CN111460268A

CN111460268A - Method and device for determining database query request and computer equipment

Info

Publication number: CN111460268A
Application number: CN202010250424.9A
Authority: CN
Inventors: 汤泽亮; 宋杨
Original assignee: Chongqing Cloud Core Intelligent Technology Co ltd; Hangzhou Diji Intelligent Technology Co ltd
Current assignee: Chongqing Cloud Core Intelligent Technology Co ltd; Hangzhou Diji Intelligent Technology Co ltd
Priority date: 2020-04-01
Filing date: 2020-04-01
Publication date: 2020-07-28
Anticipated expiration: 2040-04-01
Also published as: CN111460268B

Abstract

The application relates to a determination method and device for a database query request, computer equipment and a storage medium. The method comprises the following steps: acquiring data table information and historical query information of a database to be queried; processing the data table information and the historical query information respectively to obtain first field information in the data table information and weights corresponding to the first field information and second field information in the historical query information and weights corresponding to the second field information, and further obtain target weights of the second field information in the historical query information; screening target field information from second field information according to the target weight of the second field information in the historical query information; and splicing the target field information and the data table identification information corresponding to the target field information to obtain a database query request of the database to be queried. By adopting the method, the determination accuracy of the database query request is improved.

Description

Method and device for determining database query request and computer equipment

Technical Field

The present application relates to the field of data processing technologies, and in particular, to a method and an apparatus for determining a database query request, a computer device, and a storage medium.

Background

With the development of internet technology, more and more data are stored through a database, and in order to mine and analyze data in the database, the data in the database needs to be queried through a corresponding database query request, such as a query statement.

At present, the determination mode of a database query request generally determines a query request of data having similarity with historical analysis data as a database query request through a collaborative filtering recommendation algorithm; however, the contents in the database are various, and the database query request is determined only according to the query request of the data having similarity with the historical analysis data, which results in low accuracy of the determined database query request, and thus, the determination accuracy of the database query request is low.

Disclosure of Invention

In view of the foregoing, it is desirable to provide a database query request determining method, apparatus, computer device and storage medium capable of improving accuracy of determination of a database query request.

A method of generating a database query request, the method comprising:

acquiring data table information and historical query information of a database to be queried;

processing the data table information and the historical query information respectively to obtain first field information in the data table information and weight corresponding to the first field information and second field information in the historical query information and weight corresponding to the second field information;

obtaining target weight of second field information in the historical query information according to first field information in the data table information and weight corresponding to the first field information and weight corresponding to second field information in the historical query information and the second field information;

screening target field information from second field information according to the target weight of the second field information in the historical query information;

and splicing the target field information and the data table identification information corresponding to the target field information to obtain a database query request of the database to be queried.

In one embodiment, the processing the data table information and the historical query information respectively to obtain weights corresponding to a first field information and a first field information in the data table information and weights corresponding to a second field information and a second field information in the historical query information includes:

acquiring first field information and annotation information in the data table information, and performing word segmentation processing on the annotation information to obtain annotation word segmentation information in the data table information;

determining the weight corresponding to the first field information in the data table information according to the annotation word segmentation information in the data table information;

acquiring field information in the historical query information and query frequency of the field information, and determining second field information in the historical query information and query frequency of the second field information according to the field information in the historical query information and the query frequency of the field information;

and normalizing the query frequency of each second field information to obtain the weight corresponding to each second field information in the historical query information.

In one embodiment, the determining, according to the comment participle information in the data table information, a weight corresponding to a first field information in the data table information includes:

filtering the annotation word segmentation information in the data table information to obtain filtered annotation word segmentation information;

acquiring index weight corresponding to the filtered annotation word segmentation information;

and acquiring the sum of the index weights corresponding to the filtered annotation word segmentation information as the weight corresponding to the first field information in the data table information.

In one embodiment, the determining the query frequency of the second field information and the second field information in the historical query information according to the field information in the historical query information and the query frequency of the field information includes:

determining the support degree of the field information in the historical query information according to the field information in the historical query information and the query frequency of the field information;

taking the field information with the support degree greater than or equal to a preset support degree as candidate field information in the historical query information;

determining the confidence of the candidate field information in the historical query information according to the query frequency of the candidate field information in the historical query information;

and correspondingly taking the candidate field information with the confidence coefficient greater than or equal to the preset confidence coefficient and the query frequency of the candidate field information as the second field information in the historical query information and the query frequency of the second field information.

In one embodiment, the obtaining the target weight of the second field information in the historical query information according to the first field information in the data table information and the weight corresponding to the first field information and the weight corresponding to the second field information in the historical query information includes:

identifying data table identification information corresponding to the second field information;

determining first field information matched with the second field information under the data table identification information from first field information in the data table information;

determining an additional weight corresponding to the second field information according to the weight corresponding to the first field information matched with the second field information under the data table identification information;

and carrying out weighted average processing on the additional weight and the weight corresponding to the second field information to obtain the target weight of the second field information in the historical query information.

In one embodiment, the screening target field information from the second field information according to the target weight of the second field information in the historical query information includes:

sorting second field information in the historical query information according to the target weight of the second field information in the historical query information to obtain the sorted second field information;

and determining second field information with the target weight larger than a preset weight from the sorted second field information as target field information.

In one embodiment, after the target field information and the data table identification information corresponding to the target field information are spliced to obtain the database query request of the database to be queried, the method further includes:

inquiring the database to be inquired according to the database inquiry request to obtain corresponding information;

and sending the information to a corresponding request terminal.

An apparatus for determining a database query request, the apparatus comprising:

the information acquisition module is used for acquiring data table information and historical query information of a database to be queried;

the weight determining module is used for respectively processing the data table information and the historical query information to obtain first field information in the data table information and a weight corresponding to the first field information and a weight corresponding to second field information in the historical query information and the second field information;

the target weight determining module is used for obtaining the target weight of the second field information in the historical query information according to the first field information in the data table information and the weight corresponding to the first field information as well as the second field information in the historical query information and the weight corresponding to the second field information;

the field information screening module is used for screening target field information from second field information according to the target weight of the second field information in the historical query information;

and the query request determining module is used for splicing the target field information and the data table identification information corresponding to the target field information to obtain the database query request of the database to be queried.

A computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:

A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:

The method, the device, the computer equipment and the storage medium for determining the database query request respectively process the acquired data table information and the historical query information of the database to be queried to obtain the weight corresponding to the first field information and the first field information in the data table information and the weight corresponding to the second field information and the second field information in the historical query information, and further determine the target weight of the second field information in the historical query information; then, according to the target weight of second field information in the historical query information, screening out target field information from the second field information, and splicing the screened out target field information and data table identification information corresponding to the target field information to obtain a database query request of a database to be queried; the method and the device achieve the purpose of determining the database query request of the database to be queried according to the data table information and the historical query information of the database to be queried, comprehensively consider the data table information of the database to be queried and the field information in the historical query information, enable the database query request to be determined to be more accurate, avoid the defect that the accuracy of the determined database query request is lower due to the fact that only data with similarity to historical analysis data are used, and further improve the accuracy of determining the database query request.

Drawings

FIG. 1 is a diagram of an exemplary implementation of a method for determining a database query request;

FIG. 2 is a flow diagram that illustrates a method for determining a database query request, according to one embodiment;

FIG. 3 is a flowchart illustrating the steps of determining a weight for a first field of information and a weight for a second field of information in one embodiment;

FIG. 4 is a flow diagram that illustrates the processing of tokenizing annotation information in the spreadsheet information, according to one embodiment;

FIG. 5 is a flowchart illustrating a method for determining a database query request according to another embodiment;

FIG. 6 is a block diagram showing the structure of a database query request determining apparatus according to one embodiment;

FIG. 7 is a diagram illustrating an internal structure of a computer device according to an embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

The method for determining the database query request provided by the application can be applied to the application environment shown in fig. 1. Referring to fig. 1, the application environment diagram includes a server 110, and the server 110 may be implemented by an independent server or a server cluster composed of a plurality of servers. In fig. 1, the server 110 is an independent server for explanation, and referring to fig. 1, the server 110 obtains data table information and historical query information of a database to be queried; processing the data table information and the historical query information respectively to obtain first field information in the data table information and weights corresponding to the first field information and second field information in the historical query information and weights corresponding to the second field information; obtaining the target weight of second field information in the historical query information according to the first field information in the data table information and the weight corresponding to the first field information and the weight corresponding to the second field information in the historical query information; screening target field information from second field information according to the target weight of the second field information in the historical query information; and splicing the target field information and the data table identification information corresponding to the target field information to obtain a database query request of the database to be queried.

It should be noted that the method for determining a database query request provided by the present application may also be applied to other database query scenarios, such as a business data query scenario, a financial data query scenario, a report data query scenario, and the like, and the present application is not limited in particular.

In one embodiment, as shown in fig. 2, a method for determining a database query request is provided, which is described by taking the method as an example applied to the server in fig. 1, and includes the following steps:

step S201, obtaining data table information and historical query information of a database to be queried.

The DATA table information refers to basic information constituting a DATA table, such as DATA table identification information (e.g., TAB L E _ NAME), field information (e.g., CO L UMN _ NAME), field information TYPE (e.g., DATA _ TYPE), COMMENT information (e.g., CO L UMN _ COMMENT), and in an actual scenario, the DATA table identification information refers to a DATA table NAME, the field information refers to a field NAME, and the field information TYPE refers to a field TYPE.

It should be noted that each piece of data table information refers to a row of information formed by data table identification information, field information type, and comment information; for example, such as fact _ mdc _ product _ info | TRANS _ DATE | varchar | DATE; wherein, the fact _ mdc _ product _ info refers to data table identification information, the TRANS _ DATE refers to field information, the varchar refers to a field information type, and the DATE refers to comment information. Note that the data table information in the present application refers to a plurality of data table information, for example, data table information 1: the data table comprises data table identification information A, field information B, field information type C and comment information D; data table information 2: data table identification information a, field information E, field information type F, comment information G, and so on.

The historical query information refers to a historical query language of a database to be queried, such as SQ L (structured query L anguage), and includes a data table name, field information, and the like, and can be obtained by collecting data audit information of the database to be queried specifically.

"SE L ECT TAB L E _ NAME, CO L UMN _ NAME, DATA _ TYPE, CO L UMN _ COMMENT information _ SCHEMA, CO L UMNs worker TAB L E _ SCHEMA", WHERE information _ SCHEMA refers to a database.

Specifically, the server extracts data table information from a database to be queried according to a preset data extraction instruction; obtaining a historical query log of a database to be queried, and extracting historical query information of the database to be queried from the historical query log of the database to be queried. Therefore, by acquiring the data table information and the historical query information of the database to be queried, the subsequent analysis and processing of the data table information and the historical query information of the database to be queried are facilitated, and the weight corresponding to the first field information and the first field information in the data table information and the weight corresponding to the second field information and the second field information in the historical query information are obtained.

For example, the server obtains a preset data extraction instruction, and extracts basic information of the data table, such as data table identification information, field information type, comment information, and the like, from an information database (such as an information _ schema database) of the database to be queried according to the preset data extraction instruction; constructing data table information of a database to be queried according to the basic information of the data table; then, the server collects historical query logs containing historical query information, such as data audit information, by using a database log upgrading tool, and extracts information corresponding to the historical query information identifier from the historical query logs as the historical query information of the database to be queried.

Further, after the data table information and the historical query information of the database to be queried are obtained, the data table information of the database to be queried can be filtered to obtain the filtered data table information, for example, the data table information with the field information type of C L OB/B L OB is filtered, and for example, the data table information with the field information of ID field information is filtered.

Step S202, the data table information and the historical query information are respectively processed, and the weight corresponding to the first field information and the first field information in the data table information and the weight corresponding to the second field information and the second field information in the historical query information are obtained.

The first field information refers to field information in data table information, and the second field information refers to effective field information screened from field information in historical query information.

The weight corresponding to the first field information in the data table information is used for measuring the recommendation degree of the first field information in the data table information; generally, the larger the weight corresponding to the first field information in the data table information is, the larger the recommendation degree of the first field information in the data table information is represented; the smaller the weight corresponding to the first field information in the data table information is, the smaller the recommendation degree of the first field information in the data table information is.

The weight corresponding to the first field information in the data table information is determined by the weight corresponding to the comment information in the data table information; generally, the larger the weight corresponding to the comment information in the data table information is, the larger the weight corresponding to the first field information in the data table information is; the smaller the weight corresponding to the comment information in the data table information, the smaller the weight corresponding to the first field information in the data table information.

The weight corresponding to the second field information in the historical query information is used for measuring the recommendation degree of the second field information in the historical query information; generally, the larger the weight corresponding to the second field information in the historical query information is, the larger the recommendation degree of the second field information in the historical query information is represented; the smaller the weight corresponding to the second field information in the historical query information is, the smaller the recommendation degree of the second field information in the historical query information is.

The weight corresponding to the second field information in the historical query information is determined by the query frequency of the second field information in the historical query information; generally, the larger the query frequency of the second field information in the historical query information is, the larger the weight corresponding to the second field information in the historical query information is; the smaller the query frequency of the second field information in the historical query information is, the smaller the weight corresponding to the second field information in the historical query information is.

Specifically, the server extracts first field information and annotation information from the data table information, queries a database in which weights corresponding to a plurality of annotation information are stored, and acquires the weight corresponding to the annotation information; identifying the weight corresponding to the annotation information as the weight corresponding to the first field information; acquiring field information in the historical query information, and performing statistical analysis on the field information in the historical query information to obtain query frequency of the field information in the historical query information; according to the query frequency of the field information in the historical query information, combining with an association rule algorithm, screening effective field information from the field information in the historical query information to serve as second field information in the historical query information; and obtaining the weight corresponding to the second field information in the historical query information according to the query frequency of the second field information in the historical query information. Therefore, the target weight of the second field information in the historical query information can be accurately determined in the follow-up process by acquiring the first field information in the data table information and the weight corresponding to the first field information and the weight corresponding to the second field information in the historical query information and the weight corresponding to the second field information.

Step S203, according to the first field information in the data table information and the weight corresponding to the first field information and the second field information in the historical query information and the weight corresponding to the second field information, obtaining the target weight of the second field information in the historical query information.

The target weight of the second field information in the historical query information refers to the final weight of the second field information in the historical query information.

Specifically, the server determines, from first field information in the data table information, first field information that corresponds to the data table identification information and data table identification information corresponding to second field information in the historical query information are consistent and matched with the second field information in the historical query information; and adjusting the weight corresponding to the second field information in the historical query information according to the weight corresponding to the first field information matched with the second field information in the historical query information to obtain the adjusted weight which is used as the target weight of the second field information in the historical query information. Therefore, the target field information can be screened from the second field information according to the target weight of the second field information in the historical query information.

Further, the server may perform weighting processing on a weight corresponding to the first field information matched with the second field information in the historical query information and a weight corresponding to the second field information in the historical query information to obtain a target weight of the second field information in the historical query information.

And step S204, screening out target field information from the second field information according to the target weight of the second field information in the historical query information.

The target weight of the second field information in the historical query information is used for measuring the recommendation strength of the second field information in the historical query information; generally, the larger the target weight of the second field information in the historical query information is, the greater the recommendation strength of the second field information in the historical query information is represented; the smaller the target weight of the second field information in the historical query information is, the smaller the recommendation strength of the second field information in the historical query information is.

The target field information refers to field information with a finally determined target weight meeting requirements, for example, second field information with a target weight greater than a preset weight.

Specifically, the server screens out second field information with the target weight larger than the preset weight from second field information in the historical query information as target field information. Therefore, the determined target field information and the data table identification information corresponding to the target field information can be automatically spliced to obtain the database query request of the database to be queried, the database query request does not need to be manually compiled, and the labor cost is reduced.

Step S205, performing a splicing process on the target field information and the data table identification information corresponding to the target field information to obtain a database query request of the database to be queried.

The data table identification information refers to identification information of the data table information, such as a data table name, a data table number and the like, and the database query request refers to a request for querying a database to be queried, such as SQ L.

Specifically, the server acquires data table identification information corresponding to target field information, and performs splicing processing on the target field information and the data table identification information corresponding to the target field information according to a preset splicing instruction to obtain spliced information serving as a database query request of a database to be queried; therefore, the method is beneficial to comprehensively considering the data table information of the database to be queried and the field information in the historical query information, the defect that the accuracy of the determined database query request is low due to the fact that only data with similarity to the historical analysis data are used is avoided, and the accuracy of the determination of the database query request is further improved.

For example, if the target field information is arg _ name and use _ times, and the data table identification information corresponding to the target field information is MDC, the determined database query request is select arg _ name and use _ times from MDC.

In the method for determining the database query request, the acquired data table information and the acquired historical query information of the database to be queried are respectively processed to obtain the first field information in the data table information and the weight corresponding to the first field information and the second field information in the historical query information and the weight corresponding to the second field information, and further the target weight of the second field information in the historical query information is determined; then, according to the target weight of second field information in the historical query information, screening out target field information from the second field information, and splicing the screened out target field information and data table identification information corresponding to the target field information to obtain a database query request of a database to be queried; the method and the device achieve the purpose of determining the database query request of the database to be queried according to the data table information and the historical query information of the database to be queried, comprehensively consider the data table information of the database to be queried and the field information in the historical query information, enable the database query request to be determined to be more accurate, avoid the defect that the accuracy of the determined database query request is lower due to the fact that only data with similarity to historical analysis data are used, and further improve the accuracy of determining the database query request.

In an embodiment, as shown in fig. 3, in the step S202, the processing is performed on the data table information and the historical query information respectively to obtain weights corresponding to a first field information and a first field information in the data table information and weights corresponding to a second field information and a second field information in the historical query information, and the method specifically includes the following steps:

step S301, acquiring first field information and annotation information in the data table information, and performing word segmentation processing on the annotation information to obtain annotation word segmentation information in the data table information.

The annotation word segmentation information refers to words contained in the annotation information; for example, if the comment information is "date of product", the comment participle information is "product", "date".

Specifically, the server extracts information corresponding to a preset field information identifier from the data table information as first field information; extracting information corresponding to a preset annotation information identifier from the data table information as annotation information; and performing word segmentation processing on the annotation information according to a preset word segmentation processing instruction to obtain words contained in the annotation information, wherein the words are used as the annotation word segmentation information in the data table information.

For example, the word segmentation is used as a maximum forward matching method for description, and referring to fig. 4, assuming that the longest word in the dictionary knowledge base includes i chinese characters, the first i chinese characters in the annotation information are used as matching fields to be matched with the longest word in the dictionary knowledge base that includes i chinese characters; if the matching fails, removing the last Chinese character in the first i Chinese character characters in the annotation information to obtain the first i-1 Chinese character characters in the annotation information, using the first i-1 Chinese character characters as matching fields, and continuing to match words containing the i-1 Chinese character characters in a dictionary knowledge base; if the matching is successful, splitting the annotation information, taking the first i Chinese characters in the annotation information as first annotation word segmentation information, simultaneously judging whether the rest Chinese characters in the annotation information are empty, if so, outputting word segmentation results of the annotation information, and if not, taking the first i Chinese characters of the rest Chinese characters in the annotation information as matching fields to be matched with the longest word containing the i Chinese characters in a dictionary knowledge base; by analogy, the annotation word segmentation information in the data table information can be obtained.

It should be noted that the present application may also perform word segmentation processing on the annotation information by other word segmentation methods based on string matching, such as a reverse maximum matching method, a minimum segmentation method, a bidirectional maximum matching method, and the like; of course, the annotation information may also be subjected to word segmentation processing by a word segmentation method based on understanding, a word segmentation method based on statistics, and the like, and the specific application is not limited.

Step S302, determining the weight corresponding to the first field information in the data table information according to the comment participle information in the data table information.

Specifically, the server obtains the weight of the annotation participle information in the data table information, and determines the weight corresponding to the first field information in the data table information according to the weight of the annotation participle information in the data table information.

Step S303, acquiring the field information and the query frequency of the field information in the historical query information, and determining the second field information and the query frequency of the second field information in the historical query information according to the field information and the query frequency of the field information in the historical query information.

The query frequency of the field information refers to the occurrence frequency of the field information in the historical query information, and specifically refers to the use frequency of the field information in the historical query information.

Specifically, the server extracts information corresponding to a preset field information identifier from the historical query information, and the information is used as field information in the historical query information; carrying out statistical analysis on field information in the historical query information to obtain the query frequency of the field information; according to an association rule algorithm (such as an Apriori algorithm), field information meeting requirements is screened out from field information in historical query information by utilizing the query frequency of the field information to serve as candidate field information, the field information meeting the requirements is screened out from the candidate field information to serve as second field information in the historical query information, and the query frequency corresponding to the field information is used as the query frequency of the second field information.

Step S304, normalization processing is carried out on the query frequency of each second field information, and the weight corresponding to each second field information in the historical query information is obtained.

For example, assuming that there are 3 pieces of second field information, which are a1, a2, and A3, respectively, and the corresponding query frequencies are b1, b2, and b3, respectively, the weights corresponding to the 3 pieces of second field information, a1, a2, and A3, are b1/(b1+ b2+ b3), b2/(b1+ b2+ b3), and b3/(b1+ b2+ b3), respectively.

In this embodiment, the target weight of the second field information in the historical query information can be accurately determined in the following process by obtaining the weight corresponding to the first field information and the first field information in the data table information and the weight corresponding to the second field information and the second field information in the historical query information.

In an embodiment, the step S302 of determining, according to the comment participle information in the data table information, a weight corresponding to the first field information in the data table information includes: filtering the annotation word segmentation information in the data table information to obtain filtered annotation word segmentation information; acquiring index weight corresponding to the filtered annotation word segmentation information; and acquiring the sum of the index weights corresponding to the filtered annotation participle information as the weight corresponding to the first field information in the data table information.

Specifically, the server performs text deduplication processing and general word deletion processing on the annotation participle information in the data table information by using a dirty data knowledge base in which meaningless annotation information, meaningless field information and the like are stored, for example, removing repeated parts in the annotation participle information, deleting meaningless annotation participle information such as update time, an operator and the like, and thus obtaining filtered annotation participle information; inquiring an index knowledge base in which index weights corresponding to a plurality of index information are stored, determining index information matched with the annotation participle information, and taking the index weight corresponding to the index information as the index weight of the annotation participle information; by referring to the method, index weights corresponding to the filtered annotation word segmentation information can be obtained; and adding the index weights corresponding to the filtered annotation participle information to obtain the weight corresponding to the first field information in the data table information. The index knowledge base stores index information of the characteristic industry and corresponding index weights, such as industrial utilization rate, starting rate and the like; the index weight refers to the degree of use and reception of the corresponding index information in the industry or field, for example, the index weight of the utilization rate is 0.9, and the index weight of the activation rate is 0.8.

After determining the weight corresponding to the first field information in the data table information according to the comment participle information in the data table information, the data format of the data table information is as follows: the data table identification information, the first field information, the field information type, the comment participle information (after filtering), and the weight corresponding to the first field information. In an actual scenario, the data format of the data table information is as follows: table name, field type, comment list information, weight value.

In the embodiment, by filtering the annotation participle information in the data table information, the interference of redundant information is avoided, so that the accuracy of determining the weight corresponding to the first field information in the data table information is improved.

In one embodiment, the step S303 of determining query frequencies of the second field information and the second field information in the historical query information according to the field information and the query frequency of the field information in the historical query information includes: determining the support degree of the field information in the historical query information according to the field information in the historical query information and the query frequency of the field information; taking the field information with the support degree greater than or equal to the preset support degree as candidate field information in the historical query information; determining the confidence coefficient of the candidate field information in the historical query information according to the query frequency of the candidate field information in the historical query information; and correspondingly taking the candidate field information with the confidence coefficient greater than or equal to the preset confidence coefficient and the query frequency of the candidate field information as the second field information and the query frequency of the second field information in the historical query information.

Wherein, the support degree refers to the occurrence probability of the item set { X, Y } in the total item set, the confidence degree refers to the occurrence probability of Y in the item set containing X, and X, Y respectively represents field information; in an actual scenario, the support ({ X- > Y }) -the number of times that the field information X and the field information Y appear in one query record at the same time/the total query record number, and the confidence ({ X- > Y }) -the number of times that the field information X and the field information Y appear in one query record at the same time/the number of times that the field information X appears.

It should be noted that the preset support degree and the preset confidence degree may be adjusted according to actual situations, and the specific application is not limited.

Specifically, the server acquires the total query frequency of the historical query information, determines the ratio of the query frequency of the field information in the historical query information to the total query frequency of the historical query information, and uses the ratio as the support degree of the field information in the historical query information, and uses the field information of which the support degree is greater than or equal to the preset support degree as the candidate field information in the historical query information; determining the ratio of the previous field information and the next field information according to the query frequency of the candidate field information in the historical query information and the query frequency of the first field information in the candidate field information, using the ratio as the confidence coefficient of the candidate field information in the historical query information, and correspondingly using the candidate field information with the confidence coefficient being greater than or equal to the preset confidence coefficient and the query frequency of the candidate field information as the second field information and the query frequency of the second field information in the historical query information.

For example, the server performs statistical analysis on the query frequency of the field information in the historical query information based on Apriori algorithm to obtain the field information with the support degree greater than or equal to the preset support degree, and the field information is used as a field information frequent item set of the historical query information; and counting the query frequency of the field information frequent item set and the query frequency of the first field information in the field information frequent item set to obtain the query frequency of the field information frequent item set and the field information frequent item set, wherein the confidence coefficient of the field information frequent item set is greater than or equal to the preset confidence coefficient, and the query frequency is correspondingly used as the second field information and the second field information in the historical query information.

It should be noted that, after determining the query frequency of the second field information and the second field information in the historical query information according to the field information and the query frequency of the field information in the historical query information, the data format of the historical query information is as follows: the data table identification information, the second field information and the query frequency of the second field information. In an actual scenario, the data format of the historical query information is as follows: table name, combined field list, number of uses; such as MDC, time field, plant field, 20.

In this embodiment, according to the field information in the historical query information and the query frequency of the field information, the second field information with the support degree and the confidence degree both meeting the requirements is determined, which is favorable for improving the determination accuracy of the second field information in the historical query information.

In an embodiment, in step S203, obtaining a target weight of the second field information in the historical query information according to the first field information in the data table information and the weight corresponding to the first field information, and the second field information in the historical query information and the weight corresponding to the second field information, includes: identifying data table identification information corresponding to the second field information; determining first field information matched with second field information under the data table identification information from the first field information in the data table information; determining an additional weight corresponding to the second field information according to the weight corresponding to the first field information matched with the second field information under the data table identification information; and carrying out weighted average processing on the additional weight and the weight corresponding to the second field information to obtain the target weight of the second field information in the historical query information.

Specifically, the server acquires historical query information of a second field information, extracts data table identification information as data table identification information corresponding to the second field information from the historical query information, determines first field information matched with the second field information under the data table identification information from first field information in the data table information, for example, the second field information is field information B and field information C, the data table identification information of the second field information is data table A, the corresponding data table information is data table A, the field information B-C-S.

It should be noted that, after the target weight of the second field information in the historical query information is obtained, the data format of the historical query information is as follows: data table identification information, second field information and target weight; in an actual scenario, the data format of the historical query information is as follows: table name, combined field list, weight value.

In this embodiment, by obtaining the target weight of the second field information in the historical query information, it is beneficial to subsequently screen out the target field information from the second field information according to the target weight of the second field information in the historical query information, and further determine the database query request of the database to be queried.

In an embodiment, in step S204, the screening out the target field information from the second field information according to the target weight of the second field information in the historical query information includes: sorting the second field information in the historical query information according to the target weight of the second field information in the historical query information to obtain the sorted second field information; and determining second field information with the target weight larger than the preset weight from the sorted second field information as target field information.

Specifically, the server sorts the second field information in the historical query information according to the sequence of the target weight of the second field information in the historical query information from high to low, and determines the second field information with the target weight larger than 0.6 from the sorted second field information as the target field information.

In this embodiment, the target field information is screened from the second field information, which is beneficial to performing automatic splicing processing on the determined target field information and the data table identification information corresponding to the target field information subsequently to obtain a database query request of the database to be queried; the defect that the accuracy of the determined database query request is low due to the fact that only data with similarity to historical analysis data are used is avoided, and the accuracy of the determination of the database query request is further improved.

In an embodiment, in step S205, after the splicing processing is performed on the target field information and the data table identification information corresponding to the target field information to obtain the database query request of the database to be queried, the method further includes: inquiring a database to be inquired according to the database inquiry request to obtain corresponding information; and sending the information to the corresponding request terminal.

The request terminal may be various computer devices or terminal devices, such as a personal computer, a notebook computer, a smart phone, and the like.

Specifically, the server queries the database to be queried according to the database query request, acquires information corresponding to the database query request from the database to be queried, and sends the information to the corresponding request terminal for displaying.

In this embodiment, the database to be queried is queried through the accurately determined database query request, which is beneficial to improving the accuracy of the information obtained by querying and further improving the accuracy of data query.

In one embodiment, as shown in fig. 5, another method for determining a database query request is provided, which is described by taking the method as an example applied to the server in fig. 1, and includes the following steps:

step S501, data table information and historical query information of a database to be queried are obtained.

Step S502, filtering the data table information of the database to be queried to obtain the filtered data table information.

Step S503, acquiring the first field information and the comment information in the filtered data table information, and performing word segmentation processing on the comment information to obtain the comment word segmentation information in the filtered data table information.

And step S504, filtering the annotation participle information in the filtered data table information to obtain the filtered annotation participle information.

Step S505, acquiring index weight corresponding to the filtered annotation participle information; and acquiring the sum of the index weights corresponding to the filtered annotation word segmentation information as the weight corresponding to the first field information in the filtered data table information.

Step S506, field information in the historical query information and the query frequency of the field information are obtained.

Step S507, determining the support degree of the field information in the historical query information according to the field information in the historical query information and the query frequency of the field information.

Step S508, using the field information with the support degree greater than or equal to the preset support degree as the candidate field information in the historical query information.

Step S509, determining the confidence of the candidate field information in the historical query information according to the query frequency of the candidate field information in the historical query information.

Step S510, the candidate field information with the confidence greater than or equal to the preset confidence and the query frequency of the candidate field information are used as the second field information and the query frequency of the second field information in the historical query information.

Step S511, performing normalization processing on the query frequency of each second field information to obtain a weight corresponding to each second field information in the historical query information.

Step S512, identifying the data table identification information corresponding to the second field information; and determining first field information matched with the second field information under the data table identification information from the first field information in the data table information.

Step S513, determining an additional weight corresponding to the second field information according to the weight corresponding to the first field information matched with the second field information under the data table identification information.

Step S514, performing weighted average processing on the additional weight and the weight corresponding to the second field information to obtain the target weight of the second field information in the historical query information.

Step S515, sorting the second field information in the historical query information according to the target weight of the second field information in the historical query information, so as to obtain the sorted second field information.

Step S516, determining second field information with a target weight greater than a preset weight from the sorted second field information as target field information.

And step S517, splicing the target field information and the data table identification information corresponding to the target field information to obtain a database query request of the database to be queried.

The method for determining the database query request comprises the steps of processing the acquired data table information and historical query information of the database to be queried respectively to obtain the weight corresponding to first field information and first field information in the data table information and the weight corresponding to second field information and second field information in the historical query information, and further determining the target weight of the second field information in the historical query information; then, according to the target weight of second field information in the historical query information, screening out target field information from the second field information, and splicing the screened out target field information and data table identification information corresponding to the target field information to obtain a database query request of a database to be queried; the method and the device achieve the purpose of determining the database query request of the database to be queried according to the data table information and the historical query information of the database to be queried, comprehensively consider the data table information of the database to be queried and the field information in the historical query information, enable the database query request to be determined to be more accurate, avoid the defect that the accuracy of the determined database query request is lower due to the fact that only data with similarity to historical analysis data are used, and further improve the accuracy of determining the database query request.

It should be understood that although the steps in the flowcharts of fig. 2, 3, and 5 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2, 3, and 5 may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed alternately or alternately with other steps or at least some of the other steps or stages.

In one embodiment, as shown in fig. 6, there is provided a database query request determining apparatus, including: an information obtaining module 610, a weight determining module 620, a target weight determining module 630, a field information screening module 640, and a query information determining module 650, wherein:

the information obtaining module 610 is configured to obtain data table information and historical query information of a database to be queried.

The weight determining module 620 is configured to process the data table information and the historical query information respectively to obtain a weight corresponding to a first field information and a first field information in the data table information and a weight corresponding to a second field information and a second field information in the historical query information.

And a target weight determining module 630, configured to obtain a target weight of the second field information in the historical query information according to the first field information in the data table information and a weight corresponding to the first field information, and the second field information in the historical query information and a weight corresponding to the second field information.

And the field information screening module 640 is configured to screen the target field information from the second field information according to the target weight of the second field information in the historical query information.

And the query request determining module 650 is configured to splice the target field information and the data table identification information corresponding to the target field information to obtain a database query request of the database to be queried.

In one embodiment, the weight determining module 620 is further configured to obtain first field information and comment information in the data table information, and perform word segmentation processing on the comment information to obtain comment word segmentation information in the data table information; determining the weight corresponding to the first field information in the data table information according to the annotation word segmentation information in the data table information; acquiring field information in the historical query information and the query frequency of the field information, and determining second field information in the historical query information and the query frequency of the second field information according to the field information in the historical query information and the query frequency of the field information; and normalizing the query frequency of each second field information to obtain the weight corresponding to each second field information in the historical query information.

In one embodiment, the weight determining module 620 is further configured to filter the annotation segmentation information in the data table information to obtain filtered annotation segmentation information; acquiring index weight corresponding to the filtered annotation word segmentation information; and acquiring the sum of the index weights corresponding to the filtered annotation participle information as the weight corresponding to the first field information in the data table information.

In one embodiment, the weight determining module 620 is further configured to determine a support degree of the field information in the historical query information according to the field information in the historical query information and the query frequency of the field information; taking the field information with the support degree greater than or equal to the preset support degree as candidate field information in the historical query information; determining the confidence coefficient of the candidate field information in the historical query information according to the query frequency of the candidate field information in the historical query information; and correspondingly taking the candidate field information with the confidence coefficient greater than or equal to the preset confidence coefficient and the query frequency of the candidate field information as the second field information and the query frequency of the second field information in the historical query information.

In one embodiment, the target weight determination module 630 is further configured to identify data table identification information corresponding to the second field information; determining first field information matched with second field information under the data table identification information from the first field information in the data table information; determining an additional weight corresponding to the second field information according to the weight corresponding to the first field information matched with the second field information under the data table identification information; and carrying out weighted average processing on the additional weight and the weight corresponding to the second field information to obtain the target weight of the second field information in the historical query information.

In one embodiment, the field information screening module 640 is further configured to sort the second field information in the historical query information according to the target weight of the second field information in the historical query information, so as to obtain the sorted second field information; and determining second field information with the target weight larger than the preset weight from the sorted second field information as target field information.

In one embodiment, the apparatus for determining a database query request further includes a data query module, configured to query a database to be queried according to the database query request, so as to obtain corresponding information; and sending the information to the corresponding request terminal.

The embodiments achieve the purpose of determining the database query request of the database to be queried according to the data table information and the historical query information of the database to be queried, comprehensively consider the data table information of the database to be queried and the field information in the historical query information, so that the determination of the database query request is more accurate, the defect that the accuracy of the determined database query request is lower due to the fact that only data with similarity to historical analysis data are used is avoided, and the determination accuracy of the database query request is further improved.

The specific definition of the determining device for the database query request may refer to the above definition of the determining method for the database query request, and is not described herein again. The modules in the database query request determination device may be implemented in whole or in part by software, hardware, and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.

In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 7. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing data such as data table information, historical query information and the like. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of determining a database query request.

Those skilled in the art will appreciate that the architecture shown in fig. 7 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the above-described method embodiments when executing the computer program.

In an embodiment, a computer-readable storage medium is provided, in which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include at least one of non-volatile and volatile memory. Non-volatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others.

The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims

1. A method for determining a database query request, the method comprising:

2. The method according to claim 1, wherein the processing the data table information and the historical query information to obtain weights corresponding to a first field information and a first field information in the data table information and weights corresponding to a second field information and a second field information in the historical query information respectively comprises:

3. The method of claim 2, wherein the determining the weight corresponding to the first field information in the data table information according to the annotation participle information in the data table information comprises:

4. The method of claim 2, wherein determining the query frequency of the second field information and the second field information in the historical query information according to the field information in the historical query information and the query frequency of the field information comprises:

5. The method according to claim 1, wherein obtaining the target weight of the second field information in the historical query information according to the first field information in the data table information and the weight corresponding to the first field information and the weight corresponding to the second field information in the historical query information comprises:

6. The method of claim 1, wherein the screening out target field information from second field information according to a target weight of the second field information in the historical query information comprises:

7. The method according to any one of claims 1 to 6, wherein after the target field information and the data table identification information corresponding to the target field information are spliced to obtain the database query request of the database to be queried, the method further comprises:

and sending the information to a corresponding request terminal.

8. An apparatus for determining a database query request, the apparatus comprising:

9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 7.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.