Implementing data cubes efficiently
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Improved query performance with variant indexes
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Cubetree: organization of and bulk incremental updates on the data cube
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
An alternative storage organization for ROLAP aggregate views based on cubetrees
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
Small Materialized Aggregates: A Light Weight Index Structure for Data Warehousing
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
A Query-Driven Approach to the Design and Management of Flexible Database Systems
Journal of Management Information Systems
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Using materialized view to accelerate OLAP queries is one of the most common methods used in ROLAP systems. However, high storage and computation cost make this method very difficult to be implemented in the actual environment. Among various issues associated with this, index selection and view materialization are two of the top challenges. In this paper, we propose to build indexes on subsets of the primary keys rather than the full sets if the index selectivity for these smaller indexes can be maintained above the required level. Based on that we propose an index filtering rule, Dominant Prime (DPrime) Index Set Filter, to filter out candidate indexes that have insufficient index selectivity or have cheaper alternatives. In the second part, we propose a view materialization method, Nested Relation Approach, to group tuples with the same value for index attributes into one super tuple using a nested relation and implement this method using Oracle VARRAY. In performance tests, our method outperforms others significantly.