What the data for this category looks like
Securities investment research data comes from Shanghai, Shenzhen, and Beijing Stock Exchange public announcements, listed companies’ periodic reports, industry broker research reports, macroeconomic indicators, and real-time trading quotes. Update frequencies fall into three categories:
- Real-time trading quotes are pushed quasi-real-time.
- Exchange announcements are updated synchronously upon release.
- Industry research reports are stored on the day of publication.
- Periodic reports are updated concentratedly during quarterly and annual report windows.
Document structures cover three types:
- Structured market data
- Semi-structured research reports and announcements
- Unstructured long analysis texts
Fields and units follow financial industry standards:
- Stock codes are 6-digit numbers
- Stock price unit is RMB yuan
- Trading volume unit is shares or trading lots
- Research report rating fields use five standardized categories: buy, overweight, neutral, underweight, sell.
Constraints for database and operations
Quasi-real-time pushing of real-time market data requires databases to support low-latency writing and high-concurrency queries. This prevents data lag from impacting investment research decisions. Concentrated updates of periodic reports create write peaks. Databases need elastic scaling capabilities to handle sudden load. Mixed storage of structured market data and semi-structured research reports requires operations to balance the structured query advantages of relational databases and the semi-structured adaptation capabilities of document databases. Differences in field formats across data sources require configuration of standardized cleaning rules in operations. This unifies units and field naming. Additionally, compliance storage requirements for securities data mandate configuration of database permission auditing, log retention, and backup mechanisms. These meet financial data security specifications.
Configuration settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
DB_CONNECTION_POOL_SIZE | 10-30 | Adapts to concurrent query demands of securities investment research scenarios, balances request response speed and database resource usage |
PARSE_DOCUMENT_CHUNK_SIZE | 800-1200 characters | Preserves semantic integrity of long texts such as research reports and announcements, avoids splitting that breaks logical connections between industry analysis and financial data |
DB_WRITE_BATCH_SIZE | 500-1000 entries | Handles batch writing scenarios during concentrated periodic report updates, balances writing efficiency and single-database load |
SQL_QUERY_TIMEOUT | 30-60 seconds | Covers execution durations of complex investment research associated queries, prevents valid business requests from being interrupted by timeouts |
VECTOR_SEARCH_TOP_K | 10-20 entries | Balances richness of investment research reference materials and context window load, avoids excessive redundant information interfering with analysis |
DB_BACKUP_INTERVAL | 02:00 daily | Performs backups outside trading hours, ensures data security without impacting real-time business access |
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 case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three common configuration errors
- Phenomenon: When executing custom investment research SQL queries, some queries return results successfully, while others do not respond or return empty values. Logs show
504 Gateway Timeouterrors. Cause: Database connection pool parameters are not adjusted for concurrent peaks in securities data. Connection exhaustion during peak hours causes some requests to be dropped. - Phenomenon: When attempting to store quantitative strategy code, research report attachment code, or similar data, query results show format corruption or missing fields. Cause: Chunking rules adapted to code text are not configured. Splitting destroys code indentation and syntax structure, leading to subsequent parsing failures.
- Phenomenon: After calling the database query tool node, workflow execution stalls with no return and no clear error message. Cause: Reasonable SQL query timeout parameters are not set. Complex investment research multi-table association queries exceed default timeout thresholds, and no timeout feedback mechanism is triggered.
How to verify proper configuration
- Run simulated real-time market batch queries, observe database connection count changes, confirm that connection pool parameters adapt to current business concurrent load.
- Batch import a set of listed company periodic reports and industry research reports, check that chunked documents retain core fields and semantic integrity, with no obvious logical breaks.
- Run multiple investment research query SQL statements involving multi-table associations, verify that query timeout parameters cover most business scenarios with no abnormal interruptions.
- Trigger a scheduled backup task, confirm that backup files are generated normally, and that the backup process does not impact real-time trading data queries and writes.
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.