A Bounded Incremental Graph Partitioning Method and System

Abstract

The invention discloses a method and system for dividing a bounded incremental graph. The method includes: the coordinator divides the initial graph structure into a plurality of first subgraphs, correspondingly obtains a plurality of first subdivisions, and distributes the first subdivisions to multiple services; The partition is iteratively expanded, and during the iterative expansion process, it is judged whether the first sub-division reaches the preset equilibrium upper bound, and if the first sub-division reaches the preset equilibrium upper bound, the expansion of the first sub-division is stopped; the coordinator Confirm whether there is updated data; if there is updated data, first merge the updated data with the initial graph structure to obtain an updated partial graph structure, and then divide the partial graph structure into multiple second subgraphs, and the corresponding second subgraphs Partition, distribute the second sub-partition to the service, and perform iterative expansion by the service that receives the second sub-partition. The invention can reduce the calculation overhead when the distributed graph is divided, and make the division result more balanced.

Description

technical field [0001] The invention relates to the field of distributed graph division, in particular to a bounded incremental graph division method and system. Background technique [0002] A graph is a network of vertices and edges between vertices. Graph partition (graph partition) is to divide a graph into several subgraphs, so that the sizes of different subgraphs are approximately equal, and the resulting partition cost (cutting edge or point) is minimized as much as possible. Graph partitioning can be divided into: vertex partitioning and edge partitioning according to the partitioning mode. The former divides the node set of the graph; while the latter divides the edge set of the graph. Graph partitioning problems are ubiquitous in various aspects of computer science and technology, such as image segmentation, data clustering, large-scale integrated circuit design and distributed parallel computing systems, etc. On the other hand, many practical problems can also ...

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Problems solved by technology

The second is the communication overhead, that is, the communication between each node through the network will also increase the response time

[0006] Existing graph partitioning methods all have certain shortcomings. For example, for non-incremental point partitioning and edge partitioning, even a small amount of update needs to be completely recalculated, resulting in increased computational overhead; for non-bounded incremental For point division, the division results are unbalanced, and the calculation cost is high when there is a small amount of updates; In terms of the point division of the quantity, it cannot achieve a balanced effect when dividing the graph

That is to say, the above-mentioned distributed graph partitioning methods are more or less unable to meet the two indicators that need to be considered when performing graph partitioning.

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