业务场景应用案例
# 业务场景应用案例
# 案例概述
本案例集展示StreamSQL在各种实际业务场景中的应用，涵盖电商、金融、物联网、社交媒体等多个领域。
# 案例1：电商推荐系统
# 业务场景
基于用户实时行为数据，动态调整商品推荐策略，提升转化率。
# 数据输入
{
"user_id": "U001",
"action": "view_product",
"product_id": "P001",
"category": "electronics",
"price": 299.99,
"timestamp": "2024-01-15T10:30:00Z",
"session_id": "S001",
"source": "search"
}
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# 期望输出
{
"user_id": "U001",
"recommendations": [
{
"product_id": "P002",
"score": 0.95,
"reason": "similar_category"
},
{
"product_id": "P003",
"score": 0.88,
"reason": "frequently_bought_together"
}
],
"user_profile": {
"preferred_categories": ["electronics", "books"],
"price_range": "200-500",
"purchase_probability": 0.75
},
"timestamp": "2024-01-15T10:30:00Z"
}
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# 案例2：智能客服路由
# 业务场景
根据客户问题类型、紧急程度和客服技能，智能分配客服资源。
# 数据输入
{
"ticket_id": "T001",
"customer_id": "C001",
"question": "My order hasn't arrived yet",
"category": "shipping",
"priority": "medium",
"customer_tier": "premium",
"timestamp": "2024-01-15T10:30:00Z"
}
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# 期望输出
{
"ticket_id": "T001",
"assigned_agent": {
"agent_id": "A001",
"name": "Sarah Johnson",
"skills": ["shipping", "returns"],
"current_load": 3,
"estimated_response_time": "5 minutes"
},
"routing_reason": "skill_match_and_availability",
"escalation_rules": {
"auto_escalate_after": "30 minutes",
"escalate_to": "supervisor"
},
"timestamp": "2024-01-15T10:30:00Z"
}
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# 案例3：供应链优化
# 业务场景
基于实时销售数据和库存状况，优化采购和配送策略。
# 数据输入
{
"product_id": "P001",
"warehouse_id": "WH001",
"current_stock": 50,
"daily_sales_avg": 15,
"lead_time_days": 7,
"supplier_id": "SUP001",
"timestamp": "2024-01-15T10:30:00Z"
}
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# 期望输出
{
"product_id": "P001",
"warehouse_id": "WH001",
"inventory_analysis": {
"days_of_stock": 3.3,
"reorder_point": 105,
"suggested_order_quantity": 200,
"urgency_level": "high"
},
"optimization_actions": [
{
"action": "emergency_reorder",
"supplier": "SUP001",
"quantity": 200
},
{
"action": "redistribute_stock",
"from_warehouse": "WH002",
"quantity": 30
}
],
"timestamp": "2024-01-15T10:30:00Z"
}
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# 案例4：金融风险控制
# 业务场景
实时监控交易行为，识别欺诈交易和异常模式。
# 数据输入
{
"transaction_id": "TXN001",
"user_id": "U001",
"amount": 2500.00,
"merchant": "Online Store",
"location": "Tokyo",
"device_fingerprint": "DEV001",
"timestamp": "2024-01-15T10:30:00Z"
}
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# 期望输出
{
"transaction_id": "TXN001",
"risk_assessment": {
"overall_score": 0.75,
"risk_factors": [
{
"factor": "unusual_location",
"weight": 0.3,
"description": "Transaction from new location"
},
{
"factor": "high_amount",
"weight": 0.25,
"description": "Amount above user's typical range"
}
]
},
"decision": "manual_review",
"recommended_actions": [
"verify_user_identity",
"check_device_history"
],
"timestamp": "2024-01-15T10:30:00Z"
}
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# 案例5：智慧城市交通管理
# 业务场景
基于实时交通数据，优化信号灯控制和路线推荐。
# 数据输入
{
"intersection_id": "INT001",
"traffic_flow": {
"north": 45,
"south": 32,
"east": 28,
"west": 38
},
"weather": "rainy",
"time_of_day": "rush_hour",
"timestamp": "2024-01-15T08:30:00Z"
}
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# 期望输出
{
"intersection_id": "INT001",
"signal_optimization": {
"north_south_green_time": 45,
"east_west_green_time": 35,
"cycle_length": 90,
"efficiency_improvement": 15
},
"traffic_predictions": {
"congestion_level": "moderate",
"estimated_wait_time": 120,
"alternative_routes": ["Route_A", "Route_B"]
},
"alerts": [
{
"type": "weather_impact",
"message": "Reduced visibility due to rain"
}
],
"timestamp": "2024-01-15T08:30:00Z"
}
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# 案例6：社交媒体内容审核
# 业务场景
实时审核用户发布的内容，识别违规内容和垃圾信息。
# 数据输入
{
"post_id": "POST001",
"user_id": "U001",
"content": "Check out this amazing product!",
"media_urls": ["https://example.com/image1.jpg"],
"hashtags": ["#product", "#amazing"],
"timestamp": "2024-01-15T10:30:00Z"
}
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# 期望输出
{
"post_id": "POST001",
"moderation_result": {
"status": "approved",
"confidence": 0.92,
"flags": [],
"content_score": {
"spam_probability": 0.05,
"toxicity_score": 0.02,
"quality_score": 0.88
}
},
"recommendations": {
"boost_eligible": true,
"target_audience": "product_enthusiasts",
"engagement_prediction": 0.75
},
"timestamp": "2024-01-15T10:30:00Z"
}
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# 案例7：能源管理优化
# 业务场景
基于实时能耗数据和天气预报，优化能源分配和使用策略。
# 数据输入
{
"building_id": "B001",
"current_consumption": 150.5,
"temperature": 22.5,
"occupancy": 85,
"weather_forecast": "sunny",
"time_of_day": "morning",
"timestamp": "2024-01-15T09:30:00Z"
}
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# 期望输出
{
"building_id": "B001",
"energy_optimization": {
"recommended_temperature": 21.0,
"hvac_schedule": {
"next_hour": "reduce_by_10_percent",
"afternoon": "increase_cooling"
},
"estimated_savings": 25.5
},
"predictions": {
"peak_demand_time": "14:00",
"daily_consumption_forecast": 1850.0,
"cost_optimization": 125.50
},
"alerts": [],
"timestamp": "2024-01-15T09:30:00Z"
}
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# 业务价值
# 实时决策
- 即时响应: 基于实时数据做出快速决策
- 动态调整: 根据变化自动调整策略
- 预测分析: 提前预测趋势和问题
# 运营效率
- 自动化: 减少人工干预和错误
- 资源优化: 最大化资源利用效率
- 成本控制: 降低运营成本
# 用户体验
- 个性化: 提供个性化的服务体验
- 响应速度: 快速响应用户需求
- 服务质量: 提升整体服务质量
# 📚 相关文档
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上次更新: 2025/07/27, 15:17:27