What this category’s data looks like
Aviation airport investment research data comes primarily from publicly released statistical documents of civil aviation regulatory authorities, annual and quarterly financial reports of airlines, airport operation logs, and airspace planning policy documents. Update cycles include minute-level (real-time flight takeoff and landing data), monthly (passenger throughput statistics), quarterly (flight schedule adjustments), and annual (infrastructure planning reports). Document types cover structured tables (takeoff and landing counts, passenger throughput), semi-structured PDF annual reports, and long-text policy documents. Core fields include ICAO airport code, three-letter airport code, passenger throughput (unit: person-times), and flight slots (unit: sorties per hour). Some documents include exclusive fields such as airspace capacity and infrastructure investment.
What constraints these characteristics impose on database and operations workflows
Real-time flight data requires high-frequency writes, so databases must support low-latency concurrent write operations without blocking regular query tasks. Mixed synchronization of data sources with varying update cycles requires a layered synchronization mechanism. This mechanism differentiates synchronization frequencies for real-time and offline statistical data, preventing full synchronization from consuming excessive storage and computing resources. Parsing long-text annual reports and policy documents requires databases to support long-text sharded storage while retaining contextual association information for documents. This avoids losing paragraph logic during retrieval. High-frequency queries for exclusive fields require targeted indexes. These indexes improve query efficiency for specific fields and prevent performance loss from full table scans.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 1000 MB | Aviation airport investment research documents include complete airline annual reports and airspace planning PDFs. Single-file size usually exceeds the limit for general documents, and 1000 MB covers most scenarios |
PARSE_FILE_TIMEOUT_SECONDS | 1200 seconds | Parsing long-text annual reports requires traversing multiple pages. 1200 seconds prevents parsing tasks from being interrupted by timeouts |
RECALL_TOP_N | Top 15 entries | Aviation airport investment research covers multi-dimensional data including airspace, passenger flow, and infrastructure. 15 entries balances information coverage and context window pressure |
SIMILARITY_THRESHOLD | 0.72–0.78 | Aviation airport data fields have strong specificity. A threshold that is too low introduces irrelevant airspace and passenger flow data, while a threshold that is too high misses relevant segmented scenarios |
DB_WRITE_POOL_SIZE | 8–12 | Real-time flight takeoff and landing data has high-frequency write requirements. Adjusting the connection pool size adapts to concurrent write needs and prevents connection exhaustion |
DB_INDEX_FIELDS | icao_code, passenger_volume, flight_slot | Core query fields for aviation airport investment research are airport codes, passenger throughput, and flight slots. Creating dedicated indexes improves query efficiency |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require targeted analysis. It is recommended to test on your own samples before finalizing settings.
Three common errors
- Issue: After upgrading to v4.10.1, knowledge base content fails to sync and display. Cause: The database migration script for the corresponding version was not executed. Metadata fields differ between old and new versions, and table structure updates were not completed.
- Issue: When creating a "Question Classification" node, clicking run or save and publish triggers an error. Switching to another AI model restores normal functionality. Cause: The context window configuration of the default AI model does not adapt to aviation airport long-text investment research documents. Parsed sharded data exceeds the model's limit, causing verification failure.
- Issue: Database write latency is too high, and real-time flight data updates lag. Cause: Read-write separation is not configured. The primary database bears both query and write pressure, and concurrent write requests block normal query processes.
How to confirm configurations are properly set
- Upload a single airline annual report PDF under 1000 MB, verify that the parsing task completes within 1200 seconds with no error prompts.
- Submit a query containing the
icao_codefield, verify that the matching degree of returned results falls within the preset similarity threshold range. - Check database connection pool monitoring, confirm that the connection occupancy rate of real-time write requests does not exceed the configured
DB_WRITE_POOL_SIZElimit. - Execute the database migration script for the corresponding version, restart the service, and verify that knowledge base content matches source data.
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.