🌊 Streaming & Real-time

Content Outline

Comprehensive guide to streaming and real-time data processing in PyMapGIS:

1. Streaming Architecture

• Event-driven architecture design
• Stream processing pipeline
• Real-time data ingestion
• Scalability and performance
• Fault tolerance and recovery

2. Kafka Integration

• Apache Kafka integration
• Producer and consumer implementation
• Topic management and partitioning
• Serialization and deserialization
• Error handling and retry logic

3. MQTT Integration

• MQTT protocol implementation
• IoT device integration
• Message routing and filtering
• Quality of service (QoS) handling
• Security and authentication

4. Stream Processing

• Real-time data transformation
• Windowing and aggregation
• Event correlation and pattern detection
• Complex event processing
• State management

5. Geospatial Streaming

• Spatial data streaming protocols
• Real-time location tracking
• Geofencing and spatial alerts
• Moving object databases
• Temporal-spatial analysis

6. Performance Optimization

• Stream processing optimization
• Memory management for streams
• Parallel processing strategies
• Backpressure handling
• Throughput optimization

7. Integration with Core Modules

• Vector data streaming
• Raster data streaming
• Real-time visualization
• Web service integration
• Machine learning on streams

8. Monitoring and Observability

• Stream monitoring and metrics
• Performance tracking
• Error detection and alerting
• Debugging and troubleshooting
• Health check implementation

9. Use Case Applications

• Real-time vehicle tracking
• Environmental sensor monitoring
• Social media geolocation
• Emergency response systems
• Smart city applications

10. Testing and Quality Assurance

• Stream testing strategies
• Load testing and benchmarking
• Fault injection testing
• Integration testing
• Performance validation

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This guide will provide detailed information on implementing streaming and real-time data processing capabilities in PyMapGIS.