What the Data for This Category Looks Like
Yield and market data for this category is sourced from the China Paper Association’s daily industry monitoring ledger, domestic commodity spot market paper product quotes, and production daily reports from leading paper enterprises. Data is synced daily in the early morning for the previous day’s full range of paper business data. Each individual data document includes fixed fields: data collection date, paper type classification (e.g., corrugated base paper, white cardstock), raw material cost per unit, ex-factory selling price per unit, unit production capacity input, and unit production capacity revenue. All field units follow uniform standards: date uses YYYY-MM-DD format, price and revenue values use yuan/ton, and input values use tons/day. Data is aggregated by paper type. Each batch of data documents includes corresponding entries for 10 to 20 paper types.
What Constraints Do These Characteristics Impose on Database and Operations Workflows?
This category’s data is multi-source heterogeneous and updated incrementally daily. Databases must support scheduled incremental synchronization tasks to avoid excessive resource usage from full data pulls. The document structure aggregated by paper type requires a composite index on paper type and collection date to improve query efficiency across dimensions. Fields include multiple price and revenue metrics. Format validation rules must be configured during data ingestion to prevent non-numeric data from being stored. The timeliness of data updates requires that database read-write latency be kept within a reasonable range. Operations workflows must regularly check the execution status of synchronization tasks to avoid delayed daily report content. Additionally, conflict validation for multi-source data must be built into database operations workflows to ensure consistency of same-dimensional data from different sources.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://username:password@host:port/paper_yield?authSource=admin | Supports identity authentication and specifies the paper manufacturing yield database, compatible with multi-environment deployment needs |
SYNC_TASK_CRON | 0 0 1 * * ? | Executes synchronization at 1 AM daily, avoids peak business hours, and matches the daily data update schedule |
INDEX_COMPOUND_FIELDS | ["paper_type", "collect_date"] | Covers high-frequency query scenarios by paper type and date, improves retrieval performance |
DATA_VALIDATION_SCHEMA | {"collect_date": {"bsonType": "date"}, "price": {"bsonType": "double", "minimum": 0}, "yield_income": {"bsonType": "double", "minimum": 0}} | Validates date format and numerical legitimacy, prevents dirty data from being ingested |
BACKUP_RETENTION_DAYS | 7 days | Meets historical data query requirements while controlling storage resource usage |
READ_CONCURRENCY_LIMIT | 20 | Balances query performance and server resource usage, adapts to average daily query volume |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require targeted analysis, and it is recommended to test against local samples before finalizing.
Three Common Pitfalls
- Issue: FastGPT connecting to a locally deployed Windows MongoDB returns a
Connection refusederror, with logs showing inability to establish a network connection. Cause: The MongoDB configuration file does not bind0.0.0.0, only allowing access via the local loopback address, and the system firewall has not opened the corresponding port. - Issue: After configuring tool call rules, the knowledge base does not return matching paper manufacturing yield content when present, directly triggering a preset response. Cause: The
TOOL_KNOWLEDGE_BASE_MATCH_THRESHOLDparameter is not configured correctly, or the trigger description editing did not clearly specify the knowledge base matching priority. - Issue: After upgrading FastGPT from v4.6.7 to v4.8.10, the original database table model fails to load, with logs showing an
Unknown collectionerror. Cause: System metadata tables were omitted during database directory migration, or the correctMONGO_INITDB_DATABASEparameter was not configured in the new deployment environment.
How to Confirm Proper Configuration
- Run a database connection test script, attempt to write a simulated paper manufacturing yield data entry and read it back, and verify that fields such as collection date and paper type classification match the source data format.
- View scheduled synchronization task execution logs to confirm that daily incremental synchronization tasks complete on time, with no failed or timed out records.
- Check database index status to confirm that the composite index on
paper_typeandcollect_datehas been successfully created and is active. - Trigger a tool call test to verify that when the knowledge base contains matching paper manufacturing yield content, the corresponding answer is returned, and a preset specified response is returned when no match is found.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.