What the Data for This Category Looks Like
Data for this category primarily originates from advertising platform backends, customer qualification databases, contract systems, and publicly available regulatory rules. Core daily documents include four types: advertising review forms, qualification attachments, delivery records, and rectification notices. Data updates follow a cycle of individual delivery campaigns or natural months. Each individual record includes fields such as delivery entity, qualification ID, compliance review status, and rectification deadline. No unified fixed units apply; field rules must be matched based on document type.
Constraints on Scheduled Tasks and Automation Posed by Data Characteristics
The data characteristics of this category impose multiple constraints on scheduled tasks and automation workflows. Since updates follow individual delivery campaign or natural month cycles, scheduled trigger timing must support flexible configuration to adapt to different update rhythms. Data sources are scattered across multiple systems, so automated workflows must support multi-source data pulling and validation logic. Field rules for individual records change dynamically based on document type, so dynamic field mapping rules must be configured to avoid archiving errors. The time-consuming core links of qualification archiving and rectification evidence organization require batch automated processing, otherwise compliance timelines will be delayed. Failure consequences directly relate to regulatory and customer liability and account penalties, so failed execution links must be fully retained for subsequent retrospective analysis.
This document is compatible with FastGPT v4.17.0.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Task trigger timing | Trigger based on delivery campaign nodes; trigger at 2:00 AM daily during natural months when no active campaigns are running | Matches the update cycle of data based on campaigns or months |
| Multi-source data pulling concurrency | 2-4 concurrent requests | Avoids exceeding the interface rate limit thresholds of advertising platform backends |
| Field mapping validation threshold | 90% match rate | Balances field differences across document types and archiving accuracy |
| Batch processing single limit | 500 records per batch | Fits the single archiving scale of compliance data and avoids task timeouts |
| Failure alert trigger condition | Trigger within 10 minutes after task execution fails | Enables timely response to compliance risks and avoids delayed rectification |
| Log retention period | 180 days | Meets evidence retention requirements for regulatory and customer retrospective reviews |
Three Common Misconfigurations
- Observation: Required global variable validation errors occur for the original app after switching between apps. Cause: Old global variable bindings are not cleared in task configurations, leaving residual old configurations in context.
- Observation: Delivery record fields are empty after scheduled task execution. Cause: No retry mechanism is configured for multi-source data pulling, so failed interface calls do not re-pull corresponding data.
- Observation: Interface rate limit errors occur during batch processing. Cause: Multi-source data pulling concurrency is not restricted, exceeding the interface call limits of advertising platform backends.
How to Verify Proper Configuration
- Manually trigger the scheduled task once, and confirm that the number of pulled documents matches the number of delivery records in the corresponding cycle on the advertising platform backend.
- Review the task trigger timing configuration, and confirm that both delivery campaign nodes and natural month cycle scenarios are covered.
- Check the failure alert configuration, and confirm that task failures will push notifications to the designated channel.
- Verify the log retention configuration, and confirm that the retention period meets compliance requirements.
The values provided 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 2026-10-19.