More and more data-driven companies are looking to adopt stream processing and streaming analytics. With this concise ebook, youll learn best practices for designing a reliable architecture that supports this emerging big-data paradigm.
Authors Ted Dunning and Ellen Friedman (Real World Hadoop) help you explore some of the best technologies to handle stream processing and analytics, with a focus on the upstream queuing or message-passing layer. To illustrate the effectiveness of these technologies, this book also includes specific use cases.
Ideal for developers and non-technical people alike, this book describes:
- Key elements in good design for streaming analytics, focusing on the essential characteristics of the messaging layer
- New messaging technologies, including Apache Kafka and MapR Streams, with links to sample code
- Technology choices for streaming analytics: Apache Spark Streaming, Apache Flink, Apache Storm, and Apache Apex
- How stream-based architectures are helpful to support microservices
- Specific use cases such as fraud detection and geo-distributed data streams