Propuesta de Apache Spark para consultas de grandes cantidades de datos
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Fecha
2022
Autores
Balza Guerrero, Holman
Florez Amaris, Kevin
Mercado Lopez, Leonardo
Mendoza Mendoza, Rony
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Ediciones Universidad Simón Bolívar
Facultad de Ingenierías
Facultad de Ingenierías
Resumen
El siguiente documento consta de una problemática con referencia a la evolución del software de la app y de los programas web que tiene un amplio flujo de datos estos estaban presentando retrasos a la hora de lectura perdida de información entre otras y es donde nace Apache Spark, siendo una de las herramientas BigData con mayor crecimiento y adopción en la actualidad, esta representa una gran oportunidad para las organizaciones de obtener los beneficios del análisis de datos a gran escala. Apache Spark ha emergido recientemente para integrarse y quedarse en el dominio del análisis de datos a gran escala.
The following document consists of a problem with reference to the evolution of the app software and web programs that have a large flow of data, these were presenting delays when reading lost information, among others, and that is where Apache Spark was born. Being one of the Big Data tools with the highest growth and adoption today, it represents a great opportunity for organizations to obtain the benefits of large-scale data analysis. Apache Spark has recently emerged to enter and remain in the domain of large-scale data analysis.
The following document consists of a problem with reference to the evolution of the app software and web programs that have a large flow of data, these were presenting delays when reading lost information, among others, and that is where Apache Spark was born. Being one of the Big Data tools with the highest growth and adoption today, it represents a great opportunity for organizations to obtain the benefits of large-scale data analysis. Apache Spark has recently emerged to enter and remain in the domain of large-scale data analysis.
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Palabras clave
Apache Spark, Big Data, Analítica de datos, MapReduce, Hadoop, Clúster, Apache Spark, Big Data, Data Analytics, MapReduce, Hadoop, Cluster
