Campus Units

Electrical and Computer Engineering, Computer Science

Document Type

Article

Publication Version

Submitted Manuscript

Publication Date

2019

Journal or Book Title

arXiv

Abstract

Random sampling has been widely used in approximate query processing on large databases, due to its potential to significantly reduce resource usage and response times, at the cost of a small approximation error. We consider random sampling for answering the ubiquitous class of group-by queries, which first group data according to one or more attributes, and then aggregate within each group after filtering through a predicate. The challenge with group-by queries is that a sampling method cannot focus on optimizing the quality of a single answer (e.g. the mean of selected data), but must simultaneously optimize the quality of a set of answers (one per group).
We present CVOPT, a query- and data-driven sampling framework for a set of group-by queries. To evaluate the quality of a sample, CVOPT defines a metric based on the norm (e.g. ℓ2 or ℓ∞) of the coefficients of variation (CVs) of different answers, and constructs a stratified sample that provably optimizes the metric. CVOPT can handle group-by queries on data where groups have vastly different statistical characteristics, such as frequencies, means, or variances. CVOPT jointly optimizes for multiple aggregations and multiple group-by clauses, and provides a way to prioritize specific groups or aggregates. It can be tuned to cases when partial information about a query workload is known, such as a data warehouse where queries are scheduled to run periodically.
Our experimental results show that CVOPT outperforms current state-of-the-art on sample quality and estimation accuracy for group-by queries. On a set of queries on two real-world data sets, CVOPT yields relative errors that are 5x smaller than competing approaches, under the same space budget.

Comments

This is a pre-print of the article Nguyen, Trong Duc, Ming-Hung Shih, Sai Sree Parvathaneni, Bojian Xu, Divesh Srivastava, and Srikanta Tirthapura. "Random Sampling for Group-By Queries." arXiv preprint arXiv:1909.02629 (2019). Posted with permission.

Copyright Owner

The Authors

Language

en

File Format

application/pdf

Published Version

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