In a fuzzy relational database where a relation is a fuzzy set of tuples and ill-known data are represented by possibility distributions, nested fuzzy queries can be expressed in the Fuzzy SQL language. Although it provides a very convenient way for users to express complex queries, a nested fuzzy query may be very inefficient to process with the naive evaluation method based on its semantics. In conventional databases, nested queries are unnested to improve the efficiency of their evaluation. In this paper, we extend the unnesting techniques to process several types of nested fuzzy queries. An extended merge-join is used to evaluate the unnested fuzzy queries. As shown by both theoretical analysis and experimental results, the unnesting techniques with the extended merge-join significantly improve the performance of evaluating nested fuzzy queries.

Presents an efficient algorithm for processing distributed queries with the existence of partition dependencies. For a given query, the algorithm first partitions the referenced relations into a number of non-exclusive subsets such that the join operation(s) associated with the relations in the subset can be locally processed without data transfer. Each subset is associated with a set of processing sites and can be used to generate an execution plan for the given query. Then, the algorithm determines a set of referenced fragmented relations that are not in the subset, such that only the fragments (instead of the whole relation) need to be replicated at the processing sites. The other referenced relations are duplicated at each of the processing sites. Among the alternatives, the algorithm picks the plan that gives the minimum response time for the query. Experimental results show that our algorithm improves the performance of distributed query processing significantly.

Placement dependency is a data allocation constraint in distributed multidatabase systems. It has been shown that this constraint can be used to speed up query processing. However, update operations may violate placement dependency. It is important to support the maintenance of placement dependency in distributed multidatabase systems. We present a method for maintaining placement dependency. We discuss how this method is used to test whether update operations will violate placement dependency and provide general resolutions for update operations that violate placement dependency.

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With recent emphasis placed by data warehouse applications on aggregate queries with vatious grouping criteria, it is natural to expect muhiple aggregate queries on the same set of tables. In this paper, we provide a fmmework for global optimization of aggregate queries under the concept of aggregate query blocks. We propose an extension to SQL to allow users to define explicit query blocks. The paper coveys the integration of the gZobaZ aggregate optimization with the oprimization of individual queries. We present easy-to-implement optimization algolithms applicable to aggregate query blocks. We show that these algorirhms add minimum overhead to the fofai optimization cost, whiie dramatically reducing the overall execution cost.

Article Free Access Share on Performance evaluation of G-tree and its application in fuzzy databases Authors: Chengwen Liu DePaul University, Chicago, Illinois DePaul University, Chicago, IllinoisView Profile , Aris Ouksel University of Illinois at Chicago University of Illinois at ChicagoView Profile , Prasad Sistla University of Illinois at Chicago University of Illinois at ChicagoView Profile , Jing Wu University of Illinois at Chicago University of Illinois at ChicagoView Profile , Clement Yu University of Illinois at Chicago University of Illinois at ChicagoView Profile , Naphtali Rishe Florida International University Florida International UniversityView Profile Authors Info & Claims CIKM '96: Proceedings of the fifth international conference on Information and knowledge managementNovember 1996 Pages 235–242https://doi.org/10.1145/238355.238503Published:12 November 1996Publication History 11citation347DownloadsMetricsTotal Citations11Total Downloads347Last 12 Months6Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

We present an algorithm to make use of placement dependency information to process distributed queries. Our algorithm first partitions the referenced relations of a given query into a number of non-exclusive subsets such that the fragmented relations within a subset have placement dependency and the join operation(s) associated with the relations in the subset can be locally processed without data transfer. Each subset is associated with a set of sites and can be used to generate an execution plan for the given query. It does this by keeping the fragmented relations in the subset fragmented at the sites where they are situated, while replicating the other referenced relations at each of the processing sites. Among the alternatives, our algorithm picks the plan that gives the minimum response time. Our experimental results show that our algorithm improves response time significantly.

We make use of a refined E-R model to represent the contents of pictures. We propose remedies to handle mismatches which may arise due to differences in perception of picture contents. An iconic user interface for visual query construction is presented. A naive user can specify his/her intention without learning a query language. A function which computes the similarity between a picture and a user's description is provided. Pictures which are sufficiently close to the user description, as measured by the similarity function, are retrieved. We present the results of a user-friendliness experiment to evaluate the user interface as well as retrieval effectiveness. Encouraging retrieval results and valuable lessons are obtained.>

Fuzzy databases have been introduced to deal with uncertain or incomplete information in many applications. The efficiency of processing fuzzy queries in fuzzy databases is a major concern. We provide techniques to unnest nested fuzzy queries of two blocks in fuzzy databases. We show both theoretically and experimentally that unnesting improves the performance of nested queries significantly. The results obtained in the paper form the basis for unnesting fuzzy queries of arbitrary blocks in fuzzy databases.>

A new hybrid algorithm is proposed for well-formed path problems including the transitive closure problem. The CPU time for computation is O(ne), and blocking technique is incorporated to reduce the disk I/O cost in disk-resident environment. The new features of the new algorithm are that only parents sets instead of descendant sets are loaded in from disk, and the computation can be parallelized efficiently. Simulation results show that our algorithm is superior to other existing algorithms in sequential computation, and that linear speedup is achieved in parallel computation.>

The authors discuss various performance issues in distributed query processing. They validate and evaluate the performance of the local reduction (LR) the fragment and replicate strategy (FRS) and the partition and replicate strategy (PRS) optimization algorithms. The experimental results reveal that the choices made by these algorithms concerning which local operations should be performed, which relation should remain fragmented or which relation should be partitioned are valid. It is shown using experimental results that various parameters, such as the number of processing sites, partitioning speed relative to join speed, and sizes of the join relations, affect the performance of PRS significantly. It is also shown that the response times of query execution are affected significantly by the degree of site autonomy, interferences among processes, interface with the local database management systems (DBMSs) and communications facilities. Pipeline strategies for processing queries in an environment where relations are fragmented are studied.>

The partition-and-replicate-strategy (PRS) algorithm for distributed query processing is evaluated and its performance is validated. Although in principle PRS is better than single-site processing, early experimental results indicate the contrary. Based on experimental results, the factor which causes performance deterioration is identified and a remedy is provided. As a result, it is shown that the PRS strategy outperforms single-site processing in a realistic environment and that various parameters, such as the number of processing sites, partitioning speed relative to join speed, and sizes of the join relations, affect the performance of the PRS strategy significantly. Among these parameters, the algorithm is most sensitive to the partition speed.>

A technique for compressing large databases is presented. The method replaces frequent variable-length byte strings (words or word fragments) in the database by minimum-redundancy codes—Huffman codes. An essential part of the technique is the construction of the dictionary to yield high compression ratios. A heuristic is used to count frequencies of word fragments. A detailed analysis is provided of our implementaton in support of high compression ratios and efficient encoding and decoding under the constraint of a fixed amount of main memory. In each phase of our implementation, we explain why certain data structures or techniques are employed. Experimental results show that our compression scheme is very effective for compressing large databases of library records. © 1991 John Wiley & Sons, Inc.

Different implementations of an experimental distributed query processing system which is constructed on top of existing database management systems (DBMSs) are presented. A performance evaluation is carried out. It is shown that the response times of query execution are affected significantly by the degree of site autonomy, interferences among processes, interface with the local DBMSs, and communications facilities. Too much autonomy for data replication increases response times. However lack of processing autonomy also increases response times. A goal is to identify the type of autonomy that facilitates query processing. It is shown that pipelining of the actions for data replication, which include local reduction, data transfer, and union fragments, improves performance whereas pipelining between join and data replication causes deterioration in performance because of competition of resources. However, the simulation results indicate that, in a multiprocessor environment, pipelining always improves performance provided that processes which compete for the same resource are assigned to different processors.>