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- Volume 1, Issue 1 2023
By Syed Noorullah Shah
10.20547/aibd.231103
Keywords: Large language model (LLMs), Hallucination, Rouge Metrics, Blue Score
The internet has opened up vast opportunities, connecting people globally and revolutionizing industries. The emergence of internet lead to multiple societal transformations such as the way people interact and perform their daily operations. However, it also presents several challenges of big data. The exponential growth of data generated from various sources requires advanced technologies and analytical tools to effectively process, store, and analyze this massive volume of information. Managing this huge data is crucial for organizations to make data-driven decisions and stay competitive in today’s data-driven world. The challenges posed by massive datasets have led to the development of new technologies and the evolution of several big data processing frameworks. While there are studies related to comparative analysis of prominent big data frameworks like Hadoop, Spark, Storm, etc. Recently some newer big data frameworks have got immense research interests. These big data frameworks are developed by tech giants such as Facebook and Twitter, and have been widely used in the industry. The goal of this research is to fill the knowledge gap by offering a detailed examination and comparison, providing valuable information to the academic and professional community since there may be a lack of comprehensive studies or resources that specifically compare and analyze the performance, features, and limitations of the chosen frameworks. This research can contribute to the existing body of knowledge in the field of big data frameworks. The findings and insights can add to the collective understanding of these frameworks’ strengths, weaknesses, and practical implications, facilitating further research and advancements in the field. Moreover, we present a detailed discussion that can serve as a decision-making guide to selecting the appropriate framework for an application.