence follows three patterns: batch updates when new devices go online, periodic synchronization of monthly maintenance records, and real-time submission of review files during the review workflow. Document structure includes structured forms (with fields such as equipment ID, rated lifting capacity) and unstructured attachments (PDF test reports, site photos). Fields include 17-character alphanumeric device serial numbers, rated lifting capacity measured in tons, operating hours measured in hours, and file numbers with year prefixes.
What constraints do these characteristics impose on deployment and upgrades
The data characteristics of this category impose multiple constraints on deployment and upgrade operations. The multi-type field storage requirements of structured forms require databases to support multiple data formats such as characters, numerical values, and enumerations. Single unstructured test reports can reach tens of megabytes in size, so sufficient storage resources and reasonable file upload limits must be configured. The global uniqueness requirement for device serial numbers requires database connection pools to support high-concurrency queries to avoid duplicate submissions. Short-term high write pressure from batch maintenance data updates requires adjustments to database connection parameters. Temporary states of file review workflows must use Redis caching to enable fast read and write operations.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 20–30 | Adapts to the high-concurrency query and batch write requirements of construction machinery declaration data, and avoids database connection exhaustion |
MONGODB_URI | mongodb://user:pass@host:27017/fastgpt?authSource=admin | Unstructured attachment metadata for file reviews and device historical records are suitable for MongoDB's document-oriented storage |
PG_URL | postgresql://user:pass@host:5432/fastgpt | Structured declaration forms, file numbers and other fields are suitable for transactional storage in relational databases |
REDIS_URL | redis://:pass@host:6379/0 | Caches temporary states of review workflows and hot data for device queries, reducing database read and write pressure |
STORAGE_S3_ENDPOINT | Fill in according to the access address of the local object storage or cloud storage service provider | Adapts to the distributed storage requirements of large unstructured test reports |
FILE_TOKEN_KEY | Randomly generated 32-bit string | Ensures access security for uploaded attachments and prevents unauthorized file access |
Three common mistakes
- Phenomenon: A
MongoDB connection timeouterror appears when starting the container after deployment, or a 503 status code is returned when loading declaration data on the page. Cause: TheDB_MAX_LINKparameter is not adjusted according to the high-concurrency requirements of construction machinery data, resulting in database connection pool exhaustion. - Phenomenon: Uploading a construction machinery test report larger than 50 MB triggers an upload failure prompt. Cause: Reasonable file size limits are not configured, or the storage service pointed to by
STORAGE_S3_ENDPOINTdoes not allow large file upload permissions. - Phenomenon: After migrating data from the PostgreSQL version to the vector storage version, the query results for device serial numbers are empty. Cause: Structured device number fields are not mapped to index fields in the vector database, or uniqueness constraints for the fields are not retained during migration.
How to confirm correct configuration
- Run the built-in database connection test tool to verify the connection status of
MONGODB_URIandPG_URL, and confirm there are no timeout or permission errors. - Upload a PDF test report that meets construction machinery declaration requirements, and verify that the
STORAGE_S3_ENDPOINTstorage function works normally, and the file can be downloaded and viewed correctly. - Submit a simulated device declaration record, check whether the corresponding structured record and unstructured metadata are generated in the database, and confirm that the
DB_MAX_LINKconnection count does not trigger exhaustion. - Start the FastGPT v4.17.0 backend service, check that there are no Redis connection failure errors in the logs, and confirm that the
REDIS_URLconfiguration is correct.
The values provided here are common starting points, and should be evaluated 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.