CN115495620A

CN115495620A - Data management method based on graph structure and related equipment

Info

Publication number: CN115495620A
Application number: CN202211189822.XA
Authority: CN
Inventors: 尹邦贵; 胡元
Original assignee: Ping An Technology Shenzhen Co Ltd
Current assignee: Ping An Technology Shenzhen Co Ltd
Priority date: 2022-09-28
Filing date: 2022-09-28
Publication date: 2022-12-20

Abstract

The application provides a data management method and device based on a graph structure, an electronic device and a storage medium, wherein the data management method based on the graph structure comprises the following steps: extracting entity data from a preset relational database; constructing nodes according to the entity data, and combining the nodes according to the incidence relation among the entity data to construct a graph database; acquiring newly added data in the preset relational database in real time, and constructing a newly added node and newly added association relationship according to the newly added data; inserting the newly added nodes into the graph database according to the newly added incidence relation; and checking the legality of each node in the graph database so as to complete the updating of the graph database. The method can convert the relational database into the graph database in real time according to the primary key and the foreign key, so that the efficiency of data management and updating can be improved.

Description

Data management method based on graph structure and related equipment

Technical Field

The present application relates to the field of artificial intelligence technologies, and in particular, to a data management method and apparatus based on a graph structure, an electronic device, and a storage medium.

Background

With the development of information technology, more and more enterprises or organizations tend to manage enterprise data in a digital form to provide reliable data support for intelligent operation and maintenance.

At present, relational databases are generally taken as main databases to perform storage management on data of enterprises and organizations. Relational databases typically require complex model design, maintenance, and long version cycles, are difficult to manage with varying day-to-day data scenarios, and lack solutions for faster delivery requirements. Therefore, it is imperative to find a way to efficiently manage enterprise data.

Disclosure of Invention

In view of the foregoing, it is desirable to provide a data management method based on graph structure and related devices, so as to solve the technical problem of how to improve the efficiency of data management, where the related devices include a data management apparatus based on graph structure, an electronic device and a storage medium.

The embodiment of the application provides a data management method based on a graph structure, which comprises the following steps:

extracting entity data from a preset relational database;

constructing nodes according to the entity data, and combining the nodes according to the incidence relation among the entity data to construct a graph database;

acquiring newly added data in the preset relational database in real time, and constructing a newly added node and newly added association relationship according to the newly added data;

inserting the newly added nodes into the graph database according to the newly added incidence relation;

and checking the legality of each node in the graph database so as to complete the updating of the graph database.

In some embodiments, the predetermined relational database comprises a plurality of data tables, and the extracting entity data from the predetermined relational database comprises:

querying a theme of each data table, wherein the theme is used for representing the category of data stored in the data table;

inquiring a primary key and a foreign key in each data table, taking the data table with the primary key as an entity table, and taking the data table without the primary key as a supplementary attribute table;

regarding each row of data in the entity table, taking the primary key as an entity name, and taking data except the primary key as a first entity attribute of the entity;

taking each line of data in the supplementary attribute table as a second entity attribute of the entity corresponding to the foreign key of the line of data;

unifying a first entity attribute and a second entity attribute of the entity to be used as the entity attribute of the entity;

and taking the theme of the entity table as an entity label of each row of data in the entity table.

In some embodiments, the constructing nodes according to the entity data and combining the nodes according to the incidence relation between the entity data to construct the graph database includes:

combining the entity name, the entity label and the entity attribute to construct a node corresponding to each entity datum;

encoding the entity name to obtain an index corresponding to the node;

if the entity table is provided with the external key, entity data in the entity table and entity data corresponding to the external key have an incidence relation;

and storing the indexes of the nodes corresponding to the entity data with the incidence relation as a key value pair form to construct a graph database.

In some embodiments, the obtaining new data in the preset relational database in real time, and constructing a new node and new association relationship according to the new data includes:

acquiring newly added data in the preset relational database in real time, and inquiring a main key and a foreign key of the newly added data;

if the newly added data comprise the primary key, constructing a newly added node according to the newly added data;

if the newly added data further comprises a foreign key, inquiring the association relationship between the newly added node and each node in the graph database according to the foreign key of the newly added data;

and if the newly added data does not contain the primary key but contains the foreign key, taking the newly added data as the supplementary attribute data of the entity corresponding to the foreign key.

In some embodiments, the inserting the new node into the graph database according to the new association relationship includes:

inquiring the association nodes of the newly added nodes according to the association relationship of the newly added nodes;

and adding the index of the newly added node to the incidence relation key value pair of the incidence node to complete the insertion of the newly added node.

In some embodiments, said checking the validity of each of said nodes in said graph database to complete said updating of said graph database comprises:

a, marking all nodes in the graph database as not accessed;

b, selecting one node from the graph database as a current node, checking the current node according to a preset checking algorithm to obtain a checking result of the current node, and marking the current node as visited, wherein the checking result comprises checking passing and checking failure;

c, inquiring the associated node of the current node, checking the associated node to obtain the checking result of the associated node, and marking the associated node as visited;

d, repeating the steps b to c until all nodes in the graph database are marked as visited, stopping traversing and obtaining the verification results of all nodes;

and e, if the check results of all nodes in the graph database are passed through, updating the graph database, and if the check result of at least one node in the graph database is failed, deleting the newly added node from the graph database and sending a validity alarm.

In some embodiments, the predetermined verification algorithm comprises:

taking the index of the current node as an index to be checked, and simultaneously inquiring all associated nodes of the current node;

sequentially inquiring the association relation key value pair of each association node, and if the index to be checked exists in each association relation key value pair, passing the check;

if at least one of the incidence relation key value pairs does not contain the index to be checked, the check is failed.

An embodiment of the present application further provides a data management apparatus based on a graph structure, where the apparatus includes:

the extraction unit is used for extracting entity data from a preset relational database;

the first construction unit is used for constructing nodes according to the entity data and combining the nodes according to the incidence relation among the entity data to construct a graph database;

the second construction unit is used for acquiring newly-added data in the preset relational database in real time and constructing a newly-added node and newly-added incidence relation according to the newly-added data;

the inserting unit is used for inserting the newly added nodes into the graph database according to the newly added incidence relation;

and the checking unit is used for checking the legality of each node in the graph database so as to complete the updating of the graph database.

An embodiment of the present application further provides an electronic device, where the electronic device includes:

a memory storing computer readable instructions; and

a processor executing computer readable instructions stored in the memory to implement the graph structure based data management method.

Embodiments of the present application further provide a computer-readable storage medium, in which computer-readable instructions are stored, and the computer-readable instructions are executed by a processor in an electronic device to implement the graph structure-based data management method.

According to the data management method based on the graph structure, the entity data and the incidence relation in the relational database are obtained by inquiring the primary key and the foreign key of the data table in the relational database, the nodes corresponding to the entity data are combined by utilizing the incidence relation to complete the construction of the graph database, in order to maintain the stability of the graph database, the newly-added data in the relational database are inserted into the graph database in real time, and the legality of all the nodes in the graph database is checked after the insertion is completed so as to maintain the legality of the whole graph database, so that the efficient data management can be realized.

Drawings

Fig. 1 is a flow chart of a preferred embodiment of a data management method based on a graph structure according to the present application.

Fig. 2 is a functional block diagram of a preferred embodiment of a data management apparatus based on a graph structure according to the present application.

Fig. 3 is a schematic structural diagram of an electronic device according to a preferred embodiment of the data management method based on a graph structure according to the present application.

Fig. 4a is a schematic structural diagram of a server information table according to an embodiment of the present application.

Fig. 4b is a schematic structural diagram of a server supplemental attribute table according to an embodiment of the present application.

Fig. 4c is a schematic structural diagram of a cabinet information table according to an embodiment of the present application.

Fig. 4d is a schematic diagram of a data center floor information table according to an embodiment of the present application.

FIG. 5 is a schematic diagram of a graph database according to an embodiment of the present application.

Detailed Description

For a clearer understanding of the objects, features and advantages of the present application, reference is made to the following detailed description of the present application along with the accompanying drawings and specific examples. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict. In the following description, numerous specific details are set forth to provide a thorough understanding of the present application, and the described embodiments are merely a subset of the embodiments of the present application and are not intended to be a complete embodiment.

Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, features defined as "first", "second", may explicitly or implicitly include one or more of the described features. In the description of the present application, "a plurality" means two or more unless specifically limited otherwise.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the description of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.

The embodiment of the present Application provides a data management method based on a graph structure, which may be applied to one or more electronic devices, where the electronic devices are devices capable of automatically performing numerical calculation and/or information processing according to a preset or stored instruction, and hardware of the electronic devices includes, but is not limited to, a microprocessor, an Application Specific Integrated Circuit (ASIC), a Programmable Gate Array (FPGA), a Digital Signal Processor (DSP), an embedded device, and the like.

The electronic device may be any electronic product capable of performing human-computer interaction with a user, for example, a Personal computer, a tablet computer, a smart phone, a Personal Digital Assistant (PDA), a game machine, an interactive Internet Protocol Television (IPTV), an intelligent wearable device, and the like.

The electronic device may also include a network device and/or a user device. Wherein the network device includes, but is not limited to, a single network server, a server group consisting of a plurality of network servers, or a Cloud Computing (Cloud Computing) based Cloud consisting of a large number of hosts or network servers.

The Network where the electronic device is located includes, but is not limited to, the internet, a wide area Network, a metropolitan area Network, a local area Network, a Virtual Private Network (VPN), and the like.

Fig. 1 is a flow chart of a preferred embodiment of the data management method based on graph structure according to the present application. The order of the steps in the flow chart may be changed and some steps may be omitted according to different needs.

And S10, extracting entity data from the preset relational database.

In an optional embodiment, the preset relational database contains a plurality of data tables, the entity data includes an entity name, an entity tag, and an entity attribute, and the extracting the entity data from the preset relational database includes:

inquiring a primary key and a foreign key in each data table, taking the data table with the primary key as an entity table, and taking the data table with only the foreign key as a supplementary attribute table;

unifying a first entity attribute and a second entity attribute of the entity data as an entity attribute of the entity data;

In this optional embodiment, the preset relational database is configured to store the entity data by using the plurality of data tables, and the preset relational database may be an existing relational database such as a MySQL database, an Oracle database, and the like, which is not limited in this application. The entity may be a server, a switch, a program interface, an organization role, and the like, which is not limited in this application. When the entity is a server, the entity data comprises a server number, a server name, a server creator, server creation time and the like; and when the entity is an organization role, the entity data comprises an organization role name, an organization role number, a department to which the organization role belongs, an organization role position name and the like.

In this alternative embodiment, the data table includes a plurality of rows of data and a plurality of columns of data, and the data table includes a primary key and/or at least one foreign key. Each data table has a topic, and the topic is used for representing the category of data stored in each data table, for example, the topic of the data table may be a server, a switch, a program interface, an organization role, employee information, and the like. The primary key is a column of data in the data table, and is used to represent a unique identifier of each row of data in the data table, and may be used as an entity name of the entity data, for example, when the subject of the data table is a server, the primary key of the data table may be a number of the server; when the theme of the data table is employee information, the main key of the data table can be an employee job number; when the subject of the data table is a program interface, the primary key of the data table may be a program interface number.

The foreign key is a column of data in the data table, and the foreign key is a primary key in another data table, for example, as shown in fig. 4a, it is a schematic structural diagram of an entity table whose topic is "server information", as shown in fig. 4c, it is a schematic structural diagram of an entity table whose topic is "cabinet information", the server information table includes a foreign key "cabinet number", and the "cabinet number" is a primary key in the cabinet information table.

In this alternative embodiment, when the data table includes the primary key, it indicates that each row of data in the data table is entity data in the relational database, and the data table may be used as an entity table, and data in each row of data in the entity table except the primary key may be used as the first entity attribute of the entity. For example, if the primary key in the entity table shown in fig. 4a is a server number, the data in each line of data in the entity table except for the server number may be used as the first entity attribute of each server; if the primary key in the entity table shown in fig. 4c is the cabinet number, the data in each row of data in the entity table except the cabinet number may be used as the first entity attribute of each cabinet.

In this optional embodiment, when the data table does not include a primary key but includes a foreign key, it indicates that each row of data in the data table is not an entity in the relational database, and the data table may be used as a supplementary attribute table, where each row of data in the supplementary attribute table is a second entity attribute of an entity corresponding to the foreign key in each row of data. For example, as shown in fig. 4b, the structure of the server supplemental attribute table is schematically illustrated, where the server supplemental attribute table does not include a primary key and has a foreign key, and the foreign key is a server number, and therefore, an entity corresponding to the foreign key is an entity in the entity table whose server number is the primary key, that is, an entity in the server information table illustrated in fig. 4 a. Therefore, each row of data in the server supplemental attribute table is the second entity attribute of each entity in the server information table shown in fig. 4 a. In this optional embodiment, the subject of each data table in the relational database is queried, and if the data table is an entity table, the subject may be used as an entity tag corresponding to all entity data in the entity table.

Therefore, the extraction of entity data is realized by inquiring the theme, the primary key and the foreign key of the data table in the relational database, and a data basis is provided for the subsequent construction of a graph database.

S11, constructing nodes according to the entity data, and combining the nodes according to the incidence relation among the entity data to construct a graph database.

In an optional embodiment, the constructing nodes according to the entity data and combining the nodes according to the incidence relation between the entity data to construct the graph database includes:

combining the entity name, the entity label and the entity attribute to construct a node corresponding to each entity;

encoding the entity name to obtain an index corresponding to the node;

In this optional embodiment, the entity name, the entity tag, and the entity attribute may be combined according to a preset combination order to construct a node corresponding to each entity, where the node may be in the form of a list, a character string, or the like, which is not limited in this application. The preset combination sequence may be "entity name + entity label + entity attribute".

Illustratively, when the entity name is server a, the entity tag is server, and the entity attribute is "creation time: 10/7/2022, cabinet number: cabinet 1, memory capacity: capacity 1, I/O Rate: 1Gb/s ", the node corresponding to the entity is [ server a, server, creation time: 7/10/2022, cabinet number: cabinet 1, memory capacity: capacity 1,I/O rate: 1Gb/s ].

In this optional embodiment, the entity name may be encoded according to a preset encoding algorithm to serve as an index of a node corresponding to each entity, where the preset encoding algorithm may be an existing encoding algorithm such as a hash encoding algorithm, an ASCII encoding algorithm, and a UTF-8 encoding algorithm, which is not limited in this application.

In this optional embodiment, if the entity table has an external key, the entity data in the entity table and the entity data corresponding to the external key have an association relationship, an index of a node corresponding to the entity data in the entity table may be used as a key, and an index of a node corresponding to the entity data by the external key may be used as a value to construct a key value pair, for example, the entity data in fig. 4a and 4c have an association relationship, and all the key value pairs are stored to obtain a graph database, as shown in fig. 5, which is a schematic structural diagram of the graph database.

In this alternative embodiment, if the entity table does not have a foreign key and the primary key in the entity table is not a foreign key in the rest of the data tables in the preset relational database, it indicates that the node corresponding to the entity in the entity table has no relationship with any node, for example, as shown in fig. 4d, it is a structural diagram of the entity table without a foreign key, the primary key of the table is "floor", and the primary key of the table is not a foreign key in the rest of the data tables, so that the entity in the table has no relationship with any entity, and the node corresponding to the entity in the table is a node in the graph database that exists in isolation, such as node a in the graph database shown in fig. 5.

Therefore, the nodes are constructed based on the entity data in the relational database, and all the nodes are stored into a graph structure by utilizing the incidence relation among the nodes, so that the relational database is converted into a graph database, and the efficiency of subsequent data query can be improved.

And S12, acquiring newly added data in the preset relational database in real time, and constructing a newly added node and newly added association relationship according to the newly added data.

In an optional embodiment, the obtaining new data in the preset relational database in real time, and constructing a new node and new association relationship according to the new data includes:

In this optional embodiment, the new data in the preset relational database is obtained in real time, and the primary key and the foreign key of the new data can be queried according to a preset SQL procedure.

If the newly added data has the primary key, the newly added data is indicated to be entity data, the subject of a data table where the newly added data is located can be inquired to serve as an entity label of the newly added data, the primary key of the newly added data serves as the entity name of the newly added data, data except the primary key serves as the entity attribute of the newly added data, the entity name, the entity label and the entity attribute are combined to construct a newly added node corresponding to the newly added data, and the entity name in the newly added node is encoded according to the preset encoding algorithm to obtain the index of the newly added node.

In this optional embodiment, if the new data further includes a foreign key, the entity data corresponding to the foreign key of the new data may be queried, and the node corresponding to the entity data is recorded as an associated node, the index of the new node may be used as a key, and the index of the associated node may be used as a value to construct a new key value pair, where the new key value pair is used to represent an association relationship between the new node and an existing node in the graph database.

For example, when the newly added data is server information data, the primary key of the newly added data is a server number, and if the newly added data has an external key and the external key is a cabinet number, the entity corresponding to the cabinet number may be queried, that is, the cabinet number is used as an entity in the data table of the primary key, and the node corresponding to the entity is used as the associated node of the newly added node corresponding to the newly added data.

In this optional embodiment, if the newly added data does not have the primary key but has the foreign key, it indicates that the newly added data is not entity data, and the newly added data may be used as supplementary attribute data of an entity corresponding to the foreign key.

Therefore, the main key and the foreign key of the newly added data are inquired to perform different operations on the newly added data, and guidance can be provided for updating data in a subsequent graph database.

And S13, inserting the newly added nodes into the graph database according to the newly added association relationship.

In an optional embodiment, the inserting the new node into the graph database according to the new association relationship includes:

In this optional embodiment, the association relationship of the newly added node is a newly added key value pair, the key of the newly added key value pair is an index of the newly added node, the value of the newly added key value pair is an index of a node having an association relationship with the newly added node, and a node having an association relationship with the newly added node can be queried according to the value of the newly added key value pair to serve as an association node.

In this optional embodiment, a key in the association key value of the association node is an index of the association node, a value in the association key value pair is an index of a node having an association with the association node, and the index of the newly added node is added to the association key value pair of each association node, so as to update the association of the association node, thereby completing the insertion of the newly added node.

Therefore, the insertion operation of the newly added node is completed by updating the incidence relation key value pair of the incidence node, the graph database can be updated in real time according to the updating of the entity data in the relational database, and the integrity of the data in the graph database can be ensured.

S14, checking the legality of each node in the graph database so as to complete the updating of the graph database.

In an optional embodiment, said checking the validity of each of said nodes in said graph database to complete said updating of said graph database comprises:

a, marking all nodes in the graph database as not accessed;

and e, if the check results of all nodes in the graph database are passed through, updating the graph database is completed, if the check result of at least one node in the graph database is failed, the error is generated in the process of inserting the newly added node into the graph database, so that the state of the graph database needs to be rolled back to the state before the newly added node is added, namely the newly added node is deleted from the graph database, and a legality alarm is sent to developers of the graph database to remind the developers to investigate the error reason. In an optional embodiment, the predetermined verification algorithm includes:

sequentially inquiring the association relationship key value pair of each association node, and if the index to be verified exists in each association relationship key value pair, passing the verification;

Therefore, the data of each node in the graph database is checked to obtain a check result, and the validity of the association relation of each node in the graph database is evaluated in real time through the check result, so that the stability of the graph database can be improved.

The data management method based on the graph structure obtains the entity data and the incidence relation in the relational database by inquiring the main key and the foreign key of the data table in the relational database, and combines the nodes corresponding to the entity data by utilizing the incidence relation so as to complete the construction of the graph database.

Fig. 2 is a functional block diagram of a preferred embodiment of a data management device based on a graph structure according to an embodiment of the present application. The data management apparatus 11 based on the graph structure includes an extraction unit 110, a first construction unit 111, a second construction unit 112, an insertion unit 113, and a verification unit 114. The module/unit referred to in this application refers to a series of computer program segments that can be executed by the processor 13 and that can perform a fixed function, and that are stored in the memory 12. In the present embodiment, the functions of the modules/units will be described in detail in the following embodiments.

In an alternative embodiment, the extraction unit 110 is used for extracting the entity data from the preset relational database.

In an optional embodiment, the preset relational database includes a plurality of data tables, and the extracting entity data from the preset relational database includes:

In this optional embodiment, the preset relational database is configured to store the entity data by using the plurality of data tables, and the preset relational database may be an existing relational database such as a MySQL database, an Oracle database, and the like, which is not limited in this application. The entity may be a server, a switch, a program interface, an organization role, etc., which is not limited in this application. When the entity is a server, the entity data comprises a server number, a server name, a server creator, server creation time and the like; when the entity is an organization role, the entity data comprises an organization role name, an organization role number, a department to which the organization role belongs, an organization role position name and the like.

In this alternative embodiment, the data table includes a plurality of rows of data and a plurality of columns of data, and the data table includes a primary key and/or at least one foreign key. Each data table has a theme used for representing the category of data stored in each data table, for example, the theme of the data table may be a server, a switch, a program interface, an organization role, employee information, and the like. The primary key is a column of data in the data table, and is used to represent a unique identifier of each row of data in the data table, and may be used as an entity name of the entity data, for example, when the subject of the data table is a server, the primary key of the data table may be a number of the server; when the theme of the data table is employee information, the main key of the data table can be an employee job number; when the subject of the data table is a program interface, the primary key of the data table may be a program interface number.

The foreign key is a column of data in the data table, and the foreign key is a primary key in another data table, for example, as shown in fig. 4a, a structural diagram of an entity table with a topic of "server information" is shown, as shown in fig. 4c, a structural diagram of an entity table with a topic of "cabinet information" is shown, the server information table includes a foreign key "cabinet number", and the "cabinet number" is a primary key in the cabinet information table.

In this optional embodiment, when the data table does not include a primary key but includes a foreign key, it indicates that each row of data in the data table is not an entity in the relational database, and the data table may be used as a supplementary attribute table, where each row of data in the supplementary attribute table is a second entity attribute of an entity corresponding to the foreign key in each row of data. For example, as shown in fig. 4b, the structure of the server supplemental attribute table is schematically illustrated, where the server supplemental attribute table does not include a primary key and has a foreign key, and the foreign key is a server number, and therefore, an entity corresponding to the foreign key is an entity in an entity table with the server number as the primary key, that is, an entity in the server information table shown in fig. 4 a. Therefore, each row of data in the server supplemental attribute table is the second entity attribute of each entity in the server information table shown in fig. 4 a. In this optional embodiment, the subject of each data table in the relational database is queried, and if the data table is an entity table, the subject may be used as an entity tag corresponding to all entity data in the entity table.

In an alternative embodiment, the first constructing unit 111 is configured to construct nodes according to the entity data, and combine the nodes according to the association relationship between the entity data to construct the graph database.

encoding the entity name to obtain an index corresponding to the node;

Illustratively, when the entity name is server a, the entity tag is server, and the entity attribute is "creation time: 10 months 7 in 2022, cabinet number: cabinet 1, memory capacity: capacity 1, I/O Rate: 1Gb/s ", then the node corresponding to the entity is [ server a, server, creation time: 7/10/2022, cabinet number: cabinet 1, memory capacity: capacity 1,I/O rate: 1Gb/s ].

In this optional embodiment, the entity name may be encoded according to a preset encoding algorithm to serve as an index of a node corresponding to each entity, where the preset encoding algorithm may be an existing encoding algorithm such as a hash algorithm, an ASCII encoding algorithm, and a UTF-8 encoding algorithm, and the present application does not limit this.

In this alternative embodiment, if the entity table does not have a foreign key and the primary key in the entity table is not a foreign key in the rest of the data tables in the preset relational database, it indicates that the node corresponding to the entity in the entity table is not related to any node, for example, as shown in fig. 4d, it is a schematic structural diagram of the entity table without a foreign key, the primary key of the table is "floor", and the primary key of the table is not a foreign key in the rest of the data tables, so that the entity in the table is not related to any entity, and the node corresponding to the entity in the table is an isolated node in the graph database, such as node a in the graph database shown in fig. 5.

In an optional embodiment, the second constructing unit 112 is configured to obtain new data in the preset relational database in real time, and construct a new node and a new association relationship according to the new data.

In this optional embodiment, if the newly added data further includes an external key, the entity data corresponding to the external key of the newly added data may be queried, and the node corresponding to the entity data is recorded as an associated node, the index of the newly added node may be used as a key, and the index of the associated node may be used as a value to construct a newly added key value pair, where the newly added key value pair is used to represent an association relationship between the newly added node and an existing node in the graph database.

In an optional embodiment, the inserting unit 113 is configured to insert the new node into the graph database according to the new association relationship.

inquiring the association node of the newly added node according to the association relationship of the newly added node;

In an alternative embodiment, the verification unit 114 is configured to verify the validity of each node in the graph database to complete the update of the graph database.

a, marking all nodes in the graph database as not accessed;

d, repeating the steps b to c until all the nodes in the graph database are marked as visited, stopping traversing and obtaining the verification results of all the nodes;

Fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application. The electronic device 1 comprises a memory 12 and a processor 13. The memory 12 is used for storing computer readable instructions, and the processor 13 is used for executing the computer readable instructions stored in the memory to implement the data management method based on the graph structure according to any one of the above embodiments.

In an alternative embodiment, the electronic device 1 further comprises a bus, a computer program stored in the memory 12 and executable on the processor 13, such as a data management program based on a graph structure.

Fig. 3 only shows the electronic device 1 with components 12-13, and it will be understood by a person skilled in the art that the structure shown in fig. 3 does not constitute a limitation of the electronic device 1, and may comprise fewer or more components than shown, or a combination of certain components, or a different arrangement of components.

In conjunction with fig. 1, the memory 12 in the electronic device 1 stores a plurality of computer-readable instructions to implement a data management method based on a graph structure, and the processor 13 can execute the plurality of instructions to implement:

extracting entity data from a preset relational database;

acquiring new data in the preset relational database in real time, and constructing a new node and a new incidence relation according to the new data;

Specifically, the specific implementation method of the instruction by the processor 13 may refer to the description of the relevant steps in the embodiment corresponding to fig. 1, which is not described herein again.

Memory 12 includes at least one type of readable storage medium, which may be non-volatile or volatile. The readable storage medium includes flash memory, removable hard disks, multimedia cards, card type memory (e.g., SD or DX memory, etc.), magnetic memory, magnetic disks, optical disks, etc. The memory 12 may in some embodiments be an internal storage unit of the electronic device 1, for example a removable hard disk of the electronic device 1. The memory 12 may also be an external storage device of the electronic device 1 in other embodiments, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like provided on the electronic device 1. Further, the memory 12 may also include both an internal storage unit and an external storage device of the electronic device 1. The memory 12 can be used not only for storing application software installed in the electronic device 1 and various types of data, such as codes of a data management program based on a graph structure, etc., but also for temporarily storing data that has been output or is to be output.

The processor 13 may be composed of an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or may be composed of a plurality of integrated circuits packaged with the same or different functions, including one or more Central Processing Units (CPUs), microprocessors, digital Processing chips, graphics processors, and combinations of various control chips. The processor 13 is a Control Unit (Control Unit) of the electronic device 1, connects various components of the electronic device 1 by various interfaces and lines, and executes various functions of the electronic device 1 and processes data by running or executing programs or modules stored in the memory 12 (for example, executing a data management program based on a graph structure, etc.), and calling data stored in the memory 12.

The processor 13 executes an operating system of the electronic device 1 and various types of application programs installed. The processor 13 executes the application program to implement the steps in the various graph structure-based data management method embodiments described above, such as the steps shown in fig. 1.

Illustratively, the computer program may be partitioned into one or more modules/units that are stored in the memory 12 and executed by the processor 13 to accomplish the present application. The one or more modules/units may be a series of computer-readable instruction segments capable of performing certain functions, which are used to describe the execution of the computer program in the electronic device 1. For example, the computer program may be divided into an extraction unit 110, a first construction unit 111, a second construction unit 112, an insertion unit 113, a verification unit 114.

The integrated unit implemented in the form of a software functional module may be stored in a computer-readable storage medium. The software functional module is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a computer device, or a network device) or a processor (processor) to execute parts of the data management method based on the graph structure according to the embodiments of the present application.

The integrated modules/units of the electronic device 1 may be stored in a computer-readable storage medium if they are implemented in the form of software functional units and sold or used as separate products. Based on such understanding, all or part of the processes in the methods of the embodiments described above may be implemented by a computer program, which may be stored in a computer-readable storage medium and executed by a processor, to implement the steps of the embodiments of the methods described above.

Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U-disk, removable hard disk, magnetic disk, optical disk, computer Memory, read-Only Memory (ROM), random-access Memory and other Memory, etc.

Further, the computer-readable storage medium may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data created according to the use of the blockchain node, and the like.

The block chain referred by the application is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.

The bus may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one arrow is shown in FIG. 3, but this does not indicate only one bus or one type of bus. The bus is arranged to enable connected communication between the memory 12 and at least one processor 13 or the like.

An embodiment of the present application further provides a computer-readable storage medium (not shown), where the computer-readable storage medium stores computer-readable instructions, and the computer-readable instructions are executed by a processor in an electronic device to implement the data management method based on a graph structure according to any of the foregoing embodiments.

In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.

The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.

In addition, functional modules in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.

Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the specification may also be implemented by one unit or means through software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.

Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present application and not for limiting, and although the present application is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions can be made on the technical solutions of the present application without departing from the spirit and scope of the technical solutions of the present application.

Claims

1. A method for data management based on graph structure, the method comprising:

extracting entity data from a preset relational database;

2. The graph structure-based data management method according to claim 1, wherein the predetermined relational database comprises a plurality of data tables, and the extracting entity data from the predetermined relational database comprises:

3. The graph structure-based data management method according to claim 2, wherein said constructing nodes from the entity data and combining the nodes according to the association relationship between the entity data to construct a graph database comprises:

encoding the entity name to obtain an index corresponding to the node;

4. The graph structure-based data management method of claim 1, wherein the obtaining new data in the preset relational database in real time and constructing a new node and new association relationship according to the new data comprises:

5. The graph structure-based data management method according to claim 1, wherein the inserting the new node into the graph database according to the new association relationship comprises:

6. The graph structure-based data management method according to claim 1, wherein said verifying the validity of each of said nodes in said graph database to complete updating of said graph database comprises:

a, marking all nodes in the graph database as not accessed;

7. The graph structure-based data management method according to claim 6, wherein the preset verification algorithm comprises:

8. An apparatus for managing data based on a graph structure, the apparatus comprising:

9. An electronic device, characterized in that the electronic device comprises:

a memory storing computer readable instructions; and

a processor executing computer readable instructions stored in the memory to implement the graph structure based data management method of any one of claims 1 to 7.

10. A computer-readable storage medium characterized by: the computer-readable storage medium stores therein computer-readable instructions which are executed by a processor in an electronic device to implement the graph structure-based data management method according to any one of claims 1 to 7.