What the Data for This Category Looks Like
Rural commercial bank yield data mainly comes from the local bank’s retail credit product ledgers, interbank certificate of deposit issuance ledgers, and daily public quotes of wealth management products distributed within its jurisdiction. The update schedule is batch synchronization and generation after daily business closes. The data uses a structured relational table structure, including core fields such as institution code, product category, product ID, yield benchmark value, and statistical date. There are no nested levels, and each entry corresponds to the daily yield benchmark data of a single product. All fields use annualized yield benchmark units, and no unstructured attachment content is included.
Constraints on Database and Operations Imposed by These Data Characteristics
Multi-source data access requires configuring cross-data source connection and mapping rules, and verifying field consistency across different systems to avoid data misalignment. The daily batch update schedule requires reserving non-core business windows in operations to run synchronization tasks, preventing interference with core transactions during business hours. The institution code field design requires configuring row-level data permissions, ensuring that operations personnel from different branches can only access data within their respective jurisdictions. Data timeliness requirements mandate configuring timeout retry mechanisms to handle temporary delays from upstream systems, ensuring timely delivery of daily report broadcasts. The fine-grained product classification requires configuring targeted database indexes to support high-frequency query needs by category and date.
Configuration Recommendations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
DB_SYNC_CRON | 0 30 22 * * ? | Adapts to the daily business closing window before 22:00 for rural commercial banks, avoiding synchronization interference with core business |
DB_CONNECTION_TIMEOUT | 60 seconds | Covers average response delays across core systems and interbank platforms, preventing connection interruptions |
KNOWLEDGE_BASE_SYNC_RETRY_TIMES | 3 times | Addresses temporary upstream system fluctuations, reducing the probability of batch synchronization failure |
WHITELIST_ALLOWED_IPS | Local core business IP ranges, distributed partner platform IP ranges | Restricts database access to only trusted sources, ensuring data security |
DB_JOIN_INDEX_CONFIG | Create a joint index using statistical date and institution code | Matches high-frequency query scenarios for daily report broadcasting filtered by date and institution, improving query performance |
The parameter values provided on this page are conventional recommendations used as starting points for configuration. Actual values are affected by data format, data volume and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Phenomenon: A
10060error code appears after configuring the database connection, and a connection cannot be established. Cause: The IP of the FastGPT deployment server is not added to the database whitelist, violating database access permission restrictions. - Phenomenon: Some fields are empty during batch data synchronization, and yield data in the knowledge base lacks specified categories. Cause: Cross-data source field mapping rules are not configured, leaving unaligned field name differences across different systems unaddressed.
- Phenomenon: A timeout alarm is triggered after a scheduled synchronization task runs, and the task status shows failure. Cause: The synchronization task execution window does not reserve sufficient buffer time, and the connection timeout parameter value is not adjusted, resulting in upstream system response timeout without completed retries.
How to Verify Proper Configuration
- Execute the database connection test script to verify that the configured IP, port, account and password can establish a normal connection, and confirm that the returned field list matches the preset rural commercial bank yield data fields.
- Manually trigger a scheduled synchronization task, check that the number of synchronized entries in the task log matches the actual number of data entries from the upstream system, and confirm no field missing or misalignment.
- Log in to the database management tool, check whether the preset joint index has been created, and verify that the index field combination matches the configuration item.
- Check the FastGPT knowledge base synchronization records, confirm that the daily synchronization task execution status is successful, with no error messages.
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.