WinMagic: Subquery Elimination Using Window Aggregation
Calisto Zuzarte, Hamid Pirahesh, et al.
SIGMOD 2003
We describe the design and implementation of a new data layout scheme, called multi-dimensional clustering, in DB2 Universal Database Version 8. Many applications, e.g., OLAP and data warehousing, process a table or tables in a database using a multi-dimensional access paradigm. Currently, most database systems can only support organization of a table using a primary clustering index. Secondary indexes are created to access the tables when the primary key index is not applicable. Unfortunately, secondary indexes perform many random I/O accesses against the table for a simple operation such as a range query. Our work in multi-dimensional clustering addresses this important deficiency in database systems. Multi-Dimensional Clustering is based on the definition of one or more orthogonal clustering attributes (or expressions) of a table. The table is organized physically by associating records with similar values for the dimension attributes in a cluster. We describe novel techniques for maintaining this physical layout efficiently and methods of processing database operations that provide significant performance improvements. We show results from experiments using a star-schema database to validate our claims of performance with minimal overhead.
Calisto Zuzarte, Hamid Pirahesh, et al.
SIGMOD 2003
Lipyeow Lim, Bishwaranjan Bhattacharjee
HICSS 2011
Huong Morris, Hui Liao, et al.
ICEBE 2008
Mohammad Sadoghi, Souvik Bhattacherjee, et al.
EDBT 2018