A data query method, device, apparatus and storage medium

Abstract

This application discloses a data query method, apparatus, device, and storage medium. The method relates to big data and machine learning, and includes: a database middleware layer acquiring query configuration information and generating an aggregated query interface corresponding to the query configuration information. The database middleware layer uses the aggregated query interface to obtain an aggregated query request, which includes query text information and the business data to be queried. The query text information is segmented in a search engine to obtain segmented text information, and the target business data corresponding to the business data to be queried is obtained based on the query configuration information and the segmented text information. This method can generate an aggregated query interface corresponding to the query configuration information with simple configuration in the database middleware layer, and perform aggregated queries on business data in the database, improving the versatility of the database and also improving the efficiency and accuracy of business data query.

Description

Technical Field

[0001] This application relates to the field of big data, and in particular to a data query method, apparatus, device, and storage medium. Background Technology

[0002] With the advent of the cloud era, big data, as a collection of data whose scale far exceeds the capabilities of traditional database software tools in terms of acquisition, storage, management, and analysis, has attracted increasing attention. The business data stored in databases is often custom-developed. When new business data is added to the database, custom development is required for the new data, necessitating the creation of separate data interfaces, thus reducing the database's versatility. Furthermore, current technologies generally only provide basic query functions and cannot simultaneously search multiple business data sets with different data structures, thereby reducing the accuracy of business data queries. Summary of the Invention

[0003] This application provides a data query method, apparatus, device, and storage medium that can improve the versatility of databases and the accuracy of business data queries.

[0004] On the one hand, this application provides a data query method, the method comprising:

[0005] Obtain query configuration information, which represents the data protocol corresponding to the aggregate query;

[0006] Generate an aggregated query interface corresponding to the query configuration information;

[0007] The aggregate query request is obtained using the aggregate query interface. The aggregate query request includes query text information and multiple business information to be queried.

[0008] The query text information is segmented into words to obtain segmented text information;

[0009] Based on the query configuration information and the word segmentation text information, query the target business data corresponding to the business information to be queried.

[0010] On the other hand, a data query device is provided, which includes: a configuration information acquisition module, an interface generation module, a query request acquisition module, a word segmentation processing module, and an aggregation query module;

[0011] The configuration information acquisition module is used to acquire query configuration information, which represents the data protocol corresponding to the aggregate query.

[0012] The interface generation module is used to generate an aggregated query interface corresponding to the query configuration information;

[0013] The query request acquisition module is used to acquire an aggregated query request using the aggregated query interface. The aggregated query request includes query text information and multiple business information to be queried.

[0014] The word segmentation module is used to segment the query text information to obtain segmented text information;

[0015] The aggregation query module is used to query the target business data corresponding to the business information to be queried based on the query configuration information and the word segmentation text information.

[0016] On the other hand, an electronic device is provided, the device including a processor and a memory, the memory storing at least one instruction or at least one program, the at least one instruction or the at least one program being loaded and executed by the processor to implement a data query method as described above.

[0017] On the other hand, a computer-readable storage medium is provided, the storage medium including a processor and a memory, the memory storing at least one instruction or at least one program, the at least one instruction or the at least one program being loaded and executed by the processor to implement a data query method as described above.

[0018] According to one aspect of this application, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the method provided in the various alternative implementations of the aforementioned data query.

[0019] This application provides a data query method, apparatus, device, and storage medium. The method includes: a database middleware layer acquiring query configuration information and generating an aggregated query interface corresponding to the query configuration information. The database middleware layer uses the aggregated query interface to obtain an aggregated query request, which includes query text information and the business to be queried. The query text information is segmented in a search engine to obtain segmented text information. Based on the query configuration information and the segmented text information, the target business data corresponding to the business to be queried is obtained. This method can generate an aggregated query interface corresponding to the query configuration information with simple configuration in the database middleware layer, perform aggregated queries, improve the versatility of the database, and also improve the efficiency and accuracy of data query. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a schematic diagram illustrating an application scenario of a data query method provided in an embodiment of this application;

[0022] Figure 2 This is a schematic diagram of the distributed storage of the server middleware layer and the database in a data query method provided in an embodiment of this application;

[0023] Figure 3 A flowchart illustrating a data query method provided in this application embodiment;

[0024] Figure 4 A flowchart illustrating the word segmentation process of a data query method provided in this application embodiment;

[0025] Figure 5 A flowchart illustrating an aggregation query in a data query method provided in this application embodiment;

[0026] Figure 6 A schematic diagram of the configuration interface for the aggregated query condition field in a data query method provided in this application embodiment;

[0027] Figure 7 This is a flowchart illustrating conditional filtering of aggregated query results in a data query method provided in an embodiment of this application;

[0028] Figure 8 A flowchart illustrating a data query method provided in an embodiment of this application;

[0029] Figure 9 A schematic diagram of a training data model for a data query method provided in an embodiment of this application;

[0030] Figure 10 A logical diagram illustrating a data query method provided in this application for use in a "Look Around" scenario;

[0031] Figure 11 This is a schematic diagram of the server-side structure of a data query method provided in an embodiment of this application;

[0032] Figure 12 This is a schematic diagram of the structure of a data query device provided in an embodiment of this application;

[0033] Figure 13This is a schematic diagram of the hardware structure of a device for implementing the method provided in the embodiments of this application. Detailed Implementation

[0034] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0035] In the description of this application, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. Furthermore, the terms "first," "second," etc., are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein.

[0036] Please see Figure 1 This illustration shows an application scenario diagram of a data query method provided in this application embodiment. The application scenario includes a user terminal 110 and a server 120. The server 120 includes a database middleware layer 1201 and a data layer 1202. The user terminal 110 configures an aggregation protocol, enabling the database middleware layer 1201 to obtain query configuration information. The database middleware layer 1201 generates a corresponding aggregation query interface based on the query configuration information. The user terminal 110 inputs an aggregation query request to the database middleware layer 1201 based on the aggregation query interface. The database middleware layer 1201 obtains the query text information and multiple business information items to be queried from the aggregation query request. The data layer 1202 performs word segmentation processing on the query text information to obtain segmented text information. The data layer 1202 queries the target business data corresponding to the business information to be queried based on the query configuration information and the segmented text information.

[0037] In this embodiment, the user terminal 110 includes physical devices such as smartphones, desktop computers, tablets, laptops, digital assistants, and smart wearable devices, and may also include software running on the physical device, such as applications. The operating system running on the physical device in this embodiment may include, but is not limited to, Android, iOS, Linux, Unix, and Windows. The user terminal 110 also includes a UI (User Interface) layer, through which the user terminal 110 configures the aggregation protocol and displays target business data. Additionally, it sends aggregation query requests to the server 120 based on the API (Application Programming Interface).

[0038] In this embodiment, server 120 may include a standalone server, a distributed server, or a server cluster consisting of multiple servers. Server 120 may include a network communication unit, a processor, and a memory, etc. Specifically, server 120 can be used to obtain query configuration information, generate a corresponding aggregate query interface, obtain an aggregate query request using the aggregate query interface, and query the target business data corresponding to the business information to be queried based on the query configuration information and the aggregate query request.

[0039] In addition, it should be noted that, Figure 1 The server middleware layer 1201 and data layer 1202 in this embodiment are merely examples. In this specification, the server middleware layer 1201 and data layer 1202 in server 120 may also include a distributed database corresponding to a blockchain network. Specifically, as shown below... Figure 2 As shown, it can include distributed nodes 201, 202, 203, 204, 205, and 206. These distributed nodes can be connected via communication links, such as wired or wireless communication links.

[0040] Blockchain is a novel application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and cryptographic algorithms. Essentially, a blockchain is a decentralized database, a chain of data blocks linked together using cryptographic methods. Each data block contains information about a batch of network transactions, used to verify the validity of the information (anti-counterfeiting) and generate the next block. A blockchain can include an underlying platform, a platform product and service layer, and an application service layer.

[0041] The underlying blockchain platform can include processing modules such as user management, basic services, smart contracts, and operational monitoring. The user management module is responsible for managing the identity information of all blockchain participants, including maintaining public and private key generation (account management), key management, and maintaining the correspondence between user real identities and blockchain addresses (access management). Furthermore, under authorization, it monitors and audits transactions of certain real identities and provides risk control rule configuration (risk control audit). The basic services module is deployed on all blockchain node devices to verify the validity of business requests. After consensus is reached on valid requests, they are recorded in storage. For a new business request, the basic services first perform interface adaptation parsing and authentication (interface adaptation), and then encrypt the business information using a consensus algorithm (consensus management). After encryption, the data is transmitted completely and consistently to the shared ledger (network communication) and recorded and stored. The smart contract module is responsible for contract registration, issuance, triggering, and execution. Developers can define contract logic using a programming language and publish it to the blockchain (contract registration). According to the contract terms, the key or other events are invoked to trigger execution and complete the contract logic. It also provides functions for contract upgrades and cancellations. The operation monitoring module is mainly responsible for deployment, configuration modification, contract settings, cloud adaptation, and real-time status visualization during product launch, such as alarms, monitoring network conditions, and monitoring the health status of node devices.

[0042] Server 120 provides the basic capabilities and implementation framework for typical applications. Developers can leverage these basic capabilities, add business characteristics, and complete the blockchain implementation of business logic. Server 120 provides application services based on blockchain solutions to user terminal 110.

[0043] In this embodiment, server 120 uses word segmentation technology from machine learning to segment the query text information. Server 120 then performs subsequent aggregation query steps based on the segmentation results. Machine learning (ML) is a multidisciplinary field involving probability theory, statistics, approximation theory, convex analysis, algorithm complexity theory, and many other disciplines. It specifically studies how computers can simulate or implement human learning behavior to acquire new knowledge or skills and reorganize existing knowledge structures to continuously improve their performance. Machine learning is the core of artificial intelligence and the fundamental way to give computers intelligence; its applications span all areas of artificial intelligence. Machine learning and deep learning typically include techniques such as artificial neural networks, belief networks, reinforcement learning, transfer learning, inductive learning, and instructional learning.

[0044] Please see Figure 3 It demonstrates a data query method applicable to the server side, which includes:

[0045] S310. Obtain query configuration information, which represents the data protocol corresponding to the aggregate query;

[0046] Specifically, the query configuration information is the data protocol corresponding to the aggregation query. The data protocol can include multiple fields, such as data identifier information, business name, business description, business type, and pageviews. The data protocol and fields constitute the data structure of the corresponding business data. The query configuration can be done by adding the fields required for the aggregation query to the data protocol.

[0047] S320. Generate an aggregate query interface corresponding to the query configuration information;

[0048] Specifically, based on the query configuration information, a corresponding aggregate query interface is generated. The client can perform aggregate queries on business data in the data layer through this interface, and the data layer can return the target business data corresponding to the fields in the query configuration information to the client. The aggregate query interface is generated by the HyperText Transfer Protocol (HTTP) service of the database middleware layer, which is a "protocol-as-a-service" database middleware layer. The aggregate query interface corresponds to the HTTP protocol in the HTTP service. For example, when the HTTP service of the database middleware layer is a Representational State Transfer (RESTful) style protocol, the aggregate query interface is also a RESTful style interface. RESTful is a design style and development method for web applications based on the HTTP protocol, suitable for scenarios where the database middleware layer serves as a business enabling interface, enabling the client to call business data.

[0049] The database middleware layer includes an HTTP service. This service generates an interface corresponding to the data operation to be performed by the user, based on a configured data protocol, to receive the data operation request sent by the user and return the result. As an optional implementation, when the data operation is an aggregation query, the HTTP service generates an interface corresponding to the aggregation query to be performed by the user, based on a configured data protocol, to receive the aggregation query request sent by the user and return the result. The database middleware layer can also perform protocol checks on the query configuration information, obtain the check results, and convert the query configuration information into a data protocol applicable to the database. Based on this internal data protocol, it can retrieve business data from within the database. The database middleware layer encapsulates the database in the data layer, providing data access functionality to the user through the aggregation query interface generated by the HTTP service.

[0050] The data layer comprises a search engine and a database. The search engine contains search text information, which is text field information of business data stored within the search engine. The search text information is identified by a second data identifier. The database contains database content information, which is business data stored within the database. The database content information is identified by a first data identifier. There is a one-to-one correspondence between the data stored in the search engine and the database, which can be established using the first and second data identifiers. When executing an aggregate query, the search engine first retrieves the search text information and sends the corresponding second data identifier to the user. Then, based on the search text information, the database checks whether corresponding database content information exists. This determination is made using both the first and second data identifiers. Finally, the determined database content information is sent back to the user, allowing them to access the corresponding database content information when clicking on the second data identifier provided by the search engine.

[0051] The database middleware layer can generate corresponding interfaces through data protocol configuration, allowing users to perform data operations based on the interfaces without the need for additional development when adding new business functions. This improves the versatility of the database and enables aggregate queries, thereby improving the query performance of the database middleware layer and ultimately enhancing the efficiency and accuracy of data queries.

[0052] S330. Use the aggregate query interface to obtain the aggregate query request, which includes query text information and multiple business information to be queried;

[0053] S340. Perform word segmentation on the query text information to obtain segmented text information;

[0054] Further, please see Figure 4 The query text information is segmented into words to obtain segmented text information, including:

[0055] S400. Match the character information in the query text with the preset dictionary data;

[0056] S410. Use the character information in the query text that matches the single word in the dictionary data as the target single word information;

[0057] S420. Use the character information in the query text that matches the beginning of a multi-word phrase in the dictionary data as prefix information;

[0058] S430. Treat the characters following the prefix information in the query text information as suffix information;

[0059] S440. Combine the suffix information and the prefix information to obtain a set of combined word information;

[0060] S450. Match the combination word information set with dictionary data;

[0061] S460. If any combination word in the combination word information set matches the first word of a multi-character word in the dictionary data, then update the prefix information based on the combination word information that matches the first word of the multi-character word, and update the suffix information based on the updated prefix information.

[0062] S470. Repeat the steps of combining the updated prefix information and the updated suffix information to obtain the updated set of combined words, and matching the updated set of combined words with the dictionary data until the suffix information of the combined words in the updated set of combined words matches the word ending of the multi-character words in the dictionary data. Use the combined words in the updated set of combined words whose suffix information matches the word ending of the multi-character words in the dictionary data as the target multi-character words.

[0063] S480. Use the target single-word information and the target multi-word information as segmented text information.

[0064] Specifically, word segmentation can be performed using the IK Tokenizer plugin for the Elasticsearch search engine. Elasticsearch is a search server based on the full-text search engine (Lucene), providing a distributed search and data analysis engine with a RESTful interface. When using the IK Tokenizer for word segmentation, the query text information is first divided into character information.

[0065] The system matches character information with single-character words in the dictionary data. If a match is found, the matched character information is output as the target single-character word. If a match is found with the beginning of a multi-character word, the matched character information is used as a prefix, and the characters following the prefix in the query text are used as suffixes. The suffixes and prefixes are combined to obtain a set of combined words, which are then matched against the dictionary data. If a multi-character word is found in the dictionary data, this combined word is output as the target multi-character word.

[0066] Since there may also be words with more than two character information, or fixed phrases composed of multiple words. For example, in the phrase "While the front door drives out the tiger, the back door admits the wolf", "front door", "drives out the tiger", "tiger", "back door", "admits", "wolf" can all be divided as words. At the same time, "While the front door drives out the tiger, the back door admits the wolf" is also a fixed phrase combination, and both "While the front door drives out the tiger" and "the back door admits the wolf" can be regarded as a word. Therefore, after dividing multi-character words with two characters, if the combined word information of these two characters can also match the word head of multi-character words in the dictionary data, then update the prefix information according to the combined word information that matches the word head of multi-character words in the dictionary data, and update the suffix information. Take this combined word information as the updated prefix information, and take the character information after this combined word in the query text information as the updated suffix information. Recombine the updated prefix information and the updated suffix information to obtain a new set of combined word information. Then match the combined word information in the new set of combined word information with the dictionary data. When the suffix information of the combined word information successfully matches the word tail of the multi-character word in the dictionary data, output the combined word with the successfully matched suffix information and the word tail of the multi-character word in the dictionary data as the target multi-character word information.

[0067] The target single-character word information and the target multi-character word information form the segmented text information. For example, after segmenting "While the front door drives out the tiger, the back door admits the wolf", the segmented text information obtained after the segmentation process should be "front", "front door", "drives out", "tiger", "While the front door drives out the tiger", "back", "back door", "admits", "wolf", "the back door admits the wolf".

[0068] Perform a segmentation process on the search text information to obtain the segmented text information, and use the segmented text information to match the search text information in the subsequent query steps, which can improve the accuracy and search efficiency of data query.

[0069] S350. Query the target service data corresponding to the service information to be queried according to the query configuration information and the segmented text information.

[0070] Furthermore, please refer to Figure 5 , the query configuration information includes the basic query protocol and the aggregation query protocol. Querying the target service data corresponding to the service information to be queried according to the query configuration information and the segmented text information includes:

[0071] S510. Obtain the query permission for the service to be queried corresponding to the service information to be queried;

[0072] S520. Determine the aggregation query condition fields according to the aggregation query protocol;

[0073] S530. Determine the basic query fields according to the basic query protocol;

[0074] S540. Based on query permissions, query the search text information that matches the basic query field, the aggregate query condition field, and the word segmentation text information respectively from the search text information. The search text information is the text field information of the business data stored in the search engine.

[0075] S550. Use the search text information that matches the basic query field, the aggregate query condition field, and the word segmentation text information as the aggregate query result;

[0076] S560. Use the business data corresponding to the aggregate query results as the target business data, which is business data with different data protocols.

[0077] Specifically, aggregate queries can simultaneously search business data from multiple sources using different data protocols, thus involving multiple pieces of business information to be queried. Before performing an aggregate query, the user client needs to obtain query permissions for each of these pieces of business information. If the user client cannot obtain query permissions for even one of the pieces of business information, then the user client cannot query that piece of business information.

[0078] The aggregation query protocol includes aggregation query condition fields; please refer to [link / reference]. Figure 6 ,like Figure 6 The diagram shows the configuration interface for aggregate query condition fields. Only business data that includes aggregate query condition fields can be used for aggregate queries, and the data types of the aggregate query condition fields in the business data must be consistent. For example, if the aggregate query condition field is pageviews, and the data type is integer, and business data A has a pageviews field with an integer data type, and business data B has a pageviews field with an integer data type, and business data C lacks a pageviews field, while the pageviews field in business data D has a floating-point data type, then business data A and business data B can be used as target business data transmitted to the user. However, business data C and business data D cannot be used as the result of the aggregate query that specifies pageviews as the aggregate query condition field, and therefore cannot be used as target business data transmitted to the user.

[0079] The business data corresponding to the aggregate query results can be business data with different data protocols, as long as these business data all include the aggregate query protocol.

[0080] The basic query protocol includes basic query fields, which can be fields such as title, author, or abstract. The content corresponding to the basic query fields includes query text information, which can be used for word segmentation to obtain segmented text information. The content also includes target business data content sent to the user's end for display in aggregate queries.

[0081] When performing aggregate queries based on query permissions, the segmented text information is used as keywords to match the search text information in the search engine. The results that match the basic query fields and aggregate query condition fields are used as the aggregate query results.

[0082] The business data corresponding to the aggregated query results is used as the target business data, which can be retrieved from the database. When retrieving the target business data, the database middleware can convert the basic query protocol and aggregated query protocol used in the search engine into a data protocol suitable for the database's internal use. Based on this internally applicable data protocol, the business data corresponding to the aggregated query results is retrieved from the database.

[0083] By using aggregate queries, multiple search text messages can be retrieved at once, improving the efficiency of data retrieval. At the same time, only search text messages that meet the aggregate query conditions can be used as aggregate query results, which can improve the accuracy of data retrieval.

[0084] Further, please see Figure 7 The aggregated query request also includes business data range information. Based on the query configuration information and word segmentation text information, the target business data corresponding to the business information to be queried also includes:

[0085] S710. Obtain query permissions for the business information to be queried;

[0086] S720. Determine the aggregate query condition fields according to the aggregate query protocol;

[0087] S730. Determine the basic query fields according to the basic query protocol;

[0088] S740. Based on query permissions, retrieve search text information that matches the basic query field, the aggregate query condition field, and the word segmentation text information from the search text information. The search text information is the text field information of the business data stored in the search engine.

[0089] S750. Use the search text information that matches the basic query field, the aggregate query condition field, and the word segmentation text information as the aggregate query result;

[0090] S760. Parse the business data range information in the aggregate query request to obtain filtering condition information that can be recognized by the search engine;

[0091] S770. Filter aggregated query results that match the filter criteria from the aggregated query results;

[0092] The business data corresponding to the aggregate query results is used as the target business data, including:

[0093] S780. Use the business data corresponding to the matched aggregate query results as the target business data.

[0094] Specifically, business scope information refers to the information used by operators to limit the scope of aggregated query results, while filter condition information is business scope information that the search engine can recognize. Based on the filter condition information, the search engine filters aggregated query results that match the scope defined by the operators. Thus, the filtered aggregated query results yield the target business data that meets the user's needs. The operators can be shown in the table below:

[0095]

[0096] The business scope information is parsed and converted into filtering conditions that can be recognized by the search engine. Aggregated query results that match the filtering conditions are then selected, and the business data corresponding to these matching results is used as the target business data. For example, if the filtering condition is to retrieve the top 100 aggregated query results, then the top 100 results are selected based on this condition, and the business data corresponding to these results is used as the target business data.

[0097] By using conditional filtering, aggregated query results can be filtered to obtain results that better meet user needs, thereby improving the accuracy of data queries.

[0098] Furthermore, the business data corresponding to the aggregated query results is included as the target business data, including:

[0099] S810. Query the target database content information that corresponds to the aggregate query result in the database content information. The database content information is the business data stored in the database.

[0100] S820. Use the content information of the target database as the target business data.

[0101] Specifically, see Figure 8 ,like Figure 8The diagram illustrates the query process of an aggregate query. After retrieving the aggregate query results from the search engine, the server performs an existence check on the results in the database to verify data consistency. The existence check involves identifying the target database content information corresponding to the aggregate query result within the database's content information. This target database content information is then sent to the user as the target business data, thus ensuring that the aggregate query result definitely exists in the database. If an aggregate query result does not have corresponding target database content information, the result is invalid, and the corresponding target database content information cannot be sent to the user.

[0102] As an optional embodiment, second data identifier information corresponding to the aggregated query results in the search engine can be obtained. Then, a first data identifier information corresponding to the second data identifier information can be queried in the database. The database content information corresponding to the first data identifier information is used as the target database content information corresponding to the search result. This target database content information is then used as the target business data and sent to the user terminal. If no corresponding first data identifier information exists for a given second data identifier information, the aggregated query result corresponding to that second data identifier information does not have corresponding target database content information. Therefore, the aggregated query result corresponding to that second data identifier information is an invalid result, and the corresponding business data cannot be returned to the user terminal.

[0103] During operation, data consistency checks are performed to ensure that all aggregate query results are valid results that can be obtained from the database, thereby improving the rationality of data queries and avoiding the generation of illegal results.

[0104] Further, please see Figure 9 The method also includes:

[0105] S910. Retrieve text field information for newly added database content;

[0106] S920. Combine the text field information to form the search text information corresponding to the newly added database content information;

[0107] S930. Store search text information in the search engine.

[0108] Specifically, the interfaces generated based on the database middleware layer can also include interfaces for adding, modifying, and deleting data, as well as basic data query interfaces, allowing for data operations corresponding to different interfaces. An aggregated query interface can only be generated when an aggregated query protocol is added during data protocol configuration. If only a basic query protocol is configured, a basic query interface will be generated, and aggregated queries will not be possible.

[0109] The database middleware layer generates an interface for adding new data, which is then used to add business data, essentially storing the new database content information. The search engine can then retrieve the text field information from the new database content information based on the applicable data protocol within the database, identifying fields containing text content. This text field information is then combined to form search text information, which is stored. The search engine can perform word segmentation and indexing on the search text information to obtain word segmentation data associated with it. During the aggregation query step, the word segmentation text information and the word segmentation data are compared to determine the search text information that matches the word segmentation text information. The text field information can include content corresponding to fields such as author, abstract, and title.

[0110] If a data modification interface is generated through a database middleware layer, and business data is modified using this interface, then the database content information is modified. If the text fields of the database content information are modified, the search engine will re-retrieve the modified text fields and update the search results accordingly.

[0111] A data deletion interface is generated through the database middleware layer. This interface is used to delete business data, which means deleting the database content information to be deleted from the database. The process involves retrieving the first data identifier information corresponding to the database content information to be deleted, determining the corresponding second data identifier information based on the first data identifier information, deleting the database content information corresponding to the first data identifier information, and deleting the search text information corresponding to the second data identifier information from the search engine.

[0112] When adding, modifying, or deleting data, failures may occur, leading to inconsistencies between the search engine and the database. Therefore, periodic consistency checks are necessary. For further details, please refer to [link to relevant documentation]. Figure 10 Methods for performing consistency checks include:

[0113] S1010. Transmit the text field information of the database content information to the search engine so that the search engine can update the search text information based on the text field information of the database content information;

[0114] and / or;

[0115] S1020. Obtain the first data identifier information corresponding to the database content information in the database;

[0116] S1020. Obtain the second data identifier information corresponding to the search text information in the search engine;

[0117] S1030. Based on the first data identifier information and the second data identifier information, perform consistency verification on the data in the database and the search engine, so that the search engine deletes the search text information corresponding to the second data identifier information that failed the verification.

[0118] Specifically, in addition to performing data consistency checks on the database and search engine during their operation at the data layer, data consistency checks can also be performed on the database and search engine according to a preset check cycle.

[0119] As an optional embodiment, text field information from the database content can be transmitted to the search engine, overwriting the search text information in the search engine. This updates the search text information, ensuring consistency between the search text information and the database content information. For example, the database contains database content information X and database content information Y. The text field information for database content information X is X1, and the text field information for database content information Y is Y1. The search engine contains search text information X1. Transmitting text field information X1 and text field information Y1 to the search engine causes the search engine to overwrite the original search text information X1, resulting in search text information X1 and search text information Y1 that are consistent with the database content information.

[0120] As an optional embodiment, a first data identifier corresponding to database content information in the database and a second data identifier corresponding to search text information in the search engine can be obtained. The first and second data identifiers are compared. If no first data identifier corresponding to the second data identifier exists, the search text information corresponding to the second data identifier is determined to be redundant data and deleted, thus completing the consistency check. For example, database content information X corresponds to first data identifier x, search text information X1 corresponds to second data identifier x1, and search text information Y1 corresponds to second data identifier y1. Where second data identifier x1 corresponds to first data identifier x, then search text information X1 corresponds to database content information X. If no first data identifier corresponding to second data identifier y1 exists, then search text information Y1 is redundant data and is deleted from the search engine.

[0121] Periodically performing consistency checks on the data in the search engine and database ensures that the results of aggregated queries are all legitimate results that can be obtained from the corresponding business data in the database, thereby improving the rationality of data queries and avoiding the generation of illegal results.

[0122] As an optional embodiment, please refer to Figure 11 ,like Figure 11The diagram illustrates the server-side architecture. The database middleware layer generates interfaces for adding, deleting, modifying, basic querying, and aggregated querying. Based on the functions in the aggregated query execution module, aggregated queries are performed in the data layer. When an aggregated query is performed, the user configures the corresponding data protocol on the server's configuration platform, adding the necessary fields to the data protocol to obtain query configuration information. This configuration information includes the basic query protocol and the aggregated query protocol. The server middleware layer generates the corresponding aggregated query interface based on the query configuration information. The user sends an aggregated query request through this interface, which includes query text information and multiple pieces of business information to be queried. After the database middleware layer determines that the user has the query permissions for the business information to be queried, the server's aggregated query execution module transmits the query text information corresponding to the text fields in the query configuration information to the search engine. The search engine performs word segmentation on the query text information to obtain segmented text information. The search engine then queries the aggregated query results corresponding to the segmented text information, the basic query protocol, and the aggregated query protocol. The search engine segments all stored search text information into words, obtaining segmented data. When the segmented data matches the segmented text information, it is identified as the initial query result. Then, from the initial query result, the target query result matching the fields specified in the basic query protocol and the aggregation query protocol is determined, and this target query result is used as the aggregation query result. The aggregation query execution module can also parse the business scope information in the aggregation query request to determine the filtering conditions that the search engine can recognize. The search engine filters the aggregation query results based on these filtering conditions. After determining the aggregation query result, the aggregation query execution module can also perform an existence check on the aggregation query result at runtime, querying the database for the target database content information corresponding to the aggregation query result. The database middleware layer uses the target database content information as the target business data and, using the aggregation query interface, feeds back the summary information of the target business data to the user.

[0123] The aggregate query execution module can also periodically perform consistency checks on the data in the database and the search engine. It can delete redundant data in the search engine or overwrite the data in the search engine with data from the database to ensure that the data in the database and the search engine are consistent.

[0124] This application proposes a data query method, which includes: a database middleware layer obtaining query configuration information and generating an aggregated query interface corresponding to the query configuration information. The database middleware layer uses the aggregated query interface to obtain an aggregated query request, which includes query text information and the business data to be queried. The query text information is then segmented in a search engine to obtain segmented text information. Based on the query configuration information and the segmented text information, the target business data corresponding to the business data to be queried is obtained. This method allows for simple configuration within the database middleware layer to generate an aggregated query interface corresponding to the query configuration information, enabling aggregated queries and improving the database's versatility, accuracy, and efficiency of data queries. Furthermore, this method improves the rationality of data queries and avoids generating illegal results through runtime data consistency checks and periodic data consistency checks.

[0125] This application also provides a data query device; please refer to [link to relevant documentation]. Figure 12 The device includes: a configuration information acquisition module 1210, an interface generation module 1220, a query request acquisition module 1230, a word segmentation processing module 1240, and an aggregation query module 1250;

[0126] The configuration information acquisition module 1210 is used to acquire query configuration information, which represents the data protocol corresponding to the aggregate query.

[0127] The interface generation module 1220 is used to generate an aggregate query interface corresponding to the query configuration information;

[0128] The query request acquisition module 1230 is used to acquire aggregate query requests using the aggregate query interface. The aggregate query request includes query text information and multiple business information to be queried.

[0129] The word segmentation module 1240 is used to perform word segmentation on the query text information to obtain segmented text information.

[0130] The aggregation query module 1250 is used to query the target business data corresponding to the business information to be queried based on the query configuration information and the word segmentation text information.

[0131] Furthermore, the query configuration information includes the basic query protocol and the aggregated query protocol. The aggregated query module 1250 includes: a query permission acquisition unit, an aggregated query condition acquisition unit, a basic query condition acquisition unit, a search text matching unit, an aggregated query result acquisition unit, and a target business data acquisition unit.

[0132] The query permission acquisition unit is used to acquire the query permission for the business information to be queried.

[0133] The aggregation query condition acquisition unit is used to determine the aggregation query condition fields according to the aggregation query protocol;

[0134] The basic query condition acquisition unit is used to determine the basic query fields according to the basic query protocol;

[0135] The search text matching unit is used to retrieve search text information that matches the basic query field, the aggregate query condition field, and the word segmentation text information from the search text information based on query permissions. The search text information is the text field information of the business data stored in the search engine.

[0136] The aggregate query result acquisition unit is used to obtain the search text information that matches the basic query field, the aggregate query condition field, and the word segmentation text information as the aggregate query result;

[0137] The target business data acquisition unit is used to take the business data corresponding to the aggregate query results as the target business data.

[0138] Furthermore, the aggregation query module 1250 also includes:

[0139] The filter condition acquisition unit is used to parse the business data range information in the aggregate query request to obtain filter condition information that can be recognized by the search engine.

[0140] The filtering unit is used to filter aggregated query results that match the filtering conditions.

[0141] Furthermore, the target business data acquisition unit is also used to take the business data corresponding to the matched aggregate query results as the target business data.

[0142] Furthermore, the target business data acquisition unit includes: a business data query unit.

[0143] The business data query unit is used to query the target database content information that corresponds to the aggregate query result in the database content information. The database content information is the business data stored in the database, and the target database content information is used as the target business data.

[0144] Furthermore, the device also includes: a text field acquisition module, a search text composition module, and a search text storage module;

[0145] The text field acquisition module is used to retrieve text field information from pre-stored business data;

[0146] The search text composition module is used to compose search text information corresponding to pre-stored business data from text field information.

[0147] The search text storage module is used to store search text information into the search engine.

[0148] Furthermore, the device also includes: a search text update module, a first data identifier acquisition module, a second data identifier acquisition module, and a consistency verification module;

[0149] The search text update module is used to transmit the text field information of the database content information to the search engine, so that the search engine can update the search text information according to the text field information of the database content information.

[0150] and / or;

[0151] The first data identifier acquisition module is used to acquire the first data identifier information corresponding to the database content information in the database;

[0152] The second data identifier acquisition module is used to acquire the second data identifier information corresponding to the search text information in the search engine;

[0153] The consistency verification module is used to perform consistency verification on the data in the database and the search engine based on the first data identification information and the second data identification information, so that the search engine deletes the search text information corresponding to the second data identification information that failed the verification.

[0154] Furthermore, the word segmentation processing module 1240 includes: a single-character word matching unit, a combined word acquisition unit, a multi-character word matching unit, and a word segmentation text determination unit.

[0155] The single-word matching unit is used to match the character information in the query text information with the preset dictionary data, and to take the character information in the query text information that matches the single-word information in the dictionary data as the target single-word information;

[0156] The combined word acquisition unit is used to take the character information in the query text information that matches the first word of a multi-character word in the dictionary data as prefix information; take the character information in the query text information that follows the prefix information as suffix information; and combine the suffix information and the prefix information to obtain the combined word information set.

[0157] The multi-word matching unit is used to match the combined word information set and the dictionary data. If any combined word information in the combined word information set matches the beginning of a multi-word in the dictionary data, the prefix information is updated based on the combined word information that matches the beginning of the multi-word, and the suffix information is updated based on the updated prefix information. The steps of combining the updated prefix information and the updated suffix information are repeated to obtain the updated combined word information set, and the updated combined word information set and the dictionary data are matched until the suffix information of the combined word information in the updated combined word information set matches the end of a multi-word in the dictionary data. The combined word information that matches the end of the suffix information in the updated combined word information set with the end of a multi-word in the dictionary data is taken as the target multi-word information.

[0158] The word segmentation text determination unit is used to use the target single-character word information and the target multi-character word information as the word segmentation text information.

[0159] The apparatus provided in the above embodiments can execute the methods provided in any embodiment of this application, and has the corresponding functional modules and beneficial effects for executing the method. Technical details not described in detail in the above embodiments can be found in a data query method provided in any embodiment of this application.

[0160] This embodiment also provides a computer-readable storage medium storing computer-executable instructions, which are loaded by a processor and executed by the data query method described above in this embodiment.

[0161] This embodiment also provides a device including a processor and a memory, wherein the memory stores a computer program adapted to be loaded by the processor and executed as described above in this embodiment of a data query method.

[0162] The device can be a computer terminal, a mobile terminal, or a server, and it can also participate in constituting the apparatus or system provided in the embodiments of this application. For example... Figure 13 As shown, server 13 may include one or more processors 1302 (shown as 1302a, 1302b, ..., 1302n in the figure) 1302 (processor 1302 may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.), a memory 1304 for storing data, and a transmission device 1306 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a network interface, a power supply, and / or a camera. Those skilled in the art will understand that... Figure 13 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, server 13 may also include... Figure 13 The more or fewer components shown, or having the same Figure 13 The different configurations shown.

[0163] It should be noted that the aforementioned one or more processors 1302 and / or other data processing circuitry are generally referred to herein as “data processing circuitry.” This data processing circuitry may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuitry may be a single, independent processing module, or may be integrated, in whole or in part, into any other element within the server 13.

[0164] The memory 1304 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the method in this embodiment. The processor 1302 executes various functional applications and data processing by running the software programs and modules stored in the memory 1304, thereby realizing the above-described method for generating temporal behavior capture boxes based on self-attention networks. The memory 1304 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 1304 may further include memory remotely located relative to the processor 1302, and these remote memories can be connected to the server 13 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0165] The transmission device 1306 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the mobile terminal 13. In one example, the transmission device 1306 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 1306 may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0166] The display can be, for example, a touchscreen liquid crystal display (LCD) that allows the user to interact with the user interface of server 13.

[0167] This specification provides method operation steps as shown in the embodiments or flowcharts, but based on conventional or non-inventive labor, more or fewer operation steps may be included. The steps and order listed in the embodiments are merely one possible execution order among many steps and do not represent the only execution order. In actual system or interrupt product execution, the methods shown in the embodiments or drawings can be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment).

[0168] The structures shown in this embodiment are only partial structures related to the solution of this application and do not constitute a limitation on the device to which the solution of this application is applied. Specific devices may include more or fewer components than shown, or combinations of certain components, or arrangements of different components. It should be understood that the methods, apparatuses, etc., disclosed in this embodiment can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection between devices or unit modules through some interfaces.

[0169] Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0170] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this specification can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of each example have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0171] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A data query method, characterized in that, The method includes: Obtain query configuration information, which represents the data protocol corresponding to the aggregate query; the query configuration information includes the basic query protocol and the aggregate query protocol. Generate an aggregated query interface corresponding to the query configuration information; The aggregate query request is obtained using the aggregate query interface. The aggregate query request includes query text information and multiple business information to be queried. The query text information is segmented into words to obtain segmented text information; Based on the query configuration information and the word segmentation text information, query the target business data corresponding to the business information to be queried; The step of querying the target business data corresponding to the business information to be queried based on the query configuration information and the word segmentation text information includes: Obtain query permissions for the business information to be queried; Determine the aggregation query condition fields according to the aggregation query protocol; Based on the aforementioned basic query protocol, determine the basic query fields; Based on the query permissions, search text information that matches the basic query field, the aggregate query condition field, and the word segmentation text information is retrieved from the search text information. The search text information is the text field information of business data stored in the search engine. The search text information that matches the basic query field, the aggregate query condition field, and the word segmentation text information is used as the aggregate query result; The business data corresponding to the aggregated query results is used as the target business data, and the target business data is business data with different data protocols.

2. The data query method according to claim 1, characterized in that, The aggregate query request also includes business data range information, and before using the business data corresponding to the aggregate query result as the target business data, it further includes: The business data range information in the aggregated query request is parsed to obtain the filtering condition information that the search engine can recognize; Filter the aggregated query results that match the filtering conditions from the aggregated query results; The step of using the business data corresponding to the aggregated query result as the target business data includes: The business data corresponding to the matched aggregate query results is used as the target business data.

3. The data query method according to claim 1 or 2, characterized in that, The step of using the business data corresponding to the aggregated query result as the target business data includes: Query the target database content information that corresponds to the aggregated query result in the database content information, where the database content information is business data stored in the database; The target database content information is used as the target business data.

4. The data query method according to claim 1, characterized in that, The method further includes: Retrieve text field information for newly added database content; The text field information is used to compose the search text information corresponding to the newly added database content information; The search text information is stored in the search engine.

5. The data query method according to claim 1, characterized in that, The method further includes: The text field information of the database content information is transmitted to the search engine so that the search engine updates the search text information based on the text field information of the database content information. and / or; Obtain the first data identifier information corresponding to the database content information in the database; Obtain the second data identifier information corresponding to the search text information in the search engine; Based on the first data identifier information and the second data identifier information, a consistency check is performed on the data in the database and the search engine, so that the search engine deletes the search text information corresponding to the second data identifier information that failed the check.

6. The data query method according to claim 1, characterized in that, The word segmentation process performed on the query text information to obtain segmented text information includes: The character information in the query text is matched with preset dictionary data; The character information in the query text that matches the single word in the dictionary data is taken as the target single word information; The character information in the query text that matches the first word of a multi-word phrase in the dictionary data is used as prefix information; The characters in the query text information that follow the prefix information are used as suffix information; The suffix information and the prefix information are combined to obtain a set of combined word information; The combined word information set and the dictionary data are matched; If any combination word in the combination word information set matches the first word of a multi-character word in the dictionary data, then the prefix information is updated based on the combination word information that matches the first word of the multi-character word. The suffix information is updated based on the updated prefix information; Repeat the steps of combining the updated prefix information and the updated suffix information to obtain an updated set of combined word information, and matching the updated set of combined word information with the dictionary data until the suffix information of the combined word information in the updated set of combined word information matches the word ending of the multi-character words in the dictionary data. The combined word information in the updated set of combined word information whose suffix information matches the word ending of the multi-character words in the dictionary data is taken as the target multi-character word information. The target single-word information and the target multi-word information are used as the segmented text information.

7. A data query device, characterized in that, The device includes: a configuration information acquisition module, an interface generation module, a query request acquisition module, a word segmentation processing module, and an aggregation query module; The configuration information acquisition module is used to acquire query configuration information, which represents the data protocol corresponding to the aggregate query; the query configuration information includes the basic query protocol and the aggregate query protocol. The interface generation module is used to generate an aggregated query interface corresponding to the query configuration information; The query request acquisition module is used to acquire an aggregated query request using the aggregated query interface. The aggregated query request includes query text information and multiple business information to be queried. The word segmentation module is used to segment the query text information to obtain segmented text information; The aggregation query module is used to query the target business data corresponding to the business information to be queried based on the query configuration information and the word segmentation text information; The aggregated query module includes a query permission acquisition unit, an aggregated query condition acquisition unit, a basic query condition acquisition unit, a search text matching unit, an aggregated query result acquisition unit, and a target business data acquisition unit; The query permission acquisition unit is used to acquire the query permission for the business to be queried corresponding to the business information to be queried; The aggregation query condition acquisition unit is used to determine the aggregation query condition fields according to the aggregation query protocol; The basic query condition acquisition unit is used to determine the basic query fields according to the basic query protocol; The search text matching unit is used to query search text information that matches the basic query field, the aggregate query condition field, and the word segmentation text information respectively, based on the query permission. The search text information is the text field information of business data stored in the search engine. The aggregated query result acquisition unit is used to take the search text information that matches the basic query field, the aggregated query condition field and the word segmentation text information as the aggregated query result; The target business data acquisition unit is used to take the business data corresponding to the aggregated query result as the target business data, and the target business data is business data with different data protocols.

8. The apparatus according to claim 7, characterized in that, The aggregation query module also includes: The filtering condition acquisition unit is used to parse the business data range information in the aggregate query request to obtain filtering condition information that the search engine can recognize. The filtering unit is used to filter aggregated query results that match the filtering condition information from the aggregated query results; The target business data acquisition unit is further configured to use the business data corresponding to the matched aggregate query result as the target business data.

9. The apparatus according to claim 7 or 8, characterized in that, The target business data acquisition unit includes a business data query unit; The business data query unit is used to query the target database content information corresponding to the aggregated query result in the database content information, where the database content information is business data stored in the database; and the target database content information is used as the target business data.

10. The apparatus according to claim 7, characterized in that, The device further includes: a text field acquisition module, a search text composition module, and a search text storage module; The text field acquisition module is used to acquire text field information of newly added database content information; The search text composition module is used to compose the text field information into search text information corresponding to the newly added database content information; The search text storage module is used to store the search text information in the search engine.

11. The apparatus according to claim 7, characterized in that, The device further includes: a search text update module, a first data identifier acquisition module, a second data identifier acquisition module, and a consistency verification module; The search text update module is used to transmit the text field information of the database content information to the search engine, so that the search engine updates the search text information according to the text field information of the database content information. and / or; The first data identifier acquisition module is used to acquire the first data identifier information corresponding to the database content information in the database; The second data identifier acquisition module is used to acquire the second data identifier information corresponding to the search text information in the search engine; The consistency verification module is used to perform consistency verification on the data in the database and the search engine based on the first data identification information and the second data identification information, so that the search engine deletes the search text information corresponding to the second data identification information that failed the verification.

12. The apparatus according to claim 7, characterized in that, The word segmentation processing module includes: a single-character word matching unit, a combined word acquisition unit, a multi-character word matching unit, and a word segmentation text determination unit; The single-word matching unit is used to match the character information in the query text information with the preset dictionary data; and to take the character information in the query text information that matches the single-word information in the dictionary data as the target single-word information. The combined word acquisition unit is used to take the character information in the query text information that matches the first word of the multi-word in the dictionary data as prefix information; take the character information in the query text information after the prefix information as suffix information; and combine the suffix information and the prefix information to obtain a combined word information set. The multi-character word matching unit is used to match the combined word information set and the dictionary data. If any combined word information in the combined word information set matches the beginning of a multi-character word in the dictionary data, the prefix information is updated based on the combined word information matching the beginning of the multi-character word. The suffix information is updated based on the updated prefix information. The steps of combining the updated prefix information and the updated suffix information to obtain an updated combined word information set and matching the updated combined word information set with the dictionary data are repeated until the suffix information of the combined word information in the updated combined word information set matches the end of a multi-character word in the dictionary data. The combined word information whose suffix information in the updated combined word information set matches the end of a multi-character word in the dictionary data is taken as the target multi-character word information. The word segmentation text determination unit is used to use the target single-word information and the target multi-word information as the word segmentation text information.

13. An electronic device, characterized in that, The device includes a processor and a memory, the memory storing at least one instruction or at least one program, the at least one instruction or the at least one program being loaded and executed by the processor to implement a data query method as described in any one of claims 1-6.

14. A computer-readable storage medium, characterized in that, The storage medium includes a processor and a memory, wherein the memory stores at least one instruction or at least one program, and the at least one instruction or the at least one program is loaded and executed by the processor to implement a data query method as described in any one of claims 1-6.

15. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by an electronic device, it implements a data query method as described in any one of claims 1-6.

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