Database and Operations for Dairy Product Yield Rate Daily

What data for this category looks like

Data related to dairy product yield rates is primarily sourced from fresh milk trading markets, production enterprise ERP systems, terminal retail POS data, and industry association monitoring reports. Data is updated daily, with a full-category summary document generated each day. Individual documents can exceed 10 MB in size. Most documents use multi-worksheet Excel format, where each worksheet corresponds to a dairy product category such as pasteurized milk, yogurt, cheese, etc. Each row contains fields including product SKU, raw material purchase unit price, production and processing costs, terminal selling price, per-box gross profit, and more. Units include yuan/kg and yuan/box.

Constraints for Database and Operations

Daily generated large-volume Excel documents require the database to support batch parallel imports, to avoid single-file parsing timeouts. The multi-SKU, multi-category field structure requires database tables to be partitioned by product category, reducing resource consumption from full-table scans. Format differences across multiple data sources require pre-configured unified data validation rules, to fix issues such as inconsistent units and missing fields. The timeliness of daily reports requires database write tasks to be completed within a fixed window. Operations monitoring must focus on the success rate and duration of import tasks. Additionally, dairy product SKUs are updated frequently, so database table structures must reserve extensible fields to adapt to statistical requirements for new categories.

Configuration Recommendations

Configuration Item	Recommended Value	Rationale
`PARSE_FILE_TIMEOUT_SECONDS`	`600–900 seconds`	Parsing a single dairy product daily report document over 10 MB requires a long duration, to avoid task interruption from mid-run timeouts
`UPLOAD_FILE_MAX_SIZE`	`1500 MB`	Adapts to the maximum size of individual dairy product daily report documents, supports batch upload of multiple daily report files
`MYSQL_CHARSET`	`utf8mb4`	Compatible with special characters and Chinese content in dairy product brand names, prevents garbled text during database storage
`DB_BATCH_INSERT_SIZE`	`500–1000 records/batch`	Balances memory usage and execution efficiency for multi-SKU data imports, avoids blocking caused by overly large single import volumes
`PARSE_SHEET_NUM`	`10–15 worksheets`	Covers the number of worksheets for mainstream dairy product categories, avoids parsing redundant non-business worksheets
`DB_CONN_POOL_SIZE`	`20–30 connections`	Meets connection requirements for multi-task parallel imports, avoids task failure caused by exhausted connections

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. Each situation requires specific analysis. It is recommended to test on your own samples before finalizing settings.

Three Common Mistakes

Symptom: Document parsing task times out and fails, log shows ETIMEDOUT error. Cause: The PARSE_FILE_TIMEOUT_SECONDS parameter was not adjusted, the default timeout duration is insufficient for dairy product daily report documents over 10 MB.
Symptom: Dairy product name fields in MySQL databases display garbled text. Cause: MYSQL_CHARSET was not configured as utf8mb4, using only the utf8 character set cannot accommodate special characters in some dairy product brand names.
Symptom: Generated SQL query statements cannot execute due to included punctuation. Cause: No punctuation filtering was applied to SKU name fields in documents, directly concatenating into SQL statements caused syntax errors.

How to Confirm Proper Configuration

Upload a dairy product daily report document over 10 MB, check the parsing task duration, adjust PARSE_FILE_TIMEOUT_SECONDS to a value longer than the time required for task completion.
Insert a test data entry containing a Chinese brand name, query the field to confirm no garbled text, verifying that the MYSQL_CHARSET configuration is active.
Run a batch import test, check database connection counts and memory usage, adjust DB_CONN_POOL_SIZE to a range that meets concurrency requirements.
Generate test SKU name data containing special punctuation, concatenate into an SQL statement and execute, confirming no syntax errors.

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.