What the data for this category looks like
Production data for this category covers the full process of carbonated drink, juice, tea drink, functional drink, and packaged drinking water factories. Daily documents include recipe sheets, water treatment records, preparation records, sterilization or aseptic filling records, packaging material inspection records, and finished product inspection records. Data comes from water source and raw material testing systems, recipe management systems, online sugar and acidity monitoring equipment, filling equipment, visual inspection equipment, and LIMS systems. Updates occur per production batch, per shift operation, and via continuous real-time collection. Fields include raw material batch numbers, testing values, equipment parameters, inspection results, and more. Some fields must be associated with batch numbers and shelf life information.
Constraints Imposed on Database and Operations by These Data Characteristics
This category’s data characteristics create multiple constraints for the database and operations link. Real-time data collected continuously from multiple sources requires databases to support high-concurrency writes and low-latency reads. This ensures data synchronization for critical links such as filling and inspection. Multiple document types cover structured test values and unstructured logs. This requires compatibility with mixed data storage formats. Updates tied to batches and shifts require data to be partitioned and archived by production batch. This prevents excessive data volume in single tables. Fields linked to batch numbers and shelf life must follow strict primary key rules. This prevents data misalignment across batches, and provides clear query dimensions for cross-source association in ledger aggregation.
How to Configure Settings
The following configurations apply to FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
MONGODB_URI | mongodb://[username:password@]host1:port1,host2:port2/?replicaSet=rs0&authSource=admin | Multi-source real-time data for this category requires highly available storage. Replica set configuration ensures write stability, and adapts to high-concurrency requirements for continuous collection |
PG_URL | postgresql://username:password@host:port/dbname?sslmode=require | Structured batch and inspection data requires strongly consistent queries. SSL encryption secures transmission of sensitive test data |
DB_MAX_LINK | 200–300 | Adapts to concurrent connection demands from continuous multi-device collection. Prevents data write interruptions caused by exhausted connection pools |
REDIS_URL | redis://:password@host:port/0?maxmemory-policy=allkeys-lru | Used to cache batch metadata and frequently queried test results. The LRU policy ensures reasonable cache resource utilization |
Three Common Configuration Mistakes
- Phenomenon: Database write interruptions occur when application concurrency exceeds expected levels. Cause: The
DB_MAX_LINKconfiguration value is too low, and does not adapt to concurrent demands of simultaneous multi-device collection. - Phenomenon: A
400 Messages with role 'format error returns when executing a database query plugin. Cause: The context parameter’s role field is not configured correctly, or the incoming request body lacks the required role identifier. - Phenomenon: Water treatment or filling process records are missing from ledger aggregation results. Cause: The batch number field of multi-source data is not used as an association key, so cross-system data cannot be matched correctly.
How to Confirm Proper Configuration
- Execute a single-batch ledger query. Verify that returned results include full process record fields such as recipes, water treatment, and filling. Confirm that data association logic works as expected.
- Simulate multiple concurrent write requests. Check that no database connection pool exhaustion errors appear. Confirm that the configuration adapts to actual concurrency demands.
- View the cache monitoring panel. Confirm that the cache policy regularly recycles expired batch metadata, to avoid resource overflow.
- Test transmission of sensitive test data. Confirm that the encryption configuration takes effect, with no plaintext transmission risk.
The values provided are common starting points and should be measured against the reader's own samples.