CN116842043A - Data query method, device, equipment and storage medium - Google Patents
Data query method, device, equipment and storage medium Download PDFInfo
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2453—Query optimisation
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
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Abstract
The application provides a data query method, a device, equipment and a storage medium, wherein the method is used for acquiring field information in a business system by communicating with an industry data model client, wherein the field information comprises a complete set of user data fields and coded information of organization codes; performing data processing on the field information to obtain a federal learning user data field full model; generating at least one main index of the user data field full model according to the preset field; responding to an information inquiry request packet sent by an inquiry client to acquire an inquiry field corresponding to the information inquiry request; generating a sub-query field packet according to the query field, the user data field full model and the main index; respectively sending the sub-query field packets to corresponding industry data model clients so that the industry data model clients perform data query according to the sub-query field packets to obtain query results, and sending the query results to a data query device; and acquiring a query result, and sending the query result to a query client.
Description
Technical Field
The present application relates to the field of data processing technologies, and in particular, to a data query method, device, apparatus, and storage medium.
Background
The network checking and controlling means that information on the network is monitored and controlled by a technical means. The implementation of network checking and control needs to depend on various technical means and tools, such as network monitoring software, a firewall, a data packet filter and the like. These tools can help monitor network traffic, detect malware, filter illegal content, etc., thereby ensuring network security.
At present, the data is queried through a system established by centralization of the data, the aim of network checking and controlling is realized, after each database encrypts or desensitizes the data, part of the data is disclosed to the system established by centralization, and only part of the data can be obtained during network checking and controlling.
However, the prior art data query method has difficulty in acquiring complete data.
Disclosure of Invention
The application provides a data query method, a device, equipment and a storage medium, which are used for solving the technical problem that complete data are difficult to obtain in the prior art.
In a first aspect, the present application provides a data query method, including:
acquiring field information in a business system by communicating with an industry data model client, wherein the field information comprises a complete set of user data fields and coded information of organization codes;
performing data processing on the field information to obtain a federal learning user data field full model;
generating at least one main index of the user data field full model according to a preset field;
responding to an information inquiry request packet sent by an inquiry client, and acquiring an inquiry field corresponding to the information inquiry request;
generating a sub-query field packet according to the query field, the user data field full model and the main index;
respectively sending the sub-query field packages to corresponding industry data model clients, so that the industry data model clients perform data query according to the sub-query field packages to obtain query results, and sending the query results to a data query device;
and acquiring a query result, and sending the query result to a query client.
The application can build the full model of federal learning user data field by communicating with the industry data model client to build the full model of federal learning user data field, and can realize data query without uploading the data set to the system built by data centralization.
Optionally, the data processing is performed on the field information to obtain a federal learning user data field full model, including:
adding a time stamp to the field information;
and carrying out aggregation processing and repeated item removal processing on the field information added with the time stamp to obtain the federal learning user data field full model.
After the data is uploaded by the industry data model client, the federal learning user data field full model is obtained through aggregation processing and repeated item removal processing, so that accurate and complete aggregation of the data is realized, and the efficiency of data query is improved conveniently.
Optionally, before the data processing is performed on the field information to obtain the federal learning user data field full model, the method further includes:
acquiring updated field information by communicating with an industry data model client;
correspondingly, the data processing is performed on the field information to obtain a federal learning user data field full model, which comprises the following steps:
and carrying out data processing on the field information and the updated field information to obtain a full model of the federal learning user data field.
The industry data model client side can update data in real time, and the data query equipment side can update the full model of the federal learning user data field in real time according to the data, so that more accurate data is obtained, an accurate query result is provided for a user, and user experience is improved.
Optionally, before the information query request packet sent by the query client is received, the method further includes:
responding to an information inquiry request sent by an inquiry client, and determining whether the inquiry client inquires permission;
if the query client side is determined to have the query authority, sending an audit signature to the query client side, so that the query client side adds the audit signature, a query client side public key and the query client side signature to the information query request after receiving the audit signature to obtain an information query request packet, and sends the information query request packet to a data query device side;
correspondingly, the responding to the information inquiry request packet sent by the inquiry client obtains an inquiry field corresponding to the information inquiry request, including:
and carrying out signature verification on the information inquiry request packet, and if verification is successful, acquiring an inquiry field corresponding to the information inquiry request.
After receiving the information inquiry request sent by the inquiry client, the application determines in advance whether the inquiry client inquires the authority and issues the signature for the inquiry client with the inquiry authority so as to enable the inquiry client to inquire the information, the authentication provides reliable guarantee for the safety of the user data, and the safety and the reliability of the data inquiry are further improved.
Optionally, after determining whether the querying client queries the authority in response to the information query request sent by the querying client, the method further includes:
and if the query client side is determined not to have the query authority, returning the information query request.
Here, the application returns the querying client without querying rights to protect the data security.
Optionally, the obtaining the query result and sending the query result to the query client includes:
obtaining a query result, and carrying out private key encryption processing on the query result to obtain an encrypted query result;
and sending the encrypted query result to the query client.
When the query result is sent to the query client, the query result is firstly encrypted, so that the safety in the data transmission process is ensured, the safety, the integrity and the reliability of data query are further improved, and the user experience is improved.
In a second aspect, the present application provides a data query apparatus, comprising:
the system comprises an acquisition module, a service system and a service system, wherein the acquisition module is used for acquiring field information in the service system by communicating with an industry data model client, wherein the field information comprises a complete set of user data fields and coded information of mechanism codes;
the model building module is used for carrying out data processing on the field information to obtain a full model of the federal learning user data field;
the generation module is used for generating at least one main index of the user data field full model according to a preset field;
the first query processing module is used for responding to an information query request packet sent by a query client and acquiring a query field corresponding to the information query request;
the second query processing module is used for generating a sub-query field packet according to the query field, the user data field full model and the main index;
the first sending module is used for respectively sending the sub-query field packages to corresponding industry data model clients so that the industry data model clients can perform data query according to the sub-query field packages to obtain query results and send the query results to a data query device end;
and the second sending module is used for obtaining the query result and sending the query result to the query client.
Optionally, the model building module is specifically configured to:
adding a time stamp to the field information;
and carrying out aggregation processing and repeated item removal processing on the field information added with the time stamp to obtain the federal learning user data field full model.
Optionally, before the model building module performs data processing on the field information to obtain a federal learning user data field full model, the apparatus further includes an updating module, configured to:
acquiring updated field information by communicating with an industry data model client;
correspondingly, the model building module is specifically used for:
and carrying out data processing on the field information and the updated field information to obtain a full model of the federal learning user data field.
Optionally, before the first query processing module responds to the information query request packet sent by the query client to obtain the query field corresponding to the information query request, the apparatus further includes an authentication module, configured to:
responding to an information inquiry request sent by an inquiry client, and determining whether the inquiry client inquires permission;
if the query client side is determined to have the query authority, sending an audit signature to the query client side, so that the query client side adds the audit signature, a query client side public key and the query client side signature to the information query request after receiving the audit signature to obtain an information query request packet, and sends the information query request packet to a data query device side;
correspondingly, the first query processing module is specifically configured to:
and carrying out signature verification on the information inquiry request packet, and if verification is successful, acquiring an inquiry field corresponding to the information inquiry request.
Optionally, after the determining, by the authentication module, whether the querying client queries the rights or not in response to the information query request sent by the querying client, the authentication module is further configured to:
and if the query client side is determined not to have the query authority, returning the information query request.
Optionally, the second sending module is specifically configured to:
obtaining a query result, and carrying out private key encryption processing on the query result to obtain an encrypted query result;
and sending the encrypted query result to the query client.
In a third aspect, the present application provides a data query device, comprising: at least one processor and memory;
the memory stores computer-executable instructions;
the at least one processor executes the computer-executable instructions stored in the memory to cause the at least one processor to perform the data query method as described above in the first aspect and the various possible designs of the first aspect.
In a fourth aspect, the present application provides a computer-readable storage medium having stored therein computer-executable instructions which, when executed by a processor, implement the data query method according to the first aspect and the various possible designs of the first aspect.
In a fifth aspect, the present application provides a computer program product comprising a computer program which, when executed by a processor, implements the data query method according to the first aspect and the various possible designs of the first aspect.
The data query method, the device, the equipment and the storage medium provided by the application, wherein the method acquires all field information in a business system by communicating with an industry data model client, thereby establishing a federal learning user data field full model, realizing data query without uploading data to a system established by data centralization, having high data security, providing complete data for users during user query through the federal learning user data field full model, improving the data query integrity and realizing high-efficiency data query.
Drawings
In order to more clearly illustrate the embodiments of the application or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the application, and that other drawings can be obtained according to these drawings without inventive faculty for a person skilled in the art.
FIG. 1 is a schematic diagram of a data query system architecture according to an embodiment of the present application;
fig. 2 is a schematic flow chart of a data query method according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a data query device according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of a data query device according to an embodiment of the present application.
Specific embodiments of the present disclosure have been shown by way of the above drawings and will be described in more detail below. These drawings and the written description are not intended to limit the scope of the disclosed concepts in any way, but rather to illustrate the disclosed concepts to those skilled in the art by reference to specific embodiments.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present disclosure as detailed in the accompanying claims.
The terms "first," "second," "third," and "fourth" and the like in the description and in the claims and in the above drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be noted that, the user information (including but not limited to user equipment information, user personal information, etc.) and the data (including but not limited to data for analysis, stored data, presented data, etc.) related to the present application are information and data authorized by the user or fully authorized by each party, and the collection, use and processing of the related data need to comply with related laws and regulations and standards, and provide corresponding operation entries for the user to select authorization or rejection.
At present, the network execution checking and controlling system still has some unavoidable problems, and the system is built through data centralization nowadays, and the unreliability of data of all parties leads to incomplete data which can be checked.
In order to solve the technical problems, the embodiments of the present application provide a data query method, a device, and a storage medium, where the method obtains all field information in a business system by communicating with an industry data model client, so as to establish a federal learning user data field full model, and can realize data query without uploading data set to a system established in a centralized manner.
Optionally, fig. 1 is a schematic diagram of a data query system architecture according to an embodiment of the present application. In fig. 1, the above architecture includes at least one of a receiving device 101, a processor 102, and a display device 103.
It will be appreciated that the architecture illustrated by embodiments of the present application does not constitute a particular limitation on the architecture of the data interrogation system. In other possible embodiments of the present application, the architecture may include more or less components than those illustrated, or some components may be combined, some components may be split, or different component arrangements may be specifically determined according to the actual application scenario, and the present application is not limited herein. The components shown in fig. 1 may be implemented in hardware, software, or a combination of software and hardware.
In a specific implementation, the receiving device 101 may be an input/output interface or a communication interface.
The processor 102 can communicate with the industry data model client through the receiving device 101 to acquire all field information in the business system, so that a federal learning user data field full model is built, and data query can be realized without uploading data sets to a system built by data centralization.
The display device 103 may be used to display the above results and the like.
The display device may also be a touch screen for receiving user instructions while displaying the above to enable interaction with a user.
It should be understood that the above-described processor may be implemented by a processor that reads instructions in a memory and executes the instructions, or may be implemented by a chip circuit.
In addition, the network architecture and the service scenario described in the embodiments of the present application are for more clearly describing the technical solution of the embodiments of the present application, and do not constitute a limitation on the technical solution provided by the embodiments of the present application, and as a person of ordinary skill in the art can know, with evolution of the network architecture and occurrence of a new service scenario, the technical solution provided by the embodiments of the present application is also applicable to similar technical problems.
The following description of the present application is given by taking several embodiments as examples, and the same or similar concepts or processes may not be described in detail in some embodiments.
Fig. 2 is a schematic flow chart of a data query method according to an embodiment of the present application, where an execution body of the embodiment of the present application may be the processor 102 in fig. 1, and the specific execution body may be determined according to an actual application scenario. As shown in fig. 2, the method comprises the steps of:
s201: and acquiring field information in the business system by communicating with the industry data model client.
Wherein the field information includes a complete set of user data fields and organization-encoded encoding information.
Optionally, the industry data model client serves as a federal learning participant, downloads the latest model from the data query device end, and locally calculates model parameters to send to the data query device end.
S202: and carrying out data processing on the field information to obtain a full model of the federal learning user data field.
Optionally, after a plurality of data iterations of the participants, a federal learning user data field full model is obtained.
Optionally, performing data processing on the field information to obtain a full model of federal learning user data fields, including:
adding a time stamp to the field information; and carrying out aggregation processing and repeated item removal processing on the field information added with the time stamp to obtain the federal learning user data field full model.
After uploading data by the client of the industrial data model, the embodiment of the application obtains the full model of the federal learning user data field through aggregation processing and repeated item removal processing, thereby realizing accurate and complete aggregation of the data and being convenient for improving the efficiency of data query.
Optionally, before performing data processing on the field information to obtain the federal learning user data field full model, the method further comprises: acquiring updated field information by communicating with an industry data model client; correspondingly, carrying out data processing on the field information to obtain a full model of the federal learning user data field, which comprises the following steps: and carrying out data processing on the field information and the updated field information to obtain a full model of the federal learning user data field.
The data query equipment end can update the full model of the federal learning user data field in real time according to the data, so that more accurate data is obtained, an accurate query result is provided for a user, and the user experience is improved.
S203: and generating at least one main index of the full model of the user data field according to the preset field.
The primary index may be information such as name, identification number, etc.
S204: and responding to the information inquiry request packet sent by the inquiry client, and acquiring an inquiry field corresponding to the information inquiry request.
Optionally, before the information query request packet sent by the query client is responded to, the method further comprises the following steps:
responding to an information inquiry request sent by an inquiry client, and determining whether the inquiry client inquires permission; if the query client has the query authority, sending an audit signature to the query client, so that the query client adds the audit signature, the public key of the query client and the signature of the query client to the information query request after receiving the audit signature to obtain an information query request packet, and sends the information query request packet to the data query equipment; correspondingly, responding to the information inquiry request packet sent by the inquiry client, acquiring an inquiry field corresponding to the information inquiry request, including: and carrying out signature verification on the information inquiry request packet, and if verification is successful, acquiring an inquiry field corresponding to the information inquiry request.
After receiving the information inquiry request sent by the inquiry client, the embodiment of the application determines whether the inquiry client inquires the permission or not in advance, and issues the signature for the inquiry client with the inquiry permission so as to enable the inquiry client to inquire the information, the authentication provides reliable guarantee for the safety of the user data, and the safety and the reliability of the data inquiry are further improved.
Optionally, after determining whether the querying client queries the rights in response to the information query request sent by the querying client, the method further includes: and if the query client side is determined not to have the query authority, returning the information query request.
Here, the embodiment of the application returns the query client without the query authority to protect the data security.
S205: and generating a sub-query field packet according to the query field, the user data field full model and the main index.
Alternatively, according to the query field, the user data field full model query is combined with the main index, and a sub-query field packet can be obtained.
S206: and respectively sending the sub-query field packets to the corresponding industry data model clients so that the industry data model clients perform data query according to the sub-query field packets to obtain query results, and sending the query results to the data query equipment.
S207: and acquiring a query result, and sending the query result to a query client.
Optionally, acquiring the query result, and sending the query result to the query client, including:
obtaining a query result, and carrying out private key encryption processing on the query result to obtain an encrypted query result; and sending the encrypted query result to the query client.
When the query result is sent to the query client, the query result is firstly encrypted, so that the safety in the data transmission process is ensured, the safety, the integrity and the reliability of data query are further improved, and the user experience is improved.
The embodiment of the application acquires all field information in the business system by communicating with the industry data model client, thereby establishing the federal learning user data field full model, realizing data query without uploading data set to the data centralization established system, having high data security, providing complete data for users during user query through the federal learning user data field full model, improving the integrity of data query and realizing high-efficiency data query.
In a possible implementation manner, the embodiment of the application provides a data acquisition system for performing check control based on federal learning, which mainly comprises a data model acquisition module for the check control industry, a check control model maintenance update module, a check control model generation module, a check control model audit module and a check control data model release module.
The execution check and control industry data model acquisition module is built on each ticketing system, and the execution check and control industry data model acquisition module acquires information through communication with industry data model clients in the mechanism business systems. When the customer data field in the institution business system changes, the industry data model client sends the change information to the data model acquisition module of the execution check and control industry. Initially, the industry data model client collects the whole set of the customer data fields in the business system and sends the stm3 coding information of the organization codes to the industry data model collection module for executing check and control.
And the data model acquisition module of the execution check industry adds a time stamp to the received field information and sends the time stamp to the maintenance and update module of the check industry. And if the data field is updated by the data field updating module, adding a time stamp after updating the client data field, and sending the data field to the check and control model maintenance updating module.
After receiving the field models sent by the data model clients of each industry, the check and control model maintenance and update module gathers, removes repeated items, generates a full model of the client data field, and uses names, telephone numbers and the like as the main index of the data field. And sending the data field model information to a query data model release module.
When a query client needs to query data, firstly, a query control model auditing module proposes a query control information requirement, and a related field (the field set is a full set field in a query control data model issuing module) is checked.
And the checking and controlling model checking module checks the data inquiry requirement of the client according to the role and the authority of the inquiring client, and returns the application if the role does not have the inquiry authority. If the inquiring client has the authority, the inquiring client sends the signature of the checking and controlling model checking module to the inquiring client through the request, and after the inquiring client receives the information, the inquiring client sends a data inquiring request to the checking and controlling data model issuing module, and the signature and public key of the client are carried in the information, and the signature of the checking and controlling model checking module is carried out.
After receiving the inquiry request, the inquiry control data model issuing module checks the signature, after the signature passes the check, assembles inquiry field packets according to the data field requirements of the clients and the industry organization information, and sends the inquiry field packets to business systems of the industry organizations respectively. And the business system of the industry organization provides an interface to respond to the request, feeds information back to the query data model issuing module, collects all data fields well, encrypts the data packet according to the signature and public key of the client, and sends the data packet to the query client.
After receiving the information, the inquiring client decrypts the data packet by using the private key, thereby obtaining the data information to be inquired.
Fig. 3 is a schematic structural diagram of a data query device according to an embodiment of the present application, where, as shown in fig. 3, the device according to an embodiment of the present application includes: the system comprises an acquisition module 301, a model building module 302, a generation module 303, a first query processing module 304, a second query processing module 305, a first sending module 306 and a second sending module 307. The data query means may be a server or a terminal device, or a chip or an integrated circuit implementing the functions of the server or the terminal device. Here, the division of the acquisition module 301, the model building module 302, the generation module 303, the first query processing module 304, the second query processing module 305, the first sending module 306, and the second sending module 307 is just a division of a logic function, and both may be integrated or independent physically.
The system comprises an acquisition module, a service system and a service system, wherein the acquisition module is used for acquiring field information in the service system by communicating with an industry data model client, and the field information comprises a complete set of user data fields and coding information of organization codes;
the model building module is used for carrying out data processing on the field information to obtain a full model of the federal learning user data field;
the generation module is used for generating at least one main index of the full model of the user data field according to the preset field;
the first query processing module is used for responding to the information query request packet sent by the query client and acquiring a query field corresponding to the information query request;
the second query processing module is used for generating a sub-query field packet according to the query field, the user data field full model and the main index;
the first sending module is used for respectively sending the sub-query field packages to the corresponding industry data model clients so that the industry data model clients can perform data query according to the sub-query field packages to obtain query results and send the query results to the data query equipment;
and the second sending module is used for obtaining the query result and sending the query result to the query client.
Optionally, the model building module is specifically configured to:
adding a time stamp to the field information;
and carrying out aggregation processing and repeated item removal processing on the field information added with the time stamp to obtain the federal learning user data field full model.
Optionally, before the model building module performs data processing on the field information to obtain the full model of the federal learning user data field, the apparatus further includes an updating module, configured to:
acquiring updated field information by communicating with an industry data model client;
correspondingly, the model building module is specifically used for:
and carrying out data processing on the field information and the updated field information to obtain a full model of the federal learning user data field.
Optionally, before the first query processing module responds to the information query request packet sent by the query client to obtain the query field corresponding to the information query request, the apparatus further includes an authentication module, configured to:
responding to an information inquiry request sent by an inquiry client, and determining whether the inquiry client inquires permission;
if the query client has the query authority, sending an audit signature to the query client, so that the query client adds the audit signature, the public key of the query client and the signature of the query client to the information query request after receiving the audit signature to obtain an information query request packet, and sends the information query request packet to the data query equipment;
accordingly, the first query processing module is specifically configured to:
and carrying out signature verification on the information inquiry request packet, and if verification is successful, acquiring an inquiry field corresponding to the information inquiry request.
Optionally, the authentication module is further configured to, after determining whether the querying client queries the rights in response to the information query request sent by the querying client:
and if the query client side is determined not to have the query authority, returning the information query request.
Optionally, the second sending module is specifically configured to:
obtaining a query result, and carrying out private key encryption processing on the query result to obtain an encrypted query result;
and sending the encrypted query result to the query client.
Referring to fig. 4, there is shown a schematic diagram of a data querying device 400 suitable for use in implementing embodiments of the present disclosure, the data querying device 400 may be a terminal device or a server. The terminal device may include, but is not limited to, a mobile terminal such as a mobile phone, a notebook computer, a digital broadcast receiver, a personal digital assistant (Personal Digital Assistant, PDA for short), a tablet (Portable Android Device, PAD for short), a portable multimedia player (Portable Media Player, PMP for short), an in-vehicle terminal (e.g., an in-vehicle navigation terminal), and the like, and a fixed terminal such as a digital TV, a desktop computer, and the like. The data querying device shown in fig. 4 is only one example and should not be construed as limiting the functionality and scope of use of the disclosed embodiments.
As shown in fig. 4, the data query device 400 may include a processing means (e.g., a central processing unit, a graphic processor, etc.) 401 that may perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 402 or a program loaded from a storage 408 into a random access Memory (Random Access Memory, RAM) 403. In the RAM 403, various programs and data required for the operation of the data inquiry apparatus 400 are also stored. The processing device 401, the ROM 402, and the RAM 403 are connected to each other by a bus 404. An input/output (I/O) interface 405 is also connected to bus 404.
In general, the following devices may be connected to the I/O interface 405: input devices 406 including, for example, a touch screen, touchpad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; an output device 407 including, for example, a liquid crystal display (Liquid Crystal Display, LCD for short), a speaker, a vibrator, and the like; storage 408 including, for example, magnetic tape, hard disk, etc.; and a communication device 409. The communication means 409 may allow the data querying device 400 to communicate wirelessly or by wire with other devices to exchange data. While fig. 4 shows a data querying device 400 having various means, it should be understood that not all of the illustrated means are required to be implemented or provided. More or fewer devices may be implemented or provided instead.
In particular, according to embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flowcharts. In such an embodiment, the computer program may be downloaded and installed from a network via communications device 409, or from storage 408, or from ROM 402. The above-described functions defined in the methods of the embodiments of the present disclosure are performed when the computer program is executed by the processing device 401.
It should be noted that the computer readable medium described in the present disclosure may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this disclosure, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present disclosure, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, fiber optic cables, RF (radio frequency), and the like, or any suitable combination of the foregoing.
The computer readable medium may be contained in the data querying device; or may exist alone without being assembled into the data querying device.
The computer-readable medium carries one or more programs which, when executed by the data querying device, cause the data querying device to perform the method shown in the above embodiment.
Computer program code for carrying out operations of the present disclosure may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a local area network (Local Area Network, LAN for short) or a wide area network (Wide Area Network, WAN for short), or it may be connected to an external computer (e.g., connected via the internet using an internet service provider).
In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of elements is merely a logical functional division, and there may be additional divisions of actual implementation, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. This application is intended to cover any adaptations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It is to be understood that the present disclosure is not limited to the precise arrangements and instrumentalities shown in the drawings, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (10)
1. A method of querying data, comprising:
acquiring field information in a business system by communicating with an industry data model client, wherein the field information comprises a complete set of user data fields and coded information of organization codes;
performing data processing on the field information to obtain a federal learning user data field full model;
generating at least one main index of the user data field full model according to a preset field;
responding to an information inquiry request packet sent by an inquiry client, and acquiring an inquiry field corresponding to the information inquiry request;
generating a sub-query field packet according to the query field, the user data field full model and the main index;
respectively sending the sub-query field packages to corresponding industry data model clients, so that the industry data model clients perform data query according to the sub-query field packages to obtain query results, and sending the query results to a data query device;
and acquiring a query result, and sending the query result to a query client.
2. The method of claim 1, wherein the data processing the field information to obtain a federally learned user data field full model comprises:
adding a time stamp to the field information;
and carrying out aggregation processing and repeated item removal processing on the field information added with the time stamp to obtain the federal learning user data field full model.
3. The method of claim 1, further comprising, prior to said data processing of said field information to obtain a federally learned user data field full model:
acquiring updated field information by communicating with an industry data model client;
correspondingly, the data processing is performed on the field information to obtain a federal learning user data field full model, which comprises the following steps:
and carrying out data processing on the field information and the updated field information to obtain a full model of the federal learning user data field.
4. A method according to any one of claims 1 to 3, further comprising, before the obtaining, in response to the information query request packet sent by the query client, a query field corresponding to the information query request:
responding to an information inquiry request sent by an inquiry client, and determining whether the inquiry client inquires permission;
if the query client side is determined to have the query authority, sending an audit signature to the query client side, so that the query client side adds the audit signature, a query client side public key and the query client side signature to the information query request after receiving the audit signature to obtain an information query request packet, and sends the information query request packet to a data query device side;
correspondingly, the responding to the information inquiry request packet sent by the inquiry client obtains an inquiry field corresponding to the information inquiry request, including:
and carrying out signature verification on the information inquiry request packet, and if verification is successful, acquiring an inquiry field corresponding to the information inquiry request.
5. The method of claim 4, further comprising, after said determining whether said querying client queries for rights in response to an information query request sent by said querying client:
and if the query client side is determined not to have the query authority, returning the information query request.
6. A method according to any one of claims 1 to 3, wherein the obtaining the query result, and sending the query result to a query client, comprises:
obtaining a query result, and carrying out private key encryption processing on the query result to obtain an encrypted query result;
and sending the encrypted query result to the query client.
7. A data query device, comprising:
the system comprises an acquisition module, a service system and a service system, wherein the acquisition module is used for acquiring field information in the service system by communicating with an industry data model client, wherein the field information comprises a complete set of user data fields and coded information of mechanism codes;
the model building module is used for carrying out data processing on the field information to obtain a full model of the federal learning user data field;
the generation module is used for generating at least one main index of the user data field full model according to a preset field;
the first query processing module is used for responding to an information query request packet sent by a query client and acquiring a query field corresponding to the information query request;
the second query processing module is used for generating a sub-query field packet according to the query field, the user data field full model and the main index;
the first sending module is used for respectively sending the sub-query field packages to corresponding industry data model clients so that the industry data model clients can perform data query according to the sub-query field packages to obtain query results and send the query results to a data query device end;
and the second sending module is used for obtaining the query result and sending the query result to the query client.
8. A data query device, comprising: a processor, and a memory communicatively coupled to the processor;
the memory stores computer-executable instructions;
the processor executes computer-executable instructions stored in the memory to implement the method of any one of claims 1 to 6.
9. A computer readable storage medium having stored therein computer executable instructions which when executed by a processor are adapted to carry out the method of any one of claims 1 to 6.
10. A computer program product comprising a computer program, characterized in that the computer program, when executed by a processor, implements the method of any of claims 1 to 6.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310802278.XA CN116842043A (en) | 2023-06-30 | 2023-06-30 | Data query method, device, equipment and storage medium |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310802278.XA CN116842043A (en) | 2023-06-30 | 2023-06-30 | Data query method, device, equipment and storage medium |
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| CN116842043A true CN116842043A (en) | 2023-10-03 |
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| CN202310802278.XA Pending CN116842043A (en) | 2023-06-30 | 2023-06-30 | Data query method, device, equipment and storage medium |
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| CN (1) | CN116842043A (en) |
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