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

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.