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Informative Article | Data & Knowledge Engineering | India | Volume 8 Issue 1, January 2019 | Rating: 4.9 / 10
Designing Data Schema and Formats for Efficient Storage and Processing within Hadoop
Abstract: Designing and optimizing data schemas and formats is essential for harnessing the full potential of Hadoop, a powerful platform for storage and processing of large - scale data. However, organizations often face difficulties in determining the most suitable configurations that maximize performance, scalability, and compatibility. This paper addresses the challenges in selecting file formats, designing efficient schemas, optimizing storage techniques, enhancing data processing efficiency, and utilizing the appropriate tools and frameworks. Through comprehensive research and analysis, this study aims to provide guidance to organizations seeking to maximize the efficiency of their Hadoop implementations. By addressing these challenges, organizations can achieve efficient storage, faster processing, improved query performance, and enhanced overall performance within the Hadoop ecosystem.
Keywords: Hadoop, data schema, data formats, optimization, performance, scalability, compatibility, file formats, schema design, storage optimization, data processing efficiency, tools and frameworks
Edition: Volume 8 Issue 1, January 2019,
Pages: 2258 - 2261