Alexander Dean – författare

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.

SummaryEvent Streams in Action is a foundational book introducing the ULP paradigm and presenting techniques to use it effectively in data-rich environments.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the TechnologyMany high-profile applications, like LinkedIn and Netflix, deliver nimble, responsive performance by reacting to user and system events as they occur. In large-scale systems, this requires efficiently monitoring, managing, and reacting to multiple event streams. Tools like Kafka, along with innovative patterns like unified log processing, help create a coherent data processing architecture for event-based applications.About the BookEvent Streams in Action teaches you techniques for aggregating, storing, and processing event streams using the unified log processing pattern. In this hands-on guide, you''ll discover important application designs like the lambda architecture, stream aggregation, and event reprocessing. You''ll also explore scaling, resiliency, advanced stream patterns, and much more! By the time you''re finished, you''ll be designing large-scale data-driven applications that are easier to build, deploy, and maintain.What''s insideValidating and monitoring event streamsEvent analyticsMethods for event modelingExamples using Apache Kafka and Amazon KinesisAbout the ReaderFor readers with experience coding in Java, Scala, or Python.About the AuthorAlexander Dean developed Snowplow, an open source event processing and analytics platform. Valentin Crettaz is an independent IT consultant with 25 years of experience.Table of Contents

PART 1 - EVENT STREAMS AND UNIFIED LOGS

Introducing event streamsThe unified log 24Event stream processing with Apache KafkaEvent stream processing with Amazon KinesisStateful stream processing

PART 2- DATA ENGINEERING WITH STREAMS

SchemasArchiving eventsRailway-oriented processingCommands

PART 3 - EVENT ANALYTICS

Analytics-on-readAnalytics-on-write