Data analysis method based on zero code and computer equipment

Abstract

The invention relates to the technical field of data analysis, and discloses a data analysis method based on zero codes, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: S1, acquiring an operator, connecting the operator with output data of a father node, and generating a current data node; s2, configuring parameters of the current data node based on the output data of the father node; s3, performing automatic debugging analysis on the current data node, generating output data of the current data node, and determining whether the output data of the current data node is valid data or not; s4, if the data are valid data, the current data node completes data analysis; if the output data is invalid data, the current data node returns to the step S2 to reconfigure the parameters of the current data node until the output data of the current data node is valid data; and S5, after the current data node completes data analysis, continuing to execute according to the steps S1-S4. By adopting the method, the data analysis efficiency can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of data analysis, and more specifically, to a zero-code based data analysis method, a computer device, a computer-readable storage medium, and a computer program product. Background Art

[0002] In recent years, as the importance and status of big data in various industries continue to increase, higher business demands have been placed on the in-depth application of big data. How to fully tap the value of data, lower the threshold for business personnel to use data analysis, and reduce the time and labor costs of data analysis have become the main issues facing the data analysis field.

[0003] At present, data analysis methods based on interactive modeling are usually used. With this method, users can create, edit and manage big data models more intuitively and conveniently through interface interaction. By dragging and dropping data elements and calculation components, complex data models can be easily constructed, and the relationships and behaviors between models can be defined. This visual modeling method not only simplifies the modeling process, but also allows non-technical personnel to participate in data analysis and decision-making.

[0004] The patent application document with publication number CN116339600A discloses an interactive modeling big data governance service method and system, which includes obtaining a big data model, wherein the big data model includes at least a data unit and a target data unit, the data unit and the target data unit represent two related units in the data processing flow, and the data unit and the target data unit are graphical interfaces respectively; obtaining an operator that establishes a logical connection between the data unit and the target data unit; in the big data model, dragging the data unit and the target data unit to the editing interface in turn, and connecting the data unit and the target data unit through a directional line, wherein the line represents the operator. Through simple side dragging operations and line connections, a data processing flow can be established, such as generating a service API and an analysis report.

[0005] Although the above interactive modeling big data governance service method can realize the interactive modeling process, it is impossible to debug the model parameters in real time during the data processing process, so it is impossible to find invalid parameter configurations in time, and then make the invalid configurations participate in the entire data flow. The invalid configuration here does not include wrong parameter configurations, but only refers to the situation where the data obtained by data analysis after parameter configuration is empty. When users find invalid data, they need to gradually check the nodes of data processing to adjust the parameter configuration. This operation is time-consuming and reduces the efficiency of data analysis. Summary of the invention

[0006] In order to solve the problem of how to improve the efficiency of data analysis, the present invention provides a zero-code based data analysis method, a computer device, a computer-readable storage medium and a computer program product, which can improve the efficiency of data analysis.

[0007] To achieve the above object, according to a first aspect of the present invention, a data analysis method based on zero code is provided, the method comprising:

[0008] S1, obtain the operator, connect the operator with the output data of the parent node, generate the current data node, and the parent node is the starting data node or the target data node;

[0009] S2, configure the parameters of the current data node based on the output data of the parent node;

[0010] S3, automatically debugging and analyzing the current data node, generating output data of the current data node, and determining whether the output data of the current data node is valid data;

[0011] S4, if the data is valid, the current data node completes data analysis; if the data is invalid, the current data node outputs an error message, or returns to step S2 to reconfigure the parameters of the current data node until the output data of the current data node is valid data;

[0012] S5, after the current data node completes data analysis, continue to execute according to the above steps S1-S4.

[0013] Furthermore, the above-mentioned zero-code-based data analysis method also includes acquiring data resources and generating a starting data node; preprocessing the data resources to obtain output data of the starting data node.

[0014] Furthermore, operators include intersection, difference, full join, left join, adding fields, table structure processing, data filtering, string processing, date processing, data deduplication, column calculation or group statistics.

[0015] Furthermore, the attributes of the data node include a unique identifier, a category identification field, a category name, a node name, an array object containing the unique identifier of the parent node, input data, output data and a parameter configuration object, the input data includes an input table name and input table field information, the output data includes an output table name and output table field information; the above-mentioned zero-code-based data analysis method also includes obtaining an operation instruction selected by the user through an input device, the operation instruction includes copying, deleting, parameter configuration, and viewing, and copying, deleting, parameter configuring or viewing the data node according to the operation instruction.

[0016] Furthermore, the current data node is automatically debugged and analyzed, and the output data of the current data node is generated, including automatically calling a data analysis service module, and judging whether the parameter configuration of the current data node is correct through the data analysis service module. If the parameter configuration is wrong, a parameter configuration error prompt is given; if the parameter configuration is correct, the output data of the current data node is generated.

[0017] Further, determining whether the output data of the current data node is valid data includes judging whether the output data of the current data node is empty. If it is not empty, determining that the output data of the current data node is valid data.

[0018] Furthermore, the above-mentioned zero-code-based data analysis method also includes displaying debugging results, and the debugging results include preview results, execution time, and debugging information. When the output data of the current data node is valid data, the preview result is the output data of the current data node; when the output data of the current data node is invalid data, the preview result is empty; the debugging information includes execution start, execution end, or execution exception.

[0019] According to a second aspect of the present invention, there is also provided a computer device, which includes a memory, a processor and a computer program stored in the memory, and the processor executes the computer program to implement the steps of any one of the above methods.

[0020] According to a third aspect of the present invention, there is also provided a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the steps of any of the above methods are implemented.

[0021] According to a fourth aspect of the present invention, there is also provided a computer program product, comprising a computer program, which implements the steps of any of the above methods when executed by a processor.

[0022] In general, the above technical solutions conceived by the present invention can achieve the following beneficial effects compared with the prior art:

[0023] (1) The present invention provides a zero-code-based data analysis method, which introduces an automatic debugging function in the data processing process. That is, based on the parameter configuration of the data node, the data analysis service is connected for automatic debugging. It first determines whether the output data of the current data node is valid data. If it is valid, it will continue to perform the next data analysis. Otherwise, it will output an error message prompt, or reconfigure the parameters of the current data node until the output data of the current data node is valid data, thereby realizing zero-code-based data analysis, avoiding repeated configuration operations caused by invalid configuration, saving data analysis time, and achieving the purpose of improving the efficiency of data analysis.

[0024] (2) The zero-code data analysis method provided by the present invention can intuitively view the output table information and debugging log information of the data node, so that the user can have a clearer and controllable understanding of the data flow process, and can analyze the execution status of each data node in combination with the execution time in the log, so that relevant personnel can intervene in the optimization solution more quickly and accurately.

[0025] (3) The zero-code data analysis method provided by the present invention can be applied to multiple fields such as data exploration, decision support, business optimization, customer insight, risk management, etc., and supports access to multiple external data sources for joint analysis, high-concurrency point query scenarios, and high-throughput complex analysis scenarios. By providing zero-code data modeling, automatic data debugging and analysis, and intuitive data visualization functions, it helps users better understand data, discover insights, better utilize the value of big data, and make more accurate decisions and adjustments, thereby improving efficiency and competitiveness. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0027] Figure 1 A flowchart of a zero-code-based data analysis method provided in an embodiment of the present application;

[0028] Figure 2 A schematic diagram of a zero-code based data analysis method provided by another embodiment of the present application;

[0029] Figure 3 A schematic diagram of the data preprocessing steps provided in the embodiment of the present application;

[0030] Figure 4A A schematic diagram of operator processing steps provided in an embodiment of the present application;

[0031] Figure 4B A schematic diagram of the parameter configuration steps provided in the embodiment of the present application;

[0032] Figure 5 A schematic diagram of a preview result provided in an embodiment of the present application;

[0033] Figure 6 A schematic diagram of debugging information provided by an embodiment of the present application;

[0034] Figure 7 A schematic diagram of an operation bar of a canvas provided in an embodiment of the present application;

[0035] Figure 8 A schematic diagram of a model saving function of a canvas provided in an embodiment of the present application;

[0036] Fig. 9 A schematic diagram of the internal structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0038] The terms "first", "second", "third", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0039] like Figure 1 As shown, a zero-code-based data analysis method is provided, which can be executed by a terminal or by a server that communicates with the terminal through a network. The terminal can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, etc. The server can be an independent server, or a server cluster composed of multiple servers can be used. Taking the application of the method to a terminal as an example, the method includes the following steps:

[0040] S1, obtain the operator, connect the operator with the output data of the parent node, generate the current data node, and the parent node is the starting data node or the target data node.

[0041] The parent node is a node used to connect the operator to be processed, which can be a starting data node or a target data node, that is, other generated data nodes except the starting data node. The output data of the parent node is the process data and result data generated during the data analysis process.

[0042] Operators include intersection, difference, full join, left join, adding fields, table structure processing, data filtering, string processing, date processing, data deduplication, column calculation or group statistics, etc.

[0043] Exemplarily, the user determines an operator related to the output data of the parent node, clicks an input device (such as a mouse), and selects the operator to be executed from the display screen of the terminal. The terminal obtains the operator selected by the user through the input device; connects the operator with the output data of the parent node to generate the current data node.

[0044] S2, configure the parameters of the current data node based on the output data of the parent node.

[0045] S3, automatically debug and analyze the current data node, generate output data of the current data node, and determine whether the output data of the current data node is valid data.

[0046] The valid data is determined according to actual needs, and may be that the output data of the current data node are all integers, or that the output data of the current data node are not empty.

[0047] Exemplarily, the data analysis service module is automatically called to determine whether the parameter configuration of the current data node is correct. If the parameter configuration is wrong, a parameter configuration error prompt is given; if the parameter configuration is correct, the output data of the current data node is generated; and it is determined whether the output data of the current data node is empty. If it is not empty, the output data of the current data node is determined to be valid data. The data analysis service module is a software function module.

[0048] S4, if it is valid data, the current data node completes data analysis; if it is invalid data, the current data node outputs an error message prompt, or returns to step S2 to reconfigure the parameters of the current data node until the output data of the current data node is valid data.

[0049] S5, after the current data node completes data analysis, continue to execute according to the above steps S1-S4.

[0050] In the above-mentioned zero-code-based data analysis method, an automatic debugging function is introduced in the data processing process, that is, based on the parameter configuration of the data node, the data analysis service is connected for automatic debugging. First, it is determined whether the output data of the current data node is valid data. If it is valid, the next data analysis will be performed. Otherwise, the parameters of the current data node are reconfigured until the output data of the current data node is valid data, thereby realizing zero-code-based data analysis, avoiding repeated configuration operations caused by invalid configuration, saving data analysis time, and achieving the purpose of improving the efficiency of data analysis.

[0051] In one embodiment, the above zero-code-based data analysis method further includes acquiring data resources to generate a starting data node; and preprocessing the data resources to obtain output data of the starting data node.

[0052] Among them, data resources include at least one kind of data in MySQL database, PostgreSQL database, Oracle database or SQLServer database. Data resources are divided into public data and personal data according to content. Among them, the query permission of public data is for all users, and the query permission of personal data is only for the user who uploaded the data.

[0053] Exemplarily, data resources are acquired to generate a starting data node; a field selected by a user through an input device (such as a mouse, a display screen, etc.) is acquired, and data resources are screened according to the field to obtain output data of the starting data node.

[0054] In one embodiment, the above-mentioned zero-code-based data analysis method also includes displaying debugging results, and the debugging results include preview results, execution time, and debugging information. When the output data of the current data node is valid data, the preview result is the output data of the current data node; when the output data of the current data node is invalid data, the preview result is empty; the debugging information includes execution start, execution end, or execution exception.

[0055] In one embodiment, a zero-code data analysis method is implemented based on a front-end interactive drag data processing component and a back-end data analysis service component. The front-end interactive drag data processing component is implemented using the vue3 development framework and Antv / X6 graph editing engine technology. The back-end data analysis service component is implemented based on the Apache Doris data query engine.

[0056] The Antv / X6 graph editing engine provides a registration mechanism, supports custom methods to generate canvases, nodes, edges, etc., and provides a complete component configuration extension that can be dragged and dropped. In this embodiment, data resource nodes, operator class nodes, edges, and canvases are generated through Antv / X6. Extension plug-ins such as mini-maps, box selection, scrolling canvas, undo and redo, and automatic layout are introduced to help users analyze data more conveniently. The automatic debugging results based on parameter configuration and data analysis service components are displayed below the canvas area, so that the data flow process can be clearly displayed to the user, and the execution time in the debugging information can be combined to analyze the execution status of each data node, and more quickly and accurately find error nodes or time-consuming nodes.

[0057] like Figure 2 As shown, a zero-code based data analysis method specifically includes the following steps:

[0058] S21, acquiring data resources, generating a starting data node, preprocessing the data resources, and obtaining output data of the starting data node;

[0059] S22, obtain the operator, connect the operator with the output data of the parent node, generate the current data node, and configure the parameters of the current data node;

[0060] S23, accessing the data analysis service to perform automatic data debugging and analysis for the parameters of the current data node, and generating output data of the current data node;

[0061] S24, if the output data of the current data node is valid data, start the next step of operator processing according to the above step S22; otherwise, return to the above step S22 to reconfigure the parameters of the current data node.

[0062] In step S21, data preprocessing is to screen data fields of a single or multiple data resources. Figure 3 As shown, taking the case where the filter fields include subject and name as an example, by selecting the filter field as subject or name, the corresponding output data is obtained.

[0063] In step S22, the operators include intersection, difference, full join, left join, adding fields, table structure processing, data filtering, string processing, date processing, data deduplication, column calculation, grouping statistics, data deduplication and operators customized according to the business. Figure 4A As shown in the figure, connect the data in the table named Student Score Table_1 with the operator of Data Deduplication_1, and configure Figure 4B The parameters of the deduplication field and the parameters of the deduplication rule shown implement data deduplication for the output data of the parent node.

[0064] A data node is a data object containing multiple attributes. The attributes include the unique identifier id, the category name name, the node name title, the array object parents containing the unique identifier of the parent node, the category identification field type, the input data inputColumns, the output data outpouColumns, and the parameter configuration object settings. Among them, the input data inputColumns of the data node includes the input table name and input table field information. According to the operator type, the data node can be configured with one or more input data. The output data outpouColumns of the data node includes the output table name and output table field information.

[0065] For the starting data node, its input data is the data resource (such as a table directly obtained from the database), and its output data is the preprocessed data resource (such as a table after field screening). For the target data node, its input data is the output data of the parent node, and its output data is the data processed by the target data node after parameter configuration.

[0066] Based on the attributes of the data node, the operation instructions (such as copying, deleting, parameter configuration, and viewing) selected by the user through the input device (such as by monitoring the mouse events of the data node) can also be obtained, and the data node can be copied, deleted, configured with parameters, viewed (such as outputting table field information), etc. according to the operation instructions. Preferably, for the copy operation, only the starting data node or the operator without parameter configuration can be copied.

[0067] When the parameter configuration is completed, the output data of the current data node is passed to the backend data parsing service component for data parsing. When the output data is invalid, the parameters of the current data node need to be reconfigured. Only when the output data of the current data node is valid data is it allowed to continue connecting to the next operator.

[0068] like Figure 5 and Figure 6 As shown in the figure, the results of automatic debugging of the data node are displayed below the canvas. The displayed information includes preview results, execution time, and debugging information. The preview result is the output data table of the current data node, which can be sorted by numerical or string type fields.

[0069] like Figure 7 As shown, the canvas can also implement the following functions. In the operation bar above the canvas, click the "Edit" icon button to modify the model name. Click the "Undo" button to undo the last operation, and click the "Restore" button to restore the last operation. Select "Box Selection Mode" to box select multiple nodes to move or batch delete nodes. The types of connecting lines support straight lines, curves, and broken lines. Click "Fit Window" or "One-click Layout" to optimize the layout according to specified requirements. Click "Run Preview" to preview the results of the data node at the end point of the connecting line. For example, for the function of previewing data results, the user can complete the data preview operation in one step by directly clicking the "Run Preview" button on the data node with the mouse. The data preview results are dynamically displayed at the bottom of the canvas. To switch the data node to run the preview, you only need to directly operate on another data node, and the data preview results will be refreshed in real time. In addition, if Figure 8 As shown, you can also save / publish the current model.

[0070] In this embodiment, in terms of data processing: the data processing process can be automatically debugged to determine whether the output of the current data node is empty, and the data can be queried in real time in a visual manner, avoiding repeated data processing processes caused by incorrect parameter configuration and invalid parameter configuration, thereby more conveniently realizing modeling analysis and deep mining of massive data, and improving the efficiency of data analysis. In addition, in terms of technology: data processing is realized in a zero-code manner, so that users, especially non-technical personnel, can realize data processing by clicking on the screen or selecting the data options displayed on the display screen, which lowers the threshold for data analysis and reduces the time and labor costs of data analysis spent by users.

[0071] In addition, in terms of interface usability, data operations are faster and more convenient, and data display is clearer and more intuitive. Data node operation buttons are laid out on the data nodes, and the entry is intuitive; you can quickly and intuitively view the data node name, table name and other information, the output fields and execution status of the data node, etc.; support for canvas operations such as box selection, undo, restore, adapt to window, one-click layout, and small map, which improves the modeling speed.

[0072] The present application also provides a computer device, the internal structure diagram of which can be as follows: Fig. 9 As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a data analysis method based on zero code is implemented. The display unit of the computer device is used to form a visually visible image, and can be a display screen, a projection device or a virtual reality imaging device. The input device of the computer device can be a touch layer covered on the display screen, or a button, trackball or touchpad set on the computer device casing, or an external keyboard, touchpad or mouse, etc.

[0073] Those skilled in the art will understand that Fig. 9The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0074] like Fig. 9 As shown, the present application also provides a computer device, which includes a memory, a processor, and a computer program stored in the memory, and the processor executes the computer program to implement the steps in the above-mentioned method embodiments.

[0075] The present application also provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented. The computer-readable storage medium may include, but is not limited to, any type of disk, including a floppy disk, an optical disk, a DVD, a CD-ROM, a micro drive, and a magneto-optical disk, a ROM, a RAM, an EPROM, an EEPROM, a DRAM, a VRAM, a flash memory device, a magnetic card or an optical card, a nanosystem (including a molecular memory IC), or any type of medium or device suitable for storing instructions and / or data.

[0076] The present application also provides a computer program product, including a computer program, which implements the steps in the above-mentioned method embodiments when executed by a processor.

[0077] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0078] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0079] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0080] The above is only an exemplary embodiment of the present disclosure, and the scope of the present disclosure cannot be limited thereto. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the specification and practicing the disclosure here, those skilled in the art will easily think of the implementation scheme of the present disclosure. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field not recorded in the present disclosure. The description and examples are only regarded as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

[0081] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0082] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A data analysis method based on zero code, characterized in that: The following steps are involved: S1, obtain an operator, connect the operator with the output data of the parent node, and generate the current data node, where the parent node is the starting data node or the target data node; S2, configure the parameters of the current data node based on the output data of the parent node; S3, automatically debugging and analyzing the current data node, generating output data of the current data node, and determining whether the output data of the current data node is valid data; S4, if the data is valid, the current data node completes data analysis; If the data is invalid, the current data node outputs an error message, or returns to step S2 to reconfigure the parameters of the current data node until the output data of the current data node is valid data; S5, after the current data node completes data analysis, continue to execute according to the above steps S1-S4.

2. The method according to claim 1, characterized in that The method further comprises: Obtain data resources and generate starting data nodes; The data resource is preprocessed to obtain output data of the starting data node.

3. The method according to claim 1, characterized in that The operators include intersection, difference, full join, left join, adding fields, table structure processing, data filtering, string processing, date processing, data deduplication, column calculation or group statistics.

4. The method according to claim 1, characterized in that The attributes of the data node include a unique identifier, a category identification field, a category name, a node name, an array object containing a parent node unique identifier, input data, output data, and a parameter configuration object, wherein the input data includes an input table name and input table field information, and the output data includes an output table name and output table field information; the method also includes obtaining an operation instruction selected by a user through an input device, wherein the operation instruction includes copying, deleting, parameter configuration, and viewing, and copying, deleting, parameter configuration, or viewing the data node according to the operation instruction.

5. The method according to claim 1, characterized in that The automatic debugging and analysis of the current data node to generate output data of the current data node includes: The data analysis service module is automatically called to determine whether the parameter configuration of the current data node is correct. If the parameter configuration is wrong, a parameter configuration error prompt is given; if the parameter configuration is correct, the output data of the current data node is generated.

6. The method according to claim 1, characterized in that The determining whether the output data of the current data node is valid data includes: It is determined whether the output data of the current data node is empty. If not, it is determined that the output data of the current data node is valid data.

7. The method according to claim 1, characterized in that The method further comprises: Display debugging results, which include preview results, execution time, and debugging information. When the output data of the current data node is valid data, the preview result is the output data of the current data node; when the output data of the current data node is invalid data, the preview result is empty; the debugging information includes execution start, execution end, or execution exception.

8. A computer device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method according to any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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