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AIclinicalresearch/docs/02-通用能力层/04-数据ETL引擎/README.md
HaHafeng 31d555f7bb docs: Update architecture docs with platform infrastructure details
- Add platform infrastructure chapter to frontend-backend architecture design
- Update system architecture document with 6 new infrastructure modules
- Update AI onboarding guide with infrastructure overview
- Link to backend/src/common/README.md for detailed usage guide

Key Updates:
- Storage service (LocalAdapter + OSSAdapter)
- Logging system (Winston + JSON format)
- Cache service (Memory + Redis)
- Async job queue (Memory + Database)
- Health check endpoints
- Monitoring metrics
- Database connection pool
- Environment config management

All modules support zero-code switching between local and cloud environments.

Related: #Platform-Infrastructure
2025-11-17 08:36:10 +08:00

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# 数据ETL引擎
> **能力定位:** 通用能力层
> **复用率:** 29% (2个模块依赖)
> **优先级:** P2
> **状态:** ⏳ 待实现
---
## 📋 能力概述
数据ETL引擎负责
- Excel多表JOIN
- 数据清洗
- 数据转换
- 数据验证
---
## 📊 依赖模块
**2个模块依赖29%复用率):**
1. **DC** - 数据清洗整理(核心依赖)
2. **SSA** - 智能统计分析(数据预处理)
---
## 💡 核心功能
### 1. Excel多表处理
- 读取多个Excel文件
- 自动JOIN操作
- GROUP BY聚合
### 2. 数据清洗
- 缺失值处理
- 重复值处理
- 异常值检测
### 3. 数据转换
- 类型转换
- 格式标准化
---
## 🏗️ 技术方案
### 云端版(最优)
```python
# 基于Polars性能极高
class ETLEngine:
def read_excel(self, files: List[File]) -> List[DataFrame]
def join(self, dfs: List[DataFrame], keys: List[str]) -> DataFrame
def clean(self, df: DataFrame, rules: Dict) -> DataFrame
def export(self, df: DataFrame, format: str) -> bytes
```
### 单机版(兼容)
```python
# 基于SQLite内存友好
# 分块读取数据库引擎处理JOIN
```
---
## 🔗 相关文档
- [通用能力层总览](../README.md)
- [DC模块需求](../../03-业务模块/DC-数据清洗整理/README.md)
---
**最后更新:** 2025-11-06
**维护人:** 技术架构师