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Overlay Spreadsheets

Published: 21 July 2023 Publication History

Abstract

Efforts to scale spreadsheets either follow a 'virtual' strategy that layers a spreadsheet interface on top of an existing database engine or a 'materialized' strategy based on re-engineering a spreadsheet engine. Because databases are not optimized for spreadsheet access patterns, the materialized approach has better performance. However, the virtual approach offers several advantages that can not be easily replicated in the materialized approach, including the ability to re-apply user interactions to an updated input dataset. We propose the overlay update model, a hybrid approach that overlays user updates on an existing dataset (as in the virtual approach) and indexes user updates (as in the materialized approach). A key feature of our approach is storing updates generated by bulk operations (e.g., copy/paste) as compact "patterns" that can be leveraged to reduce execution costs. We implement an overlay spreadsheet over Apache Spark and demonstrate that, compared to DataSpread (a materialized spreadsheet), it can significantly reduce execution costs.

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cover image ACM Conferences
HILDA '23: Proceedings of the Workshop on Human-In-the-Loop Data Analytics
June 2023
76 pages
ISBN:9798400702167
DOI:10.1145/3597465
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Publication History

Published: 21 July 2023

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Overall Acceptance Rate 28 of 56 submissions, 50%

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