Home // DBKDA 2020, The Twelfth International Conference on Advances in Databases, Knowledge, and Data Applications // View article
Authors:
Wei Hu
Mirco Speretta
Keywords: partitioning; computation; cross join
Abstract:
Experimental studies are based on data that, sometimes, needs to be manually created. Moreover, the data is handled in relational databases to exploit their capabilities of manipulating (i.e., sorting, combining, and inserting) data. In this study, we show how this approach was successful in solving a combinatorics challenge to create a data set used in a separate research study that involves all the possible card combinations of the SET game®. The data required for the study was very extensive. The exact number was unknown, as this is an open combinatorics question, but the estimate was in the order of hundreds of millions. We solved this challenge by using a relational database (i.e., MySQL) as a computational tool to generate the data set. Advanced SQL scripts, based on cross joins, were applied to generate all the data. Table partitioning was also applied to improve the database performance of tables whose number of records exceeded the size capability of the database table. The data set created from this project was then used to support a Web based user interface that collects data to be used in a separate research study based on the SET® game.
Pages: 7 to 12
Copyright: Copyright (c) IARIA, 2020
Publication date: September 27, 2020
Published in: conference
ISSN: 2308-4332
ISBN: 978-1-61208-790-0
Location: Lisbon, Portugal
Dates: from September 27, 2020 to October 1, 2020