Towards Online Aggregation for SPJ Queries

MPhil Thesis Defence


Title: "Towards Online Aggregation for SPJ Queries"

By

Mr. Yuan QIU


Abstract

Select-Project-Join (SPJ) Queries are essential building blocks of general 
queries. Efficiently estimating their output sizes critically affects the 
effectiveness of Cost-Based Optimizers (CBOs) in generating optimal query 
plans. Despite a rich literature in selection and join size estimation 
techniques, estimating the result size of a distinct projection remains an 
open problem when arbitrary filter and join conditions are present. In 
this thesis, we provide an efficient online aggregation algorithm for 
accurately estimating the result size of SPJ queries, equivalently the 
distinct count. By continuously sampling paths from the join, our 
algorithm quickly converges to the exact value. Comprehensive experiments 
are conducted to prove the new algorithm outperforms existing ones by 
orders of magnitudes.


Date:			Tuesday, 27 August 2019

Time:			3:00pm - 5:00pm

Venue:			Room 3494
 			Lifts 25/26

Committee Members:	Prof. Ke Yi (Supervisor)
 			Dr. Qiong Luo (Chairperson)
 			Dr. Kai Chen


**** ALL are Welcome ****