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Description
Streaming Architecture: New Designs Using Apache Kafka and MapR StreamsMore 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.' webkit tap highlight color: transparent; color: rgb(102, 102, 102); font family: "Open Sans"; font size: 13px; margin top: 0px; margin bottom: 0px; padding: 6px 0px; background color: rgb(255, 255, 255);'Authors Ted
More and more data-driven companies are looking to adopt stream processing and streaming analytics. With this concise ebook, you’ll learn best practices for designing a reliable architecture that supports this emerging big-data paradigm.'-webkit-tap-highlight-color: transparent; color: rgb(102, 102, 102); font-family: "Open Sans"; font-size: 13px; margin-top: 0px; margin-bottom: 0px; padding: 6px 0px; background-color: rgb(255, 255, 255);'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.'-webkit-tap-highlight-color: transparent; color: rgb(102, 102, 102); font-family: "Open Sans"; font-size: 13px; margin-top: 0px; margin-bottom: 0px; padding: 6px 0px; background-color: rgb(255, 255, 255);'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
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