Unified Log Processing Integrating and Processing Event Streams

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.