Database and Operations for Education Service Yield Reporting

Public compliant financial market APIs and the platform's internal course revenue accounting system provide daily yield and market report data for

What the Data for This Category Looks Like

Public compliant financial market APIs and the platform's internal course revenue accounting system provide daily yield and market report data for education service scenarios. Data updates follow fixed daily refresh times during trading days. Only low-frequency static revenue data updates on non-trading days. Temporary market fluctuations trigger incremental data pushes. Each data entry includes fields such as course identification string, student group enumeration value, benchmark revenue value, actual revenue value, market target code, and update timestamp. Numeric fields have no fixed decimal place requirements, and timestamps use the ISO 8601 format.

Constraints on Database and Operations Workflows

Fixed daily batch updates create concentrated write pressure, requiring database parameters optimized for batch operations. Incremental update scenarios require support for upsert operations to prevent duplicate entry of daily report data for the same date. High-frequency query scenarios mostly revolve around date, market target code, and course identification. Creating indexes for these fields speeds up retrieval. Data sources include external APIs, so deployments reserve sufficient database connection pool resources to handle concurrent peak loads. Additionally, education service scenarios must meet data compliance requirements: enable database audit logs to retain operation trails, and align the data retention period with industry regulatory standards.

Configuration Settings

Configuration ItemRecommended ValueRationale
db_batch_insert_size60–90 records/batchMatches daily batch update data volume, balances write efficiency and single request load
db_upsert_enabledEnabledSupports duplicate data deduplication in incremental update scenarios, avoids duplicate daily report data entry, and is compatible with upsert syntax for domestic databases
db_index_fieldsupdate_time, target_code, course_idCovers high-frequency query needs by date, market target, and course, speeds up retrieval
db_connection_pool_max25–35 connectionsAdapts to concurrent peaks of external financial data sources and LLM API calls, prevents database connection exhaustion and restricted API call frequency
db_read_timeout15 secondsMatches response time of external market APIs, prevents read request timeouts that cause reporting failures
db_audit_log_enabledEnabledMeets data compliance audit requirements for education services, retains all data operation trails
db_typeDomestic compatible version (e.g., Dameng, KingbaseES)Adapts to scenarios where open-source or foreign database components cannot be used, meets compliance requirements

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, and it is recommended to test using samples from the target deployment environment before finalizing settings.

Three Common Misconfigurations

  • Symptom: ETIMEDOUT error occurs after batch update tasks are triggered. Cause: No reasonable db_batch_insert_size is set, and the single write data volume exceeds the database load limit, causing connection timeout.
  • Symptom: Response delays occur in consecutive daily report query requests. Cause: No database indexes are created for the update_time and target_code fields, leading to full table scans that occupy excessive system resources.
  • Symptom: Knowledge base-associated question answering cannot retain context, with the second question answering off-topic. Cause: Session context persistence storage configuration is not enabled, causing context state to reset with each request and preventing association of historical conversation information.

How to Verify Proper Configuration

  • Execute a batch write test script, observe the database write log, and confirm that the write batch size matches the configured db_batch_insert_size value.
  • Initiate a query request by date and market target code, verify the completeness and accuracy of the returned result fields, and confirm that the index configuration is active.
  • Check the database audit log, confirm that all data operations are correctly recorded, and verify that the db_audit_log_enabled configuration is enabled.
  • Initiate consecutive query requests, observe the response duration, and confirm that the connection pool configuration adapts to concurrent peak requirements.

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.