Database query optimization method and system, and storage medium

Abstract

The present invention relates to the field of query optimization technology, and specifically discloses a database query optimization method, system, and storage medium. The present invention receives query request information and obtains user information to extract multiple query hub words; performs a hub main query to obtain hub query information; generates multiple query identity words, performs an identity-combined subquery to obtain identity query information; generates multiple query event words, performs an event-combined subquery to obtain event query information; performs historical correlation zooming, and generates and displays a result display interface. It is capable of performing a hub main query, an identity-combined subquery, and an event-combined subquery to obtain hub query information, identity query information, and event query information, respectively, and perform historical correlation zooming to generate a result display interface, thereby achieving professional and proactive optimization of database queries, diversifying query results, and enabling users to quickly find the query results they need, thereby meeting the actual usage needs of users.

Description

Technical Field

[0001] The present invention belongs to the technical field of query optimization, and in particular relates to a database query optimization method and system, and a storage medium. Background Art

[0002] A database is a warehouse that organizes, stores, and manages data according to a data structure. It is a collection of large amounts of data stored in a computer for a long time, organized, shareable, and uniformly managed. Relational databases use structured query language (SQL) to query the database.

[0003] In the existing technology, there is only one way to query the database, and it is impossible to perform more professional and proactive database query optimization based on user identity and work events. As a result, the query results are often scattered and do not meet the user's data usage needs. Users are also required to select the required data from a large amount of data, which is inconvenient for users' actual use. Summary of the Invention

[0004] The purpose of the embodiments of the present invention is to provide a database query optimization method and system, and a storage medium, aiming to solve the problems raised in the background technology.

[0005] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions:

[0006] A database query optimization method, the method specifically comprising the following steps:

[0007] Receive query request information, obtain user information, perform key recognition analysis, and extract multiple query keywords from the query request information;

[0008] Based on the plurality of query hub words, a hub main query is performed in a preset target database to obtain hub query information;

[0009] Combining the user information and the plurality of query keywords to generate a plurality of query identity words, performing identity-combined sub-queries in the target database to obtain identity query information;

[0010] Combining the user information and the plurality of query keywords to generate a plurality of query event words, performing event-combined sub-queries in the target database to obtain event query information;

[0011] Perform historical correlation scaling on the hub query information, the identity query information, and the event query information, and generate and display a result display interface.

[0012] As a further limitation of the technical solution of the embodiment of the present invention, the receiving of query request information, obtaining user information, performing keyword recognition analysis, and extracting multiple query keywords from the query request information specifically includes the following steps:

[0013] Receive query request operation and build query request window;

[0014] Receiving user's query request information through the query request window;

[0015] Obtain the request address of the query request information and obtain user information;

[0016] Perform key identification analysis on the query request information to extract multiple query keywords.

[0017] As a further limitation of the technical solution of the embodiment of the present invention, the step of integrating the user information and the plurality of query keywords to generate a plurality of query identity keywords, performing identity-combined sub-queries in the target database, and obtaining identity query information specifically includes the following steps:

[0018] generating a plurality of key identity words based on the user information;

[0019] Using the user information, identity screening and marking are performed on the plurality of query keywords to obtain a plurality of screening identity words;

[0020] Combining the plurality of key identity words and the plurality of screening identity words, and marking to obtain a plurality of query identity words;

[0021] Based on the plurality of query identity words, an identity combined sub-query is performed in the target database to obtain identity query information.

[0022] As a further limitation of the technical solution of the embodiment of the present invention, the step of integrating the user information and the plurality of query keywords to generate a plurality of query event words, performing an event-combined subquery in the target database, and obtaining event query information specifically includes the following steps:

[0023] generating a plurality of key event words according to the user information;

[0024] Using the user information, event screening and marking are performed on the plurality of query keywords to obtain a plurality of screening event words;

[0025] Combining the plurality of key event words and the plurality of screening event words, and marking them to obtain a plurality of query event words;

[0026] Based on the multiple query event words, an event combination sub-query is performed in the target database to obtain event query information.

[0027] As a further limitation of the technical solution of the embodiment of the present invention, generating a plurality of key event words according to the user information specifically includes the following steps:

[0028] Acquiring event planning information according to the user information;

[0029] A plurality of key event words are generated according to the event planning information.

[0030] As a further limitation of the technical solution of the embodiment of the present invention, performing historical correlation scaling on the hub query information, the identity query information, and the event query information, and generating and displaying a result display interface specifically includes the following steps:

[0031] Get historical query record information;

[0032] Analyze the historical query record information to obtain the classification usage ratio;

[0033] Performing historical correlation scaling on the hub query information, the identity query information, and the event query information according to the classification usage ratio, and generating a result display interface;

[0034] The result display interface is displayed.

[0035] A database query optimization system includes a query request processing unit, a hub main query unit, an identity-binding sub-query unit, an event-binding sub-query unit, and a history correlation scaling unit, wherein:

[0036] A query request processing unit, configured to receive query request information, obtain user information, perform key identification analysis, and extract multiple query keywords from the query request information;

[0037] A hub main query unit, configured to perform a hub main query in a preset target database based on the plurality of query hub words to obtain hub query information;

[0038] an identity-combining sub-query unit, configured to synthesize the user information and the plurality of query keywords to generate a plurality of query identity keywords, perform identity-combining sub-queries in the target database, and obtain identity query information;

[0039] An event-combining sub-query unit, configured to synthesize the user information and a plurality of query keywords to generate a plurality of query event keywords, perform an event-combining sub-query in a target database, and obtain event query information;

[0040] The history correlation scaling unit is configured to perform history correlation scaling on the hub query information, the identity query information, and the event query information, and generate and display a result display interface.

[0041] As a further limitation of the technical solution of the embodiment of the present invention, the query request processing unit specifically includes:

[0042] An operation receiving module is used to receive a query request operation and build a query request window;

[0043] An information receiving module, configured to receive a user's query request information through the query request window;

[0044] An information acquisition module is used to obtain the request address of the query request information and obtain user information;

[0045] The key recognition module is used to perform key recognition analysis on the query request information and extract multiple query keywords.

[0046] As a further limitation of the technical solution of the embodiment of the present invention, the history association scaling unit specifically includes:

[0047] History acquisition module, used to obtain historical query record information;

[0048] A ratio analysis module is used to analyze the historical query record information to obtain the classification usage ratio;

[0049] an interface generation module, configured to perform historical correlation scaling on the hub query information, the identity query information, and the event query information according to the classification usage ratio, and generate a result display interface;

[0050] The interface display module is used to display the result display interface.

[0051] A computer-readable storage medium stores a computer program, which, when executed by a processor, causes the processor to execute the steps of the above-mentioned database query optimization method.

[0052] Compared with the prior art, the present invention has the following beneficial effects:

[0053] 1. The present invention can perform hub main queries, identity-based sub-queries, and event-based sub-queries, respectively obtaining hub query information, identity query information, and event query information. This enables professional and proactive optimization of database queries, diversifying query results and enabling users to quickly find the required query results, thus meeting their actual usage needs.

[0054] 2. The present invention can perform historical correlation scaling on hub query information, identity query information and event query information, generate and display a result display interface, which not only makes it convenient for users to browse and use query results according to their habits, but also can display different query information at the same time, making it convenient for users to quickly find appropriate query results for use. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention.

[0056] Figure 1 A flow chart of a method provided by an embodiment of the present invention is shown.

[0057] Figure 2 The flowchart of the query request information reception process in the method provided by the embodiment of the present invention is shown.

[0058] Figure 3 A flowchart of performing identity-combined subquery in the method provided by an embodiment of the present invention is shown.

[0059] Figure 4 A flowchart of performing event-combined subquery in the method provided by an embodiment of the present invention is shown.

[0060] Figure 5 A flow chart of generating multiple key event words in the method provided by an embodiment of the present invention is shown.

[0061] Figure 6 A flow chart of generating a result display interface in the method provided in an embodiment of the present invention is shown.

[0062] Figure 7 The application architecture diagram of the system provided by the embodiment of the present invention is shown.

[0063] Figure 8 The structure block diagram of the query request processing unit in the system provided by the embodiment of the present invention is shown.

[0064] Figure 9 A structural block diagram of a history correlation scaling unit in a system provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0065] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0066] It is understandable that in the existing technology, there is only one way to query the database, and it is impossible to perform more professional and proactive database query optimization based on user identity and work events. As a result, the query results are often scattered and do not meet the user's data usage needs. The user is also required to select the required data from a large amount of data, which is inconvenient for the user's actual use.

[0067] To solve the above problems, the embodiment of the present invention receives query request information, obtains user information, performs key identification analysis, and extracts multiple query keywords from the query request information; based on the multiple query keywords, performs a hub main query in a preset target database to obtain hub query information; integrates user information and multiple query keywords to generate multiple query identity keywords, performs identity-combined sub-queries in the target database to obtain identity query information; integrates user information and multiple query keywords to generate multiple query event keywords, performs event-combined sub-queries in the target database to obtain event query information; performs historical correlation scaling on the hub query information, identity query information, and event query information, and generates and displays a result display interface. The embodiment can perform a hub main query, an identity-combined sub-query, and an event-combined sub-query to obtain hub query information, identity query information, and event query information, respectively, and perform historical correlation scaling to generate a result display interface, thereby achieving professional and proactive optimization of database queries, diversifying query results, and enabling users to quickly find the query results they need, meeting their actual usage needs.

[0068] Figure 1 A flow chart of a method provided by an embodiment of the present invention is shown.

[0069] Specifically, in a preferred embodiment of the present invention, a database query optimization method is provided, the method specifically comprising the following steps:

[0070] Step S101: receiving query request information, obtaining user information, performing key recognition analysis, and extracting multiple query keywords from the query request information.

[0071] In an embodiment of the present invention, when a user is designing and making tooling accessories for a camera, if he or she has a query need, he or she can perform a query request operation. By receiving the user's query request operation, a query request window is constructed and displayed. The user can enter query request information in the query request window, thereby obtaining the query request information through the query request window, and then performing content analysis on the query request information to identify modal particles, punctuation marks, verbs, personal nouns, etc. in the query request information, and then remove the modal particles, punctuation marks, verbs, personal nouns, etc. in the query request information, and then extract multiple query keywords from the remaining query request information. At the same time, by analyzing the request address of the query request information, the corresponding request ID is determined, and then the user information is obtained.

[0072] For example, if the query request information entered by the user in the query request window is "I need a 3D image of camera A", then "I", "need" and "ah" in "I need a 3D image of camera A" are removed, and the query keywords "camera A" and "3D image" are extracted.

[0073] Specifically, Figure 2 The flowchart of the query request information reception process in the method provided by the embodiment of the present invention is shown.

[0074] In a preferred embodiment of the present invention, the steps of receiving query request information, obtaining user information, performing key identification analysis, and extracting multiple query keywords from the query request information specifically include the following steps:

[0075] Step S1011: receiving a query request operation and constructing a query request window.

[0076] Step S1012: Receive the user's query request information through the query request window.

[0077] Step S1013: Obtain the request address of the query request information and obtain user information.

[0078] Step S1014: perform keyword recognition analysis on the query request information to extract multiple query keywords.

[0079] Furthermore, the database query optimization method further includes the following steps:

[0080] Step S102: Based on the plurality of query keywords, a hub main query is performed in a preset target database to obtain hub query information.

[0081] In the embodiment of the present invention, multiple query hub words are used as query index words, and index query is performed in a preset target database using the multiple query hub words to obtain hub query information.

[0082] For example, when performing an index query using "camera A" and "3D image", the obtained pivotal query information is the 3D data of camera A and the 3D thumbnail of camera A.

[0083] Step S103 : synthesizing the user information and the plurality of query keywords to generate a plurality of query identity keywords, performing identity-combined sub-queries in the target database to obtain identity query information.

[0084] In an embodiment of the present invention, based on user information, the user's work identity in the enterprise is determined, and multiple key identity words related to the user's work identity are generated. According to the user's work identity, multiple query hub words are screened for identity, and query hub words that are not related to the user's work identity are eliminated. The multiple retained query hub words are marked as screened identity words, and then multiple key identity words and multiple screened identity words are combined and marked to obtain multiple query identity words. Then, multiple query identity words are used as query index words, and in a preset target database, identity-combined index queries are performed through multiple query identity words to obtain identity query information.

[0085] For example: if the user's work identity in the enterprise is "tooling and auxiliary tools design engineer", then the multiple key identity words are "tooling" and "auxiliary tools". Since the query hub words "A camera" and "three-dimensional image" do not need to be filtered, the multiple filtered identity words are "A camera" and "three-dimensional image". At this time, the multiple query identity words with comprehensive tags can be "tooling", "auxiliary tools", "A camera" and "three-dimensional image"; the identity query information obtained can be the three-dimensional data of camera A, the three-dimensional thumbnail of camera A, the three-dimensional data of multiple tooling and auxiliary tools of camera A, and the three-dimensional thumbnail of multiple tooling and auxiliary tools of camera A.

[0086] Specifically, Figure 3 A flowchart of performing identity-combined subquery in the method provided by an embodiment of the present invention is shown.

[0087] In a preferred embodiment of the present invention, the user information and multiple query keywords are integrated to generate multiple query identity keywords, and identity-combined sub-queries are performed in the target database to obtain identity query information, specifically including the following steps:

[0088] Step S1031: Generate multiple key identity words based on the user information.

[0089] Step S1032: using the user information, perform identity screening and tagging on the plurality of query keywords to obtain a plurality of screened identity words.

[0090] Step S1033 , combining the plurality of key identity words and the plurality of screening identity words, and marking to obtain a plurality of query identity words.

[0091] Step S1034: Based on the plurality of query identity words, perform identity combination sub-query in the target database to obtain identity query information.

[0092] Furthermore, the database query optimization method further includes the following steps:

[0093] Step S104 : synthesizing the user information and the plurality of query keywords to generate a plurality of query event words, performing event-combined sub-queries in the target database to obtain event query information.

[0094] In an embodiment of the present invention, based on user information, the user's event planning information is obtained from the enterprise's work planning information, and then based on the event planning information, multiple corresponding key event words are generated, and according to the user's event planning information, multiple query hub words are screened for events, query hub words that are irrelevant to the user's event planning are eliminated, and the retained multiple query hub words are marked as screened event words, and then multiple key event words and multiple screened event words are combined and marked to obtain multiple query event words, and then multiple query event words are used as query index words, and in a preset target database, event-combined index query is performed through multiple query event words to obtain event query information.

[0095] For example: the user's event planning information is "module consistency tooling design on XX month XX day", then the multiple key event words are "module" and "consistency tooling". Since the query hub words "A camera" and "three-dimensional image" do not need to be filtered, the multiple filtered event words are "A camera" and "three-dimensional image". At this time, the multiple query event words with comprehensive tags are "module", "consistency tooling", "A camera" and "three-dimensional image"; the event query information obtained can be the three-dimensional data of the A camera module, the three-dimensional thumbnail of the A camera module, the three-dimensional data of the module consistency tooling of the A camera, and the three-dimensional thumbnail of the module consistency tooling of the A camera.

[0096] Specifically, Figure 4 A flowchart of performing event-combined subquery in the method provided by an embodiment of the present invention is shown.

[0097] In a preferred embodiment of the present invention, the step of integrating the user information and the plurality of query keywords to generate a plurality of query event keywords, performing an event-combined sub-query in the target database, and obtaining event query information specifically includes the following steps:

[0098] Step S1041: Generate multiple key event words based on the user information.

[0099] Specifically, Figure 5 A flow chart of generating multiple key event words in the method provided by an embodiment of the present invention is shown.

[0100] In a preferred embodiment of the present invention, generating a plurality of key event words according to the user information specifically includes the following steps:

[0101] Step S10411: Acquire event planning information based on the user information.

[0102] Step S10412: Generate multiple key event words based on the event planning information.

[0103] Furthermore, the step of synthesizing the user information and the plurality of query keywords to generate a plurality of query event words, performing event-combined sub-queries in the target database, and obtaining event query information further includes the following steps:

[0104] Step S1042: Using the user information, perform event screening and tagging on the plurality of query keywords to obtain a plurality of screened event words.

[0105] Step S1043 : synthesize the plurality of key event words and the plurality of screening event words, and mark and obtain a plurality of query event words.

[0106] Step S1044: Based on the multiple query event words, an event combination sub-query is performed in the target database to obtain event query information.

[0107] Furthermore, the database query optimization method further includes the following steps:

[0108] Step S105 : Perform historical correlation scaling on the hub query information, the identity query information, and the event query information, and generate and display a result display interface.

[0109] In an embodiment of the present invention, according to user information, the user's historical query record information is obtained, and by analyzing the historical query record information, the browsing time of the user on the hub query information, identity query information and event query information during the historical query process is obtained, and the three different browsing times are compared to generate a classification usage ratio. Then, according to the classification usage ratio, in a preset standard interface, the interface display size of the currently obtained hub query information, identity query information and event query information is scaled and adjusted to generate a result display interface, and then in the result display interface, the currently obtained hub query information, identity query information and event query information are displayed.

[0110] It can be understood that in the preset standard interface, hub query information is displayed on the left, identity query information is displayed in the middle, and event query information is displayed on the right. According to the classification usage ratio, the interface display size of the hub query information, identity query information and event query information is scaled and adjusted. The larger the proportion of information in the classification usage ratio, the larger the interface display size, and the smaller the proportion of information in the classification usage ratio, the smaller the interface display size.

[0111] Specifically, Figure 6 A flow chart of generating a result display interface in the method provided in an embodiment of the present invention is shown.

[0112] In a preferred embodiment of the present invention, performing historical correlation scaling on the hub query information, the identity query information, and the event query information, and generating and displaying a result display interface specifically includes the following steps:

[0113] Step S1051, obtaining historical query record information.

[0114] Step S1052: Analyze the historical query record information to obtain the classification usage ratio.

[0115] Step S1053 : performing historical correlation scaling on the hub query information, the identity query information, and the event query information according to the classification usage ratio, and generating a result display interface.

[0116] Step S1054: display the result display interface.

[0117] Further, Figure 7 The application architecture diagram of the system provided by the embodiment of the present invention is shown.

[0118] In another preferred embodiment of the present invention, a database query optimization system includes:

[0119] The query request processing unit 101 is configured to receive query request information, obtain user information, perform keyword recognition analysis, and extract multiple query keywords from the query request information.

[0120] In an embodiment of the present invention, when a user is designing and making tooling accessories for a camera, if he or she needs to make a query, he or she can perform a query request operation. The query request processing unit 101 constructs and displays a query request window by receiving the user's query request operation. The user can enter query request information in the query request window, thereby obtaining the query request information through the query request window, and then performing content analysis on the query request information to identify modal particles, punctuation marks, verbs, personal nouns, etc. in the query request information, and then remove the modal particles, punctuation marks, verbs, personal nouns, etc. in the query request information, and then extract multiple query keywords from the remaining query request information. At the same time, by analyzing the request address of the query request information, the corresponding request ID is determined, and then the user information is obtained.

[0121] Specifically, Figure 8 It shows a structural block diagram of the query request processing unit 101 in the system provided by an embodiment of the present invention.

[0122] In a preferred embodiment of the present invention, the query request processing unit 101 specifically includes:

[0123] The operation receiving module 1011 is used to receive a query request operation and build a query request window.

[0124] The information receiving module 1012 is configured to receive the user's query request information through the query request window.

[0125] The information acquisition module 1013 is used to obtain the request address of the query request information and obtain user information.

[0126] The key identification module 1014 is configured to perform key identification analysis on the query request information and extract multiple query keywords.

[0127] Furthermore, the database query optimization system further includes:

[0128] The hub main query unit 102 is configured to perform a hub main query in a preset target database based on the plurality of query hub words to obtain hub query information.

[0129] In the embodiment of the present invention, the hub main query unit 102 uses multiple query hub words as query index words, performs index query through the multiple query hub words in a preset target database, and obtains hub query information.

[0130] The identity-combining sub-query unit 103 is configured to synthesize the user information and the plurality of query keywords to generate a plurality of query identity words, perform identity-combining sub-queries in the target database, and obtain identity query information.

[0131] In an embodiment of the present invention, the identity-combining sub-query unit 103 determines the user's work identity in the enterprise based on the user information, generates multiple key identity words related to the user's work identity, and performs identity screening on multiple query hub words according to the user's work identity, eliminates query hub words that are not related to the user's work identity, and marks the retained multiple query hub words as screened identity words. Then, multiple key identity words and multiple screened identity words are combined and marked to obtain multiple query identity words, and then multiple query identity words are used as query index words. In the preset target database, identity-combined index query is performed through multiple query identity words to obtain identity query information.

[0132] The event-combined sub-query unit 104 is configured to synthesize the user information and the plurality of query keywords to generate a plurality of query event words, perform an event-combined sub-query in the target database, and obtain event query information.

[0133] In an embodiment of the present invention, the event combination sub-query unit 104 obtains the user's event planning information from the enterprise's work planning information based on the user information, and then generates multiple corresponding key event words based on the event planning information, and performs event screening on multiple query hub words according to the user's event planning information, eliminates query hub words that are not related to the user's event planning, and marks the retained multiple query hub words as screening event words, and then combines multiple key event words and multiple screening event words, and marks them to obtain multiple query event words, and then uses multiple query event words as query index words, and performs event-combined index query through multiple query event words in a preset target database to obtain event query information.

[0134] The history correlation scaling unit 105 is configured to perform history correlation scaling on the hub query information, the identity query information, and the event query information, and generate and display a result display interface.

[0135] In an embodiment of the present invention, the historical association scaling unit 105 obtains the user's historical query record information according to the user information, and obtains the browsing time of the user on the hub query information, identity query information and event query information respectively during the historical query process by analyzing the historical query record information, compares the three different browsing times, and generates a classification usage ratio. Then, according to the classification usage ratio, in a preset standard interface, the interface display size of the currently obtained hub query information, identity query information and event query information is scaled and adjusted to generate a result display interface, and then in the result display interface, the currently obtained hub query information, identity query information and event query information are displayed.

[0136] Specifically, Figure 9 FIG. 1 shows a structural block diagram of the history correlation scaling unit 105 in the system provided by an embodiment of the present invention.

[0137] In a preferred embodiment of the present invention, the history association scaling unit 105 specifically includes:

[0138] The history acquisition module 1051 is used to acquire historical query record information.

[0139] The ratio analysis module 1052 is used to analyze the historical query record information to obtain the classification usage ratio.

[0140] The interface generation module 1053 is configured to perform historical correlation scaling on the hub query information, the identity query information, and the event query information according to the classification usage ratio, and generate a result display interface.

[0141] The interface display module 1054 is used to display the result display interface.

[0142] Furthermore, in another preferred embodiment of the present invention, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the processor performs the following steps:

[0143] Receive query request information, obtain user information, perform key recognition analysis, and extract multiple query keywords from the query request information;

[0144] Based on the plurality of query hub words, a hub main query is performed in a preset target database to obtain hub query information;

[0145] Combining the user information and the plurality of query keywords to generate a plurality of query identity words, performing identity-combined sub-queries in the target database to obtain identity query information;

[0146] Combining the user information and the plurality of query keywords to generate a plurality of query event words, performing event-combined sub-queries in the target database to obtain event query information;

[0147] Perform historical correlation scaling on the hub query information, the identity query information, and the event query information, and generate and display a result display interface.

[0148] The above-described embodiments merely illustrate several implementations of the present invention, and while their descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art would be able to make numerous variations and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

Claims

1. A database query optimization method, characterized in that: The method specifically comprises the following steps: Receive query request information, obtain user information, perform key recognition analysis, and extract multiple query keywords from the query request information; Based on the plurality of query hub words, a hub main query is performed in a preset target database to obtain hub query information; Combining the user information and the plurality of query keywords to generate a plurality of query identity words, performing identity-combined sub-queries in the target database to obtain identity query information; specifically comprising the following steps: generating a plurality of key identity words based on the user information; Using the user information, identity screening and marking are performed on the plurality of query keywords to obtain a plurality of screening identity words; Combining the plurality of key identity words and the plurality of screening identity words, and marking to obtain a plurality of query identity words; Based on the plurality of query identity words, performing identity combined sub-queries in the target database to obtain identity query information; Combining the user information and the plurality of query keywords to generate a plurality of query event words, performing event-combined sub-queries in the target database to obtain event query information; specifically comprising the following steps: generating a plurality of key event words according to the user information; Using the user information, event screening and marking are performed on the plurality of query keywords to obtain a plurality of screening event words; Combining the plurality of key event words and the plurality of screening event words, and marking them to obtain a plurality of query event words; Based on the multiple query event words, performing event combination sub-queries in the target database to obtain event query information; Performing historical correlation scaling on the hub query information, the identity query information, and the event query information, and generating and displaying a result display interface; The specific steps include: Get historical query record information; Analyze the historical query record information to obtain the classification usage ratio; Performing historical correlation scaling on the hub query information, the identity query information, and the event query information according to the classification usage ratio, and generating a result display interface; The result display interface is displayed.

2. The database query optimization method according to claim 1, characterized in that: The receiving of query request information, obtaining user information, performing key identification analysis, and extracting multiple query keywords from the query request information specifically includes the following steps: Receive query request operation and build query request window; Receiving user's query request information through the query request window; Obtain the request address of the query request information and obtain user information; Perform key identification analysis on the query request information to extract multiple query keywords.

3. The database query optimization method according to claim 2, characterized in that: Generating a plurality of key event words according to the user information specifically includes the following steps: Acquiring event planning information according to the user information; A plurality of key event words are generated according to the event planning information.

4. A database query optimization system, characterized in that: The system includes a query request processing unit, a hub main query unit, an identity-binding sub-query unit, an event-binding sub-query unit, and a history correlation scaling unit, wherein: A query request processing unit, configured to receive query request information, obtain user information, perform key identification analysis, and extract multiple query keywords from the query request information; A hub main query unit, configured to perform a hub main query in a preset target database based on the plurality of query hub words to obtain hub query information; an identity-combining sub-query unit, configured to synthesize the user information and the plurality of query keywords to generate a plurality of query identity keywords, perform identity-combining sub-queries in the target database, and obtain identity query information; An event-combining sub-query unit, configured to synthesize the user information and a plurality of query keywords to generate a plurality of query event keywords, perform an event-combining sub-query in a target database, and obtain event query information; a history correlation scaling unit, configured to perform history correlation scaling on the hub query information, the identity query information, and the event query information, and generate and display a result display interface; The history association scaling unit specifically includes: History acquisition module, used to obtain historical query record information; A ratio analysis module is used to analyze the historical query record information to obtain the classification usage ratio; an interface generation module, configured to perform historical correlation scaling on the hub query information, the identity query information, and the event query information according to the classification usage ratio, and generate a result display interface; An interface display module, used to display the result display interface; The identity combined subquery includes the following steps: generating a plurality of key identity words based on the user information; Using the user information, identity screening and marking are performed on the plurality of query keywords to obtain a plurality of screening identity words; Combining the plurality of key identity words and the plurality of screening identity words, and marking to obtain a plurality of query identity words; Based on the plurality of query identity words, performing identity combined sub-queries in the target database to obtain identity query information; The event is combined with a subquery, which includes the following steps: generating a plurality of key event words according to the user information; Using the user information, event screening and marking are performed on the plurality of query keywords to obtain a plurality of screening event words; Combining the plurality of key event words and the plurality of screening event words, and marking them to obtain a plurality of query event words; Based on the multiple query event words, an event combination sub-query is performed in the target database to obtain event query information.

5. The database query optimization system according to claim 4, characterized in that: The query request processing unit specifically includes: An operation receiving module is used to receive a query request operation and build a query request window; An information receiving module, configured to receive a user's query request information through the query request window; An information acquisition module is used to obtain the request address of the query request information and obtain user information; The key recognition module is used to perform key recognition analysis on the query request information and extract multiple query keywords.

6. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor executes the steps of the database query optimization method according to any one of claims 1 to 3.

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