A query statement generation method, device and equipment and storage medium

Abstract

The application relates to the computer field and discloses a query statement generation method and device, equipment and a storage medium. The method comprises the following steps: obtaining a database statement to be parsed, inputting the database statement into a search engine for format conversion processing to generate list data; performing parsing processing on the list data to assemble a query condition expression; converting the query condition expression into a search engine code and generating a search engine code package according to the search engine code; receiving a business logic query request of a client, obtaining the search engine code from the search engine code package, and assembling a query statement corresponding to the business logic query request. According to the application, the database statement is converted into a query statement of a search engine suitable for a predetermined language system, and then the search engine can quickly query corresponding business data according to the query statement, so that the query efficiency is improved.

Description

Technical Field

[0001] This application relates to the field of computers, and more particularly to a method, apparatus, device, and storage medium for generating query statements. Background Technology

[0002] Currently, Elasticsearch technology is widely used in real-world business scenarios such as fintech due to its excellent features, including real-time searching of massive amounts of data, fast multi-dimensional querying and aggregation. Business systems are built using Elasticsearch technology.

[0003] In fintech and other sectors, such as banks, the increasing number of users and developers using internal banking systems, coupled with the continuous upgrades and iterations of Elasticsearch technology, has led to increasingly severe labor costs and risks associated with developing complex business systems based on Elasticsearch. Furthermore, when performing database queries and other operations within these Elasticsearch-based systems, the incompatibility between database statements and the constantly evolving search engine languages ​​within the business system results in low query efficiency and inefficient data management. Summary of the Invention

[0004] In view of this, in order to overcome the shortcomings of the existing technology, this application provides a query statement generation method, apparatus, device and storage medium that can be applied to fields such as financial technology or other fields.

[0005] Firstly, this application provides a method for generating query statements, including:

[0006] Obtain the database statement to be parsed, and input the database statement into the search engine for format conversion processing to generate list data;

[0007] The list data is parsed and processed to assemble a query condition expression;

[0008] The query condition expression is converted into search engine code, and a search engine code package is generated based on the search engine code;

[0009] The system receives a business logic query request from a client, retrieves the search engine code from the search engine code package, and assembles it into a query statement corresponding to the business logic query request.

[0010] In an optional implementation, the step of inputting the database statement into a search engine for format conversion processing to generate list data includes:

[0011] The database statement is split into key values ​​using a search engine to obtain condition strings and symbol characters.

[0012] The condition string and the symbol character are stored in list form respectively to generate list data.

[0013] In an optional implementation, storing the condition string and the symbol character in list form to generate list data includes:

[0014] Find the left parenthesis character among the symbol characters, record the position information of the left parenthesis character in the database statement, and store the position information in the form of a stack;

[0015] The condition string and the symbol characters that do not contain the left parenthesis character are stored in list form to generate list data.

[0016] In an optional implementation, the step of parsing the list data to assemble it into a query condition expression includes:

[0017] Traverse the list data and find the operator from the symbol characters; wherein the operator is used to indicate business operation logic;

[0018] Based on the operators, the condition strings are assembled into query condition expressions corresponding to the business operation logic.

[0019] In an optional implementation, converting the query condition expression into search engine code includes:

[0020] Set the query time and filtering conditions, and set the aggregation fields using the aggregation functions supported by the search engine;

[0021] The query time, the filtering conditions, and the aggregation fields are respectively combined with the query condition expression to generate search engine code.

[0022] In an optional implementation, the method further includes:

[0023] Set a routing value, wherein the routing value is used to indicate the storage location information of the business data corresponding to the condition string in the query condition expression;

[0024] Add the routing value to the search engine code to generate search engine code containing routing information.

[0025] In an optional implementation, after obtaining the search engine code from the search engine code package and assembling it into a query statement corresponding to the business logic query request, the method further includes:

[0026] Based on the routing value in the query statement, the business data indicated by the routing value is queried and processed, and then the business data is used as the result data returned after the query statement is executed.

[0027] Secondly, this application provides a query statement generation apparatus, comprising:

[0028] The acquisition module is used to acquire the database statement to be parsed, and input the database statement into the search engine for format conversion processing to generate list data;

[0029] The parsing module is used to parse and process the list data to assemble it into a query condition expression;

[0030] A conversion module is used to convert the query condition expression into search engine code and generate a search engine code package based on the search engine code;

[0031] The generation module is used to receive the client's business logic query request, obtain the search engine code from the search engine code package, and assemble it into a query statement corresponding to the business logic query request.

[0032] Thirdly, this application provides a computer device, the computer device including a memory and at least one processor, the memory storing a computer program, and the processor executing the computer program to implement the aforementioned query statement generation method.

[0033] Fourthly, this application provides a computer storage medium storing a computer program, which, when executed, implements the aforementioned query statement generation method.

[0034] The embodiments of this application have the following beneficial effects:

[0035] This application provides a query statement generation method, which includes: obtaining a database statement to be parsed, inputting the database statement into a search engine for format conversion processing to generate list data; parsing the list data to assemble it into a query condition expression; converting the query condition expression into search engine code, and generating a search engine code package based on the search engine code; receiving a business logic query request from a client, obtaining the search engine code from the search engine code package, and assembling it into a query statement corresponding to the business logic query request. This application improves query efficiency by converting the database statement into a query statement suitable for a search engine with a predetermined language system, thereby enabling the search engine to quickly retrieve the corresponding business data based on the query statement. Attached Figure Description

[0036] To more clearly illustrate the technical solutions of this application, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of this application and should not be considered as a limitation on the scope of protection of this application. In the various drawings, similar components are numbered similarly.

[0037] Figure 1 This illustration shows a schematic diagram of the first implementation of the query statement generation method in this application.

[0038] Figure 2 A schematic diagram of a second embodiment of the query statement generation method in this application is shown;

[0039] Figure 3 A schematic diagram of a third embodiment of the query statement generation method in this application is shown;

[0040] Figure 4 This illustration shows a fourth implementation diagram of the query statement generation method in this application.

[0041] Figure 5 A schematic diagram of the fifth embodiment of the query statement generation method in this application is shown;

[0042] Figure 6 A schematic diagram of the sixth embodiment of the query statement generation method in this application is shown;

[0043] Figure 7 A schematic diagram of the query statement generation device in an embodiment of this application is shown. Detailed Implementation

[0044] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0045] The components of the embodiments of this application described and illustrated in the accompanying drawings can be arranged and designed in a variety of different configurations. Therefore, the following detailed description of the embodiments of this application provided in the drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0046] In the following, the terms “comprising,” “having,” and their cognates, which may be used in various embodiments of this application, are intended only to indicate a particular feature, number, step, operation, element, component, or combination thereof, and should not be construed as excluding, firstly, the presence of one or more other features, numbers, steps, operations, elements, components, or combinations thereof, or adding the possibility of one or more features, numbers, steps, operations, elements, components, or combinations thereof.

[0047] Furthermore, the terms "first," "second," and "third" are used only to distinguish descriptions and should not be interpreted as indicating or implying relative importance.

[0048] Unless otherwise specified, all terms used herein (including technical and scientific terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which the various embodiments of this application pertain. Terms (such as those defined in commonly used dictionaries) shall be interpreted as having the same meaning as in their contextual meaning in the relevant technical field and shall not be construed as having an idealized or overly formal meaning, unless clearly defined in the various embodiments of this application.

[0049] Elasticsearch: A distributed, RESTful search engine. It supports retrieval of various data types, offers fast search speeds, provides real-time search services, is easily horizontally scalable, and can process petabytes of data per second.

[0050] Currently, Elasticsearch technology is widely used in real-world business scenarios such as fintech to build relevant business systems for data interaction and management.

[0051] However, with the increasing number of business systems and developers using Elasticsearch, coupled with continuous upgrades and iterations of Elasticsearch itself, the labor costs and risks of developing complex business systems based on Elasticsearch technology have become increasingly severe. Previously, development isolated the complex implementation of the database using SQL, but the constantly evolving Elasticsearch technology makes it difficult for the query language of the search engine within the business system to adapt to database statements. Therefore, the industry also needs a language similar to SQL that can interact with Elasticsearch (i.e., EQL) for the rapid and secure development of business systems using Elasticsearch, improving the efficiency of data retrieval within the database.

[0052] Based on this, this application provides a query statement generation method. By assembling database statements into query statements suitable for search engines (i.e., EQL), it facilitates data query operations in business systems developed using Elasticsearch technology, thereby effectively improving data query efficiency and data management efficiency. This also makes it easier for business personnel to query relevant data, enhancing the user experience and demonstrating good practicality. This method can be applied to servers or terminal devices equipped with search engines. This embodiment specifically uses a server as an example; please refer to... Figure 1 The method will now be explained in detail.

[0053] S10: Obtain the database statement to be parsed, input the database statement into the search engine for format conversion processing, and generate list data.

[0054] The server obtains the database statement to be parsed (i.e., the EQL statement) and passes it to the search engine through key-value pairs for syntax parsing and transformation. The search engine then generates a query statement, which is subsequently analyzed to determine the corresponding business data.

[0055] Specifically, the default search engine can split the database statement to be parsed and convert the split database statement format into list data suitable for the search engine, so that the list data can be converted into an executable query statement later.

[0056] Furthermore, such as Figure 2 As shown, the step S10 above, "inputting the database statement into the search engine for format conversion processing to generate list data," specifically includes the following steps:

[0057] S11 uses a search engine to split the database statement into keyword values, resulting in condition strings and symbol characters.

[0058] S12: Store the condition string and symbol characters in list form respectively to generate list data.

[0059] By splitting database statements into keyword values ​​using a search engine, the hierarchical structure of the database statements can be identified. This allows the database statements to be reorganized based on the keyword values ​​and hierarchical structure, making them suitable for the search engine.

[0060] Specifically, in this embodiment, the keyword value includes a condition string and a symbol character. The database statement is then split to obtain the condition string and the symbol character, and the condition string and the symbol character are stored in a list format to obtain list data.

[0061] The condition string includes definition strings, assignment strings, and conditional strings; symbol characters include parentheses (such as "(" and ")") and commas (such as ","). The specific settings for this keyword value can be adjusted according to actual needs to split the database statement as required; no specific limitations are specified here.

[0062] For example, if the database statement to be parsed is “acctNbr=13233,((org=242,billMonth=11111) / billMonth=2222),cardNbr$in=123|456”; then, after splitting it, the generated list data is (“[]” represents a list storage structure): [acctNbr=13233],[,],[(],[(],[org=242],[,],[billMonth=11111],[)],[ / ],[billMonth=2222],[)],[,],[cardNbr$in=123|456]; obviously, “acctNbr=13233” etc. are condition strings, and “,” etc. are symbol characters.

[0063] Furthermore, such as Figure 3 As shown, S12 specifically includes the following steps:

[0064] S121, find the left bracket character among the symbol characters, record the position information of the left bracket character in the database statement, and store the position information in the form of a stack.

[0065] S122, store the condition string and the symbol characters that do not contain left parentheses in list form respectively, and generate list data.

[0066] It is important to note that if the symbolic characters obtained from splitting the database statement to be parsed contain a left parenthesis character, the hierarchical structure of the database statement is traversed to record the position information of all left parenthesis characters in the database statement, and this position information is stored in the form of a stack. That is, a stack structure is used to record the position information of the left parenthesis character, while the remaining characters are stored in the form of a list to obtain list data.

[0067] S20: Parse and process the list data to assemble it into a query condition expression.

[0068] The server parses the list data to analyze its hierarchical structure and then assembles it into a query expression suitable for the search engine.

[0069] Specifically, such as Figure 4 As shown, S20 in this embodiment specifically includes the following steps:

[0070] S21, traverse the list data and find the operator from the symbol characters; where the operator is used to indicate the business operation logic.

[0071] S22, based on the operators, assemble the condition strings into query condition expressions corresponding to the business operation logic.

[0072] The list is traversed to find the corresponding operator, which determines the corresponding business operation logic. Each database statement contains at least one operator, which determines the executable business operation logic corresponding to that database statement. Operators include arithmetic operators, aggregation operators, and logical combiners.

[0073] Each operator corresponds to a different operation logic. Therefore, the corresponding condition string can be assembled into a query condition expression that conforms to the business operation logic based on the operator. In other words, the operator is used to indicate what form of query operation should be performed on the query condition expression.

[0074] For example, the specific definition of this operation operator is shown in Table 1 below:

[0075] Table 1 Definition of Operators

[0076]

[0077] The specific definition of this aggregation operator is shown in Table 2 below:

[0078] Table 2 Definitions of Aggregation Operators

[0079] definition symbol illustrate definition symbol illustrate sum sum Sum of the right field total count Calculate the total of the right field mean avg Calculate the mean of the right field Enumeration value distinct Calculate the enumeration value of the right field Minimum value min Find the minimum value of the right field Maximum value max Find the maximum value of the right field

[0080] The specific definition of this logical combiner is shown in Table 3 below:

[0081] Table 3 Definition of Logical Combinators

[0082]

[0083] S30 converts the query condition expression into search engine code and generates a search engine code package based on the search engine code.

[0084] Furthermore, by converting the query condition expression into code that can be directly run on the search engine (i.e., search engine code), the corresponding query operation can be performed directly. During data transmission, the search engine code can be converted into a search engine code package for transmission and encapsulated within the search engine for easy self-invocation by the search engine.

[0085] In one implementation, such as Figure 5 As shown, S30, "converting the query condition expression into search engine code" specifically includes the following steps:

[0086] S31 sets the query time and filtering conditions, and uses aggregate functions supported by the search engine to set the aggregate fields.

[0087] S32 assembles the query time, filter conditions, and aggregation fields with the query condition expression to generate search engine code.

[0088] When generating search engine code, you can set information such as query time, filtering conditions, and aggregation fields. The query time is a predefined time limit for the execution of the query statement to be generated; its specific value is set according to actual needs and is not limited here.

[0089] Filtering conditions are set based on the operators and logical operators in the query expression. These conditions are used to filter data in the database during the execution of the generated query statement, thereby locating the required business data. The filtering conditions can be set according to actual needs and are not limited here.

[0090] Aggregate fields are fields that are aggregated based on the aggregation operators in the query condition expression, that is, aggregate fields are assembled into a single field.

[0091] Then, based on the corresponding operators in the query expression, the query time, filtering conditions, aggregation fields and query condition expressions are processed to generate the corresponding search engine code. This search engine code is directly applicable to the preset search engine, and the corresponding search results are obtained by executing the search engine code on the search engine.

[0092] It should be noted that this process is implemented according to the corresponding operators in the query condition expression. If the query condition expression contains any one or two operators, the corresponding code assembly process is executed according to those one or two operators. That is, the query condition expression does not necessarily contain all the operators, and therefore it is not necessary to assemble all the setting fields.

[0093] S40 receives the client's business logic query request, retrieves the search engine code from the search engine code package, and assembles it into a query statement corresponding to the business logic query request.

[0094] When a client needs to query, it can send a business logic query request. The server retrieves the corresponding search engine code from the search engine code based on the client's business logic query request. This search engine code is used to execute the query task through the search engine when the search engine code is running, thereby finding the corresponding business data.

[0095] Specifically, the business logic query request includes the query task to be executed and the query conditions. Based on the query conditions, the search engine code suitable for executing the query conditions can be obtained, and the executable query statement can be assembled according to the search engine code.

[0096] like Figure 6 As shown, this embodiment also specifically includes the following steps:

[0097] S51, Set the routing value, where the routing value is used to indicate the storage location information of the business data corresponding to the condition string in the query condition expression.

[0098] S52 adds route values ​​to the search engine code to generate search engine code containing route information.

[0099] In this embodiment, when setting the query time, filtering conditions, and aggregation fields, a routing value can also be set. This routing value indicates the storage location information of the business data that can be retrieved corresponding to the query condition expression. It can be understood that setting a routing value for the business data corresponding to the condition string in the query condition expression, and then adding the routing value to the search engine code, allows subsequent generation of query statements based on the search engine code containing the routing information.

[0100] Furthermore, embodiments of this application can also perform query processing on the business data indicated by the routing value in the query statement, and then use the business data as the result data returned after the query statement is executed.

[0101] In other words, when executing a query statement to perform a business logic query, the corresponding business data is found based on the routing value in the query statement, and then the business data is used as the result data returned by the query statement.

[0102] It is understandable that a query statement carrying a routing value can directly find the required business data based on the routing value, and then use it as the query result, thereby achieving fast retrieval of business data and improving search efficiency.

[0103] This application embodiment obtains the database statement to be parsed, inputs it into a search engine for format conversion processing to generate list data; parses the list data to assemble it into a query condition expression; converts the query condition expression into search engine code, and generates a search engine code package based on the search engine code; receives the client's business logic query request, obtains the search engine code from the search engine code package, and assembles it into a query statement corresponding to the business logic query request. This application embodiment improves query efficiency by converting the database statement into a query statement suitable for a search engine with a predetermined language system, thereby enabling the search engine to quickly retrieve the corresponding business data based on the query statement.

[0104] Please refer to Figure 7 This application provides a query statement generation apparatus, which includes:

[0105] The acquisition module 110 is used to acquire the database statement to be parsed, and input the database statement into the search engine for format conversion processing to generate list data;

[0106] The parsing module 120 is used to parse and process the list data to assemble it into a query condition expression;

[0107] The conversion module 130 is used to convert the query condition expression into search engine code and generate a search engine code package based on the search engine code.

[0108] The generation module 140 is used to receive the client's business logic query request, obtain the search engine code from the search engine code package, and assemble it into a query statement corresponding to the business logic query request.

[0109] The query statement generation device described above corresponds to the query statement generation method in the above embodiments; any of the options in the above embodiments are also applicable to this embodiment, and will not be described in detail here.

[0110] This application also provides a computer device, which includes a memory and at least one processor. The memory stores a computer program, and the processor executes the computer program to implement the query statement generation method of the above embodiments.

[0111] The memory may include a stored program area and a stored data area. The stored program area may store the operating system and application programs required for at least one function. The stored data area may store data created based on the use of the computer device (such as search engine code). In addition, the memory may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0112] This application also provides a computer storage medium storing computer-executable instructions. When the computer-executable instructions are invoked and executed by a processor, the computer-executable instructions cause the processor to perform the steps of the query statement generation method described in the above embodiments.

[0113] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that, in alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0114] In addition, the functional modules or units in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0115] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a smartphone, personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0116] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for generating query statements, characterized in that, include: Obtain the database statement to be parsed, and input the database statement into the search engine for format conversion processing to generate list data; wherein, the list data stores conditional strings and symbol characters; The list data is parsed and processed to assemble a query condition expression; The query condition expression is converted into search engine code, and a search engine code package is generated based on the search engine code; Receive a business logic query request from a client, obtain the search engine code from the search engine code package, and assemble it into a query statement corresponding to the business logic query request; The step of parsing the list data to assemble it into a query condition expression includes: traversing the list data and finding operators from the symbol characters; wherein the operators are used to indicate business operation logic; and assembling the condition string into a query condition expression corresponding to the business operation logic based on the operators. The step of converting the query condition expression into search engine code includes: setting the query time and filtering conditions, and setting aggregation fields using aggregation functions supported by the search engine; and assembling the query time, filtering conditions, and aggregation fields with the query condition expression to generate search engine code.

2. The query statement generation method according to claim 1, characterized in that, The step of inputting the database statement into the search engine for format conversion processing to generate list data includes: The database statement is split into key values ​​using a search engine to obtain condition strings and symbol characters. The condition string and the symbol character are stored in list form respectively to generate list data.

3. The query statement generation method according to claim 2, characterized in that, The step of storing the condition string and the symbol character in list form to generate list data includes: Find the left parenthesis character among the symbol characters, record the position information of the left parenthesis character in the database statement, and store the position information in the form of a stack; The condition string and the symbol characters that do not contain the left parenthesis character are stored in list form to generate list data.

4. The query statement generation method according to claim 1, characterized in that, The method further includes: Set a routing value, wherein the routing value is used to indicate the storage location information of the business data corresponding to the condition string in the query condition expression; Add the routing value to the search engine code to generate search engine code containing routing information.

5. The query statement generation method according to claim 1, characterized in that, After obtaining the search engine code from the search engine code package and assembling it into a query statement corresponding to the business logic query request, the method further includes: Based on the routing value in the query statement, the business data indicated by the routing value is queried and processed, and then the business data is used as the result data returned after the query statement is executed.

6. A query statement generation device, characterized in that, include: The acquisition module is used to acquire the database statement to be parsed, and input the database statement into the search engine for format conversion processing to generate list data; wherein, the list data stores condition strings and symbol characters; The parsing module is used to parse and process the list data to assemble it into a query condition expression; A conversion module is used to convert the query condition expression into search engine code and generate a search engine code package based on the search engine code; The generation module is used to receive the client's business logic query request, obtain the search engine code from the search engine code package, and assemble it into a query statement corresponding to the business logic query request. The parsing module is used to parse and process the list data to assemble it into a query condition expression, including: traversing the list data and finding operators from the symbol characters; wherein the operators are used to indicate business operation logic; and assembling the condition string into a query condition expression corresponding to the business operation logic based on the operators. The conversion module is used to convert the query condition expression into search engine code, including: setting the query time and filtering conditions, and setting the aggregation field using the aggregation function supported by the search engine; and assembling the query time, the filtering conditions, and the aggregation field with the query condition expression to generate search engine code.

7. A computer device, characterized in that, The computer device includes a memory and at least one processor, the memory storing a computer program, and the processor executing the computer program to implement the query statement generation method according to any one of claims 1-5.

8. A computer storage medium, characterized in that, It stores a computer program, which, when executed, implements the query statement generation method according to any one of claims 1-5.

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