What the data for this category looks like
Cosmetics profit margin related data mainly comes from brand public quarterly financial reports, vertical beauty industry monitoring databases, and sales review reports from leading e-commerce platforms. Data update frequencies are divided into two categories: regular monthly updates and weekly updates for core SKUs. A single data entry includes brand identifier, SKU code, subcategory (skincare/makeup/hair care, etc.), profit level value, channel sales share value, and competitor benchmark range value. The unit of profit level value is percentage points, and channel sales share value is measured on a ten-point scale, with no percentage-based expressions.
Constraints imposed on deployment and upgrade by these characteristics
Cosmetics category data has multiple sources, layered update frequencies, and a large number of SKUs, which imposes multiple constraints on the deployment and upgrade process. Pulling data from multiple sources requires configuring parsing rules adapted to different interface formats to avoid field mapping errors. Layered update frequencies require configuring differentiated scheduled task scheduling during deployment, distinguishing the pull cycles for core SKUs and regular product categories. A large volume of SKUs requires compatible memory threshold settings for batch data import during upgrades to avoid service freezes. Additionally, the differentiated unit requirements for fields require configuring unified format conversion rules during the data cleaning stage to ensure consistency of subsequent broadcast data.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
BATCH_IMPORT_SIZE | 500 items/time | The cosmetics category has a large number of SKUs; a single batch of 500 items balances import speed and service memory usage |
DATA_UNIT_CONVERT | Enabled | Cosmetics data includes two types of units: percentage points and ten-point scale. Conversion must be enabled to ensure unified broadcast data format |
SYNC_TASK_CRON | 0 0 2 * * ? (core SKUs), 0 0 1 * * ? (regular product categories) | Matches the business rhythm of weekly updates for core SKUs and monthly updates for regular product categories |
MAX_IMPORT_MEMORY | 2048 MB | This threshold prevents service out-of-memory errors when batch importing large volumes of SKU data |
DATA_DUPLICATE_CHECK | Enabled | Pulling data from multiple sources easily generates duplicate SKU data; enabling deduplication ensures data accuracy |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Adapts to the parsing duration of batch importing large volumes of SKU data, avoiding timeout errors |
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 individual analysis, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Symptom: Unable to modify login password after Docker deployment, with no password modification entry in the interface. Cause: The
./datadirectory was not mounted to the host machine, causing configuration files to fail to persist, and password modifications did not take effect. - Symptom: The service returns
504 Gateway Timeoutwhen batch importing cosmetics SKU data. Cause: ThePARSE_FILE_TIMEOUT_SECONDSparameter is set too short, failing to adapt to the parsing duration of large volumes of SKU data. - Symptom: After exposing the external network via ngrok, iOS devices experience a white screen, while macOS and Windows devices work normally. Cause: Cross-origin resource sharing rules are not configured; iOS WebView has stricter cross-origin request verification.
How to confirm configuration is complete
- Run a batch import test, check the import logs for unit conversion failure errors to confirm that the data format conversion configuration is effective.
- View the scheduled task management interface to confirm that the sync task scheduling times for core SKUs and regular product categories match the business update rhythm.
- Check port mapping and cross-origin configuration, use different terminal devices to access the exposed service address, and verify that page loading and data display work normally.
- View the data deduplication logs to confirm that duplicate SKU data is automatically filtered, with no duplicate entries appearing in the final dataset.
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.