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Graph data processing method and device, electronic equipment and storage medium

A processing method and graph data technology, applied in the computer field, can solve the problems of large data volume and graph correlation dependence, etc., and achieve the effect of reducing the amount of data calculation and improving the efficiency of data processing

Pending Publication Date: 2020-11-27
南京智慧图谱信息技术有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, due to the correlation dependence of the graph in this method, all the data needs to be included in the recalculated subgraph each time. As time goes by, the amount of calculated data becomes larger and larger, even exceeding the computing power of the online environment.

Method used

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  • Graph data processing method and device, electronic equipment and storage medium
  • Graph data processing method and device, electronic equipment and storage medium
  • Graph data processing method and device, electronic equipment and storage medium

Examples

Experimental program
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Effect test

Embodiment 1

[0031] figure 1 It is a flow chart of a graph data processing method provided in Embodiment 1 of the present invention. This embodiment is applicable to how to process graph data, especially how to efficiently process graph data to satisfy users' requirements for The subgraph computes the demand case. The method can be executed by a graph data processing device, and the device can be realized by means of software and / or hardware. Optionally, the apparatus may be configured in a device carrying a graph data processing function, such as a server. see figure 1 , the method may specifically include:

[0032] S110. Determine a target sub-map and new data added to the target sub-map according to the incremental graph data.

[0033] It can be understood that a graph is a graph, consisting of endpoints and edges. Correspondingly, graph data can include edge data and point data. Point data can include endpoint id, endpoint attributes, and endpoint types, etc. Edge data can include...

Embodiment 2

[0058] figure 2 It is a flow chart of a graph data processing method provided in Embodiment 2 of the present invention. On the basis of the above embodiments, this embodiment provides a solution for determining incremental associated data and new version associated data. see figure 2 , the method may specifically include:

[0059] S210. Determine the target sub-map and the newly added data of the target sub-map according to the incremental map data.

[0060] S220. Determine the first id of the target subgraph according to the endpoint id in the newly added data of the target subgraph.

[0061] Further, for each target subgraph, if the target subgraph is a newly added subgraph due to the introduction of incremental graph data, and the number of endpoints included in the target subgraph is one, then the target subgraph can include The id of the endpoint of is used as the first id of the target subgraph. If the target subgraph is a newly added subgraph due to the introducti...

Embodiment 3

[0079] image 3 It is a flowchart of a graph data processing method provided in Embodiment 3 of the present invention. On the basis of the above embodiments, this embodiment adds the process of updating the associated query table and querying details. see image 3 , the method may specifically include:

[0080] S310. Determine the target sub-map and the newly added data of the target sub-map according to the incremental map data.

[0081] S320. Determine the incremental associated data of the target sub-graph according to the midpoint data of the newly added data of the target sub-graph.

[0082] S330. Determine new version associated data of the target subgraph according to the incremental associated data and the original associated data of the target subgraph.

[0083] S340. Determine the new version detail data of the target subgraph according to the new version association data of the target subgraph and the edge data in the target subgraph.

[0084] S350, using the ne...

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Abstract

The embodiment of the invention discloses a graph data processing method and device, electronic equipment and a storage medium, and the method comprises: determining a target sub-graph and newly addeddata of the target sub-graph according to incremental graph data; determining incremental associated data of the target sub-graph according to the point data in the newly added data of the target sub-graph; determining new version associated data of the target sub-graph according to the incremental associated data and the original associated data of the target sub-graph; and determining new version detail data of the target sub-graph according to the new version associated data of the target sub-graph and the edge data in the target sub-graph, wherein the associated data comprises an endpointid and a sub-graph id, and the detail data comprises a sub-graph id, an edge id, an edge type, an edge associated endpoint id and an endpoint type. The calculation amount under the condition that thedata is continuously increased is greatly reduced, the graph data processing efficiency is improved, and a new thought is provided for sub-graph calculation.

Description

technical field [0001] The present invention relates to the field of computer technology, in particular to data processing and data storage technology, and in particular to a graph data processing method, device, electronic equipment and storage medium. Background technique [0002] A graph database is a database based on a graph relational (Graph, non-image) model, and the data contained in it is often point data and edge data. In the field of graph databases, there is often a need for subgraph calculations, especially in the case of calculating weakly connected subgraphs in graphs with a large amount of data, such as how many weakly connected subgraphs there are, and whether multiple points belong to the same weakly connected subgraph Graph, what are the requirements for the points and edges contained in a weakly connected subgraph. [0003] At present, real-time computing methods and offline computing methods are mainly used. Among them, the real-time calculation method...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/901G06F16/903
CPCG06F16/9024G06F16/903
Inventor 吕志军刘成军
Owner 南京智慧图谱信息技术有限公司
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