What the Data for This Category Looks Like
Data for this category comes primarily from customers' historical business systems, CSV/Excel templates, and database export files. Updates occur per order or irregularly. Daily supporting documents include data templates, migration plans, field mapping tables, and migration verification reports. Data fields cover business identifiers, business attributes, association relationships, and more. Units are defined by the customer's original system or import template, with no unified fixed format. The implementation process requires confirming field mappings, cleaning dirty data, and conducting post-import sampling checks. Errors may lead to historical data loss, field misalignment, or customer rejection.
What Constraints These Characteristics Impose on the Scheduled Tasks and Automation Link
The diversity of data sources and formats requires scheduled tasks to adapt to multiple data source types and field rules, preventing import failures caused by format incompatibility. Irregular update patterns mean task trigger timing should not rely on fixed cycles, and must support on-demand or event-driven triggering. The field mapping and dirty data cleaning links are time-consuming and error-prone. Automated tasks must embed pre-checks and cleaning logic to intercept abnormal data in advance. Post-import sampling checks require automated verification rules to ensure data compliance before migration completes. Complete logs must also be retained after task failures to facilitate retrospective analysis.
How to Set Configurations
This configuration is compatible with FastGPT v4.17.0
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Task Trigger Timing | Trigger per migration plan / Event trigger | Adapt to irregular data update patterns, avoid wasting resources from fixed cycles |
| Single Import Data Volume | 5000–10000 records | Balance system load and import efficiency, meet batch data processing needs |
| Dirty Data Processing Threshold | Calibrated via actual testing | Adapt to differences in customer data quality, avoid incorrectly intercepting valid data |
| Task Timeout Duration | 1800 seconds | Cover the time required for batch data cleaning and import, avoid abnormal task interruptions |
| Verification Rule Trigger Node | Pre-import / Post-import sampling | Correspond to field mapping and sampling check links, detect data misalignment issues early |
| Failure Retry Count | 2 times | Respond to temporary network fluctuations or system jitter, reduce manual intervention costs |
Three Common Misconfigurations
- Symptom: Import task status remains unchanged for a long time, but system monitoring shows the process is still running. Cause: No dirty data processing timeout branch configured, a large amount of dirty data cleaning work causes task deadlock.
- Symptom: Unable to customize trigger rules, only fixed cycle execution is supported. Cause: Event trigger configuration item not enabled, no association with field mapping changes or data upload events.
- Symptom: No verification result feedback after scheduled task execution. Cause: No automated log output configured for post-import sampling checks, making fault troubleshooting difficult.
How to Confirm Proper Configuration
- Upload a test CSV template, trigger the scheduled task, and check if the import log includes field mapping verification records.
- Configure an event trigger rule, upload test data that meets format requirements, and confirm the task starts automatically and generates a migration verification report.
- Simulate a dirty data scenario, confirm the task triggers preset processing logic and generates exception logs.
- View the task management interface, and confirm that the timeout duration and retry count configuration values match the preset plan.
The values provided are common starting points and should be evaluated against the samples of the corresponding deployment.
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.