Browsing by Author "Asgharzadeh Talebi, Zohreh"

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    Exact and Heuristic Methods for solving the View-Selection Problem for Aggregate Queries
    (2006-06-12) Asgharzadeh Talebi, Zohreh; Dr. Matt Stallmann, Committee Member; Dr. Yahya Fathi, Committee Co-Chair; Dr. Rada Chirkova, Committee Co-Chair
    In this thesis we present a formal study of the following view-selection problem: Given a set of queries, a database, and an upper bound on the amount of disk space that can be used to store materialized views, return definitions of views that, when materialized in the database, would reduce the evaluation costs of the queries. Optimizing the layout of stored data using view selection has a direct impact on the performance of the entire database system. At the same time, the optimization problem is intractable, even under natural restrictions on the types of queries of interest. We introduce an integer-programming model to obtain optimal solutions for the view-selection problem for aggregate queries on data warehouses. Through a computational experiment we show that this model can be used to solve realistic-size instances of the problem. We also report the results of the post-optimality analysis that we performed to determine the impact of changing certain input characteristics on the optimal solution. We solve large instances by applying several methods of reducing the size of the search space. We compare our approach to the leading heuristic procedure in the field [20].
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    Exact and Inexact Methods for Selecting Views and Indexes for OLAP Performance Improvement
    (2010-04-28) Asgharzadeh Talebi, Zohreh; Dr. Matthias Stallmann, Committee Member; Dr. Carla Savage, Committee Member; Dr. Rada Chirkova, Committee Co-Chair; Dr. Yahya Fathi, Committee Co-Chair
    In on-line analytical processing (OLAP), precomputing (materializing as views) and indexing auxiliary data aggregations is a common way of reducing query-evaluation time (cost) for important data-analysis queries. We consider an OLAP view- and index-selection problem as an optimization problem, where (i) the input includes the data-warehouse schema, a set of data-analysis queries of interest, and a storage-limit constraint, and (ii) the output is a set of views and indexes that minimizes the total cost of evaluating the input queries, subject to the storage limit. While greedy and other heuristic strategies for choosing views or indexes might have some success in reducing the cost, it is highly nontrivial to arrive at a globally optimal solution, one that reduces the processing cost of typical OLAP queries as much as is theoretically possible. In this dissertation we present a systematic study of the OLAP view- and indexselection problem. Our specific contributions are: (1) we introduce an integer programming model for OLAP view- and index-selection problem; (2) we develop an algorithm that effectively and efficiently prunes the space of potentially beneficial views and indexes of the problem, and provide formal proofs that our pruning algorithm keeps at least one globally optimal solution in the search space, thus the resulting integer-programming model is guaranteed to find an optimal solution; this allows us to solve realistic-size instances of the problem within reasonable execution time. (3) we develop a family of algorithms to further reduce the size of the search space so that we are able to solve larger instances of the problem, although we no longer guarantee global optimality of the resulting solution; and (4) we present an experimental comparison of our proposed approach with other approaches discussed in the open literature. Our experiments show that our proposed approach to view and index selection results in high-quality solutions — in fact, in the global optimal solutions for many realistic-size problem instances. Thus, it compares favorably with the well-known OLAP-centered approach of [13] and provides for a winning combination with the end-toend framework of [2] for generic view and index selection.
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    Exact and inexact methods for selecting views and indexes for OLAP performance improvement.
    (North Carolina State University. Dept. of Computer Science, 2007) Asgharzadeh Talebi, Zohreh; Chirkova, Rada Y.; Fathi, Yahya; Stallmann, Matthias F.
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    Exact and inexact methods for solving the problem Of view selection for aggregate queries
    (North Carolina State University. Dept. of Computer Science, 2007) Asgharzadeh Talebi, Zohreh; Chirkova, Rada Y.; Fathi, Yahya