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Bachelor thesis . 2016
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Bachelor thesis . 2016
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Recolector de Ciencia Abierta, RECOLECTA
Bachelor thesis . 2016
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Hadoop instrumentation

descriptionPublicationkeyboard_double_arrow_right Bachelor thesis 01 Jan 2016 Spain Publisher:Universitat Politècnica de Catalunya
Authors: Montero Rivero, Alejandro;

handle: 2117/82557

Hadoop instrumentation

Abstract

Hadoop es actualmente uno de los principales frameworks para analizar Big Data, uno de sus inconvenientes es la poca cantidad de métricas de rendimiento que se conocen sobre el. El proyecto consiste en crear una herramienta que permita extraer métricas de rendimiento de Hadoop en tiempo de ejecución

Hadoop is one of the most used frameworks to analyse Big Data, though one of it's main disadvantatges is the low number of metrics that are available. This project aims to create a new tool that is able to extract new metrics from Hadoop runtime.

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Spain
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Keywords

Big Data, System, HDFS, Aloja, Macrodades, métricas, Distributed, Big data, Distribuido, :Informàtica [Àrees temàtiques de la UPC], Hadoop, AspectJ, Sistema, MapReduce, Àrees temàtiques de la UPC::Informàtica, rendimiento, AOP, performance

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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