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