What this type of data looks like
Data sources for industrial park investment research knowledge bases include park operation ledgers, settled enterprise industrial and commercial information, industrial support policy documents, park investment promotion brochures, rent collection records, and energy consumption monitoring data. Update rhythms fall into three categories: operation ledgers and energy data are updated daily, investment promotion brochures and rent details are updated quarterly, and industrial policy documents are released irregularly. Document structures include structured tables (such as settled enterprise lists, rent unit price details), semi-structured policy documents, and long-text industrial planning reports. Fields include park ID, settled enterprise unified social credit code, rent unit price (yuan/square meter/month), energy consumption value (kilowatt-hour), and others. Some fields involve enterprise sensitive information and financial data.
Constraints on conversation logging and auditing
Industrial park investment research data has multiple structures, varied update frequencies, and sensitive attributes, which impose multiple constraints on conversation logging and auditing. First, structured data contains a large number of detailed fields. Logs must accurately record the specific field range associated with each query, and audits must trace back to the corresponding data entry. Second, different types of data have large differences in update frequencies. Logs must mark the data version timestamp used at the time of query to ensure the accuracy of audit tracing. Third, conversation contexts for long-text policies and planning reports are lengthy, so truncation positions must be fully recorded to avoid missing key information during audits. Fourth, access to sensitive fields must separately record permission verification results to meet park data compliance audit requirements.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
LOG_STORAGE_RETENTION_DAYS | 180 days | Industrial park investment research data must be retained for at least six months for compliance audits, matching park operation compliance requirements |
AUDIT_SENSITIVE_FIELD_FILTER | Enabled, filter unified social credit code, rent unit price | Industrial park data contains a large amount of enterprise sensitive information and financial data, so plaintext storage of sensitive fields in logs must be prevented |
MAX_LOG_QUERY_CONTEXT_LEN | 8000 characters | Industrial park investment research documents include long-text policies and planning reports, so sufficient context must be retained for audit tracing |
SLOW_OPERATION_THRESHOLD | 1200 milliseconds | Park data queries involve multi-dimensional associated calculations, so the threshold must be relaxed to avoid false positive slow operation logs |
API_LOG_INCLUDE_PARAMS | Only include park ID, query keywords | Reduce log redundancy and focus on core query dimensions for investment research scenarios |
LOG_ENCRYPTION_ENABLE | Enabled | Comply with data security compliance requirements and prevent leakage of sensitive investment research data |
The parameter values provided on this page are common recommended starting points for determining configurations. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing.
Three common mistakes
- Phenomenon: Slow operation alerts are continuously reported in logs, but the actual query does not time out. Cause: The
SLOW_OPERATION_THRESHOLDconfiguration is not adjusted for industrial park multi-dimensional data associated queries, and the default threshold is too low, triggering false positives. - Phenomenon: Sensitive fields such as
unified social credit codeappear in plaintext in logs. Cause: TheAUDIT_SENSITIVE_FIELD_FILTERconfiguration is not enabled, and sensitive field filtering rules are not configured. - Phenomenon: Audit logs are missing context content for some long-text conversations. Cause: The
MAX_LOG_QUERY_CONTEXT_LENparameter is not adjusted, and the default length is insufficient to store the complete context after long document parsing.
How to confirm the configuration is properly set
- Log in to the log management interface, check whether log entries stored for more than 30 days exist, to verify that the
LOG_STORAGE_RETENTION_DAYSconfiguration takes effect. - Trigger a query containing sensitive fields, check whether the corresponding fields in the log are replaced with desensitization markers, to verify that the sensitive field filtering configuration takes effect.
- Submit a query containing long-text policies, check whether the query context is fully recorded in the log, to verify that the context length configuration takes effect.
- Simulate a park data query that takes more than 1000 milliseconds, confirm whether a slow operation alert is triggered, to verify that the slow operation threshold configuration takes effect.
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.