What the data for this category looks like
Data sources are aggregated public financial market APIs and publishing industry sales subscription data APIs. The update rhythm is once daily, covering all market and revenue data from the previous calendar day. Each data document uses structured JSON format, and includes fields such as publish_product_id (unique identifier for publications, string type), report_date (data report date, date type), benchmark_return (benchmark yield value, float type), range_return (specified period yield value, float type), content_tag (associated content category tags, string array). All fields use standard yield measurement units.
What constraints these characteristics impose on conversation logs and auditing
The daily update feature requires conversation logs to be partitioned and stored by report_date, to avoid excessive single dataset size and ensure query efficiency. The multi-field design that links publications and content categories requires storing publish_product_id and content_tag in logs, to associate publication distribution records and content compliance during audits. The requirement for multi-data-source aggregation means logs must record the source API identifier for each pulled data entry, to trace abnormal data. The characteristic that data volume grows with the number of publications means log queries must use a composite index of report_date and publish_product_id, to avoid delays caused by full table scans. Compliance audit requirements mean logs must retain complete conversation context and data call chains, and critical information must not be deleted arbitrarily.
How to configure the settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
LOG_PARTITION_BY_DATE | true | Matches the daily update characteristic of daily report data, avoids excessive single dataset size, and ensures query efficiency |
LOG_INDEX_FIELDS | ["report_date", "publish_product_id", "user_id"] | Covers common audit query dimensions by date, publication, and user, improves composite query efficiency |
LOG_RETENTION_DAYS | 365 days | Meets long-term tracing requirements for compliance audits in the publishing industry, matches the archiving requirements for daily report data |
DATA_SOURCE_LOG_ENABLE | true | Matches the multi-data-source aggregation characteristic, facilitates tracing abnormal data pull links and token consumption statistics |
MAX_QUERY_LOG_SIZE | 10000 entries per request | Avoids interface overload caused by returning too much data in a single query, ensures system stability |
DELETE_LOG_PERMISSION | ["admin"] | Complies with audit permission control requirements, restricts log deletion operations to authorized personnel only |
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 case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three common configuration mistakes
- Phenomenon: After executing a user conversation deletion operation, the associated yield daily report logs are deleted synchronously. Cause: Independent storage rules for logs and conversation data are not configured, and logs are incorrectly bound to the lifecycle of conversation sessions.
- Phenomenon: Empty results are returned when querying logs by
publish_product_id. Cause: A composite index forreport_dateandpublish_product_idis not configured, causing full table scans that cannot match target data. - Phenomenon: Model token consumption cannot be counted by application dimension. Cause: The
DATA_SOURCE_LOG_ENABLEconfiguration is not enabled, and token consumption fields and associated application identifiers for model calls are not recorded.
How to confirm the configuration is correct
- Navigate to the log management interface, select a composite query using
report_dateandpublish_product_id, confirm the query response time meets expectations, and adjust the index configuration until latency meets requirements. - Perform a simulated conversation deletion operation, verify that associated logs are not deleted synchronously, and confirm the storage rule configuration is correct.
- Navigate to the token statistics page in application management, confirm that filtering and viewing consumption data by application dimension is possible, and verify that the data source log configuration is enabled.
- Check the log retention duration configuration item, confirm that it meets the retention period required for compliance, and adjust
LOG_RETENTION_DAYSto the target duration.
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.