A method, device and equipment for visualizing data processing process

Abstract

The present application relates to the field of data processing technology, and discloses a visualization method, device and equipment for a data processing process, the method comprising: displaying an initial processing flow model; in response to a data processing instruction, performing an intermediate data processing operation on the data to be processed in the initial Peirce network to obtain an intermediate data processing result; adding a data graph corresponding to the intermediate data processing result to the initial processing flow model to obtain and display the intermediate processing flow model; wherein the intermediate processing flow model is used as the initial processing flow model, and the above execution process is repeated until the final data processing result is obtained to obtain a target Peirce network; and displaying the target processing flow model obtained by visual modeling of the target Peirce network. The present application realizes an intuitive display of the specific steps and processing logic of the data processing process, improves the interactivity between the user and the data processing process, thereby improving the efficiency of the data processing process, and reducing the error rate of the data processing result.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a visualization method, device and equipment for a data processing process. Background Art

[0002] With the development of society, a large amount of data is generated every day in various fields, including time series data and statistical data. These data need to be processed to obtain corresponding processing results to provide a data basis for work in various fields. In actual situations, the process of processing data includes multiple complex steps. When users only get the processing results, they cannot know the specific calculation steps and calculation logic involved in the processing process, and thus cannot verify the processing process, which affects both data-related work and the data processing process. Therefore, it is urgent to provide a method that can intuitively display the data processing process. Summary of the invention

[0003] The present application provides a method, device and equipment for visualizing a data processing process, which constructs a real-time updated Pei network according to the data processing process, and displays the data processing process in real time through visual modeling, thereby realizing an intuitive display of the specific steps and processing logic of the data processing process, improving the interactivity between the user and the data processing process, thereby improving the efficiency of the data processing process, and reducing the error rate of the data processing results.

[0004] In order to achieve the above objectives, the main technical solutions adopted in this application include:

[0005] In a first aspect, an embodiment of the present application provides a method for visualizing a data processing process, the method comprising:

[0006] Displaying an initial processing flow model; wherein the initial processing flow model is obtained by visually modeling the initial Pei network;

[0007] In response to the data processing instruction, performing an intermediate data processing operation on the data to be processed in the initial Pei network to obtain an intermediate data processing result;

[0008] Adding a data graph corresponding to the intermediate data processing result to the initial processing flow model, obtaining and displaying the intermediate processing flow model to prompt the intermediate execution process of the intermediate data processing operation; wherein the intermediate processing flow model is used as the initial processing flow model, and the execution process of the intermediate data processing operation is repeated until the final data processing result is obtained to obtain the target Pei network;

[0009] The target processing flow model is displayed to prompt the complete execution process of obtaining the final data processing result; wherein the target processing flow model is obtained by visually modeling the target Pei network.

[0010] The visualization method of the data processing process proposed in the embodiment of the present application constructs a corresponding initial Pei network according to the data processing process, and updates the initial Pei network in response to the data processing instruction, thereby synchronously updating the initial processing flow model corresponding to the initial Pei network to display the data processing process indicated in the data processing instruction. After the data processing is completed, the present application also obtains a target Pei network storing a complete data processing process, and obtains and displays a target processing flow model by visually modeling the target Pei network to prompt the complete execution process of obtaining the final data processing result. Compared with the related art, the present application constructs a Pei network to store the data processing process, and by visually modeling the Pei network, it can intuitively display the specific steps and processing logic of obtaining the data processing result, so as to allow the user to master the data processing process and perform further data processing according to the current result, thereby improving the interactivity between the user and the data processing process, thereby improving the efficiency of the data processing process, and reducing the error rate of the data processing result.

[0011] Optionally, the method further comprises:

[0012] In the case where the intermediate data processing result does not meet the preset data requirements, determining first data to be modified in the data graph corresponding to the intermediate data processing result;

[0013] In response to a modification operation on the first data to be modified, displaying first modified data in a data graph corresponding to the intermediate data processing result;

[0014] The intermediate processing flow model is updated and displayed according to the first modified data.

[0015] Optionally, the initial processing flow model includes a data graph corresponding to the data to be processed; and the method further includes:

[0016] When the intermediate data processing result does not meet the preset data requirement, determining the second data to be modified in the data graph corresponding to the data to be processed;

[0017] In response to a modification operation on the second data to be modified, displaying the second modified data in a data graph corresponding to the data to be processed;

[0018] The intermediate processing flow model is updated and displayed according to the second modified data.

[0019] Optionally, the intermediate data processing result is used to update the initial Peikal network to obtain an updated Peikal network;

[0020] The intermediate processing flow model is obtained by visually modeling the updated Pei network.

[0021] Optionally, the updated Pei network is obtained by:

[0022] According to the intermediate data processing result and the data processing mode corresponding to the data processing instruction, a subnet is added to the location of the data to be processed in the initial PerkinElmer network to obtain the updated PerkinElmer network.

[0023] Optionally, the adding a subnet at the location of the data to be processed in the initial Perkins network according to the intermediate data processing result and the data processing mode corresponding to the data processing instruction to obtain the updated Perkins network includes:

[0024] According to the operator in the data processing instruction, determining a corresponding update transition in the preset transitions of the initial Pei network;

[0025] Storing the intermediate data processing result in the newly added library of the initial Pei network;

[0026] The updated Pei network is obtained by connecting the location of the to-be-processed data with the update transition through a directed arc, and connecting the update transition with the newly added location through a directed arc.

[0027] Optionally, the adding of a subnet at the location of the data to be processed in the initial PerkinElmer network according to the intermediate data processing result and the data processing mode corresponding to the data processing instruction to obtain the updated PerkinElmer network further includes:

[0028] If the preset transitions of the initial Petri net do not include the operator in the data processing instruction, an update transition is added to the initial Petri net according to the operator in the data processing instruction.

[0029] Optionally, the target processing flow model is obtained by:

[0030] Graphing the data in the target Petri net respectively to obtain target data graphs corresponding to the data in the target Petri net;

[0031] According to the connection direction of the directed arcs in the target Petri net, the target data graphs are directed connected to obtain the target processing flow model; wherein the directed connections between the target data graphs are used to display the changes in the target Petri net.

[0032] In a second aspect, an embodiment of the present application provides a device for visualizing a data processing process, the device comprising:

[0033] An initial model display module is used to display an initial processing flow model; wherein the initial processing flow model is obtained by visually modeling the initial Pei network;

[0034] An intermediate data processing module, used for performing intermediate data processing operations on the data to be processed in the initial Pei network in response to a data processing instruction, to obtain an intermediate data processing result;

[0035] An intermediate model updating module is used to add a data graph corresponding to the intermediate data processing result to the initial processing flow model, obtain and display the intermediate processing flow model to prompt the intermediate execution process of the intermediate data processing operation; wherein the intermediate processing flow model is used as the initial processing flow model, and the execution process of the intermediate data processing operation is repeated until the final data processing result is obtained to obtain the target Pei network;

[0036] The target model display module is used to display the target processing flow model to prompt the complete execution process of obtaining the final data processing result; wherein, the target processing flow model is obtained by visually modeling the target Pei network.

[0037] In a third aspect, an embodiment of the present application provides a computer device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the method described in any one of the above embodiments by executing the computer instructions.

[0038] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which computer instructions are stored, and the computer instructions are used to enable a computer to execute any one of the methods in the above embodiments.

[0039] In a fifth aspect, an embodiment of the present application provides a computer program product, including computer instructions, and the computer instructions are used to enable a computer to execute any one of the methods in the above embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the specific implementation methods of the present application or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0041] Figure 1A step diagram of a visualization method for a data processing process provided in an embodiment of the present application;

[0042] Figure 2 A diagram showing steps for modifying the intermediate data processing result in an embodiment of the present application;

[0043] Figure 3 A diagram showing steps for modifying the data to be processed in an embodiment of the present application;

[0044] Figure 4 A diagram showing the steps for updating the Pei network in the embodiment of the present application;

[0045] Figure 5 A diagram showing the steps of visually modeling a target Pei network in an embodiment of the present application;

[0046] Figure 6a A schematic diagram of a data graph in an embodiment of the present application;

[0047] Figure 6b A schematic diagram of a target processing flow model in an embodiment of the present application;

[0048] Figure 7 A module diagram of a visualization device for a data processing process provided in an embodiment of the present application;

[0049] Figure 8 A schematic diagram of the structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0051] With the development of society, a large amount of data is generated every day in various fields, including time series data and statistical data. These data need to be processed and analyzed to obtain corresponding processing results, thereby providing a data basis for work in various fields. In actual situations, the process of processing data may be more complex, such as synchronous and asynchronous processing of data, execution of complex algorithms, and distributed processing of large-scale data.

[0052] In the above processing, when the user only obtains the processing result, he cannot know the specific calculation steps and calculation logic included in the processing process, which makes it impossible for the user to intuitively understand the logical connection between the initial data and the processing result. In addition, since the user cannot understand the specific calculation steps and calculation logic of the processing process, and thus cannot verify the processing process, there is a situation where errors in the processing results cannot be discovered by the user, resulting in reduced accuracy of the data processing results and limiting the efficiency of the data processing process.

[0053] Based on the above problems, the present application provides a method, device and equipment for visualizing a data processing process, which utilizes the characteristics of Petri Net that can effectively handle synchronous processing, asynchronous processing and concurrent processing steps in the data processing process, constructs a real-time updated Petri Net according to the data processing process, and displays the data processing process in real time through visual modeling, thereby achieving an intuitive display of the specific steps and processing logic of the data processing process, improving the interactivity between the user and the data processing process, thereby improving the efficiency of the data processing process, and reducing the error rate of the data processing results.

[0054] The method comprises: displaying an initial processing flow model; in response to a data processing instruction, performing an intermediate data processing operation on the data to be processed in the initial Petri net to obtain an intermediate data processing result; adding a data graph corresponding to the intermediate data processing result to the initial processing flow model to obtain and display the intermediate processing flow model; wherein the intermediate processing flow model is used as the initial processing flow model, and the above execution process is repeated until the final data processing result is obtained to obtain a target Petri net; and displaying a target processing flow model obtained by visually modeling the target Petri net.

[0055] The visualization method of the data processing process proposed in the embodiment of the present application constructs a corresponding initial Pei network according to the data processing process, and updates the initial Pei network in response to the data processing instruction, thereby synchronously updating the initial processing flow model corresponding to the initial Pei network to display the data processing process indicated in the data processing instruction. After the data processing is completed, the present application also obtains a target Pei network storing the complete data processing process, obtains and displays the target processing flow model by visually modeling the target Pei network, and prompts the complete execution process of obtaining the final data processing result.

[0056] Compared with the related art, the present application constructs a Pei network to store the data processing process, and visually models the Pei network, so as to intuitively display the specific steps and processing logic for obtaining the data processing results, allowing the user to master the data processing process and perform further data processing based on the current results, thereby improving the interactivity between the user and the data processing process, thereby improving the efficiency of the data processing process, and reducing the error rate of the data processing results.

[0057] The visualization method of the data processing process provided in this specification can be applied to various types of data, including but not limited to time series data and statistical data. It is understandable that in the visualization method of the data processing process provided in this specification, the above different types of data can be processed by using preset standard operators, such as calculating changes, summing, and coincidence calculations, etc. In addition, the above data can also be processed by custom formulas.

[0058] According to an embodiment of the present application, an embodiment of a method for visualizing a data processing process is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0059] In this embodiment, a data processing visualization method is provided, which can be used for the above-mentioned various types of data. Figure 1 As shown, the method includes:

[0060] S100. Display the initial processing flow model; wherein the initial processing flow model is obtained by visually modeling the initial Pei network.

[0061] S200. In response to the data processing instruction, perform an intermediate data processing operation on the data to be processed in the initial Pei network to obtain an intermediate data processing result.

[0062] S300. Add data graphics corresponding to the intermediate data processing results to the initial processing flow model, obtain and display the intermediate processing flow model to prompt the intermediate execution process of the intermediate data processing operation; wherein, the intermediate processing flow model is used as the initial processing flow model, and the execution process of the above intermediate data processing operations is repeated until the final data processing result is obtained to obtain the target Pei network.

[0063] S400. Display the target processing flow model to indicate the complete execution process of obtaining the final data processing result; wherein the target processing flow model is obtained by visually modeling the target Pei network.

[0064] The initial data is stored in the initial Perkins network. The initial data can be obtained from a data source and can be used as one or more data as the data basis for the data processing process. The required data processing results can be obtained by processing the initial data. The initial data can be pre-processed before data processing so that the format of the initial data is the same, and the time granularity of the data needs to be aligned for time series data. After the initial data is processed, the initial Perkins network can be used to store the data processing process of the initial data. At this time, the initial Perkins network can also store the data processing results obtained by the data processing.

[0065] The data processing instruction may be an instruction issued by the user according to the data processing requirements, and the data processing instruction may include the data processing operation to be performed and the execution object of the data processing operation. The data to be processed is the data determined in the initial Pei network according to the data processing instruction, and the data to be processed may be any data stored in the initial Pei network. For example, when the execution object of the data processing instruction is the initial data, the data to be processed is the initial data; when the execution object of the data processing instruction is the data processing result, the data to be processed is the data processing result.

[0066] Specifically, the initial Pei network is visualized and modeled to obtain an initial processing flow model. The initial processing flow model may be a model containing multiple data graphs, wherein the content and order of each data graph corresponds to the data stored in the initial Pei network and its order, and the connection between the data graphs represents the data processing operation between the data corresponding to the data graphs. Based on the displayed initial processing flow model, the user can understand the specific steps of the data processing process and the execution logic of each step, and then can perform logic verification and parameter configuration of the data processing process.

[0067] Furthermore, based on the initial processing flow model, the user can also issue data processing instructions according to actual scenario needs to further process the data stored in the initial Pei network. After receiving the data processing instructions, the intermediate data processing operation is performed on the data to be processed according to the data processing instructions to obtain the intermediate data processing results. The initial processing flow model is updated using the intermediate data processing results to obtain the intermediate processing flow model, so that the data processing operations contained in the data processing instructions and the data processing results corresponding to the data processing operations can be displayed to the user.

[0068] Furthermore, the user can issue data processing instructions multiple times to repeatedly execute the intermediate data processing operation, and update the initial processing flow model according to the intermediate data processing results obtained each time. In the above process, since the intermediate processing flow model is displayed after each data processing operation is executed, the user can understand the current data processing results in real time, and stop issuing data processing instructions after obtaining the final data processing results to stop the data processing process.

[0069] It should be noted that in the above process of updating the initial processing flow model, the initial Pei network corresponding to the initial processing flow model is also updated at the same time. After obtaining the final data result, the initial Pei network at this time is saved as the target Pei network, and the target Pei network is visualized and modeled to obtain and display the target processing flow model. The target Pei network stores the complete execution process of obtaining the final data processing result from the initial data. By displaying the target processing flow model to display the above execution process to the user, the transparency of the data processing process is improved, the data black box is avoided, and the utilization effect of the data processing result is improved.

[0070] Furthermore, both the initial Petri net and the target Petri net utilize the unique advantages of Petri net in data analysis and processing, and can flexibly process synchronous and asynchronous processing of data, and can effectively represent concurrent processing steps in the data processing process. The above advantages enable the initial Petri net and the target Petri net to effectively and clearly store the data processing process including synchronous processing, asynchronous processing and concurrent processing steps when facing a complex data processing process.

[0071] The processing flow model obtained by visual modeling based on the above-mentioned Pei network also takes advantage of the above-mentioned advantages, and intuitively displays the logical relationship and data changes in the data processing process through a graphical interface, thereby helping users to quickly understand and master the specific steps and execution logic in the data processing process, so as to be able to perform corresponding verification, thereby improving the efficiency of the data processing process. In addition, displaying the data processing process also improves the transparency of the data, facilitating the sharing and use of data.

[0072] The visualization method of the data processing process provided in this embodiment constructs a corresponding initial Pei network according to the data processing process, and updates the initial Pei network in response to the data processing instruction, thereby synchronously updating the initial processing flow model corresponding to the initial Pei network to display the data processing process indicated in the data processing instruction. After the data processing is completed, the application also obtains a target Pei network storing the complete data processing process, and obtains and displays the target processing flow model by visually modeling the target Pei network to indicate the complete execution process of obtaining the final data processing result.

[0073] Compared with the related art, the present application constructs a Pei network to store the data processing process, and visually models the Pei network, so as to intuitively display the specific steps and processing logic for obtaining the data processing results, allowing the user to master the data processing process and perform further data processing based on the current results, thereby improving the interactivity between the user and the data processing process, thereby improving the efficiency of the data processing process, and reducing the error rate of the data processing results.

[0074] Reference Figure 2 As shown, as an embodiment of the present application, the method further includes:

[0075] S510. When the intermediate data processing result does not meet the preset data requirement, determine the first data to be modified in the data graph corresponding to the intermediate data processing result.

[0076] S520. In response to the modification operation on the first data to be modified, display the first modified data in the data graph corresponding to the intermediate data processing result.

[0077] S530. Update and display the intermediate processing flow model according to the first modified data.

[0078] Among them, the preset data requirements can be preset requirements on the numerical size, data structure or data type of the intermediate data processing results. The user verifies the intermediate data processing results according to the preset data requirements to determine whether the data processing process is executed correctly.

[0079] Specifically, when displaying the intermediate processing flow model, the user can not only verify the logic of the data processing process, but also verify the correctness of each data in the data processing process. In the case that the intermediate data processing result does not meet the preset data requirements, if it is found that there is a problem with the intermediate data processing result, the user can determine the first data to be modified from the data graph corresponding to the intermediate data processing result, and modify the first data to be modified in the data graph to obtain the first modified data. The data graph corresponding to the intermediate data processing result can directly save and display the first modified data.

[0080] Further, after obtaining the first modified data, the first modified data is input into the Pei network corresponding to the intermediate processing flow model, and based on the data processing flow stored in the Pei network, recalculation is performed according to the first modified data. The intermediate processing flow model is updated and displayed according to the above recalculation result to ensure the correctness of the data during the data processing process.

[0081] Reference Figure 3 As shown, as an embodiment of the present application, the initial processing flow model includes a data graph corresponding to the data to be processed; the method also includes:

[0082] S540. When the intermediate data processing result does not meet the preset data requirements, determine the second data to be modified in the data graph corresponding to the data to be processed.

[0083] S550. In response to the modification operation on the second data to be modified, display the second modified data in the data graph corresponding to the data to be processed.

[0084] S560. Update and display the intermediate processing flow model according to the second modified data.

[0085] Specifically, when the intermediate data processing results do not meet the preset data requirements, if problems are found in the data to be processed, the user can determine the second data to be modified that needs to be modified from the data graph corresponding to the data to be processed, and modify the second data to be modified in the data graph to obtain the second modified data. The data graph corresponding to the data to be processed can directly save and display the first modified data.

[0086] Further, after obtaining the second modified data, the second modified data is input into the Pei network corresponding to the intermediate processing flow model, and based on the data processing flow stored in the Pei network, recalculation is performed according to the second modified data. The intermediate processing flow model is updated and displayed according to the above recalculation result to ensure the correctness of the data during the data processing process.

[0087] Similar to the technical solution of modifying the intermediate data processing results, this embodiment utilizes the dependencies between the data in the Pei network, and recalculates other data in the data processing process according to the modified data and the data processing process stored in the Pei network, so that the data in the data processing process has consistency, that is, the processing results corresponding to the same data, thereby ensuring the correctness of the data.

[0088] As an embodiment of the present application, the intermediate data processing result is used to update the initial Peikal's network to obtain an updated Peikal's network; the intermediate processing flow model is obtained by visually modeling the updated Peikal's network.

[0089] Specifically, in the process of updating the initial processing flow model according to the intermediate data processing results, the initial Pei network is also updated at the same time, that is, the intermediate data processing operations and the intermediate data processing results are stored in the initial Pei network to obtain the updated Pei network. By visually modeling the updated Pei network, the intermediate processing flow model can be obtained. It can be understood that the intermediate processing flow model not only prompts the intermediate execution process of the intermediate data processing operation, but also prompts the execution process other than the intermediate data processing operation in the data processing process. The user can adjust the display range according to actual needs.

[0090] As an embodiment of the present application, the updated Pei network is obtained by the following method:

[0091] S210. According to the intermediate data processing result and the data processing method corresponding to the data processing instruction, a subnet is added to the location of the data to be processed in the initial PerkinElmer network to obtain an updated PerkinElmer network.

[0092] Specifically, in response to the data processing instruction, an intermediate execution process of executing the intermediate data processing operation is performed, that is, a new data processing process is added on the basis of maintaining the original data processing process unchanged. The initial Petri net is updated by adding a subnet at a corresponding position in the initial Petri net, so that the intermediate execution process is stored in the initial Petri net, and an updated Petri net storing the intermediate execution process is obtained.

[0093] Reference Figure 4 As shown, as an embodiment of the present application, according to the data processing method corresponding to the intermediate data processing result and the data processing instruction, a subnet is added to the position of the data to be processed in the initial Pei network to obtain an updated Pei network, including:

[0094] S220. According to the operator in the data processing instruction, determine the corresponding update transition in the preset transition of the initial Pei network.

[0095] S230. Store the intermediate data processing results in the newly added library of the initial Pei network.

[0096] S240. Connect the location of the data to be processed and the update transition through directed arcs, and connect the update transition and the newly added location through directed arcs to obtain an updated Pei network.

[0097] Specifically, the initial Pei network may store multiple preset transitions in advance, and the preset transitions correspond to operators respectively, and the operators include but are not limited to translation, frequency conversion, and mathematical calculation, among which frequency conversion is to change the frequency of data changes, for example, to change daily frequency data to monthly frequency data. The data processing instruction corresponds to a data processing method, and the operator corresponding to the data processing method is matched in the preset transitions, and the preset transition matching the operator is determined as the update transition.

[0098] It is understandable that if the data processing instruction includes multiple operators, the corresponding update transitions are determined according to the operators in the preset transitions, and the corresponding update transitions are sorted according to the execution order of the operators to facilitate subsequent directed arc connection and Pei network update.

[0099] Furthermore, a new place is added to the initial Peirce network, and the intermediate data processing results are stored as new data in the new place. In order to indicate the direction of data processing, the place where the data to be processed is located is first connected to the update transition through a directed arc, and then the update transition is connected to the new place through a directed arc, so that a subnet representing the intermediate execution process is added at the location of the data to be processed to obtain an updated Peirce network.

[0100] As an embodiment of the present application, according to the intermediate data processing result and the data processing method corresponding to the data processing instruction, a subnet is added to the position of the data to be processed in the initial Pei network to obtain an updated Pei network, which also includes:

[0101] S250. If the preset transitions of the initial Petri net do not include the operator in the data processing instruction, add an update transition in the initial Petri net according to the operator in the data processing instruction.

[0102] Specifically, if a preset transition that matches the operator cannot be obtained when matching in the preset transition, for example, the data processing method corresponding to the data processing instruction includes a custom formula or an operator other than the operator corresponding to the preset transition, then it is necessary to add an update transition to the initial Petri net according to the operator in the data processing instruction, so as to update the initial Petri net and obtain an updated Petri net.

[0103] Reference Figure 5 As shown, as an embodiment of the present application, the target processing flow model is obtained by the following method:

[0104] S410. Graphing the data in the target Petri net respectively to obtain target data graphs corresponding to the data in the target Petri net.

[0105] S420. Directly connect the target data graphs according to the connection directions of the directed arcs in the target Petri net to obtain a target processing flow model; wherein the directed connections between the target data graphs are used to display the changes in the target Petri net.

[0106] Specifically, the initial processing flow model and the intermediate processing flow model are similar in form to the target processing flow model, and both include data graphs obtained by graphing the data in the corresponding Pei network, and directed connection arcs for connecting the above data graphs. The graphical method of the data graph can be determined according to the type, distribution and purpose of data display, including but not limited to drawing line graphs, bar graphs and histograms, so that the data can be effectively displayed. The directed connection can be an arc that connects the data graph of the data to be processed to the data graph of the data processing result to indicate the direction of data processing.

[0107] For example, the data graph may be in the form of Figure 6aAs shown, data graphics can include data-related information in addition to data charts, such as Figure 6a As shown in the table on the right, it includes the indicator name, frequency, unit and other information corresponding to the data, as well as the specific value at each time point, so that users can verify the data. If problems are found in the data during the verification process, users can issue modification operations for the problematic data. In response to the modification operation on the problematic data, the problematic data is updated and displayed to display the modified data in the data graph. For example, users can manually modify the data by clicking the corresponding position in the table to ensure the normal progress of the data processing process and reduce the error rate of the data processing results.

[0108] The target processing flow model can be found in Figure 6b As shown, Figure 6b The target processing flow model shown includes first data to be processed and second data to be processed, and a data processing result is obtained by performing a composite calculation on the first data to be processed and the second data to be processed. A directed connection is used to display the transition in the target Pei network, so as to connect the data graphs of the first data to be processed and the second data to be processed to the data graph of the data processing result. During the display process, the user can determine the specific execution process of obtaining the data processing result according to the directed connection.

[0109] Accordingly, please refer to Figure 7 , an embodiment of the present application provides a visualization device for a data processing process, the device comprising:

[0110] The initial model display module 100 is used to display the initial processing flow model; wherein the initial processing flow model is obtained by visually modeling the initial Pei network;

[0111] The intermediate data processing module 200 is used to perform intermediate data processing operations on the data to be processed in the initial Pei network in response to the data processing instruction to obtain the intermediate data processing results;

[0112] The intermediate model updating module 300 is used to add data graphics corresponding to the intermediate data processing results to the initial processing flow model, obtain and display the intermediate processing flow model to prompt the intermediate execution process of the intermediate data processing operation; wherein the intermediate processing flow model is used as the initial processing flow model, and the execution process of the intermediate data processing operation is repeated until the final data processing result is obtained to obtain the target Pei network;

[0113] The target model display module 400 is used to display the target processing flow model to indicate the complete execution process of obtaining the final data processing result; wherein the target processing flow model is obtained by visually modeling the target Pei network.

[0114] In some optional embodiments, the device further includes a data modification module, including:

[0115] The first data to be modified determining unit is used to determine the first data to be modified in the data graph corresponding to the intermediate data processing result when the intermediate data processing result does not meet the preset data requirements.

[0116] The first data modification unit is used to display the first modified data in the data graph corresponding to the intermediate data processing result in response to the modification operation on the first data to be modified.

[0117] The first data updating unit is used to update and display the intermediate processing flow model according to the first modified data.

[0118] In some optional implementations, the initial processing flow model includes a data graph corresponding to the data to be processed; and the data modification module further includes:

[0119] The second data to be modified determining unit is used to determine the second data to be modified in the data graph corresponding to the data to be processed when the intermediate data processing result does not meet the preset data requirements.

[0120] The second data modification unit is used to display the second modified data in the data graph corresponding to the data to be processed in response to the modification operation on the second data to be modified.

[0121] The second data updating unit is used to update and display the intermediate processing flow model according to the second modified data.

[0122] In some optional implementations, the intermediate data processing results in the intermediate data processing module 200 are used to update the initial Peikal's network to obtain an updated Peikal's network; the intermediate processing flow model in the intermediate model updating module 300 is obtained by visually modeling the updated Peikal's network.

[0123] In some optional implementations, the intermediate data processing module 200 includes:

[0124] The Perkins network updating unit is used to add a subnet at the location of the data to be processed in the initial Perkins network according to the intermediate data processing result and the data processing method corresponding to the data processing instruction to obtain an updated Perkins network.

[0125] In some optional implementations, the Pei network updating unit includes:

[0126] The update transition determination subunit is used to determine the corresponding update transition in the preset transitions of the initial Pei network according to the operator in the data processing instruction.

[0127] The newly added place construction subunit is used to store the intermediate data processing results in the newly added place of the initial Pei network.

[0128] The Peikal net updating subunit is used to connect the location of the data to be processed with the update transition through directed arcs, and to connect the update transition with the newly added location through directed arcs to obtain an updated Peikal net.

[0129] In some optional implementations, the Pei network updating unit further includes:

[0130] The update transition adding subunit is used to add update transitions. If the preset transitions of the initial Petri net do not include the operator in the data processing instruction, the update transition is added to the initial Petri net according to the operator in the data processing instruction.

[0131] In some optional implementations, the target model display module 400 includes:

[0132] The data graphics unit is used to respectively graphics the data in the target Petri net to obtain target data graphics corresponding to the data in the target Petri net.

[0133] The data image directed connection unit is used to connect the target data graphics in a directed manner according to the connection direction of the directed arcs in the target Petri net to obtain a target processing flow model; wherein the directed connections between the target data graphics are used to display the changes in the target Petri net.

[0134] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0135] The visualization device of the data processing process in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0136] See also Figure 8 , Figure 8It is a structural diagram of a computer device provided by an embodiment of the present application. As shown in the figure, the computer device includes: one or more processors 10, a memory 20, and an interface for connecting various components, including a high-speed interface and a low-speed interface. Each component uses different buses to communicate with each other, and can be installed on a common motherboard or installed in other ways as needed. The processor can process instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 8 A processor 10 is taken as an example.

[0137] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0138] The memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

[0139] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0140] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0141] The computer device further comprises a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0142] The embodiment of the present application also provides a computer-readable storage medium. The above method according to the embodiment of the present application can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0143] The embodiment of the present application provides a computer program product, which includes computer instructions, which are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the method of any embodiment of the present application.

[0144] Although the embodiments of the present application are described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present application, and such modifications and variations are all within the scope defined by the appended claims.

[0145] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0146] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0147] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0148] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0149] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0150] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0151] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity 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, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0152] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0153] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

[0154] Although the embodiments of the present application have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present application, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A method for visualizing a data processing process, characterized in that: The method comprises: Displaying an initial processing flow model; wherein the initial processing flow model is obtained by visually modeling the initial Pei network; In response to the data processing instruction, performing an intermediate data processing operation on the data to be processed in the initial Pei network to obtain an intermediate data processing result; Adding a data graph corresponding to the intermediate data processing result to the initial processing flow model, obtaining and displaying the intermediate processing flow model to prompt the intermediate execution process of the intermediate data processing operation; wherein the intermediate processing flow model is used as the initial processing flow model, and the execution process of the intermediate data processing operation is repeated until the final data processing result is obtained to obtain the target Pei network; The target processing flow model is displayed to prompt the complete execution process of obtaining the final data processing result; wherein the target processing flow model is obtained by visually modeling the target Pei network.

2. The method according to claim 1, characterized in that: The method further comprises: In the case where the intermediate data processing result does not meet the preset data requirements, determining first data to be modified in the data graph corresponding to the intermediate data processing result; In response to a modification operation on the first data to be modified, displaying first modified data in a data graph corresponding to the intermediate data processing result; The intermediate processing flow model is updated and displayed according to the first modified data.

3. The method according to claim 1, characterized in that The initial processing flow model includes a data graph corresponding to the data to be processed; the method further includes: When the intermediate data processing result does not meet the preset data requirement, determining the second data to be modified in the data graph corresponding to the data to be processed; In response to a modification operation on the second data to be modified, displaying the second modified data in a data graph corresponding to the data to be processed; The intermediate processing flow model is updated and displayed according to the second modified data.

4. The method according to claim 1, characterized in that The intermediate data processing result is used to update the initial Pei network to obtain an updated Pei network; The intermediate processing flow model is obtained by visually modeling the updated Pei network.

5. The method according to claim 4, characterized in that The updated Pei network is obtained by: According to the intermediate data processing result and the data processing mode corresponding to the data processing instruction, a subnet is added to the location of the data to be processed in the initial PerkinElmer network to obtain the updated PerkinElmer network.

6. The method according to claim 5, characterized in that The step of adding a subnet at the location of the data to be processed in the initial Perkins network according to the intermediate data processing result and the data processing method corresponding to the data processing instruction to obtain the updated Perkins network includes: According to the operator in the data processing instruction, determining a corresponding update transition in the preset transitions of the initial Pei network; Storing the intermediate data processing result in the newly added library of the initial Pei network; The updated Pei network is obtained by connecting the location of the to-be-processed data with the update transition through a directed arc, and connecting the update transition with the newly added location through a directed arc.

7. The method according to claim 6, characterized in that The step of adding a subnet at the location of the data to be processed in the initial Perkins network according to the intermediate data processing result and the data processing method corresponding to the data processing instruction to obtain the updated Perkins network further includes: If the preset transitions of the initial Petri net do not include the operator in the data processing instruction, an update transition is added to the initial Petri net according to the operator in the data processing instruction.

8. The method according to any one of claims 1 to 7, characterized in that The target processing flow model is obtained by: Graphing the data in the target Petri net respectively to obtain target data graphs corresponding to the data in the target Petri net; According to the connection direction of the directed arcs in the target Petri net, the target data graphs are directed connected to obtain the target processing flow model; wherein the directed connections between the target data graphs are used to display the changes in the target Petri net.

9. A visualization device for a data processing process, characterized in that: The device comprises: An initial model display module is used to display an initial processing flow model; wherein the initial processing flow model is obtained by visually modeling the initial Pei network; An intermediate data processing module, used for performing intermediate data processing operations on the data to be processed in the initial Pei network in response to a data processing instruction, to obtain an intermediate data processing result; An intermediate model updating module is used to add a data graph corresponding to the intermediate data processing result to the initial processing flow model, obtain and display the intermediate processing flow model to prompt the intermediate execution process of the intermediate data processing operation; wherein the intermediate processing flow model is used as the initial processing flow model, and the execution process of the intermediate data processing operation is repeated until the final data processing result is obtained to obtain the target Pei network; The target model display module is used to display the target processing flow model to prompt the complete execution process of obtaining the final data processing result; wherein, the target processing flow model is obtained by visually modeling the target Pei network.

10. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method according to any one of claims 1 to 8 by executing the computer instructions.

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