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
