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Sinopsis
In the present scenario, Hadoop is just like the kernel for big data, having distributed storage and compute capabilities to handle structured/semi-structured/unstructured data. Hadoop framework is also utilized for data warehousing and in the field of data science, which makes new informative discoveries about data. In this book two advanced algorithm named as K-Means Clustering and Frequent Item sets mining are applied on Hadoop MapReduce environment, which presents them in a problem/solution format. Predictive analysis of the output is done with the help of Tableau. Each problem is explored step by step, which automatically helps the reader in growing more comfortable with Hadoop in the world of big data. This hand book helps the reader to demonstrate how the real world data is handled using hadoop framework. It also helps readers in understanding the basic concepts of MapReduce and Hadoop Distributed File System (HDFS).
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Reseña del editor
In the present scenario, Hadoop is just like the kernel for big data, having distributed storage and compute capabilities to handle structured/semi-structured/unstructured data. Hadoop framework is also utilized for data warehousing and in the field of data science, which makes new informative discoveries about data. In this book two advanced algorithm named as K-Means Clustering and Frequent Item sets mining are applied on Hadoop MapReduce environment, which presents them in a problem/solution format. Predictive analysis of the output is done with the help of Tableau. Each problem is explored step by step, which automatically helps the reader in growing more comfortable with Hadoop in the world of big data. This hand book helps the reader to demonstrate how the real world data is handled using hadoop framework. It also helps readers in understanding the basic concepts of MapReduce and Hadoop Distributed File System (HDFS).
Biografía del autor
The Authors of this book have been actively involved in the research field of Big Data Analytics. They have published various books and papers in international refereed journals and prestigious conferences. Presently, they are working on “Hybrid Approach of Frequent Item-sets Mining and K-Means Clustering" with integration of encryption algorithm.
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- EditorialLAP LAMBERT Academic Publishing
- Año de publicación2016
- ISBN 10 3659906247
- ISBN 13 9783659906244
- EncuadernaciónTapa blanda
- IdiomaInglés
- Número de páginas84
- Contacto del fabricanteno disponible
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Knowledge Discovery Using Big Data Analytics
Publicado por
LAP LAMBERT Academic Publishing Jun 2016, 2016
ISBN 10: 3659906247
ISBN 13: 9783659906244
Nuevo
Taschenbuch
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In the present scenario, Hadoop is just like the kernel for big data, having distributed storage and compute capabilities to handle structured/semi-structured/unstructured data. Hadoop framework is also utilized for data warehousing and in the field of data science, which makes new informative discoveries about data. In this book two advanced algorithm named as K-Means Clustering and Frequent Item sets mining are applied on Hadoop MapReduce environment, which presents them in a problem/solution format. Predictive analysis of the output is done with the help of Tableau. Each problem is explored step by step, which automatically helps the reader in growing more comfortable with Hadoop in the world of big data. This hand book helps the reader to demonstrate how the real world data is handled using hadoop framework. It also helps readers in understanding the basic concepts of MapReduce and Hadoop Distributed File System (HDFS). 84 pp. Englisch. Nº de ref. del artículo: 9783659906244
Cantidad disponible: 2 disponibles
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Knowledge Discovery Using Big Data Analytics : With Practical Approach on Hadoop
Publicado por
LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659906247
ISBN 13: 9783659906244
Nuevo
Taschenbuch
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In the present scenario, Hadoop is just like the kernel for big data, having distributed storage and compute capabilities to handle structured/semi-structured/unstructured data. Hadoop framework is also utilized for data warehousing and in the field of data science, which makes new informative discoveries about data. In this book two advanced algorithm named as K-Means Clustering and Frequent Item sets mining are applied on Hadoop MapReduce environment, which presents them in a problem/solution format. Predictive analysis of the output is done with the help of Tableau. Each problem is explored step by step, which automatically helps the reader in growing more comfortable with Hadoop in the world of big data. This hand book helps the reader to demonstrate how the real world data is handled using hadoop framework. It also helps readers in understanding the basic concepts of MapReduce and Hadoop Distributed File System (HDFS). Nº de ref. del artículo: 9783659906244
Cantidad disponible: 1 disponibles
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Knowledge Discovery Using Big Data Analytics
Publicado por
LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659906247
ISBN 13: 9783659906244
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Tapa blanda
Librería: moluna, Greven, Alemania
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Agarwal RuchiThe Authors of this book have been actively involved in the research field of Big Data Analytics. They have published various books and papers in international refereed journals and prestigious conferences. Presently, th. Nº de ref. del artículo: 159147409
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Knowledge Discovery Using Big Data Analytics: With Practical Approach on Hadoop
Publicado por
LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659906247
ISBN 13: 9783659906244
Nuevo
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Librería: Revaluation Books, Exeter, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: Brand New. 84 pages. 8.66x5.91x0.19 inches. In Stock. Nº de ref. del artículo: 3659906247
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