Addresses the problem of fragmenting a relation to make the parallel computation of the transitive closure efficient, based on the disconnection set approach. To better understand this design problem, the authors focus on transportation networks. These are characterized by loosely interconnected clusters of nodes with a high internal connectivity rate. Three requirements that have to be fulfilled by a fragmentation are formulated, and three different fragmentation strategies are presented, each emphasizing one of these requirements. Some test results are presented to show the performance of the various fragmentation strategie

Apers, Peter M.G.

Houtsma, M.A.W.

Houtsma, Maurice A.W.

Schipper, Gideon L.V.

English

A topic that is currently inspiring a lot of research is parallel (distributed) computation of transitive closure queries. In [lo] the disconnection set approach has been introduced as an effective strategy for such a computation. It involves reformulating a transitive closure query on a relation into a number of transitive closure queries on smaller fragments; these queries can then execute independently on the fragments, without need for communication and without computing the same tuples at more than one processor. Now that effective strategies as just mentioned have been developed, the next problem is that of developing adequate data fragmentation strategies for these approaches. This is a dificult problem, but of paramount importance to the success of these approaches. We discuss the issues that influence data fragmentation. We present a number of algorithms, each focusing on one of the important issues. We discuss the pros and cons of the algorithms, and we give some results of applying the algorithms to different types of graphs. This last aspect shows to what respect the algorithms indeed conform to the goals we set out

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Data fragmentation for parallel transitive closure strategies

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Data fragmentation for parallel transitive closure strategies

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