What the data for this category looks like
Personal care product profit margin data primarily comes from internal brand inventory and sales systems, third-party e-commerce platform APIs, and publicly available industry monitoring datasets. Data is split by SKU. Each record includes fields such as SKU code, product name, brand name, unit cost, unit selling price, daily sales volume, daily total revenue, and gross margin coefficient. Units are uniformly yuan per item or unitless coefficients. Update cadence has two modes: full data synchronization completes daily between 2:00 and 4:00 AM, and core SKUs support hourly incremental updates. Single data documents use standardized JSON or CSV formats with no nested complex hierarchies.
What constraints do these characteristics impose on database and maintenance workflows
Multi-data source access requires configuring cross-source data consistency check rules to avoid data discrepancies between internal systems and third-party platforms. For fine-grained storage requirements by SKU and statistical date, the primary key must be bound to the SKU code and statistical date fields to prevent duplicate records. For scenarios where daily full synchronization and hourly incremental updates coexist, a date-partitioned table structure must be used to reduce single-table query pressure and synchronization time. For cases with a large number of SKUs, a scheduled task for automatically cleaning expired historical data must be configured to prevent exhaustion of storage resources. For traffic fluctuations from real-time incremental synchronization, the number of concurrent synchronization tasks must be limited to avoid occupying core resources of the business database.
How to set the configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
DB_POOL_SIZE | 15–25 | Adapts to query pressure from the large number of personal care SKUs, and prevents database connection exhaustion |
SYNC_INTERVAL_HOUR | 1 | Matches the hourly incremental update requirement for core SKUs, and controls synchronization frequency |
INCREMENTAL_SYNC_ENABLE | true | Differentiates between full and incremental synchronization tasks, reducing resource usage from daily full synchronization |
DATA_CLEANUP_DAYS | 90 | Retains detailed data for 90 days, automatically archives data beyond this range, and controls storage scale |
INDEX_FIELD_LIST | ["skucode", "statdate", "brand_name"] | Creates indexes based on high-frequency query fields to improve data retrieval efficiency |
MAX_SYNC_CONCURRENCY | 8 | Calibrated based on actual testing, avoids synchronization tasks from occupying core resources of the business database |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material forms, data volume, and business rules. Specific issues require individual analysis, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Symptom: An error is triggered during saving or running when initializing an AI model for a new question classification node, and the error disappears after switching the AI model. Cause: The initialized model is not bound to the data source permissions for profit margin data, and cannot read field information from the corresponding database table.
- Symptom: After upgrading from v4.9.13 to v4.10.1, profit margin data in the knowledge base fails to sync and display. Cause: The upgrade script did not execute the table structure change for incremental data synchronization, causing the newly added statistical fields to not be recognized by the system.
- Symptom: When querying profit margin data for a specified date, the number of returned results does not match expectations, and a large number of expired data records are included. Cause: The
stat_dateindex in theINDEX_FIELD_LISTconfiguration is not set, resulting in inefficient full-table scan filtering and return of records from non-target dates.
How to confirm the configuration is correct
- Run the database connection test script to verify that connections for the
DB_POOL_SIZEconfiguration can be established normally, with no timeout or connection refused errors. - Manually trigger an incremental synchronization task, check the synchronization logs, and confirm that there are no duplicate, lost, or format-error records.
- Enter a specified SKU code and statistical date to query profit margin data, and confirm that the returned fields match the
INDEX_FIELD_LISTconfiguration. - Check the running logs of the data cleaning task to confirm that historical data older than 90 days has been automatically archived to offline storage.
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.