What this category of data looks like
Semiconductor yield and market trend data draws from public market APIs of domestic stock exchanges and public datasets from semiconductor industry monitoring platforms. Two update cadences are in use: full daily report data sync runs after daily market close, and real-time market data updates every 15 minutes. Each data entry uses a structured format, including fields such as trading date, security code, semiconductor product category, average transaction unit price, daily trading volume, and industry growth index. The unit for average transaction price is yuan per product unit, trading volume is measured in ten thousand units, and industry growth index is a dimensionless value. Each record covers trading and market information for a single product category on one trading day.
Constraints on database and operations
Semiconductor market and yield data uses two update cadences. It requires support for both daily full batch sync and 15-minute real-time incremental pulls, which demands the database’s concurrent read/write capabilities. The data includes multi-dimensional classification fields, so teams must create composite indexes to enable fast queries by product category and trading date. Daily full sync jobs handle large data volumes, so configure a reasonable batch write threshold to avoid single write operation timeouts. High-frequency real-time updates generate many small data packets, so enable database batch write optimization to reduce IO overhead. Differences in field units and format requirements require validation rule configuration before data ingestion, to prevent dirty data from entering the database.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
database_type | Use a domestically compliant relational or document database | Meets domestic replacement requirements, avoids restrictions on overseas component use |
db_batch_insert_size | 500–1000 records/batch | Adapts to daily full sync data scale, balances write efficiency and single IO overhead |
real_time_sync_interval | 900 seconds | Matches the 15-minute update cadence of semiconductor market data, reserves reasonable buffer time |
maxContext | 8000–12000 characters | Supports long-document context association for semiconductor market data, avoids semantic context loss during consecutive queries |
api_rate_limit | 100 requests/minute | Adapts to high-frequency real-time market data call demands, alleviates concurrency restriction issues |
query_index_fields | ["trade_date", "product_category"] | Matches multi-dimensional query scenarios, improves composite query response speed |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing settings.
Three common misconfigurations
- Symptom: The knowledge base fails to load semiconductor market data normally, and the console reports "unsupported database type". Cause: The
database_typeconfiguration is not set to a domestically compliant database type, and overseas open-source components are used directly. - Symptom: When consecutively asking questions about semiconductor yield rates, subsequent answers fail to associate security codes or product categories from previous questions, resulting in off-topic responses. Cause: The
maxContextparameter value is too small, and insufficient context storage space is reserved. - Symptom: Concurrent queries for real-time market data frequently return
429 Too Many Requestserrors. Cause: A reasonableapi_rate_limitparameter is not configured, interface call frequency is not restricted, and the platform's current limit threshold is exceeded.
How to confirm configurations are correctly applied
- Run a full data sync task, check database write logs, and confirm that the single-write batch count matches the configured
db_batch_insert_sizeparameter. - Initiate two consecutive semiconductor market data queries, check whether subsequent answers associate keywords from the first query, and confirm that context configuration takes effect.
- Initiate multiple concurrent real-time market data query requests, check interface return status codes, and confirm that current-limiting errors are not triggered.
- Run a composite query by trading date and product category, check the matching range of returned results, and confirm that index configuration takes effect.
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.