Managing and Optimizing Big Data Workloads for On-Demand User Centric Reports

Baicoianu Alexandra; Scheianu Ion Valentin

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Managing and Optimizing Big Data Workloads for On-Demand User Centric Reports

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摘要

The term "big data" refers to the vast amount of structured and unstructured data generated by businesses, organizations, and individuals on a daily basis. The rapid growth of big data has led to the development of new technologies and techniques for storing, processing, and analyzing these data in order to extract valuable information. This study examines some of these technologies, compares their pros and cons, and provides solutions for handling specific types of reporting using big data tools. In addition, this paper discusses some of the challenges associated with big data and suggests approaches that could be used to manage and analyze these data. The findings demonstrate the benefits of efficiently managing the datasets and choosing the appropriate tools, as well as the efficiency of the proposed solution with hands-on examples.

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来源
《Big Data and Cognitive Computing》 |2023年第2期|共18页
作者
Baicoianu Alexandra; Scheianu Ion Valentin;
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作者单位

Transilvania Univ Brasov;

Transilvania Univ Brasov;

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原文格式 PDF
正文语种英语
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关键词
big data; optimization; performance; Druid; terabyte; data skewness; unbalanced dataset; Hadoop; MapReduce; Spark;

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Managing and Optimizing Big Data Workloads for On-Demand User Centric Reports

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