Journal of Information Processing
Online ISSN : 1882-6652
ISSN-L : 1882-6652
Let High-level Graph Queries Be Parallel Efficient: An Approach Over Structural Recursion On Pregel
Chong LiLe-Duc TungXiaodong MengZhenjiang Hu
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2016 Volume 24 Issue 6 Pages 928-936

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Abstract

Graphs play an important role today in managing big data. Supporting declarative graph queries is one of the most crucial parts for efficiently manipulating graph databases. Structural recursion has been studied for graph querying and graph transformations. However, most of the previous studies about graph structural recursion do not exploit in practical the power of parallel computing. The bulk semantics, which is used for parallel evaluation of structural recursion, still impose many constraints that limit the performance of querying in parallel. In this paper, we propose a framework that systematically generates structural recursive functions from high-level declarative graph queries, then the generated functions are evaluated efficiently on our framework on top of the Pregel model. Therefore, the complexity in developing efficient structural recursive functions is relaxed by our solution.

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© 2016 by the Information Processing Society of Japan
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