Hazardous Chemicals Storage and Transportation Ledger Summary and Report Generation: Database and Operations Maintenance

Hazardous Chemicals Storage and Transportation Ledger Summary and Report Generation: Database and Operations Maintenance

What the data for this category looks like

The data for hazardous chemicals storage and transportation comes primarily from tank farm temperature, humidity, and pressure sensors, transportation vehicle GPS terminals, warehouse in-out inventory registration systems, and loading and unloading operation record terminals. Data updates follow two rhythms. Real-time data (sensors, terminal positioning) updates every second or minute. Batch data (in-out inventory ledgers, monthly inventory counts) updates daily or per batch. A single data record includes fields such as the hazardous chemical’s common name, CAS registration number, storage bin number, inbound time, outbound quantity, real-time temperature and humidity, transportation license plate number, and carrier number. Units include tons, degrees Celsius, megapascals, kilometers, hours, and others.

Reference only; verify against the target FastGPT release and deployment documentation.

How to set the configurations

Configuration ItemRecommended ValueRationale
MONGODB_URImongodb://admin:securepass@db-host:27017/whp_storage?replicaSet=whp-rsAdapted for storing real-time sensor data from hazardous chemical storage and transportation; replica set configuration ensures high availability and data redundancy
PG_URLpostgresql://admin:securepass@db-host:5432/whp_ledger?sslmode=requireStores structured ledger data and associated query data; sslmode=require ensures encrypted data transmission
DB_MAX_LINK20–30Balances database connection pool resource usage and read-write concurrency peaks, matching the read-write rhythm of hazardous chemical data
REDIS_URLredis://:securepass@cache-host:6379/0Caches ledger statistics results from high-frequency queries to reduce repeated query pressure on core databases

Three common misconfigurations

  • Symptom: connection refused error appears after Docker deployment, and the interface returns a 503 status code. Cause: The connection addresses for MONGODB_URI or PG_URL were not modified correctly in the deployment configuration, causing the application to fail to connect to the database.
  • Symptom: Associated fields are empty in ledger summary results, such as missing storage bin information. Cause: Database indexes were not created for core associated fields such as hazardous chemical CAS numbers and storage bin numbers, causing multi-table associated query timeouts or no matching results.
  • Symptom: Real-time sensor data write delay exceeds 10 seconds. Cause: The DB_MAX_LINK configuration value is too low, failing to support concurrent requests for high-frequency writes, leading to connection pool exhaustion.

How to verify a correct configuration

  • Run the built-in database connection test tool in FastGPT to verify that the connection status of MONGODB_URI and PG_URL is normal, with no timeout or permission errors.
  • Import a test hazardous chemical ledger data record, check that the corresponding fields in the database are fully written and the format conforms to preset rules.
  • Trigger a ledger summary task, confirm that the returned result includes all associated fields and the data matching meets expectations.
  • View the Redis cache monitoring panel, confirm that ledger statistics results from high-frequency queries are properly cached, with no cache penetration or expiration anomalies.

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.