Year: 2024
Type: article
Abstract: Query optimization becomes particularly relevant in big data analytics systems due to the need that is required. Such environments are faced with queries involving joins aggregation and sorting of terabytes or petabytes of data. If we have them in their nonoptimized forms, finishing these queries could take hours or days if the results are required in a real-time or near real-time fashion. Query optimization covers data retrieval processes and eliminates the difficulties of searching for data not required, hence making them faster and charging less computational power. Keywords: Amazon Redshift, Google BigQuery, Query Optimization, Performance, MPP
DOI: 10.55041/ijsrem25253
Author: Rameshbabu Lakshmanasamy
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4405097825