What data for this category looks like
Duty-free yield rate-related data comes from three main sources: duty-free operator inventory and sales systems, customs offshore duty-free filing APIs, and official price adjustment announcements from local duty-free shops. The data includes these fields: product SKU code, purchase cost (excluding tax, unit: yuan), listed selling price (unit: yuan), offshore duty-free discounted actual selling price (unit: yuan), policy subsidy amount (unit: yuan), and daily net profit per product (unit: yuan). Update cadence follows this schedule: real-time sync for SKUs with same-day price adjustments, daily batch update for full-category daily net profit summaries, weekly update for category average net profit, and monthly update for benchmark profit parameters after policy adjustments.
What constraints do these characteristics impose on deployment and upgrade?
Deployments must configure permission verification and request fault tolerance for multi-source data integration, as data sources include third-party APIs, internal systems, and public announcements. Layered scheduling rules are required for data sources with different update cadences. Real-time price adjustment data needs low-latency sync logic. Batch summary data needs sufficient reserved computing resources. Policy subsidy fields adjust dynamically based on regulatory requirements. Upgrades must support flexible field mapping configurations to avoid adaptation failures from hardcoding. Full-category SKU and daily summary data volumes require sufficient reserved concurrent processing capacity for deployments.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MAX_WORKERS | CPU core count × 1.2–1.5 | Adapts to concurrent processing needs for multi-source data sync and batch tasks, avoids single-thread blocking |
SYNC_TASK_TIMEOUT | 600 seconds | Customs filing APIs have relatively high response latency, reserve sufficient timeout window for batch SKU synchronization |
CRON_SCHEDULE_DAILY | 0 2 * | Avoids peak business hours, matches the end of duty-free shop daily operating hours |
PARSE_FIELD_MAPPING | Associate purchase cost, actual selling price, and subsidy amount fields via SKU code | SKU code is the core association key for duty-free data, ensures accuracy of multi-source data matching |
UPLOAD_BATCH_SIZE | 500 items/shard | Moderate per-shard data volume, avoids single request timeouts or memory overflow |
MEMORY_LIMIT | 16 GB–32 GB | Reserve sufficient memory for data caching and calculations when processing full-category SKU data in batches |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by data format, data volume, and business rules. Specific issues require targeted analysis, and it is recommended to test on local deployment samples before finalizing settings.
Three common mistakes
- Phenomenon: After deployment on an 8-core 32GB server, batch SKU data sync tasks frequently time out. Cause: The
MAX_WORKERSconfiguration was not adjusted to the range matching the CPU core count, and sufficient memory was not reserved for caching batch data. - Phenomenon: After modifying container configurations, the data source sync interface on port 3005 fails to respond normally, while the management interface on port 3000 runs normally. Cause: Firewall rules for port 3005 were not opened, or the listening address for port 3005 was not correctly bound in the configuration file.
- Phenomenon: The policy subsidy field is empty in the generated yield rate daily report. Cause: The
PARSE_FIELD_MAPPINGconfiguration was not updated after the upgrade, and new policy subsidy field mapping rules were not associated.
How to confirm the configuration is correct
- Check the running logs of multi-source data sync. Confirm that requests to the customs filing API and inventory system API complete normally, with no persistent timeout errors.
- Manually trigger the daily summary task. Verify that generated yield rate data fields match the actual fields of the data sources.
- Check the container's resource monitoring metrics. Confirm that memory and CPU usage stay within a reasonable range, with no frequent memory overflow or thread blocking.
- Test the data source sync interface on port 3005. Confirm that port listening and access permissions take effect after configuration modifications.
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.