Data processing method and device, server, client, medium and program product

Abstract

The application provides a data processing method and device, a server, a client, a medium and a program product, relates to the technical field of big data, and the method comprises the following steps: constructing a search query instruction according to user input information; sending the search query instruction to a target search server, so that the target search server performs full-text search according to the search query instruction and obtains an initial query result; the target search server stores various asset data according to a target storage format; the initial query result is acquired from the target search server, and format conversion is performed on the initial query result, so that asset data corresponding to the target storage format is converted into asset data query results based on asset types; and the asset data query results are sent to a client corresponding to the user input information. The method of the application solves the problem that the retrieval mechanism based on attributes or attribute sets in the prior art cannot comprehensively retrieve uncertain multi-attribute documents.

Description

Technical Field

[0001] This application relates to the field of big data technology, and in particular to a data processing method, apparatus, server, client, medium and program product. Background Technology

[0002] The R&D process of large financial enterprises is a complex and systematic process. During the R&D phase, R&D personnel need to consult a variety of asset documents to meet R&D needs, such as design documents, development code assets, testing process assets, as well as various types of financial R&D assets such as standard definitions and specifications.

[0003] Currently, the use of distributed search servers (Elasticsearch, ES) for general retrieval operations is quite common in enterprises. However, its retrieval mechanism is limited to attributes or attribute sets. Since different asset types in financial enterprises may have uncertain multi-attribute situations, the retrieval method based on the above-mentioned specific attributes or attribute sets will make it difficult to comprehensively search asset data with uncertain attributes. This obviously cannot meet the needs of large financial enterprises for general retrieval of documents with uncertain multi-attribute attributes, thus indirectly affecting R&D efficiency. Summary of the Invention

[0004] This application provides a data processing method, apparatus, server, client, medium, and program product to solve the problem that existing technologies are unable to perform general retrieval of uncertain multi-attribute documents, thereby affecting the R&D efficiency of financial enterprises.

[0005] In a first aspect, this application provides a data processing method applied to a server, comprising:

[0006] Construct search query instructions based on user input;

[0007] The search query command is sent to the target search server, which then performs a full-text search based on the search query command to obtain initial query results; wherein, the target search server stores various asset data according to the target storage format;

[0008] The initial query results are obtained from the target search server, and the format of the initial query results is converted to convert the asset data corresponding to the target storage format into asset data query results based on asset type.

[0009] The asset data query results are sent to the client corresponding to the user input information, so that the client can display the asset data in the asset data query results according to the asset type.

[0010] In one implementation, the target storage format includes at least one of the following format items: a first format item corresponding to an asset attribute identifier, a second format item corresponding to a first asset attribute value, and a third format item corresponding to an asset type.

[0011] In one implementation, the format conversion of the initial query result includes:

[0012] Extract the data information carried by each format item in the initial query result, and determine the asset attribute identifier, first asset attribute value and asset type contained in the initial query result based on the data information;

[0013] For each of the asset types, the asset attribute identifier and the first asset attribute value are bound together to obtain the second asset attribute value;

[0014] The asset data query result is obtained after format conversion based on the asset type and the second asset attribute value.

[0015] In one implementation, before constructing a search query instruction based on user input information, the method further includes:

[0016] In response to an asset data retrieval request initiated by the client, obtain user input information;

[0017] The step of constructing search query instructions based on user input information includes:

[0018] The information to be queried is determined based on the user input information, and the search query instruction is constructed based on the information to be queried.

[0019] In one implementation, the user input information includes a predefined search expression;

[0020] The step of obtaining user input information includes: parsing the parameter information carried by the data retrieval request, obtaining a predefined search expression from the parsing result, and the search expression being used to determine the information to be queried.

[0021] Secondly, a data processing method is provided for application on a client side, including:

[0022] Receive user input information and generate an asset data retrieval request based on the user input information;

[0023] The system initiates an asset data retrieval request to the server, so that the server obtains the user input information according to the asset data retrieval request, constructs a search query instruction according to the user input information, and obtains initial query results based on the interaction with the target search server. The target search server stores various types of asset data according to a target storage format, and the server performs format conversion on the initial query results to convert the asset data corresponding to the target storage format into asset data query results based on asset type.

[0024] Obtain the asset data query results and display the asset data in the asset data query results according to the asset type.

[0025] In one implementation, displaying the asset data in the asset data query results according to the asset type includes:

[0026] Select the corresponding display template from the preset display templates according to the asset type, and display the asset data corresponding to the asset type according to the display template.

[0027] Thirdly, a data processing apparatus is provided for use with a server, comprising:

[0028] The module is configured to build search query instructions based on user input.

[0029] The query module is configured to send the search query command to the target search server, so that the target search server performs a full-text search according to the search query command and obtains initial query results; wherein, the target search server stores various asset data according to the target storage format;

[0030] The conversion module is configured to obtain the initial query results from the target search server and perform format conversion on the initial query results to convert the asset data corresponding to the target storage format into asset data query results based on asset type.

[0031] The sending module is configured to send the asset data query results to the client corresponding to the user input information, so that the client can display the asset data in the asset data query results according to the asset type.

[0032] Fourthly, a data processing apparatus is provided for use on a client side, comprising:

[0033] The interaction module is configured to receive user input information and generate an asset data retrieval request based on the user input information.

[0034] The request module is configured to initiate the asset data retrieval request to the server, so that the server obtains the user input information according to the asset data retrieval request, constructs a search query instruction according to the user input information, and obtains the initial query result according to the interaction with the target search server. The target search server stores various types of asset data according to the target storage format, and the server performs format conversion on the initial query result to convert the asset data corresponding to the target storage format into asset data query results based on asset type.

[0035] The display module is configured to obtain the asset data query results and display the asset data in the asset data query results according to the asset type.

[0036] Fifthly, a server is provided, comprising: a processor, and a memory communicatively connected to the processor;

[0037] The memory stores computer-executed instructions;

[0038] The processor executes computer execution instructions stored in the memory to implement the data processing method provided in the first aspect above.

[0039] In a sixth aspect, a client is provided, comprising: a processor, and a memory communicatively connected to the processor;

[0040] The memory stores computer-executed instructions;

[0041] The processor executes computer execution instructions stored in the memory to implement the data processing method provided in the second aspect above.

[0042] In a seventh aspect, a computer-readable storage medium is provided, wherein computer-executable instructions are stored therein, which, when executed by a processor of a server, are used to implement the data processing method provided in the first aspect, or when executed by a processor of a client, are used to implement the data processing method provided in the second aspect.

[0043] Eighthly, a computer program product is provided, comprising a computer program that, when executed by a processor of a server, implements the data processing method provided in the first aspect, or when executed by a processor of a client, implements the data processing method provided in the second aspect.

[0044] The data processing method, apparatus, server, client, medium, and program products provided in this application construct search query instructions based on user input information. These instructions can be query scripts generated from the user input information, without being limited to a specific format. A search query is initiated to a search server based on these instructions. The search server redefines the index document format for storing asset data of various types. Initial query results are retrieved from the search server, and format conversion is performed to transform asset data in a specific format into asset data query results based on asset type. The client then displays the data. In this process, users can match matching asset data across all indexed documents without specific limitations. This effectively solves the problem that current attribute-based or attribute set-based retrieval mechanisms cannot comprehensively search for documents with uncertain multi-attribute structures. Attached Figure Description

[0045] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0046] Figure 1 A flowchart illustrating a data processing method provided in an embodiment of this application;

[0047] Figure 2 for Figure 1 A flowchart illustrating step S103;

[0048] Figure 3 A flowchart illustrating another data processing method provided in an embodiment of this application;

[0049] Figure 4 A flowchart illustrating another data processing method provided in an embodiment of this application;

[0050] Figure 5 This is a schematic diagram of a possible scenario provided for an embodiment of this application;

[0051] Figure 6 A flowchart illustrating another data processing method provided in an embodiment of this application;

[0052] Figure 7 This is a schematic diagram of the structure of a data processing device provided in an embodiment of this application;

[0053] Figure 8 This is a schematic diagram of another data processing apparatus provided in an embodiment of this application;

[0054] Figure 9 This application provides a schematic diagram of the structure of a server according to an embodiment of the present application.

[0055] Figure 10 This is a schematic diagram of the structure of a client provided in an embodiment of this application.

[0056] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0057] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0058] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with relevant laws, regulations and standards, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0059] Elasticsearch (ES) is a commonly used distributed search and analysis engine. It uses the Hypertext Transfer Protocol (HTTP) and JavaScript Object Notation (JSON) for data indexing, that is, it achieves data indexing by restricting the search through key-value pairs.

[0060] Based on current data storage and indexing methods, when a user needs to retrieve one or more asset data, they must provide specific attribute values ​​or sets of attributes in the search expression to retrieve the corresponding asset data. Taking the retrieval of logical system type asset data as an example, the user needs to provide specific system identifiers, names, abbreviations, and manager information, among other attributes. For uncertain, multi-attribute asset data, since specific attribute information cannot be provided, retrieval methods based on specific attribute information easily lead to incomplete searches of this logical system type of asset data, or the retrieval of asset data from other asset types. Clearly, the query results obtained using the above retrieval method will be insufficient to meet the developers' needs for asset data retrieval. It is understood that the logical system in the above example typically refers to a system composed of logic circuits, program code, or algorithms, used to implement specific computational, control, or communication functions. Logic systems have wide applications in various fields and applications, such as artificial intelligence, information technology, and engineering control.

[0061] In view of this, the data processing method, apparatus, server, client, medium, and program products provided in this application, on the HTTP server side, construct a search query instruction based on the user input information. This search query instruction can be a query script generated based on the user input information, without being limited to a specific format, and initiate a search query to the search server. The search server redefines the index document format to store asset data of various types, and obtains the initial query results from the search server while performing format conversion to convert asset data of a specific format into asset data query results based on asset type, which are then displayed by the client. In this process, the user can match matching asset data in all indexed documents without specific limitations, thus effectively solving the problem that current attribute-based or attribute set-based retrieval mechanisms cannot comprehensively search for uncertain multi-attribute documents.

[0062] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will be described below with reference to the accompanying drawings.

[0063] Figure 1 This is a flowchart illustrating a data processing method provided in an embodiment of this application. The method is applied to a server, which can be an HTTP server. This embodiment uses an HTTP server as an example for illustration; however, other servers can be used in other scenarios, and the server type is not specifically limited here. Figure 1 As shown, the method may include the following steps S101-S104.

[0064] Step S101: Construct a search query instruction based on the user input information.

[0065] In this embodiment, the search query instruction can be a query script generated based on user input information, without being limited to a specific format.

[0066] In this embodiment, user input information can be obtained from an HTTP client. The user initiates an asset data query request and generates user input information through the HTTP client. Optionally, the user input information may not carry any attribute information, such as system name, identifier, etc. For example, the user input information may only carry asset type information, such as the asset type being a logical system. Alternatively, it may not even carry asset type information, but use semantic text to describe the functional information of the asset data to be queried. Based on the semantic text, the asset type is identified and a search query instruction is constructed, thereby achieving a comprehensive search for asset data within the corresponding asset type.

[0067] Step S102: Send the search query instruction to the target search server, so that the target search server performs a full-text search according to the search query instruction and obtains the initial query results; wherein, the target search server stores various asset data according to the target storage format.

[0068] In related technologies, search servers typically store data in the form of key-value pairs (attribute identifier-attribute value). Therefore, search query instructions must carry the corresponding attribute information. The search query server queries the asset data corresponding to the attribute based on the search query instruction. However, in practical applications, an asset document (i.e., asset data) may have multiple uncertain attribute information. When a user uses arbitrary attribute information to query, they may not be able to find the corresponding asset data, or they may mistakenly find asset data of other asset types.

[0069] In this embodiment, the target search server can be Elasticsearch (ES) or other search servers. By defining the target storage format, the physical storage form of asset data in the search server can be improved to support the comprehensive search of asset data.

[0070] Next, the target storage format will be further described. The target storage format may include one or more of the following: the first format item corresponding to the asset attribute identifier, the second format item corresponding to the first asset attribute value, and the third format item corresponding to the asset type.

[0071] As can be understood, attributes are specific information describing the characteristics of an asset, and can be various attribute fields of the asset, such as name, size, identifier, abbreviation, etc. For example, the target storage format of asset data in a target search server can be as follows:

[0072] Attribute identifiers (fields): type, identifier, abbreviation name, name, English name, administrator; Attribute values ​​(values): logical system; XXX-001, abbreviation system name A, system name B, system English name C, Zhang San (xx12xxx); Asset type definition (type): logical system.

[0073] In this example, type represents the asset type definition, corresponding to the third format item of the asset type; fields represents the array of original asset attribute identifiers, where the 0th position can be a fixed value _type, representing the asset type; values ​​represents the array of original asset attribute values, where the 0th position can be a fixed value of the asset type, consistent with the asset type definition value.

[0074] Compared to related technologies, the storage format used in this embodiment sets attribute identifiers, attribute values, and asset types as three format items. Even if the user input does not include attribute information or a complete set of attributes, the search server can still find comprehensive asset data within the corresponding asset type based on the asset type or the corresponding attribute array, reducing the possibility of erroneous searches for data of different asset types. Furthermore, this method achieves key-value separation, solving the negative effect of storing a single object as a unique attribute in JSON format, which can pollute search results with attribute titles, resulting in a more comprehensive search.

[0075] Step S103: Obtain the initial query result from the target search server and perform format conversion on the initial query result to convert the asset data corresponding to the target storage format into asset data query results based on asset type.

[0076] In this embodiment, to facilitate data display on the client side, after obtaining the initial query results, the data in the target storage format is converted into a JSON array format. For example, assume the asset data query results include two items:

[0077] (a) Asset type: Logical system; Attribute values: Identifier: XXX-001; Administrator: Zhang San (xx12xxx); System name: System name B; English name: English name C; Abbreviation name: Abbreviation name A;

[0078] (ii) Asset type: Logical system; Attribute values: Identifier: XXX-002; Administrator: Li Si (xx12xxx); System name: System name b; English name: English name c; Abbreviation name: Abbreviation name a.

[0079] In this example, the returned result set is converted into a JSON array format, that is, in the form of type-values, where type is the asset type definition and values ​​is a key:value collection used to represent the whole of paired asset attributes / value pairs.

[0080] Step S104: Send the asset data query result to the client corresponding to the user input information, so that the client can display the asset data in the asset data query result according to the asset type.

[0081] In one implementation, the HTTP server encapsulates the converted document object and returns it to the client (the converted document object is encapsulated in the HTTP response, which can be done by setting response headers, status codes, etc., or by using the HTTP response body to carry the document object data). The client then selects the corresponding template based on the document type to display the relevant asset data.

[0082] Next, this embodiment further describes the format conversion process of the initial query results. In one possible implementation, such as Figure 2 As shown, the format conversion of the initial query results includes the following steps S103a-S103c:

[0083] Step S103a: Extract the data information carried by each format item in the initial query result, and determine the asset attribute identifier, first asset attribute value and asset type contained in the initial query result according to the data information.

[0084] Specifically, the initial query results extracted from Es, i.e. the original document corresponding to the target storage format, are converted into JSON object format by determining the asset attribute identifier, first asset attribute value and asset type corresponding to the target storage format.

[0085] Step S103b: For each asset type, bind the asset attribute identifier and the first asset attribute value to obtain the second asset attribute value; Step S103c: Obtain the asset data query result after format conversion based on the asset type and the second asset attribute value.

[0086] As shown in the example above, the second asset attribute value is the binding result between the first asset attribute value and the attribute identifier. Through the above format conversion process, asset data can be stored in a specific physical storage document format in the search server, while the reverse conversion process facilitates its display on the user end.

[0087] Figure 3Another data processing method provided in this application embodiment, based on the above embodiment, can effectively improve data query efficiency by first determining the information to be queried and constructing a search query instruction based on the information to be queried. Specifically, before constructing the search query instruction based on the user input information in step S101, the method may further include step S301, and step S101 is further divided into step S101a.

[0088] Step S301: In response to the asset data retrieval request initiated by the client, obtain user input information.

[0089] In this embodiment, asset data retrieval requests can be transmitted via HTTP requests or other data transmission protocols.

[0090] Step S101a: Determine the information to be queried based on the user input information, and construct the search query instruction based on the information to be queried.

[0091] In this embodiment, the user's request information is not required to use specific attribute information. However, considering that in actual applications, the request information may use a generalized language, the information to be queried is determined first and a search query instruction is constructed. Optionally, a natural language model can be used to identify the query items in the user's input information to determine the information to be queried, construct a search query instruction, and transmit it to the search server for data query.

[0092] Optionally, the user input information includes a predefined search expression; obtaining the user input information in step S301 above may include the following steps: parsing the parameter information carried by the data retrieval request, obtaining the predefined search expression from the parsing result, and the search expression being used to determine the information to be queried.

[0093] In this embodiment, the predefined search expression can be a search expression randomly entered by the user, or a search expression entered based on a predefined template. Those skilled in the art can adapt the predefined template to suit specific applications and existing technologies.

[0094] Specifically, after receiving a data retrieval request, the HTTP server retrieves the parameter portion from the request, which typically includes query parameters in the Uniform Resource Locator (URL), parameters in the request header, etc. By parsing these parameter information, the server obtains the search expression passed by the client and determines the data to be queried based on the search expression.

[0095] By using the above technical solution, the information to be queried can be determined based on the user's search expression, and a search query instruction can be constructed based on the information to be queried, which can effectively improve the efficiency of data query.

[0096] Figure 4 This is a flowchart illustrating another data processing method provided in an embodiment of this application. This method can be applied to a client, such as... Figure 4 As shown, the method includes steps S401-S403:

[0097] Step S401: Receive user input information and generate an asset data retrieval request based on the user input information.

[0098] Optionally, the user input may carry a predefined search expression.

[0099] Step S402: Initiate the asset data retrieval request to the server, so that the server obtains the user input information according to the asset data retrieval request, constructs a search query instruction according to the user input information, and obtains the initial query result according to the interaction with the target search server. The target search server stores various types of asset data according to the target storage format, and the server performs format conversion on the initial query result to convert the asset data corresponding to the target storage format into asset data query results based on asset type.

[0100] Step S403: Obtain the asset data query results and display the asset data in the asset data query results according to the asset type.

[0101] In one implementation, step S403, which displays asset data from the asset data query results according to the asset type, may include the following steps: selecting a corresponding display template from preset display templates based on the asset type, and displaying the asset data corresponding to the asset type according to the display template. In this way, the client can select the corresponding template based on the document type to display the relevant asset data, thereby achieving data visualization and interaction. This approach improves user experience, making it easier for users to understand and manipulate the data.

[0102] It should be noted that the data processing method provided in this embodiment is a counterpart technical solution to the method provided in the above embodiments. Its implementation principle and technical effect are similar, and will not be described again here.

[0103] In a possible application scenario, such as Figure 5As shown, this application scenario includes a browser-side component 10 and a server-side component 20. The browser-side component 10 (i.e., the HTTP client) may include an input interaction component 11 (i.e., the interaction module 801) and a result display component 12 (i.e., the display module 803). The server-side component may include an HTTP service component (i.e., the HTTP server) and a search server 21 (such as ElasticSearch). The HTTP service component includes an HTTP interaction service module 22, a search request module 23, and a result conversion module 24. The system includes: an input interaction component 11, which allows users to select asset types, input search expressions, and generate search requests; a results display component 12, which displays search result data items (obtained from server-side component 20) on a webpage using a specific template (pagination) based on asset types; an HTTP interaction service module 22, which receives search request data from the browser; a search request module 23, which constructs search query instructions and initiates search requests to ElasticSearch; a results conversion module 24, which converts standard object documents into the physical storage document format stored in ElasticSearch and performs the reverse conversion; and an ElasticSearch engine, which specifically implements the indexing of asset physical storage documents.

[0104] Optionally, Elasticsearch defines a storage document model for the asset document (AssetDoc) and a presentation model for the asset item (AssetItem). The storage document model is used to store the actual physical storage format of the document in Elasticsearch. In other words, Elasticsearch uses the target storage format to store the asset document (AssetDoc). For a specific example, please refer to the example of the target storage format in the above embodiments. The presentation model is used to convert the storage document model into JSON format data. For a specific example, please refer to the example of the JSON array format in the above embodiments, which will not be repeated here.

[0105] Optionally, the process of converting AssetDoc to AssetItem may include the following steps: extracting the original AssetDoc document from Es; converting AssetDoc to JSON object format; creating AssetItem objects; assigning a type to the AssetItemtype property; looping through the values ​​property of AssetDoc, and starting from the index, retrieving fields[i] and values[i] in order to form a Map.Entry format, and storing it as a Map object of values ​​in the AssetItem as key-value pairs. This achieves the format conversion from the target storage format to a JSON array.

[0106] After explaining the framework of this application scenario, the technical solution of this application will be briefly introduced below with possible query examples, such as... Figure 6 As shown, the data processing flow may include the following steps:

[0107] Step 1: The HTTP client can use the search expression entered by the user to determine the content to be queried by the user;

[0108] Step 2: The HTTP client can select the range of asset types to be retrieved by the user, generate and send an asset data retrieval request to the HTTP server;

[0109] Step 4: The HTTP server receives the request sent by the client and parses the parameters;

[0110] Step 5: The HTTP server constructs an ElasticSearch query script (i.e., a search query command) and initiates a query request to ElasticSearch (carrying the search query command).

[0111] Step 7: The HTTP server responds to Elasticsearch with the result (corresponding to the target storage format);

[0112] Step 8: The HTTP server retrieves the returned document object (usually a list, i.e., the initial query results);

[0113] Step 9: The HTTP server performs format conversion on the document object according to the above format conversion method;

[0114] Step 10: The HTTP server encapsulates the converted document object (i.e., the asset data query result) and returns it to the client.

[0115] Step 11: The client selects the corresponding template based on the document type and displays the corresponding asset data.

[0116] Compared to the limitations of search servers in traditional key-value format retrieval in related technologies, this embodiment, through model transformation, can more simply achieve full-text retrieval of multiple types of assets with uncertain attributes, and returns the results in JSON format familiar to developers. While achieving general retrieval purposes, it also conforms to developers' habits, thereby improving their development efficiency based on asset data. The key-value separation strategy avoids the negative impact of storing a single object as a unique attribute in JSON format, which could pollute search results. In this embodiment, it effectively controls whether to search attribute types or simply perform full-text retrieval on attribute values. Furthermore, it simplifies the query script construction logic for general retrieval, allowing the use of a unified wildcard format to complete full-text retrieval.

[0117] Figure 7 This is a schematic diagram of the structure of a data processing device provided in an embodiment of this application. The device includes a construction module 701, a query module 702, a conversion module 703, and a sending module 704, wherein...

[0118] Module 701 is configured to construct search query instructions based on user input information;

[0119] The query module 702 is configured to send the search query instruction to the target search server, so that the target search server performs a full-text search according to the search query instruction and obtains initial query results; wherein, the target search server stores various asset data according to the target storage format;

[0120] The conversion module 703 is configured to obtain the initial query result from the target search server and perform format conversion on the initial query result to convert the asset data corresponding to the target storage format into asset data query results based on asset type.

[0121] The sending module 704 is configured to send the asset data query result to the client corresponding to the user input information, so that the client can display the asset data in the asset data query result according to the asset type.

[0122] In one implementation, the target storage format includes at least one of the following format items: a first format item corresponding to an asset attribute identifier, a second format item corresponding to a first asset attribute value, and a third format item corresponding to an asset type.

[0123] In one embodiment, the conversion module includes:

[0124] The extraction and determination unit is configured to extract the data information carried by each format item in the initial query result, and determine the asset attribute identifier, first asset attribute value and asset type contained in the initial query result based on the data information.

[0125] A binding unit is configured to bind the asset attribute identifier and the first asset attribute value for each asset type to obtain a second asset attribute value;

[0126] The conversion unit is configured to obtain the asset data query result after format conversion based on the asset type and the second asset attribute value.

[0127] In one embodiment, the device further includes:

[0128] The acquisition module is configured to acquire user input information in response to asset data retrieval requests initiated by the client.

[0129] The construction module 701 is specifically configured to determine the information to be queried based on the user input information, and to construct the search query instruction based on the information to be queried.

[0130] In one implementation, the user input information includes a predefined search expression;

[0131] The acquisition module is specifically configured to parse the parameter information carried by the data retrieval request, and obtain a predefined search expression from the parsing result. The search expression is used to determine the information to be queried.

[0132] The apparatus provided in this application embodiment can be used to execute the technical solutions of the data processing method embodiment. Its implementation principle and technical effect are similar, and will not be repeated here.

[0133] Figure 8 This is a schematic diagram of the structure of a data processing device provided in an embodiment of this application, as shown below. Figure 8 As shown, it includes the interaction module 801,

[0134] The interaction module 801 is configured to receive user input information, including a predefined search expression, and generate an asset data retrieval request based on the user input information.

[0135] The request module 802 is configured to initiate the asset data retrieval request to the server, so that the server obtains the user input information according to the asset data retrieval request, constructs a search query instruction according to the user input information, and obtains initial query results based on the interaction with the target search server; wherein, the target search server stores various types of asset data according to a target storage format, and performs format conversion on the initial query results to convert the asset data corresponding to the target storage format into asset data query results based on asset type;

[0136] The display module 803 is configured to obtain the asset data query results and display the asset data in the asset data query results according to the asset type.

[0137] In one implementation, the display module 803 is specifically configured to select and determine a corresponding display template from preset display templates according to the asset type, and display the asset data corresponding to the asset type according to the display template.

[0138] The apparatus provided in this application embodiment can be used to execute the technical solutions of the data processing method embodiment. Its implementation principle and technical effect are similar, and will not be repeated here.

[0139] It should be noted that the division of the various modules in the above device is merely a logical functional division. In actual implementation, they can be fully or partially integrated into a single physical entity, or they can be physically separated. Furthermore, these modules can be implemented entirely in software via processing element calls; they can be fully implemented in hardware; or some modules can be implemented by processing element calls to software, while others are implemented in hardware. For example, the conversion module 703 can be a separate processing element, or it can be integrated into a chip in the above device. Alternatively, it can be stored as program code in the memory of the above device, and its functions can be called and executed by a processing element of the above device. The implementation of other modules is similar. Moreover, these modules can be fully or partially integrated together, or they can be implemented independently. The processing element here can be an integrated circuit with signal processing capabilities. In the implementation process, each step of the above method or each of the above modules can be completed through the integrated logic circuits in the hardware of the processor element or through software instructions.

[0140] Fifthly, a server is provided, comprising: a processor, and a memory communicatively connected to the processor;

[0141] The memory stores computer-executed instructions;

[0142] The processor executes computer execution instructions stored in the memory to implement the data processing method.

[0143] The apparatus provided in this application embodiment can be used to execute the technical solutions of the data processing method embodiment. Its implementation principle and technical effect are similar, and will not be repeated here.

[0144] In a sixth aspect, a terminal device is provided, comprising: a processor, and a memory communicatively connected to the processor;

[0145] The memory stores computer-executed instructions;

[0146] The processor executes computer execution instructions stored in the memory to implement the data processing method.

[0147] The apparatus provided in this application embodiment can be used to execute the technical solutions of the data processing method embodiment. Its implementation principle and technical effect are similar, and will not be repeated here.

[0148] Figure 9 This is a schematic diagram of the server structure provided in an embodiment of this application. Figure 9 As shown, the server may include: transceiver 91, processor 92, and memory 93.

[0149] Processor 92 executes computer execution instructions stored in memory, causing processor 92 to perform, for example... Figures 1-3 The data processing method in the illustrated embodiment. The processor 92 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0150] The memory 93 is connected to the processor 92 via the system bus and completes communication between them. The memory 103 is used to store computer program instructions.

[0151] Transceiver 91 can be used to receive user input information from the client or to send the asset data query results to the client.

[0152] The system bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The system bus can be divided into address bus, data bus, control bus, etc. For ease of representation, only one thick line is used in the diagram, but this does not indicate that there is only one bus or one type of bus. Transceivers are used to enable communication between database access devices and other computers (e.g., clients, read-write libraries, and read-only libraries). Memory may include random access memory (RAM) and may also include non-volatile memory.

[0153] The server provided in this application embodiment can be the HTTP server described in the above embodiments.

[0154] Figure 10 This is a schematic diagram of the structure of a terminal device provided in an embodiment of this application. Figure 10 As shown, the client may include: transceiver 101, processor 102, and memory 103.

[0155] Processor 102 executes computer execution instructions stored in memory, causing processor 102 to perform, for example, Figure 4 The data processing scheme in the illustrated embodiment.

[0156] The memory 103 is connected to the processor 102 via the system bus and completes communication between them. The memory 103 is used to store computer program instructions.

[0157] The transceiver 101 can be used to receive user input information from the client or to send the asset data query results to the client.

[0158] The client provided in this application embodiment can be the HTTP client described in the above embodiments.

[0159] This application also provides a chip for executing instructions, which is used to execute the technical solution of the data processing method in any of the above embodiments.

[0160] This application also provides a computer-readable storage medium storing computer-executable instructions. When these instructions are executed on a server, at least one processor of the server executes them. Figures 1-3 The technical solution of the data processing method in the embodiment, or the execution of computer execution instructions on the client, wherein at least one processor of the client executes... Figure 4 The technical solution of the data processing method in the corresponding embodiment.

[0161] This application also provides a computer program product, which includes a computer program stored in a computer-readable storage medium. At least one processor of a server can read the computer program from the computer-readable storage medium, and when the at least one processor executes the computer program, it can achieve... Figures 1-3 The technical solution of the data processing method corresponding to the embodiment, or at least one processor of the client can read a computer program from a computer-readable storage medium, and the at least one processor can implement the following when executing the computer program: Figure 4 The technical solution of the data processing method in the corresponding embodiment.

[0162] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device 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 modules 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 through some interfaces, devices, or modules, and may be electrical, mechanical, or other forms.

[0163] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to implement the solution of this embodiment according to actual needs.

[0164] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The unit composed of the above modules can be implemented in hardware or in the form of hardware plus software functional units.

[0165] The integrated modules described above, implemented as software functional modules, can be stored in a computer-readable storage medium. These software functional modules, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods of the various embodiments of this application.

[0166] It should be understood that the aforementioned processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly manifested as being executed by a hardware processor, or executed by a combination of hardware and software modules within the processor.

[0167] The memory may include high-speed RAM, and may also include non-volatile storage (NVM), such as at least one disk storage device, and may also be a USB flash drive, external hard drive, read-only memory, disk or optical disc, etc.

[0168] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0169] The aforementioned storage medium can be implemented from any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The storage medium can be any available medium accessible to general-purpose or special-purpose computers.

[0170] An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Alternatively, the storage medium can be an integral part of the processor. The processor and storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and storage medium can exist as discrete components in an electronic control unit or main control device.

[0171] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0172] Finally, it should be noted that the above 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 or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A data processing method, characterized in that, Applied to servers, including: Construct search query instructions based on user input; The search query command is sent to the target search server, which then performs a full-text search based on the search query command to obtain initial query results; wherein, the target search server stores various asset data according to the target storage format; The initial query results are obtained from the target search server, and the format of the initial query results is converted to convert the asset data corresponding to the target storage format into asset data query results based on asset type. The asset data query results are sent to the client corresponding to the user input information, so that the client can display the asset data in the asset data query results according to the asset type; The target storage format includes at least one of the following format items: a first format item corresponding to the asset attribute identifier, a second format item corresponding to the first asset attribute value, and a third format item corresponding to the asset type; The format conversion of the initial query result includes: Extract the data information carried by each format item in the initial query result, and determine the asset attribute identifier, first asset attribute value and asset type contained in the initial query result based on the data information; For each of the asset types, the asset attribute identifier and the first asset attribute value are bound together to obtain the second asset attribute value; The asset data query result is obtained after format conversion based on the asset type and the second asset attribute value.

2. The method according to claim 1, characterized in that, Before constructing search query instructions based on user input, it also includes: In response to an asset data retrieval request initiated by the client, obtain user input information; The step of constructing search query instructions based on user input information includes: The information to be queried is determined based on the user input information, and the search query instruction is constructed based on the information to be queried.

3. The method according to claim 2, characterized in that, The user input information includes predefined search expressions; The step of obtaining user input information includes: parsing the parameter information carried by the data retrieval request, obtaining a predefined search expression from the parsing result, and the search expression being used to determine the information to be queried.

4. A data processing method, characterized in that, Applied to the client side, including: Receive user input information and generate an asset data retrieval request based on the user input information; The system initiates an asset data retrieval request to the server, enabling the server to obtain the user input information based on the request, construct a search query instruction based on the user input information, and obtain initial query results based on interaction with the target search server. The target search server stores various asset data according to a target storage format, and the server performs format conversion on the initial query results to convert the asset data corresponding to the target storage format into asset data query results based on asset type. The target storage format includes at least one of the following format items: a first format item corresponding to an asset attribute identifier, a second format item corresponding to a first asset attribute value, and a third format item corresponding to an asset type. The format conversion of the initial query results includes: extracting data information carried by each format item in the initial query results, and determining the asset attribute identifier, first asset attribute value, and asset type contained in the initial query results based on the data information; binding the asset attribute identifier and the first asset attribute value for each asset type to obtain a second asset attribute value; and obtaining the format-converted asset data query results based on the asset type and the second asset attribute value. Obtain the asset data query results and display the asset data in the asset data query results according to the asset type.

5. The method according to claim 4, characterized in that, The step of displaying asset data from the asset data query results according to the asset type includes: Select the corresponding display template from the preset display templates according to the asset type, and display the asset data corresponding to the asset type according to the display template.

6. A data processing apparatus, characterized in that, Applied to servers, including: The module is configured to build search query instructions based on user input. The query module is configured to send the search query instruction to the target search server, so that the target search server performs a full-text search according to the search query instruction and obtains an initial query result; wherein, the target search server stores various types of asset data according to a target storage format; wherein, the target storage format includes at least one of the following format items: a first format item corresponding to an asset attribute identifier, a second format item corresponding to a first asset attribute value, and a third format item corresponding to an asset type; The conversion module is configured to obtain the initial query result from the target search server and perform format conversion on the initial query result to convert the asset data corresponding to the target storage format into asset data query results based on asset type. The format conversion of the initial query result includes: extracting data information carried by each format item in the initial query result, and determining the asset attribute identifier, first asset attribute value, and asset type contained in the initial query result based on the data information; binding the asset attribute identifier and the first asset attribute value for each asset type to obtain a second asset attribute value; and obtaining the format-converted asset data query result based on the asset type and the second asset attribute value. The sending module is configured to send the asset data query results to the client corresponding to the user input information, so that the client can display the asset data in the asset data query results according to the asset type.

7. A data processing apparatus, characterized in that, Applied to the client side, including: The interaction module is configured to receive user input information and generate an asset data retrieval request based on the user input information. The request module is configured to initiate an asset data retrieval request to the server, enabling the server to obtain user input information based on the asset data retrieval request, construct a search query instruction based on the user input information, and obtain initial query results based on interaction with the target search server. The target search server stores various asset data according to a target storage format, and the server performs format conversion on the initial query results to convert the asset data corresponding to the target storage format into asset data query results based on asset type. The target storage format includes at least one of the following format items: a first format item corresponding to an asset attribute identifier, a second format item corresponding to a first asset attribute value, and a third format item corresponding to an asset type. The format conversion of the initial query results includes: extracting data information carried by each format item in the initial query results, and determining the asset attribute identifier, first asset attribute value, and asset type contained in the initial query results based on the data information; binding the asset attribute identifier and the first asset attribute value for each asset type to obtain a second asset attribute value; and obtaining the format-converted asset data query results based on the asset type and the second asset attribute value. The display module is configured to obtain the asset data query results and display the asset data in the asset data query results according to the asset type.

8. A server, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the data processing method as described in any one of claims 1-3.

9. A client, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the data processing method as described in claim 4 or 5.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a server's processor, are used to implement the data processing method as described in any one of claims 1-3, or the data processing method as described in claim 4 or 5, when executed by a client's processor.

11. A computer program product, characterized in that, It includes a computer program that, when executed by a server's processor, implements the data processing method as described in any one of claims 1-3, or when executed by a client's processor, implements the data processing method as described in claim 4 or 5.

Images