Complex object-oriented queries generally consist of path expressions and explicit join operations. Since explicit join operations have been acknowledged as the most expensive operations, query executions normally sta...
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Complex object-oriented queries generally consist of path expressions and explicit join operations. Since explicit join operations have been acknowledged as the most expensive operations, query executions normally start from the path expressions, Each path expression may form a sub-query. There are two existing strategies to sub-queries processing: 'serial' and 'parallel' execution scheduling strategies. Serial sub-queries execution corresponds to an execution of the sub-queries one-by-one, whereas parallel sub-queries execution corresponds to simultaneous execution of the sub-queries. When a sub-query is being processed, parallelization techniques may be applied. In this paper, we focus on the scheduling issues of the sub-queries, rather than the parallelization of the sub-queries themselves. Rules are formulated to guide the parallel query execution process. Our analysis shows that when there is no load skew, the serial scheduling strategy is preferred, otherwise the parallel scheduling strategy should be used. (C) 1999 Elsevier Science B.V. All lights reserved.
In this paper, parallelization models for path expressions queries are studied. Path expression queries involve multiple classes along aggregation/association hierarchies. parallelization models for path expression qu...
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In this paper, parallelization models for path expressions queries are studied. Path expression queries involve multiple classes along aggregation/association hierarchies. parallelization models for path expression queries are "inter-objectparallelization" and "inter-class parallelization". Inter-objectparallelization exploits the associativity within complex objects, whereas inter-class parallelization imposes upon process independence. The behaviours of these parallelization models are described in terms of analytical models. Performance evaluation is also performed to confirm the results from the quantitative analysis. (C) 1999 Elsevier Science Inc. All rights reserved.
Skewness has been one of the major problems not only in parallel relational database systems, but also in parallelobject-oriented database systems. To improve performance of object-oriented query processing, a carefu...
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Skewness has been one of the major problems not only in parallel relational database systems, but also in parallelobject-oriented database systems. To improve performance of object-oriented query processing, a careful and intelligent skew handling for load balancing must be established. Depending on the parallel machine environment, whether it is a shared-memory or a shared-nothing architecture, load balancing can be achieved through "physical" or "logical" data re-distribution. It is not the aim of this paper to propose or to investigate skew handling methods, but rather to analyze the impact of load balancing to query execution scheduling strategies. Our analysis shows that when load balancing is achieved, "serial" execution scheduling is preferable to "parallel" execution scheduling strategy. In other words, allocating full resources to a sub-query seems to be better than dividing resources to multiple sub-queries. (C) 2003 Elsevier Inc. All rights reserved.
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