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TITB
2016

Efficient Execution Methods of Pivoting for Bulk Extraction of Entity-Attribute-Value-Modeled Data

8 years 7 months ago
Efficient Execution Methods of Pivoting for Bulk Extraction of Entity-Attribute-Value-Modeled Data
—Entity-Attribute-Value (EAV) tables are widely used to store data in electronic medical records and clinical study data management systems. Before they can be used by various analytical (e.g., data mining and machine learning) programs, EAV-modeled data usually must be transformed into conventional relational table format through pivot operations. This time-consuming and resource-intensive process is often performed repeatedly on a regular basis, e.g., to provide a daily refresh of the content in a clinical data warehouse. Thus, it would be beneficial to make pivot operations as efficient as possible. In this paper, we present three techniques for improving the efficiency of pivot operations: (1) filtering out EAV tuples related to unneeded clinical parameters early on, (2) supporting pivoting across multiple EAV tables, and (3) conducting multi-query optimization. We demonstrate the effectiveness of our techniques through implementation. We show that our optimized execution method ...
Gang Luo, Lewis J. Frey
Added 11 Apr 2016
Updated 11 Apr 2016
Type Journal
Year 2016
Where TITB
Authors Gang Luo, Lewis J. Frey
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