What the data for this category looks like
Data sources include store POS terminals, hotel property management system (PMS) platforms, third-party food delivery platform merchant backends, and central kitchen inventory management systems. Full daily data aggregation must be completed within 1 hour after daily business concludes. Chain stores can configure hourly real-time revenue snapshot collection for ad-hoc reviews. Documents use structured CSV or Excel format. Each row represents a single store’s single-day statistics. Fields include: store code, statistical date, dine-in revenue, takeout revenue, private room revenue, average customer unit price, table turnover count, food ingredient cost, labor cost, energy consumption cost, total revenue, total cost. Units: Revenue and cost fields use Chinese Yuan (CNY). Average customer unit price uses CNY per person. Table turnover count uses times per day.
Constraints on deployment and upgrade from these characteristics
The multi-source heterogeneous data sources require that the deployment phase adapts to authentication and interface formats of different systems such as POS, PMS, and third-party food delivery platforms, which increases the complexity of docking configuration. The fixed daily aggregation + real-time snapshot update rhythm requires that both scheduled synchronization and real-time stream collection tasks are configured during deployment. The upgrade phase must support seamless switching between the two synchronization modes. The diverse fields in structured documents require that flexible field mapping rules are configured during deployment. The upgrade phase must retain legacy field compatibility logic to prevent exceptions during historical data import. The cross-system reconciliation requirement for multiple stores requires enabling basic data verification during deployment to prevent missing fields or abnormal numerical values.
How to configure the settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 500 MB | Batch daily report files for this category are mostly structured tables, and the total size of chain store data imported in a single batch usually does not exceed this threshold |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Structured table parsing requires multi-field matching and format verification. This duration covers parsing requirements for most conventional data volumes |
BATCH_IMPORT_MAX_ROWS | 15,000 rows | A single batch can cover single-day data for dozens of chain stores, preventing service timeouts caused by too many rows imported in a single operation |
SYNC_CRON_EXPRESSION | 0 0 1 * * ? | Adapts to the category’s daily summary data update rhythm of 1 hour after business closes, ensuring that same-day data synchronization is completed by the next early morning |
API_AUTH_MULTI_MODE | Enabled | This category requires docking with systems that support multiple authentication methods such as POS, PMS, and third-party food delivery platforms, so different authentication logic must be supported |
DATA_VALIDATION_LEVEL | Strict verification | Data for this category involves revenue and cost accounting. Field integrity and numerical rationality must be verified to prevent erroneous data from entering the knowledge base |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- The symptom is a
405 Method Not Allowedresponse when accessing the data synchronization interface. The cause is failure to configure the interface request method to POST or GET as required by the target POS or food delivery platform. Some third-party systems only support specified request methods. - The symptom is frequent failures of data synchronization tasks, with logs showing authentication failures. The cause is failure to configure corresponding authentication parameters for different data sources, such as incorrect filling of the food delivery platform’s API key and signature verification rules.
- The symptom is failure to load team management functions after local deployment. The cause is failure to enable the corresponding switch in the deployment configuration file, or incorrect configuration of environment variables and port mapping.
How to confirm proper configuration
- A single store’s single-day daily report file is uploaded. The parsed field list is verified against the preset mapping rules. Field mapping is adjusted until no missing or incorrectly matched fields remain.
- A scheduled synchronization task is manually triggered. The latest data synchronization time of the system is verified against the business’s daily summary time. The synchronization cycle configuration is adjusted until it meets requirements.
- The configured third-party data source interface is called. The authentication parameters are verified to take effect. The interface is confirmed to return normal data with no authentication failure prompts.
- The deployment configuration file is checked. All enabled function switches are confirmed to be correctly configured, with no syntax errors or missing environment variables.
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.