Por favor, use este identificador para citar o enlazar este ítem:http://uvadoc.uva.es/handle/10324/32896
Título
HDFS File Formats: Study and Performance Comparison
Autor
Director o Tutor
Año del Documento
2018
Titulación
Máster en Investigación en Tecnologías de la Información y las Comunicaciones
Resumen
The distributed system Hadoop has become very popular for storing and process large amounts of data (Big Data). As it is composed of many machines, its file system, called
HDFS (Hadoop Distributed File System), is also distributed. But as HDFS is not a traditional
storage system, plenty of new file formats have been developed, to take advantage
of its features. In this work we study that new formats to find out their characteristics,
and being able to decide which ones can be better knowing the needs of our data. For
that goal, we have made a theoretical framework to compare them, and easily recognize
which formats fit our needs. Also we have made an experimental study to find out how the
formats work in some specific situations, selecting two very different datasets and a set of
simple queries, resolved with MapReduce jobs, written with Java or run using Hive tool.
The final goal of this work is to be able to identify the different strengths and weakenesses
of the file formats.
Palabras Clave
Big Data
Hadoop
HDFS
MapReduce
Departamento
Departamento de Informática (Arquitectura y Tecnología de Computadores, Ciencias de la Computación e Inteligencia Artificial, Lenguajes y Sistemas Informáticos)
Idioma
eng
Derechos
openAccess
Aparece en las colecciones
- Trabajos Fin de Máster UVa [6740]
Ficheros en el ítem
La licencia del ítem se describe como Attribution-NonCommercial-NoDerivatives 4.0 International