Hadoop Application Architectures (e-bog) af Shapira, Gwen
Shapira, Gwen (forfatter)

Hadoop Application Architectures e-bog

273,24 DKK (inkl. moms 341,55 DKK)
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 books se...
E-bog 273,24 DKK
Forfattere Shapira, Gwen (forfatter)
Udgivet 30 juni 2015
Længde 400 sider
Genrer Computer programming / software engineering
Sprog English
Format epub
Beskyttelse LCP
ISBN 9781491900055
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 books second section provides detailed examples of architectures used in some of the most commonly found Hadoop applications. Whether youre 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 dataBest practices for moving data in and out of the systemData processing frameworks, including MapReduce, Spark, and HiveCommon Hadoop processing patterns, such as removing duplicate records and using windowing analyticsGiraph, GraphX, and other tools for large graph processing on HadoopUsing workflow orchestration and scheduling tools such as Apache OozieNear-real-time stream processing with Apache Storm, Apache Spark Streaming, and Apache FlumeArchitecture examples for clickstream analysis, fraud detection, and data warehousing