Get expert guidance on architecting end-to-end data management solutions with
Apache Hadoop. While many sources explain how to use various components in the
Hadoop ecosystem, this practical book takes you through architectural
considerations necessary to tie those components together into a complete
tailored application, based on your particular use case.
To reinforce those lessons, the book’s second section provides detailed
examples of architectures used in some of the most commonly found Hadoop
applications. Whether you’re designing a new Hadoop application, or planning
to integrate Hadoop into your existing data infrastructure, Hadoop Application
Architectures will skillfully guide you through the process.
This book covers:
Factors to consider when using Hadoop to store and model data
Best practices for moving data in and out of the system
Data processing frameworks, including MapReduce, Spark, and Hive
Common Hadoop processing patterns, such as removing duplicate records and
using windowing analytics
Giraph, GraphX, and other tools for large graph processing on Hadoop
Using workflow orchestration and scheduling tools such as Apache Oozie
Near-real-time stream processing with Apache Storm, Apache Spark Streaming,
and Apache Flume
Architecture examples for clickstream analysis, fraud detection, and data
warehousing
Також купити книгу Hadoop Application Architectures: Designing Real-World Big
Data Applications, Rajat (Mark) Grover, Ted Malaska, Jonathan Seidman, Gwen
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