What this category of data looks like
Apparel and home textiles investment research data is primarily sourced from public industry association reports, brand quarterly financial reports, upstream supply chain supplier quotation platforms, offline retail terminal monitoring data, and fabric composition test reports. Update frequencies vary: retail terminal monitoring data is updated daily, raw material quotation data is updated daily or semi-weekly, brand financial reports are updated quarterly, and in-depth industry reports are updated irregularly.
Individual documents cover dimensions including upstream raw material composition, supply chain cost breakdown, SKU details, terminal sales trends, and more. Fields include SKU codes, fabric composition percentage values, unit cost, terminal price ranges, and other relevant metrics. Document lengths range from several hundred-word retail monitoring entries to tens of thousands-word industry research reports.
What constraints these characteristics impose on database and operations workflows
Multi-source, uneven update rhythms require the database to support flexible incremental sync task configuration. This avoids excessive server load caused by full synchronization operations. Granular, multi-dimensional fields require strict type validation and mapping rules. This prevents format conflicts between identical data types from different sources. The wide range of document lengths requires the database to support both fast retrieval of short texts and efficient storage of long documents. The timeliness requirement of investment research data demands stable database read/write performance. This prevents timeouts during high-frequency queries or batch sync operations. The database must also support archiving and quick retrieval of historical data.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGO_CONNECTION_POOL_SIZE | 20–30 | Apparel and home textiles investment research data includes multi-source sync tasks and high-frequency retrieval requests. This parameter controls the number of MongoDB connection pools to adapt to concurrent read/write scenarios |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Long documents such as industry supply chain reports have significant length, requiring sufficient parsing timeout to prevent task interruptions |
RECALL_TOP_K | Top 10 entries | Investment research knowledge bases need to cover multi-dimensional data. Too many recalled entries will increase inference load, while too few will not support complete investment research analysis |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Individual industry research reports may contain large numbers of charts and raw data, allowing large file uploads to cover complete data sources |
DB_INCREMENT_SYNC_INTERVAL | 3600 seconds | Apparel and home textiles retail data is updated daily or weekly. Syncing hourly ensures data timeliness while reducing server load |
The parameter values provided on this page are general recommendations to serve as a starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Symptom: Unable to log in to the database after creating a custom MongoDB user, with the error
Authentication failed. Cause: Database role permissions were not correctly specified. When granting permissions other thanroot, the corresponding database was not bound. - Symptom: A
400 status code (no body)error is returned when calling database tools. Cause: The parameter format of the database connection string was not correctly configured, or required execution fields were missing from the request body. - Symptom: MongoDB connection timeout is displayed when running
pnpm devin a local development environment. Cause: The listening address and port of MongoDB were not correctly filled in the local configuration file, or the firewall blocked connection requests on the default port.
How to confirm the configuration is complete
- Run the MongoDB user creation command, log in to the corresponding database using the newly created account, and verify that the login process has no errors.
- Upload a typical apparel and home textiles industry report, wait for parsing to complete, and check the parsing logs to confirm there are no timeout or format parsing failure records.
- Initiate a recall query for the investment research knowledge base, and verify that the number of returned results matches the configured recall parameter.
- Check the database monitoring dashboard to confirm that the connection pool usage matches the load of read/write requests, with no persistent connection anomaly alerts.
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.