Data statistics visualization method, device and equipment and storage medium thereof

Abstract

The embodiment of the invention belongs to the technical field of data processing visualization, is applied to a data volume visualization statistics scene, and relates to a data statistics visualization method, device and equipment and a storage medium thereof.The data statistics visualization method comprises the steps that all task execution nodes covered by a data statistics task are displayed in a data statistics visualization component in a task execution flow chart mode; identifying a non-tail-end task execution node and a tail-end task execution node according to the execution logic relationship among all the task execution nodes; and displaying data statistics results respectively corresponding to the non-tail-end task execution nodes and the tail-end task execution nodes at the interface display reserved positions in a distinguished manner, and completing data statistics visualization. Especially in data statistics scenes with relatively complicated data such as bank data statistics and financial institution data statistics, the data statistics visualization method is adopted to display the data entry quantity counted by each task execution node to a target interface, so that data analysts can be assisted to intuitively understand a data statistics result.

Description

Technical Field

[0001] The present application relates to the technical field of data processing visualization, and is applied to data volume visualization statistics scenarios, and in particular to a data statistics visualization method, device, equipment and storage medium thereof. Background Art

[0002] Data statistical analysis can help the company's data analysts conduct risk assessments on business situations and adjust business structures in a timely manner. Scientific data analysis can not only assist data analysts in making decisions quickly and efficiently, but also save a lot of data processing time.

[0003] At present, most commonly used data automation statistical tools are for automatically collecting statistics. However, there are often problems with the sampling rate algorithm for automatically collecting statistical information, resulting in inaccurate statistical information. The task of automatically collecting statistical information is serial, which makes the task of collecting statistical information time-consuming and often cannot be completed within the maintenance window. The task of automatically collecting statistical information cannot specify the collection priority, resulting in some tables not collecting statistical information for a long time. It is impossible to manage the tasks of manually collecting statistical information. There is a lack of graphical management and display tools for data statistical results, which is not conducive to assisting data analysts to intuitively understand the data statistical results. Summary of the invention

[0004] The purpose of the embodiments of the present application is to propose a data statistics visualization method, device, equipment and storage medium thereof to solve the problem that existing commonly used data automation statistical tools lack graphical management and display tools for data statistical results, which is not conducive to assisting data analysts to intuitively understand the data statistical results.

[0005] In order to solve the above technical problems, the present application embodiment provides a data statistics visualization method, which adopts the following technical solutions:

[0006] A data statistical visualization method comprises the following steps:

[0007] Start the preset data statistics visualization component;

[0008] Receive data statistics task execution instructions sent by the target statistics terminal;

[0009] Execute the data statistics task based on the execution instruction;

[0010] The data statistics visualization component displays all task execution nodes covered by the data statistics task in the form of a task execution flow chart, wherein the task execution nodes include non-tail execution nodes and tail execution nodes;

[0011] According to the execution logic relationship between all the task execution nodes, identifying the non-tail task execution nodes and tail task execution nodes covered by the data statistics task;

[0012] The data statistical results corresponding to the non-tail-end task execution nodes and the tail-end task execution nodes are displayed separately at the reserved positions of the interface display corresponding to all the task execution nodes, so as to complete the data statistical visualization.

[0013] Furthermore, before executing the step of starting the preset data statistics visualization component, the method further includes:

[0014] The task execution flowchart pre-constructed according to the data statistics task is deployed into the data statistics visualization component, wherein the task execution flowchart includes all the task execution nodes in the data statistics task and the data statistics result display area reserved at each task execution node.

[0015] Furthermore, the step of executing the data statistics task based on the execution instruction specifically includes:

[0016] Start the execution program corresponding to the data statistics task according to the execution instruction;

[0017] Based on the preset logical statistical algorithm, the target data that needs to be counted for all task execution nodes is counted to obtain the target data volume that needs to be counted for each task execution node.

[0018] Furthermore, the step of performing statistics on the target data that needs to be counted by all task execution nodes based on a preset logical statistical algorithm to obtain the target data volume that needs to be counted by each task execution node specifically includes:

[0019] According to the preset priority identifier, statistical priority sorting is performed on all the task execution nodes to obtain a sorting result;

[0020] Based on the sorting result, data volume statistics are performed on the task execution nodes with the highest priority level to obtain the data entry volume counted by each task execution node.

[0021] Furthermore, the step of identifying the non-tail task execution nodes and tail task execution nodes covered by the data statistics task according to the execution logic relationship between all the task execution nodes specifically includes:

[0022] Based on the execution logic relationship between all the task execution nodes, identifying whether the target data volume that needs to be counted corresponding to the current task execution node is secondary counted by any subsequent task execution node;

[0023] If the target data volume that needs to be counted corresponding to the current task execution node has not been counted twice by any subsequent task execution node, the current task execution node is the tail task execution node;

[0024] If the target data volume that needs to be counted corresponding to the current task execution node is counted twice by any subsequent task execution node, then the current task execution node is the unfinished task execution node.

[0025] Furthermore, the step of displaying the data statistics results corresponding to the non-tail task execution nodes and the tail task execution nodes respectively at the reserved positions of the interface display corresponding to all the task execution nodes specifically includes:

[0026] Obtaining the amount of data entries corresponding to each non-tail task execution node, and displaying the corresponding amount of data entries in a first distinguishing color at a reserved position of an interface display corresponding to the task execution node;

[0027] The amount of data entries corresponding to each tail-end task execution node is obtained, and the corresponding amount of data entries is displayed in a second distinguishing color at a reserved position of the interface display corresponding to the task execution node.

[0028] Further, after executing the step of displaying the data statistical results corresponding to the non-tail task execution nodes and the tail task execution nodes respectively at the reserved positions of the interface display corresponding to all the task execution nodes according to the preset logical statistical algorithm, the method further includes:

[0029] performing sum processing on all data item quantities displayed in the second distinguishing color to obtain a sum processing result;

[0030] The summation processing result is mapped to a preset interface display reserved position on the task execution flowchart and displayed in a third distinguishing color, wherein the preset interface display reserved position on the task execution flowchart is used to display the expected statistical results of the data statistics task.

[0031] In order to solve the above technical problems, the embodiment of the present application also provides a data statistics visualization device, which adopts the following technical solution:

[0032] A data statistics visualization device, comprising:

[0033] A visualization component startup module is used to start a preset data statistics visualization component;

[0034] The target execution instruction receiving module is used to receive the data statistics task execution instruction sent by the target statistics terminal;

[0035] A data statistics task execution module, used to execute the data statistics task based on the execution instruction;

[0036] A task execution node display module, used to display all task execution nodes covered by the data statistics task in the form of a task execution flow chart in the data statistics visualization component, wherein the task execution nodes include non-tail execution nodes and tail execution nodes;

[0037] A task execution node type identification module, used to identify the non-tail task execution nodes and tail task execution nodes covered by the data statistics task according to the execution logic relationship between all the task execution nodes;

[0038] The data statistics result display module is used to distinguish and display the data statistics results corresponding to the non-tail task execution nodes and the tail task execution nodes respectively at the reserved positions of the interface display corresponding to all the task execution nodes, so as to complete the data statistics visualization.

[0039] In order to solve the above technical problems, the embodiment of the present application further provides a computer device, which adopts the following technical solution:

[0040] A computer device includes a memory and a processor, wherein the memory stores computer-readable instructions, and the processor implements the steps of the above-mentioned data statistical visualization method when executing the computer-readable instructions.

[0041] In order to solve the above technical problems, the embodiment of the present application further provides a computer-readable storage medium, which adopts the following technical solution:

[0042] A computer-readable storage medium stores computer-readable instructions, which, when executed by a processor, implement the steps of the data statistics visualization method as described above.

[0043] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0044] The data statistics visualization method described in the embodiment of the present application is to start the data statistics visualization component; receive the data statistics task execution instruction sent by the target statistics end; execute the data statistics task; display all the task execution nodes covered by the data statistics task in the data statistics visualization component in the form of a task execution flow chart; identify the non-tail task execution nodes and the tail execution task nodes according to the execution logic relationship between all the task execution nodes; and display the data statistics results corresponding to the non-tail task execution nodes and the tail execution task nodes at the reserved position of the interface display, so as to complete the data statistics visualization. The task execution flow chart constructed in advance according to the data statistics task is deployed into the data statistics visualization component, and the task execution nodes included in the task execution flow chart are specified, and the data statistics result display area reserved at each task execution node is reserved, so that the data statistics of each step are respectively visualized, and the data statistics results are displayed to the viewer more intuitively, especially in the data statistics scenes with complicated data such as bank data statistics and financial institution data statistics, the data statistics visualization method described in the present application is used to display the data entry amount counted by each task execution node as a display item to the target interface, which can assist statisticians and decision makers to understand the data statistics results more intuitively. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the scheme in the present application, a brief introduction is given below to the drawings required for use in the description of the embodiments of the present application. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0046] Figure 1 is an exemplary system architecture diagram to which the present application may be applied;

[0047] Figure 2 is a flow chart of an embodiment of a data statistics visualization method according to the present application;

[0048] Figure 3 yes Figure 2 A flowchart of a specific embodiment of step 203 is shown;

[0049] Figure 4 yes Figure 3 A flowchart of a specific embodiment of step 302 is shown;

[0050] Figure 5 yes Figure 2 A flowchart of a specific embodiment of step 205 is shown;

[0051] Figure 6 yes Figure 2A flowchart of a specific embodiment of step 206 is shown;

[0052] Figure 7 is a structural schematic diagram of an embodiment of a data statistics visualization device according to the present application;

[0053] Figure 8 It is a structural diagram of an embodiment of a computer device according to the present application. DETAILED DESCRIPTION

[0054] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by technicians in the technical field of the present application; the terms used in the specification of the application herein are only for the purpose of describing specific embodiments and are not intended to limit the present application; the terms "including" and "having" and any variations thereof in the specification and claims of the present application and the above-mentioned drawings are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of the present application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0055] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0056] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.

[0057] like Figure 1 As shown, the system architecture 100 may include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0058] Users can use terminal devices 101, 102, 103 to interact with server 105 through network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, 103, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social platform software, etc.

[0059] The terminal devices 101, 102, and 103 can be various electronic devices with display screens and supporting web browsing, including but not limited to smart phones, tablet computers, e-book readers, MP3 players (Moving Picture Experts Group Audio Layer III), MP4 (Moving Picture Experts Group Audio Layer IV) players, laptop computers, desktop computers, etc.

[0060] The server 105 may be a server that provides various services, such as a background server that provides support for web pages displayed on the terminal devices 101 , 102 , and 103 .

[0061] It should be noted that the data statistics visualization method provided in the embodiment of the present application is generally executed by a terminal device, and accordingly, the data statistics visualization device is generally arranged in the terminal device.

[0062] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0063] Continue to refer Figure 2 , shows a flow chart of an embodiment of a data statistics visualization method according to the present application. The data statistics visualization method comprises the following steps:

[0064] Step 201, start the preset data statistics visualization component.

[0065] In this embodiment, the preset data statistics visualization component includes a self-built data statistics visualization component and an external third-party data visualization tool, the main purpose of which is to be able to intuitively visualize the statistical results of the data statistics task.

[0066] In this embodiment, before executing the step of starting the preset data statistics visualization component, the method also includes: deploying the task execution flowchart constructed in advance according to the data statistics task into the data statistics visualization component, wherein the task execution flowchart includes all task execution nodes in the data statistics task and a data statistics result display area reserved at each task execution node.

[0067] Specifically, the task execution flowchart constructed in advance according to the data statistics task is deployed in the data statistics visualization component, and it is stipulated that the task execution flowchart includes all the task execution nodes in the data statistics task and the data statistics result display area reserved at each task execution node, so as to realize the visualization display of the data statistics of each step separately and display the data statistics results to the viewer more intuitively.

[0068] Step 202, receiving a data statistics task execution instruction sent by a target statistics terminal.

[0069] In this embodiment, the target statistical end refers to the initiator of the data statistical task, for example: the storage and withdrawal flow statistics end in a bank account scenario, or the financial data statistics end of a financial company. The target statistical end only initiates a data statistical task execution instruction, and then receives the final data statistical result, and does not participate in other processing logics, thereby achieving separation between the instruction initiator and the logic processing end, and avoiding the introduction of calculation data into the target statistical end.

[0070] Step 203: Execute the data statistics task based on the execution instruction.

[0071] Continue to refer Figure 3 , Figure 3 yes Figure 2 The flowchart of a specific embodiment of step 203 shown includes:

[0072] Step 301, starting the execution program corresponding to the data statistics task according to the execution instruction;

[0073] Specifically, the execution program corresponding to the data statistics task has been sent to the target execution processor in advance in the form of a program execution package, which starts the target execution processor according to the execution instruction to run the program execution package, thereby starting the execution program corresponding to the data statistics task.

[0074] By sending the execution program corresponding to the data statistics task to the target execution processor in advance in the form of a program execution package, the execution program corresponding to the data statistics task is packaged and processed, which facilitates the reuse of the data statistics task in the form of a third-party plug-in in data statistics scenarios with relatively complex data, such as bank data statistics and financial institution data statistics.

[0075] Step 302: Count the target data that need to be counted for all task execution nodes based on a preset logical statistical algorithm to obtain the target data volume that needs to be counted for each task execution node.

[0076] In this embodiment, the preset logical statistical algorithm includes a statistical algorithm based on statistical priority, a statistical algorithm based on key fields, a statistical algorithm based on mathematical set values, etc., which are set here according to actual needs and are not limited.

[0077] Specifically, the statistical algorithm based on statistical priority, for example, sets statistical priorities for all task execution nodes according to the execution order of the task execution nodes, and then performs statistics according to the statistical priorities.

[0078] Furthermore, the statistical algorithm based on key fields, for example, pre-sets the target fields involved in the statistics, and performs statistics on the data containing the target fields.

[0079] For another example, the statistical algorithm based on mathematical set values, for example, a preset condition is to perform statistics on data whose values ​​are greater than a preset mathematical value.

[0080] Through the preset logical statistical algorithm, the target data that needs to be counted for all task execution nodes are counted, and the target data volume that needs to be counted for each task execution node is obtained. This realizes flexible statistics of data according to different statistical needs and requirements, which is more humane and flexible, and facilitates the repeated and flexible use of the data statistical visualization method according to different statistical needs.

[0081] Continue to refer Figure 4 , Figure 4 yes Figure 3 The flowchart of a specific embodiment of step 302 shown includes:

[0082] Step 401, performing statistical priority sorting on all the task execution nodes according to a preset priority identifier to obtain a sorting result;

[0083] Specifically, the priority identifier refers to the priority of the data statistics subtask corresponding to each task execution node. The priority identifier is pre-set according to the execution logic relationship between all task execution nodes. For example, for task execution nodes in a linear relationship, the priority of the task execution node is reduced from left to right in the execution direction; for task execution nodes in a parallel relationship or a classification relationship of the same level, the priority of such task execution nodes is consistent. How to set the priority is set by the setting personnel according to the execution logic relationship between all task execution nodes, and will not be repeated here.

[0084] Step 402 : Based on the sorting result, data volume statistics are performed on the task execution nodes with the highest priority in descending order to obtain the data entry volume counted for each task execution node.

[0085] Specifically, by obtaining the amount of data entries counted by each task execution node, it is convenient to display the amount of data entries counted by each task execution node as a display item on the target interface, which can assist statisticians and decision makers to understand the data statistical results more intuitively.

[0086] Step 204: display all task execution nodes covered by the data statistics task in the form of a task execution flow chart in the data statistics visualization component, wherein the task execution nodes include non-tail execution nodes and tail execution nodes.

[0087] Specifically, the data statistics visualization component displays all task execution nodes covered by the data statistics task in the form of a task execution flowchart. Its purpose is to display all task execution nodes covered by the data statistics task in the form of a task execution flowchart, so as to facilitate intuitive viewing of the data statistical results of each step, and to be able to intuitively conduct step-by-step investigation and analysis when there are doubts about the data statistical results, accurately locate the nodes with statistical errors, make corrections and modifications in a timely manner, and intuitively perform error correction processing.

[0088] Step 205 , identifying the non-tail-end task execution nodes and tail-end task execution nodes covered by the data statistics task according to the execution logic relationship among all the task execution nodes.

[0089] Continue to refer Figure 5 , Figure 5 yes Figure 2 The flowchart of a specific embodiment of step 205 shown includes:

[0090] Step 501, based on the execution logic relationship between all the task execution nodes, identifying whether the target data volume that needs to be counted corresponding to the current task execution node is secondary counted by any subsequent task execution node;

[0091] Specifically, the secondary statistics include being counted by the current task execution node in a specific dimension and then being counted by at least any subsequent task execution node in other dimensions. At this time, it is very likely that the same data is counted twice or more times. Therefore, the current task execution node is regarded as a non-tail task execution node; correspondingly, after being counted by the current task execution node in a specific dimension, there is no need to be counted by any subsequent task execution node. The statistical result at this time is a final statistical result. Therefore, the current task execution node is regarded as a tail task execution node.

[0092] Step 502: If the target data volume that needs to be counted corresponding to the current task execution node has not been counted twice by any subsequent task execution node, the current task execution node is the tail task execution node;

[0093] Step 503: If the target data volume that needs to be counted corresponding to the current task execution node is counted twice by any subsequent task execution node, the current task execution node is the unfinished task execution node.

[0094] By identifying the non-tail task execution nodes and the tail task execution nodes, it is convenient to integrate the final data statistical results according to the types of task execution nodes.

[0095] Step 206 , the data statistical results corresponding to the non-tail-end task execution nodes and the tail-end task execution nodes are displayed at the reserved positions of the interface display corresponding to all the task execution nodes, respectively, to complete the data statistical visualization.

[0096] Continue to refer Figure 6 , Figure 6 yes Figure 2 The flowchart of a specific embodiment of step 206 shown includes:

[0097] Step 601, obtaining the amount of data entries corresponding to each non-tail task execution node, and displaying the corresponding amount of data entries in a first distinguishing color at a reserved position of an interface display corresponding to the task execution node;

[0098] Step 602, obtaining the data entry quantity corresponding to each tail-end task execution node, and displaying the corresponding data entry quantity in a second distinguishing color at the reserved position of the interface display corresponding to the task execution node.

[0099] Specifically, by displaying the data entry quantities corresponding to the non-tail-end task execution nodes and the tail-end task execution nodes in the reserved positions on the corresponding interfaces using different colors, it is not only convenient for data sorting personnel to sort and view, and identify data statistical results more intuitively, but also convenient for secondary integration of target data statistical results in combination with different colors.

[0100] In this embodiment, after executing the step of displaying the data statistical results corresponding to the non-tail task execution nodes and the tail task execution nodes respectively at the reserved interface display positions corresponding to all the task execution nodes according to the preset logical statistical algorithm, the method also includes: summing up all the data entry quantities displayed in the second distinguishing color to obtain a summing result; mapping the summing result to the reserved interface display position preset on the task execution flowchart, and displaying it in a third distinguishing color, wherein the reserved interface display position preset on the task execution flowchart is used to display the expected statistical results of the data statistics task.

[0101] Specifically, the data items displayed in the second distinguishing color are summed to obtain a summing result; the summing result is mapped to the preset interface display reserved position on the task execution flow chart, and displayed in the third distinguishing color, i.e., the secondary integration process. Generally speaking, the data statistical results output by the final task execution node of the entire data statistical task, i.e., the expected statistical results of this data statistical task, are subjected to secondary integration processing in order to comprehensively characterize the total number of data items of the expected statistical results, and are displayed in combination with the first distinguishing color, the second distinguishing color and the third area color, so as to more intuitively characterize the data statistical results and facilitate decision makers to review and analyze the data.

[0102] By starting a data statistics visualization component; receiving a data statistics task execution instruction sent by a target statistics terminal; executing a data statistics task; displaying all task execution nodes covered by the data statistics task in the form of a task execution flow chart in the data statistics visualization component; identifying non-tail-end task execution nodes and tail-end task execution nodes according to the execution logic relationship between all task execution nodes; and displaying the data statistics results corresponding to the non-tail-end task execution nodes and the tail-end task execution nodes at the reserved position for displaying the interface, data statistics visualization is completed. The task execution flow chart constructed in advance according to the data statistics task is deployed into the data statistics visualization component, and the task execution nodes included in the task execution flow chart are specified, as well as the data statistics result display area reserved at each task execution node, so that the data statistics of each step are respectively visualized and displayed to the viewing party more intuitively, especially in data statistics scenarios with complex data such as bank data statistics and financial institution data statistics, the data statistics visualization method described in this application is used to display the data entry amount counted by each task execution node as a display item to the target interface, which can assist statisticians and decision makers to understand the data statistics results more intuitively.

[0103] The present application starts a data statistics visualization component; receives a data statistics task execution instruction sent by a target statistics terminal; executes a data statistics task; displays all task execution nodes covered by the data statistics task in the form of a task execution flow chart in the data statistics visualization component; identifies non-tail task execution nodes and tail task execution nodes according to the execution logic relationship between all task execution nodes; and displays the data statistics results corresponding to the non-tail task execution nodes and tail task execution nodes at the reserved position of the interface display, thereby completing data statistics visualization. The task execution flow chart constructed in advance according to the data statistics task is deployed into the data statistics visualization component, and the task execution nodes included in the task execution flow chart are specified, as well as the data statistics result display area reserved at each task execution node, so as to realize the visualization display of the data statistics of each step respectively, and more intuitively display the data statistics results to the viewing party, especially in data statistics scenarios with complex data such as bank data statistics and financial institution data statistics, the data statistics visualization method described in the present application is used to display the data entry amount counted by each task execution node as a display item to the target interface, which can assist statisticians and decision makers to understand the data statistics results more intuitively.

[0104] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial Intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0105] AI basic technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, mechatronics, etc. AI software technologies mainly include computer vision technology, robotics technology, biometrics technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0106] In the embodiment of the present application, by starting the data statistics visualization component; receiving the data statistics task execution instruction sent by the target statistics end; executing the data statistics task; displaying all the task execution nodes covered by the data statistics task in the data statistics visualization component in the form of a task execution flow chart; identifying the non-tail task execution nodes and the tail execution task nodes according to the execution logic relationship between all the task execution nodes; and displaying the data statistics results corresponding to the non-tail task execution nodes and the tail execution task nodes respectively at the reserved position of the interface display, the data statistics visualization is completed. The task execution flow chart constructed in advance according to the data statistics task is deployed into the data statistics visualization component, and the task execution nodes included in the task execution flow chart are specified, and the data statistics result display area reserved at each task execution node is reserved, so that the data statistics of each step are respectively visualized, and the data statistics results are more intuitively displayed to the viewing party, especially in the data statistics scenes with complex data such as bank data statistics and financial institution data statistics, the data statistics visualization method described in the present application is used to display the data entry amount counted by each task execution node as a display item to the target interface, which can assist statisticians and decision makers to understand the data statistics results more intuitively.

[0107] Further references Figure 7 , as a response to the above Figure 2 In order to realize the method shown in the figure, the present application provides an embodiment of a data statistics visualization device, and the device embodiment is Figure 2 Corresponding to the method embodiment shown, the device can be specifically applied to various electronic devices.

[0108] like Figure 7 As shown, the data statistics visualization device 700 described in this embodiment includes: a visualization component startup module 701, a target execution instruction receiving module 702, a data statistics task execution module 703, a task execution node display module 704, a task execution node type identification module 705 and a data statistics result display module 706. Among them:

[0109] A visualization component startup module 701 is used to start a preset data statistics visualization component;

[0110] The target execution instruction receiving module 702 is used to receive the data statistics task execution instruction sent by the target statistics terminal;

[0111] A data statistics task execution module 703, configured to execute the data statistics task based on the execution instruction;

[0112] The task execution node display module 704 is used to display all the task execution nodes covered by the data statistics task in the form of a task execution flow chart in the data statistics visualization component, wherein the task execution nodes include non-tail execution nodes and tail execution nodes;

[0113] The task execution node type identification module 705 is used to identify the non-tail task execution nodes and tail task execution nodes covered by the data statistics task according to the execution logic relationship between all the task execution nodes;

[0114] The data statistics result display module 706 is used to display the data statistics results corresponding to the non-tail task execution nodes and the tail task execution nodes respectively at the reserved positions of the interface display corresponding to all the task execution nodes, so as to complete the data statistics visualization.

[0115] The data statistics visualization device proposed in the present application belongs to the technical field of data processing visualization, and is applied to data volume visualization statistics scenarios, by starting a data statistics visualization component; receiving a data statistics task execution instruction sent by a target statistics terminal; executing a data statistics task; displaying all task execution nodes covered by the data statistics task in the form of a task execution flow chart in the data statistics visualization component; identifying non-tail task execution nodes and tail execution task nodes based on the execution logic relationship between all task execution nodes; and distinguishing and displaying the data statistics results corresponding to the non-tail task execution nodes and the tail execution task nodes at the reserved positions on the interface display, thereby completing data statistics visualization. The task execution flowchart constructed in advance according to the data statistics task is deployed into the data statistics visualization component, and the task execution nodes included in the task execution flowchart are specified, as well as the data statistics result display area reserved at each task execution node, so as to realize the visualization display of the data statistics of each step separately, and to display the data statistics results to the viewers more intuitively. Especially in data statistics scenarios with complex data such as bank data statistics and financial institution data statistics, the data statistics visualization method described in this application is used to display the amount of data entries counted by each task execution node as a display item on the target interface, which can assist statisticians and decision makers to understand the data statistics results more intuitively.

[0116] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through computer-readable instructions, and the computer-readable instructions can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the aforementioned storage medium can be a non-volatile storage medium such as a disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0117] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0118] To solve the above technical problems, the present application also provides a computer device. Figure 8 , Figure 8 This is a basic structural block diagram of the computer device in this embodiment.

[0119] The computer device 8 includes a memory 8a, a processor 8b, and a network interface 8c that are interconnected through a system bus. It should be noted that the figure only shows a computer device 8 having components 8a-8c, but it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital processors (DSPs), embedded devices, etc.

[0120] The computer device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The computer device may interact with a user through a keyboard, a mouse, a remote controller, a touch pad, or a voice control device.

[0121] The memory 8a includes at least one type of readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 8a can be an internal storage unit of the computer device 8, such as a hard disk or memory of the computer device 8. In other embodiments, the memory 8a can also be an external storage device of the computer device 8, such as a plug-in hard disk equipped on the computer device 8, a smart memory card (Smart Med i aCard, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. Of course, the memory 8a can also include both the internal storage unit of the computer device 8 and its external storage device. In this embodiment, the memory 8a is generally used to store the operating system and various application software installed on the computer device 8, such as a computer-readable instruction of a data statistical visualization method, etc. In addition, the memory 8a can also be used to temporarily store various types of data that have been output or are to be output.

[0122] The processor 8b may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chips in some embodiments. The processor 8b is generally used to control the overall operation of the computer device 8. In this embodiment, the processor 8b is used to run the computer-readable instructions stored in the memory 8a or process data, such as computer-readable instructions for running the data statistics visualization method.

[0123] The network interface 8c may include a wireless network interface or a wired network interface. The network interface 8c is generally used to establish a communication connection between the computer device 8 and other electronic devices.

[0124] The computer device proposed in this embodiment belongs to the field of data processing visualization technology and is applied to data volume visualization statistics scenarios. This application completes data statistics visualization by starting a data statistics visualization component; receiving a data statistics task execution instruction sent by a target statistics terminal; executing a data statistics task; displaying all task execution nodes covered by the data statistics task in the form of a task execution flow chart in the data statistics visualization component; identifying non-tail task execution nodes and tail execution task nodes based on the execution logic relationship between all task execution nodes; and displaying the data statistics results corresponding to the non-tail task execution nodes and the tail execution task nodes at the reserved position on the interface display. The task execution flowchart constructed in advance according to the data statistics task is deployed into the data statistics visualization component, and the task execution nodes included in the task execution flowchart are specified, as well as the data statistics result display area reserved at each task execution node, so as to realize the visualization display of the data statistics of each step separately, and to display the data statistics results to the viewers more intuitively. Especially in data statistics scenarios with complex data such as bank data statistics and financial institution data statistics, the data statistics visualization method described in this application is used to display the amount of data entries counted by each task execution node as a display item on the target interface, which can assist statisticians and decision makers to understand the data statistics results more intuitively.

[0125] The present application also provides another embodiment, namely, providing a computer-readable storage medium, wherein the computer-readable storage medium stores computer-readable instructions, and the computer-readable instructions can be executed by a processor to enable the processor to perform the steps of the data statistical visualization method as described above.

[0126] The computer-readable storage medium proposed in this embodiment belongs to the field of data processing visualization technology and is applied to data volume visualization statistics scenarios. This application completes data statistics visualization by starting a data statistics visualization component; receiving a data statistics task execution instruction sent by a target statistics terminal; executing a data statistics task; displaying all task execution nodes covered by the data statistics task in the form of a task execution flow chart in the data statistics visualization component; identifying non-tail task execution nodes and tail execution task nodes based on the execution logic relationship between all task execution nodes; and displaying the data statistics results corresponding to the non-tail task execution nodes and the tail execution task nodes at the reserved position on the interface display. The task execution flowchart constructed in advance according to the data statistics task is deployed into the data statistics visualization component, and the task execution nodes included in the task execution flowchart are specified, as well as the data statistics result display area reserved at each task execution node, so as to realize the visualization display of the data statistics of each step separately, and to display the data statistics results to the viewers more intuitively. Especially in data statistics scenarios with complex data such as bank data statistics and financial institution data statistics, the data statistics visualization method described in this application is used to display the amount of data entries counted by each task execution node as a display item on the target interface, which can assist statisticians and decision makers to understand the data statistics results more intuitively.

[0127] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0128] Obviously, the embodiments described above are only some embodiments of the present application, rather than all embodiments. The preferred embodiments of the present application are given in the accompanying drawings, but they do not limit the patent scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present application more thorough and comprehensive. Although the present application is described in detail with reference to the aforementioned embodiments, for those skilled in the art, it is still possible to modify the technical solutions recorded in the aforementioned specific implementation methods, or to perform equivalent replacement of some of the technical features therein. Any equivalent structure made using the contents of the specification and drawings of this application, directly or indirectly used in other related technical fields, is similarly within the scope of patent protection of this application.

Claims

1. A data statistical visualization method, characterized in that: The steps include: Start the preset data statistics visualization component; Receive data statistics task execution instructions sent by the target statistics terminal; Execute the data statistics task based on the execution instruction; The data statistics visualization component displays all task execution nodes covered by the data statistics task in the form of a task execution flow chart, wherein the task execution nodes include non-tail execution nodes and tail execution nodes; According to the execution logic relationship between all the task execution nodes, identifying the non-tail task execution nodes and tail task execution nodes covered by the data statistics task; The data statistical results corresponding to the non-tail-end task execution nodes and the tail-end task execution nodes are displayed separately at the reserved positions of the interface display corresponding to all the task execution nodes, so as to complete the data statistical visualization.

2. The data statistical visualization method according to claim 1, characterized in that: Before executing the step of starting the preset data statistics visualization component, the method further includes: The task execution flowchart pre-constructed according to the data statistics task is deployed into the data statistics visualization component, wherein the task execution flowchart includes all the task execution nodes in the data statistics task and the data statistics result display area reserved at each task execution node.

3. The data statistical visualization method according to claim 1, characterized in that: The step of executing the data statistics task based on the execution instruction specifically includes: Start the execution program corresponding to the data statistics task according to the execution instruction; Based on the preset logical statistical algorithm, the target data that needs to be counted for all task execution nodes is counted to obtain the target data volume that needs to be counted for each task execution node.

4. The data statistical visualization method according to claim 3, characterized in that: The step of performing statistics on the target data that needs to be counted by all task execution nodes based on a preset logical statistics algorithm to obtain the target data volume that needs to be counted by each task execution node specifically includes: According to the preset priority identifier, statistical priority sorting is performed on all the task execution nodes to obtain a sorting result; Based on the sorting result, data volume statistics are performed on the task execution nodes with the highest priority level to obtain the data entry volume counted by each task execution node.

5. The data statistics visualization method according to claim 1, characterized in that: The step of identifying the non-tail task execution nodes and tail task execution nodes covered by the data statistics task according to the execution logic relationship between all the task execution nodes specifically includes: Based on the execution logic relationship between all the task execution nodes, identifying whether the target data volume that needs to be counted corresponding to the current task execution node is secondary counted by any subsequent task execution node; If the target data volume that needs to be counted corresponding to the current task execution node has not been counted twice by any subsequent task execution node, the current task execution node is the tail task execution node; If the target data volume that needs to be counted corresponding to the current task execution node is counted twice by any subsequent task execution node, then the current task execution node is the unfinished task execution node.

6. The data statistics visualization method according to claim 1 or 5, characterized in that: The step of displaying the data statistics results corresponding to the non-tail task execution nodes and the tail task execution nodes respectively at the reserved positions of the interface display corresponding to all the task execution nodes specifically includes: Obtaining the amount of data entries corresponding to each non-tail task execution node, and displaying the corresponding amount of data entries in a first distinguishing color at a reserved position of an interface display corresponding to the task execution node; The amount of data entries corresponding to each tail-end task execution node is obtained, and the corresponding amount of data entries is displayed in a second distinguishing color at a reserved position of the interface display corresponding to the task execution node.

7. The data statistics visualization method according to claim 6, characterized in that: After executing the step of displaying the data statistical results corresponding to the non-tail task execution nodes and the tail task execution nodes respectively at the reserved positions of the interface display corresponding to all the task execution nodes according to the preset logical statistical algorithm, the method further includes: performing sum processing on all data item quantities displayed in the second distinguishing color to obtain a sum processing result; The summation processing result is mapped to a preset interface display reserved position on the task execution flowchart and displayed in a third distinguishing color, wherein the preset interface display reserved position on the task execution flowchart is used to display the expected statistical results of the data statistics task.

8. A data statistics visualization device, characterized in that: include: A visualization component startup module is used to start a preset data statistics visualization component; The target execution instruction receiving module is used to receive the data statistics task execution instruction sent by the target statistics terminal; A data statistics task execution module, used to execute the data statistics task based on the execution instruction; A task execution node display module, used to display all task execution nodes covered by the data statistics task in the form of a task execution flow chart in the data statistics visualization component, wherein the task execution nodes include non-tail execution nodes and tail execution nodes; A task execution node type identification module, used to identify the non-tail task execution nodes and tail task execution nodes covered by the data statistics task according to the execution logic relationship between all the task execution nodes; The data statistics result display module is used to distinguish and display the data statistics results corresponding to the non-tail task execution nodes and the tail task execution nodes respectively at the reserved positions of the interface display corresponding to all the task execution nodes, so as to complete the data statistics visualization.

9. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores computer-readable instructions, and the processor implements the steps of the data statistical visualization method according to any one of claims 1 to 7 when executing the computer-readable instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by a processor, the steps of the data statistical visualization method according to any one of claims 1 to 7 are implemented.

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