What this type of data looks like
Telecommunications service revenue yield data primarily comes from telecommunications operator operation systems and public industry monitoring platforms. Daily data collection is completed at a fixed time each day. Data is stored in structured JSON or CSV format. Each entry includes fields such as service type code, total daily revenue, active user count, unit service price, and month-over-month change indicator. Revenue and price fields use Chinese yuan as the unit. User count uses the unit of users. Updates follow a T+1 batch synchronization schedule. No real-time incremental pushes are available.
What constraints do these characteristics impose on database and operations workflows?
Daily fixed-time batch data synchronization requires database write operations to be concentrated within a fixed window. Configure scheduled tasks to limit concurrent write scale, to avoid peak load exceeding database carrying limits. For structured multi-field storage structures, create regular indexes for frequently queried fields such as daily_revenue and daily_user_count, to shorten query response times. For fields bound to units, add format validation rules during data import, to filter dirty data with mismatched units. For the fixed window collection logic, configure timeout retry and alert mechanisms, to handle failed batch synchronization tasks.
How to configure the settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
DB_SYNC_CRON | 0 30 2 * * ? | Telecommunications service daily reports are typically collected between 1:00 and 2:00 AM. Synchronizing at this time ensures access to the latest complete data |
MAX_BATCH_INSERT_SIZE | 500 records | Typical batch data volume for telecommunications service daily reports falls in the hundreds range. This value balances write efficiency and database load |
DATA_VALIDATION_ENABLED | true | Field format and unit matching must be validated to prevent dirty data from entering the database |
QUERY_TIMEOUT | 30 seconds | Structured queries involve multi-field aggregation. This duration covers conventional query scenarios |
DB_CONNECTION_POOL_SIZE | 10–15 | Concurrent write requests during daily synchronization peak periods typically number around 10. This value avoids connection exhaustion |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by data 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 misconfigurations
- A 504 Gateway Timeout error occurs during database queries. Cause: The
QUERY_TIMEOUTparameter was not adjusted based on the batch data scale of telecommunications service daily reports, causing queries to be interrupted after exceeding the preset duration. - Historical telecommunications service synchronization data is lost after upgrading FastGPT to the latest version. Cause: The
comm_service_revenuetable in thefastgpt_dbdatabase was not backed up in advance, and the data directory mount configuration was not retained during the upgrade process. - The number of database query return results does not match expectations. Cause: The
MAX_BATCH_INSERT_SIZEparameter was not configured, causing partial data to be truncated during batch synchronization, resulting in incomplete imported data.
How to confirm the configuration is correctly applied
- View database synchronization task logs to confirm that synchronization records triggered by
DB_SYNC_CRONappear during the daily specified time window, and no failed batches are present. - Perform a manual data synchronization, check that imported data fields and units match preset rules, and no dirty data exists.
- Test high-frequency query statements, confirm that query response times meet business requirements, and adjust the
QUERY_TIMEOUTparameter to an appropriate range. - View database connection pool monitoring metrics, confirm that connection counts do not exceed the
DB_CONNECTION_POOL_SIZEconfiguration limit.
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.