Logo
Munich Personal RePEc Archive

Big Data et Technologies de Stockage et de Traitement des Données Massives : Comprendre les bases de l’écosystème HADOOP (HDFS, MAPREDUCE, YARN, HIVE, HBASE, KAFKA et SPARK)

Keita, Moussa (2021): Big Data et Technologies de Stockage et de Traitement des Données Massives : Comprendre les bases de l’écosystème HADOOP (HDFS, MAPREDUCE, YARN, HIVE, HBASE, KAFKA et SPARK).

[img]
Preview
PDF
MPRA_paper_110334.pdf

Download (3MB) | Preview

Abstract

Over the past decade, many technological solutions have been designed to meet the multiple challenges of Big Data, namely the problematic of storing and processing huge volumes of data generated at continuous pace. Two major concepts are at the heart of the solutions designed to meet the challenges: storage in distributed architecture and parallelized processing. HADOOP is one of the first frameworks that implemented this approach. In this document, we provide a general overview of the HADOOP framework, its main functionalities as well as some technological layers that form its ecosystem. First, we present the basic components of HADOOP technology: HDFS, MAPREDUCE and YARN. And secondly, we present some tools that allow exploiting data stored in HADOOP environment. Especially, we present HIVE a query engine, HBASE a distributed database, KAFKA a tool of ingestion and integration of streams of data and SPARK a parallelized data processing engine.

Atom RSS 1.0 RSS 2.0

Contact us: mpra@ub.uni-muenchen.de

This repository has been built using EPrints software.

MPRA is a RePEc service hosted by Logo of the University Library LMU Munich.