Corpus ID: 7801645

Materialized Views Selection in a Multidimensional Database

  title={Materialized Views Selection in a Multidimensional Database},
  author={E. Baralis and S. Paraboschi and Ernest Teniente},
A multidimensional database is a data repository that supports the efficient execution of complex business decision queries. Query response can be significantly improved by storing an appropriate set of materialized views. These views are selected from the multidimensional lattice whose elements represent the solution space of the problem. Several techniques have been proposed in the past to perform the selection of materialized views for databases with a reduced number of dimensions. When the… Expand
Normal forms for multidimensional databases
This paper proposes two multidimensional normal forms that ensure the validity of analytical computations on the multiddimensional database, but also favor an efficient physical database design. Expand
Materialized Views in Multidimensional Databases
This chapter presents materialized views in the context of multidimensional databases (MDDBs) and presents the problems of choosing and maintaining materialised views with the corresponding solutions. Expand
Views for Data Selection in Dataware House
Introduction A data warehouse (DW) is a repository of information retrieved from multiple, possibly heterogeneous, autonomous, distributed database and other information sources for the purpose ofExpand
Evolving Materialized Views in Data
A data warehouse contains multiple views accessed by queries. One of the most important decisions in designing a data warehouse is the selection of materialized views for the purpose of eecientlyExpand
Materialized View Selection in Data Warehousing
  • C. A. Dhote, M. S. Ali
  • Computer Science
  • Fourth International Conference on Information Technology (ITNG'07)
  • 2007
Proposed approach can be used to optimize the views for the better performance of the data warehouse. Expand
Comparing nested GPSJ queries in multidimensional databases
This paper focuses on a relevant class of queries, those modeled by Nested Generalized Projection / Selection / Join (NGPSJ) expressions, in which different aggregation functions may be applied in sequence to the same measure and selections may be formulated, at different granularities, on both dimensions and measures of the cube. Expand
Materialized View Selection for Multidimensional Datasets
This dissertation describes techniques for speeding up Online Analytical Processing or OLAP queries, and presents an empirical study of PBS that demonstrates that PBS picks a surprisingly good set of aggregates even when the conditions do not hold, and proposes algorithms that perform significantly better than previously proposed algorithms for multicube workloads. Expand
On Schema Evolution in Multidimensional Databases
This paper presents a formal framework to describe evolutions of multidimensional schemas and their effects on the schema and on the instances and describes how the algebra enables a tool supported environment for schema evolution. Expand
Selecting materialized views in a data warehouse
This paper addressed and designed algorithm to select a set of views to materialize in order to answer the most queries under the constraint of a given space and shows that the proposed algorithm gives a less complexity and higher speeds and feasible expandability. Expand
Query optimization by using derivability in a data warehouse environment
This article uses materialized summary tables and cached query results to present conditions for derivability in a large number of relevant cases which go beyond previous approaches. Expand


Implementing Data Cubes E ciently
Decision support applications involve complex queries on very large databases. Since response times should be small, query optimization is critical. Users typically view the data as multidimensionalExpand
Implementing data cubes efficiently
This paper investigates the issue of which cells (views) to materialize when it is too expensive to materialized all views, and presents greedy algorithms that work off this lattice and determine a good set of views to materializing. Expand
Storage Estimation for Multidimensional Aggregates in the Presence of Hierarchies
Three strategies for estimating the storage blowup that will result from a proposed set of precomputations without actually computing them are proposed: one based on sampling, onebased on mathematical approximation, and one based upon probabilistic counting. Expand
Index selection for OLAP
The authors give algorithms that automate the selection of summary tables and indexes, and present a family of algorithms of increasing time complexities, and prove strong performance bounds for them. Expand
View maintenance in a warehousing environment
This work introduces a new algorithm, ECA (for "Eager Compensating Algorithm"), that eliminates the anomalies of previous incremental view maintenance algorithms, but extra "compensating" queries are used to eliminate anomalies. Expand
On the Computation of Multidimensional Aggregates
This paper presents fast algorithms for computing a collection of group bys using sort-based and hashbased grouping methods with several .optimizations, like combining common operations across multiple groupbys, caching, and using pre-computed group-by8 for computing other groupbys. Expand
Materialized view maintenance and integrity constraint checking: trading space for time
It is shown that it is possible to reduce the total time cost of view maintenance by materializing (and maintaining) additional views, and it is demonstrated that global optimization cannot, in general, be achieved by locally optimizing each materialized subview. Expand
The Data Warehouse Toolkit: Practical Techniques for Building Dimensional Data Warehouses
This definitive guide succinctly explains how to build a data warehouse by using actual case studies of existing data warehouses developed for specific types of business applications such as retail,Expand
Proc. ACM SIGMOD '96
  • Proc. ACM SIGMOD '96
  • 1996
The Data Warehouse Toolkit
  • The Data Warehouse Toolkit
  • 1996