What the data for this category looks like
Data sources for e-commerce service investment research primarily include product detail pages from public e-commerce platforms, real-time transaction data, user reviews, competitor store monitoring data, and third-party industry e-commerce market reports. Data update rhythms fall into three categories: core metrics such as product price and inventory are updated in minute-level real time; user reviews are synced in daily batches; industry market reports are updated weekly.
Document structure includes structured fields and unstructured text. Structured fields include sku_id, price (unit: yuan), inventory, competitor_rank, and others. Unstructured text includes product detail descriptions, long user reviews, competitor campaign copy, and others.
What constraints do these characteristics place on the database and operations link?
Minute-level real-time updated transaction data requires the database to support high-frequency writing and synchronization. This imposes requirements on operational stability, and writing blocking must be avoided. Mixed structured and unstructured data requires the database to support both relational indexing and full-text search. Without this, efficient recall of user feedback and competitor information needed for investment research is not possible.
E-commerce data has strong time sensitivity. Expired price and inventory data will mislead investment research conclusions. An automated data expiration cleanup mechanism must be configured to avoid invalid data occupying storage. Long-text user reviews and product details will increase index construction pressure. Configuration parameters for word segmentation and indexing must be adjusted accordingly.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
DB_SYNC_INTERVAL | 30 seconds | Matches the minute-level update rhythm of core e-commerce metrics (price, inventory) to ensure real-time availability of investment research data |
TEXT_INDEX_SETTING | {"weights": {"comment_content": 2, "product_desc": 1.5}} | Increases the retrieval weight of user reviews and product details, aligning with investment research focus on user feedback and product selling points |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Supports importing large e-commerce industry reports and bulk competitor monitoring data, preventing import failures due to oversized files |
RECALL_TOP_N | Top 8–12 entries | Balances the information breadth required for investment research and result accuracy, avoiding excessive redundant data interfering with analysis |
DATA_CLEANUP_CYCLE | 7 days | Clears expired inventory and price data older than 7 days, reducing invalid storage usage and ensuring database operational efficiency |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Adapts to the parsing duration of long-text product details and bulk user reviews, preventing parsing timeouts and interruptions |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material formats, data volumes, and business rules. Specific issues require targeted analysis, and it is recommended to test on your own samples before finalizing settings.
Three common configuration mistakes
- The symptom is a console error
text index required for $text query. The cause is that full-text indexes have not been configured for unstructured fields such ascomment_contentandproduct_desc, preventing retrieval requests from executing. - The symptom is knowledge base data loss after upgrading FastGPT. The cause is that a database persistent storage volume has not been configured. High-frequency updated e-commerce data is not persistently stored, and local data is cleared during the upgrade process.
- The symptom is that the number of query results does not match expectations. The cause is that the
RECALL_TOP_Nconfiguration value does not match the information needs of the investment research scenario. A too-low configuration will miss key competitor information, while a too-high configuration will introduce redundant noise.
How to confirm the configuration is correct
- Execute a full-text search that includes the
comment_contentfield, verify that user review data containing specified keywords can be retrieved. - Restart the database service, check that previously imported e-commerce data has not been lost, confirming that the persistent configuration is active.
- Simulate a product price update, wait for the configured synchronization interval, then query the database to confirm that the latest price has been synchronized successfully.
- Adjust the
SIMILARITY_THRESHOLDparameter, verify that the matching degree of returned results meets the accuracy requirements for investment research analysis.
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.