Database and Operations for Tourist Attraction Revenue

What data for this category looks like

Tourist attraction revenue yield data comes from ticket verification systems, on-site catering POS terminals, secondary consumption equipment (cable cars, sightseeing vehicles), and member management systems. The system completes full aggregation of the previous day’s data every early morning, generating one daily report document. Each document includes these fields: unique attraction identifier, statistical date, revenue for each business module, total revenue, average daily passenger flow, and customer unit price. Revenue is measured in yuan. Passenger flow is measured in people. Customer unit price is measured in yuan per person. The data structure covers three core business modules: ticketing, catering, and secondary consumption. It has no complex fields with overly deep nested layers.

Constraints imposed on database and operations

Field mapping complexity increases with multiple data sources. Coordination of field naming rules across ticketing, catering and other systems is required to avoid data confusion. Configuring scheduled tasks is required for the daily batch update schedule. Delayed synchronization from some data sources must be handled to prevent missing data. Cross-business field association verification needs, such as matching revenue and passenger flow, require enabling a data verification mechanism to avoid invalid data being stored. Daily report data must be retained long-term for trend analysis, which sets clear requirements for database archiving strategies. Field integrity for historical version data must be ensured to prevent missing fields during subsequent queries.

How to set configurations

Configuration Item	Recommended Value	Rationale
`DATASOURCE_SYNC_CRON`	`0 1 * * *`	Matches the schedule for synchronizing the previous day’s data at 1 AM daily for tourist attraction revenue yield daily reports
`MONGO_BULK_INSERT_BATCH_SIZE`	`500 records per batch`	Tourist attractions typically have hundreds of data entries per batch, which adapts to bulk write performance
`DATA_VALIDATION_ENABLED`	`Enabled`	Requires verification of cross-business field matching to avoid inconsistencies between ticketing revenue and passenger flow data
`DATA_ARCHIVE_RETENTION_DAYS`	`365 days`	Daily report data must be retained long-term for trend analysis, and meets compliance requirements
`SHARE_LINK_ADD_DB_ID`	`Enabled`	Adapts to the need for passing database identifiers in login-free scenarios
`MAX_CONCURRENT_REQUESTS`	`800`	Matches daily concurrent access scale for tourist attractions, avoids insufficient success rates under high concurrency

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 targeted analysis. It is recommended to test on your own samples before finalizing settings.

Three common configuration errors

Symptom: Data source synchronization fails after deployment. Review logs for 503 Service Unavailable errors. Cause: Deployment uses a NAS with 8 GB memory and Intel 6600T processor. Single-node concurrent processing capacity is insufficient, unable to support daily batch synchronization traffic.
Symptom: Historical version queries return empty fields. Some documents in the MongoAppVersion table lack the tmbId field. Cause: Required field validation rules are not configured, leading to omission of the tmbId field during old version data synchronization, causing abnormal cloud historical version functionality.
Symptom: Login-free shared links cannot associate specified database instances, and cannot retrieve revenue yield data for the corresponding attraction. Cause: The SHARE_LINK_ADD_DB_ID configuration item is not enabled. The link does not carry database identifier parameters, causing the system to fail to match the target data source.

How to confirm configurations are properly set

A manual data source synchronization task is initiated. Synchronization logs are checked for field verification failure prompts to confirm the DATA_VALIDATION_ENABLED configuration is active.
A login-free shared link is generated. Link parameters are checked for inclusion of the database identifier field to confirm the SHARE_LINK_ADD_DB_ID configuration is correct.
Historical documents in the MongoAppVersion table in MongoDB are reviewed. The tmbId field is confirmed to be fully written with no missing entries.
Concurrent requests are simulated. Interface return status codes and success rates are observed. The MAX_CONCURRENT_REQUESTS configuration is adjusted to a value matching the business scale.

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.