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IDEBench: A Benchmark for Interactive Data Exploration

Eichmann, Philipp and Zgraggen, Emanuel and Binnig, Carsten and Kraska, Tim (2020):
IDEBench: A Benchmark for Interactive Data Exploration.
In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1555-1569,
ACM, SIGMOD/PODS '20: International Conference on Management of Data, virtual Conference, 14.-19.06, ISBN 9781450367356,
DOI: 10.1145/3318464.3380574,
[Conference or Workshop Item]

Abstract

In recent years, many query processing techniques have been developed to better support interactive data exploration (IDE) of large structured datasets. To evaluate and compare database engines in terms of how well they support such workloads, experimenters have mostly used self-designed evaluation procedures rather than established benchmarks. In this paper we argue that this is due to the fact that the workloads and metrics of popular analytical benchmarks such as TPC-H or TPC-DS were designed for traditional performance reporting scenarios, and do not capture distinctive IDE characteristics. Guided by the findings of several user studies we present a new benchmark called IDEBench, designed to evaluate database engines based on common IDE workflows and metrics that matter to the end-user. We demonstrate the applicability of IDEBench through a number of experiments with five different database engines, and present and discuss our findings.

Item Type: Conference or Workshop Item
Erschienen: 2020
Creators: Eichmann, Philipp and Zgraggen, Emanuel and Binnig, Carsten and Kraska, Tim
Title: IDEBench: A Benchmark for Interactive Data Exploration
Language: English
Abstract:

In recent years, many query processing techniques have been developed to better support interactive data exploration (IDE) of large structured datasets. To evaluate and compare database engines in terms of how well they support such workloads, experimenters have mostly used self-designed evaluation procedures rather than established benchmarks. In this paper we argue that this is due to the fact that the workloads and metrics of popular analytical benchmarks such as TPC-H or TPC-DS were designed for traditional performance reporting scenarios, and do not capture distinctive IDE characteristics. Guided by the findings of several user studies we present a new benchmark called IDEBench, designed to evaluate database engines based on common IDE workflows and metrics that matter to the end-user. We demonstrate the applicability of IDEBench through a number of experiments with five different database engines, and present and discuss our findings.

Title of Book: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data
Publisher: ACM
ISBN: 9781450367356
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Data Management
Event Title: SIGMOD/PODS '20: International Conference on Management of Data
Event Location: virtual Conference
Event Dates: 14.-19.06
Date Deposited: 14 Dec 2020 09:23
DOI: 10.1145/3318464.3380574
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