What data for this category looks like
Data for this category comes from submitted reports of the national building materials industry monitoring platform and regional spot trading centers. There are two update frequencies: regional spot-related data is updated daily, and national average yield dimension data is updated weekly. Each data entry includes fields such as cement grade, producing province, statistical cycle, baseline transaction price, cycle yield difference, and regional circulation volume. The unit of baseline transaction price is yuan/ton, the unit of cycle yield difference is yuan/ton, and the unit of circulation volume is 10,000 tons. Data is split by region and grade, with a clear single-document structure and no nested field levels.
What constraints these characteristics impose on database and operations work
Dual update frequencies require database sync tasks to distinguish daily and weekly trigger rules to avoid task conflicts or missed updates. The data structure split by region and grade requires creating a joint index covering the grade, producing area, and statistical cycle fields to support fast multi-dimensional queries. Multi-source data access requires configuring data deduplication logic to avoid duplicate entry of the same monitoring data. Temporary abnormal fluctuations exist in building material price data, so field validation rules must be configured to filter invalid data and ensure data consistency within the database. The daily update data volume has periodic fluctuations, so adjust the maximum number of database connection pools to adapt to peak traffic.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGO_CONNECTION_TIMEOUT | 30 seconds | Adapts to the synchronization verification time consumption of multi-source cement data, avoids short timeouts causing valid data synchronization failures |
DUPLICATE_CHECK_ENABLED | Enabled | Addresses deduplication requirements for dual data source access, avoids duplicate entry of monitoring data with the same grade, same producing area, and same cycle |
MAX_CONNECTIONS_PER_POOL | 50–80 | Adapts to peak traffic during daily data updates, avoids task interruptions caused by exhausted connection pools |
DB_PARTITION_POLICY | Partition by statistical cycle on a monthly basis | Matches the storage requirements of weekly/daily updated data split by cycle, accelerates historical data queries |
DATA_SYNC_TRIGGER_RULE | Trigger by data source type | Distinguishes synchronization tasks for daily spot data and weekly average data, avoids task execution conflicts |
DB_FIELD_VALIDATION_RULE | Calibrated based on actual measurements | Filters invalid data with abnormal baseline price fluctuations, ensures data consistency within the database |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Symptom: After deployment, connecting to the local MongoDB database via MongoDB Compass fails, with a prompt of connection timeout or authentication failure. Cause: The
MONGO_INITDB_ROOT_PASSWORDandMONGO_URIparameters are not configured correctly, or the firewall blocks traffic on the default MongoDB port 27017. - Symptom: A large number of duplicate cement yield data appears after the data synchronization task is executed. Cause: The
DUPLICATE_CHECK_ENABLEDparameter is not enabled, and deduplication verification is not performed for data with the same grade, same producing area, and same cycle. - Symptom: The daily data synchronization task times out and fails, with the
ETIMEDOUTerror code returned in the logs. Cause: TheMONGO_CONNECTION_TIMEOUTparameter is set too short, unable to complete the multi-source data verification and import process.
How to confirm proper configuration
- Execute the database connection test script to verify the correctness of the
MONGO_URIparameter and confirm that a normal connection can be established. - Submit a test cement data entry, check the synchronization task logs, and confirm that synchronization is triggered according to the rules of
DATA_SYNC_TRIGGER_RULE. - Query the test data in the database, confirm that the joint index and partitioning policy take effect, and that query latency meets the preset threshold.
- Submit simulated invalid data, confirm that
DB_FIELD_VALIDATION_RULEcan filter non-compliant invalid 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.