What Data for This Category Looks Like
Aquaculture investment research data sources include online monitoring terminals deployed at ponds, daily breeding ledger reports, industry meteorological and hydrological datasets, and seedling and feed purchase documents. Online monitoring data updates at minute-level intervals. Ledgers and purchase documents update daily. Industry public reports update weekly or monthly. Document types are divided into structured time-series monitoring data, semi-structured breeding ledgers, and unstructured research notes and industry analysis documents. Available fields include pond unique identifier, monitoring time, dissolved oxygen concentration, water temperature, pH value, feed feeding amount, seedling survival count, and regional code. Corresponding units: no identifier, ISO 8601 formatted time, mg/L, ℃, dimensionless, kilogram, head, administrative regional code.
Constraints Imposed on Dialogue Logging and Auditing
Minute-level update frequency of online monitoring data requires dialogue logs to record the data time range associated with each query. This enables traceability of data timeliness and integrity during audits. Structured time-series data with multiple fields requires logs to fully record field filtering conditions and query parameters. This ensures data screening logic can be restored during audits. Mixed structured and unstructured document types require the audit process to distinguish parsing and invocation logs for each document type. It also requires separate recording of structured data import verification results and chunking/vectorization processes for unstructured documents. The presence of pond unique identifiers requires logs to be bound to the corresponding pond code. This enables full-link traceability of investment research for individual ponds. High-frequency log writing must avoid excessive storage resource usage. A reasonable log rolling strategy must be configured.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
LOG_RETENTION_DAYS | 30–90 days | Aquaculture investment research audit cycles typically cover monthly or quarterly review needs. Retaining logs for 30 to 90 days meets conventional audit and troubleshooting requirements |
PARSE_STRUCTURED_DATA_LOG | Enabled | Structured monitoring data and ledgers for aquaculture require separate recording of parsing and verification results. This ensures traceability of field matching rate and format correctness for every imported structured data set |
QUERY_CONTEXT_LOG_LEVEL | Detailed | Investment research queries involve multi-field filtering and pond scope restrictions. Detailed logs record complete query parameters, recalled data source IDs, and time ranges. This facilitates audit traceability |
LOG_STORAGE_MAX_SIZE | 500 GB | Dialogue logs for minute-level monitoring data generate significant volume. A 500 GB storage limit covers 90 days of conventional log storage needs and prevents storage overflow |
SLOW_OPERATION_THRESHOLD | 3000 milliseconds | Time-series data queries for aquaculture typically involve batch data across multiple ponds. A 3000 millisecond threshold identifies abnormally slow query operations. This aids audit localization of performance issues |
AUDIT_TRAIL_BIND_ENTITY_ID | Enabled | Logs must be bound to pond unique identifiers. This enables full-link traceability of investment research for individual ponds and meets specialized audit requirements for aquaculture investment research |
The parameter values provided on this page are common starting points for configuration setup. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis. It is recommended to test against the reader’s own samples before finalizing settings.
Three Common Configuration Errors
- Symptom: Slow operation logs trigger frequently, displaying
slow operation xxxxmserrors, and knowledge base file parsing progress stalls. Cause: TheSLOW_OPERATION_THRESHOLDsetting is not adapted to batch time-series data query scenarios for aquaculture. The default threshold is too low, causing normal multi-pond data queries to be classified as slow operations. - Symptom: Dialogue logs do not show pond identifiers associated with queries. Single-pond investment research processes cannot be traced. Cause: The
AUDIT_TRAIL_BIND_ENTITY_IDconfiguration is not enabled. Logs are not bound to pond unique identifiers. - Symptom: After structured breeding ledger import, parsing and verification logs are missing. Field mismatch issues cannot be troubleshooted. Cause: The
PARSE_STRUCTURED_DATA_LOGconfiguration is not enabled. Parsing and verification processes for structured data are not recorded.
How to Verify Correct Configuration
- View the system log configuration page to confirm that the
LOG_RETENTION_DAYSvalue matches preset audit cycle requirements. - Initiate an investment research query that includes pond filtering conditions. Verify that the log fully records query parameters and pond identifiers.
- Upload a structured breeding ledger file. Check that parsing logs include field matching rate and format verification results.
- Simulate a batch time-series data query. Verify that the slow operation log trigger threshold matches the preset configuration.
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.