What This Type of Data Looks Like
Data for construction engineering investment research comes from sources including project construction drawing PDFs, cost list Excel files, construction log documents, material quality inspection reports, section settlement files, and more. Updates trigger alongside project phases: key milestones such as foundation, main structure, and decoration will sync documents for the corresponding phase, while material price data updates monthly. Each individual document includes fields like project number, section name, construction location, material model, test values, and cost breakdowns. Units include square meters, cubic meters, tons, yuan per square meter, millimeters, and others. Some semi-structured documents have nested fields and inconsistent units.
What Constraints Do These Characteristics Impose on Database and Operations Workflows
The multi-source, heterogeneous nature of construction engineering data requires the database to support multi-format parsing and flexible schema mapping, to prevent format mismatches during structured data imports. The non-fixed update cycle requires configuring incremental synchronization mechanisms to balance real-time performance and server resource usage. Document sizes vary significantly; individual construction drawings can reach hundreds of MB, so the system must support large file upload and parsing. Inconsistent fields and units require adding standardized validation and mapping rules during database operations to ensure consistent search results. Additionally, scenarios where multiple engineers launch investment research queries simultaneously place higher demands on the database's concurrent processing capabilities.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_MAX_SIZE | 1000 MB | Individual construction drawing PDFs for construction engineering can reach hundreds of MB, so parsing restrictions need to be relaxed for oversized files |
UPLOAD_CHUNK_SIZE | 8 MB | Most construction engineering documents are large files; chunked uploads can avoid single upload timeouts |
DB_CONNECTION_TIMEOUT | 300 seconds | When pulling cost databases across servers, complex queries take longer, so the timeout threshold needs to be extended |
RECALL_TOP_K | 10–15 entries | Construction engineering investment research needs to balance comprehensiveness and search efficiency; too many results will increase subsequent processing burden |
SQL_SERVER_ENABLED | Enabled | Most industry legacy data is stored in SQL Server databases, so compatibility is required |
INCREMENTAL_SYNC_INTERVAL | 1 hour | Construction engineering project data updates have no fixed cycle; incremental synchronization balances real-time performance and resource usage |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material formats, data volume and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing.
Three Common Misconfigurations
- Symptom: API calls return a
503 Service Unavailablestatus code, and logs show the database connection pool is exhausted. Cause: The connection pool upper limit was not configured for the concurrent query scenario of construction engineering projects, leading to a large number of requests seizing database resources. - Symptom: The data source table corresponding to the search result cannot be located, and the query returns an error "associated table metadata not found". Cause: Table-level metadata mapping was not configured for structured documents of construction engineering projects, making it impossible to associate with the original database table.
- Symptom: Table data in a specified SQL Server database cannot be called via a plugin. Cause: The
SQL_SERVER_ENABLEDconfiguration item was not enabled, or the instance name and access permissions in the database connection string were not correctly configured.
How to Verify Proper Configuration
- Upload a single construction drawing PDF larger than 500 MB, verify that the parsing task does not trigger a timeout error, and confirm that the
PARSE_FILE_MAX_SIZEconfiguration meets business requirements. - Initiate more than 10 concurrent API search requests, observe the database connection pool status, and confirm that the connection pool upper limit configuration can support business peak loads.
- Configure a SQL Server database connection plugin, attempt to query legacy cost list tables, verify that structured data can be returned normally, and confirm that the connection parameters are correct.
- Import a material data document with inconsistent units, verify that the system automatically completes unit standardization conversion, and confirm that the field mapping rules are effective.
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.