What the Data for This Category Looks Like
Historical query record data is sourced from natural language search request logs initiated by end users, covering various query interactions in financial, insurance, and wealth management scenarios. The update cadence is near-real-time, with one new record generated each time a user completes a search operation. The document structure of a single record includes fields such as unique user identifier, search initiation time, search text content, associated session ID, returned result list, and operating terminal type. The unique user identifier uses a string format. The search initiation time follows the ISO 8601 standard format. The search text content is plain natural language text. The returned result list is a set of unique identifiers for associated resources.
What Constraints These Characteristics Impose on Deployment and Upgrade
Since data is sourced from end-user real-time interaction logs, the deployment phase must integrate with the terminal’s log collection interface. It must also configure strict permission verification rules to prevent sensitive user data leaks. The near-real-time update cadence requires the deployment phase to adapt to incremental synchronization mechanisms, avoiding full synchronization that consumes excessive system resources. The multi-field document structure requires configuring data cleaning rules during deployment to filter invalid or expired record fields. The upgrade phase must be compatible with different versions of field structures, and execute field migration scripts between versions to prevent old data from failing to be parsed by the new system. Additionally, data compliance requirements in financial scenarios require configuring automatic cleanup rules for expired records.
How to Configure the Settings
| Configuration Key | Recommended Value | Rationale |
|---|---|---|
QUERY_LOG_BATCH_SIZE | 50-100 entries/batch | Balances the efficiency of batch collection and interface load, and adapts to the near-real-time update cadence |
VECTOR_DB_INCREMENT_SYNC_INTERVAL | 30-60 seconds | Matches the near-real-time update requirements of historical query records, while controlling synchronization resource usage for the vector database |
MAX_HISTORY_QUERY_RECALL | Top 20 entries | Adapts to the context length limit of terminal search, avoiding excessive historical records consuming token quotas |
HISTORY_QUERY_CLEANUP_THRESHOLD | 90 days | Complies with compliance data retention requirements in financial scenarios, automatically cleaning up expired historical records |
PARSE_HISTORY_QUERY_TIMEOUT | 300 seconds | Covers the parsing and synchronization time of a single batch of historical records, preventing task interruptions due to timeout |
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.
Three Common Mistakes
- The symptom is an
Unknown fielderror after upgrade. The cause is failing to execute the field migration script for intermediate versions during cross-version upgrade, resulting in fields from old historical query records failing to be parsed by the new system. - The symptom is that the number of recalled historical query records does not meet expectations during terminal search. The cause is that the
MAX_HISTORY_QUERY_RECALLconfiguration value is set too low, failing to cover the actual context requirements of user sessions. - The symptom is frequent delays in vector database synchronization tasks. The cause is that
QUERY_LOG_BATCH_SIZEis set too large, exceeding the concurrent processing limit of the terminal log collection interface, leading to backlogs in the collection queue.
How to Confirm the Configuration Is Complete
- Check the system’s synchronization logs to confirm that the incremental synchronization task for historical query records runs at the interval specified by
VECTOR_DB_INCREMENT_SYNC_INTERVAL, with no abnormal interruption records. - Initiate a simulated user search request to verify that the number of recalled historical query records matches the
MAX_HISTORY_QUERY_RECALLconfiguration value, and that the record content matches actual search behavior. - Check the operation logs of the data cleaning module to confirm that historical records exceeding the
HISTORY_QUERY_CLEANUP_THRESHOLDhave been automatically cleaned up, with no expired data remaining. - Execute the version upgrade script to verify that there are no field parsing errors. After upgrade, historical query records can be normally called by terminal search, and data integrity is not affected.
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.