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Translating Relational Queries into Spreadsheets

Spreadsheets are among the most commonly used applications for data management and analysis. They combine data processing with very diverse supplementary features: statistics, visualization, reporting, linear programming solvers, Web queries periodically downloading data from external sources, etc....

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Bibliographic Details
Published in:IEEE transactions on knowledge and data engineering 2015-08, Vol.27 (8), p.2291-2303
Main Authors: Sroka, Jacek, Panasiuk, Adrian, Stencel, Krzysztof, Tyszkiewicz, Jerzy
Format: Article
Language:English
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Summary:Spreadsheets are among the most commonly used applications for data management and analysis. They combine data processing with very diverse supplementary features: statistics, visualization, reporting, linear programming solvers, Web queries periodically downloading data from external sources, etc. However, the spreadsheet paradigm of computation still lacks sufficient analysis. In this article, we demonstrate that a spreadsheet can implement all data transformations definable in SQL, merely by utilizing spreadsheet formulas. We provide a query compiler, which translates any given SQL query into a worksheet of the same semantics, including NULL values. Thereby, database operations become available to the users who do not want to migrate to a database. They can define their queries using a high-level language and then get their execution plans in a plain vanilla spreadsheet. The functions available in spreadsheets impose limitations on the algorithms one can implement. In this paper, we offer O(n log 2 n) sorting spreadsheet, using a non-constant number of rows, and, surprisingly, Depth-First-Search and Breadth-First-Search on graphs.
ISSN:1041-4347
1558-2191
DOI:10.1109/TKDE.2015.2397440