• Spatial Information Research
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• 제18권1호
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• pp.77-87
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• 2010

Spatio-temporal join operators are essential to the management of spatio-temporal data such as moving objects. For example, the join operators are parts of processing to analyze movement of objects and search similar patterns of moving objects. Various studies on spatio-temporal join queries in outdoor space have been done. Recently with advance of indoor positioning techniques, location based services are required in indoor space as well as outdoor space. Nevertheless there is no one about processing of spatio-temporal join query in indoor space. In this paper, we introduce continuous spatio-temporal self-join queries in indoor space and propose a method of processing of the join queries over stream data of moving objects. The continuous spatio-temporal self-join query is to update the joined result set satisfying spatio-temporal predicates continuously. We assume that positions of moving objects are represented by symbols such as a room or corridor. This paper proposes a data structure, called Candidate Pairs Buffer, to filter and maintain massive stream data efficiently and we also investigate performance of proposed method in experimental study.

• The Transactions of the Korea Information Processing Society
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• 제6권6호
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• pp.1468-1480
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• 1999

In database systems, join operations are the most complex and time consuming ones which limit performance of such system. Many parallel join algorithms have been proposed for the systems. However, they did not consider data skew, such as attribute value skew (AVS) and join product skew (JPS). In the skewness environments, performance of framework for a uniform load distribution and an efficient parallel join algorithm using the framework to handle AVS and JPS. In our algorithm, we estimate data distributions of input and output relations of join operations using the sampling methodology and evaluate join cost for the estimated data distributions. Finally, using the histogram equalization method we distribute data among nodes to achieve good load balancing among nodes in the local joining phase. For performance comparison, we present simulation model of our algorithm and other join algorithms and present the result of some simulation experiments. The results indicate that our algorithm outperforms other algorithms in the skewed case.

• Journal of KIISE:Databases
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• 제32권5호
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• pp.536-546
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• 2005

In this paper, we focus on the filtering step of candidate objects for spatial join operations on the input tables that none of the inputs is indexed. Over the last decade, several spatial Join algorithms for the input tables with index have been extensively studied. Those algorithms show excellent performance over most spatial data, while little research on solving the performance degradation in the presence of skewed data has been attempted. Therefore, we propose a spatial hash strip join(SHSJ) algorithm that can refine the problem of skewed data in the conventional spatial hash Join(SHJ) algorithm. The basic idea is similar to the conventional SHJ algorithm, but the differences are that bucket capacities are not limited while allocating data into buckets and SSSJ algorithm is applied to bucket join operations. Finally, as a result of experiment using Tiger/line data set, the performance of the spatial hash strip join operation was improved over existing SHJ algorithm and SSSJ algorithm.

• Journal of Computing Science and Engineering
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• 제1권2호
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• pp.177-194
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• 2007

Index selection is one of the most important decisions to take in the physical design of relational data warehouses. Indices reduce significantly the cost of processing complex OLAP queries, but require storage cost and induce maintenance overhead. Two main types of indices are available: mono-attribute indices (e.g., B-tree, bitmap, hash, etc.) and multi-attribute indices (join indices, bitmap join indices). To optimize star join queries characterized by joins between a large fact table and multiple dimension tables and selections on dimension tables, bitmap join indices are well adapted. They require less storage cost due to their binary representation. However, selecting these indices is a difficult task due to the exponential number of candidate attributes to be indexed. Most of approaches for index selection follow two main steps: (1) pruning the search space (i.e., reducing the number of candidate attributes) and (2) selecting indices using the pruned search space. In this paper, we first propose a data mining driven approach to prune the search space of bitmap join index selection problem. As opposed to an existing our technique that only uses frequency of attributes in queries as a pruning metric, our technique uses not only frequencies, but also other parameters such as the size of dimension tables involved in the indexing process, size of each dimension tuple, and page size on disk. We then define a greedy algorithm to select bitmap join indices that minimize processing cost and verify storage constraint. Finally, in order to evaluate the efficiency of our approach, we compare it with some existing techniques.

• Journal of KIISE:Databases
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• 제30권6호
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• pp.593-605
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• 2003

Since spatial join processing consumes much time, several algorithms have been proposed to improve spatial join performance. The M-way R-tree join (MRJ) is a join algorithm which synchronously traverses M R-trees in the M-way spatial join. In this paper, we introduce indirect predicates which do not directly come from the multi-way join conditions but are indirectly derived from them. By applying the concept of indirect predicates to MRJ, we improve the performance of MRJ. We call such a multi-way R-tree join algorithm using indirect predicates indirect predicate filtering (IPF). Through experiments using synthetic data and real data, we show that IPF significantly

• Journal of KIISE:Computer Systems and Theory
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• 제30권3_4호
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• pp.117-129
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• 2003

In this paper, we propose advanced parallel join algorithm to efficiently process join operation on hypercube systems. This algorithm uses a broadcasting method in processing relation R which is compatible with hypercube structure. Hence, we can present optimized parallel join algorithm for that hypercube structure. The proposed algorithm has a complete solution of two essential problems - load balancing problem and data skew problem - in parallelization of join operation. In order to solve these problems, we made good use of the characteristics of clustering effect in the algorithm. As a result of this, performance is improved on the whole system than existing algorithms. Moreover. new algorithm has an advantage that can implement non-equijoin operation easily which is difficult to be implemented in hash based algorithm. Finally, according to the cost model analysis. this algorithm showed better performance than existing parallel join algorithms.

• The Pure and Applied Mathematics
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• 제29권1호
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• pp.19-29
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• 2022

Information systems and decision rules with imprecision and uncertainty in data analysis are studied in complete residuated lattices. In this paper, we introduce the notions of Alexandrov pretopology (precotopology) and join-meet (meet-join) operators in complete co-residuated lattices. Moreover, their properties and examples are investigated.

• Journal of Korea Spatial Information System Society
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• 제4권1호
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• pp.39-46
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• 2002

In distributed spatial database systems, users nay issue a query that joins two relations stored at different sites. The sheer volume and complexity of spatial data bring out expensive CPU and I/O costs during the spatial join processing. This paper shows a new spatial join method which joins two spatial relation in a parallel way. Firstly, the initial join operation is divided into two distinct ones by partitioning one of two participating relations based on the region. This two join operations are assigned to each sites and executed simultaneously. Finally, each intermediate result sets from the two join operations are merged to an ultimate result set. This method reduces the number of spatial objects participating in the spatial operations. It also reduces the scope and the number of scanning spatial indices. And it does not materialize the temporary results by implementing the join algebra operators using the iterator. The performance test shows that this join method can lead to efficient use in terms of buffer and disk by narrowing down the joining region and decreasing the number of spatial objects.

• Korean Journal of Mathematics
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• 제22권2호
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• pp.265-277
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• 2014

We investigate the properties of join and meet preserving maps in complete residuated lattices. In particular, we give their examples.

• The Pure and Applied Mathematics
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• 제21권3호
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• pp.183-194
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• 2014

In this paper, we investigate the properties of Alexandrov fuzzy topologies and meet-join approximation operators. We study fuzzy preorder, Alexandrov topologies and meet-join approximation operators induced by Alexandrov fuzzy topologies. We give their examples.