What Data for This Category Looks Like
Residential development yield-related data comes from three main sources: internal enterprise resource planning (ERP) cost systems, real estate registration online signing interfaces, and project engineering management platforms. Data updates follow a fixed monthly natural calendar schedule. Each data document corresponds to one residential development project, and includes fields such as project approval number, planned floor area, cost breakdown by phase, current period sales and payment collection data, and financing details. Some fields use standard industry units: total land transfer fee and cumulative project progress payment use yuan, while planned floor area uses square meters.
Constraints on Database and Operations Work
Multi-source data access requires the database to support cross-system field mapping and incremental synchronization, to avoid repeated full data imports. Fixed monthly update schedules require operation scripts to be configured with scheduled trigger tasks, to ensure consistent and timely data updates. Single-project data includes multi-dimensional breakdown fields, requiring reasonable splitting of database table structures to avoid reduced query efficiency from too many fields in a single table. Data involves sensitive internal business information of real estate enterprises, requiring strict database permission control rules to restrict unauthorized access.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
DB_SYNC_INTERVAL | 2592000 seconds | Matches the monthly update schedule of residential development yield data, avoids frequent synchronization consuming system resources |
PARSE_DATA_BATCH_SIZE | 100 entries | Single-project data has many details; too large a batch will cause memory overflow, too small a batch will prolong synchronization time |
DB_INDEX_FIELDS | ["project_id", "update_time", "sales_amount"] | Daily queries are often filtered by project ID, update time, or aggregated by sales amount; creating corresponding indexes improves query efficiency |
DATA_CLEAN_RULES | {"field_mapping": {"land_cost": "total land transfer fee"}, "null_value_handle": "default_zero"} | Field names differ across multi-source systems, requiring unified mapping; null values need to be filled with zero to avoid calculation errors later |
DB_BACKUP_CRON | 0 0 2 1 * * | Triggers backup at 2 AM on the 1st of each month, retains a full data copy after monthly data updates are completed |
CONNECTION_TIMEOUT | 30 seconds | Internal system interface responses have certain delays; too short a timeout will cause data synchronization tasks to fail |
The parameter values provided on this page are common starting points for configuration setup. Actual values are affected by data format, data volume, and business rules. Specific issues require targeted analysis, and testing on local deployment samples is recommended before finalizing settings.
Three Common Configuration Errors
- A
500 Internal Server Errorappears when installing the database connection plugin. The database connection environment variableMONGO_URIis not configured, so the plugin cannot establish a valid connection during initialization. - After monthly data synchronization finishes, financing detail fields for some residential development projects are empty. The field mapping rule in
DATA_CLEAN_RULESis not configured, and differences in field names across internal systems prevent correct data writing to the target table. - A known security vulnerability alert triggers during database scanning. The current MongoDB version
5.0.18has a high-risk vulnerability, and the deployment is not upgraded to the official fixed release version.
How to Verify Successful Configuration
- Run a manual data synchronization task, and check the synchronization logs for errors such as field mapping failures or connection timeouts. After confirming no abnormalities, verify that newly added project data in the target database is complete.
- Log in to the database management interface, and check that indexes for the
project_idandupdate_timefields have been created, with normal enabled status. - Trigger the database backup task, and confirm that the backup file generation path and file size meet expectations, with no interruptions to the backup process.
- Access the FastGPT database connection plugin management page, and confirm the plugin status is connected, with no abnormal alert prompts.
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.