Abstract
Spreadsheets such as Microsoft Excel are OLAP(On-Line Analytical Processing) [2] applications to easily analyze complex multidimensional data. In general, spreadsheets provide grid-like graphical interfaces together with various chart tools [4,5]. However, previous work on OLAP spreadsheets adopts a naive approach that directly retrieves, transmits, and presents all the resulting data at once. Thus, it is difficult to use the previous work for very large relational tables with millions of rows or columns due to the communication and space overhead.
Keywords
- Index Attribute
- Screen Capture
- Space Overhead
- Source Table
- Temporary Array
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References
Agrawal, R., et al.: Storage and Querying of E-Commerce Data. In: Proc. the 27th Int’l Conf. on Very Large Data Base, Roma, Italy, pp. 149–158 (September 2001)
Chaudhuri, S., Dayal, U.: An Overview of Data Warehousing and OLAP Technology. SIGMOD Record 26(1), 65–74 (1997)
Microsoft SQL Server (2005), http://www.microsoft.com/sql/
Raman, V., et al.: Scalable Spreadsheets for Interactive Data Analysis. In: Proc. ACM SIGMOD Workshop on DMKD, Philadelphia (May 1999)
Witkowski, A., et al.: Spreadsheets in RDBMS for OLAP. In: Proc. Int’l Conf. on Management of Data. In: ACM SIGMOD, San Diego, California, pp. 52–63 (June 2003)
Witkowski, A., et al.: Query By Excel. In: Proc. the 31st Int’l Conf. on Very Large Data Bases, Trondheim, Norway, pp. 1204–1215 (September 2005)
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Shin, SH., Choi, HY., Kim, J., Moon, YS., Kim, SW. (2007). An Efficient Sheet Partition Technique for Very Large Relational Tables in OLAP. In: Cooper, R., Kennedy, J. (eds) Data Management. Data, Data Everywhere. BNCOD 2007. Lecture Notes in Computer Science, vol 4587. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73390-4_19
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DOI: https://doi.org/10.1007/978-3-540-73390-4_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73389-8
Online ISBN: 978-3-540-73390-4
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