What the data for paper manufacturing categories looks like
Market data for paper manufacturing categories comes from the paper section of domestic bulk commodity trading platforms and public market data interfaces from the China Paper Industry Association. Full market data for the previous calendar day is updated at 02:00 daily. The document uses a structured table format, with each row corresponding to a single paper product category. Fields include: category name, daily ex-factory average price (unit: yuan/ton), main raw material purchase average price (unit: yuan/ton), actual daily shipment volume (unit: ton), daily production line operating duration (unit: hour). Data only covers industry-specific indicators for paper manufacturing, with no redundant cross-category fields.
What constraints do these characteristics impose on workflow orchestration
First, data updates at a fixed daily time. Workflows must be configured with a scheduled trigger node, and the trigger time must be later than the data source update completion time to avoid pulling outdated unupdated data. Second, fields only cover paper category-specific ex-factory price, raw material price, shipment volume, and operating duration. Workflows need to pre-configure a field whitelist to only retain paper-related data fields and filter out irrelevant fields. Third, numeric fields have clear units. A unit validation logic must be added to the data cleaning step to prevent unit confusion across category data. Fourth, public data sources have call frequency limits. Workflows must configure call interval parameters to avoid triggering interface rate limits.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
CRON_EXPRESSION | 0 0 3 * * * | The data source completes updates at 02:00 daily. Triggering one hour later ensures the latest complete data is pulled |
DATA_FIELD_WHITELIST | Category Name, Daily Factory Average Price, Main Raw Material Purchase Average Price, Daily Actual Shipment Volume, Daily Production Line Operating Duration | Only retain paper category-specific data fields, filter out irrelevant fields to simplify subsequent processing logic |
API_CALL_INTERVAL | 5 seconds | Public industry data sources typically limit calls to no more than 20 times per minute. A 5-second interval complies with call frequency limits |
API_REQUEST_TIMEOUT | 10 seconds | Paper market interfaces have stable response speeds. 10 seconds is sufficient for data pulling and initial parsing |
WORKFLOW_VALIDATION_TIMES | 3 times | Daily pull task stability must be verified to avoid task failure caused by single interface fluctuations |
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 individual analysis. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- The symptom is a "Please check if nodes are filled correctly" prompt in the workflow debug interface, with a 400 status code returned by the interface. The cause is that paper category-specific fields are not configured in
DATA_FIELD_WHITELIST, causing the node to filter all valid data and leave the node input empty. - The symptom is "Invalid character parsing failed" in data cleaning logs, with some category name fields empty. The cause is that paper category names contain special characters such as double quotes, and no escaping rules are configured in the data cleaning node.
- The symptom is no baseline test result output after the workflow runs. The cause is that the workflow's baseline test configuration item is not enabled, and the sample dataset and evaluation metrics for the comparative experiment are not specified.
How to confirm the configuration is complete
- Manually trigger the workflow once, check that the pulled data only includes the pre-configured paper category-specific fields, with no irrelevant fields included.
- Check the workflow's scheduled task logs to confirm the trigger time is later than the data source's update completion time, with no early triggers.
- Run the data cleaning node, verify that category names containing special characters can be parsed normally with no error logs.
- Enable the baseline test configuration, run the comparative experiment, confirm that the generated evaluation results can be exported normally.
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.