O'reilly Media Hadoop application architectures: designing real-world big data applications, paperback/mark grover

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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 Map Reduce, Spark, and Hive Common Hadoop processing patterns, such as removing duplicate records and using windowing analytics Giraph, Graph X, 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 About the Author: Mark is a committer on Apache Bigtop and a committer and PMC member on Apache Sentry (incubating) and a contributor to Apache Hadoop, Apache Hive, Apache Sqoop and Apache Flume projects.

He is also a section author of O'Reilly's book on Apache Hive - Programming Hive.

Ted is a Senior Solutions Architect at Cloudera helping clients be successful with Hadoop and the Hadoop ecosystem.

Previously, he was a Lead Architect at the Financial Industry Regulatory Authority (FINRA), helping build out a number of solutions from web applications and Service Oriented Architectures to big data applicatons.

He has also contributed code to Apache Flume, Apache Avr.