Less is More: How Fewer Results Improve Progressive Join Query Processing

Zhang, Xin; Eldawy, Ahmed

doi:10.1145/3603719.3603728

35th International Conference on Scientific and Statistical Database Management 2023

DOI: 10.1145/3603719.3603728

|View full text |Cite

Less is More: How Fewer Results Improve Progressive Join Query Processing

Xin Zhang,

Ahmed Eldawy

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

QPJVis Demo: Quality-Boost Progressive Join Query Processing System

Zhang,

Eldawy

2024

Proc. VLDB Endow.

View full text Add to dashboard Cite

Progressive query processing enables data scientists to efficiently analyze and explore large datasets. Data scientists can start further analyses earlier if the progressive result can represent the complete results well. Most progressive processing frameworks carefully control which parts of the input to process in order to improve the quality of progressive results. The input control strategies work well when the data are processed uniformly. However, the progressive results will be biased towards the join keys if the processed data are not uniform. A recently proposed input&output framework named QPJ corrects the bias by temporarily hiding some results. The framework dynamically estimates the distribution of the complete result and outputs progressive results with a similar distribution to the estimated complete result. This demo presents QPJVis, which is a progressive query processing system designed to inherently process the progressive queries using the QPJ framework. Additionally, we also implement an input control framework, Prism, in QPJVis so that users can compare the difference between the input&output framework and a purely input framework.

show abstract

QPJVis Demo: Quality-Boost Progressive Join Query Processing System

Zhang,

Eldawy

2024

Proc. VLDB Endow.

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Less is More: How Fewer Results Improve Progressive Join Query Processing

Cited by 1 publication

References 20 publications

QPJVis Demo: Quality-Boost Progressive Join Query Processing System

QPJVis Demo: Quality-Boost Progressive Join Query Processing System

Contact Info

Product

Resources

About