CN112685443B - Data query method, device, electronic equipment and computer readable storage medium - Google Patents
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Abstract
The embodiment of the application provides a data query method, a data query device, electronic equipment and a computer readable storage medium, and relates to the field of computers. The data query method comprises the following steps: selecting a target access interface from the access interface mart layer according to the received access request; the requirement dimension corresponding to the target access interface is matched with the actual business requirement of the access request; requesting feedback data related to the requirement dimension corresponding to the target access interface from the data mart layer through a data model corresponding to the target access interface; the feedback data are fused by utilizing a data model corresponding to the target access interface, and response data corresponding to the access request are obtained; response data is issued. The user can obtain the data meeting the actual service requirement after fusion by selecting the target access interface according to the actual service requirement, so that the capability of coping with the service requirement change is improved, and the resource waste caused by repeated data carding is avoided.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a data query method, a data query device, an electronic device, and a computer readable storage medium.
Background
Today, the digital transformation of enterprises is urgent, many enterprises have a great deal of data to be stored, and various types of data storage can be perfectly solved by the existing various databases. However, the stored data is often not directly user-oriented, as mere data is not useful to the user, and a combination of data and business requirements is required to obtain data useful to the user.
Currently, data that has been deposited in a data lake is typically sorted according to current business needs, the relationships between the data are sorted and cleaned and integrated, and then user-oriented data is provided. However, this process is repeated when the service demand changes, resulting in great resource waste, and the process is long and error-prone.
Disclosure of Invention
In view of the above, an object of the present application is to provide a data query method, apparatus, electronic device, and computer-readable storage medium.
In order to achieve the above object, the technical scheme adopted by the embodiment of the application is as follows:
in a first aspect, the present application provides a data query method, where the data query method is applied to the data query system, and the data query system includes a data mart layer, a data model layer, and an access interface mart layer; the data model in the data model layer is used for fusing data conforming to different demand dimensions; each access interface in the access interface mart layer corresponds to a data model; each of the access interfaces corresponds to a requirement dimension; the data query method comprises the following steps:
selecting a target access interface from the access interface mart layer according to the received access request; the requirement dimension corresponding to the target access interface is matched with the actual service requirement of the access request;
requesting feedback data related to a demand dimension corresponding to the target access interface from the data mart layer through the data model corresponding to the target access interface;
fusing the feedback data by utilizing the data model corresponding to the target access interface to obtain response data corresponding to the access request;
and sending out the response data.
In an alternative embodiment, the step of selecting the target access interface from the access interface bazaar layer according to the received access request includes:
analyzing the access request to obtain the access right corresponding to the access request;
matching an access interface to be selected from the access interface mart layer according to the access authority;
matching the actual service requirement carried in the access request with the requirement dimension corresponding to the to-be-selected access interface;
and determining the candidate access interface successfully matched as the target access interface.
In an optional embodiment, the step of requesting, from the data mart layer, feedback data related to a requirement dimension corresponding to the target access interface through the data model corresponding to the target access interface includes:
creating a query demand instruction according to the demand dimension of the target access interface by using a corresponding data model;
and forwarding the query demand instruction to the data mart layer to acquire the feedback data.
In an alternative embodiment, the data query method further includes:
analyzing the query demand instruction, and determining a target database related to the query demand instruction from a data lake;
converting the query demand instruction into query information corresponding to the target database, and sending the query information to the corresponding target database;
and generating the feedback data according to the query result fed back by the target database.
In an alternative embodiment, the step of generating the feedback data according to the query result fed back by the target database includes:
and according to a unified feedback module, converting the query result fed back by the target database into a standard format to obtain the feedback data.
In a second aspect, the present application provides a data query device, where the data query device is applied to the data query system, and the data query system includes a data mart layer, a data model layer, and an access interface mart layer; the data model in the data model layer is used for fusing data conforming to different demand dimensions; each access interface in the access interface mart layer corresponds to a data model; each of the access interfaces corresponds to a requirement dimension; the data query device:
the selection module is used for selecting a target access interface from the access interface mart layer according to the received access request; the requirement dimension corresponding to the target access interface is matched with the actual service requirement of the access request;
the request module is used for requesting feedback data related to a demand dimension corresponding to the target access interface from the data mart layer through the data model corresponding to the target access interface;
the fusion module is used for fusing the feedback data by utilizing the data model corresponding to the target access interface to obtain response data corresponding to the access request;
and the sending module is used for sending out the response data.
In an alternative embodiment, the selection module is specifically configured to:
analyzing the access request to obtain the access right corresponding to the access request;
matching an access interface to be selected from the access interface mart layer according to the access authority;
matching the actual service requirement carried in the access request with the requirement dimension corresponding to the to-be-selected access interface;
and determining the candidate access interface successfully matched as the target access interface.
In an alternative embodiment, the request module is specifically configured to:
creating a query demand instruction according to the demand dimension of the target access interface by using a corresponding data model;
and forwarding the query demand instruction to the data mart layer to acquire the feedback data.
In a third aspect, the application provides an electronic device comprising a processor and a memory storing machine executable instructions executable by the processor to implement the method of any of the preceding embodiments.
In a fourth aspect, the present application provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method according to any of the preceding embodiments.
Compared with the prior art, the data query method provided by the embodiment of the application is applied to the data query system, and the data query system comprises a data mart layer, a data model layer and an access interface mart layer; the data model in the data model layer is used for fusing data conforming to different demand dimensions; each access interface in the access interface mart layer corresponds to a data model; each of the access interfaces corresponds to a requirement dimension; the data query method comprises the following steps: selecting a target access interface from the access interface mart layer according to the received access request; the requirement dimension corresponding to the target access interface is matched with the actual service requirement of the access request; requesting feedback data related to a demand dimension corresponding to the target access interface from the data mart layer through the data model corresponding to the target access interface; fusing the feedback data by utilizing the data model corresponding to the target access interface to obtain response data corresponding to the access request; and sending out the response data. In the embodiment of the application, a plurality of access interfaces are defined from a plurality of service requirement dimensions in advance, so that a user can obtain the data meeting the actual service requirement after fusion by selecting the target access interface according to the actual service requirement, the capability of coping with service requirement change is improved, and the resource waste caused by repeated data carding is avoided.
In order to make the above objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 shows a schematic diagram of a data query system according to an embodiment of the present application.
Fig. 2 shows a schematic diagram of an electronic device according to an embodiment of the present application.
Fig. 3 shows one of the step flowcharts of the data query method provided by the embodiment of the present application.
Fig. 4 shows a second flowchart of a step of the data query method according to the embodiment of the present application.
Fig. 5 shows a schematic diagram of a data query device according to an embodiment of the present application.
Icon: 100-an electronic device; 110-memory; a 120-processor; 130-a communication module; 300-a data query device; 301-selecting a module; 302-request module; 303-a fusion module; 304-issue module.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the application, as presented in the figures, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by a person skilled in the art without making any inventive effort, are intended to be within the scope of the present application.
It is noted that relational terms such as "first" and "second", and the like, are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
Referring to fig. 1, fig. 1 shows an application scenario of a data query method and apparatus provided by an embodiment of the present application, that is, a data query system. As shown in FIG. 1, the data query system includes a data mart layer, a data model layer, and an access interface mart layer.
The data mart layer described above provides data lake entry capability. It will be appreciated that the data accessed from the data lake is not stored directly in the data mart layer, but the data mart layer may instead take the raw data from the data lake. The data mart layer is utilized, the data stored in different forms can be accessed in a unified mode, and various problems in the process of data re-storage or data migration are avoided.
The above data lake is an environment actually used for data storage. The data lake may be composed of a plurality of types of databases. For example, a data lake is composed of Mysql database, hbase database, elastiscearch database, etc. for storing different types of data.
The data model layer can extract required original data from the data lake through the data mart layer and carry out carding integration to obtain output data which can face users. The data model layer includes a plurality of data models. The data model is used for fusing data meeting different demand dimensions. Alternatively, the demand dimension corresponding to different data models may be different. When designing the data model, all the demand dimensions possibly faced by all the users can be firstly combed, then the different demand dimensions are combined, a corresponding data model is created, and the created data model can fuse the data meeting the corresponding demand dimensions.
In other words, the data model layer is a service-oriented solution in fact, and by means of the unified data access capability of the data mart layer, a user can have multiple service requirements and design a fused data model. Such as sales data of a product that the original user wants to access, a batch of data such as sales person dimension, dealer dimension data, sales fact data, etc. needs to be accessed and integrated by himself. The data model can integrate three parts of data to generate an enterprise sales data model, and of course, more demand dimensions and fact data, such as comment data of sales shops, can be fused, so that the large data model can be provided for a plurality of users to use without re-fusing the data each time, thereby greatly reducing the data production period and the error rate, and further reducing the data use cost.
The business of the data model is strongly correlated, and the business requirement can be corresponding to the data model, but the data model is required to function and an access interface is required to provide data outwards. Furthermore, for the same data model, the user may have different query requirements, such as aggregation according to time window, such as aggregation according to region, etc., and at this time the access interface is required to have flexible coping capability, and the user may need data provided by different data models, that is, the user needs multiple access interfaces. Therefore, the data query system in the embodiment of the application is also provided with an access interface mart layer. The access interface bazaar layer is a layer directly facing the data requirement of the user, and the access interface bazaar layer can acquire the data required by the user from the data model layer. The access interface mart layer consists of a plurality of access interfaces. Each access interface in the access interface mart layer corresponds to a data model; each of the access interfaces corresponds to a requirement dimension. In other words, each data model may correspond to multiple access interfaces, but one access interface corresponds to one data model. The user can acquire the data obtained after the fusion processing from the corresponding data model through the access interface. Furthermore, each access interface corresponds to at least one requirement dimension.
As described above, a single data model may fuse multiple demand dimensions and fact data, and if the demand dimension corresponding to the access interface selected by the user is not all the demand dimensions of the corresponding data model, the data model may also integrate the demand dimension of the selected access interface and the corresponding fact data, and feed back the data actually required by the user. The applicability of a single data model is improved.
The data query system described above may be deployed on an electronic device 100 as shown in fig. 2. The electronic device 100 may be, but is not limited to, a personal computer (personal computer, PC), a server, a distributed deployment computer, and the like. It is understood that the electronic device 100 is not limited to a physical server, and may be a virtual machine on a physical server, a virtual machine built on a cloud platform, or a computer that can provide the same function as the server or the virtual machine.
Referring to fig. 2, a block diagram of the electronic device 100 is shown. The electronic device 100 includes a memory 110, a processor 120, and a communication module 130. The memory 110, the processor 120, and the communication module 130 are electrically connected directly or indirectly to each other to realize data transmission or interaction. For example, the components may be electrically connected to each other via one or more communication buses or signal lines.
Wherein the memory 110 is used for storing programs or data. The Memory 110 may be, but is not limited to, a random access Memory 110 (Random Access Memory, RAM), a Read Only Memory 110 (ROM), a programmable Read Only Memory 110 (Programmable Read-Only Memory, PROM), an erasable Read Only Memory 110 (Erasable Programmable Read-Only Memory, EPROM), an electrically erasable Read Only Memory 110 (Electric Erasable Programmable Read-Only Memory, EEPROM), etc.
The processor 120 is used to read/write data or programs stored in the memory 110 and perform corresponding functions.
The communication module 130 is configured to establish a communication connection between the electronic device 100 and other communication terminals through the network, and is configured to transmit and receive data through the network.
It should be understood that the structure shown in fig. 2 is merely a schematic diagram of the structure of the electronic device 100, and that the electronic device 100 may further include more or fewer components than those shown in fig. 2, or have a different configuration than that shown in fig. 2. The components shown in fig. 2 may be implemented in hardware, software, or a combination thereof.
Referring to fig. 3, fig. 3 illustrates a data query method according to an embodiment of the present application. As shown in fig. 3, the data query method includes the following steps:
step S101, selecting a target access interface from the access interface mart layer according to the received access request.
The dimension of the requirement corresponding to the target access interface is matched with the actual business requirement of the access request. The access request carries the actual service requirement selected by the user.
In some embodiments, when receiving an access request triggered by a user, the electronic device 100 selects a matched target access interface from the access interface bazaar layer according to an actual service requirement item carried in the access request.
In addition, in some embodiments, in order to facilitate management of data and also to ensure security of accessed data, it is necessary to set access rights for each user. In this scenario, the user's rights issue also needs to be taken into account when selecting the target access interface. Therefore, the step S101 may further include the following steps:
(1) Analyzing the access request and obtaining the access right corresponding to the access request.
It can be appreciated that when the user creates an access request, the access request carries the access right of the user. The access authority may be an authority given to the user by an administrator maintaining the access interface layer, for example, which access interfaces in the access interface layer may be used, which access interfaces may not be used, and a usable lifetime of the usable access interfaces. Of course, the above access request may be written with identification information indicating the access rights, and the electronic device 100 may also store a mapping table between different identification information and access rights. Thus, the access right corresponding to the access request can be determined by querying the mapping table.
(2) And matching the to-be-selected access interface from the access interface mart layer according to the access authority.
(3) And matching the actual service requirement carried in the access request with the requirement dimension corresponding to the to-be-selected access interface.
For example, the actual business needs are market feedback for viewing a specified commodity, and then the need dimension that matches the actual business needs may be a dealer dimension, an evaluation dimension, a retail dimension, and so on.
Of course, a lookup table between different actual service demands and different demand dimensions can be established for the existing demand dimensions in the system, so that the demand dimensions matched with the actual service demands carried by the access requests can be determined through the lookup table.
In addition, when creating a new actual service requirement, if a requirement dimension matching the new actual service requirement can be obtained by combining the existing requirement dimensions, the lookup table can be directly updated to increase the corresponding relationship between the new actual service requirement and the requirement dimension. If existing demand dimensions cannot be combined to obtain a demand dimension that matches the new actual business demand, then a new demand dimension can be created to satisfy the match with the actual business demand.
In addition, in the case of creating a new demand dimension, the new demand dimension may be combined with an existing demand dimension, and a data model corresponding to the newly added combined demand dimension may be created.
(4) And determining the candidate access interface successfully matched as a target access interface.
Step S102, requesting feedback data related to a demand dimension corresponding to the target access interface from the data mart layer through a data model corresponding to the target access interface.
In some embodiments, the query requirement instructions may be created from the requirement dimension of the target access interface first using the corresponding data model. It will be appreciated that the query requirement instruction described above may be an instruction for querying data from a data lake. The query requirement instruction created according to the requirement dimension of the target access interface can be used for querying data meeting the requirement dimension of the target access interface from the data lake.
In some embodiments, query demand instructions may be created in a fixed template, regardless of the database in which the queried data is stored. And secondly, forwarding the query demand instruction to a data mart layer to acquire feedback data.
Further, after forwarding the query requirement instruction to the data mart layer, as shown in fig. 4, the data query method may further include the following steps:
in step S201, the query demand instruction is parsed, and the target database related to the query demand instruction is determined from the data lake.
It will be appreciated that the data stored in the data lake is typically stored in a database of the corresponding type by data type, e.g., relational data is stored in a relational database. For another example, the document type data is stored in a document database. Thus, in some embodiments, the target database may be determined from a data lake based on the data type of the data to which the query demand instruction relates.
Step S202, the query demand instruction is converted into query information corresponding to the target database, and the query information is sent to the corresponding target database.
For example, the target database is a Mysql database, and then the query requirement instruction is converted into query information which can be used for querying the Mysql database according to a Mysql query instruction template.
It can be seen that, in the data query method provided by the embodiment of the present application, through the steps S201 to S202, the query requirement instruction created by the unified template is converted into the query information of the corresponding query template, but only the query details are converted, and the differences of the query templates come from the differences of the query sentences defined by the various data sources. The virtualization access and detail shielding capability is achieved in the mode, and the upper layer application can access all data in the data lake only according to the unified access form without concern about the storage scheme from which the data comes.
Step S203, feedback data is generated according to the query result fed back by the target database.
The data formats returned by different databases are the agreed formats of the databases, for example, the return modes of the structured databases are tables, and the document databases are json data structures returned by the elastic search. The conversion scheme can be customized according to the return form of each database, and the return results can be unified, so that the aim of complete data detail shielding is fulfilled.
Therefore, in some embodiments, the step S203 may be to convert the query result fed back by the target database into a standard format according to the unified feedback module, so as to obtain the feedback data.
And step S103, fusing the feedback data by utilizing a data model corresponding to the target access interface to obtain response data corresponding to the access request.
In some embodiments, each target access interface corresponds to a data model, and thus feedback data drawn from the data lake that meets the demand dimension of the target access interface is passed to the corresponding data model. And fusing the obtained feedback data by the data model to generate the finally required response data.
Step S104, sending out response data.
In some embodiments, the resulting response data may be sent to the user, e.g., to a user-specified device for display. In some embodiments, the user-specified device may be a device communicatively coupled to the electronic device 100. In other embodiments, the user-specified device may be part of a structure in the electronic device 100, such as a display screen, i.e., a display screen is utilized to present response data to the user.
In order to perform the corresponding steps in the foregoing embodiments and the various possible manners, an implementation manner of the data query apparatus 300 is given below, and alternatively, the data query apparatus 300 may employ the device structure of the electronic device 100 shown in fig. 2. Further, referring to fig. 5, fig. 5 is a functional block diagram of a data query device 300 according to an embodiment of the present application. It should be noted that, the basic principle and the technical effects of the data query device 300 provided in this embodiment are the same as those of the foregoing embodiments, and for brevity, reference may be made to the corresponding contents of the foregoing embodiments. The data query device 300 includes: a selection module 301, a request module 302, a fusion module 303 and an issue module 304.
A selecting module 301, configured to select, according to the received access request, a target access interface from the access interface bazaar layer; the requirement dimension corresponding to the target access interface is matched with the actual service requirement of the access request.
And the request module 302 is configured to request feedback data related to a requirement dimension corresponding to the target access interface to the data mart layer through the data model corresponding to the target access interface.
And a fusion module 303, configured to fuse the feedback data by using the data model corresponding to the target access interface, so as to obtain response data corresponding to the access request.
An issuing module 304, configured to issue the response data.
In some embodiments, the selection module 301 is specifically configured to:
analyzing the access request to obtain the access right corresponding to the access request;
matching an access interface to be selected from the access interface mart layer according to the access authority;
matching the actual service requirement carried in the access request with the requirement dimension corresponding to the to-be-selected access interface;
and determining the candidate access interface successfully matched as the target access interface.
In some embodiments, the request module 302 is specifically configured to: creating a query demand instruction according to the demand dimension of the target access interface by using a corresponding data model; and forwarding the query demand instruction to the data mart layer to acquire the feedback data.
Alternatively, the above modules may be stored in the memory 110 shown in fig. 2 or solidified in an Operating System (OS) of the electronic device 100 in the form of software or Firmware (Firmware), and may be executed by the processor 120 in fig. 2. Meanwhile, data, codes of programs, and the like, which are required to execute the above-described modules, may be stored in the memory 110.
In summary, the data query method and related device provided by the embodiments of the present application can enable enterprise data to be easily imported into the data mart provided by the API mart in a virtualized manner, and do not need to care about various problems in the data re-storage or data migration process, which is different from the current data service platform, the data is not repeatedly dropped, and meanwhile, the data query method and related device are compatible with various storage formats, because the data book inside the enterprise is various. In addition, by providing business abstraction to the enterprise's internal data lakes and unified access to the data marts, data managers can quickly create accessible multidimensional data models. By selecting and subscribing to related data APIs in the API marketplace, the business department can easily obtain data access capability, and needs developers and a large number of business personnel to re-comb the complicated data stored in the data lake, and the business combing matters only need to be modified once or a small number of times by the related business personnel.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. The apparatus embodiments described above are merely illustrative, for example, of the flowcharts and block diagrams in the figures that illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products 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.
In addition, functional modules in the embodiments of the present application may be integrated together to form a single part, or each module may exist alone, or two or more modules may be integrated to form a single part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The above description is only of the preferred embodiments of the present application and is not intended to limit the present application, but various modifications and variations can be made to the present application by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.
Claims (8)
1. The data query method is characterized by being applied to a data query system, wherein the data query system comprises a data mart layer, a data model layer and an access interface mart layer; the data model in the data model layer is used for fusing data conforming to different demand dimensions; each access interface in the access interface mart layer corresponds to a data model; each of the access interfaces corresponds to at least one demand dimension; the data query method comprises the following steps:
selecting a target access interface from the access interface mart layer according to the received access request; the requirement dimension corresponding to the target access interface is matched with the actual service requirement of the access request;
requesting feedback data related to a demand dimension corresponding to the target access interface from the data mart layer through the data model corresponding to the target access interface;
fusing the feedback data by utilizing the data model corresponding to the target access interface to obtain response data corresponding to the access request;
sending out the response data;
according to the received access request, the step of selecting the target access interface from the access interface mart layer comprises the following steps:
analyzing the access request to obtain the access right corresponding to the access request; the access request comprises identification information representing access rights, a mapping table is formed between the identification information and the access rights, and the access rights corresponding to the access request are determined by inquiring the mapping table;
matching an access interface to be selected from the access interface mart layer according to the access authority;
matching the actual service requirement carried in the access request with the requirement dimension corresponding to the to-be-selected access interface;
and determining the candidate access interface successfully matched as the target access interface.
2. The data query method according to claim 1, wherein the step of requesting feedback data related to a demand dimension corresponding to the target access interface from the data mart layer through the data model corresponding to the target access interface includes:
creating a query demand instruction according to the demand dimension of the target access interface by using a corresponding data model;
and forwarding the query demand instruction to the data mart layer to acquire the feedback data.
3. The data query method of claim 2, wherein the data query method further comprises:
analyzing the query demand instruction, and determining a target database related to the query demand instruction from a data lake;
converting the query demand instruction into query information corresponding to the target database, and sending the query information to the corresponding target database;
and generating the feedback data according to the query result fed back by the target database.
4. The data query method as claimed in claim 3, wherein the step of generating the feedback data according to the query result fed back by the target database comprises:
and according to a unified feedback module, converting the query result fed back by the target database into a standard format to obtain the feedback data.
5. The data query device is characterized by being applied to a data query system, wherein the data query system comprises a data mart layer, a data model layer and an access interface mart layer; the data model in the data model layer is used for fusing data conforming to different demand dimensions; each access interface in the access interface mart layer corresponds to a data model; each of the access interfaces corresponds to a requirement dimension; the data query device:
the selection module is used for selecting a target access interface from the access interface mart layer according to the received access request; the requirement dimension corresponding to the target access interface is matched with the actual service requirement of the access request;
the request module is used for requesting feedback data related to a demand dimension corresponding to the target access interface from the data mart layer through the data model corresponding to the target access interface;
the fusion module is used for fusing the feedback data by utilizing the data model corresponding to the target access interface to obtain response data corresponding to the access request;
the sending module is used for sending out the response data;
the selection module is specifically configured to:
analyzing the access request to obtain the access right corresponding to the access request; the access request comprises identification information representing access rights, a mapping table is formed between the identification information and the access rights, and the access rights corresponding to the access request are determined by inquiring the mapping table;
matching an access interface to be selected from the access interface mart layer according to the access authority;
matching the actual service requirement carried in the access request with the requirement dimension corresponding to the to-be-selected access interface;
and determining the candidate access interface successfully matched as the target access interface.
6. The data query device of claim 5, wherein the request module is specifically configured to:
creating a query demand instruction according to the demand dimension of the target access interface by using a corresponding data model;
and forwarding the query demand instruction to the data mart layer to acquire the feedback data.
7. An electronic device comprising a processor and a memory, the memory storing machine-executable instructions executable by the processor to implement the method of any one of claims 1-4.
8. A computer readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, implements the method according to any of claims 1-4.
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| CN114461676A (en) * | 2022-04-11 | 2022-05-10 | 武汉中科通达高新技术股份有限公司 | Cross-region data query method and device, electronic equipment and storage medium |
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