What the data for this category looks like
Data for real estate registration scenarios comes from the real estate registration information system, cadastral survey database, housing transaction online signing system, tax system, and electronic certificate repository. The update frequency is daily. Commonly processed documents include registration application forms, ownership certificates, surveying and mapping results, tax payment vouchers, real estate ownership certificates, and registration books. Data fields include real estate unit number, right holder name/title, location, right type, area, registration date, and more. Units include square meters, number of parcels, number of documents, and others. The data covers structured forms, unstructured documents, and relational data.
Constraints Imposed on Database and Operations Workflows by These Characteristics
Daily updates of multi-source data require the database to support incremental synchronization and batch writing, to avoid full synchronization consuming excessive business resources. Diverse data structures require the database to support both structured queries and unstructured storage, to adapt to different types of ledger fields and relational data. The accuracy of ownership data is directly tied to administrative responsibilities, so the database layer must include data verification and scheduled backup mechanisms to prevent subsequent disputes caused by writing errors. High-frequency ledger summary queries require read-write separation configuration for the database, to prevent synchronization tasks and business queries from competing for resources and impacting query efficiency.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
MONGODB_URI | Cluster read-only replica address with account password | Used to store unstructured registration documents and relational data; read-only replicas reduce the impact of synchronization tasks on business queries |
PG_URL | Dedicated database connection address for structured data | Used to store structured fields of ledgers, such as real estate unit numbers, right holder information, etc., supporting complex associated queries |
DB_MAX_LINK | 10–15 connections | Adapts to the concurrent requirements of daily incremental updates and daily queries, avoiding service blocking caused by exhausted connection counts |
REDIS_URL | Locally deployed single-instance address, calibrated based on actual testing (usually 1–2 GB memory specification) | Used to cache ledger summary results and workflow session data from high-frequency queries, reducing repeated query pressure on the database |
Three Common Configuration Mistakes
- No output from database connections: The workflow returns empty results after calling the database tool. This occurs when correct access permissions for
MONGODB_URIorPG_URLare not configured, or when the corresponding database resource is not bound in the workflow node. - SQL execution error from variable passing: SQL execution fails, returning a parameter parsing exception. This occurs when passed variables are not safely escaped, or when variable values are not submitted in the parameter binding format required by FastGPT — for example, when placeholders are not used instead of directly spliced variables.
- Workflow cannot call the database tool: The tool node execution times out (usually exceeding 600 seconds) or returns a 500 status code. This occurs when
DB_MAX_LINKis set too low, leading to exhausted concurrent connections, or whenREDIS_URLis not configured, causing cache failure and blocking requests from high-frequency queries.
How to Verify Proper Configuration
- Manually write test SQL in the FastGPT workflow, pass the real estate unit number as a variable, and check if the returned results include the correct right holder information and registration date.
- Log in to the database monitoring panel, check if the current connection count is lower than the
DB_MAX_LINKsetting value, and confirm that the connection pool is not exhausted. - Trigger a daily data synchronization task, check if there are no abnormal errors in the logs, and confirm that the incremental synchronization process is running normally.
- Test the variable binding function, pass the surveying and mapping area as a variable into the SQL query statement, and confirm that the returned results after execution match the actual data.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.