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AIclinicalresearch/tests/run_tests.sh
HaHafeng 4c6eaaecbf feat(dc): Implement Postgres-Only async architecture and performance optimization
Summary:
- Implement async file upload processing (Platform-Only pattern)
- Add parseExcelWorker with pg-boss queue
- Implement React Query polling mechanism
- Add clean data caching (avoid duplicate parsing)
- Fix pivot single-value column tuple issue
- Optimize performance by 99 percent

Technical Details:

1. Async Architecture (Postgres-Only):
   - SessionService.createSession: Fast upload + push to queue (3s)
   - parseExcelWorker: Background parsing + save clean data (53s)
   - SessionController.getSessionStatus: Status query API for polling
   - React Query Hook: useSessionStatus (auto-serial polling)
   - Frontend progress bar with real-time feedback

2. Performance Optimization:
   - Clean data caching: Worker saves processed data to OSS
   - getPreviewData: Read from clean data cache (0.5s vs 43s, -99 percent)
   - getFullData: Read from clean data cache (0.5s vs 43s, -99 percent)
   - Intelligent cleaning: Boundary detection + ghost column/row removal
   - Safety valve: Max 3000 columns, 5M cells

3. Bug Fixes:
   - Fix pivot column name tuple issue for single value column
   - Fix queue name format (colon to underscore: asl:screening -> asl_screening)
   - Fix polling storm (15+ concurrent requests -> 1 serial request)
   - Fix QUEUE_TYPE environment variable (memory -> pgboss)
   - Fix logger import in PgBossQueue
   - Fix formatSession to return cleanDataKey
   - Fix saveProcessedData to update clean data synchronously

4. Database Changes:
   - ALTER TABLE dc_tool_c_sessions ADD COLUMN clean_data_key VARCHAR(1000)
   - ALTER TABLE dc_tool_c_sessions ALTER COLUMN total_rows DROP NOT NULL
   - ALTER TABLE dc_tool_c_sessions ALTER COLUMN total_cols DROP NOT NULL
   - ALTER TABLE dc_tool_c_sessions ALTER COLUMN columns DROP NOT NULL

5. Documentation:
   - Create Postgres-Only async task processing guide (588 lines)
   - Update Tool C status document (Day 10 summary)
   - Update DC module status document
   - Update system overview document
   - Update cloud-native development guide

Performance Improvements:
- Upload + preview: 96s -> 53.5s (-44 percent)
- Filter operation: 44s -> 2.5s (-94 percent)
- Pivot operation: 45s -> 2.5s (-94 percent)
- Concurrent requests: 15+ -> 1 (-93 percent)
- Complete workflow (upload + 7 ops): 404s -> 70.5s (-83 percent)

Files Changed:
- Backend: 15 files (Worker, Service, Controller, Schema, Config)
- Frontend: 4 files (Hook, Component, API)
- Docs: 4 files (Guide, Status, Overview, Spec)
- Database: 4 column modifications
- Total: ~1388 lines of new/modified code

Status: Fully tested and verified, production ready
2025-12-22 21:30:31 +08:00

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#!/bin/bash
# Linux/Mac脚本 - 运行缺失值处理功能测试
echo "========================================"
echo "缺失值处理功能 - 自动化测试"
echo "========================================"
echo
# 检查Python是否安装
if ! command -v python3 &> /dev/null; then
echo "[错误] Python未安装"
exit 1
fi
echo "[1/3] 检查Python服务状态..."
if ! curl -s http://localhost:8001/health > /dev/null 2>&1; then
echo "[警告] Python服务未运行请先启动服务"
echo " cd extraction_service"
echo " python main.py"
echo
exit 1
fi
echo "[OK] Python服务运行正常"
echo
echo "[2/3] 检查依赖..."
python3 -c "import pandas, numpy, requests" 2> /dev/null
if [ $? -ne 0 ]; then
echo "[警告] 缺少依赖,正在安装..."
pip3 install pandas numpy requests
fi
echo "[OK] 依赖检查完成"
echo
echo "[3/3] 运行测试..."
echo
python3 test_fillna_operations.py
echo
echo "========================================"
echo "测试完成"
echo "========================================"