IMPLEMENTING LOW-COST, HIGH-PERFORMANCE CLUSTERS WITH RASPBERRY PI AND APACHE HADOOP: A systematic mapping
DOI:
https://doi.org/10.21728/p2p.2025v11n2e-7277Keywords:
clusters, high performance, parallelism, Raspberry PI, Apache HadoopAbstract
Technological advances have led the computer industry to develop new, faster and more robust computer architectures, called parallel architectures, consisting of computers with multiple processors that collaborate to solve complex problems, exploring different levels of parallelism. An economically viable alternative, used to meet the high demand for data processing, as well as energy costs and the problems caused by the cost of acquiring and maintaining supercomputers, is the use of clusters, formed by groups of homogeneous and/or heterogeneous computers, which work in a distributed and collaborative manner, processing several simultaneous parallel tasks, behaving as a single system. However, to get the most out of a cluster, it is necessary to use a parallelism library, which is responsible for communication and message exchange between the equipment in this system, working simultaneously and distributed in the execution of complex tasks, which is efficient, reliable, scalable and fault tolerant. Furthermore, it is essential to use a hardware platform with high processing power, low acquisition cost and excellent energy efficiency, such as the Raspberry Pi, an SBC (Single Board Computer) platform that has all components integrated on a single board. Given this context, this article aimed to carry out a systematic mapping of studies related to the implementation of clusters, which used the Raspberry Pi as the hardware platform and Apache Hadoop as the parallelism library. The methodology used in this research was quantitative, descriptive and exploratory, aiming at deepening the research topic.
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