What the data for this category looks like
Core data for tourist attraction revenue yield comes from in-house ticketing systems, entry turnstiles, merchant POS terminals, and cultural tourism regulatory platform APIs. Data updates occur once daily, with full batch aggregation of the previous day’s data completed during the early morning of the next day. Each data entry uses the scenic spot as the sole statistical unit, and includes fields such as scenic spot ID, statistical date, total daily ticket sales revenue, total entry visits, average revenue per visitor, daily operating costs, daily net profit, and more. Field units are uniformly Renminbi yuan or visits, with no nested sub-document structures.
What constraints do these characteristics impose on deployment and upgrade?
The fixed daily batch processing requirement means timed tasks aligned with the scenic spot’s data synchronization rhythm must be configured during deployment, to avoid conflicts with core business batch processing. Multi-source data access requires pre-completion of API authentication and field mapping configurations. Differences in data source formats across scenic spots will increase deployment adaptation costs. Data volume grows with the scenic spot’s operational scale, so storage and computing resource expansion space must be reserved during upgrades. The atomicity of batch processing tasks requires upgrades to be completed during non-core business hours, and database and configuration file backups must be performed in advance to prevent data loss from interrupted upgrades. Additionally, daily report data verification logic must be configured during the deployment phase to avoid abnormal data flowing into the final report.
How to set the configurations
| Configuration Item | Recommended Value | Rationale for This Value |
|---|---|---|
CRON_JOB_MAX_RUN_TIME | 3600 seconds | Matches the typical duration of scenic spot daily report batch processing, to avoid forced task termination mid-execution |
RECALL_COUNT | top 10 entries | Scenic spot revenue yield data entries are relatively few; recalling too many will increase computing overhead |
SIMILARITY_THRESHOLD | 0.75–0.85 | Filters low-match scenic spot data association requests, to improve report accuracy |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Accommodates single scenic spot full-year historical revenue yield data import files |
LOG_RETENTION_DAYS | 90 days | Meets compliance retention requirements for scenic spot operational data, while controlling storage usage |
DOCKER_RESTART_POLICY | unless-stopped | Ensures the scheduled task service restarts automatically after abnormal exit |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing.
Three common mistakes
- Symptom: A
500 Internal Server Erroroccurs after running the upgrade command, and version switching cannot be completed. Cause: Thedocker-compose.ymland.envconfiguration files were not backed up in advance, and the original data source mapping configuration was overwritten during the upgrade process. - Symptom: The scheduled batch processing task returns empty results after execution, with a
field not founderror displayed in the logs. Cause: Mapping configurations were not completed for differences in data source fields across scenic spots, and the default template was used directly to import data. - Symptom: Calling the speech recognition interface returns a
404 Not Founderror, or recognition results cannot be obtained. Cause: The Whisper plugin was not enabled in the FastGPT model configuration, or the interface access address was not configured correctly.
How to confirm that configurations are properly set
- Run a manually triggered daily report batch processing task, check that there are no abnormal errors in the task logs, and that the generated report includes the expected scenic spot data fields.
- Restart the service after adjusting configuration items, use the
docker pscommand to confirm that all containers are running normally, and that the restart policy matches the preset requirements. - Send a query request containing tourist attraction revenue yield keywords to the system, check that the number of returned results matches the
RECALL_COUNTconfiguration parameter. - Check the disk usage of the log directory, confirm that storage resources are not exhausted due to the log retention configuration.
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.