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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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Published in: | IEEE transactions on knowledge and data engineering 2015-08, Vol.27 (8), p.2291-2303 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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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. |
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ISSN: | 1041-4347 1558-2191 |
DOI: | 10.1109/TKDE.2015.2397440 |