What the Data for This Category Looks Like
Ledger data for the basic chemical industry has three sources: real-time collection systems in production workshops, weighing records from raw material warehouses, and offline inspection reports from quality control departments. Data updates follow two rhythms: Real-time incremental data for key process nodes is pushed hourly. Full ledger summaries and archiving are completed each day. A single ledger document includes these fields: raw material batch number, feeding mass, average reaction period temperature, intermediate product concentration, final product yield, energy consumption indicators. Unified field units apply: Feeding mass is measured in tons, average temperature in degrees Celsius, yield in kilograms, energy consumption in kilowatt-hours.
Constraints on Database and Operations Maintenance
Multi-source mixed data, hot and cold update differences, strongly correlated fields, and compliance requirements for basic chemical ledger data create multiple constraints for the database and operations maintenance process. Multi-source data includes real-time collected process parameters and offline inspection reports. The system must support mixed workloads of real-time writing and batch import to prevent single-database read-write blocking. There is a clear need for hot and cold data tiering: hourly incremental real-time data should be stored in high-performance storage, while daily summarized historical ledgers can be migrated to low-cost archive storage. Strongly correlated batch number fields require strict foreign key constraints to prevent cross-batch data confusion. Regulatory retention requirements for chemical data require automatic archiving and backup strategies to ensure data traceability.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PG_URL | postgresql://ledger_user:secure_pass@db-host:5432/chemical_ledger?sslmode=require | Batch association and field validation for basic chemical ledgers require transaction and foreign key support from relational databases. PostgreSQL is selected to adapt to structured ledger data |
DB_MAX_LINK | 20–30 | The data volume of a single ledger entry is moderate. The number of concurrent connections must match the peak real-time data write volume during production hours to avoid connection exhaustion |
REDIS_URL | redis://cache_user:secure_pass@redis-host:6379/0 | Used to cache frequently queried batch number mappings and real-time process data to reduce database read and write pressure |
MONGODB_URI | mongodb://archive_user:secure_pass@mongo-host:27017/ledger_archive?authSource=admin | Used to store fully archived historical ledger data, adapting to unstructured inspection attachments and long-text reports |
| Database automatic archiving threshold | 30 days | Migrate historical ledger data older than 30 days to archive storage to reduce storage pressure on the online database |
Three Common Mistakes
- Calling the database query plugin returns the
400 Messages with role 'error. The cause is that ledger data fields contain spaces or special characters, and no escaping was performed when splicing SQL statements, leading to abnormal request formatting. - Locally deploying FastGPT and calling the database connection results in no output. The cause is that the
PG_URLconfiguration does not include thesslmode=requireparameter. Production environment PostgreSQL instances enforce SSL connections, causing connection timeout and no response. - The number of database query return results does not match expectations. The cause is that no reasonable value is configured for
DB_MAX_LINK. The connection pool is exhausted, causing some query requests to be discarded and returning empty results.
How to Confirm Proper Configuration
- Run a test query, enter a known raw material batch number, and verify that the returned fields match the preset ledger structure.
- Check the database connection pool monitoring to confirm that the active connection count does not exceed the
DB_MAX_LINKconfiguration value. - Trigger a batch data import task, and verify that the corresponding data backup is generated in the archive storage.
- Simulate high-concurrency write requests to confirm that the database does not experience read-write blocking or connection errors.
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.