What the data for this category looks like
Data related to specialized equipment yield comes from three sources: built-in device operating parameter collection modules, connected financial market data source APIs, and locally stored historical calibration logs. Data update rhythms fall into three categories:
- Daily yield calculation values are updated once per calendar day
- Real-time market-related data is updated every 15 minutes
- Full summary broadcast data is generated by 18:00 each day
Each data entry includes: unique device identifier, data collection timestamp, daily yield calculation value, associated ticker code, and device health status indicator. The unique device identifier is a 16-digit hexadecimal string. Collection timestamps use the ISO 8601 format.
What constraints these characteristics impose on database and operations
Multi-source data access requires the database to support mixed read-write modes, separating connection resources for real-time writes and bulk imports to avoid blocking caused by resource contention. High-frequency queries based on device and time range require joint indexes to speed up retrieval; otherwise, query latency will become excessively high. Daily fixed-time full bulk tasks need reasonable timeout thresholds configured to prevent unfinished tasks from disrupting the next day’s broadcast process. Data from multiple sources requires additional identification fields, otherwise logs and stored data cannot be managed by data source category. The timeliness requirement for real-time collected data requires regular cleanup of expired data to free up hot storage resources.
Configuration Recommendations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
DB_CONNECTION_POOL_SIZE | 16-24 | Adapts to mixed scenarios of real-time writes and bulk imports for multi-source data, avoiding connection resource exhaustion |
BATCH_IMPORT_TIMEOUT | 600 seconds | Matches the import duration requirements of daily full summary data, reserving sufficient space for batch processing |
INDEX_COMBINED_FIELDS | device_id, collect_time | Covers core retrieval scenarios based on device and time range, accelerating query response |
DATA_CLEANUP_CRON | 0 2 0 * * * | Runs expired data cleanup at 2:00 AM daily to free up hot storage resources |
SOURCE_HEALTH_CHECK_INTERVAL | 30 seconds | Monitors connectivity status of device sensors and market APIs, detecting data source anomalies promptly |
PLUGIN_DB_QUERY_TIMEOUT | 8 seconds | Adapts to the single query complexity of specialized equipment data, avoiding timeouts that disrupt broadcast processes |
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, and specific issues require individual analysis. Testing on relevant samples is recommended before finalizing settings.
Three Common Mistakes
- Phenomenon: Database connection plugin execution time has increased significantly compared to older versions. Older versions took 0.2 seconds, while newer versions take over 3 seconds. Cause: The connection pool size was not adjusted for the multi-source data scenario of specialized equipment, leading to connection resource contention between real-time writes and queries.
- Phenomenon: The number of vector search return results does not match the configured settings, with empty results or redundant results. Cause: The joint index fields were not configured correctly, and the combined query conditions for device ID and collection time were not covered, leading to deviations in vector index matching.
- Phenomenon: MongoDB logs cannot distinguish write requests from specialized equipment data sources and other business data sources. Cause: No source identification field was included during data writing, or no log field filtering rules were configured, making it impossible to distinguish logs by source tag.
How to Confirm Configuration is Correct
- Submit a full historical data import task for specialized equipment, verify that the task completion time falls within the preset timeout parameter range, and adjust parameters to match actual execution time.
- Execute a combined retrieval request using
device_idand a time range, confirm that the number of returned search results matches the configured recall parameters, and verify that the joint index is active. - View the database logs, confirm that each written data entry carries a source identification field, and use this field to distinguish specialized equipment data sources from other business data.
- Trigger a data source health check, confirm that the execution interval of the check action matches the configured health check parameters.
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.