What this category’s data looks like
Consumer construction materials investment research data primarily comes from industry association monthly reports, weekly factory quotation reports from building material manufacturers, real-time bid winning information from national bidding platforms, and offline retail terminal monitoring data. Each data document includes fields such as category name, specification model, origin, factory price, retail price, period-over-period change, supplier qualification, test report number, and more. Price units cover yuan per square meter, yuan per barrel, per kilogram, and other category-specific units. Update rhythms vary significantly: bid winning information updates in real time, factory quotations are synced weekly, and industry reports are released monthly.
Constraints on database and operations workflows
The varying update frequencies of multi-source data require the database to support flexible synchronization task configuration, with separate write logic for real-time stream data and periodic batch data. Category-specific units and specification formats require the database layer to add field validation and standardization rules to avoid data chaos. The high-frequency write requirement for real-time bid winning information requires configuring sufficient connection pools and write concurrency limits to prevent write blocking. Historical data retrieval requirements require the operations workflow to configure appropriate backup and version retention strategies to support historical data queries for investment research scenarios.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
data_sync_interval | 10 minutes–24 hours | Consumer construction materials data includes sources with different update frequencies: real-time bid winning information, weekly quotations, monthly reports. Adjust synchronization intervals by data type |
field_normalization_enabled | enabled | Consumer construction materials have multiple format expressions for specification models and units. Standardization processing is required to ensure data consistency |
batch_insert_max_size | 500 records per batch | When importing industry reports in batches, avoid excessive single write volume that causes high database load |
unit_verification_enabled | enabled | Multiple unit types exist for price and usage fields of consumer construction materials. Unit matching validation is required |
query_timeout | 30 seconds | Avoid timeouts affecting investment research response efficiency when performing cross-source joint queries |
backup_retention_days | 7–30 days | Retain historical investment research data for retrieval. Adjust the period according to compliance requirements |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by data type, data volume, and business rules. Specific issues require targeted analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Phenomenon: The large model returns structured data but does not reference original database snippets, only displays field values. Cause: The original field content retrieved from the database was not concatenated into the large model prompt context, only structured parameters were passed.
- Phenomenon: Database query results cannot be correctly assigned to array variables, only single record data is returned. Cause: Batch result parsing configuration was not enabled, or the field path for array mapping was not correctly configured.
- Phenomenon: Unable to connect after starting a docker-deployed MongoDB, and a
mongosystemmodel not founderror appears during invocation. Cause: The container environment variablesMONGO_INITDB_ROOT_USERNAMEandMONGO_INITDB_ROOT_PASSWORDwere not correctly set, and the connection string with authentication information was not filled in the knowledge base configuration.
How to Confirm Configuration is Correct
- Execute the database query statement
db.consumption_building_materials.find({"品类名称": "陶瓷砖"}, {"规格型号": 1, "出厂价": 1, "单位": 1}), confirm that the returned results include expected fields and correct formatting. - Trigger a batch data import task, check the database monitoring panel, confirm that the number of inserts per batch matches the
batch_insert_max_sizeconfiguration, and there are no timeout or write failure logs. - Call a Function CALL query for building material quotation data, check whether the large model returned content includes original database snippets, such as "The factory price of this batch of ceramic tiles is 35 yuan per square meter".
- Check the MongoDB container logs, confirm there are no
connection refusedor authentication failure errors, and the connection string configuration is correct.
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.