Database statement conversion method and device, equipment and storage medium

Abstract

The invention discloses a database statement conversion method and device, equipment and a storage medium, and is applied to the field of databases. The method comprises the steps that a to-be-converted database statement of a to-be-converted database is acquired, the to-be-converted database statement is analyzed, and an abstract syntax tree of the to-be-converted database statement is acquired; setting an intermediate state data structure, traversing tree nodes of the abstract syntax tree, and converting the abstract syntax tree into an intermediate state statement under the intermediate state data structure; determining a target database dialect of the target database, and analyzing the clause of each intermediate state statement based on the target database dialect to obtain a clause analysis result; and splicing the parsed results of the clauses to obtain a target database statement of the target database. By providing the universal database statement analysis and conversion method, the problems of low efficiency and high error rate caused by manually writing different conversion scripts based on different database types to perform database conversion are avoided.

Description

Technical Field

[0001] The present invention relates to the field of databases, and in particular to a database statement conversion method, device, electronic equipment and computer-readable storage medium. Background Art

[0002] Data storage and processing have become an integral part of enterprise services. In order to effectively manage and access this data, relational databases have become the core middleware technology. However, as business grows and needs change, enterprises may choose database solutions from different database vendors or open source projects. Due to the different interpretations of SQL syntax by different database systems, syntax errors and performance issues may occur during database migration. The existing technology generally converts by manually writing corresponding database conversion scripts based on each database type. Manually writing conversion scripts relies on manual intervention, which is inefficient and has a high error rate. Especially when dealing with complex or large-scale database dialect conversions, the cost and time investment of this method are very high and cannot meet the rapidly changing market needs. Summary of the invention

[0003] The purpose of the present invention is to provide a database statement conversion method, device, electronic device and computer-readable storage medium, which are applied to the database field. The method avoids the problems of low efficiency and high error rate caused by manually writing different conversion scripts based on different database types for database conversion by providing a universal database statement parsing and conversion method.

[0004] In order to solve the above technical problems, the present invention provides a database statement conversion method, comprising: Obtaining a database statement to be converted of the database to be converted, parsing the database statement to be converted, and obtaining an abstract syntax tree of the database statement to be converted; Setting an intermediate state data structure, traversing the tree nodes of the abstract syntax tree, and converting the abstract syntax tree into an intermediate state statement under the intermediate state data structure; Determining a target database dialect of a target database, and parsing the clauses of each of the intermediate statements based on the target database dialect to obtain a clause parsing result; The parsing results of each of the clauses are concatenated to obtain a target database statement of the target database.

[0005] Optionally, parsing the database statement to be converted to obtain an abstract syntax tree of the database statement to be converted includes: Configure grammar files of various types of databases in ANTLR4, and determine the target grammar file of the database to be converted from the grammar files; The target grammar file is converted into execution code based on the antlr4-maven-plugin plug-in, and the database statement to be converted is subjected to lexical analysis, grammatical analysis and semantic analysis based on the execution code to obtain the abstract syntax tree.

[0006] Optionally, traversing tree nodes of the abstract syntax tree to convert the abstract syntax tree into an intermediate statement under the intermediate data structure includes: In the visitor mode of the ANTLR4, each tree node in the abstract syntax tree is traversed and visited; Recursively parse the statements in each of the tree nodes, disassemble the statements in the tree nodes, and convert them into the intermediate state statements under the intermediate state data structure.

[0007] Optionally, the determining a target database dialect of the target database, and parsing the clauses of each of the intermediate statements based on the target database dialect to obtain a clause parsing result, includes: Parsing the intermediate state sentence, and decomposing the intermediate state sentence into a plurality of the clauses; Constructing a database dialect dictionary; the database dialect dictionary encapsulates the parsing logic of multiple database dialects; Determining the target database dialect of the target database, and determining a target parsing logic from the database dialect dictionary based on the target database dialect; The clause of the intermediate state sentence is parsed based on the target parsing logic to obtain the clause parsing result.

[0008] Optionally, parsing the clause of the intermediate state sentence based on the target parsing logic to obtain the clause parsing result includes: Build parsers for various types of database languages; Determining a target parser from among the parsers based on the database language type of the intermediate statement; The clause in the intermediate state sentence is parsed based on the target parser to obtain the clause parsing result.

[0009] Optionally, parsing the clause in the intermediate state sentence based on the target parser to obtain the clause parsing result includes: Constructing a clause parsing method corresponding to the clause type in the parser; determining a target clause parsing method from the target parser based on the clause type of the clause; The clause in the intermediate sentence is parsed based on the target clause parsing method to obtain the clause parsing result.

[0010] Optionally, the intermediate data structure is in XML format or JSON format.

[0011] In order to solve the above technical problems, the present invention provides a database statement conversion device, comprising: The first module is used to obtain a database statement to be converted of a database to be converted, parse the database statement to be converted, and obtain an abstract syntax tree of the database statement to be converted; The second module is used to set an intermediate state data structure, traverse the tree nodes of the abstract syntax tree, and convert the abstract syntax tree into an intermediate state statement under the intermediate state data structure; The third module is used to determine the target database dialect of the target database, and parse the clauses of each of the intermediate statements based on the target database dialect to obtain a clause parsing result; The fourth module is used to splice the parsing results of each clause to obtain the target database statement of the target database.

[0012] In order to solve the above technical problems, the present invention provides an electronic device, comprising: Memory, for storing computer programs; A processor is used to implement the above-mentioned database statement conversion method when executing the computer program.

[0013] In order to solve the above technical problem, the present invention provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, the above-mentioned database statement conversion method is implemented.

[0014] It can be seen that the method of the present invention obtains the database statement to be converted of the database to be converted, parses the database statement to be converted, and obtains the abstract syntax tree of the database statement to be converted; sets an intermediate data structure, traverses the tree nodes of the abstract syntax tree, and converts the abstract syntax tree into intermediate statements under the intermediate data structure; determines the target database dialect of the target database, and parses the clauses of each intermediate statement based on the target database dialect to obtain the clause parsing result; and splices the clause parsing results to obtain the target database statement of the target database.

[0015] The method of the present invention sets a unified intermediate data structure, traverses the abstract syntax tree generated by the database statement to be converted, converts it into an intermediate statement, and converts the intermediate statement into a target database statement based on the target database dialect. By providing a universal database statement parsing and conversion method, the problem of low efficiency and high error rate caused by manually writing different conversion scripts based on different database types for database conversion is avoided. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0017] Figure 1 A flowchart of a database statement conversion method provided by an embodiment of the present invention; Figure 2 A structural block diagram of a database statement conversion device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] In today's data-driven world, data storage and processing have become an integral part of enterprise services. In order to effectively manage and access this data, relational databases have become the core middleware technology. However, as business grows and needs change, enterprises may choose database solutions from different database vendors or open source projects. Although these databases are all managed using SQL (Structured Query Language), they have extended the SQL syntax to meet specific needs, resulting in increasing syntax differences between different databases.

[0020] This difference becomes a major challenge when migrating or upgrading a database. For example, a company may need to migrate to another database system after using a certain database system for multiple iterations. Due to the different interpretations of SQL syntax by different database systems, direct migration will lead to syntax errors or performance issues. Therefore, a method that can understand and convert different database SQL syntax is needed to enable seamless migration and data exchange between different database systems. This technical problem is particularly prominent in enterprise-level applications because it is directly related to data reliability and system stability. As the amount of data grows and the complexity increases, it becomes more urgent to solve this problem in order to maintain the company's data processing capabilities and competitive advantage.

[0021] In the prior art, conversion between databases usually relies on manually writing conversion scripts or using some commercial tools. These methods mainly rely on experienced database administrators to have a deep understanding of the syntax differences between different databases. Although manually writing conversion scripts is flexible, it is inefficient and prone to errors. Although commercial tools have a high degree of automation, they can often only handle limited situations, and manual intervention is still required for complex SQL statement conversions. These technical defects make the prior art limited in processing conversion between databases and cannot meet the growing needs of data management and processing. Therefore, a more efficient and automated method is needed to solve these problems.

[0022] The following combination Figure 1 , Figure 1 A flowchart of a database statement conversion method provided by an embodiment of the present invention, the method may include: S101: Obtain a database statement to be converted of a database to be converted, parse the database statement to be converted, and obtain an abstract syntax tree of the database statement to be converted.

[0023] The Abstract Syntax Tree (AST) of a database statement is a tree-like data structure used to represent the grammatical structure of an SQL query statement.

[0024] This embodiment can obtain the database statement to be converted of the database to be converted, and parse the database statement to be converted to obtain the abstract syntax tree of the database statement to be converted. The database to be converted in this embodiment can be a database that needs to be migrated. This embodiment can migrate data from the database to be converted to a target database. This embodiment does not limit the specific types of the database to be converted and the target database, and can be set based on actual applications.

[0025] In the process of generating an abstract syntax tree, the present embodiment may first perform lexical analysis on the database statement to be converted, and decompose the database statement to be converted into multiple lexical units, such as keywords, identifiers, operators, and constants, etc. These lexical units are the basic components of SQL statements and provide a basis for subsequent syntax parsing and semantic analysis.

[0026] After the lexical analysis is completed, the syntax analysis can be performed. This step organizes the lexical units into an abstract syntax tree. The abstract syntax tree can represent the structure and hierarchical relationship of the SQL statement in detail. By analyzing the syntax tree, you can deeply understand the composition and grammatical rules of the SQL statement.

[0027] Furthermore, since different databases have different grammatical rules, in this embodiment, a database can be constructed based on the grammatical rules of the database to be converted to ensure the accuracy and compatibility of SQL statements. Through grammatical parsing, we can convert SQL statements into a structured grammar tree, which helps the subsequent query optimization and execution process.

[0028] After syntax parsing, the abstract syntax tree can also be semantically analyzed to verify the semantic correctness of the SQL statement and process it. The semantic analyzer traverses the syntax tree or its products to check whether the table name, field name, constraint conditions, etc. in the SQL statement exist and confirm whether they comply with the constraint rules of the database.

[0029] This embodiment does not limit the specific method of generating an abstract syntax tree. In a specific embodiment, ANTLR4 can be used to obtain an abstract syntax tree. ANTLR4 is a powerful parser generator that can generate parser code according to defined grammar rules. It defines language grammar in the g4 file format, which has a clear and easy-to-understand format, making it easier to write and maintain grammar rules. The abstract syntax tree structure generated using ANTLR4 clearly shows the various parts of the SQL statement and their relationships with each other. This structured representation makes it easier to understand and process SQL statements.

[0030] Specifically, first, the grammar files of various types of databases can be configured in ANTLR4, and the target grammar file of the database to be converted can be determined from the grammar file, that is, the target grammar file that conforms to the database type of the database to be converted can be selected from the grammar file. Based on the antlr4-maven-plugin plug-in, the target grammar file is converted into execution code, and the database statement to be converted is subjected to lexical parsing, grammatical parsing and semantic analysis based on the execution code to obtain the abstract syntax tree. antlr4-maven-plugin is a plug-in in ANTLR4, which is used to realize the generation of grammar file to parser code.

[0031] S102: Setting an intermediate state data structure, traversing the tree nodes of the abstract syntax tree, and converting the abstract syntax tree into an intermediate state statement under the intermediate state data structure.

[0032] Since the syntax tree is a structured representation, it clearly shows the various parts of the database statement (ie, SQL statement) and the relationships between them. After generating the abstract syntax tree, this embodiment can convert the database statement based on the abstract syntax tree.

[0033] This embodiment may set a general intermediate state data structure, traverse the tree nodes of the abstract syntax tree, and convert the abstract syntax tree into intermediate state statements under the intermediate state data structure.

[0034] This embodiment does not limit the specific method of converting the abstract syntax tree into intermediate statements. Generally, in the visitor mode of ANTLR4, each tree node in the abstract syntax tree can be traversed and visited; the statements in each tree node are recursively parsed, the statements in the tree nodes are disassembled, and converted into intermediate statements under the intermediate data structure.

[0035] Specifically, in this embodiment, the abstract syntax tree can be acquired and the intermediate statements can be converted through the parser engine SQLParserEngine and the observer engine SQLVisitorEngine in ANTLR4.

[0036] SQLParserEngine is the core component in ANTLR4 for parsing SQL statements and generating AST. It is responsible for converting the input SQL string into ANTLR's ParseTree object according to predefined grammar rules. SQLParserEngine will create the corresponding parser according to the database type and perform parsing operations.

[0037] In ANTLR4, SQLVisitorEngine is implemented based on the visitor pattern, which is used to traverse the generated AST and convert it into a format that can be understood by the application or perform specific operations. In this embodiment, the abstract syntax tree can be converted into an intermediate statement under an intermediate data structure based on SQLVisitorEngine.

[0038] This embodiment does not limit the specific type of intermediate statements, which can generally be general SQL statements, such as general SQL statements composed of basic SQL statements such as SELECT, FROM, WHERE, GROUP BY, ORDER BY and LIMIT. Furthermore, the intermediate data structure can also be in XML format or JSON format. XML is a markup language that allows users to define their own tags, so it has extremely high flexibility. JSON is an open standard file format and data exchange format that is easy for people to read and write, and is also easy for machines to parse and generate.

[0039] S103: Determine a target database dialect of the target database, and parse the clauses of each intermediate statement based on the target database dialect to obtain a clause parsing result.

[0040] S104: Connect the parsing results of each clause to obtain a target database statement of the target database.

[0041] This embodiment can determine the target database dialect of the target database, parse the clauses of each intermediate statement based on the target database dialect to obtain a clause parsing result, and finally concatenate the clause parsing results to obtain the target database statement of the target database.

[0042] Database dialect refers to the characteristics and syntax of a specific database system, the way it processes data and the rules for writing query statements. In different database systems, the syntax and characteristics may vary, and these differences are called database dialects.

[0043] This embodiment does not limit the specific method of parsing intermediate statements. Generally, the intermediate statements can be parsed and decomposed into multiple clauses; a database dialect dictionary is constructed; the database dialect dictionary encapsulates the parsing logic of multiple database dialects; the target database dialect of the target database is determined, and the target parsing logic is determined from the database dialect dictionary based on the target database dialect; the clauses of the intermediate statements are parsed based on the target parsing logic to obtain the clause parsing results.

[0044] Specifically, the intermediate statement can be decomposed into multiple clauses based on the type of the intermediate statement. Taking the SELECT statement as an example, it can be divided into clauses such as project segment (ProjectSegment), source segment (FromSegment) and LimitSegment (limit segment).

[0045] This embodiment can construct a database dialect dictionary. Generally, the database dialect dictionary encapsulates the parsing logic of multiple database dialects. This embodiment can parse the clauses of the intermediate state statement based on the data parsing logic corresponding to the target database.

[0046] Generally, under each parsing logic, parsers for various types of database languages ​​can be constructed. General database language types may include DML (Data Manipulation Language), DDL (Data Definition Language), DQL (Data Query Language) and DCL (Data Control Language), etc. Therefore, this embodiment can construct corresponding DDL parsers, DML parsers, DQL parsers and DCL parsers according to the database language type, which are respectively used to parse the corresponding types of intermediate statements.

[0047] Specifically, this embodiment can construct parsers for various types of database languages; determine a target parser from the parser based on the database language type of the intermediate statement; and parse the clauses in the intermediate statement based on the target parser to obtain a clause parsing result.

[0048] Since each database statement can be composed of one or more clauses, the clauses in the database statement are the basic components of the SQL query statement. Each clause plays a specific role in the query and defines different aspects of the query. Some common clauses include SELECT clause, FROM clause, WHERE clause, GROUP BY clause, HAVING clause and ORDER BY clause.

[0049] Since the parsers of different types of database languages ​​may contain different clause types, this embodiment can construct a clause parsing method corresponding to the clause type in the parser. Further, the target clause parsing method can be determined from the target parser based on the clause type of the clause obtained by decomposing the intermediate state statement; the clause in the intermediate state statement is parsed based on the target clause parsing method to obtain the clause parsing result. Finally, the clause parsing results are spliced ​​to obtain the target database statement of the target database.

[0050] In a specific embodiment, in ANTLR4, a Translator class can be designed for the conversion of intermediate statements. A data dialect dictionary is encapsulated in the translator to store dialect instances of different databases. The corresponding parsing logic is encapsulated in the dialect, and interfaces of various parsers (Compilers) are provided.

[0051] You can further set the SQLCompiler (SQL parser) class. The SQLCompiler class is an abstract interface that defines a compilerDispatch (parser distribution) method, which is used to dispatch intermediate statements to the corresponding parser for parsing.

[0052] In this embodiment, the intermediate statement can be a general Bean object parsed by the database to be converted, and can be further parsed according to the type of the database statement to be converted to obtain the clauses of the intermediate statement. In the Java programming language, Bean is a Java class that follows a specific convention, usually used to represent an entity object, which can be encapsulated, serialized and visualized.

[0053] In order to achieve recursive parsing of intermediate statements, this embodiment can set the visit method corresponding to the clause parsing method under each type of SQL parser, and customize a visitName for each type of clause, and select the corresponding visit method through visitName to parse the corresponding clause. In the SQLCompiler class, the compilerDispatch method is used to call the corresponding visit method according to the visitName of the clause to perform parsing and obtain the clause parsing result. In ANTLR4, the visit method is the key method used to traverse the parse tree, and visitName is a user-defined method used to process specific name or identifier nodes.

[0054] Based on the above embodiments, the method of the present invention sets a unified intermediate data structure, traverses the abstract syntax tree generated by the database statement to be converted, converts it into an intermediate statement, and converts the intermediate statement into a target database statement based on the target database dialect. By providing a universal database statement parsing and conversion method, the problem of low efficiency and high error rate caused by manually writing different conversion scripts based on different database types for database conversion is avoided.

[0055] The following combination Figure 2 , Figure 2 A structural block diagram of a database statement conversion device provided by an embodiment of the present invention, the device may include: The first module 100 is used to obtain a database statement to be converted of a database to be converted, parse the database statement to be converted, and obtain an abstract syntax tree of the database statement to be converted; The second module 200 is used to set an intermediate state data structure, traverse the tree nodes of the abstract syntax tree, and convert the abstract syntax tree into an intermediate state statement under the intermediate state data structure; The third module 300 is used to determine the target database dialect of the target database, and parse the clauses of each of the intermediate statements based on the target database dialect to obtain clause parsing results; The fourth module 400 is used to concatenate the parsing results of each of the clauses to obtain a target database statement of the target database.

[0056] Based on the above embodiments, the method of the present invention sets a unified intermediate data structure, traverses the abstract syntax tree generated by the database statement to be converted, converts it into an intermediate statement, and converts the intermediate statement into a target database statement based on the target database dialect. By providing a universal database statement parsing and conversion method, the problem of low efficiency and high error rate caused by manually writing different conversion scripts based on different database types for database conversion is avoided.

[0057] Based on the above embodiment, the first module 100 may include: The first submodule is used to configure the grammar files of various types of databases in ANTLR4, and determine the target grammar file of the database to be converted from the grammar files; The second submodule is used to convert the target grammar file into execution code based on the antlr4-maven-plugin plug-in, and perform lexical analysis, grammatical analysis and semantic analysis on the database statement to be converted based on the execution code to obtain the abstract syntax tree.

[0058] Based on the above embodiments, the second module 200 may include: A third submodule is used for traversing and accessing each of the tree nodes in the abstract syntax tree in the visitor mode of the ANTLR4; The fourth submodule is used to recursively parse the statements in each of the tree nodes, disassemble the statements in the tree nodes, and convert them into the intermediate state statements under the intermediate state data structure.

[0059] Based on the above embodiments, the third module 300 may include: A fifth submodule, configured to parse the intermediate state sentence and decompose the intermediate state sentence into a plurality of clauses; The sixth submodule is used to construct a database dialect dictionary; the database dialect dictionary encapsulates the parsing logic of multiple database dialects; A seventh submodule is used to determine the target database dialect of the target database, and determine a target parsing logic from the database dialect dictionary based on the target database dialect; An eighth submodule is used to parse the clause of the intermediate state sentence based on the target parsing logic to obtain the clause parsing result.

[0060] Based on the above embodiments, the eighth submodule may include: Unit 1 is used to build parsers for various types of database languages; A second unit is used to determine a target parser from the parsers based on the database language type of the intermediate statement; The third unit is used to parse the clause in the intermediate state sentence based on the target parser to obtain the clause parsing result.

[0061] Based on the above embodiments, the third unit may include: A first subunit is used to construct a clause parsing method corresponding to the clause type in the parser; A second subunit, configured to determine a target clause parsing method from the target parser based on the clause type of the clause; The third subunit is used to parse the clause in the intermediate sentence based on the target clause parsing method to obtain the clause parsing result.

[0062] Based on the above embodiments, the intermediate data structure is in XML format or JSON format.

[0063] Based on the above embodiments, the present invention further provides an electronic device, which may include a memory and a processor, wherein the memory stores a computer program, and when the processor calls the computer program in the memory, the steps provided in the above embodiments may be implemented. Of course, the device may also include various necessary network interfaces, power supplies, and other components.

[0064] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by an execution terminal or a processor, the method provided in the embodiment of the present invention can be implemented; the storage medium may include: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

[0065] In this article, relational terms such as first and second, etc. are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

Claims

1. A database statement conversion method, characterized in that: include: Obtaining a database statement to be converted of the database to be converted, parsing the database statement to be converted, and obtaining an abstract syntax tree of the database statement to be converted; Setting an intermediate state data structure, traversing the tree nodes of the abstract syntax tree, and converting the abstract syntax tree into an intermediate state statement under the intermediate state data structure; Determining a target database dialect of a target database, and parsing the clauses of each of the intermediate statements based on the target database dialect to obtain a clause parsing result; The parsing results of each of the clauses are concatenated to obtain a target database statement of the target database.

2. The database statement conversion method according to claim 1, characterized in that: Parsing the database statement to be converted to obtain an abstract syntax tree of the database statement to be converted includes: Configure grammar files of various types of databases in ANTLR4, and determine the target grammar file of the database to be converted from the grammar files; The target grammar file is converted into execution code based on the antlr4-maven-plugin plug-in, and the database statement to be converted is subjected to lexical analysis, grammatical analysis and semantic analysis based on the execution code to obtain the abstract syntax tree.

3. The database statement conversion method according to claim 2, characterized in that: Traversing the tree nodes of the abstract syntax tree and converting the abstract syntax tree into an intermediate state statement under the intermediate state data structure includes: In the visitor mode of the ANTLR4, each tree node in the abstract syntax tree is traversed and visited; Recursively parse the statements in each of the tree nodes, disassemble the statements in the tree nodes, and convert them into the intermediate state statements under the intermediate state data structure.

4. The database statement conversion method according to claim 1, characterized in that: The determining a target database dialect of the target database, and parsing the clauses of each of the intermediate statements based on the target database dialect to obtain a clause parsing result, includes: Parsing the intermediate state sentence, and decomposing the intermediate state sentence into a plurality of the clauses; Constructing a database dialect dictionary; the database dialect dictionary encapsulates the parsing logic of multiple database dialects; Determining the target database dialect of the target database, and determining a target parsing logic from the database dialect dictionary based on the target database dialect; The clause of the intermediate state sentence is parsed based on the target parsing logic to obtain the clause parsing result.

5. The database statement conversion method according to claim 4, characterized in that: Parsing the clause of the intermediate state sentence based on the target parsing logic to obtain the clause parsing result includes: Build parsers for various types of database languages; Determining a target parser from among the parsers based on the database language type of the intermediate statement; The clause in the intermediate state sentence is parsed based on the target parser to obtain the clause parsing result.

6. The database statement conversion method according to claim 5, characterized in that: Parsing the clause in the intermediate state sentence based on the target parser to obtain the clause parsing result includes: Constructing a clause parsing method corresponding to the clause type in the parser; determining a target clause parsing method from the target parser based on the clause type of the clause; The clause in the intermediate sentence is parsed based on the target clause parsing method to obtain the clause parsing result.

7. The database statement conversion method according to claim 1, characterized in that: The intermediate data structure is in XML format or JSON format.

8. A database statement conversion device, characterized in that: include: The first module is used to obtain a database statement to be converted of a database to be converted, parse the database statement to be converted, and obtain an abstract syntax tree of the database statement to be converted; The second module is used to set an intermediate state data structure, traverse the tree nodes of the abstract syntax tree, and convert the abstract syntax tree into an intermediate state statement under the intermediate state data structure; The third module is used to determine the target database dialect of the target database, and parse the clauses of each of the intermediate statements based on the target database dialect to obtain a clause parsing result; The fourth module is used to splice the parsing results of each clause to obtain the target database statement of the target database.

9. An electronic device, characterized in that: include: Memory, for storing computer programs; A processor, configured to implement the database statement conversion method as claimed in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, the database statement conversion method according to any one of claims 1 to 7 is implemented.

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