Big data : covers hadoop 2, mapreduce, hive, YARN, pig, R and data visualization

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Detalles Bibliográficos
Autor Corporativo: DT Editorial Services (Editor )
Formato: Libro
Lenguaje:Español
Inglés
Publicado: Delhi : Dreamtech Press, 2020.
Colección:Black Book
Materias:
Aporte de:Registro referencial: Solicitar el recurso aquí
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245 1 |a Big data :   |b covers hadoop 2, mapreduce, hive, YARN, pig, R and data visualization 
260 |a Delhi :  |b Dreamtech Press,  |c 2020. 
300 |a 972 p. :  |b il., tb. ;  |c 24 cm. 
490 |a Black Book 
500 |a Completamente revisado y actualizado. 
500 |a Nivel intermedio / avanzado. 
505 |a Intruduction. - -Book preview. -- Getting an overview of Big Data. -- Exploring the use of Big Data in business context. -- Introducing technologies for handling Big Data. -- Understanding hadoop ecosystem. -- Understanding mapreduce fundamentals and Hbase. -- Understanding Big Data technology foundations. -- Storing data in databases and data warehouses. -- Processing your data with mapreduce. -- Customizing mapreduce execution and implementing mapreduce program. -- Testing and debugging mapreduce applications. -- Understanding hadoop YARN architecture. -- Exploring hive. -- Analyzing data whit pig. -- Using Oozie. -- NoSQL data management. -- Data movement withflume and Sqoop. -- Intruction to mahout. -- Understanding analytcs and Big Data. -- Analytical approaches and tools to analyze data. -- Exploring R. -- Reading datasets and exporting data form R. -- Manipulating and processing data in R. -- Working with functions and packages in R. -- Performing graphical analysis in R. -- Integrating R and Hadoop and understanding hive. -- Data visualization-I. -- Data visualization with tableau (Data visualization-II). -- Social Media analytics and text mining. -- Mobile analytics. -- Finding a job in the Big Data market. -- Big Data practical. -- Appendix A: Cassandra. -- Appendix B: ZooKeeper. 
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