Pro Hadoop Data Analytics
Designing and Building Big Data Systems using the Hadoop Ecosystem
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Beschreibung
Learn advanced analytical techniques and leverage existing toolkits to make your analytic applications more powerful, precise, and efficient. This book provides the right combination of architecture, design, and implementation information to create analytical systems which go beyond the basics of classification, clustering, and recommendation.In Pro Hadoop Data Analytics best practices are emphasized to ensure coherent, efficient development. A complete example system will be developed using standard third-party components which will consist of the toolkits, libraries, visualization and reporting code, as well as support glue to provide a working and extensible end-to-end system.The book emphasizes four important topics:The importance of end-to-end, flexible, configurable, high-performance data pipeline systems with analytical components as well as appropriate visualization results. Deep-dive topics will include Spark, H20,Vopal Wabbit (NLP), Stanford NLP, and other appropriate toolkits and plugins.Best practices and structured design principles. This will include strategic topics as well as the how to example portions.The importance of mix-and-match or hybrid systems, using different analytical components in one application to accomplish application goals. The hybrid approach will be prominent in the examples.Use of existing third-party libraries is key to effective development. Deep dive examples of the functionality of some of these toolkits will be showcased as you develop the example system.
Learn advanced analytical techniques and leverage existing tool kits to make your analytic applications more powerful, precise, and efficient. This book provides the right combination of architecture, design, and implementation information to create analytical systems that go beyond the basics of classification, clustering, and recommendation.
Pro Hadoop Data Analytics emphasizes best practices to ensure coherent, efficient development. A complete example system will be developed using standard third-party components that consist of the tool kits, libraries, visualization and reporting code, as well as support glue to provide a working and extensible end-to-end system.
The book also highlights the importance of end-to-end, flexible, configurable, high-performance data pipeline systems with analytical components as well as appropriate visualization results. You'll discover the importance of mix-and-match or hybrid systems, using different analytical components in one application. This hybrid approach will be prominent in the examples.
What You'll Learn
- Build big data analytic systems with the Hadoop ecosystem
- Use libraries, tool kits, and algorithms to make development easier and more effective
- Apply metrics to measure performance and efficiency of components and systems
- Connect to standard relational databases, noSQL data sources, and more
- Follow case studies with example components to create your own systems
Software engineers, architects, and data scientists with an interest in the design and implementation of big data analytical systems using Hadoop, the Hadoop ecosystem, and other associated technologies.
Provides useful code examples of real-world situations and solutions to common problems Provides an end-to-end example solution which can be expanded upon by the reader Gives extensive case studies and application examples from a variety of domains and problem areas
Autor*in
Kerry Koitzsch
Themen in »Pro Hadoop Data Analytics«
Analytics Data Analytics Hadoop Scala Python Maven OpenCV Apache Mahout NoSQL Ralational Database Lucene Solr Architecture Algorithms Data Visualisation