Achieving scalability in OLAP materialized view selection
Tom Nadeau,Toby J. Teorey +1 more
- 08 Nov 2002
- pp 28-34
TL;DR: The Polynomial Greedy Algorithm functions effectively where existing algorithms fail dramatically, and empirical evidence demonstrates benefits close to existing algorithms.
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Abstract: The goal of on-line analytical processing (OLAP) is to quickly answer queries from large amounts of data residing in a data warehouse. Materialized view selection is an optimization problem encountered in OLAP systems. Published work on the problem of materialized view selection presents solutions scalable in the number of possible views. However, the number of possible views is exponential relative to the number of database dimensions. A truly scalable solution must be polynomial time relative to the number of dimensions. We present such a solution, our Polynomial Greedy Algorithm. Complexity analysis proves scalability, and a performance study verifies the result. Empirical evidence demonstrates benefits close to existing algorithms. We conclude the Polynomial Greedy Algorithm functions effectively where existing algorithms fail dramatically.
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Citations
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Relational database management system having integrated non-relational multi-dimensional data store of aggregated data elements
Reuven Bakalash,Guy Shaked,Joseph Caspi +2 more
- 31 Mar 2009
TL;DR: In this paper, an improved method of and apparatus for joining and aggregating data elements integrated within a relational database management system (RDBMS) using a non-relational multi-dimensional data structure (MDD) is presented.
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Enterprise-wide data-warehouse with integrated data aggregation engine
Reuven Bakalash,Guy Shaked,Joseph Caspi +2 more
- 09 Dec 2002
TL;DR: In this article, an enterprise-wide data-warehouse comprising a database management system (DBMS) including a relational datastore storing data in tables is described, and a query processing mechanism processes query statements, wherein, upon identifying that a given query statement is on the second reference, the query process mechanism communicates with the aggregation module to retrieve portions of aggregated data identified by the reference that are relevant to the given query statements.
173
•Posted Content
Clustering-Based Materialized View Selection in Data Warehouses
TL;DR: In this paper, a framework for materialized view selection that exploits a data mining technique (clustering), in order to determine clusters of similar queries is proposed. But it is based on cost models that evaluate the cost of accessing data using views and the costs of storing these views.
116
Data mining-based materialized view and index selection in data warehouses
Kamel Aouiche,Jérôme Darmont +1 more
- 01 Aug 2009
TL;DR: This paper couple materialized view and index selection to take view–index interactions into account and achieve efficient storage space sharing and results show that this strategy performs better than an independent selection of materialized views and indexes.
•Posted Content
Data Mining-based Materialized View and Index Selection in Data Warehouses
Kamel Aouiche,Jérôme Darmont +1 more
TL;DR: In this article, the authors adopt the opposite stance and couple materialized view and index selection to take view-index interactions into account and achieve efficient storage space sharing, where candidate materialized views and indexes are selected through a data mining process.
91
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289
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