Efficient query processing is a critical requirement for data warehousing systems as decision support applications often require minimum response times to answer complex, ad-hoc queries having aggregations, multi-ways joins over vast repositories of data. This can be achieved by fragmenting warehouse data. The data fragmentation concept in the context of distributed databases aims to reduce query execution time and facilitates the parallel execution of queries. In this paper, we propose a methodology for applying the fragmentation technique in a Data Warehouse (DW) star schema to reduce the total query execution cost. We present an algorithm for fragmenting the tables of a star schema. During the fragmentation process, we observe that the choice of the dimension tables used in fragmenting the fact table plays an important role on overall performance. Therefore, we develop a greedy algorithm in selecting "best" dimension tables. We propose an analytical cost model for executing a set of OLAP queries on a fragmented star schema. Finally, we conduct some experiments to evaluate the utility of fragmentation for efficiently executing OLAP queries. Key Words : Data Warehouses, Star schema, Fragmentation, Query Optimization, Performance Evaluation 1

The changes in the distributed database environment during its lifetime necessitate a redesign of the distributed databases so as to keep the performance of the applications/transactions from degrading. Till now most of the work in distributed database design dealt with developing better fragmentation and allocation algorithms. This paper introduces an hitherto unexplored step in distributed database design dealing with the materialization of a new design after the redesign for an existing populated distributed relational database. We define materialization of a distributed database design as a process of global restructuring of the populated local databases in order to achieve conformance with the logical definition of the distributed database. Work on distributed database design dealing with mixed fragmentation facilitates the development of a formal basis for materializing distributed database designs. We present two approaches (Query Generator method and Operator method) to achieve...

Horizontal partitioning is a technique for reducing the number of disk accesses to execute a query by minimizing the number of irrelevant instances accessed. In this paper, we develop a cost model for query execution in the case of unpartitioned and horizontally partitioned classes. We present three algorithms to perform horizontal partitioning in OODBSs, namely: Cost-Driven Algorithm(CDA), Predicate Affinity Algorithm (PAA) and Approximate Algorithm. CDA is based on the cost model, that aims to reduce the number of disk accesses for executing a set of queries, and PAA is an extension of the graph theoretic algorithm for a relational model to an OODB model. The Approximate algorithm takes the advantages of both PAA and CDA to facilitate efficient and good horizontal fragmentation scheme design for object-oriented databases. We also evaluate the goodness of horizontal class fragmentation through experiments using an analytical cost model. Finally, horizontal class partitioning could als...

An application processing center consists of a set of well-defined, well-designed and well-tested applications that are dynamically executed over a period of time. We assume that there is a set of candidate distributed database designs each of which is optimal for some applications. The random execution of applications on a distributed database design is modeled as a discrete Markov process, and the problem of selecting the candidate design for each execution of an application is solved by using sequential Markovian decision process analysis to generate an optimal redesign policy vector. The scope of the methodology developed in this paper is applicable to environments similar to application processing centers. The viability of this methodology is illustrated by means of a case study conducted at Georgia Tech. 1 Introduction Relational database system technology has been under development for more than two decades. There are many efficient commercial relational database systems in exi...

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butes, security levels, and the page size, were varied for a Selection and Join query. We were particularly interested in the relationship between performance degradation and changes in the quantity of these properties. The performance of each scheme was measured in terms of its response time. The response times for the element level fragmentation scheme increased as the numbers of tuples, attributes, security levels, and the page size were increased, more significantly so than when the number of tuples and attributes were increased. The response times for the attribute level fragmentation scheme was the fastest, suggesting that the performance of the attribute level scheme is superior to the tuple and element level fragmentation schemes. In the context of assurance, this research has also shown that the distribution of fragments based on security level is a more natural approach to implementing security in MLS/DBMS systems, because a multilevel database is analogous to a

Query processing remains one of the most important challenges of object oriented database systems (OODBSs). A cost model for query processing is very useful in performing the physical query optimization. Horizontal class partitioning (HCP) is a technique for reducing the number of disk accesses for executing a given set of queries by minimizing the number of irrelevant object instances accessed. Moreover, its importance in reduction of query execution time has been widely acknowledged. However, existing cost models for query processing in OODBSs do not take into consideration the HCP criteria. In this paper, we present an analytical cost model for query execution for unpartitioned and horizontally partitioned classes. This cost is necessary for deciding whether to use HCP or to keep all classes unpartitioned. The effect of HCP upon the query execution process is analyzed. Key Words : Object-oriented database, horizontal class partitioning, cost model, query processing, query optimizat...

Resource migration in a distributed computer system can be performed for performance enhancement and we call this activity "load balancing with resource migration". We propose a general load balancing model with both job and resource migration and demonstrate how this model applies to the file migration problem in distributed databases. The intractability of this load balancing model suggests obtaining approximate solutions. In this paper, we propose an approximation approach that partitions the distributed system into regions so that resource migration takes place between the regions while job migration occurs within the regions. By using a good rule for partitioning the system into regions, good approximate solutions can be obtained. We present theoretical bounds and experimental results to indicate how our approximation approach can provide close to optimal solutions in many instances. List of Symbols d F J ; FR ; c J ; c R V; P (V ); u; v; I; I 0 f; g; h; b x ; q; d xy ffi(:...

Many researchers have demonstrated the importance of entity fragmentation in distributed relational database design. Database design will be essential in the "next-generation" engineering design environment that exploits object-oriented technologies. Fragmentation enhances application performance by reducing the amount of irrelevant data accessed and the amount of data transferred unnecessarily between distributed sites. Algorithms for effecting horizontal and vertical fragmentation of relations exist, but fragmentation techniques for class objects in a distributed object based system have not appeared in the literature. This paper first presents a taxonomy of the fragmentation problem in a distributed object based system capable of supporting systems engineering applications. Detailed horizontal fragmentation algorithms are then presented for one of these class models using a top--down approach where the entity of fragmentation is the class object. The algorithms described i...

The database volumes of enterprise resource planning (ERP) systems like SAP R/3 are growing at a tremendous rate and some of them have already reached a size of several Terabytes. OLTP (Online Transaction Processing) databases of this size are hard to maintain and tend to perform poorly. Therefore most database vendors have implemented new features like horizontal partitioning to optimize such mission critical applications. Horizontal partitioning was already investigated in detail in the context of shared nothing distributed database systems but today's ERP systems mostly use a centralized database with a shared everything architecture. In this work, we therefore investigate how an SAP R/3 system performs when the data in the underlying database is partitioned horizontally.