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No file available [This article belongs to Volume - 57, Issue - 2]
Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-24-02-2025-818
Title : Feasibility Framework for Approximate Join-Aggregate Query Processing on Big Data using AI
Bala Maruthi Subba Rao Kuppala, , Hussain Vali Buvvaji,

Abstract : Executing Join-Aggregate queries on Big Data can incur enormous computational costs. Hence, the Approximate Aggregate Query Processing Techniques (AQPTs) are an attractive choice to execute such join-aggregate queries, because they incur limited computational costs. The AQPTs utilize random sampling to approximately execute a given join aggregate query. However, the effectiveness of random sampling is highly correlated with the number of qualifying tuples of the given query. If the given query h

Keywords : Feasibility Framework, Approximate Join, Aggregate Query Processing, feasibility, framework