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DESCRIPTIONEvent Streams in Action is a foundational book introducing the ULPparadigm and presenting techniques to use it effectively in data-richenvironments. The book begins with an architectural overview,illustrating how ULP addresses the thorny issues associated withprocessing data from multiple sources. It then guides the readerthrough examples using the unified log technologies Apache Kafkaand Amazon Kinesis and a variety of stream processing frameworksand analytics databases. Readers learn to aggregate events frommultiple sources, store them in a unified log, and build data processingapplications on the resulting event streams. As readers progressthrough the book, they learn how to validate, filter, enrich, and storeevent streams, master key stream processing approaches, and exploreimportant patterns like the lambda architecture, stream aggregation,and event re-processing. The book also dives into the methods andtools usable for event modelling and event analytics, along withscaling, resiliency, and advanced stream patterns. KEY FEATURES • Building data-driven applications that are easier to design,deploy, and maintain• Uses real-world examples and techniques• Full of figures and diagrams• Hands-on code samples and walkthroughs This book assumes that the reader has written some Java code. SomeScala or Python experience is helpful but not required. ABOUT THE TECHNOLOGYUnified Log Processing is a coherent data processing architecture thatcombines batch and near-real time stream data, event logging andaggregation, and data processing into a unified event stream. By efficientlycreating a single log of events from multiple data sources, Unified LogProcessing makes it possible to design large-scale data-driven applicationsthat are easier to design, deploy, and maintain. AUTHOR BIOAlexander Dean is co-founder and technical lead of Snowplow Analytics,an open source event processing and analytics platform.

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