What the data for this category looks like
Telecommunications service revenue yield and daily market trend data is sourced from public operational monitoring APIs of the telecommunications industry and internal business report APIs of carriers. The update rhythm follows a daily T+1 schedule, meaning full data for the previous day is collected and synchronized by T+1.
Each individual data document uses a structured format, including the following fields: service_category (telecommunications service category identifier, such as cloud dedicated line, IoT access, call center service), report_date (data date, format YYYY-MM-DD), operating_revenue (unit: ten thousand yuan), cost_expense (unit: ten thousand yuan), service_scale (number of service coverage nodes).
The data has no extra nested levels. All fields are basic string or numeric types, with no complex enumeration extensions.
How these characteristics impose constraints on deployment and upgrade
The daily T+1 update rhythm requires that scheduled tasks matching the data source synchronization window be configured during deployment. Avoid executing synchronization operations during peak data source hours to prevent request rate limiting.
The structured, non-complex nested field characteristics simplify the data parsing process, but require strict alignment of field names and types between the data source and local database during deployment to avoid parsing failures.
The diversity of telecommunications service categories requires that knowledge base category mapping rules be updated synchronously during upgrades to ensure new service types can be properly identified and broadcast.
Data scale grows gradually as service nodes expand. Reasonable database storage space must be reserved during deployment, and historical data format conversion logic must be supported during upgrades.
How to set configurations
| Configuration Item | Suggested Value | Rationale |
|---|---|---|
SYNC_DATA_CRON | 0 30 1 * * * | Matches the completion window of T+1 updates for most telecommunications data sources, ensuring complete previous-day data is retrieved |
PARSE_DATA_TIMEOUT_SECONDS | 600 seconds | Adapts to the parsing time of a single batch of telecommunications service data, preventing parsing interruptions caused by large data volumes |
RECALL_SIMILARITY_THRESHOLD | 0.70–0.80 | Balances recall accuracy and coverage across multiple telecommunications service categories, reducing false recalls |
UPLOAD_BATCH_SIZE | 50 records/batch | Controls the request load for single data uploads to avoid triggering interface rate limiting rules |
SYNC_MAX_RETRY_TIMES | 3 retries | Addresses temporary fluctuations in data source APIs, reducing the risk of broadcast interruptions caused by a single synchronization failure |
TEMPLATE_UPDATE_STRATEGY | Automatically sync latest version | Ensures broadcast templates always adapt to new telecommunications service categories and field rules |
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, and it is recommended to test against your own samples before finalizing settings.
Three common mistakes
- Symptom: After Docker deployment, there is no corresponding channel entry in the data synchronization service configuration interface. Cause: The configuration volume was not correctly mounted during Docker build, so the channel configuration file was not loaded into the runtime environment.
- Symptom: After upgrading to version 4.8.10, workflow debugging throws
ETIMEDOUTerror. Cause: The new version adjusted the default value of the data source request timeout parameter, which does not adapt to the parsing time of original telecommunications data. - Symptom: When deploying locally on Windows 10, the self-hosted MongoDB instance cannot be connected. Cause: The configured
MONGODB_URIwas not correctly bound to the local host address and port, causing connection requests to be blocked.
How to confirm the configuration is complete
- View the execution logs of the scheduled synchronization task to confirm that the last synchronization task completed at the daily specified time with no error records.
- Manually trigger a data parse to check that the parsed fields are fully aligned with the data source fields, with no missing or misaligned entries.
- Trigger a market trend broadcast to check that the output content includes all configured telecommunications service categories, with no abnormal missing fields.
- Access the front-end configuration interface to confirm that the channel configuration entry loads normally, and that synchronization rules can be saved and updated normally.
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.