Process generation method and computing device

Abstract

The embodiment of the invention provides a process generation method and computing equipment, and the method comprises the steps: obtaining initial data sent by a terminal, the initial data being used for indicating to generate an operation process, and the operation process being used for executing a target task; determining a plurality of pieces of flow indication information based on the initial data, wherein the plurality of pieces of flow indication information are used for indicating a plurality of nodes corresponding to the target task and association relationships among the nodes; according to the multiple pieces of process indication information, operation process configuration data is generated, the operation process configuration data is used for generating an operation process displayed in a canvas displayed by the terminal, and the operation process comprises multiple nodes and association relationships among the nodes; and according to the operation process configuration data, generating an operation process, and sending the operation process to the terminal. The method is used for improving the generation efficiency of the operation process.

Description

Technical Field

[0001] Embodiments of the present application relate to the field of artificial intelligence technology, and in particular, to a process generation method and a computing device. Background Art

[0002] Users can systematically design and manage business or data by orchestrating job processes to monitor and record each step in business or data processing in real time, ensuring the consistency of business processing and improving work efficiency.

[0003] In related technologies, when generating a job process, users need to manually drag and drop and input each node and edit the content of each node on the canvas.

[0004] However, the above method has relatively high requirements for users. Users need to be familiar with node dragging methods and the configuration content of each node, and the operation is relatively complex, resulting in low efficiency when generating job processes. Summary of the Invention

[0005] Embodiments of the present application provide a process generation method and a computing device, which are beneficial to improving the efficiency of generating job processes.

[0006] In a first aspect, embodiments of the present application provide a process generation method, which includes:

[0007] Obtain initial data sent by a terminal, where the initial data is used to indicate generating a job process, and the job process is used to execute a target task;

[0008] Determine multiple process indication messages based on the initial data, where the multiple process indication messages are used to indicate multiple nodes corresponding to the target task and the association relationship between each node;

[0009] Generate job process configuration data according to the multiple process indication messages, where the job process configuration data is used to generate a job process displayed in a canvas displayed on the terminal, and the job process includes multiple nodes and the association relationship between each node;

[0010] Generate a job process according to the job process configuration data, and send the job process to the terminal.

[0011] In the above technical solution, the terminal can interact with the computing device based on the initial data to generate a job process for executing the target task. This process makes process orchestration more intelligent, reduces manual intervention in the process of generating a job process, reduces the operation complexity of users, facilitates user operation, is beneficial to improving the generation efficiency of job processes, and can make the generated job process more standard.

[0012] In a possible implementation manner, generating job process configuration data according to the multiple process indication messages includes:

[0013] Based on multiple process indication messages, determine at least one node type corresponding to multiple nodes, the node association types and the number of nodes corresponding to each node type, and the association relationships between each pair of nodes. The node association types include at least one of the following: data source, execution environment, message notification policy, timeout policy, or execution frequency;

[0014] Generate job process configuration data according to the association relationships, at least one node type, and the node association types and the number of nodes corresponding to each node type.

[0015] In the above technical solution, based on multiple process indication messages, at least one node type corresponding to multiple nodes, the node association types and the number of nodes corresponding to each node type, and the association relationships between each pair of nodes can be quickly determined; and then, according to the association relationships, at least one node type, and the node association types and the number of nodes corresponding to each node type, job process configuration data can be quickly generated, which is beneficial to accelerating the generation efficiency of job processes.

[0016] In a possible implementation manner, generating job process configuration data according to the association relationships, at least one node type, and the node association types and the number of nodes corresponding to each node type includes:

[0017] Generate node configuration data according to at least one node type, and the node association types and the number of nodes corresponding to each node type. The node configuration data is used to generate multiple nodes to be displayed in a canvas displayed on a terminal;

[0018] Generate relationship configuration data according to the node configuration data and the association relationships. The relationship configuration data is used to generate the connection relationships between each pair of nodes to be displayed in the canvas displayed on the terminal;

[0019] Generate job process configuration data according to the node configuration data and the relationship configuration data.

[0020] In the above technical solution, node configuration data can be quickly generated according to at least one node type, and the node association types and the number of nodes corresponding to each node type; and relationship configuration data can be quickly generated according to the node configuration data and the association relationships; and then, by assembling and processing the node configuration data and the relationship configuration data, job process configuration data is obtained. This process does not require manual intervention by the user, reduces the operation complexity of the user, and makes the generation processes of the node configuration data, the relationship configuration data, and the job process configuration data more convenient and intelligent, which is beneficial to improving the generation efficiency of job processes.

[0021] In a possible implementation manner, generating node configuration data according to at least one node type, the node association types and the number of nodes corresponding to each node type includes:

[0022] For any one node type, determine the first configuration parameter of the node type, the second configuration parameter of the node association type corresponding to the node type, and the third configuration parameter of the number of nodes corresponding to the node type, and generate the child node configuration data corresponding to the node type according to the first configuration parameter, the second configuration parameter, and the third configuration parameter;

[0023] Generate node configuration data according to at least one child node configuration data corresponding to at least one node type.

[0024] In the above technical solution, standardized node configuration data can be generated according to the first configuration parameter corresponding to each node type, the second configuration parameter of the node association type corresponding to each node type, and the third configuration parameter corresponding to the number of nodes, so as to avoid the problem of low compatibility or low standard degree of the generated node configuration data due to different user operations when generating node configuration data.

[0025] In a possible implementation manner, at least one node type includes at least one of the following:

[0026] Script type, the nodes of the script type are used for data processing, and the script type includes at least one of the following: Structured Query Language SQL type, Python type, or shell type;

[0027] Logic type, the nodes of the logic type are used for logical judgment processing, and the logic type includes at least one of the following: the type based on the node output result judgment and the type based on the logical relationship judgment;

[0028] Task type, the nodes of the task type are used for collaborative task processing, and the task type includes at least one of the following: development type or dependency type.

[0029] In the above technical solution, by dividing different node types, it is convenient for the computing device to configure the adapted configuration data according to the service requirements corresponding to each node type, making the node configuration data more accurate.

[0030] In a possible implementation manner, determine multiple process indication information based on the initial data, including:

[0031] Preprocess the initial data to obtain preprocessed data, where the preprocessed data includes multiple indication information corresponding to the job process, and the preprocessing includes at least one of the following: stop word processing, word segmentation processing, or word form processing;

[0032] Perform keyword extraction processing on the preprocessed data to obtain multiple process indication information, and the multiple indication information includes multiple process indication information.

[0033] In the above technical solution, by preprocessing the initial data and extracting keywords, it is beneficial to remove the useless data in the initial data, reduce the amount of data to be processed in the subsequent generation of job process configuration data, improve the data processing efficiency, and thus is beneficial to improving the generation efficiency of job process configuration data.

[0034] In a possible implementation manner, when the keyword extraction process for the preprocessed data fails, the method further includes:

[0035] Sending a prompt message to the terminal, where the prompt message is used to prompt the input of correct initial data.

[0036] In the above technical solution, the terminal can display the prompt message so that the user can conveniently and quickly understand how to input correct initial data, which is beneficial to improving the user experience.

[0037] In a possible implementation manner, the prompt message includes reference data, the reference data is used to generate a reference job process, the reference data includes reference process indication information corresponding to the reference job process, the reference job process is used to execute a reference task, and the reference process indication information is used to indicate multiple reference nodes corresponding to the reference task and the reference association relationship between each reference node.

[0038] In the above technical solution, the reference data can be prompted in the prompt message so that the user can input correct initial data by imitating the reference data, avoiding the user from repeatedly inputting incorrect initial data, which is beneficial to improving the user experience, beneficial to saving the time for the computing device to obtain the initial data input by the user, and improving the efficiency of obtaining the initial data.

[0039] In a possible implementation manner, after generating the job process, the method further includes:

[0040] Obtaining update data sent by the terminal, where the update data is used to indicate the update of the job process;

[0041] Determining multiple update process indication information based on the update data, where the multiple update process indication information is used to indicate the update of at least one node and / or the association relationship of at least one node in the job process;

[0042] Updating the job process according to the multiple update process indication information to obtain an updated job process;

[0043] Sending the updated job process to the terminal.

[0044] In the above technical solution, after obtaining the updated data, the terminal can also interact with the computing device, so that the computing device automatically updates the generated job process based on the updated data, enabling the job process to be executed more smoothly and efficiently, reducing manual intervention by the user, lowering the operation complexity of the user, alleviating the workload of the user, facilitating the avoidance of inconsistency problems caused by different user configurations during the process update, and improving the process update efficiency.

[0045] In a second aspect, an embodiment of the present application provides a process generation device, which includes:

[0046] A transceiver module, configured to obtain initial data sent by a terminal, where the initial data is used to indicate the generation of a job process, and the job process is used to execute a target task;

[0047] A processing module, configured to determine multiple process indication messages based on the initial data, where the multiple process indication messages are used to indicate multiple nodes corresponding to the target task and the association relationship between each node;

[0048] The processing module is further configured to generate job process configuration data according to the multiple process indication messages, where the job process configuration data is used to generate a job process displayed in a canvas displayed on the terminal, and the job process includes multiple nodes and the association relationship between each node;

[0049] The processing module is further configured to generate a job process according to the job process configuration data;

[0050] The transceiver module is further configured to send the job process to the terminal.

[0051] In a possible implementation manner, the processing module is specifically configured to:

[0052] According to the multiple process indication messages, determine at least one node type corresponding to the multiple nodes, the node association type and the number of nodes corresponding to each node type, and the association relationship between each node, where the node association type includes at least one of the following: data source, execution environment, message notification policy, timeout policy, or execution frequency;

[0053] Generate job process configuration data according to the association relationship, at least one node type, and the node association type and the number of nodes corresponding to each node type.

[0054] In a possible implementation manner, the processing module is further specifically configured to:

[0055] Generate node configuration data according to at least one node type, and the node association type and the number of nodes corresponding to each node type, where the node configuration data is used to generate multiple nodes displayed in a canvas displayed on the terminal;

[0056] Generate relationship configuration data according to node configuration data and association relationships, where the relationship configuration data is used to generate connection relationships between various nodes displayed in a canvas displayed on a terminal;

[0057] Generate job process configuration data according to node configuration data and relationship configuration data.

[0058] In a possible implementation, the processing module is further specifically configured to:

[0059] For any node type, determine a first configuration parameter of the node type, a second configuration parameter of the node association type corresponding to the node type, and a third configuration parameter of the number of nodes corresponding to the node type, and generate sub-node configuration data corresponding to the node type according to the first configuration parameter, the second configuration parameter, and the third configuration parameter;

[0060] Generate node configuration data according to at least one sub-node configuration data corresponding to at least one node type.

[0061] In a possible implementation, at least one node type includes at least one of the following:

[0062] Script type, where nodes of the script type are used for data processing, and the script type includes at least one of the following: Structured Query Language SQL type, Python type, or shell type;

[0063] Logic type, where nodes of the logic type are used for logical judgment processing, and the logic type includes at least one of the following: a type based on the output result of the node judgment and a type based on logical relationship judgment;

[0064] Task type, where nodes of the task type are used for collaborative task processing, and the task type includes at least one of the following: development type or dependency type.

[0065] In a possible implementation, the processing module is further specifically configured to:

[0066] Preprocess the initial data to obtain preprocessed data, where the preprocessed data includes multiple indication messages corresponding to the job process, and the preprocessing includes at least one of the following: stop word processing, word segmentation processing, or word form processing;

[0067] Perform keyword extraction processing on the preprocessed data to obtain multiple process indication messages, where the multiple indication messages include multiple process indication messages.

[0068] In a possible implementation, in the case where the keyword extraction processing of the preprocessed data fails, the transceiver module is further configured to send a prompt message to the terminal, where the prompt message is used to prompt to input correct initial data.

[0069] In a possible implementation, the prompt information includes reference data, which is used to generate a reference operation process. The reference data includes reference process indication information corresponding to the reference operation process. The reference operation process is used to execute a reference task, and the reference process indication information is used to indicate multiple reference nodes corresponding to the reference task and the reference association relationship between each reference node.

[0070] In a possible implementation, after generating the operation process, the transceiver module is further configured to obtain update data sent by the terminal, where the update data is used to indicate an updated operation process;

[0071] The processing module is further configured to determine multiple update process indication information based on the update data, where the multiple update process indication information is used to indicate an update to at least one node and / or the association relationship of at least one node in the operation process;

[0072] The processing module is further configured to perform an update process on the operation process according to the multiple update process indication information to obtain an updated operation process;

[0073] The transceiver module is further configured to send the updated operation process to the terminal.

[0074] In a third aspect, an embodiment of the present application provides a computing device, including: a processor and a memory; the processor and the memory are coupled;

[0075] The memory is used to store program instructions;

[0076] The processor is used to execute the program instructions to execute the method described in any item of the first aspect.

[0077] The computing device provided by the embodiment of the present application can execute the technical solution described in any item of the first aspect, and the beneficial effects are similar, so details are not described herein again.

[0078] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored, and when the computer-executable instructions are executed by a computer, the method described in any item of the first aspect is implemented.

[0079] The computer-readable storage medium provided by the embodiment of the present application can execute the technical solution described in any item of the first aspect, and the beneficial effects are similar, so details are not described herein again.

[0080] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, and when the computer program is executed by a processor, the method described in any item of the first aspect is implemented.

[0081] The computer program product provided by the embodiments of the present application can execute the technical solutions described in any item of the first aspect, and the beneficial effects are similar, so details are not described herein again.

[0082] The process generation method and computing device provided by the embodiments of the present application enable a terminal to interact with the computing device based on initial data to generate a job process for executing a target task. This process reduces manual intervention during the generation of the job process, simplifies the user's operation complexity, helps reduce the user's workload, and avoids problems such as long process generation cycles and high investment caused by workload and multi-team configurations during the process generation. It makes process orchestration more intelligent and is conducive to improving the process generation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] Figure 1 It is a schematic diagram of an application scenario provided by the embodiments of the present application;

[0084] Figure 2 It is one of the schematic flowcharts of the process generation method provided by the embodiments of the present application;

[0085] Figure 3 It is a schematic diagram of the process orchestration interface of a process orchestration tool provided by the embodiments of the present application;

[0086] Figure 4 It is the second schematic flowchart of the process generation method provided by the embodiments of the present application;

[0087] Figure 5 It is a schematic diagram of the input process of initial data provided by the embodiments of the present application;

[0088] Figure 6 It is the third schematic flowchart of the process generation method provided by the embodiments of the present application;

[0089] Figure 7 It is a schematic diagram of the process of the process generation method provided by the embodiments of the present application;

[0090] Figure 8 It is a schematic diagram of the structure of a process generation device provided by the embodiments of the present application;

[0091] Figure 9 It is a schematic diagram of the hardware structure of a computing device provided by the embodiments of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0092] Exemplary embodiments will be described in detail herein, and examples thereof are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the embodiments of the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the embodiments of the present application as detailed in the appended claims.

[0093] It should be noted that in the embodiments of the present application, some industry-existing solutions such as certain software, components, models, etc. may be mentioned. They should be considered exemplary, and their purpose is only to illustrate the feasibility in the implementation of the technical solution of the present application, but it does not mean that the applicant has already or necessarily used this solution.

[0094] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in one or more embodiments of this specification are all information and data authorized by the user or fully authorized by all parties. And the collection, use, and processing of relevant data need to comply with relevant laws, regulations, and standards, and corresponding operation entrances are provided for users to choose to authorize or refuse.

[0095] First, relevant terms involved in the embodiments of the present application will be introduced.

[0096] Artificial Intelligence (AI): refers to the technology and methods by which a computer system or machine simulates human intelligence. An AI system can perform tasks that typically require human intelligence. For example, an AI system can perform tasks such as visual perception, speech recognition, decision-making, and language translation.

[0097] Natural Language Processing (NLP): is a branch of AI that can be used to understand, interpret, and generate human language. The application fields of NLP can include fields such as speech recognition, text analysis, and translation.

[0098] Automation: refers to the process in which a user uses technical means to enable a system to automatically perform tasks or operations without human intervention. For example, a user can use technical means to automate business processes such as job flow management, task assignment, and progress tracking, which is conducive to ensuring the consistency of the processing process and improving the processing efficiency. Combining AI technology with automation can enable the system to achieve more intelligent decision-making and adaptive capabilities. For example, machine learning-driven predictive maintenance and optimization regulation, etc.

[0099] Process Orchestration: Process orchestration refers to the coordination and management of multiple tasks, services, or processes through automated tools and technologies to achieve complex business functions or operational processes. Process orchestration usually involves the integration and collaboration of multiple systems and components.

[0100] Keywords: Automatically identify and extract important words or phrases from text, which can represent the main content or theme of the text.

[0101] Data Source: Refers to the original location or system that provides data. Data sources can be databases, files, application programming interfaces (APIs), sensors, etc., which can be used for data collection and analysis.

[0102] Association Relationship: The connection or link between data or objects, indicating that they are interdependent or related to some extent.

[0103] Process Job: A series of tasks or activities executed in a specific order, which can be used to complete a specific business process. Process jobs can be executed manually or orchestrated and managed through automated tools.

[0104] The embodiments of the present application provide a process generation method. In this method, a computing device can obtain initial data sent by a terminal. The initial data can be used to indicate the generation of a job process, and the job process can be used to execute a target task. The computing device can perform intelligent parsing on the initial data to parse out multiple process indication messages for indicating multiple nodes corresponding to the target task and the association relationship between each node. And according to the multiple process indication messages, generate corresponding job process configuration data quickly and accurately. And, according to the job process configuration data, generate a job process and send the job process to the terminal. In this process, the user can input initial data to the terminal based on the requirements of the target business, so that the terminal interacts with the computing device based on the initial data to generate a job process for executing the target task. This process makes process orchestration more intelligent, reduces manual intervention in the process of generating job processes, reduces the operation complexity of users, is convenient for users to operate, is beneficial to improving the generation efficiency of job processes, and can make the generated job processes more standard.

[0105] Figure 1 Schematic diagram of an application scenario provided by the embodiments of the present application. Please refer to Figure 1, in this application scenario, the computing device and the terminal can communicate with each other. Exemplarily, the computing device can include, but is not limited to, an independent physical server, or a server cluster composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery network (CDN), and big data and artificial intelligence platforms. The terminal can include, but is not limited to, a smart phone, a smart watch, a tablet computer, a laptop computer, a desktop computer, a portable laptop computer, etc.

[0106] The terminal can display a dialogue interface. The user can input initial data in the dialogue interface through the terminal, and the terminal can send the initial data to the computing device. The computing device can generate a corresponding job process based on the initial data by using the process generation method provided in the embodiments of the present application, and send the job process to the terminal. The terminal can display the job process to the user. A process orchestration tool can be run in the terminal, and the terminal can display the job process on the canvas of the process orchestration tool.

[0107] It should be noted that the process generation method provided in the embodiments of the present application can be applied to the job process generation scenario or the process generation scenario in any field, and the present application does not limit the application scenario of the process generation method. For example, the process generation method can be applied to the data service processing scenario.

[0108] The technical solution of the present application will be described in detail below with specific embodiments. These specific embodiments below can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below with reference to the accompanying drawings.

[0109] Figure 2 is one of the flow diagrams of the process generation method provided in the embodiments of the present application. It should be noted that this method can be executed interactively by Figure 1 the computing device and the terminal in the embodiment. Please refer to Figure 2 , and this method can specifically include the following steps:

[0110] S201. The computing device obtains the initial data sent by the terminal.

[0111] The initial data can be used to indicate the generation of a job process, and the job process can be used to execute a target task.

[0112] The initial data can be text data or voice data. It can be understood that if the initial data is voice data, the voice data can be converted into corresponding text data.

[0113] Exemplarily, the initial data may be "schedule an executable job, the content of the job includes 2 Structured Query Language (SQL) nodes, 2 python nodes, and 1 shell node. These 5 nodes execute in parallel. The data sources of the SQL nodes are the population database data source and the marriage situation data source respectively. After the 5 nodes execute in parallel successfully, determine whether to execute the data development node based on the running results of the two SQL nodes."

[0114] Exemplarily, the target task may be a data development task.

[0115] In some embodiments, the computing device and the terminal may establish a communication connection. After the communication connection is successfully established, the computing device may obtain the initial data sent by the terminal.

[0116] S202. The computing device determines multiple process indication messages based on the initial data.

[0117] The multiple process indication messages are used to indicate the association relationships between the multiple nodes corresponding to the target task and each node.

[0118] Exemplarily, the multiple nodes may include SQL nodes, python nodes, Switch nodes, and development nodes. The association relationships between the nodes may be: the SQL nodes and the python nodes execute in parallel, the SQL nodes and the python nodes execute before the Switch node, and the Switch node executes before the development node. The connection relationships between these multiple nodes may be: the SQL nodes and the python nodes may be respectively connected before the Switch node, and the Switch node is connected before the development node.

[0119] In some embodiments, the computing device may perform keyword extraction processing on the initial data to obtain multiple process indication messages.

[0120] Optionally, an AI model may be set in the computing device, and keyword extraction processing may be performed on the initial data based on this AI model to obtain multiple process indication messages. This AI model may parse multiple process indication messages in the initial data input by the user based on natural language processing of AI to quickly and accurately identify the user's intention.

[0121] In some scenarios, it may occur that the AI model fails to parse the initial data and cannot extract process indication messages from the initial data. In this scenario, the computing device may further perform the following steps: send a prompt message to the terminal, and this prompt message may be used to indicate to input correct initial data.

[0122] In some embodiments, the prompt message can be used to feedback to the user that the current parsing fails and prompt the user to re-enter the data. Exemplarily, the prompt message can be "The data parsing fails. Please re-enter the correct data."

[0123] The terminal can output the prompt message based on Figure 3 the shown dialogue interface, so that the user can conveniently and quickly understand how to enter the correct initial data, which is beneficial to improving the user experience.

[0124] In some embodiments, the prompt message can further include reference data, which can be used to generate a reference operation process. The reference data can include reference process indication information corresponding to the reference operation process. The reference operation process can be used to execute a reference task, and the reference process indication information can be used to indicate multiple reference nodes corresponding to the reference task and the reference association relationship between each reference node.

[0125] It can be understood that the reference process indication information can be one or more. For example, if the reference task is a data development task and the reference operation process is an operation process for executing the data development task, the reference process indication information can include: 2 SQL nodes, 2 python nodes, 1 shell node, 5 nodes are executed in parallel, judgment, and data development node. The reference data can be a piece of information composed of the reference process indication information, or can only include the reference process indication information. For example, the reference data can be "The following is an example of the choreography of an executable job, including 2 SQL nodes, 2 python nodes, 1 shell node, these 5 nodes are executed in parallel, and according to the running results of the two SQL nodes, it is judged whether to execute the data development node." The reference data can also be "The following is a keyword example of an executable job: 2 SQL nodes, 2 python nodes, 1 shell node, 5 nodes are executed in parallel, judgment, and data development node."

[0126] The process generation method can prompt the reference data in the prompt message, so that the user can input the correct initial data by imitating the reference data, avoiding the user from repeatedly inputting due to inputting incorrect initial data again, which is beneficial to improving the user experience, beneficial to saving the time for the computing device to obtain the initial data input by the user, and improving the efficiency of obtaining the initial data.

[0127] S203. The computing device generates job process configuration data according to multiple process indication information.

[0128] The job process configuration data can be used to generate a job process displayed in a canvas displayed on the terminal. The job process can include multiple nodes and the association relationship between each node.

[0129] The data format of the job process configuration data may be in the form of JS key-value pair data (JavaScript Object Notation, JSON), or in other data formats. The embodiments of the present application do not limit the data format of the job process configuration data.

[0130] It should be noted that the process of generating the job process configuration data will be Figure 6 described in detail in the embodiments.

[0131] S204. The computing device generates a job process according to the job process configuration data.

[0132] In some embodiments, the computing device may also pre-create a process generation method or write a process generation script according to business requirements. After obtaining the job process configuration data, the computing device may call the process generation method or the process generation script to generate the job process corresponding to the initial data based on the job process configuration data.

[0133] S205. The computing device sends the job process to the terminal.

[0134] In some embodiments, the terminal may also display the job process on the canvas of the process orchestration tool and output an interface link in the dialogue interface. The interface link can be used to jump to the process orchestration interface, and the process orchestration interface includes a canvas for displaying the job process.

[0135] For example, in Figure 1 the shown dialogue interface, the terminal may output the dialogue "The job process has been generated. Please click the following link to view the generated job process: Link 1". The terminal may respond to the trigger operation of the user on Link 1 in the dialogue interface and jump from the dialogue interface to the process orchestration interface where the canvas for displaying the job process is located.

[0136] By displaying the job process on the canvas shown on the terminal and outputting the interface link, the process generation method can facilitate the user to quickly and conveniently view the generated job process on the canvas of the process orchestration interface based on the interface link, which is beneficial to improving the user experience.

[0137] The process orchestration tool may include configuration controls, process orchestration components, and a canvas for orchestrating the job process. The canvas can be used to display the job process, and the user can drag multiple process orchestration components onto the canvas to orchestrate the job process.

[0138] The configuration controls may include at least one of the following: parameter configuration control, timing configuration control, scheduling configuration control, deletion control, version control, export control, save control, and publish component. Among them, the parameter configuration control can be used to configure the parameters of the job process in the canvas; the timing configuration control can be used to configure the execution time of the job process in the canvas; the scheduling configuration control can be used to manage the resource allocation of the job process in the canvas and configure the execution frequency of the job process; the deletion control can be used to delete part or all of the content of the job process in the canvas; the version control can be used to manage the version information of the job process in the canvas, the export control can be used to export the job process displayed in the canvas; the save control is used to save the job process displayed in the canvas, and the publish control can be used to publish the job process displayed in the canvas.

[0139] The process choreography components may include: components of script type, components of logic type, and components of task type. Among them, the components of script type are used for data processing, for example, SQL components, python components, or shell components; the components of logic type are used for logical judgment processing, for example, judgment (Switch) components and conditions (Conditions) components; the components of task type are used for collaborative task processing, for example, data development components or dependent job components.

[0140] Figure 3 This is a schematic diagram of the process choreography interface of a process choreography tool provided by an embodiment of the present application. The process choreography interface includes a canvas, a component display area, and a control display area, where:

[0141] The canvas is used to display the job process. For example, in Figure 3 the job process includes 3 levels of nodes and the connection relationships between each node in these 3 levels of nodes. Among them, the first-level nodes include 5 parallel nodes, namely node 1 of type A (for example, SQL1), node 2 of type A (for example, SQL2), node 1 of type B (for example, python1), node 2 of type B (for example, python2), and node of type C (for example, shell); the second-level nodes include 1 judgment node (for example, Switch node); the third-level nodes include 1 data development node, and this condition node is respectively connected to the data development node and each of the 5 parallel nodes.

[0142] The component display area can be used to classify and display various process choreography components involved in generating the job process based on the component type. For example, in Figure 3Among them, multiple process orchestration components include: data development components, dependent job components, type A components (e.g., SQL components), type B components (e.g., python components), type C components (e.g., shell components), type D components (e.g., FlinkSQL components), Conditions components, and Switch components. Among them, the component types of data development components and dependent job components are task types, the component types of type A components, type B components, type C components, and type D components are script types, and the component types of Conditions components and Switch components are process control types.

[0143] The control display area can be used to display various controls. For example, in Figure 3 Among them, the control display area can display parameter configuration controls, timing configuration controls, scheduling configuration controls, deletion controls, version controls, export controls, save controls, and publish components.

[0144] For the process generation method provided by the embodiments of the present application, the user can input initial data to the terminal based on the requirements of the target business. After the terminal obtains the initial data input by the user, it can interact with the computing device to quickly and accurately generate the job process corresponding to the initial data, reducing manual intervention in the process of generating the job process, reducing the operation complexity of the user, facilitating the reduction of the user's workload, and avoiding the problems of long process generation cycle and large investment caused by workload and multi-team configuration in the process generation process, making the process orchestration more intelligent and conducive to improving the process generation efficiency.

[0145] Figure 4 This is the second process schematic diagram of the process generation method provided by the embodiments of the present application. It should be noted that this method can be executed by the interaction of the Figure 1 terminal and the computing device in the embodiment. Please refer to Figure 4 . Specifically, this method can include the following steps:

[0146] S401. The terminal obtains the initial data input by the user.

[0147] In some embodiments, the user can access the target website of the process orchestration tool through the browser in the terminal. The process orchestration tool can be used to orchestrate the job process. The target website can display a dialogue interface for generating the job process. The dialogue interface can include an input box, and the user can input the initial data to the terminal through the input box.

[0148] Figure 5 This is a schematic diagram of the input process of an initial data provided by the embodiments of the present application. Please refer to Figure 5, the terminal can display the user interaction interface of the process orchestration tool through the target website. The user can enter the account number and password in this user interaction interface to log in to the process orchestration tool. After the terminal successfully verifies the account number and password, it jumps from the user interaction interface to the working interface of the process orchestration tool, which can include data development controls. The user can click on the data development controls on this working interface. The terminal can respond to the user's click operation on the data development controls and jump from the working interface to the data development interface, which can include job orchestration controls. The user can further click on the job orchestration controls on this data development interface. The terminal can respond to the user's click operation on the job orchestration controls and display a dialogue interface. The user can enter the initial data in this dialogue interface.

[0149] S402. The terminal sends the initial data to the computing device.

[0150] It should be noted that the specific execution process of step S402 can refer to the specific execution process of step S201, which will not be elaborated here.

[0151] S403. The computing device preprocesses the initial data to obtain preprocessed data.

[0152] The preprocessed data can include multiple indication messages corresponding to the job process. The preprocessing can include at least one of the following: stop word processing, word segmentation processing, or word form processing.

[0153] Some common high-frequency stop words that are useless for generating the job process may appear in the initial data. For example, these stop words can be "de" or "shi". These high-frequency stop words can be removed from the initial data to improve the subsequent retrieval efficiency of the initial data.

[0154] Exemplarily, a stop word list can be stored in the computing device, or the computing device can request the database to obtain the stop word list. The computing device can determine the stop words in the initial data according to the stop word list and remove these stop words from the initial data.

[0155] The computing device can perform word segmentation processing on the initial data to split the initial data into individual words or phrases, so as to facilitate the computing device to quickly perform keyword extraction processing on the initial data in the future. For example, if the initial data is "5 nodes execute in parallel", after word segmentation processing, two phrases "5 nodes" and "execute in parallel" can be obtained.

[0156] Morphological processing may include stemming processing and / or lemmatization processing. By performing morphological processing on each word in the initial data, the computing device can restore each word to its most primitive form to reduce the inflected forms of each word, facilitating subsequent keyword extraction processing on the initial data. For example, after performing morphological processing on the word "nodes", its most primitive form "node" can be obtained.

[0157] S404. The computing device performs keyword extraction processing on the preprocessed data to obtain multiple process indication messages.

[0158] The multiple indication messages include multiple process indication messages.

[0159] Optionally, a keyword extraction algorithm may be used to perform keyword extraction processing on the preprocessed data or the initial data. Exemplarily, the keyword extraction algorithm may include at least one of the following: Term Frequency-Inverse Document Frequency (TF-IDF), TextRank algorithm, or Rapid Automatic Keyword Extraction (RAKE).

[0160] The TF-IDF algorithm can be used to measure the importance of a word. The algorithm can determine the importance of the word in the document by calculating the frequency of the word in the document (Term Frequency, TF); the algorithm can also determine the general importance of the word in the document set composed of multiple documents by calculating the inverse frequency of the word in the document set (Inverse Document Frequency, IDF).

[0161] The TextRank algorithm is improved from the PageRank algorithm. It can extract keywords by constructing a word graph and calculating the importance of each node in the word graph.

[0162] The RAKE algorithm can quickly identify keywords in the text based on phrase co-occurrence relationships and summary features and extract these keywords.

[0163] Optionally, keyword extraction processing on the preprocessed data can also be performed through a keyword extraction model.

[0164] In some examples, the computing device can identify specific type entities in the preprocessed data or the initial data through a Named Entity Recognition (NER) model. For example, these specific type entities may include person names, place names, or organization names, etc.

[0165] In some embodiments, the computing device may also perform dependency parsing and syntactic analysis on the preprocessed data or the initial data through a dependency analysis model to determine the core components such as the subject, predicate, and object of each sentence in the preprocessed data or the initial data, and extract key verbs, nouns, etc. from these core components.

[0166] In some embodiments, the computing device may also perform keyword extraction processing on the preprocessed data or the initial data through a deep learning model. Exemplarily, a pre-trained language model may be run in the computing device, and this pre-trained language model can capture complex language patterns and semantic information, and it can accurately identify keywords in the preprocessed data or the initial data through context understanding and attention mechanisms. For example, the pre-trained language model may be a Bidirectional Encoder Representations from Transformers (BERT) model or a Generative Pre-Trained Transformer (GPT) model.

[0167] This process generation method preprocesses and performs keyword extraction processing on the initial data, which is beneficial to removing useless data in the initial data, reducing the amount of data to be processed in the subsequent process of generating job flow configuration data, improving data processing efficiency, and thus being beneficial to improving the generation efficiency of job flow configuration data.

[0168] S405. The computing device determines at least one node type corresponding to multiple nodes, the node association types and the number of nodes corresponding to each node type, and the association relationship between each node according to multiple process indication messages.

[0169] The at least one node type may include at least one of the following: script type, logic type, or task type.

[0170] Nodes of the script type may be used for data processing, and the data processing may include at least one of the following: data storage, data query, or data calculation.

[0171] According to the different execution environments of the nodes, the script type may include at least one of the following sub-script types: Structured Query Language (SQL) type, Python type, or shell type. In actual application, nodes of an adapted sub-script type can be selected according to the execution environment of the nodes required for the target task. For example, when the execution environment is an SQL language environment, SQL type nodes can be selected; when the execution environment is a Python language environment, Python type nodes can be selected; when the execution environment is a shell language environment, shell type nodes can be selected.

[0172] Nodes of the logical type can be used for logical judgment processing. For example, in a scenario where it is necessary to determine whether to execute a data development node based on the output results of two SQL nodes, a logical-type node can be added after the two SQL nodes.

[0173] According to the different judgment methods of the logical-type nodes, the logical type can include at least one of the following: the type based on the output result of the node and the type based on the logical relationship judgment. Exemplarily, the type based on the output result of the node can include the Switch type, and the type based on the logical relationship judgment can include the Conditions type. The logical relationship can include at least one of the following three relationships: AND, OR, NOT.

[0174] Suppose there are a first node, a second node, a third node, and a logical node. If the logical node needs to determine whether to execute the third node based on the output results of the first node and the second node, the type of this logical node can be the type based on the output result of the node. If the logical node needs to determine whether to execute the third node based on the logical relationship between the first node and the second node, the type of this logical node can be the type based on the logical relationship judgment.

[0175] Nodes of the task type can be used for collaborative task processing. Nodes of the task type can cooperate to process tasks by calling multiple nodes or multiple scripts. The task type can include at least one of the following: development type or dependency type. Among them, nodes of the development type can cooperate to execute data development tasks or code development tasks by calling multiple nodes or multiple scripts, and nodes of the dependency type can depend on other nodes to cooperate in processing tasks.

[0176] The number of nodes can be 1 or more, and more than 1 includes 2 and more than 2.

[0177] The node association type can include at least one of the following: data source, execution environment, message notification policy, timeout policy, or execution frequency.

[0178] When performing data processing, nodes of the SQL type can obtain data through the data source. The node association type corresponding to the SQL type can include the data source. Exemplarily, the data source can include a population database data source and a marital status data source.

[0179] Exemplarily, the execution environment can include: SQL language environment, Python language environment, and shell language environment.

[0180] The message notification policy can be used to indicate the specific operations of the node during the message notification process.

[0181] The timeout policy can be used to indicate the specific operations of the node in case of node processing timeout.

[0182] In some embodiments, "execution frequency" and "execution cycle" can be interchanged, and the execution frequency or execution cycle can be used to indicate how often a node executes.

[0183] For any two nodes (node 1 and node 2), the association relationship between these two nodes can be in the following situations:

[0184] Situation 1: Node 1 and node 2 are connected in parallel. In this case, node 1 and node 2 execute in parallel. For example, node 1 and node 2 can be Figure 3 type A node 1 and type A node 2 in

[0185] Situation 2: Node 1 and node 2 are connected in series. In this case, the connection sequence between node 1 and node 2 can be determined according to the execution sequence between node 1 and node 2.

[0186] If node 1 executes before node 2, then node 1 is connected before node 2. For example, node 1 and node 2 can be Figure 3 type A node 2 and a judgment node in

[0187] If node 1 executes after node 2, then node 1 is connected after node 2. For example, node 1 and node 2 can be Figure 3 a data development node and a judgment node in

[0188] S406. The computing device generates job flow configuration data according to the association relationship, at least one node type, and the node association type and node quantity corresponding to each node type.

[0189] In some embodiments, the computing device can generate node configuration data according to at least one node type, and the node association type and node quantity corresponding to each node type. The node configuration data is used to generate multiple nodes displayed in a canvas displayed on a terminal; generate relationship configuration data according to the node configuration data and the association relationship, and the relationship configuration data is used to generate the connection relationship between each node displayed in the canvas displayed on the terminal; generate job flow configuration data according to the node configuration data and the relationship configuration data.

[0190] The node configuration data can include at least one of the following configuration parameters: the identity (Identity document, ID) of the node, the identity of the task executed by the node (including the task name and / or task number), the execution environment, the data source, the node content, the judgment condition, the code name, the code configuration, the dependent job identity, the task identity within the dependent job, the judgment condition, the task identity corresponding to the condition, the logical condition, the logical node identity, the failed node identity, or the successful node identity.

[0191] For any two nodes among multiple nodes corresponding to an operation process: a first node and a second node, the relationship configuration data can be used to indicate that the first node is an upstream node or a downstream node of the second node. The relationship configuration data can include the node identifier and the association relationship identifier of the first node, as well as the node identifier and the association relationship identifier of the second node. The association relationship identifier can be used to indicate whether the node is an upstream node or a downstream node.

[0192] The data formats of the node configuration data and the relationship configuration data can be in the format of JS key-value pairs (JavaScript Object Notation, JSON), or in other data formats. The embodiments of the present application do not limit the data formats of the node configuration data and the relationship configuration data.

[0193] It should be noted that the process of generating the node configuration data corresponding to the nodes of each node type is the same. In Figure 6 the following, taking the generation of the node configuration data corresponding to the nodes of any one node type as an example, the process of generating the node configuration data corresponding to the nodes of each node type will be described in detail.

[0194] The process generation method can quickly determine at least one node type corresponding to multiple nodes, the node association types and the number of nodes corresponding to each node type, and the association relationships between each node according to multiple process indication information; and quickly generate node configuration data according to at least one node type and the node association types and the number of nodes corresponding to each node type; and quickly generate relationship configuration data according to the node configuration data and the association relationships; and then obtain the operation process configuration data by performing an assembly process on the node configuration data and the relationship configuration data. This process does not require manual intervention by the user, reduces the operation complexity of the user, makes the generation process of the node configuration data, the relationship configuration data and the operation process configuration data more convenient and intelligent, and is beneficial to improving the generation efficiency of the operation process.

[0195] S407. The computing device generates an operation process according to the operation process configuration data.

[0196] S408. The computing device sends the operation process to the terminal.

[0197] It should be noted that the specific execution processes of steps S407 and S408 can refer to the specific execution processes of steps S407 and S408, and will not be elaborated here.

[0198] S409. The terminal displays the operation process.

[0199] In some embodiments, a process orchestration tool may be run in the terminal. The process orchestration tool may include a configuration control, a process orchestration component, and a canvas for orchestrating a job process. The terminal may display the job process in the canvas.

[0200] In some embodiments, the user may also manually update the job process displayed in the canvas based on the configuration control and the process orchestration component in the process orchestration tool. Alternatively, the user may also update the job process by performing steps S410 to S414 as shown below.

[0201] In some embodiments, the configuration control of the process orchestration tool may include a publishing control. When the user determines that the job process does not need to be updated, the user may trigger the publishing component in the process orchestration tool through the terminal. The terminal may respond to the trigger operation of the publishing component and send the job process to the corresponding computing node to execute the job process through the computing node.

[0202] S410. The terminal obtains update data input by the user.

[0203] The update data may be used to indicate an update to the job process.

[0204] The update data may be voice data or text data. If the update data is voice data, the voice data may be converted into text data.

[0205] Exemplarily, the update data may be "add a shell node to the generated job process, and the shell node executes in parallel with the generated SQL node, python node, and shell node".

[0206] It should be noted that the process by which the terminal obtains the update data input by the user may refer to the process by which the terminal obtains the initial data input by the user in step S401, and will not be elaborated here.

[0207] S411. The terminal sends the update data to the computing device.

[0208] The computing device may obtain the update data sent by the terminal.

[0209] S412. The computing device determines multiple update process indication messages based on the update data.

[0210] The multiple update process indication messages may be used to indicate an update to at least one node and / or the association relationship of at least one node in the job process.

[0211] In some embodiments, the computing device may preprocess the update data and perform keyword extraction processing to obtain a plurality of update process indication messages. It should be noted that the preprocessing and keyword extraction processing of the update data by the computing device may refer to the above-mentioned preprocessing and keyword extraction processing of the initial data by the computing device, and will not be elaborated here.

[0212] S413. The computing device updates the job process according to the plurality of update process indication messages to obtain an updated job process.

[0213] The update processing of the job process may include at least one of the following: adding a node to the job process and adding an association relationship between the added node and the existing nodes in the job process; modifying or deleting an existing node in the job process; adding, modifying, or deleting the association relationship between the existing nodes in the job process.

[0214] In some embodiments, the computing device may regenerate the node configuration data and the relationship configuration data according to the plurality of update process indication messages and the job process configuration data corresponding to the job process; generate updated job process configuration data based on the regenerated node configuration data and relationship configuration data; and generate an updated job process based on the updated job process configuration data.

[0215] S414. The computing device sends the updated job process to the terminal.

[0216] The terminal may display the updated job process on the canvas of the process orchestration tool. When the user determines that the updated job process does not need to be updated, the terminal may send the updated job process to the corresponding computing node to execute the updated job process through the computing node.

[0217] In this process generation method, after obtaining the update data, the terminal may also interact with the computing device to enable the computing device to automatically update the generated job process based on the update data, so that the job process can be executed more smoothly and effectively. In the above update process, the manual intervention of the user is reduced, the operation complexity of the user is reduced, the workload of the user is reduced, it is beneficial to avoid the inconsistency problems caused by different user configurations during the process update, and the process update efficiency is improved.

[0218] In the process generation method provided by the embodiments of the present application, after the terminal obtains the initial data input by the user, the terminal can interact with the computing device to quickly and accurately generate the job process corresponding to the initial data, reduce the manual intervention in the process of generating the job process, reduce the operation complexity of the user, help reduce the workload of the user, and avoid the problems of long process generation cycle and large investment caused by the workload and multi-team configuration in the process generation process, making the process of generating and updating the job process more intelligent, which is conducive to improving the process generation efficiency and process update efficiency.

[0219] Next, in conjunction with Figure 6 , the process of the computing device generating the job process configuration data based on multiple process indication information will be described in detail.

[0220] Figure 6 FIG. 3 is a schematic flowchart of the process generation method provided by the embodiments of the present application. It should be noted that this method can be executed by the computing device in the Figure 1 embodiment, or can also be executed by the process generation device set in the computing device. The process generation device can be implemented by software or by a combination of software and hardware.

[0221] Please refer to Figure 6 , and the method can specifically include the following steps:

[0222] S601. Determine at least one node type corresponding to multiple nodes, the node association type and the number of nodes corresponding to each node type, and the association relationship between each node according to multiple process indication information.

[0223] In some embodiments, developers can pre-configure the keywords and first configuration parameters corresponding to multiple node types, the keywords and second configuration parameters corresponding to multiple node association types, the keywords and third configuration parameters corresponding to the number of nodes, and the keywords and fourth configuration parameters corresponding to the association relationship in the configuration file according to business requirements. For example, the configuration file can be as shown in Table 1.

[0224] Table 1

[0225]

[0226]

[0227] In some embodiments, the computing device can perform matching processing between multiple process indication information and multiple keywords in the configuration file to obtain at least one node type corresponding to multiple process indication information, the node association type and the number of nodes corresponding to each node type, and the association relationship between the nodes of each node type.

[0228] S602. Generate node configuration data according to at least one node type, and the node association type and the number of nodes corresponding to each node type.

[0229] In some embodiments, for any node type, the node configuration data can be generated according to the node type, the node association type corresponding to the node type, and the number of nodes corresponding to the node type by performing steps S6021 and S6022 as shown below.

[0230] S6021. For any node type, determine the first configuration parameter of the node type, the second configuration parameter of the node association type corresponding to the node type, and the third configuration parameter of the number of nodes corresponding to the node type, and generate the sub-node configuration data corresponding to the node type according to the first configuration parameter, the second configuration parameter, and the third configuration parameter.

[0231] In some embodiments, the computing device can query the first configuration parameter corresponding to each node type, the second configuration parameter corresponding to each node association type, and the third configuration parameter corresponding to each number of nodes in the configuration file.

[0232] For example, in the configuration file described in Table 1, the node type is SQL type, and the first configuration parameter may include: component type, node identifier, task identifier executed by the node, execution environment, data source, SQL content; the node association type is data source, and the second configuration parameter may include: data source type, data source link name, data source database name, data source schema name; the number of nodes is 2, and the third configuration parameter may include: circularly increment the node configuration data of the current configured node, and the number of loops is 1.

[0233] In some embodiments, the developer can also pre-create a method for generating node configuration data. For example, the method for generating node configuration data can be the CreatedNode() method. The computing device can call the method for generating node configuration data to generate node configuration data according to the first configuration parameter, the second configuration parameter, and the third configuration parameter.

[0234] In this process generation method, the computing device can call the method for generating node configuration data to quickly generate node configuration data without manual intervention by the user, reducing the operation complexity of the user, making the generation process of relationship configuration data more convenient and intelligent, facilitating the improvement of the generation efficiency of relationship configuration data, and further facilitating the improvement of the generation efficiency of the job process.

[0235] For example, assume that multiple process indication messages include: an SQL node, data sources 1 and 2. Then, the following information can be determined: the node type is of the SQL type, the node association type is a data source, and the number of nodes is 2. The computing device can generate node configuration data with reference to the following steps: (1) Query the configuration file shown in Table 1 to obtain the second configuration parameter corresponding to the data source, and generate the configuration data corresponding to data source 1 according to the second configuration parameter and a preset assembly template; (2) Query the configuration file shown in Table 1 to obtain the first configuration parameter corresponding to the SQL type, and generate the sub-node configuration data 1 corresponding to the SQL node according to the configuration data corresponding to data source 1, this first configuration parameter, and the preset assembly template; (3) Query the configuration file shown in Table 1 to obtain that the third configuration parameter corresponding to the number 2 is "circulate and increment the node configuration data of the current configured node, and the number of circulations is 1". The computing device can, on the basis of the node configuration data corresponding to the SQL node, add a sub-node configuration data corresponding to the SQL node to obtain 2 sub-node configuration data corresponding to 2 SQL nodes.

[0236] S6022. Generate node configuration data according to at least one sub-node configuration data corresponding to at least one node type.

[0237] The computing device can perform an assembly process on at least one sub-node configuration data according to a preset assembly rule to obtain the node configuration data.

[0238] The process generation method provided by the embodiments of the present application can perform parsing processing on initial data to obtain multiple process indication messages, and determine at least one node type corresponding to multiple nodes, the node association type corresponding to each node type, and the number of nodes according to the multiple process indication messages; and then generate standardized node configuration data according to the first configuration parameter corresponding to each node type in the configuration file, the second configuration parameter corresponding to the node association type of each node type, and the third configuration parameter corresponding to the number of nodes, so as to avoid the problem that the generated node configuration data has low compatibility or low standardization due to different operations of users when generating the node configuration data.

[0239] S603. Generate relationship configuration data according to the node configuration data and the association relationship.

[0240] In some embodiments, the computing device can generate the relationship configuration data according to the fourth configuration parameter corresponding to the association relationship and the node configuration data.

[0241] In some embodiments, a developer can pre-create a method for generating relationship configuration data. For example, this method for generating relationship configuration data can be the LinkNode() method. The computing device can also call this method for generating relationship configuration data to generate the corresponding relationship configuration data according to the node configuration data and the association relationship.

[0242] In this process generation method, the computing device can call the relationship configuration data generation method to quickly generate relationship configuration data without manual intervention by the user, reducing the operation complexity of the user, making the generation process of the relationship configuration data more convenient and intelligent, facilitating the improvement of the generation efficiency of the relationship configuration data, and further facilitating the improvement of the generation efficiency of the job process.

[0243] It can be understood that if multiple users are involved in the generation process of the job process, when using the drag-and-drop method to generate the job process, problems such as low compatibility or low standardization may occur in the generated job process due to different operations of different users. To solve the above problems, the process generation method provided in the embodiments of the present application can parse the initial data to obtain multiple process indication messages, and based on the multiple process indication messages, parse at least one node type corresponding to multiple nodes, the node association types and the number of nodes corresponding to each node type, and the association relationship between each node; and then generate standardized node configuration data and relationship configuration data according to the first configuration parameter corresponding to each node type in the configuration file, the second configuration parameter corresponding to the node association type of each node type, the third configuration parameter corresponding to the number of nodes, and the fourth configuration parameter corresponding to the association relationship, and assemble the standardized job process configuration data based on the node configuration data and the relationship configuration data, so as to avoid the problem that the job process generation fails due to low compatibility or low standardization when generating the job process based on the job process configuration data subsequently, facilitating the acceleration of the generation efficiency of the job process and the improvement of the accuracy of the job process generation.

[0244] S604. Generate job process configuration data according to the node configuration data and the relationship configuration data.

[0245] In some embodiments, the computing device can fill the node configuration data and the relationship configuration data into a configuration template of a preset job process configuration data to obtain the job process configuration data.

[0246] For the process generation method provided in the embodiments of the present application, the computing device can quickly determine at least one node type corresponding to multiple nodes, the node association types and the number of nodes corresponding to each node type, and the association relationship between each node according to multiple process indication messages; and quickly generate node configuration data according to at least one node type and the node association types and the number of nodes corresponding to each node type; and quickly generate relationship configuration data according to the node configuration data and the association relationship; and then obtain the job process configuration data through an assembly process on the node configuration data and the relationship configuration data. This process does not require manual intervention by the user, reducing the operation complexity of the user, making the generation processes of the node configuration data, the relationship configuration data, and the job process configuration data more convenient and intelligent, and facilitating the improvement of the generation efficiency of the job process.

[0247] Figure 7 This is a process schematic diagram of a process generation method provided by an embodiment of the present application. Please refer to Figure 7 , the terminal can interact with the computing device to implement the generation process of the job flow. The terminal can display a dialogue interface for generating the job flow, and the dialogue interface can include an input box through which the user can input the initial data to the terminal. It can be understood that Figure 7 the terminals shown in

[0248] can be the same. Exemplarily, the initial data can be "Schedule an executable job, the content of the job includes 2 SQL nodes, 2 python nodes, and 1 shell node, and these 5 nodes are executed in parallel. The data sources of the SQL nodes are the population database data source and the marriage situation data source respectively. After the 5 nodes are executed in parallel successfully, it is judged whether to execute the data development node according to the running results of the two SQL nodes".

[0249] The computing device can also generate node configuration data and relationship configuration data according to these multiple process indication information. The node configuration data can include 7 sub-node configuration data corresponding to 7 nodes, and the relationship configuration data can include 6 sub-relationship configuration data. Exemplarily, these 7 sub-node configuration data and 6 sub-relationship configuration data can be as shown in Table 2.

[0250] Table 2

[0251]

[0252] The computing device can also generate job flow configuration data according to the node configuration data and the relationship configuration data, and call the process generation method to generate the corresponding job flow through the job flow configuration data, and send the job flow to the terminal.

[0253] The terminal can output the reply information corresponding to the initial data in the dialogue interface, and the reply information can be "The job flow has been generated. Please click the following link to view the generated job flow: Link 1". The terminal can also respond to the triggering operation of the user on Link 1 in the dialogue interface, and jump from the dialogue interface to the process choreography interface where the canvas for displaying the job flow is located.

[0254] The process generation method provided by the embodiments of this application enables users to generate a job process based on a dialogue interface for generating a job process displayed on a terminal, making it convenient and fast for users to generate a job process, reducing the operation complexity of users, alleviating the workload of users, and improving the efficiency of job process generation.

[0255] Figure 8 Please refer to the structure schematic diagram of a process generation device provided by the embodiments of this application. Figure 8 The process generation device 10 may include:

[0256] A transceiver module 11, configured to obtain initial data sent by a terminal, where the initial data is used to indicate generating a job process, and the job process is used to execute a target task;

[0257] A processing module 12, configured to determine multiple process indication messages based on the initial data, where the multiple process indication messages are used to indicate multiple nodes corresponding to the target task and the association relationship between each node;

[0258] The processing module 12 is further configured to generate job process configuration data according to the multiple process indication messages, where the job process configuration data is used to generate a job process displayed in a canvas displayed on the terminal, and the job process includes multiple nodes and the association relationship between each node;

[0259] The processing module 12 is further configured to generate a job process according to the job process configuration data;

[0260] The transceiver module 11 is further configured to send the job process to the terminal.

[0261] In a possible implementation manner, the processing module 12 is specifically configured to:

[0262] According to the multiple process indication messages, determine at least one node type corresponding to the multiple nodes, the node association type and the number of nodes corresponding to each node type, and the association relationship between each node, where the node association type includes at least one of the following: data source, execution environment, message notification policy, timeout policy, or execution frequency;

[0263] Generate job process configuration data according to the association relationship, at least one node type, and the node association type and the number of nodes corresponding to each node type.

[0264] In a possible implementation manner, the processing module 12 is further specifically configured to:

[0265] Generate node configuration data according to at least one node type and the node association type and the number of nodes corresponding to each node type, where the node configuration data is used to generate multiple nodes displayed in a canvas displayed on the terminal;

[0266] Generate relationship configuration data according to the node configuration data and the association relationship, where the relationship configuration data is used to generate the connection relationships between the various nodes displayed in the canvas displayed on the terminal;

[0267] Generate job flow configuration data according to the node configuration data and the relationship configuration data.

[0268] In a possible implementation, the processing module 12 is further specifically configured to:

[0269] For any node type, determine the first configuration parameter of the node type, the second configuration parameter of the node association type corresponding to the node type, and the third configuration parameter of the number of nodes corresponding to the node type, and generate the sub-node configuration data corresponding to the node type according to the first configuration parameter, the second configuration parameter, and the third configuration parameter;

[0270] Generate node configuration data according to at least one sub-node configuration data corresponding to at least one node type.

[0271] In a possible implementation, at least one node type includes at least one of the following:

[0272] Script type, where the nodes of the script type are used for data processing, and the script type includes at least one of the following: Structured Query Language SQL type, Python type, or shell type;

[0273] Logic type, where the nodes of the logic type are used for logical judgment processing, and the logic type includes at least one of the following: the type based on the node output result judgment and the type based on the logical relationship judgment;

[0274] Task type, where the nodes of the task type are used for collaborative task processing, and the task type includes at least one of the following: development type or dependency type.

[0275] In a possible implementation, the processing module 12 is further specifically configured to:

[0276] Preprocess the initial data to obtain preprocessed data, where the preprocessed data includes multiple indication messages corresponding to the job flow, and the preprocessing includes at least one of the following: stop word processing, word segmentation processing, or word form processing;

[0277] Perform keyword extraction processing on the preprocessed data to obtain multiple process indication messages, where the multiple indication messages include multiple process indication messages.

[0278] In a possible implementation, in the case where the keyword extraction processing of the preprocessed data fails, the transceiver module 11 is further configured to send a prompt message to the terminal, where the prompt message is used to prompt to input correct initial data.

[0279] In one possible implementation, the prompt information includes reference data, the reference data is used to generate a reference operation process, the reference data includes reference process indication information corresponding to the reference operation process, the reference operation process is used to execute a reference task, and the reference process indication information is used to indicate multiple reference nodes corresponding to the reference task and reference association relationships between each reference node.

[0280] In a possible implementation, after the operation flow is generated, the transceiver module 11 is further used to obtain update data sent by the terminal, where the update data is used to indicate the update of the operation flow;

[0281] The processing module 12 is further used to determine a plurality of update process indication information based on the update data, wherein the plurality of update process indication information is used to indicate to update at least one node and / or an association relationship of at least one node in the operation process;

[0282] The processing module 12 is further used to update the operation process according to the multiple update process indication information to obtain an updated operation process;

[0283] The transceiver module 11 is also used to send the updated operation flow to the terminal.

[0284] The process generation device provided in the embodiment of the present application can execute the technical solution implemented by the computing device in the above method embodiment, and its beneficial effects are similar and will not be repeated here.

[0285] Figure 9 A hardware structure diagram of a computing device provided in an embodiment of the present application. Figure 9 The computing device 20 may be the computing device in the above method embodiment, and may include a processor 21 and a memory 22, wherein the processor 21 and the memory 22 are coupled. The processor 21 and the memory 22 may communicate; illustratively, the processor 21 and the memory 22 communicate via a communication bus 23.

[0286] The memory 22 is used to store program instructions;

[0287] The processor 21 is used to execute program instructions to perform the technical solution shown in the above method embodiment.

[0288] Optionally, the computing device 20 may further include a communication interface, which may include a transmitter and / or a receiver.

[0289] Optionally, the above-mentioned processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in the embodiments of the present application can be directly implemented by a hardware processor, or can be implemented by a combination of hardware and software modules in the processor.

[0290] The embodiments of the present application provide a computer-readable storage medium, on which computer-executable instructions are stored; when the computer-executable instructions are executed by a processor, they are used to implement the process generation method as described in the above embodiments.

[0291] The embodiments of the present application provide a computer program product, which includes a computer program. When the computer program is executed by a processor, the computer is enabled to execute the process generation method described in the above embodiments.

[0292] All or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions. The foregoing program can be stored in a readable memory. When the program is executed, it executes the steps including the above method embodiments; and the foregoing memory (storage medium) includes: read-only memory (abbreviation: ROM), RAM, flash memory, hard disk, solid-state drive, magnetic tape, floppy disk, optical disc, and any combination thereof.

[0293] The embodiments of the present application are described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, and the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processing unit of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable devices to generate a machine, so that the instructions executed by the processing unit of the computer or other programmable devices generate a device for implementing the specified functions in one process Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0294] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable device to operate in a particular manner, such that the instructions stored in the computer-readable memory produce a manufacture including an instruction device that implements the functions specified in one or more of the processes Figure 1 and / or boxes Figure 1 of one or more of the processes and / or boxes.

[0295] These computer program instructions can also be loaded onto a computer or other programmable device, such that a series of operational steps are performed on the computer or other programmable device to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more of the processes Figure 1 and / or boxes Figure 1 of one or more of the boxes.

[0296] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the embodiments of the present application, and are not intended to limit them; although the embodiments of the present application have been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A process generation method, characterized in that: The method comprises: Acquire initial data sent by the terminal, wherein the initial data is used to instruct generation of an operation flow, and the operation flow is used to execute a target task; Determine a plurality of process indication information based on the initial data, wherein the plurality of process indication information is used to indicate a plurality of nodes corresponding to the target task and an association relationship between each of the nodes; Generate operation process configuration data according to the plurality of process indication information, wherein the operation process configuration data is used to generate an operation process displayed in a canvas displayed on the terminal, wherein the operation process includes the plurality of nodes and associations between the nodes; The operation flow is generated according to the operation flow configuration data, and the operation flow is sent to the terminal.

2. The method according to claim 1, characterized in that Generating operation process configuration data according to the plurality of process indication information includes: Determine, according to the plurality of process indication information, at least one node type corresponding to the plurality of nodes, a node association type and a number of nodes corresponding to each node type, and an association relationship between the nodes, wherein the node association type includes at least one of the following: a data source, an execution environment, a message notification strategy, a timeout strategy, or an execution frequency; The job flow configuration data is generated according to the association relationship, the at least one node type, and the node association type and the node quantity corresponding to each node type.

3. The method according to claim 2, characterized in that Generating the job flow configuration data according to the association relationship, the at least one node type, and the node association type and node quantity corresponding to each node type, including: Generate node configuration data according to the at least one node type, and the node association type and node quantity corresponding to each node type, wherein the node configuration data is used to generate a plurality of nodes displayed in a canvas displayed by the terminal; Generate relationship configuration data according to the node configuration data and the association relationship, wherein the relationship configuration data is used to generate a connection relationship between each node displayed in a canvas displayed by the terminal; The job flow configuration data is generated according to the node configuration data and the relationship configuration data.

4. The method according to claim 3, characterized in that Generate node configuration data according to the at least one node type, the node association type corresponding to each node type, and the number of nodes, including: For any node type, determine a first configuration parameter of the node type, a second configuration parameter of the node association type corresponding to the node type, and a third configuration parameter of the number of nodes corresponding to the node type, and generate subnode configuration data corresponding to the node type according to the first configuration parameter, the second configuration parameter, and the third configuration parameter; The node configuration data is generated according to at least one sub-node configuration data corresponding to the at least one node type.

5. The method according to any one of claims 2 to 4, characterized in that: The at least one node type includes at least one of the following: A script type, wherein a node of the script type is used for data processing, and the script type includes at least one of the following: a structured query language SQL type, a Python type, or a shell type; A logic type, where a node of the logic type is used for logic judgment processing, and the logic type includes at least one of the following: a type based on node output result judgment and a type based on logical relationship judgment; A task type, a node of the task type is used for collaborative task processing, and the task type includes at least one of the following: a development type or a dependency type.

6. The method according to any one of claims 1 to 5, characterized in that: Determining a plurality of process indication information based on the initial data includes: Preprocessing the initial data to obtain preprocessed data, wherein the preprocessed data includes a plurality of indication information corresponding to the operation flow, and the preprocessing includes at least one of the following: stop word processing, word segmentation processing, or word form processing; Keyword extraction processing is performed on the pre-processed data to obtain the multiple process indication information, and the multiple indication information includes the multiple process indication information.

7. The method according to claim 6, characterized in that In the case where the keyword extraction process of the preprocessed data fails, the method further includes: Sending prompt information to the terminal, wherein the prompt information is used to prompt input of correct initial data.

8. The method according to claim 7, characterized in that The prompt information includes reference data, the reference data is used to generate a reference operation process, the reference data includes reference process indication information corresponding to the reference operation process, the reference operation process is used to execute a reference task, and the reference process indication information is used to indicate multiple reference nodes corresponding to the reference task and the reference association relationship between each reference node.

9. The method according to any one of claims 1 to 8, characterized in that: After generating the operation flow, the method further includes: Acquire update data sent by the terminal, wherein the update data is used to indicate updating of the operation process; Determining a plurality of update process indication information based on the update data, wherein the plurality of update process indication information is used to indicate updating at least one node in the job process and / or an association relationship of the at least one node; According to the plurality of update process indication information, the operation process is updated to obtain an updated operation process; The updated operation flow is sent to the terminal.

10. A computing device, characterized in that include: Processor and memory; The processor is coupled to the memory; The memory is used to store program instructions; The processor is used to execute the program instructions to implement the method according to any one of claims 1 to 9.

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