What this type of data looks like
Data sources include official exchange market data APIs and compliant third-party market data feeds. Update frequency varies with trading hours: high-frequency updates occur during trading sessions, and full daily datasets are generated after market close. Each data entry includes the unique security identification code, full name, trading date, opening price, closing price, yield metrics, and transaction scale fields. Yield fields use standardized floating-point values. Price fields use values matching their pricing units. Transaction scale fields include original transaction counts and monetary amount values.
What constraints these characteristics impose on database and operations
High-frequency real-time market data creates continuous write pressure, requiring database clusters to support high-throughput write capabilities and adapt to sudden traffic peaks during trading hours. Batch generation and synchronization of full daily datasets require efficient batch write and incremental data verification logic to prevent data duplication or loss. The high-precision floating-point storage requirement for yield fields requires matching numerical type parameters to avoid precision loss that affects subsequent calculations. Additionally, securities data must meet compliance retention requirements: databases must support periodic archiving of historical data and retain complete traceability links, and maintenance operations must avoid trading hours to prevent disruption to real-time services.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
DB_WRITE_BATCH_SIZE | 50–200 records/batch | Adapts to batch writes of high-frequency securities data, balances write efficiency and transaction overhead |
QUERY_TIMEOUT_SECONDS | 30–60 seconds | Covers long-running queries for all securities, prevents mid-execution timeout interruptions |
FLOAT_PRECISION | 10 decimal places | Matches the high-precision storage requirement for securities yields, avoids numerical deviation |
DATA_ARCHIVE_RETENTION_DAYS | 365–730 days | Meets compliance retention requirements for securities data |
CONNECTION_POOL_MAX_SIZE | 20–50 connections | Adapts to concurrent query requests during trading hours, prevents connection exhaustion |
INCREMENTAL_SYNC_INTERVAL | 10–30 seconds | Matches the update frequency of real-time securities market data, ensures data timeliness |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by data format, data volume, and business rules. Specific issues require individual analysis, and testing on samples is recommended before finalizing settings.
Three common configuration mistakes
- Symptom: Occasional SQL query execution failures occur, returning a
504 Gateway Timeoutstatus code. Cause: Failure to adapt to securities data traffic peaks, insufficient connection pool configuration, and concurrent requests during trading hours exhausting connections and causing timeouts. - Symptom: Tool call nodes become unresponsive after reaching the database stage, causing workflow interruptions. Cause: Database connection timeout parameters are not configured, or the timeout threshold is set too short, and long-running full market queries are terminated before completion.
- Symptom: Format errors occur when importing security code type data, and fields cannot be stored normally. Cause: The matching string type field is not used to store security codes, and numerical types are mistakenly used, leading to loss of leading zeros.
How to verify proper configuration
- Run a single full query for all securities, verify that the precision of returned fields matches the original data source, and adjust corresponding parameters based on business requirements.
- Simulate concurrent requests during trading hours, monitor database connection pool usage, and adjust connection pool configuration parameters based on peak conditions.
- Trigger an incremental synchronization task, verify that the synchronization interval matches the market data update frequency, and adjust the synchronization interval parameter based on data timeliness requirements.
- Check the database archiving link, confirm that historical data is automatically archived according to the configured cycle, and adjust the retention period parameter based on compliance requirements.
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.