Graph data query task processing method and device, computer equipment and storage medium

Abstract

The invention relates to a graph data query task processing method and device, computer equipment and a storage medium. The method comprises the following steps of: obtaining a graph data set and a graph data query task set, wherein the graph data set is a set of graph data structures stored in a plurality of machine nodes in a distributed manner; identifying a graph data type of the graph data set; depending on graph data types, calculating the similarity or the difference between every two query tasks in the graph data query task set, dividing the graph data query task set into a plurality of graph data query task subsets based on the similarity or the difference between every two query tasks, and inputting the graph data query task subsets into a preset distributed graph query system toobtain corresponding query results. By adopting the scheme, the problem of load balancing when batch tasks are processed in a distributed system is solved, meanwhile, the problems of low efficiency of serial execution of query tasks and low utilization rate of parallel resources are optimized, the execution efficiency of the query tasks is improved, and the real-time requirement of query is relieved.

Description

technical field [0001] The present application relates to the technical field of data processing, in particular to a graph data query task processing method, device, computer equipment and storage medium. Background technique [0002] With the rapid development of Internet technology and electronic informatization, the amount of information in various fields has exploded, and people's demand for data transmission and data processing is also increasing. As a data storage structure, graph (graph) can effectively express all kinds of information. People have higher and higher real-time requirements for many graph-related tasks, such as real-time public opinion detection, product recommendation, etc., based on hard disk computing mode I / The slow speed of O(Input / Output) also affects the user experience. Therefore, it is necessary to use the high-speed I / O characteristics of the memory for optimization, but the memory of a single machine cannot meet the storage requirements of ...

AI Technical Summary

Problems solved by technology

As a data storage structure, graph (graph) can effectively express all kinds of information. People have higher and higher real-time requirements for many graph-related tasks, such as real-time public opinion detection, product recommendation, etc., based on hard disk computing mode I/ Slow O(Input/Output) speed also affects user experience

Therefore, it is necessary to use the high-speed I/O characteristics of the memory for optimization, but the memory of a single machine cannot meet the storage requirements of such large

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