Vector and matrix operations programmed with UDFs in a relational DBMS
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
PIVOT and UNPIVOT: optimization and execution strategies in an RDBMS
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Referential integrity quality metrics
Decision Support Systems
Statistical Model Computation with UDFs
IEEE Transactions on Knowledge and Data Engineering
Horizontal Aggregations in SQL to Prepare Data Sets for Data Mining Analysis
IEEE Transactions on Knowledge and Data Engineering
Can we analyze big data inside a DBMS?
Proceedings of the sixteenth international workshop on Data warehousing and OLAP
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SQL presents limitations to return aggregations as tables with a horizontal layout. A user generally needs to write separate queries and data definition statements to combine transposition with aggregation. With that motivation in mind, we introduce horizontal aggregations, a complementary class of aggregations to traditional (vertical) SQL aggregations. The SQL syntax extension is minimal and it significantly enhances the expressive power and ease of use of SQL. Our proposed SQL extension blurs the boundary between row values and column names. We present a prototype query optimizer that can evaluate arbitrary nested queries combining filtering, joins and both classes of aggregations. Horizontal aggregations have many applications in ad-hoc querying, OLAP cube processing and data mining. We demonstrate query optimization of horizontal aggregations introduces new research challenges.