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by Dean Wampler
Fast Data Architectures for Streaming Applications, 2nd Edition
1. Introduction
A Brief History of Big Data
Batch-Mode Architecture
2. The Emergence of Streaming
Streaming Architecture
What About the Lambda Architecture?
3. Logs and Message Queues
The Log Is the Core Abstraction
Message Queues and Integration
Combining Logs and Queues
The Case for Apache Kafka
Alternatives to Kafka
When Should You Not Use a Log System?
4. How Do You Analyze Infinite Data Sets?
Streaming Semantics
Which Streaming Engines Should You Use?
Criteria for Evaluating Streaming Engines
Spark and Flink: Scalable Data Processing Systems
Akka Streams and Kafka Streams: Data-Centric Microservices
Okay, So What Should I Use?
5. Real-World Systems
Some Specific Recommendations
6. Example Application
Other Machine Learning Considerations
7. Recap and Where to Go from Here
Additional References
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