Context MapReduce is a processing model used in Big Data to facilitate the analysis of large
data under a distributed architecture. Objective The aim of this study is to identify and …

Big Data is reforming many industrial domains by providing decision support through
analyzing large data volumes. Big Data testing aims to ensure that Big Data systems run …

New processing models are being adopted in Big Data engineering to overcome the
limitations of traditional technology. Among them, MapReduce stands out by allowing for the …

MapReduce is a parallel data processing paradigm oriented to process large volumes of
information in data-intensive applications, such as Big Data environments. A characteristic of …

Big Data programs are those that process large data exceeding the capabilities of traditional
technologies. Among newly proposed processing models, MapReduce stands out as it …

Big data has become the primary objective for any area or department on the globe,
including government, healthcare, and industrial sectors. Every day, a large amount of big …

To make sure big data systems are reliable and effective, performance testing is essential. In
light of big data applications, this study offers a comparative review of important performance …

Programs that process a large volume of data generally run in a distributed and parallel
architecture, such as the programs implemented in the processing model MapReduce. In …

Massive datasets are quickly becoming a concern for many industries. For example, many
web-based applications must be able to handle petabytes worth of transactions on a daily …

Among the current technologies to analyse large data, the MapReduce processing model
stands out in Big Data. MapReduce is implemented in frameworks such as Hadoop, Spark …