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Node associated variable quantity calculation method and node anomaly identification method and device

A computing method and node technology, applied in the field of big data computing, can solve the problems of inter-node messages occupying memory, unable to determine whether super nodes are abnormal, computing tasks cannot be executed normally, etc., to achieve the effect of ensuring smooth execution and reducing memory

Pending Publication Date: 2022-07-29
融慧金科金融服务外包(北京)有限公司
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Problems solved by technology

[0003] In order to overcome at least to a certain extent the problem that when there are super nodes, messages between nodes occupy a large amount of memory during the transmission process, resulting in the failure of normal execution of computing tasks and the inability to determine whether the super nodes are abnormal. This application provides a calculation method for the number of node-associated variables , node anomaly identification method and device

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  • Node associated variable quantity calculation method and node anomaly identification method and device
  • Node associated variable quantity calculation method and node anomaly identification method and device
  • Node associated variable quantity calculation method and node anomaly identification method and device

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Embodiment Construction

[0045] In order to make the objectives, technical solutions and advantages of the present application clearer, the technical solutions of the present application will be described in detail below. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all of the embodiments. Based on the examples in this application, all other implementations obtained by those of ordinary skill in the art without creative work fall within the scope of protection of this application.

[0046] figure 1 A flowchart of a method for calculating the number of associated variables of a node provided by an embodiment of the present application, such as figure 1 As shown, the method for calculating the number of variables associated with the node includes:

[0047] S11: Receive string information sent by at least one target node, and the string information is obtained by serializing the HLL data structure corresponding to the parameters of the targ...

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Abstract

The invention relates to a node associated variable number calculation method and device and a node anomaly recognition method and device, and the node associated variable number calculation method comprises the steps that character string information sent by at least one target node is received, and the character string information is obtained through serialization processing according to an HLL data structure corresponding to target node parameters; performing deserialization processing on the received character string information of the target node to obtain an HLL data structure corresponding to the target node; combining the parameter information corresponding to all the target nodes to obtain an element set; according to the method, the quantity of all elements in the element set is counted to obtain the associated variable quantity value, and the HLL data structure can effectively reduce the memory required for calculating the associated variable quantity value, so that the smooth execution of the calculation task can be ensured, and meanwhile, the calculation of the associated variable quantity with more hops can be supported.

Description

technical field [0001] The present application belongs to the technical field of big data computing, and in particular relates to a method for calculating the number of variables associated with nodes, a method and device for identifying node anomalies. Background technique [0002] Compared with traditional relational data, graph data has unique advantages. First of all, graph data can avoid the establishment of table structure, and the original data can be abstracted into graph node data or graph relational data as needed. , use common graph query algorithms. However, a prerequisite for using graph data for calculation is that the nodes in the graph are normal nodes. If there are abnormal nodes, the accuracy of the graph data calculation results will be affected. Among them, the abnormal node is identified by calculating the number of associated variables, that is, the number of target nodes associated with the concerned node within a few hops is calculated. If the number...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/31G06F40/126G06F40/151G06F40/216
CPCG06F16/31G06F16/325G06F40/126G06F40/151G06F40/216
Inventor 张燕
Owner 融慧金科金融服务外包(北京)有限公司
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