Method, device, computer system and storage medium for determining association analysis relationships

Abstract

The disclosure provides a method for determining a correlation relationship, which can be applied to the technical field of computers. The method comprises: obtaining a to-be-processed data table from a configuration management system, obtaining a first model list, a second model list and a third model list according to a preset division rule based on the to-be-processed data table; obtaining determined node data, first relationship type data and second relationship type data based on the first model list, the second model list and the third model list, and storing the determined node data, the first relationship type data and the second relationship type data in a graph database; obtaining third relationship type data based on production data and calling data obtained from a server and an application connected to the server, and storing the third relationship type data in the graph database; and determining a correlation relationship topology graph based on the node data, the first relationship type data, the second relationship type data and the third relationship type data. The disclosure also provides a data processing device, a computing device and a medium.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of computer, in particular, to the technical field of database, more particularly, to a method and device for determining association relationship, a computer system and a storage medium. BACKGROUND

[0002] A configuration management database (CMDB) stores information of applications, devices, system software, etc. of an enterprise by discovery and update, and provides accurate static configuration information for event processing, fault positioning, problem analysis, change emergency, etc. in production and operation by storing a large amount of data in the form of data tables. With the increasing requirement of production continuity, the static configuration data table gradually cannot meet the operation and maintenance requirements, and the following problems exist: the data table cannot support immediate fault positioning, the data table stored in the current configuration management system is mostly static fixed configuration data with very low change frequency, such as CPU, memory and disk size of a server; these data cannot reflect the state of the server in production and operation, and cannot play a role in operation and maintenance scenarios with high real-time requirements; the table management cannot show the mutual relationship, the existing configuration management data is mostly in the form of table management for data display, only the information of a single device or node can be reflected, the position and role of the device or node in the system cannot be reflected, and it is not conducive to quickly finding the problem chain in fault positioning; and the production calling information is split, a large amount of production service dynamic data and calling information are generated at any time in production and operation, and are generally reserved in the form of logs, the production data and calling data are considered as important data for positioning problem causes. However, the data table information stored in the CMDB cannot be uniformly called and analyzed with the calling information, and the application information stored in the CMDB is objectively split from the application software logs, which is not conducive to production problem troubleshooting. SUMMARY

[0003] Therefore, the present disclosure provides a method and device for determining association relationship, a computer system and a storage medium.

[0004] According to one aspect of the present disclosure, a method for determining association relationship is provided, comprising:

[0005] The to-be-processed data table obtained from the configuration management system, based on the key value and actual attribute of each table in the to-be-processed data table, the first model list, the second model list and the third model list are obtained according to the preset division rule.

[0006] Based on the first model list, the second model list, and the third model list, node data, first relationship type data, and second relationship type data are determined, and the node data, the first relationship type data, and the second relationship type data are stored in the graph database.

[0007] Based on the server and the production data and the call data obtained in the application connected to the server, third relationship type data is obtained and stored in the graph database.

[0008] Based on the node data, the first relationship type data, the second relationship type data, and the third relationship type data, an association relationship topology graph is determined.

[0009] According to an embodiment of the present disclosure, based on the to-be-processed data table obtained in the configuration management system, the first model list, the second model list, and the third model list are obtained, which includes:

[0010] According to the preset division rule, the number of key values contained in the to-be-processed data table is determined, and whether the to-be-processed data table contains an actual attribute is determined, and the to-be-processed data table is divided into the first model list, the second model list, and the third model list according to the number of key values and whether the to-be-processed data table contains the actual attribute.

[0011] The actual attribute is an attribute that has actual meaning and is defined in advance in the to-be-processed data table.

[0012] In addition, the preset division rule includes:

[0013] When there is only one key value and the actual attribute, the to-be-processed data table is divided into the first model list; when the number of key values is greater than or equal to 2 and there is no actual attribute, the to-be-processed data table is divided into the second model list; and when the number of key values is greater than or equal to 2 and there is an actual attribute, the to-be-processed data table is divided into the third model list.

[0014] According to an embodiment of the present disclosure, the node data is determined, which includes:

[0015] According to the preset division rule, the node data is determined based on the first key value and the first attribute in the first model list and the third model list, and the node data is stored in the graph database.

[0016] In addition, the preset division rule further includes:

[0017] The first key value is the primary key of the first model list and the third model list, and the third model list further contains other key values in addition to the primary key. The scanned key values are sorted according to the order of scanning; and the actual attribute is sorted according to the order of scanning, and the first scanned attribute is the first attribute.

[0018] According to an embodiment of the present disclosure, determining the first relationship type data and the second relationship type data comprises:

[0019] Based on all the key values in the second model list and the third model list, the first relationship type data and the second relationship type data are determined.

[0020] In addition, the preset division rule further comprises:

[0021] The key values contained in the second model list are combined in pairs according to mathematical arrangement. The key value in the front of the arrangement order is taken as the starting point, the key value in the rear of the arrangement order is taken as the ending point, and the relationship between the two key values is defined as the first relationship type, thereby obtaining the first relationship type data. The second relationship type data in the third model list is obtained in the same rule.

[0022] According to an embodiment of the present disclosure, obtaining the third relationship type data comprises:

[0023] The information collection program collects the data in the production data and the calling data at a predetermined time interval, and the third relationship type data is obtained through a formatting method.

[0024] According to an embodiment of the present disclosure, obtaining the association relationship topology graph based on the node data, the first relationship type data, the second relationship type data, and the third relationship type data comprises:

[0025] In the graph database, the third relationship type data is matched with the node data, the third relationship type data that is matched successfully is attached to the node data, complete node data is obtained, the nodes with the same attribute are recursively processed to obtain node group nodes, the node group nodes with the same attribute are recursively processed to obtain application group nodes, so that all the nodes are classified into the node group nodes or the application group nodes, the relationship between the nodes is represented according to the corresponding starting point, ending point, and relationship type of the key values in the first relationship type data and the second relationship type data, and the relationship between the complete node data, thereby obtaining the association relationship topology graph.

[0026] Another aspect of the present disclosure provides an association analysis device for configuration management data, comprising:

[0027] A first generation module is configured to generate node data, first relationship type data, and second relationship type data according to a to-be-processed data table obtained from a configuration management system.

[0028] A second generation module is configured to generate third relationship type data according to a to-be-processed data table obtained from a server and an application connected to the server.

[0029] and a third generation module configured to generate the topology graph based on the node data, the first relationship type data, the second relationship type data, and the third relationship type data.

[0030] According to an embodiment of the present disclosure, the first generation module comprises:

[0031] A receiving unit configured to receive to-be-processed data of the configuration management system, wherein the to-be-processed data comprises a to-be-processed data table.

[0032] A determination unit configured to determine the number of key values and whether the actual attribute is contained based on the to-be-processed data table.

[0033] and a generation unit configured to match the key values and the attribute to generate the node data, the first relationship type data, and the second relationship type data.

[0034] Another aspect of the present disclosure provides a computer readable storage medium storing computer executable instructions, which when executed, implement the method as described above.

[0035] Another aspect of the present disclosure provides a computer program comprising computer executable instructions, which when executed, implement the method as described above.

[0036] Another aspect of the present disclosure provides a computer system comprising: one or more processors; and a storage device storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method as described above.

[0037] According to an embodiment of the present disclosure, based on the to-be-processed data table, the first model list, the second model list, and the third model list are obtained according to a preset division rule, the node data, the first relationship type data, and the second relationship type data are obtained based on data in the first model list, the second model list, and the third model list, and are stored in a graph database, the third relationship type data is obtained based on production data and calling data obtained in the server and an application connected to the server, and the third relationship type data is stored in the graph database, and the associated relationship topology graph is determined based on the node data, the first relationship type data, the second relationship type data, and the third relationship type data, so that at least part of the technical problems in the related art that the mutual relationship between data tables cannot be exhibited and the data table data cannot be implemented for real-time fault positioning are overcome, and the technical effect of providing accurate information in real time is achieved. BRIEF DESCRIPTION OF DRAWINGS

[0038] The above and other objects, features and advantages of the present disclosure will become more apparent from the following description when taken in conjunction with the accompanying drawings, in which:

[0039] Figure 1 An example system architecture of the method and apparatus for determining the association relationship according to the embodiments of the present disclosure is schematically shown;

[0040] Figure 2 A flowchart of the method for determining the association relationship according to the embodiments of the present disclosure is schematically shown;

[0041] Figure 3 A flowchart of obtaining the first model list, the second model list and the third model list based on the to-be-processed data table according to the embodiments of the present disclosure is schematically shown;

[0042] Figure 4 A flowchart of determining the node data according to the embodiments of the present disclosure is schematically shown;

[0043] Figure 5 A flowchart of determining the first relationship type data and the second relationship type data according to the embodiments of the present disclosure is schematically shown;

[0044] Figure 6 A flowchart of obtaining the association relationship topology graph based on the node data, the first relationship type data, the second relationship type data and the third relationship type data according to the embodiments of the present disclosure is schematically shown;

[0045] Figure 7 A three-layer architecture of application node→application node type→application formed according to the embodiments of the present disclosure is schematically shown;

[0046] Figure 8 A schematic diagram when viewing the dynamic relationship based on the three-layer architecture of application node→application node type→application according to the embodiments of the present disclosure is schematically shown;

[0047] Figure 9 A structural block diagram of the apparatus for determining the association relationship according to the embodiments of the present disclosure is schematically shown;

[0048] Figure 10 A block diagram of an electronic device suitable for implementing the method for determining the association relationship according to the embodiments of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0049] Hereinafter, the embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it is to be understood that these descriptions are only exemplary and are not intended to limit the scope of the present disclosure. In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the present disclosure. However, it will be apparent to those skilled in the art that one or more embodiments can be practiced without these specific details. In addition, in the following description, descriptions of well-known structures and techniques have been omitted to avoid unnecessarily obscuring the concept of the present disclosure.

[0050] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used herein, the terms "comprises", "comprising", "includes", "including" and the like are, generally used

[0051] All terms used herein, including technical and scientific terms, have the meanings commonly understood by one of ordinary skill in the art unless otherwise defined. It should be noted that the use of certain terms or phrases in various places in the specification is not intended to exclude those terms or phrases from the scope of the specification in other instances.

[0052] In the case where expressions such as "at least one of A, B, and C, etc." are used, it generally should be interpreted to include any of one of A, B, or C, and also to include a combination of at least one of A, B, and C, unless otherwise specified. In the case where expressions such as "at least one of A, B, or C, etc." are used, it generally should be interpreted to include any of one of A, B, or C, and also to include a combination of at least one of A, B, and C, unless otherwise specified.

[0053] Embodiments of the disclosure provide a method for determining an association relationship, comprising: obtaining a to-be-processed data table from a configuration management system, obtaining a first model list, a second model list, and a third model list according to a preset division rule based on a key value and an actual attribute of each table in the to-be-processed data table; determining node data, first relationship type data, and second relationship type data based on data in the first model list, the second model list, and the third model list, and storing the node data, the first relationship type data, and the second relationship type data into a graph database; obtaining third relationship type data based on production data and calling data obtained from a server and an application connected to the server, and storing the third relationship type data into the graph database; and determining an association relationship topology graph based on the node data, the first relationship type data, the second relationship type data, and the third relationship type data.

[0054] Figure 1 An exemplary system architecture 100 of the method and apparatus for determining an association relationship according to embodiments of the disclosure is schematically shown. It should be noted that, Figure 1The examples shown are merely examples of system architectures for applying the embodiments of this disclosure, intended to help those skilled in the art understand the technical content of this disclosure, but do not imply that the embodiments of this disclosure cannot be used in other devices, systems, environments, or scenarios.

[0055] like Figure 1 As shown, the system architecture 100 according to this embodiment may include terminal devices 101, 102, and 103, a network 104, and a server 105. The network 104 serves as a medium for providing a communication link between the terminal devices 101, 102, and 103 and the server 105. The network 104 may include various connection types, such as wired and / or wireless communication links, etc.

[0056] Users can use terminal devices 101, 102, and 103 to interact with server 105 via network 104 to receive or send messages, etc. Various data processing applications can be installed on terminal devices 101, 102, and 103, such as configuration management library applications, graph database applications, data acquisition software, etc. (for example only).

[0057] Terminal devices 101, 102, and 103 can be various electronic devices with displays that support web browsing and data processing, including but not limited to smartphones, tablets, laptops, and desktop computers.

[0058] Server 105 can be a server that provides various services, such as a backend management server that supports the data processed by users using terminal devices 101, 102, and 103 (for example only). The backend management server can analyze and process the received user requests and other data, and feed back the processing results (such as information, data, topology diagrams, etc. obtained or generated according to user requests) to the terminal devices.

[0059] It should be noted that the method for determining association relationships provided in this disclosure embodiment can generally be executed by server 105. Correspondingly, the apparatus for determining association relationships provided in this disclosure embodiment can generally be located in server 105. The method for determining association relationships provided in this disclosure embodiment can also be executed by a server or server cluster that is different from server 105 and capable of communicating with terminal devices 101, 102, 103 and / or server 105. Correspondingly, the apparatus for determining association relationships provided in this disclosure embodiment can also be located in a server or server cluster that is different from server 105 and capable of communicating with terminal devices 101, 102, 103 and / or server 105. Alternatively, the method for determining association relationships provided in this disclosure embodiment can also be executed by terminal devices 101, 102, or 103, or by other terminal devices different from terminal devices 101, 102, or 103. Accordingly, the device for determining the association relationship provided in the embodiments of this disclosure may also be provided in terminal devices 101, 102, or 103, or in other terminal devices different from terminal devices 101, 102, or 103.

[0060] For example, the data table to be processed, the first model list, the second model list, the third model list, node data, the first relationship type data, the second relationship type data, and the third relationship type data can originally be stored in any one of terminal devices 101, 102, or 103 (e.g., terminal device 101, but not limited thereto), or stored on an external storage device and can be imported into terminal device 101. Then, terminal device 101 can locally execute the method for determining association relationships provided in the embodiments of this disclosure. Alternatively, the data table to be processed, the first model list, the second model list, the third model list, node data, the first relationship type data, the second relationship type data, and the third relationship type data can be sent to other terminal devices, servers, or server clusters, and the other terminal devices, servers, or server clusters that receive the set of orders to be identified and historical transaction features can execute the method for determining association relationships provided in the embodiments of this disclosure.

[0061] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0062] Figure 2 A flowchart illustrating a method for determining association relationships according to an embodiment of this disclosure is shown schematically.

[0063] like Figure 2 As shown, the process of determining the association relationship in this embodiment includes operations S210 to S240.

[0064] In operation S210, based on the key value and the actual attribute of each table in the to-be-processed data table, the first model list, the second model list, and the third model list are obtained according to a preset division rule from the to-be-processed data table obtained from the configuration management system.

[0065] In an embodiment of the present disclosure, before obtaining the information of the user, the consent or authorization of the user can be obtained. For example, before operation S210, a request for obtaining the user-related data can be sent to the user. In the case where the user agrees or authorizes the user-related data to be obtained, operation S210 is performed.

[0066] According to an embodiment of the present disclosure, the data stored in the configuration management system can include to-be-processed data tables and a graph database. The to-be-processed data tables can include data tables of various applications used by the user, application maintenance information data tables, and system data tables connecting servers between various applications used by the user. Each of the various applications in the various applications used by the user contains a plurality of application nodes, and each of the various servers in the various servers contains a plurality of system nodes. The various to-be-processed data tables can contain data table names and data table attributes, wherein the attribute is each column of the data table.

[0067] According to an embodiment of the present disclosure, the to-be-processed data table is obtained from the configuration management system, and the to-be-processed data table can include hardware devices, system information, application information, and to-be-processed data table node types stored in the configuration management system. The key value and the actual attribute of the to-be-processed data table are determined when the to-be-processed data table is obtained. According to the key value and the actual attribute of each table in the to-be-processed data table, the to-be-processed data table is divided into the first model list, the second model list, and the third model list. The first model list, the second model list, and the third model list are stored in the configuration management system for subsequent processing.

[0068] In operation S220, based on the data in the first model list, the second model list, and the third model list, the node data, the first relationship type data, and the second relationship type data are determined, and the node data, the first relationship type data, and the second relationship type data are stored in the graph database.

[0069] According to an embodiment of the present disclosure, the first model list, the second model list, and the third model list are obtained based on the to-be-processed data table. The division basis is the type of the key value and the actual attribute. The data in the first model list, the second model list, and the third model list obtained do not change, but the connection between the data in the first model list, the second model list, and the third model list is increased. The display mode of each to-be-processed data table is changed. The same type of data table is more convenient to search when searching for data, and the efficiency of data processing is improved.

[0070] In operation S230, third relationship type data is obtained based on the production data and the invocation data obtained in the server and the application connected to the server, and the third relationship type data is stored in the graph database.

[0071] According to an embodiment of the present disclosure, the production data and the invocation data can be used to represent the real-time state of the server and the application connected to the server, the program information in the production data and the invocation data is collected by the information collection program, and the user can flexibly adjust the collection frequency by setting the collection interval of the information collection program to obtain the real-time updated production data and invocation data.

[0072] In operation S240, the association relationship topology graph is determined based on the node data, the first relationship type data, the second relationship type data, and the third relationship type data.

[0073] According to an embodiment of the present disclosure, the node data can be obtained from the first model list, the third model list based on the actual attribute existing in each to-be-processed data table, that is, the node data is obtained from the first model list and the third model list; the key value other than the first key value in each to-be-processed data table can be the first key value of the to-be-processed data table other than this to-be-processed data table, and the first relationship type data and the second relationship type data can represent the relationship between the key values in the second model list and the third model list; the node data, the first relationship type data, and the second relationship type data can associate the data tables with the same attribute among the first model list, the second model list, and the third model list; by combining the node data, the first relationship type data, the second relationship type data, and the third relationship type data in the graph database, the node information of the application nodes and / or the system nodes contained in the first model list, the second model list, and the third model list is collectively displayed in the form of the topology graph, so that the state of the application nodes and / or the system nodes can be updated in real time, and the association relationship between the application nodes and / or the system nodes can be easily displayed to the user.

[0074] The method shown in Figures 3-6 will be further described below with reference to specific embodiments. Figure 2

[0075] Figure 3 The flowchart of obtaining the first model list, the second model list, and the third model list based on the to-be-processed data table according to an embodiment of the present disclosure is schematically shown.

[0076] As shown in Figure 3 , the flow of the method for determining the association relationship of this embodiment includes operation S211 and operation S212.

[0077] In operation S211, the number of key values contained in the to-be-processed data table is determined according to a preset division rule, and it is determined whether the to-be-processed data table contains an actual attribute.​

[0078] According to an embodiment of the present disclosure, when the to-be-processed data table is stored to the configuration management system, the attributes of the to-be-processed data table can be processed, and it can be marked whether each attribute is a key value, for example, an attribute identifying each row of the to-be-processed data table can be defined as a key value; an attribute having actual meaning can be defined as an actual attribute, and other attributes can be defined as non-actual attributes, for example, a timestamp in the to-be-processed data table can be defined as a non-actual attribute.

[0079] In operation S212, the to-be-processed data table is divided into a first model list, a second model list, and a third model list according to the number of key values and whether the to-be-processed data table contains actual attributes.

[0080] According to an embodiment of the present disclosure, when there is only one key value in the to-be-processed data table and there is an actual attribute, the to-be-processed data table is divided into the first model list; when the number of key values in the to-be-processed data table is greater than or equal to 2 and there is no actual attribute, the to-be-processed data table is divided into the second model list; and when the number of key values in the to-be-processed data table is greater than or equal to 2 and there is an actual attribute, the to-be-processed data table is divided into the third model list.

[0081] Figure 4 A flowchart for determining node data according to an embodiment of the present disclosure is schematically shown.

[0082] As shown in FIG. 22, the flow of determining node data according to an embodiment of the present disclosure includes operation S221 and operation S222. Figure 4

[0083] In operation S221, a first key value and a first attribute in the first model list and the third model list are determined.

[0084] According to an embodiment of the present disclosure, when the first model list and the third model list are stored to the configuration management system, the key values in each of the first model list and the third model list can be processed, a key value that can uniquely represent information of the to-be-processed data table is defined as a primary key, the primary key is defined as the first key value, the third model list further contains other key values in addition to the primary key, and the scanned key values are sorted according to the order of scanning; the scanned actual attributes are sorted according to the order of scanning, and the first scanned attribute is the first attribute.

[0085] In operation S222, node data is determined according to the first key value and the first attribute, and the node data is stored in the graph database.

[0086] ​According to an embodiment of the present disclosure, the first model list, the third model list, and the first key value contained in each of the lists are combined with the first attribute to generate new key value pair data, the key value pair data contains an attribute name and an attribute value, the key value pair data is taken as node data, and the node data is stored in the graph database.

[0087] Figure 5 A flowchart for determining the first relationship type data and the second relationship type data according to an embodiment of the present disclosure is schematically shown.

[0088] As shown in Figure 5 , the process of determining the first relationship type data and the second relationship type data of the embodiment includes operation S310 to operation S320.

[0089] In operation S310, the first relationship type data is determined based on all key values in the second model list, and the first relationship type is stored in the graph database.

[0090] According to an embodiment of the present disclosure, at least one list in the second model list has at least two key values, since there is no actual attribute in the second model list, there is no key value in the second model list that can identify all actual attributes of the second model list, and the second model list has no primary key, the order of the key values is determined by the order of scanning, the key value scanned first is taken as the starting point of the first relationship type data, the key value scanned last is taken as the end point of the first relationship type data, and the relationship between the two key values is the first relationship.

[0091] According to an embodiment of the present disclosure, the key values in at least one list in the second model list can be the primary keys of the first model list or the third model list, and the relationship between each two is the first relationship, the relationship between the nodes corresponding to the key values in these second model lists is represented by the first relationship type data, and there is a connection relationship between the nodes.

[0092] In operation S320, the second relationship type data is determined based on all key values in the third model list, and the second relationship type is stored in the graph database.

[0093] According to an embodiment of the present disclosure, at least one list in the third model list has at least two key values, and the third model list has actual attributes, and at least one list in the third model list has key values that can identify all actual attributes of the third model list, that is, at least one list in the third model list has a primary key, the primary key is defined as the first key value, and the arrangement order of the remaining key values is determined by the scanning order, the key value in the front order is taken as the starting point of the second relationship type data, the key value scanned in the rear order is taken as the end point of the second relationship type data, and the relationship type between the two key values is the second relationship.

[0094] According to an embodiment of the present disclosure, the remaining key values in at least one list in the third model list except the primary key can be the primary keys of other model lists except the second model list, the relationship between the primary key and the remaining key values in at least one list in the third model list is defined as the second relationship, the relationship between the nodes corresponding to the key values in the third model list is represented by the second relationship type data, and the nodes have a dependent relationship; the second relationship type data is stored in the graph database, and the nodes corresponding to the key values in the third model list and the connection relationship between the nodes are displayed to the user through the topological graph in the subsequent process.

[0095] According to an embodiment of the present disclosure, the third relationship type data includes:

[0096] The information collection program collects data in the production data and the calling data in the application connected to the server according to a predetermined time interval, and obtains the third relationship type data through a formatting method.

[0097] According to an embodiment of the present disclosure, the user can obtain different types of program information in the production data and the calling data by selecting different information collection programs, wherein the different types of program information can include real-time processes of different applications, real-time states of mutual communication between different applications, real-time states of mutual communication between the server and the application, and the like, and the different types of program information are formatted to obtain the third relationship type data containing different attributes to meet different needs of the user.

[0098] Figure 6 A flowchart for obtaining an association relationship topological graph based on node data, first relationship type data, second relationship type data, and third relationship type data according to an embodiment of the present disclosure is schematically shown.

[0099] As shown in Figure 6 The flowchart for obtaining an association relationship topological graph based on node data, first relationship type data, second relationship type data, and third relationship type data according to the embodiment includes operations S241-S243.

[0100] In operation S241, the third relationship type data is matched with the node data in the graph database, the third relationship type data that is successfully matched is attached to the node data, and complete node data is obtained.

[0101] According to an embodiment of the present disclosure, based on the attribute information of the third relationship type data, the actual attribute same as the node data is matched, the node corresponding to the actual attribute is obtained, the attribute information of the third relationship type data is added to the corresponding node, the information of the node is perfected, the third relationship type data with timeliness is contained in the node, and complete node data is obtained.

[0102] In operation S242, recursive processing is performed based on the complete node data with the same attribute, node group nodes are obtained, recursive processing is performed based on the node group nodes with the same attribute, application group nodes are obtained, and all complete node data is classified into the node group nodes or the application group nodes.

[0103] According to an embodiment of the present disclosure, the complete node data with the same attribute is divided into the same node group, and in the same node group, the node group node data belonging to the same application or system is divided into the same application group, so that all complete node data is classified into the node group nodes or the application group nodes.

[0104] In operation S243, the relationship between the complete node data is represented according to the corresponding start point, end point and relationship type of the key values of the first relationship type data and the second relationship type data, and an association relationship topology graph is obtained.

[0105] According to an embodiment of the present disclosure, the complete node data is displayed in the graph database according to the node group nodes or the application group nodes, the relationship between the nodes is represented by the first relationship type data or the second relationship type data, and an association relationship topology graph is obtained. The association relationship topology graph can intuitively display the node data and the relationship between the nodes, which is beneficial to monitoring whether there is a fault between the nodes and quickly determining the fault position. By combining the production data, the calling data, the first model list, the second model list and the third model list, the application information and the system information with low change frequency stored in the configuration management system library are combined with the real-time production data and the calling data, so that the configuration management data has real-time performance, the dimension of the configuration management data is improved, the granularity of the configuration management data is refined, and the management data can display more accurate information.

[0106] According to an embodiment of the present disclosure, the association relationship between the payment software and the server is taken as an example to describe the embodiment of the present disclosure in detail.

[0107] According to an embodiment of the present disclosure, the application data table to be processed and the system data table to be processed are divided into a first model list, a second model list and a third model list according to the number of key values and whether the actual attribute is contained, the first model list only contains one key value and contains the actual attribute, for example, the application table (APPINFO) contains only one key value and two attributes, the two attributes contained in the application table (APPINFO) are sorted according to the scanning order to obtain a first attribute and a second attribute, the key value contained in the application table (APPINFO) is only a primary key, and the primary key is defined as a first key value; the specific content is represented in the following table:

[0108] Attribute name Marked in program Attribute meaning APPCI Primary key (first key value) Application CI ENAME_SIMPLE First attribute Application simple name APPNAME Second attribute Application name

[0109] The specific data of the attribute is represented in the following table:

[0110] APPCI ENAME_SIMPLE APPNAME 0101-I-APP-000001 F-WAPB Mobile bank

[0111] For another example, the system node table (SYSNODEINFO) contains only one key value and one attribute, and the specific content of the system node table (SYSNODEINFO) is obtained according to the preset rule and represented in the following table:

[0112] Attribute name Marked in program Attribute meaning SYSNODECI Primary key (first key value) SYSNODECI HOSTNAME First attribute Host name

[0113] The specific data of the attribute is represented in the following table:

[0114] SYSNODECI HOSTNAME 0010-H-SYS-000000070 pdccbwapbapp001 0010-H-SYS-000000071 dccbwapbapp002

[0115] According to an embodiment of the present disclosure, the number of key values in the second model list is greater than or equal to 2 and no actual attribute is contained, for example, the system node application node relationship table (SYSNODEAPPNODEREL) contains only key values and no actual attribute, the two key values contained in the system node application node relationship table (SYSNODEAPPNODEREL) are sorted according to the scanning order to obtain a first key value and a second key value; the specific content is represented in the following table:

[0116] Attribute name Marked in program Attribute meaning SYSNODECI First key value SYSNODECI APPNODECI Second key value APPNODECI

[0117] The specific data of the attribute representing the key value is represented in the following table:

[0118]

[0119]

[0120] According to an embodiment of the present disclosure, the number of key values in the third model list is greater than or equal to 2 and there is an actual attribute, for example, the application node table (APPNODEINFO) contains multiple key values and there is an actual attribute; the specific content is represented in the following table:

[0121] Attribute name Attribute classification Attribute meaning APPNODECI Primary key (first key value) Application node CI APPCI Second key value Application CI APPMODIFYCI Third key value Application maintenance CI APP_NODENAME First attribute Application node name

[0122] The specific data of the attribute is represented in the following table:

[0123]

[0124] For another example, the application maintenance information table (APPMODIFYINFO) contains two key values and there is an actual attribute; the specific content is represented in the following table:

[0125] Attribute name Marked in program Attribute meaning APPMODIFYCI Primary key Application maintenance CI APPCI Foreign key 1 Application CI APPMAINT Attribute 1 Maintainer

[0126] The specific data of the attribute is represented in the following table:

[0127]

[0128] Finally, the first model list, the second model list and the third model list obtained by the division are stored in the configuration management system, and the division results of the first model list, the second model list and the third model list are as follows:

[0129] Table name Type APPINFO First model list SYSNODEINFO First model list SYSNODEAPPNODEREL Second model list APPNODEINFO Third model list APPMODIFYINFO Third model list

[0130] According to an embodiment of the present disclosure, the data storage mode in the graph database is node (node) and edge (edge), the node data can be taken as the node, the first relationship type data and the second relationship type data can be taken as the edge, the storage form of the node data is a key value pair, all attributes of the node are stored, the first relationship type data and the second relationship type data contain a starting point and an ending point, and some other attributes can also be contained.

[0131] According to an embodiment of the present disclosure, the node data is determined according to the first key value and the first attribute in the first model list and the third model list.

[0132] The node data can be obtained from the above embodiment list; the specific content is represented in the following table:

[0133] Primary key (first key value) First attribute APPCI ENAME_SIMPLE SYSNODECI HOSTNAME APPNODECI APP_NODENAME APPMODIFYCI APPMAINT

[0134] The first key value and the data of the corresponding first attribute can be combined to generate the node data, that is, the specific content of the first key value and the specific content of the corresponding first attribute are stored in the graph database in the form of a key value pair.

[0135] According to an embodiment of the present disclosure, the first relationship type data and the second relationship type data are divided for the relationship between the key values in the second model list and the third model list, and the first relationship type data and the second relationship type data are stored in the graph database.

[0136] For example, the system node application node relationship table (SYSNODEAPPNODEREL) belonging to the second model list contains the first key value (SYSNODECI) and the second key value (APPNODECI) obtained in the scanning order, the first key value and the second key value have a connection relationship, and the relationship type between the two key values is marked as the first relationship in the attribute; (SYSNODECI→APPNODECI) is stored as the first relationship type data in the graph database.

[0137] For another example, the application node table (APPNODEINFO) belonging to the third model list contains the first key value (APPNODECI) and the second key value (APPCI) and the third key value (APPMODIFYCI) obtained in the scanning order, the first key value and the second key value have a dependency relationship, and the relationship type between the two key values is marked as the second relationship in the attribute; (APPNODE→APP, APPNODE→APPMODIFY) is stored as the second relationship type data in the graph database.

[0138] The final relationship model list is as follows:

[0139]

[0140] According to an embodiment of the present disclosure, the data of the second model list and the third model list is converted into node data and stored in the graph database; for example, according to the system node application node relationship table (SYSNODEAPPNODEREL), node data node1 needs to be generated:

[0141] {sysnodeci:0010-H-SYS-000000070, hostname:pdccbwapbapp001},

[0142] According to the above relationship model list, relationship data is generated and stored in the graph database, and according to the Sysnode_appnode relationship in the relationship model list, the first relationship data relation1 needs to be generated:

[0143] {startnode:0010-H-SYS-000000070, endNode:0001-R-APP-000685481, relationName:sysnode_appnode}

[0144] According to the embodiments of the present disclosure, the information collection program Agent can be used to collect the production data and the application program information contained in the calling data obtained from the server and the application connected to the server, format the application program information, obtain the required start and target information, match the start and target information with the node data in the graph database, obtain the newly added third relationship data, and store the third relationship data in the graph database. The specific representation is as shown in the following table:

[0145]

[0146] According to the start and target information, the "pdccbwapbapp001" and "pdccbwapbapp002" corresponding to the "0010-H-SYS-000000070" and "0010-H-SYS-000000071" nodes in the graph database are matched respectively, and a new dynamic relationship data is obtained:

[0147] {startnode: 0010-H-SYS-000000070, endnode: 0010-H-SYS-000000071, relationName: ATP-alipay, timestamp: 20211203220000}

[0148] The information collection program Agent can also be used to collect dynamic configuration information as a supplement. The collected dynamic configuration information is specifically represented as shown in the following table:

[0149] Target memMB http pdccbwapbapp001 3972 135

[0150] According to the target information, the "pdccbwapbapp001" corresponding to the "0010-H-SYS-000000070" node in the graph database is matched, and the third relationship data is specifically represented as: {sysnodeci: 0010-H-SYS-000000070, hostname: pdccbwapbapp001, memMB: 3972, cpu:, http: 135}.

[0151] According to the embodiments of the present disclosure, the node data, the first relationship type data, the second relationship type data, and the third relationship type data in the graph database are recursively processed to obtain the association relationship topology graph.

[0152] According to an embodiment of the present disclosure, the complete node data matched for the third relationship type data is subjected to node recursive processing, for example, the complete node data is matched according to the application node table attribute (APP_NODENAME), the graph database nodes with the same node table attribute are marked as nodes of the same node group, and the nodes in the data of the above graph database that simultaneously have the {APP_NODENAME: "application quick payment group"} attribute are marked as nodes of the same node group; the nodes of the same node group can also be subjected to recursive processing, the node group node data belonging to the same application or system is divided into the same application group to obtain an application type node (appnodetype), that is, the nodes of the node group with the same application attribute (APPCI) can also be divided into the same application group, for example, the nodes in the data of the above graph database that have the {APP_NODENAME: "application quick payment group"} attribute are two: application node 0001-R-APP-000685481 and application node 0001-R-APP-000685482, which form an application type node appnodetype1:

[0153] { id: appnodetype1, name: application quick payment group: APCI: 0101-I-APP-000001};

[0154] The nodes with the {APP_NODENAME: "application withdrawal group"} attribute are two: application node 0001-R-APP-000685486 and application node 0001-R-APP-000685487, which form an application type node appnodetype2:

[0155] { id: appnodetype2, name: application withdrawal group: APCI: 0101-I-APP-000001};

[0156] According to the relationship model list in the graph database, a dependency relationship (relation-appnodetype) can be formed:

[0157] { startnode: 0101-I-APP-000001, endnode: appnodetype1};

[0158] { startnode: 0101-I-APP-000001, endnode: appnodetype2}.

[0159] Figure 7 The three-layer architecture of application node→application node type→application formed according to an embodiment of the present disclosure is schematically shown.

[0160] As shown in Figure 7 , based on the recursive nodes, the node group nodes with the same attribute are obtained; according to different applications to which the node group nodes belong, the application type nodes appnodetype1 and appnodetype2 are obtained; according to the relationship model list relationship in the graph database, the applications associated with the application type are obtained, forming a three-layer architecture of application node→application node type→application. The relationship between nodes is displayed through the topology graph, the unified display of nodes with the same attribute is changed, the display form of the data table of the configuration management system is changed, the node association is enhanced, and the display efficiency is improved.

[0161] Figure 8 The schematic diagram when viewing the dynamic relationship based on the three-layer architecture of application node→application node type→application according to the embodiment of the present disclosure is shown.

[0162] As shown in Figure 8 , based on the node data, the first relationship type data, the second relationship type data and the third relationship type data in the graph database, when the specific node group node is displayed in detail, the association relationship of application node→application can be directly displayed, for example, when the application node 0001-R-APP-000685481 in the application type node appnodetype1 and the application node 0001-R-APP-000685486 in the application type node appnodetype2 of the application 0101-I-APP-000001 are viewed in the dynamic relationship, the topology graph can display the association relationship of application node→application; and the association relationship of the third relationship type data combined with the node data can be displayed in real time, for example, when the information collection program Agent collects the third relationship data {sysnodeci:0010-H-SYS-000000070, hostname:pdccbwapbapp001, memMB:3972, cpu:, http:135}, according to the node 0001-R-APP-000685481 matched by “pdccbwapbapp001”, the real-time third relationship data combined with the node data is displayed in the topology graph; the display process of the application node 0001-R-APP-000685486 is similar, which will not be described in detail here; the dynamic relationship between the application nodes displayed in the topology graph can be viewed, for example, if the production call information of ATP-alipay between the application node 0001-R-APP-000685481 and the application node 0001-R-APP-000685486 is not displayed, it indicates that there may be a problem between the applications.

[0163] Based on the method for determining the association relationship, the disclosure further provides a device for determining the association relationship. The following will be described in detail in combination with Figure 9 The device is described in detail.

[0164] Figure 9 The structure block diagram of the device for determining the association relationship according to the embodiment of the disclosure is schematically shown.

[0165] As Figure 9 shown, the device 900 for determining the association relationship of the embodiment includes a first generation module 910, a second generation module 920, and a third generation module 930.

[0166] The first generation module 910 is configured to generate node data, first relationship type data, and second relationship type data according to the to-be-processed data table obtained in the configuration management system. In an embodiment, the first generation module 910 can be configured to perform the operations S210-S220 described above, and details are not described herein again.

[0167] The second generation module 920 is configured to generate third relationship type data according to the production data and the calling data obtained in the server and the application connected to the server. In an embodiment, the second generation module 920 can be configured to perform the operation S230 described above, and details are not described herein again.

[0168] The third generation module 930 is configured to generate a topology graph according to the node data, the first relationship type data, the second relationship type data, and the third relationship type data. In an embodiment, the third generation module 930 can be configured to perform the operation S240 described above, and details are not described herein again.

[0169] According to the embodiment of the disclosure, the first generation module 910 can include:

[0170] The receiving unit 911 is configured to receive the to-be-processed data of the configuration management system, wherein the to-be-processed data includes a to-be-processed data table.

[0171] The determination unit 912 is configured to determine the number of key values and whether the actual attribute is contained according to the to-be-processed data table.

[0172] The generation unit 913 is configured to match the key values and the attribute to generate the node data, the first relationship type data, and the second relationship type data.

[0173] According to the embodiment of the disclosure, the second generation module 920 can include:

[0174] The receiving unit 921 is configured to receive the production data and the calling data obtained in the server and the application connected to the server.

[0175] And a generating unit 922 is configured to collect the data in the production data and the calling data according to a predetermined time interval through the information collection program, and obtain the third relationship type data through a formatting method.

[0176] According to an embodiment of the present disclosure, any of the first generating module 910, the second generating module 920 and the third generating module 930 can be combined in one module, or any of them can be split into multiple modules. Alternatively, at least part of the function of one or more of these modules can be combined with at least part of the function of the other modules and implemented in one module. According to an embodiment of the present disclosure, at least one of the first generating module 910, the second generating module 920 and the third generating module 930 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on chip, a system on substrate, a system on package, an application specific integrated circuit (ASIC), or any other reasonable way of hardware or firmware that can be integrated or packaged with a circuit, or any one of software, hardware and firmware or any appropriate combination of any of them. Alternatively, at least one of the first generating module 910, the second generating module 920 and the third generating module 930 can be at least partially implemented as a computer program module which can perform corresponding functions when it is run.

[0177] Figure 10 A block diagram of an electronic device suitable for implementing the method of determining the association relationship according to an embodiment of the present disclosure is schematically shown.

[0178] As Figure 10 shown, the electronic device 1000 according to an embodiment of the present disclosure includes a processor 1001 which can perform various appropriate actions and processes according to the program stored in a read only memory (ROM) 1002 or the program loaded from a storage portion 1008 into a random access memory (RAM) 1003. The processor 1001 may, for example, include a general purpose microprocessor (such as a CPU), an instruction set processor and / or a related chipset and / or a special purpose microprocessor (such as an application specific integrated circuit (ASIC)), etc. The processor 1001 can also include an on-board memory for cache use. The processor 1001 can include a single processing unit or multiple processing units for performing different actions of the method processes according to an embodiment of the present disclosure.

[0179] In the RAM 1003, various programs and data required for the operation of the electronic device 1000 are stored. The processor 1001, the ROM 1002, and the RAM 1003 are connected to each other via the bus 1004. The processor 1001 performs various operations of the method flow according to the embodiments of the present disclosure by executing the programs in the ROM 1002 and / or the RAM 1003. It should be noted that the programs can also be stored in one or more memories other than the ROM 1002 and the RAM 1003. The processor 1001 can also perform various operations of the method flow according to the embodiments of the present disclosure by executing the programs stored in the one or more memories.

[0180] According to an embodiment of the present disclosure, the electronic device 1000 can further include an input / output (I / O) interface 1005 that is also connected to the bus 1004. The electronic device 1000 can further include one or more of the following components connected to the I / O interface 1005: an input part 1006 including a keyboard, a mouse, etc.; an output part 1007 including a display such as a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage part 1008 including a hard disk, etc.; and a communication part 1009 including a network interface card such as a LAN card, a modem, etc. The communication part 1009 performs communication processing via a network such as the Internet. A drive 1010 is also connected to the I / O interface 1005 as necessary. A removable recording medium 1011 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc. is attached to the drive 1010 as necessary, so that a computer program read out therefrom is installed in the storage part 1008 as necessary.

[0181] The present disclosure also provides a computer readable storage medium, which can be included in the device / apparatus / system described in the above embodiments; or can exist separately without being assembled into the device / apparatus / system. The above computer readable storage medium carries one or more programs, when the one or more programs are executed, the method according to the embodiments of the present disclosure is implemented.

[0182] According to an embodiment of the present disclosure, the computer readable storage medium can be a nonvolatile computer readable storage medium, for example, can include, but is not limited to, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any appropriate combination thereof. In the present disclosure, the computer readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device. For example, according to an embodiment of the present disclosure, the computer readable storage medium can include one or more memories such as the ROM 1002 and / or the RAM 1003 described above and / or one or more memory chips other than the ROM 1002 and the RAM 1003.

[0183] Embodiments of the present disclosure also include a computer program product including a computer program containing program codes for executing the methods shown in the flowcharts. When the computer program product is run in a computer system, the program codes are used to make the computer system implement the item recommendation method provided by the embodiments of the present disclosure.

[0184] The above-described functions defined in the system / device of the embodiments of the present disclosure are performed when the computer program is executed by the processor 1001. According to an embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by computer program modules.

[0185] In one embodiment, the computer program can rely on a tangible storage medium such as an optical storage device, a magnetic storage device, etc. In another embodiment, the computer program can also be transmitted, distributed, and downloaded in the form of a signal on a network medium and installed and downloaded through the communication part 1009 and / or installed from the detachable medium 1011. The program codes contained in the computer program can be transmitted by any appropriate network medium, including but not limited to wireless, wired, etc., or any appropriate combination thereof.

[0186] In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 1009 and / or installed from the detachable medium 1011. When the computer program is executed by the processor 1001, the above-described functions defined in the system of the embodiments of the present disclosure are performed. According to an embodiment of the present disclosure, the system, device, apparatus, module, unit, etc. described above can be implemented by computer program modules.

[0187] According to embodiments of the present disclosure, program code of the computer program for performing the methods provided by the embodiments of the present disclosure can be written in any combination of one or more programming languages, and can be implemented in a computer program product. Specifically, the computer program can be implemented in a high-level procedural and / or object-oriented programming language, and / or in assembly / machine language. The programming language includes, but is not limited to, Java, C++, python, “C” language, or similar programming languages. The program code can execute entirely on the user's computing device, partly on the user's device, and partly on a remote computing device, or entirely on the remote computing device or server. In the latter scenario, the remote computing device can be connected to the user's computing device through any kind of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computing device, such as through the Internet using an Internet Service Provider (ISP).

[0188] The computer program product of the present disclosure can be a computer program product, which is a machine-readable medium (or computer readable medium) having stored therein a sequence of instructions readable by a machine (e.g., a computer). The instructions in the machine-readable medium focus on the function of the computer program (e.g., in the form of a program unit) and on the cooperation behavior between such program units. The program can be distributed over networks coupled to one or more processors or computers, and can be stored on computer readable media including computer program products, hard drives, RAMs, or any other device (internal or external) from which a processor or computer reads incoming data or instructions. In addition to being distributed over the Internet, or over any other publicly or privately accessed network, the aforementioned program product can also be stored in the memory of the respective machine and / or processor.

[0189] Those skilled in the art will understand that features of the various embodiments and / or claims of the present disclosure can be combined or / and integrated with one another, even though such combinations or integrations are not expressly disclosed in the present disclosure. In particular, the features of the various embodiments and / or claims of the present disclosure can be combined and / or integrated with one another in any manner, without departing from the spirit and teachings of the present disclosure. All such combinations and / or integrations are within the scope of the present disclosure.

[0190] The above describes embodiments of the present disclosure. However, these embodiments are merely for illustrative purposes, and are not intended to limit the scope of the present disclosure. Although each embodiment is described above separately, this does not mean that the measures in each embodiment cannot be used advantageously in combination. The scope of the present disclosure is defined by the appended claims and their equivalents. Those skilled in the art can make various substitutions and modifications without departing from the scope of the present disclosure, and these substitutions and modifications should all fall within the scope of the present disclosure.

Claims

1. A method for determining an association relationship, comprising: obtaining a to-be-processed data table from a configuration management system, and obtaining a first model list, a second model list and a third model list according to a preset division rule based on key values and actual attributes of each table in the to-be-processed data table; determining node data, first relationship type data and second relationship type data based on the first model list, the second model list and the third model list, and storing the node data, the first relationship type data and the second relationship type data in a graph database, wherein the first relationship type data and the second relationship type data are determined based on all key values in the second model list and the third model list; the preset division rule further comprises: combining the key values contained in the second model list two by two according to mathematical arrangement, taking the key value in the front of the arrangement order as the starting point and the key value at the end of the arrangement order as the terminal point, defining the relationship between the two key values as a first relationship, and obtaining the first relationship type data; the second relationship type data in the third model list is obtained with the same rule; obtaining third relationship type data based on production data and calling data obtained from a server and an application connected to the server, and storing the third relationship type data in the graph database; and determining an association relationship topology based on the node data, the first relationship type data, the second relationship type data and the third relationship type data, comprising: matching the third relationship type data with the node data in the graph database, attaching the third relationship type data that matches successfully to the node data to obtain complete node data, recursively processing the complete node data with the same attribute to obtain a node group node, recursively processing the node group node with the same attribute to obtain an application group node, so that all the complete node data is classified into the node group node or the application group node, and representing the relationship between the complete node data according to the corresponding starting point, terminal point and relationship type of the key values of the first relationship type data and the second relationship type data to obtain the association relationship topology; obtaining the first model list, the second model list and the third model list based on the to-be-processed data table obtained from the configuration management system comprises: determining the number of key values contained in the to-be-processed data table according to the preset division rule, determining whether the to-be-processed data table contains an actual attribute, and dividing the to-be-processed data table into the first model list, the second model list and the third model list according to the number of key values and whether the to-be-processed data table contains the actual attribute; the actual attribute is an attribute that is defined in advance and has actual meaning among the attributes contained in the to-be-processed data table; and the preset division rule comprises: when there is only one key value and an actual attribute, the to-be-processed data table is divided into the first model list; when the number of key values is greater than or equal to 2 and there is no actual attribute, the to-be-processed data table is divided into the second model list; and when the number of key values is greater than or equal to 2 and there is an actual attribute, the to-be-processed data table is divided into the third model list.

2. The method of claim 1, wherein, the determination of the node data comprises: According to the preset division rule, the first key value and the first attribute in the first model list and the third model list are determined to obtain the node data; the node data is stored in a graph database; and The preset division rule further includes: The first key value is a primary key of the first model list and the third model list, the third model list further contains other key values in addition to the primary key, and the scanned key values are sorted according to the order of scanning; the actual attribute sorting is according to the order of scanning, and the first attribute is scanned first.

3. The method of claim 1, wherein, The third relationship type data includes: The third relationship type data is obtained by collecting data in the production data and the calling data at a predetermined time interval through an information collection program and by formatting the data.

4. An apparatus for determining an association relationship, comprising: A first generation module configured to generate node data, first relationship type data and second relationship type data according to a to-be-processed data table obtained from a configuration management system, wherein the first generation module is configured to perform: The to-be-processed data table obtained from the configuration management system, based on the key value and the actual attribute of each table in the to-be-processed data table, the first model list, the second model list and the third model list are obtained according to the preset division rule, wherein the first model list, the second model list and the third model list are obtained based on the to-be-processed data table obtained from the configuration management system, which includes: determining the number of key values contained in the to-be-processed data table according to the preset division rule, determining whether the to-be-processed data table contains the actual attribute, and dividing the to-be-processed data table into the first model list, the second model list and the third model list according to the number of key values and whether the to-be-processed data table contains the actual attribute; the actual attribute is an attribute with actual meaning defined in advance in the to-be-processed data table; and the preset division rule includes: when there is only one key value and the actual attribute, the to-be-processed data table is divided into the first model list; when the number of key values is greater than or equal to 2 and there is no actual attribute, the to-be-processed data table is divided into the second model list; and when the number of key values is greater than or equal to 2 and there is an actual attribute, the to-be-processed data table is divided into the third model list; Based on the first model list, the second model list and the third model list, the node data, the first relationship type data and the second relationship type data are determined and stored in a graph database, wherein the first relationship type data and the second relationship type data are determined based on all key values in the second model list and the third model list; the preset division rule further includes: the key values contained in the second model list are combined two by two according to mathematical arrangement, the key value in the front of the arrangement order is the starting point, the key value in the back of the arrangement order is the end point, the relationship between the two key values is defined as the first relationship, and the first relationship type data is obtained; the second relationship type data obtained in the third model list has the same rule. a second generation module configured to generate third relationship type data according to the server and the to-be-processed data table obtained from the application connected to the server; and a third generation module configured to generate a correlation relationship topology graph according to the node data, the first relationship type data, the second relationship type data, and the third relationship type data, wherein the third generation module is configured to perform the following operations: matching the third relationship type data with the node data in the graph database, adding the third relationship type data that is successfully matched to the node data to obtain complete node data, performing recursive processing based on the complete node data having the same attribute to obtain a node group node, performing recursive processing based on the node group node having the same attribute to obtain an application group node, so that all the complete node data is classified into the node group node or the application group node, and representing the relationship between the complete node data according to the corresponding start point, end point, and relationship type of the key-value pair of the first relationship type data and the second relationship type data to obtain the correlation relationship topology graph.

5. The apparatus of claim 4, wherein, The first generation module includes: a receiving unit configured to receive to-be-processed data of the configuration management system, wherein the to-be-processed data includes the to-be-processed data table; a determining unit configured to determine the number of key values and whether the actual attribute is contained according to the to-be-processed data table; and a generation unit configured to generate the node data, the first relationship type data, and the second relationship type data. 6.A computer system, comprising: one or more processors; a memory configured to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method of any one of claims 1 to 3. 7.A computer-readable storage medium having stored thereon executable instructions that, when executed by a processor, cause the processor to implement the method of any one of claims 1 to 3.

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