BibTeX
@MISC{Spiegel_tugsynopses,
author = {Joshua Spiegel and Neoklis Polyzotis},
title = {TuG synopses and . . . },
year = {}
}
Share
 |
 |
 |
 |
||
OpenURL
Abstract
This paper introduces the Tuple Graph (TuG) synopses, a new class of data summaries that enable accurate approximate answers for complex relational queries. The proposed summarization framework adopts a “semi-structured” view of the relational database, modeling a relational data set as a graph of tuples and join queries as graph traversals respectively. The key idea is to approximate the structure of the induced data graph in a concise synopsis, and to approximate the answer to a query by performing the corresponding traversal over the summarized graph. We detail the TuG synopsis model that is based on this novel approach, and we describe an efficient and scalable construction algorithm for building accurate TuGs within a specific storage budget. We validate the performance of TuGs with an extensive experimental study on real-life and synthetic data sets. Our results verify the effectiveness of TuGs in generating accurate approximate answers for complex join queries, and demonstrate their benefits over existing summarization techniques.
Keyphrases
tug synopsis summarization technique tuple graph new class concise synopsis summarization framework novel approach join query complex relational query semi-structured view scalable construction algorithm accurate approximate answer accurate tug induced data graph relational database complex join query specific storage budget tug synopsis model key idea relational data set corresponding traversal extensive experimental study enable accurate approximate answer summarized graph synthetic data set data summary graph traversal
