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  4. Aggregation and Exploration of High-Dimensional Data Using the Sudokube Data Cube Engine
 
conference paper

Aggregation and Exploration of High-Dimensional Data Using the Sudokube Data Cube Engine

Basil John, Sachin  
•
Lindner, Peter  
•
Jiang, Zhekai
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2023
Companion of the 2023 International Conference on Management of Data
2023 ACM SIGMOD/PODS Conference

We present Sudokube, a novel system that supports interactive speed querying on high-dimensional data using partially materialized data cubes. Given a storage budget, it judiciously chooses what projections to precompute and materialize during cube construction time. Then, at query time, it uses whatever information is available from the materialized projections and extrapolates missing information to approximate query results. Thus, Sudokube avoids costly projections at query time while also avoiding the astronomical compute and storage requirements needed for fully materialized high-dimensional data cubes. In this paper, we show the capabilities of the Sudokube system and how it approximates query results using different techniques and materialization strategies.

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sudokube-demo.pdf

Type

Preprint

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Submitted version (Preprint)

Access type

openaccess

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CC BY-NC-ND

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521.52 KB

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Adobe PDF

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8d659cd241737499963ebfae47e7f02f

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