Graph division method and device and computer readable storage medium

Abstract

The invention discloses a graph division method and device and a computer readable storage medium. The method comprises the following steps: determining a graph division rule for proportionally distributing graph data to each computing node in advance according to the computing performance of each computing node of the parallel computing system and a preset measurement mechanism; in a graph division process, determining a data reading range of each loading thread according to a graph vertex number and a loading thread number, simultaneously calling a plurality of loading threads to read graphdata to be divided in parallel by taking a vertex as a unit, and transmitting the graph vertex data read by each loading thread to a corresponding division thread. Each division thread determines a sub-graph to which each piece of graph vertex data transmitted into the corresponding thread belongs according to a graph division rule based on the graph data divided at the current moment, and finallydivides each piece of graph vertex data to the corresponding calculation node based on a corresponding relationship between the sub-graph and the calculation node. The large graph can be efficientlyand accurately divided into a series of sub-graphs with the vertex number or the connecting edge number meeting any proportional relation.

Description

technical field [0001] The present application relates to the field of graph computing, in particular to a graph partitioning method, device and computer-readable storage medium. Background technique [0002] With the rapid development of emerging information technologies such as the Internet of Things, mobile Internet, and cloud computing, new applications represented by social networking and e-commerce have been widely used. These applications continue to generate large-scale data, and there are usually complex relationships between data elements. These large-scale and related data can be modeled with graphs. Such data is called graph big data, or big graph for short. For example, as of June 2018, Facebook, the world's largest social platform, has 2 billion users and 1 trillion friend relationships; Page, the largest public Web link graph dataset, contains 3.5 billion web pages and 128 billion hyperlinks. These large images contain huge value. Due to the limited performan...

AI Technical Summary

Problems solved by technology

However, with the advancement of computer hardware technology and asynchronous upgrades, the configuration and performance of computing nodes in parallel computing systems are not necessarily the same, so the above assumptions are not appropriate, so the result of graph division based on this implicit condition is not accurate

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