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 layer
- New messaging technologies, including Apache Kafka and MapR Streams,
with links to sample code
- Technology choices for streaming analytics: Apache Spark Streaming,
Apache Flink, Apache Storm, and Apache Apex
- How stream-based architectures are helpful to support microservices
- Specific use cases such as fraud detection and geo-distributed data
streams
Ted 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.
