CN116383194A

CN116383194A - Asset query system, method, electronic device and storage medium

Info

Publication number: CN116383194A
Application number: CN202211684611.3A
Authority: CN
Inventors: 方绪鹏; 郭超; 李洛刚; 罗盼; 王睿
Original assignee: China Electronics Industry Engineering Co ltd; Secworld Information Technology Beijing Co Ltd
Current assignee: China Electronics Industry Engineering Co ltd; Secworld Information Technology Beijing Co Ltd
Priority date: 2022-12-27
Filing date: 2022-12-27
Publication date: 2023-07-04

Abstract

The application relates to an asset query system, an asset query method, an electronic device and a storage medium, wherein the system comprises: an asset model for building a logical data architecture of an asset; the database is used for storing the assets and the association relations among the assets in the logic data architecture in the form of a graph structure; and the query interface is used for calling the assets corresponding to the first target node and the second target node from the database according to the first target node and the second target node determined by the asset query request to obtain an asset query result. According to the scheme provided by the application, the association relation between the assets in the logical data architecture of the assets can be stored in the form of a graph structure, the query interface directly retrieves the corresponding assets from the database according to the first target node and the second target node determined by the asset query request, and the asset query result is obtained.

Description

Asset query system, method, electronic device and storage medium

Technical Field

The present disclosure relates to the field of data processing technologies, and in particular, to an asset query system, an asset query method, an electronic device, and a storage medium.

Background

Asset inquiry is an important link in the asset management process, and the efficiency of asset inquiry directly affects the timeliness of asset management work.

In the related technology, because the assets are generally stored through a relational database, the relational database cannot clearly define and express the association relationship among the assets of each level, the assets are required to be queried layer by layer in sequence according to the hierarchical relationship in the process of querying the assets, the process of querying the assets is relatively complicated, and the querying efficiency is low.

It can be seen that in the related art, the method of using the relational database to realize the asset query has the technical problem of low query efficiency.

Disclosure of Invention

In order to overcome the problems in the related art, the application provides an asset query system, an asset query method, electronic equipment and a storage medium.

A first aspect of the present application provides an asset querying system, the system comprising:

an asset model for building a logical data architecture of an asset; wherein the logical data architecture comprises a plurality of levels of assets and associations between the assets of each level;

a database for storing the assets and the association relationship between the assets in the logical data architecture in the form of a graph structure;

the query interface is used for calling the assets corresponding to the first target node and the second target node from the database according to the first target node and the second target node determined by the asset query request to obtain an asset query result;

wherein the first target node and the second target node both belong to graph nodes in the graph structure.

According to the asset query system provided by the application, the asset model is specifically used for:

creating identification information of the asset based on a preset rule; the preset rule is used for defining a creation mode of the identification information;

identifying the assets of the multiple levels based on the identification information of the assets;

and determining association relations among the assets of each level, and associating the assets of the multiple levels based on the association relations to obtain the logic data architecture.

According to the asset query system provided by the application, the database is specifically used for:

and storing the assets as graph nodes of the graph structure, and storing the association relations among the assets of each level as edges of the graph structure.

According to the asset query system provided by the application, the query interface is specifically used for:

determining at least one data link taking the first target node as a starting point and the second target node as an ending point from the graph structure according to the first target node and the second target node determined by the asset inquiry request;

and taking the assets stored in at least one data link as the asset inquiry results.

A second aspect of the present application provides an asset querying method, the method being based on an asset querying system as described above, the method comprising:

receiving an asset inquiry request sent by a request end;

determining a first target node and a second target node according to the asset inquiry request;

the assets corresponding to the first target node and the second target node are called from the database through the query interface, and an asset query result is obtained;

and sending the asset inquiry result to the request end.

According to the asset query method provided by the application, the method for retrieving the assets corresponding to the first target node and the second target node from the database through the query interface to obtain an asset query result includes:

determining at least one data link taking the first target node as a starting point and the second target node as an ending point from the graph structure;

According to the asset query method provided by the application, the method further comprises the following steps:

determining a data storage range of the database based on graph nodes at edge positions in the graph structure;

and sending the information containing the data storage range to the request end.

According to the asset query method provided by the application, the asset query request is generated through the following processes:

determining assets to be queried; wherein the asset to be queried is within the data storage range;

and generating the asset inquiry request based on the asset to be inquired.

A third aspect of the present application provides an electronic device, comprising:

a processor; and

a memory having executable code stored thereon that, when executed by the processor, causes the processor to perform the asset querying method as described above.

A fourth aspect of the present application provides a non-transitory machine-readable storage medium having stored thereon executable code, which when executed by a processor of an electronic device, causes the processor to perform the asset querying method as described above.

The technical scheme that this application provided can include following beneficial effect: by storing the assets and the association relations among the assets in the logical data architecture of the assets in the database in the form of a graph structure, the query interface can directly call the assets corresponding to the first target node and the second target node from the database according to the first target node and the second target node determined by the asset query request to obtain an asset query result, and compared with an asset query mode based on a relational database, the query efficiency is effectively improved.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.

Drawings

The foregoing and other objects, features and advantages of the application will be apparent from the following more particular descriptions of exemplary embodiments of the application as illustrated in the accompanying drawings wherein like reference numbers generally represent like parts throughout the exemplary embodiments of the application.

FIG. 1 is a schematic diagram of an asset querying system shown in an embodiment of the present application;

FIG. 2 is a schematic diagram of the structure of an asset model shown in embodiments of the present application;

FIG. 3 is a schematic diagram of a relationship model in a product supply scenario according to an embodiment of the present disclosure;

FIG. 4 is a schematic diagram of a product-supply scenario in accordance with an embodiment of the present application;

FIG. 5 is a flow diagram of an asset querying method shown in an embodiment of the present application;

fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

Preferred embodiments of the present application will be described in more detail below with reference to the accompanying drawings. While the preferred embodiments of the present application are shown in the drawings, it should be understood that the present application may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

The terminology used in the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the present application. As used in this application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any or all possible combinations of one or more of the associated listed items.

It should be understood that although the terms "first," "second," "third," etc. may be used herein to describe various information, these information should not be limited by these terms. These terms are only used to distinguish one type of information from another. For example, a first message may also be referred to as a second message, and similarly, a second message may also be referred to as a first message, without departing from the scope of the present application. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. In the description of the present application, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.

The embodiment of the application mainly aims at an application scene of asset query in the asset management process, in particular to an asset query scene in the field of network security, and in the related technology, an asset query system has at least three problems:

first, asset models are generally customized according to self understanding or business needs of a certain customer, and have no unified standards and architecture;

secondly, the bottom layer stores the data related to the assets by adopting a relational database, so that the multi-level relation among the assets is difficult to clearly express, and in the multi-level asset inquiry process, the inquiry is required to be carried out level by level according to the level relation of the assets, so that the realization flow is complex and the inquiry efficiency is low;

thirdly, the query interface adopts the common Restful standard, and the front end needs to carry out data assembly.

It can be seen that in the related art, the asset query mode has the problems of complex implementation process and low query efficiency.

Aiming at the problems, the embodiment of the application provides an asset query system which can effectively solve the problem of low asset query efficiency and realize convenient and efficient query of assets.

The following describes in detail the technical schemes of the asset query system, the method, the electronic device and the storage medium provided in the embodiments of the present application with reference to fig. 1 to 6.

FIG. 1 is a schematic diagram of an asset querying system as shown in an embodiment of the present application.

Referring to fig. 1, the asset query system provided in this embodiment specifically includes:

an asset model 101 for building a logical data architecture of an asset; the logic data architecture comprises a plurality of levels of assets and association relations among the assets of each level;

a database 102 for storing assets and association relations between the assets in the logical data architecture in the form of a graph structure;

a query interface 103, configured to retrieve, from a database, assets corresponding to the first target node and the second target node according to the first target node and the second target node determined by the asset query request, to obtain an asset query result;

the first target node and the second target node both belong to graph nodes in the graph structure.

In this embodiment, an asset refers to information or resources valuable to an organization, including websites, business systems, devices, software, services, and the like, and in the field of network security refers to an object of information security management.

The asset model 101 is mainly used for identifying and associating assets, and establishing a logical data architecture of the assets, wherein the logical data architecture comprises assets of all levels and association relations among the assets of all levels.

The database 102 stores the assets of each level and the association relations between the assets of each level in the logical data architecture mainly in the form of a graph structure, and the association relations among the entities, the attributes and the assets of the assets can be modeled as graphs in the storage mode of the graph structure, so that the association relations among the assets of each level are intuitively displayed.

The query interface 103 can directly call the assets corresponding to the first target node and the second target node from the database 102 according to the first target node and the second target node determined by the asset query request, so that simple and rapid query of the target assets in a complex asset hierarchy can be realized, and an efficient query function of the assets is realized.

It can be seen that, in the embodiment of the present application, by storing the assets of each level in the logical data architecture and the association relationships between the assets of each level in the form of a graph structure, in the query link, after determining the first target node and the second target node according to the asset query request, the assets corresponding to the first target node and the second target node can be directly obtained, without a level-by-level query procedure, and the query efficiency is significantly improved.

In an exemplary embodiment, the asset model 101 may be specifically used to:

establishing identification information of the asset based on a preset rule; the method comprises the steps that a preset rule is used for defining a creation mode of identification information;

identifying and obtaining a plurality of layers of assets based on the identification information of the assets;

and determining association relations among the assets of each level, and associating the assets of the multiple levels based on the association relations to obtain a logic data architecture.

In order to solve the problem that the asset model in the related art does not have unified standards and architectures, in the present embodiment, in the asset model 101, first, the identification information of the asset is created according to the preset rule, and the asset of multiple levels can be identified based on the identification information of the asset, that is, the asset model identifies the asset through the unified standards.

Specifically, the present embodiment performs asset identification and association based on an asset classification standard of NIST (National Institute of Standards and Technology ) 7693, and the asset classification standard of NIST 7693 provides a method for identifying assets based on known characteristics and information of the assets, so that a logical data architecture of the assets can be established based on a unified standard, and unified configuration of identification standards and architecture of asset models is realized.

FIG. 2 shows an example of an asset model, which mainly includes, in ITs logical data architecture, an Organization asset, an IT asset, a Cloud Platform (Cloud Platform), a Computer Room (Computer Room), etc., where the Organization asset includes an Organization (Organization) list and a Person (Person) list, and the Person list is part of the Organization list, where data such as an Organization name (Organization Name), a mailbox Address (email Address), a telephone Number (telephone Number), and a web site (website Url) are specifically related to the Organization list; the personal list specifically relates to data such as personal Name (person Name), email Address (email Address), telephone Number (phone Number), birthday (birthdate), etc.

The IT asset comprises a Computing Device (Computing Device) list, a System (System) list, a Software (Software) list, a server (Service) list, a Network (Network) list, a Database (Database) list and a Website (Website) list, wherein the Computing Device respectively belongs to a machine room and an organization, a person is an administrator of the Computing Device and the System, the Computing Device is connected to the System, the System is connected to the Network, the Software is installed on the Computing Device, and the server provides services for the Database and the Website;

data such as an identification Name (distinguish Name), a CPE (customer premise equipment), a domain Name (fqdn), a host Name (host Name), a main board identification (mother board guid), a connection relation (connections), an administrator (administor of Person) and the like are specifically related to the computing device list; information related to a system Name (system Name) and version (version) in a system list; the software list specifically relates to information such as equipment identification (installation ID), CPE (license) and the like; the service list specifically relates to information such as a host (host), a port (port), a port Range (port Range), a protocol (protocol) and the like; the network list specifically relates to information such as network Name (network Name), IP network Range (IP Net Range), and location (locations).

In addition, the network list has an association relationship with a Location (Locations) and an IP network Range (IP Net Range) outside the IT asset list, the Location has an association relationship with a Location Point (Location Point) and a Location area (Location Region), and the Location Point list specifically relates to information such as latitude (latitudes), longitude (longitudes), altitude (elevation), radius (radius) and the like; information such as a region Name (region Name) is specifically related in the list of the location region; the list of IP network ranges specifically refers to information such as a range start point (IP-net-range-start) and a range end point (IP-net-range-end).

The computing device list also has an association with connectors (Connections) outside the IT asset list, and the server list also has an association with Port ranges (Port ranges) outside the IT asset list and hosts (Host).

It can be seen that the logical data architecture in the overall asset model can reflect assets of different levels and associations between assets.

In an exemplary embodiment, database 102 may be specifically configured to:

the assets are stored as graph nodes of the graph structure, and the association relationships among the assets of each level are stored as edges of the graph structure.

The database 102 in this embodiment may be understood as a graph database, which is a database that uses graph structures to perform semantic queries, where the database 102 may store assets in the form of graph nodes in the form of graph structures, and store relationships between assets in the form of edges.

Fig. 3 and 4 illustrate a relational model structure corresponding to a relational database and a graph model structure corresponding to a graph database in a product supply scene, respectively.

Referring to FIG. 3, the relationship model shows the relationship between a vendor (supporters) list, a Products (Products) list, order details (Order details) list, category (Categories) list, employee zone (Employee Territories) list, employee (Employees) list, zone (Territories) list, region (regions) list, orders (Orders) list, customers (Customers) list, shippers (Shippers) list, customer requirements (Customer Demo) list, and Customer satisfaction (Customer Demographics) list;

the vendor list specifically includes information such as vendor ID, company Name, contact Title, address, city, region, postal Code, country, telephone, fax, and homepage.

The Product list specifically includes information such as Product identifier (Product ID), product Name (Product Name), vendor identifier (provider ID), category identifier (Category ID), unit (quantity Per Unit), unit Price (Unit Price), stock Unit (Units In Stock), unit Order (Units On Order), reorder Level (Reorder Level), and terminated business (Discontinued).

The Category list specifically includes information such as Category identification (Category ID), category Name (Category Name), description (Description), and Picture (Picture).

The Order list specifically includes information such as Order identification (Order ID), customer identification (Customer ID), employee identification (Employee ID), order Date (Order Date), required Date (Required Date), delivery Date (Shipped Date), shipping mode (Shipvia), shipping fee (Freight), shipping Name (shipname), shipping Address (shipaddress), shipping City (shipcity), shipping Region (shipregion), shipping Postal Code (shippost Code), and shipping Country (shipcounty).

The Order detail list specifically contains Order identification (Order ID), product identification (Product ID), unit Price (Unit Price), quantity (Quantity), discount (discount), and other information.

The client list specifically contains information such as client identification (Customer ID), company Name (Company Name), contact Name (Contact Name), contact Title (Contact Title), address (Address), city (City), region (Region), postal Code (post Code), country (Country), telephone (Phone), fax (Fax), and the like.

The client requirement list specifically contains information such as client identification (client ID) and client Type identification (client Type ID).

The Customer satisfaction list specifically contains information such as Customer Type identification (Customer Type ID) and Customer description (Customer Desc).

The Shipper list specifically contains information such as Shipper identification (Shipper ID), company Name (Company Name), telephone (Phone), and the like.

The Employee list specifically includes information such as Employee ID (Employee ID), last Name (Last Name), first Name (First Name), job position (Title), title (Title Of Cour Tesy), birth Date (Birth Date), date of employment (Hire Date), address (Address), city (City), region (Region), postal Code (post Code), country (Country), base Phone (Home Phone), extension (Extension), photo (Photo), notes (Notes), report object (report To), and picture Path (Photo Path).

The Employee area list specifically comprises Employee identification (Employee ID) and area identification (Territory ID); the Region list specifically comprises a Region identifier (Territory ID), a Region description (Territory Description) and a Region identifier (Region ID); the Region list specifically includes a Region identifier (Region ID) and a Region description (Region Description).

As can be seen from the relationship model shown in FIG. 3, the hierarchical relationships of the resource-related data stored in the relationship model are complex in representation and difficult to clearly express the multi-level relationships between the assets.

Referring to fig. 4, for the above-mentioned product supply scenario, the association relationship between the assets of each layer may be clearly expressed in the form of nodes and edges in the database provided in this embodiment in the form of a graph model through a graph structure. As shown in fig. 4, five graph nodes including Employee (Employee), order (Order), product (Product), provider (provider) and Category (Category) are involved in the graph model, and the association relationship among the five graph nodes is expressed in the form of edges, wherein the Employee nodes and the Order nodes have a selling relationship and are connected through SOLD edges; the order nodes and the PRODUCT nodes are connected through the PRODUCT edges; the product nodes and the provider nodes are in a supply relation and are connected through SUPPLIES edges; the product nodes and the category nodes have a subordinate relation and are connected through a part_of edge.

By comparing the relationship model shown in fig. 3 with the graph model shown in fig. 4, it can be seen that the database in this embodiment can more intuitively display the association relationship between the assets in the form of the graph structure, and can clearly display the association relationship between the assets for the highly interconnected assets.

In an exemplary embodiment, the query interface 103 may be specifically configured to:

determining at least one data link taking the first target node as a starting point and the second target node as an ending point from a graph structure according to the first target node and the second target node determined by the asset inquiry request;

and taking the assets stored in at least one data link as asset inquiry results.

In this embodiment, graphQL is an open source data query operation language created by facing API (Application Program Interface ) and a corresponding running environment, and is used as a query interface of the asset query system. The conceptual model of the GraphQL is an entity diagram, and is naturally matched with the database and the asset model in the embodiment, and the query interface is characterized in that the query process is strong in flexibility, the GraphQL is used as the query interface, the query requirement of returning multi-layer data at one time can be met, and the asset query process is more flexible and efficient in comparison with the mode of querying multi-layer data by using a Restful HTTP interface in the related art.

Taking a website under a certain system in the asset model shown in fig. 2 as an example, if the query is required to be performed step by step according to the query mode based on the relational database in sequence according to the query sequence of the system, the device, the software, the service and the website, specifically, taking the query mode based on the relational database as an example by using the SQL language, the key codes are as follows:

“SELECT p.ProductName

FROM Product AS p JOIN ProductCategory pc ON(p.CategoryID＝pc.CategoryID ANDpc.Category Name＝"Dairy Products")

JOIN ProductCategory pc1ON(p.CategoryID＝pc1.CategoryID

JOIN ProductCategory pc2ON(pc2.ParentID＝pc2.CategoryID AND pc2.Category Name＝"Dairy Products")

JOIN ProductCategory pc3ON(p.CategoryID＝pc3.CategoryID)

JOIN ProductCategory pc4ON(pc3.ParentID＝pc4.CategoryID)

JOIN ProductCategory pc5ON(pc4.ParentID＝pc5.CategoryID AND pc5.CategoryName＝"Dairy Products")”。

if the query mode based on the graph structure can be used as the first target node, the website can be used as the second target node, the data link taking the system as the starting point and the website as the ending point can be directly determined from the graph structure, specifically, the query mode based on the graph structure is used for realizing the graph query language cytor as an example, and the key codes are as follows:

“MATCH(p:Product)-[:CATEGORY)->

(1:ProductCategory)-[:PARENT*θ..]-(:ProductCategory{name:"Dairy Products"})RETURN p.name”。

by comparing the key codes corresponding to the SQL language with the key codes corresponding to the Cypher language, the Cypher language (namely the graph query language) is simpler than the SQL language, so that the asset query system provided by the embodiment can more intuitively explain that the asset query system does not need a step-by-step query process, corresponding data links can be directly determined from the graph structure according to the first target node and the second target node, corresponding query results are directly obtained, and the query efficiency is effectively improved.

Meanwhile, the database in this embodiment may define the capability range provided to the front end data through Schema, and when the capability range is described in terms of the graph structure, the database may determine the assets of the highest level and the lowest level in the graph structure through the graph nodes located at two ends of each data link in the graph structure, that is, the data range that can be described by the graph structure, where the front end may perform data query in the range, and the rear end does not need to perform code change, so as to improve the effectiveness and accuracy of asset query.

Corresponding to the foregoing embodiments of the asset query system, the embodiments of the present application further provide an asset query method, an electronic device, and corresponding embodiments.

Fig. 5 is a flow chart illustrating an asset query method according to an embodiment of the present application, which is implemented based on the asset query system described above.

Referring to fig. 5, the asset query method provided in the embodiment of the present application specifically includes:

step 501: receiving an asset inquiry request sent by a request end;

step 502: determining a first target node and a second target node according to the asset inquiry request;

step 503: the method comprises the steps of calling assets corresponding to a first target node and a second target node from a database through a query interface to obtain asset query results;

step 504: and sending the asset inquiry result to the request end.

The execution subject of the asset query method in this embodiment may be a processor in the asset query system, or may be a processor deployed outside the asset query system. The request end refers to an end initiating an asset query request, taking an example that the asset query request is a target website under a query target system, in this case, a first target node is the target system, a second target node is the target website, the first target node and the second target node both belong to graph nodes in a graph structure in a database, and after the first target node and the second target node are determined, assets corresponding to the first target node and the second target node can be directly determined from the graph structure in the database, so that convenient and efficient asset query is realized.

In an exemplary embodiment, the retrieving, through the query interface, the asset corresponding to the first target node and the second target node from the database to obtain the asset query result may specifically include:

determining at least one data link taking a first target node as a starting point and a second target node as an ending point from the graph structure;

In this embodiment, after asset data is stored in a graph structure, each layer of assets is expressed in a graph node, each graph node is connected by an edge that can represent an association relationship between the assets, different graph nodes and edges can form a plurality of data links, in an asset query process, after determining a first target node and a second target node according to an asset query request, one or more data links with the first target node as a starting point and the second target node as an end point can be directly determined from the graph structure, so that the obtained assets stored in the data links can be used as an asset query result, and the asset query process is more convenient and efficient.

In an exemplary embodiment, the asset query method provided in the embodiment of the present application may further include:

determining a data storage range of a database based on graph nodes at edge positions in a graph structure;

In the form of a graph structure, not only can the association relation between assets of different levels be clearly shown through graph nodes and edges, but also the data range which can be provided by a database, namely the data storage range, can be determined according to the graph nodes at edge positions in the graph structure, for example, the longest data link from a system to a website exists in the graph structure, the data storage range can be determined to be the range with the system as the highest level and the website as the lowest level, and a request end can inquire the assets stored in the data link determined by any two graph nodes between the system and the website.

Based on the above embodiments, the asset query request may be generated by the following process:

determining assets to be queried; the method comprises the steps that an asset to be queried is in a data storage range;

an asset query request is generated based on the asset to be queried.

In this embodiment, after determining the data storage range of the database and sending the information including the data storage range to the requesting end, the requesting end may locate the asset to be queried within the data storage range of the database when sending the asset query request, so as to ensure the validity and accuracy of the asset query process.

In summary, according to the asset query method provided by the embodiment of the application, the assets and the association relations between the assets in the logical data architecture of the assets are stored in the form of a graph structure, and the assets corresponding to the first target node and the second target node can be directly retrieved from the database through the query interface according to the first target node and the second target node determined by the asset query request, so that the asset query result is obtained.

Referring to fig. 6, an electronic device 600 includes a memory 601 and a processor 602.

The processor 602 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The memory 601 may include various types of storage units, such as system memory, read Only Memory (ROM), and persistent storage. Where the ROM may store static data or instructions that are required by the processor 602 or other modules of the computer. The persistent storage may be a readable and writable storage. The persistent storage may be a non-volatile memory device that does not lose stored instructions and data even after the computer is powered down. In some embodiments, the persistent storage device employs a mass storage device (e.g., magnetic or optical disk, flash memory) as the persistent storage device. In other embodiments, the persistent storage may be a removable storage device (e.g., diskette, optical drive). The system memory may be a read-write memory device or a volatile read-write memory device, such as dynamic random access memory. The system memory may store instructions and data that are required by some or all of the processors at runtime. Furthermore, the memory 601 may include any combination of computer readable storage media including various types of semiconductor memory chips (DRAM, SRAM, SDRAM, flash memory, programmable read only memory), magnetic disks, and/or optical disks may also be employed.

In some embodiments, memory 601 may include readable and/or writable removable storage devices such as Compact Discs (CDs), digital versatile discs (e.g., DVD-ROMs, dual layer DVD-ROMs), blu-ray discs read only, super-density discs, flash memory cards (e.g., SD cards, min SD cards, micro-SD cards, etc.), magnetic floppy disks, and the like. The computer readable storage medium does not contain a carrier wave or an instantaneous electronic signal transmitted by wireless or wired transmission.

The memory 601 has stored thereon executable code that, when processed by the processor 602, causes the processor 602 to perform some or all of the methods described above.

The aspects of the present application have been described in detail hereinabove with reference to the accompanying drawings. In the foregoing embodiments, the descriptions of the embodiments are focused on, and for those portions of one embodiment that are not described in detail, reference may be made to the related descriptions of other embodiments. Those skilled in the art will also appreciate that the acts and modules referred to in the specification are not necessarily required in the present application. In addition, it can be understood that the steps in the method of the embodiment of the present application may be sequentially adjusted, combined and pruned according to actual needs, and the modules in the apparatus of the embodiment of the present application may be combined, divided and pruned according to actual needs.

Furthermore, the method according to the present application may also be implemented as a computer program or computer program product comprising computer program code instructions for performing part or all of the steps of the above-described method of the present application.

Alternatively, the present application may also be embodied as a non-transitory machine-readable storage medium (or computer-readable storage medium, or machine-readable storage medium) having stored thereon executable code (or a computer program, or computer instruction code) that, when executed by a processor of an electronic device (or electronic device, server, etc.), causes the processor to perform some or all of the steps of the above-described methods according to the present application.

Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the application herein may be implemented as electronic hardware, computer software, or combinations of both.

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems and methods according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The embodiments of the present application have been described above, the foregoing description is exemplary, not exhaustive, and not limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the various embodiments described. The terminology used herein was chosen in order to best explain the principles of the embodiments, the practical application, or the improvement of technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. An asset query system, comprising:

2. The asset query system of claim 1, wherein the asset model is specifically configured to:

3. The asset query system of claim 1, wherein the database is specifically configured to:

4. The asset query system of claim 1, wherein the query interface is specifically configured to:

5. An asset querying method, characterized in that it is based on an asset querying system as claimed in any one of claims 1 to 4, said method comprising:

receiving an asset inquiry request sent by a request end;

and sending the asset inquiry result to the request end.

6. The method of claim 5, wherein retrieving, via the query interface, assets corresponding to the first target node and the second target node from the database, and obtaining an asset query result, comprises:

7. The asset querying method of claim 5, further comprising:

8. The asset query method of claim 7, wherein the asset query request is generated by:

and generating the asset inquiry request based on the asset to be inquired.

9. An electronic device, comprising:

a processor; and

a memory having executable code stored thereon, which when executed by the processor causes the processor to perform the asset querying method of any of claims 5 to 8.

10. A non-transitory machine-readable storage medium having stored thereon executable code, which when executed by a processor of an electronic device, causes the processor to perform the asset querying method of any of claims 5 to 8.