Index Catalog // ScholarsArchive@OSU

Start Over

Filtering by: Alternative title ssim Circular no. 34 Committee Member Fern, Alan Contributor Termehchy, Arash

Learning to Estimate Multi-Relation Aggregation Functions

Creator:

Jadhav, Rashmi Suresh

Abstract:

Multi-relation aggregation queries process the join operator before computing the aggregation function. This join is arguably the most costly operation since traditional join algorithms spend majority of their time trying to join the parts of the relations that do not generate any output tuples. This causes slow response times with...

Resource Type:

Masters Thesis

Full Text:

. . . . . . . . . . . . . . . . . . 34 6 Conclusion and Future Work . . . . . . . . . . . . . . . . . . . . . . . . . 41 Bibliography
Collaborative Online Learning For Join Processing

Creator:

Xie, Mian

Abstract:

Relational binary operators, such as join, are arguably the most costly and frequently used operations in relational data systems. In many join algorithms, the majority of the process time is spent on scanning and attempting to join the parts of the relations that do not satisfy the join condition and...

Resource Type:

Capstone Project

Full Text:

. . . . . . . . . . . . . . . . . . . . . . . 34 5.2.3 Full Join Evaluation . . . . . . . . . . . . . . . . . . . . . . 38 6 Conclusion and Future
Principles of Variational Databases

Creator:

Ataei, Parisa S.

Abstract:

Data variations are prevalent in real-world applications. For example, software vendors have to handle numerous variations in the business requirements, conventions, and environmental settings of a software product. In database-backed software, the database of each version may have a different schema and content. As another example, data scientists often need...

Resource Type:

Masters Thesis

Full Text:

stronger than what I can even imagine. And finally, at last but by no means least, my very special