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.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 layerNew messaging technologies, including Apache Kafka and MapR Streams, with links to sample codeTechnology choices for streaming analytics: Apache Spark Streaming, Apache Flink, Apache Storm, and Apache ApexHow stream-based architectures are helpful to support microservicesSpecific use cases such as fraud detection and geo-distributed data streamsTed Dunning is Chief Applications Architect at MapR Technologies, and active in the open source community. He currently serves as VP for Incubator at the Apache Foundation, as a champion and mentor for a large number of projects, and as committer and PMC member of the Apache ZooKeeper and Drill projects. Ted is on Twitter as @ted_dunning.Ellen Friedman, a committer for the Apache Drill and Apache Mahout projects, is a solutions consultant and well-known speaker and author, currently writing mainly about big data topics. With a PhD in Biochemistry, she has years of experience as a research scientist and has written about a variety of technical topics. Ellen is on Twitter as @Ellen_Friedman.
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.Authors Ted Dunning...
評分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.Authors Ted Dunning...
評分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.Authors Ted Dunning...
評分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.Authors Ted Dunning...
評分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.Authors Ted Dunning...
又瞭解瞭一個MapR框架,kafka的用的估計比較多
评分又瞭解瞭一個MapR框架,kafka的用的估計比較多
评分又瞭解瞭一個MapR框架,kafka的用的估計比較多
评分cloud
评分又瞭解瞭一個MapR框架,kafka的用的估計比較多
本站所有內容均為互聯網搜索引擎提供的公開搜索信息,本站不存儲任何數據與內容,任何內容與數據均與本站無關,如有需要請聯繫相關搜索引擎包括但不限於百度,google,bing,sogou 等
© 2025 qciss.net All Rights Reserved. 小哈圖書下載中心 版权所有