CN112860730A - SQL statement processing method and device, electronic equipment and readable storage medium - Google Patents
SQL statement processing method and device, electronic equipment and readable storage medium Download PDFInfo
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- CN112860730A CN112860730A CN202110336670.0A CN202110336670A CN112860730A CN 112860730 A CN112860730 A CN 112860730A CN 202110336670 A CN202110336670 A CN 202110336670A CN 112860730 A CN112860730 A CN 112860730A
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/242—Query formulation
- G06F16/2433—Query languages
- G06F16/2438—Embedded query languages
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2455—Query execution
- G06F16/24553—Query execution of query operations
Abstract
The embodiment of the application provides a method and a device for processing an SQL statement, electronic equipment and a readable storage medium. The method comprises the following steps: when an SQL statement is received through a preset SQL channel, generating a query execution plan based on the SQL statement; creating a plurality of concurrently executable query tasks based on the query execution plan; and processing each query task respectively. Based on the scheme, the query efficiency based on the SQL statement can be improved, so that high-performance data query service is provided for various data application systems.
Description
Technical Field
The present application relates to the field of data processing technologies, and in particular, to a method and an apparatus for processing an SQL statement, an electronic device, and a readable storage medium.
Background
Structured Query Language (SQL) is a standard computer Language for accessing and processing databases, for accessing data and querying, updating, and managing database systems.
With the rapid development of big data technology, how to quickly and efficiently query the required data from the big data is more and more important. At present, when data query is carried out by taking SQL sentences as query commands, the query efficiency is relatively general, and high-performance data query service cannot be provided for various data application systems.
Disclosure of Invention
The present application aims to solve at least one of the above technical drawbacks. The technical scheme adopted by the application is as follows:
in a first aspect, an embodiment of the present application provides a method for processing an SQL statement, where the method includes:
when an SQL statement is received through a preset SQL channel, generating a query execution plan based on the SQL statement;
creating a plurality of concurrently executable query tasks based on the query execution plan;
and processing each query task respectively.
Optionally, creating a plurality of concurrently executable query tasks based on the query execution plan comprises:
splitting the query execution plan into a plurality of query execution phases;
the query execution phase is split into multiple query tasks.
Optionally, each query execution stage is configured with an execution hierarchy, and processes each query task separately, including:
and processing the query tasks of the query execution stages in sequence according to the execution level.
Optionally, generating the query execution plan based on the SQL statement includes:
analyzing the SQL statement;
and generating a query execution plan based on the analysis result of the SQL statement.
Optionally, generating a query execution plan based on the parsing result of the SQL statement, including:
generating an abstract syntax tree based on the analysis result of the SQL statement;
generating a query execution based on the abstract syntax tree;
determining description information of a column in a corresponding SQL statement when query execution is executed;
generating a logic execution plan based on the description information;
and generating a query execution plan based on the optimization result of the logic execution plan.
Optionally, the method further includes:
after generating the query execution, the query execution is added to the query execution queue.
Optionally, the method further includes:
and after the query task processing of each query execution stage is finished, outputting the processing result of the summarized query task through an SQL channel.
Optionally, the method further includes:
and caching the processing result.
In a second aspect, an embodiment of the present application provides an apparatus for processing an SQL statement, where the apparatus includes:
the execution plan generating module is used for generating a query execution plan based on the SQL statement when the SQL statement is received through a preset SQL channel;
the query task creating module is used for creating a plurality of query tasks which can be executed in parallel based on the query execution plan;
and the query task processing module is used for respectively processing each query task.
Optionally, the query task creating module is specifically configured to:
splitting the query execution plan into a plurality of query execution phases;
the query execution phase is split into multiple query tasks.
Optionally, each query execution phase is configured with an execution hierarchy, and the query task processing module is specifically configured to:
and processing the query tasks of the query execution stages in sequence according to the execution level.
Optionally, when the execution plan generation module generates the query execution plan based on the SQL statement, the execution plan generation module is specifically configured to:
analyzing the SQL statement;
and generating a query execution plan based on the analysis result of the SQL statement.
Optionally, when the execution plan generation module generates the query execution plan based on the analysis result of the SQL statement, the execution plan generation module is specifically configured to:
generating a query execution based on the abstract syntax tree;
determining description information of a column in a corresponding SQL statement when query execution is executed;
generating a logic execution plan based on the description information;
and generating a query execution plan based on the optimization result of the logic execution plan.
Optionally, the apparatus further comprises:
and the query execution queue module is used for adding the query execution to the query execution queue after generating the query execution.
Optionally, the apparatus further comprises:
and the processing result output module is used for outputting the processing result of the summarized query task through the SQL channel after the query task at each query execution stage is processed.
Optionally, the apparatus further comprises:
and the cache module is used for caching the processing result.
In a third aspect, an embodiment of the present application provides an electronic device, including: a processor and a memory;
a memory for storing operating instructions;
a processor, configured to execute the processing method of the SQL statement as shown in any of the embodiments of the first aspect of the present application by calling an operation instruction.
In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the processing method of the SQL statement shown in any one of the implementation manners of the first aspect of the present application.
The technical scheme provided by the embodiment of the application has the following beneficial effects:
according to the scheme provided by the embodiment of the application, when the SQL statement is received through the preset SQL channel, the query execution plan is generated based on the SQL statement, and a plurality of query tasks capable of being executed in parallel are created based on the query execution plan, so that the query tasks are processed respectively. Based on the scheme, the query efficiency based on the SQL statement can be improved, so that high-performance data query service is provided for various data application systems.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings used in the description of the embodiments of the present application will be briefly described below.
Fig. 1 is a schematic flowchart of a processing method of an SQL statement according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a processing apparatus for SQL statements provided in an embodiment of the present application;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary only for the purpose of explaining the present application and are not to be construed as limiting the present invention.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or wirelessly coupled. As used herein, the term "and/or" includes all or any element and all combinations of one or more of the associated listed items.
To make the objects, technical solutions and advantages of the present application more clear, embodiments of the present application will be described in further detail below with reference to the accompanying drawings.
The following describes the technical solutions of the present application and how to solve the above technical problems with specific embodiments. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.
Fig. 1 shows a schematic flow diagram of a processing method of an SQL statement provided in an embodiment of the present application, and as shown in fig. 1, the method mainly includes:
step S110: when an SQL statement is received through a preset SQL channel, generating a query execution plan based on the SQL statement;
step S120: creating a plurality of concurrently executable query tasks based on the query execution plan;
step S130: and processing each query task respectively.
In the embodiment of the application, the SQL channel can be provided for inputting the SQL statement and outputting the query result. The SQL channel may be an HTTP network interface using the RESTful style. RESTful is a design style and development approach for web applications, HTTP is a request-response protocol, is based on a client/server model, and is connection-oriented.
In the embodiment of the application, the SQL statement can be checked. Specifically, when the SQL statement is received through the SQL channel, the validity check of the SQL statement is performed to check whether the syntax of the SQL query statement meets the SQL syntax rules of the ANSI database management standard, and if the syntax rule is not met, corresponding error information is generated and returned through the SQL channel, and the subsequent processing procedure is omitted. After the SQL statement validity check is passed, the language meaning can be checked, whether the contents of fields, tables and the like in the SQL statement actually exist or not is checked, if not, corresponding error information is generated and returned through the SQL channel, and the subsequent processing process is omitted.
In the embodiment of the application, after the SQL statement check is passed, the SQL statement can be analyzed to generate the query execution plan, and the query execution plan is divided into a plurality of query tasks. The plurality of query tasks may be performed independently from each other.
The preset SQL channel is provided for receiving the SQL statement and outputting the query result, and the query execution plan generated based on the SQL statement is divided into a plurality of query tasks which are respectively and independently executed, so that the query efficiency based on the SQL statement can be improved.
According to the method provided by the embodiment of the application, when the SQL statement is received through the preset SQL channel, the query execution plan is generated based on the SQL statement, and a plurality of query tasks capable of being executed in parallel are created based on the query execution plan, so that the query tasks are processed respectively. Based on the scheme, the query efficiency based on the SQL statement can be improved, so that high-performance data query service is provided for various data application systems.
In an optional mode of the embodiment of the present application, creating a plurality of query tasks that can be executed in parallel based on a query execution plan includes:
splitting the query execution plan into a plurality of query execution phases;
the query execution phase is split into multiple query tasks.
In the embodiment of the application, the query execution plan can be segmented and split into a plurality of query execution stages, and the execution level of each query execution stage is configured. Each query execution stage represents a portion of a query execution plan. The query execution stages are in a tree-like hierarchical structure, and each query execution stage is provided with a root query execution stage which is used for aggregating output data of all other query execution stages and returning final data to the SQL channel.
As one example, a query execution plan may be split into 3 query execution phases: source phase, fixed phase, and single phase. Wherein, the source phase is a phase of reading data from a table of a data source; the fixed stage is positioned behind the source stage, the data read by the source stage are dispersed to a plurality of nodes for processing, and the main processing operations comprise local aggregation and local join; and the single stage is positioned after the fixed stage and used for summarizing all processing results, for example, performing final aggregation on the results of local aggregation.
In an optional manner of the embodiment of the present application, each query execution stage is configured with an execution hierarchy, and processes each query task respectively, where the execution hierarchy includes:
and processing the query tasks of the query execution stages in sequence according to the execution level.
In this embodiment of the present application, the query execution stages may be sequentially processed according to the execution hierarchy, and after the query task in the query execution stage of the previous execution hierarchy is executed, the query task in the query execution stage of the next execution hierarchy is processed.
As an example, the processing of the query task in the fixed phase is performed after the processing of the query task in the source phase is completed, and the processing of the query task in the single phase is performed after the processing of the query task in the fixed phase is completed.
In actual use, the execution state of each query task can be monitored, and the query tasks with errors in execution can be rescheduled for execution.
The query execution plan is divided into query execution stages, and the query tasks in the query execution stages are sequentially executed respectively, so that the query tasks are sequentially scheduled, result data obtained by independently executing a plurality of query tasks are collected and summarized to form final query result data, and the final query result data is returned through an SQL channel.
In an optional manner of the embodiment of the present application, generating a query execution plan based on an SQL statement includes:
analyzing the SQL statement;
and generating a query execution plan based on the analysis result of the SQL statement.
In the embodiment of the application, the query execution plan can be generated according to the analysis result of the SQL statement.
Specifically, the generating of the query execution plan based on the analysis result of the SQL statement includes:
generating an abstract syntax tree based on the analysis result of the SQL statement;
generating a query execution based on the abstract syntax tree;
determining description information of a column in a corresponding SQL statement when query execution is executed;
generating a logic execution plan based on the description information;
and generating a query execution plan based on the optimization result of the logic execution plan.
In the embodiment of the application, the SQL statement can be received, lexical and syntactic analysis can be performed on the statement, an abstract syntax tree is generated according to the analysis result, each Node in the syntax tree is a Node, and the Node is a part of the SQL statement.
Query executions (QueryExecution) are generated for starting, stopping and managing a query based on the abstract syntax tree. Different types of SQL statements may generate different queryexecutions.
When the query execution is executed, firstly, the semantic analyzer is used for carrying out semantic analysis on the SQL corresponding to the query execution, and the analysis output result is the description information of the column output in the SQL statement.
The logic planner generates a logic execution plan based on the result of the semantic analysis (i.e., the description information). The logical execution plan is a tree structure, consisting of a series of nodes of different types, such as aggregation nodes (aggregations nodes).
The logical execution plan is optimized, for example, to change if statements to case where statements. And generating a query execution plan according to the optimization result of the logic execution plan.
In an optional manner of the embodiment of the present application, the method further includes:
after generating the query execution, the query execution is added to the query execution queue.
In the embodiment of the present application, query execution may be added to a query execution queue, and the query execution queue is scheduled in a First-in First-out (FIFO) manner.
In an optional manner of the embodiment of the present application, the method further includes:
and after the query task processing of each query execution stage is finished, outputting the processing result of the summarized query task through an SQL channel.
In the embodiment of the application, the processing results of the query tasks can be collected and returned through the SQL channel.
In an optional manner of the embodiment of the present application, the method further includes:
and caching the processing result.
In the embodiment of the present application, after the processing of the SQL statement is completed to obtain the processing result, the processing result may be cached, specifically, the processing result may be cached in a cache, where the cache is a section of memory space in a computer and is used to store the processing result of the executed SQL statement before. If the processing result corresponding to the SQL statement received through the SQL channel exists in the cache, the subsequent processing process is omitted, the result data is directly obtained from the cache, and the processing result is returned through the SQL channel.
Based on the same principle as the method shown in fig. 1, fig. 2 shows a schematic structural diagram of a processing apparatus of an SQL statement provided in an embodiment of the present application, and as shown in fig. 2, the processing apparatus 20 of the SQL statement may include:
an execution plan generating module 210, configured to generate a query execution plan based on the SQL statement when the SQL statement is received through a preset SQL channel;
a query task creation module 220 for creating a plurality of query tasks that can be executed in parallel based on the query execution plan;
and the query task processing module 230 is configured to process each query task.
According to the device provided by the embodiment of the application, when the SQL statement is received through the preset SQL channel, the query execution plan is generated based on the SQL statement, and a plurality of query tasks capable of being executed in parallel are created based on the query execution plan, so that the query tasks are processed respectively. Based on the scheme, the query efficiency based on the SQL statement can be improved, so that high-performance data query service is provided for various data application systems.
Optionally, the query task creating module is specifically configured to:
splitting the query execution plan into a plurality of query execution phases;
the query execution phase is split into multiple query tasks.
Optionally, each query execution phase is configured with an execution hierarchy, and the query task processing module is specifically configured to:
and processing the query tasks of the query execution stages in sequence according to the execution level.
Optionally, when the execution plan generation module generates the query execution plan based on the SQL statement, the execution plan generation module is specifically configured to:
analyzing the SQL statement;
and generating a query execution plan based on the analysis result of the SQL statement.
Optionally, when the execution plan generation module generates the query execution plan based on the analysis result of the SQL statement, the execution plan generation module is specifically configured to:
generating a query execution based on the abstract syntax tree;
determining description information of a column in a corresponding SQL statement when query execution is executed;
generating a logic execution plan based on the description information;
and generating a query execution plan based on the optimization result of the logic execution plan.
Optionally, the apparatus further comprises:
and the query execution queue module is used for adding the query execution to the query execution queue after generating the query execution.
Optionally, the apparatus further comprises:
and the processing result output module is used for outputting the processing result of the summarized query task through the SQL channel after the query task at each query execution stage is processed.
Optionally, the apparatus further comprises:
and the cache module is used for caching the processing result.
It is understood that the above modules of the processing apparatus of the SQL statement in the present embodiment have functions of implementing the corresponding steps of the processing method of the SQL statement in the embodiment shown in fig. 1. The function can be realized by hardware, and can also be realized by executing corresponding software by hardware. The hardware or software includes one or more modules corresponding to the functions described above. The modules can be software and/or hardware, and each module can be implemented independently or by integrating a plurality of modules. For the functional description of each module of the SQL statement processing apparatus, reference may be specifically made to the corresponding description of the processing method of the SQL statement in the embodiment shown in fig. 1, and details are not repeated here.
The embodiment of the application provides an electronic device, which comprises a processor and a memory;
a memory for storing operating instructions;
and the processor is used for executing the SQL statement processing method provided by any embodiment of the application by calling the operation instruction.
As an example, fig. 3 shows a schematic structural diagram of an electronic device to which an embodiment of the present application is applicable, and as shown in fig. 3, the electronic device 2000 includes: a processor 2001 and a memory 2003. Wherein the processor 2001 is coupled to a memory 2003, such as via a bus 2002. Optionally, the electronic device 2000 may also include a transceiver 2004. It should be noted that the transceiver 2004 is not limited to one in practical applications, and the structure of the electronic device 2000 is not limited to the embodiment of the present application.
The processor 2001 is applied to the embodiment of the present application to implement the method shown in the above method embodiment. The transceiver 2004 may include a receiver and a transmitter, and the transceiver 2004 is applied to the embodiments of the present application to implement the functions of the electronic device of the embodiments of the present application to communicate with other devices when executed.
The Processor 2001 may be a CPU (Central Processing Unit), general Processor, DSP (Digital Signal Processor), ASIC (Application Specific Integrated Circuit), FPGA (Field Programmable Gate Array) or other Programmable logic device, transistor logic device, hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. The processor 2001 may also be a combination of computing functions, e.g., comprising one or more microprocessors, DSPs and microprocessors, and the like.
The Memory 2003 may be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical Disc storage, optical Disc storage (including Compact Disc, laser Disc, optical Disc, digital versatile Disc, blu-ray Disc, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to these.
Optionally, the memory 2003 is used for storing application program code for performing the disclosed aspects, and is controlled in execution by the processor 2001. The processor 2001 is configured to execute the application program code stored in the memory 2003 to implement the method for processing the SQL statement provided in any of the embodiments of the present application.
The electronic device provided by the embodiment of the application is applicable to any embodiment of the method, and is not described herein again.
Compared with the prior art, when an SQL statement is received through a preset SQL channel, a query execution plan is generated based on the SQL statement, a plurality of query tasks capable of being executed in parallel are created based on the query execution plan, and therefore all the query tasks are processed respectively. Based on the scheme, the query efficiency based on the SQL statement can be improved, so that high-performance data query service is provided for various data application systems.
The embodiment of the present application provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements the processing method of the SQL statement shown in the foregoing method embodiment.
The computer-readable storage medium provided in the embodiments of the present application is applicable to any of the embodiments of the foregoing method, and is not described herein again.
Compared with the prior art, when an SQL statement is received through a preset SQL channel, a query execution plan is generated based on the SQL statement, a plurality of query tasks capable of being executed in parallel are created based on the query execution plan, and therefore all the query tasks are processed respectively. Based on the scheme, the query efficiency based on the SQL statement can be improved, so that high-performance data query service is provided for various data application systems.
It should be understood that, although the steps in the flowcharts of the figures 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 may be performed in other orders unless explicitly stated herein. Moreover, at least a portion of the steps in the flow chart of the figure may include multiple sub-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 a portion of the sub-steps or stages of other steps.
The foregoing is only a partial embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (11)
1. A method for processing SQL statements is characterized by comprising the following steps:
when an SQL statement is received through a preset SQL channel, generating a query execution plan based on the SQL statement;
creating a plurality of concurrently executable query tasks based on the query execution plan;
and processing each query task respectively.
2. The method of claim 1, wherein creating a plurality of concurrently executable query tasks based on the query execution plan comprises:
splitting the query execution plan into a plurality of query execution phases;
splitting the query execution phase into a plurality of query tasks.
3. The method of claim 2, wherein each of the query execution stages is configured with an execution hierarchy, and wherein processing each of the query tasks separately comprises:
and processing the query tasks of the query execution stages in sequence according to the execution hierarchy.
4. The method of claim 1, wherein generating a query execution plan based on the SQL statement comprises:
analyzing the SQL statement;
and generating a query execution plan based on the analysis result of the SQL statement.
5. The method of claim 4, wherein generating a query execution plan based on the parsed result of the SQL statement comprises:
generating an abstract syntax tree based on the analysis result of the SQL statement;
generating a query execution based on the abstract syntax tree;
determining description information of a column in the corresponding SQL statement when the query execution is executed;
generating a logic execution plan based on the description information;
and generating a query execution plan based on the optimization result of the logic execution plan.
6. The method of claim 5, further comprising:
after generating the query execution, adding the query execution to a query execution queue.
7. The method of claim 2, further comprising:
and after the query task processing of each query execution stage is finished, outputting the summarized processing result of the query task through the SQL channel.
8. The method of claim 7, further comprising:
and caching the processing result.
9. An apparatus for processing an SQL statement, comprising:
the execution plan generating module is used for generating a query execution plan based on the SQL statement when the SQL statement is received through a preset SQL channel;
the query task creating module is used for creating a plurality of query tasks which can be executed in parallel based on the query execution plan;
and the query task processing module is used for respectively processing each query task.
10. An electronic device comprising a processor and a memory;
the memory is used for storing operation instructions;
the processor is used for executing the method of any one of claims 1-8 by calling the operation instruction.
11. A computer-readable storage medium, characterized in that the storage medium has stored thereon a computer program which, when being executed by a processor, carries out the method of any one of claims 1-8.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113392123A (en) * | 2021-06-10 | 2021-09-14 | 中国光大银行股份有限公司 | SQL statement processing method and device |
| CN113392252A (en) * | 2021-06-01 | 2021-09-14 | 上海徐毓智能科技有限公司 | Data processing method and device |
| CN114328595A (en) * | 2021-11-30 | 2022-04-12 | 苏州浪潮智能科技有限公司 | Data query method and device, electronic equipment and storage medium |
| WO2024046015A1 (en) * | 2022-08-29 | 2024-03-07 | 支付宝(杭州)信息技术有限公司 | Data query method and apparatus, storage medium, and electronic device |
-
2021
- 2021-03-29 CN CN202110336670.0A patent/CN112860730A/en active Pending
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113392252A (en) * | 2021-06-01 | 2021-09-14 | 上海徐毓智能科技有限公司 | Data processing method and device |
| CN113392123A (en) * | 2021-06-10 | 2021-09-14 | 中国光大银行股份有限公司 | SQL statement processing method and device |
| CN114328595A (en) * | 2021-11-30 | 2022-04-12 | 苏州浪潮智能科技有限公司 | Data query method and device, electronic equipment and storage medium |
| CN114328595B (en) * | 2021-11-30 | 2024-01-09 | 苏州浪潮智能科技有限公司 | Data query method and device, electronic equipment and storage medium |
| WO2024046015A1 (en) * | 2022-08-29 | 2024-03-07 | 支付宝(杭州)信息技术有限公司 | Data query method and apparatus, storage medium, and electronic device |
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