TY - GEN
T1 - Star/snow-flake schema driven object-relational data warehouse design and query processing strategies
AU - Gopalkrishnan, Vivekanand
AU - Li, Qing
AU - Karlapalem, Kamalakar
PY - 1999/1/1
Y1 - 1999/1/1
N2 - The conventional star schema model of Data Warehouse (DW) has its limitations due to the nature of the relational data model. Firstly, this model cannot represent the semantics and operations of multi-dimensional data adequately. Due to the hidden semantics, it is difficult to efficiently address the problems of view design. Secondly, as we move up to higher levels of summary data (multiple complex aggregations), SQL queries do not portray the intuition needed to facilitate buildingand supporting efficient execution of complex queries on complex data. In light of these issues, we propose the Object- Relational View (ORV) design for DWs. Using Object-Oriented (O-O) methodology, we can explicitly represent the semantics and reuse view (class) definitions based on the ISA hierarchy and the class composition hierarchies, thereby resulting in a more efficient view mechanism. Part of the design involves providing a translation mechanism from the star/snowflake schema to an O-O representation. This is done by flattening the fact-dimension schema and converting it to a class-composition hierarchy in an O-O framework. Vertically partitioning this O-O schema further increases the efficiency of query execution by reducing disk access. We then build a Structural Join Index Hierarchy (SJIH) on this partitioned schema to facilitate complex object retrieval and avoid using a sequence of expensive pointer chasing (or join) operations.
AB - The conventional star schema model of Data Warehouse (DW) has its limitations due to the nature of the relational data model. Firstly, this model cannot represent the semantics and operations of multi-dimensional data adequately. Due to the hidden semantics, it is difficult to efficiently address the problems of view design. Secondly, as we move up to higher levels of summary data (multiple complex aggregations), SQL queries do not portray the intuition needed to facilitate buildingand supporting efficient execution of complex queries on complex data. In light of these issues, we propose the Object- Relational View (ORV) design for DWs. Using Object-Oriented (O-O) methodology, we can explicitly represent the semantics and reuse view (class) definitions based on the ISA hierarchy and the class composition hierarchies, thereby resulting in a more efficient view mechanism. Part of the design involves providing a translation mechanism from the star/snowflake schema to an O-O representation. This is done by flattening the fact-dimension schema and converting it to a class-composition hierarchy in an O-O framework. Vertically partitioning this O-O schema further increases the efficiency of query execution by reducing disk access. We then build a Structural Join Index Hierarchy (SJIH) on this partitioned schema to facilitate complex object retrieval and avoid using a sequence of expensive pointer chasing (or join) operations.
UR - http://www.scopus.com/inward/record.url?scp=0242550665&partnerID=8YFLogxK
U2 - 10.1007/3-540-48298-9_2
DO - 10.1007/3-540-48298-9_2
M3 - Conference article published in proceeding or book
AN - SCOPUS:0242550665
SN - 3540664580
SN - 9783540664581
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 11
EP - 22
BT - Data Warehousing and Knowledge Discovery - 1st International Conference, DaWaK 1999, Proceedings
A2 - Tjoa, A. Min
A2 - Mohania, Mukesh
PB - Springer-Verlag
T2 - 1st International Conference on Data Warehousing and Knowledge Discovery, DaWaK 1999
Y2 - 30 August 1999 through 1 September 1999
ER -