Subspace Aggregation Query and Index Generation for Multidimensional Resource Space Model
Xiaoping Sun, Hai Zhuge

TL;DR
This paper introduces a novel index generation method for efficient subspace aggregation queries in multidimensional resource spaces, optimizing resource management and query performance.
Contribution
It proposes a graph index construction approach with strategies to reduce costs and improve query efficiency in multidimensional resource classification.
Findings
The index effectively supports subspace aggregation queries.
Strategies reduce index generation costs and improve query speed.
Experimental results confirm the index's efficiency and effectiveness.
Abstract
Organizing resources in a multidimensional classification space is an approach to efficiently managing and querying large-scale resources. This paper defines an aggregation query on subspace defined by a range on the partial order on coordinate tree at each dimension, where each point contains resources aggregated along the paths of partial order relations on the points so that aggregated resources at each point within the subspace can be measured, ranked and selected. To efficiently locate non-empty points in a large subspace, an approach to generating graph index is proposed to build inclusion links with partial order relations on coordinates of dimensions to enable a subspace query to reach non-empty points by following indexing links and aggregate resources along indexing paths back to their super points. Generating such an index is costly as the number of children of an index node…
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Taxonomy
TopicsGraph Theory and Algorithms · Advanced Database Systems and Queries · Data Management and Algorithms
