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%% values in them; it is your responsibility as an author to replace
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%% the commands and values with those provided to you when you
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%% complete the rights form.
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\setcopyright{none}
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\copyrightyear{2023}
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\acmYear{2023}
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\setcopyright{acmlicensed}\acmConference[HILDA '23]{Workshop on
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Human-In-the-Loop Data Analytics}{June 18, 2023}{Seattle, WA, USA}
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\acmBooktitle{Workshop on Human-In-the-Loop Data Analytics (HILDA '23),
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June 18, 2023, Seattle, WA, USA}
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\acmPrice{15.00}
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\acmDOI{10.1145/3597465.3605220}
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\acmISBN{979-8-4007-0216-7/23/06}
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%\setcopyright{none}
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% \copyrightyear{2018}
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% \acmYear{2018}
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% \acmDOI{XXXXXXX.XXXXXXX}
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% Spreadsheets provide a convenient, friendly direct manipulation interface to datasets.
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Efforts to scale spreadsheets either follow a `virtual` strategy that imposes a spreadsheet interface over an existing database engine or a `materialized' strategy based on re-engineering the spreadsheet engine.
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Because database engines are not optimized for spreadsheet access patterns, the materialized approach has better performance.
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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 dataset.
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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 dataset.
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We propose a hybrid approach, where patterns of user updates are indexed (as in the materialized approach) and overlaid on an existing dataset (as in the virtual approach).
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We introduce the overlay update model, and outline strategies for efficiently accessing an overlay spreadsheet.
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A key feature of our approach is storing updates generated by bulk operations (e.g., copy/paste) as ``patterns" that can be leveraged to reduce execution costs.
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