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Event Streams in Action - Real-time event systems with Kafka and Kinesis (Paperback)
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Event Streams in Action - Real-time event systems with Kafka and Kinesis (Paperback)
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DESCRIPTION Event Streams in Action is a foundational book
introducing the ULP paradigm and presenting techniques to use it
effectively in data-rich environments. The book begins with an
architectural overview, illustrating how ULP addresses the thorny
issues associated with processing data from multiple sources. It
then guides the reader through examples using the unified log
technologies Apache Kafka and Amazon Kinesis and a variety of
stream processing frameworks and analytics databases. Readers learn
to aggregate events from multiple sources, store them in a unified
log, and build data processing applications on the resulting event
streams. As readers progress through the book, they learn how to
validate, filter, enrich, and store event streams, master key
stream processing approaches, and explore important patterns like
the lambda architecture, stream aggregation, and event
re-processing. The book also dives into the methods and tools
usable for event modelling and event analytics, along with scaling,
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. Some Scala
or Python experience is helpful but not required. ABOUT THE
TECHNOLOGY Unified Log Processing is a coherent data processing
architecture that combines batch and near-real time stream data,
event logging and aggregation, and data processing into a unified
event stream. By efficiently creating a single log of events from
multiple data sources, Unified Log Processing makes it possible to
design large-scale data-driven applications that are easier to
design, deploy, and maintain. AUTHOR BIO Alexander Dean is
co-founder and technical lead of Snowplow Analytics, an open source
event processing and analytics platform.
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