What the data for this category looks like
The yield and market data for investment platforms primarily comes from official exchange market interfaces and compliant financial data service providers. Data update schedules fall into two categories. Intraday real-time market data is synchronized every 15 seconds. Full daily yield reports after market close are generated in batches after 17:00 local time each day. Each data entry includes fields such as asset code, asset name, daily return value, cumulative return value, trading volume, benchmark index deviation value, and more. There is no nested structure. All fields are standardized numerical or string types. The size of a single data entry is stable under 1KB. The full daily dataset can reach tens of gigabytes in scale.
Constraints on Database and Operations Workflows
The data characteristics of this category impose multiple constraints on database and operations workflows. First, the tens of gigabyte daily batch dataset requires the database to support partitioned table storage. Shard tables by date to avoid excessive single-table size that reduces query efficiency. Second, the low-latency write requirement for intraday real-time market data calls for a read-write separation architecture. This isolates real-time write traffic from historical query traffic. Additionally, financial data cannot be interrupted. Use a rolling update strategy for operations to avoid data synchronization interruptions caused by full downtime maintenance. Finally, data compliance rules require regular archiving of database logs. The retention period must meet industry regulatory requirements.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGO_SHARD_COLLECTION | ["yield_daily", "real_time_quotes"] | Core data for this category splits into daily reports and real-time quotes. Sharding by business table improves query and write performance |
READ_REPLICA_COUNT | 2–3 | Handles read traffic from real-time quotes and historical queries. Adds no excessive operational costs |
DATA_BACKUP_CRON | 0 2 * * * | Daily 2:00 is a business low-traffic period. Running backups at this time does not disrupt user access. Covers the full day’s data |
MAX_CONCURRENT_WRITE | 500–800 | Matches peak batch write traffic for intraday real-time quotes. Prevents database connection exhaustion |
LOG_RETENTION_DAYS | 365 | Meets basic data compliance retention requirements for the financial industry |
PARSE_DATA_TIMEOUT | 300 seconds | Adapts to parsing time for batch daily report data. Prevents data synchronization interruptions from timeouts |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by data format, volume, and business rules. Specific issues require targeted analysis. Testing on local samples is recommended before finalizing settings.
Three Common Misconfigurations
- Issue: MongoDB fails to start after migration. Running
systemctl status mongodreturnsFailed to start mongod.service: Unit mongod.service not found.. Cause: Residual mount directory configuration files were not cleaned during migration. The service reads invalid paths on startup. - Issue: A single-node deployment throws
503 Service Unavailableerrors when handling 50 concurrent requests. Cause: Maximum database connection pool size was not adjusted. Connection exhaustion prevents new requests from being processed. - Issue: Application logs return
Failed to connect to 192.168.xx.xx:1433. Cause: The corresponding port was not opened in the database firewall. Or the database address in the configuration file was not updated to the migrated instance address.
How to Verify Correct Configuration
- Run the database sharding validation script. Check if the
yield_dailyandreal_time_quotestables are partitioned by date. Confirm partitioning rules match configured settings. - Send simulated concurrent requests. Observe database connection pool status. Confirm maximum concurrent write configuration supports peak business traffic.
- Trigger the scheduled backup task. Check that backup files are generated and stored in the correct path. Confirm backup alignment with business low-traffic periods.
- View the database log retention directory. Confirm log files are automatically archived per the retention period. Check for no log overflow issues.
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.