CN117573320A - Task node execution method and device, storage medium and electronic device - Google Patents
Task node execution method and device, storage medium and electronic device Download PDFInfo
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Abstract
The application discloses a task node execution method, a task node execution device, a storage medium and an electronic device, and relates to the technical field of smart families, wherein the task node execution method comprises the following steps: determining N task flows to be executed, and determining M task nodes carried in each task flow; inputting N.M task nodes into a preset blood edge database, and determining data blood edge information corresponding to the N.M task nodes, wherein N, M is a positive integer; under the condition that the target task node exists in at least one task flow, the dependency relationship of the target task node is determined based on the data blood-edge information, so that the execution time of the target task node is determined according to the dependency relationship.
Description
Technical Field
The application relates to the technical field of smart families, in particular to a task node execution method, a task node execution device, a storage medium and an electronic device.
Background
With the increase of platform users, various services are continuously increased, naturally, the data to be processed by the platform and the tasks corresponding to the data are more and more, the service and service association is more and more compact and huge, for each platform developer user, more and more service data tables, tasks and service logic association between the tables, the task and the task cause each person to have challenges on the management of the part responsible for the platform user, and other service data which the platform developer needs to rely on when adding a service data processing flow can be more complicated, and at the moment, the development time is prolonged and omission is easy to occur due to the fact that the user is required to operate and maintain by manpower and set the dependence.
Therefore, aiming at the technical problems that in the related technology, the task flow dependency relationship corresponding to the newly added service data cannot be quickly determined and the dependency relationship determination process is complex, no effective solution has been proposed yet.
Disclosure of Invention
The embodiment of the application provides a task node execution method, a task node execution device, a storage medium and an electronic device, which are used for at least solving the technical problems that in the related technology, task flow dependency relationships corresponding to newly-added service data cannot be quickly determined and the dependency relationship determination process is complex.
According to an embodiment of the embodiments of the present application, there is provided a method for executing a task node, including: determining N task flows to be executed, and determining M task nodes carried in each task flow; inputting N.M task nodes into a preset blood edge database, and determining data blood edge information corresponding to the N.M task nodes, wherein N, M is a positive integer; and under the condition that at least one task flow is determined to have a target task node, determining the dependency relationship of the target task node based on the data blood-source information, so as to determine the execution time of the target task node according to the dependency relationship.
In an exemplary embodiment, determining the execution opportunity of the target task node according to the dependency relationship includes: determining a first execution result corresponding to an auxiliary task node in other task flows except the at least one task flow based on the dependency relationship, and acquiring a second execution result corresponding to a previous task node of a target task node in the at least one task flow, wherein the auxiliary task node is used for providing data support for the target task node; and determining the execution time of the target task node according to the first execution result and the second execution result.
In an exemplary embodiment, determining the execution opportunity of the target task node according to the first execution result and the second execution result includes: when the first execution result indicates that the first task corresponding to the auxiliary task node is successfully completed and the second execution result indicates that the second task corresponding to the previous task node is successfully completed, determining that the execution opportunity of the target task node is a time point corresponding to the execution result acquired at the latest; and under the condition that the first execution result indicates that the first task corresponding to the auxiliary task node fails to complete and/or the second execution result indicates that the second task corresponding to the previous task node fails to complete, initiating a repeated execution flow of the first task and/or the second task which fails to complete, and acquiring an ending time point corresponding to the repeated execution flow to determine the execution time of the target task node as the ending time point.
In an exemplary embodiment, before initiating the repeated execution flow of the first task and/or the second task that fails to complete, the method further includes: determining a target task flow to which the previous task node belongs under the condition that the first task corresponding to the auxiliary task node is determined to be completed successfully and the second execution result indicates that the second task corresponding to the previous task node fails to be completed; generating prompt information carrying the target task flow and the second task, and sending the prompt information to a target object.
In an exemplary embodiment, in a case where it is determined that at least one task flow has a target task node, determining a dependency of the target task node based on the data blood-edge information includes: analyzing the data blood-edge information and determining the association relation between different data; acquiring first data corresponding to the target task node and a plurality of second data corresponding to the target task node and/or other task nodes in a task flow using the first data; determining target second data associated with the first data from the plurality of second data through the association relation; and determining the dependency relationship of the target task node based on the task node corresponding to the target second data.
In an exemplary embodiment, before inputting n×m task nodes into a preset blood edge database and determining data blood edge information corresponding to the n×m task nodes, the method further includes: acquiring historical data of a historical task flow; analyzing and processing the historical data to obtain historical data blood edges of a plurality of task nodes existing in the historical task flow; and adding the historical data blood edges in the preset blood edge database in a preset period.
In an exemplary embodiment, after determining the dependency of the target task node based on the data blood-source information to determine the execution opportunity of the target task node according to the dependency, the method further includes: determining node information of different task nodes in the dependency relationship, wherein the task node information at least comprises: the method comprises the steps that first node information corresponding to an auxiliary task node and second node information corresponding to a previous task node of the target task node are carried, and the node information carries basic information of task flows to which different task nodes belong; and adding the node information in the execution condition of the target task node.
According to another embodiment of the embodiments of the present application, there is also provided an execution apparatus of a task node, including: the first determining module is used for determining N task flows to be executed and determining M task nodes carried in each task flow; the second determining module is used for inputting the N×M task nodes into a preset blood edge database, and determining data blood edge information corresponding to the N×M task nodes, wherein N, M is a positive integer; and the third determining module is used for determining the dependency relationship of the target task node based on the data blood edge information under the condition that the target task node exists in at least one task flow, so as to determine the execution time of the target task node according to the dependency relationship.
According to yet another aspect of the embodiments of the present application, there is also provided a computer readable storage medium having a computer program stored therein, wherein the computer program is configured to execute the execution method of the task node described above when running.
According to still another aspect of the embodiments of the present application, there is further provided an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the execution method of the task node by using the computer program.
In the embodiment of the application, N task flows to be executed are determined, and M task nodes carried in each task flow are determined; inputting N.M task nodes into a preset blood edge database, and determining data blood edge information corresponding to the N.M task nodes, wherein N, M is a positive integer; under the condition that at least one task flow is determined to have a target task node, determining the dependency relationship of the target task node based on the data blood-source information, so as to determine the execution time of the target task node according to the dependency relationship; by adopting the technical scheme, the technical problems that the task flow dependency relationship corresponding to the newly added service data cannot be determined quickly and the dependency relationship determining process is complex are solved, and further task nodes with the dependency relationship among different task flows can be determined when the new task flow is constructed through the preset blood margin database, so that the execution time of a target task with the dependency relationship is related, and the recognition efficiency of the task flow dependency relationship corresponding to the newly added service data is improved.
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The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required to be used in the description of the embodiments or the prior art will be briefly described below, and it will be obvious to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.
FIG. 1 is a schematic diagram of a hardware environment of a method for executing a task node according to an embodiment of the present application;
FIG. 2 is a flow chart of a method of performing a task node according to an embodiment of the present application;
FIG. 3 is a flow chart of a method of performing a task node according to an embodiment of the present application;
FIG. 4 is a block diagram of a task node execution device according to an embodiment of the present application;
fig. 5 is a block diagram (ii) of a task node execution device according to an embodiment of the present application.
Detailed Description
In order to make the present application solution better understood by those skilled in the art, the following description will be made in detail and with reference to the accompanying drawings in the embodiments of the present application, it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, shall fall within the scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that embodiments of the present application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
According to one aspect of the embodiments of the present application, a method for executing a task node is provided. The task node execution method is widely applied to full-house intelligent digital control application scenes such as intelligent Home (Smart Home), intelligent Home equipment ecology, intelligent Home (Intelligence House) ecology and the like. Alternatively, in the present embodiment, the above-described execution method of the task node may be applied to a hardware environment constituted by the terminal device 102 and the server 104 as shown in fig. 1. As shown in fig. 1, the server 104 is connected to the terminal device 102 through a network, and may be used to provide services (such as application services and the like) for a terminal or a client installed on the terminal, a database may be set on the server or independent of the server, for providing data storage services for the server 104, and cloud computing and/or edge computing services may be configured on the server or independent of the server, for providing data computing services for the server 104.
The network may include, but is not limited to, at least one of: wired network, wireless network. The wired network may include, but is not limited to, at least one of: a wide area network, a metropolitan area network, a local area network, and the wireless network may include, but is not limited to, at least one of: WIFI (Wireless Fidelity ), bluetooth. The terminal device 102 may not be limited to a PC, a mobile phone, a tablet computer, an intelligent air conditioner, an intelligent smoke machine, an intelligent refrigerator, an intelligent oven, an intelligent cooking range, an intelligent washing machine, an intelligent water heater, an intelligent washing device, an intelligent dish washer, an intelligent projection device, an intelligent television, an intelligent clothes hanger, an intelligent curtain, an intelligent video, an intelligent socket, an intelligent sound box, an intelligent fresh air device, an intelligent kitchen and toilet device, an intelligent bathroom device, an intelligent sweeping robot, an intelligent window cleaning robot, an intelligent mopping robot, an intelligent air purifying device, an intelligent steam box, an intelligent microwave oven, an intelligent kitchen appliance, an intelligent purifier, an intelligent water dispenser, an intelligent door lock, and the like.
In this embodiment, a method for executing a task node is provided and applied to a computer terminal, and fig. 2 is a flowchart of the method for executing a task node according to an embodiment of the present application, where the flowchart includes the following steps:
step S202, determining N task flows to be executed, and determining M task nodes carried in each task flow;
step S204, inputting N.times.M task nodes into a preset blood edge database, and determining data blood edge information corresponding to the N.times.M task nodes, wherein N, M is a positive integer;
step S206, determining a dependency relationship of the target task node based on the data blood edge information, so as to determine an execution timing of the target task node according to the dependency relationship, if it is determined that the target task node exists in at least one task flow.
Through the steps, N task flows to be executed are determined, and M task nodes carried in each task flow are determined; inputting N.M task nodes into a preset blood edge database, and determining data blood edge information corresponding to the N.M task nodes, wherein N, M is a positive integer; under the condition that at least one task flow is determined to have a target task node, determining the dependency relationship of the target task node based on the data blood-source information, so as to determine the execution time of the target task node according to the dependency relationship; by adopting the technical scheme, the technical problems that the task flow dependency relationship corresponding to the newly added service data cannot be determined quickly and the dependency relationship determining process is complex are solved, and further task nodes with the dependency relationship among different task flows can be determined when the new task flow is constructed through the preset blood margin database, so that the execution time of a target task with the dependency relationship is related, and the recognition efficiency of the task flow dependency relationship corresponding to the newly added service data is improved.
In an exemplary embodiment, for the step S204, the execution timing of the target task node may be determined according to the dependency relationship through the following technical solution, and the specific steps include:
step S21: determining a first execution result corresponding to an auxiliary task node in other task flows except the at least one task flow based on the dependency relationship, and acquiring a second execution result corresponding to a previous task node of a target task node in the at least one task flow, wherein the auxiliary task node is used for providing data support for the target task node;
step S22: and determining the execution time of the target task node according to the first execution result and the second execution result.
Based on the above, when determining the execution opportunity corresponding to the target task node, it is necessary to determine the second execution result of the task node before the target task node and the first execution result of the auxiliary task node corresponding to the other task flows associated with the current task flow with the target task, so that after determining the execution result of the other tasks with the dependency relationship with the target task, the execution opportunity of the target task node can be accurately estimated, thereby ensuring the data consistency in the task flows. In an exemplary embodiment, determining the execution opportunity of the target task node according to the first execution result and the second execution result includes: when the first execution result indicates that the first task corresponding to the auxiliary task node is successfully completed and the second execution result indicates that the second task corresponding to the previous task node is successfully completed, determining that the execution opportunity of the target task node is a time point corresponding to the execution result acquired at the latest; and under the condition that the first execution result indicates that the first task corresponding to the auxiliary task node fails to complete and/or the second execution result indicates that the second task corresponding to the previous task node fails to complete, initiating a repeated execution flow of the first task and/or the second task which fails to complete, and acquiring an ending time point corresponding to the repeated execution flow to determine the execution time of the target task node as the ending time point.
For example, an original set of business process schedules a job a, in which there are 3 node data processing tasks that are sequentially executed, corresponding to A1, A2, and A3, and it is assumed that a new business process B is now being created on a business request, and is also sequentially executed, where the table data used for the B2 task in the new business process B is generated from the A2 task of the job a, that is, the table upstream of the table used for the B2 task is the table of the A2 task. When creating a B2 task, the scheduling system automatically queries the upstream table of the B2 table and the task from the blood-source system. At this time, the scheduling system automatically prompts the upstream and downstream of the node and performs task association processing. Task B2 waits for A2 and B1 to be executed when executing, thereby achieving data accuracy.
Optionally, in the case where any one of the A2 and/or B1 is not executed completely, if the task B2 is executed, new data will be generated after the completion of the incomplete execution of the A2 and/or B1, so that the data used by the task B2 in executing is not accurate enough, and therefore, the incomplete A2 and/or B1 needs to be executed repeatedly, and the time when the execution is completed successfully is monitored.
In an exemplary embodiment, before initiating the repeated execution flow of the first task and/or the second task that fails to complete, the method further includes: determining a target task flow to which the previous task node belongs under the condition that the first task corresponding to the auxiliary task node is determined to be completed successfully and the second execution result indicates that the second task corresponding to the previous task node fails to be completed; generating prompt information carrying the target task flow and the second task, and sending the prompt information to a target object.
In short, before the target task node executes, the information of the task flow corresponding to the unfinished task and the information of the task can be combined into prompt information, and the target object is prompted to the effect of which task flow and which task the execution of the single target task node is affected by through the prompt information, so that the target object can accurately position the corresponding task to process, and the target task node can start executing under the condition that the auxiliary task node and the previous thought node are successfully completed.
In an exemplary embodiment, in a case where it is determined that at least one task flow has a target task node, determining a dependency of the target task node based on the data blood-edge information includes: analyzing the data blood-edge information and determining the association relation between different data; acquiring first data corresponding to the target task node and a plurality of second data corresponding to the target task node and/or other task nodes in a task flow using the first data; determining target second data associated with the first data from the plurality of second data through the association relation; and determining the dependency relationship of the target task node based on the task node corresponding to the target second data.
The dependency relationship among task nodes using different data is determined through the blood-edge relationship among the different data, so that the influence of the task among the task nodes on the execution of the current task and the specific condition that the data of the execution of the current task influence other tasks can be determined, and the dependency relationship among the task nodes can be constructed through the association relationship among the different data on the basis of the data blood-edge relationship.
In an exemplary embodiment, before inputting n×m task nodes into a preset blood edge database and determining data blood edge information corresponding to the n×m task nodes, the method further includes: acquiring historical data of a historical task flow; analyzing and processing the historical data to obtain historical data blood edges of a plurality of task nodes existing in the historical task flow; and adding the historical data blood edges in the preset blood edge database in a preset period.
In an exemplary embodiment, after determining the dependency of the target task node based on the data blood-source information to determine the execution opportunity of the target task node according to the dependency, the method further includes: determining node information of different task nodes in the dependency relationship, wherein the task node information at least comprises: the method comprises the steps that first node information corresponding to an auxiliary task node and second node information corresponding to a previous task node of the target task node are carried, and the node information carries basic information of task flows to which different task nodes belong; and adding the node information in the execution condition of the target task node.
It can be understood that, in order to make the execution of the target task node more accurate, after determining the relationships between different task nodes and the previous task node and the corresponding auxiliary node, node information corresponding to the previous task node and the corresponding auxiliary node respectively may be obtained, and the node information is set as an execution condition corresponding to the target task node, so that the target task node cannot initiate the execution under the condition that the node information is not satisfied, and the ensured stability of the execution of the target task node is determined.
In order to better understand the process of the execution method of the task node, the following describes the implementation method flow of the execution of the task node in combination with the alternative embodiment, but is not limited to the technical solution of the embodiment of the present application.
In the related technology, with the increase of platform users and the continuous growth of various services, the service and service association are tighter and more huge, at this time, the developer needs to comb and clear the association between each service and service table to reduce the error probability as much as possible during development, but the more complex the service, the higher the requirement on the developer, the more carefully each task dependency is processed, so that the development period is greatly increased.
In addition, each task dependency relationship requires a developer to manually enter an upstream and downstream blood-edge table and then perform blood-edge management, so that if the logic of a service is complex (sql), many tables and grammars are used, users need to analyze and distinguish whether an input table or an output table is recorded in the blood-edge table, and misoperation is easy.
For a better understanding of the present application, the related terms will now be explained, but do not limit the embodiments of the present application.
Data blood margin: refers to the association of big data between tables generated or relied upon by multiple system applications during the data cleansing process.
And (3) job scheduling: refers to a whole set of flow of data time-based cleaning treatment.
Operation node: each set of sub-node tasks in the process is referred to, and the tasks and the dependency relations among the tasks form the whole job scheduling.
In this embodiment, a method for executing a task node is provided, and fig. 3 is a schematic diagram of a method for executing a task node according to an embodiment of the present application, as shown in fig. 3, specifically including: an original business process schedules an operation A process, wherein 3 node data processing tasks are provided, and a task A, a task B and a task C are sequentially executed. The new operation flow B is established according to the service requirement, and the task D, the task E and the task F are sequentially executed. The table data for the E task in job B is produced from the B task of job A, i.e., the table upstream of the table for the E task is the table B of the B task. When creating an E-task, the scheduling system automatically queries the E's tables upstream tables and tasks from the blood-source system. At this time, the scheduling system automatically prompts the upstream and downstream of the node and performs task association processing. And the task E can wait for the execution of the task B and the task D to be completed when the task E is executed, so that the accuracy of data is achieved.
By the embodiment, the blood margin analysis and automatic dependence setting aiming at the newly added task can be realized fully automatically, so that data inconsistency caused by unfamiliar business processes or misoperation of a user is greatly reduced. The user often needs to write the service logic sql for a long time, if the user wants to associate with other services or modifies the service logic for a long time, the user wants to modify the dependence among tasks at this time to re-comb the service flow and the relationship among other service tables, and the application can automatically analyze and configure the dependence related to the configuration, so that the development cost of the user can be greatly reduced, and the development efficiency is improved.
Through the steps, when a user creates a job task flow, the user is prompted about the upstream and downstream dependent task nodes of the current task and can automatically perform dependent association with the upstream and downstream dependent task nodes, namely, the upstream and downstream of the node task are automatically analyzed, the dependent relation of the upstream and downstream tasks is automatically set, and further, codes of the automatic dependent relation can be automatically analyzed and generated. By adopting the technical scheme, the development flow of the user can be greatly shortened, the development efficiency is improved, and the accuracy of data is ensured.
From the description of the above embodiments, it will be clear to a person skilled in the art that the method according to the above embodiments may be implemented by means of software plus the necessary general hardware platform, but of course also by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk), comprising several instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method of the embodiments of the present application.
FIG. 4 is a block diagram of a task node execution device according to an embodiment of the present application; as shown in fig. 4, includes:
a first determining module 42, configured to determine N task flows to be executed, and determine M task nodes carried in each task flow;
a second determining module 44, configured to input n×m task nodes into a preset blood edge database, and determine data blood edge information corresponding to the n×m task nodes, where N, M is a positive integer;
and a third determining module 46, configured to determine, based on the data blood edge information, a dependency relationship of a target task node in the case where it is determined that at least one task flow has the target task node, so as to determine an execution opportunity of the target task node according to the dependency relationship.
Through the device, N task flows to be executed are determined, and M task nodes carried in each task flow are determined; inputting N.M task nodes into a preset blood edge database, and determining data blood edge information corresponding to the N.M task nodes, wherein N, M is a positive integer; under the condition that at least one task flow is determined to have a target task node, determining the dependency relationship of the target task node based on the data blood-source information, so as to determine the execution time of the target task node according to the dependency relationship; by adopting the technical scheme, the technical problems that the task flow dependency relationship corresponding to the newly added service data cannot be determined quickly and the dependency relationship determining process is complex are solved, and further task nodes with the dependency relationship among different task flows can be determined when the new task flow is constructed through the preset blood margin database, so that the execution time of a target task with the dependency relationship is related, and the recognition efficiency of the task flow dependency relationship corresponding to the newly added service data is improved.
In an exemplary embodiment, the third determining module 46 is further configured to determine, based on the dependency relationship, a first execution result corresponding to an auxiliary task node in a task flow other than the at least one task flow, and obtain a second execution result corresponding to a previous task node of a target task node in the at least one task flow, where the auxiliary task node is configured to provide data support for the target task node; and determining the execution time of the target task node according to the first execution result and the second execution result.
In an exemplary embodiment, the third determining module 46 is further configured to determine, when the first execution result indicates that the first task corresponding to the auxiliary task node is completed successfully, and the second execution result indicates that the second task corresponding to the previous task node is completed successfully, that the execution opportunity of the target task node is a time point corresponding to the execution result acquired at the latest; and under the condition that the first execution result indicates that the first task corresponding to the auxiliary task node fails to complete and/or the second execution result indicates that the second task corresponding to the previous task node fails to complete, initiating a repeated execution flow of the first task and/or the second task which fails to complete, and acquiring an ending time point corresponding to the repeated execution flow to determine the execution time of the target task node as the ending time point.
In an exemplary embodiment, the task node executing device includes, in addition to the first determining module 42, the second determining module 44, and the third determining module 46, the executing device further includes: the prompt module 50, the first add module 52, the second add module 54. As shown in fig. 5, fig. 5 is a block diagram (two) of a task node execution apparatus according to an embodiment of the present application,
in an exemplary embodiment, the above apparatus further includes: the prompting module 50 is configured to determine, before initiating a repeated execution flow of the first task and/or the second task that fails to complete, a target task flow to which the previous task node belongs when it is determined that the first task corresponding to the auxiliary task node is completed successfully and the second execution result indicates that the second task corresponding to the previous task node fails to complete; generating prompt information carrying the target task flow and the second task, and sending the prompt information to a target object.
In an exemplary embodiment, the third determining module 46 is further configured to parse the data blood edge information to determine an association relationship between different data; acquiring first data corresponding to the target task node and a plurality of second data corresponding to the target task node and/or other task nodes in a task flow using the first data; determining target second data associated with the first data from the plurality of second data through the association relation; and determining the dependency relationship of the target task node based on the task node corresponding to the target second data.
In an exemplary embodiment, the above apparatus further includes: the first adding module 52 is configured to input n×m task nodes into a preset blood edge database, and obtain historical data of a historical task flow before determining data blood edge information corresponding to the n×m task nodes; analyzing and processing the historical data to obtain historical data blood edges of a plurality of task nodes existing in the historical task flow; and adding the historical data blood edges in the preset blood edge database in a preset period.
In an exemplary embodiment, the above apparatus further includes: a second adding module 54, configured to determine a dependency relationship of the target task node based on the data blood edge information, so as to determine node information of different task nodes in the dependency relationship after determining an execution opportunity of the target task node according to the dependency relationship, where the task node information at least includes: the method comprises the steps that first node information corresponding to an auxiliary task node and second node information corresponding to a previous task node of the target task node are carried, and the node information carries basic information of task flows to which different task nodes belong; and adding the node information in the execution condition of the target task node.
Embodiments of the present application also provide a storage medium including a stored program, wherein the program performs the method of any one of the above when run.
Alternatively, in the present embodiment, the above-described storage medium may be configured to store program code for performing the steps of:
s1, determining N task flows to be executed, and determining M task nodes carried in each task flow;
s2, inputting N.times.M task nodes into a preset blood edge database, and determining data blood edge information corresponding to the N.times.M task nodes, wherein N, M is a positive integer;
and S3, under the condition that at least one task flow is determined to have a target task node, determining the dependency relationship of the target task node based on the data blood edge information, so as to determine the execution time of the target task node according to the dependency relationship.
Embodiments of the present application also provide an electronic device comprising a memory having a computer program stored therein and a processor arranged to run the computer program to perform the steps of any of the method embodiments described above.
Optionally, the electronic apparatus may further include a transmission device and an input/output device, where the transmission device is connected to the processor, and the input/output device is connected to the processor.
Alternatively, in the present embodiment, the above-described processor may be configured to execute the following steps by a computer program:
s1, determining N task flows to be executed, and determining M task nodes carried in each task flow;
s2, inputting N.times.M task nodes into a preset blood edge database, and determining data blood edge information corresponding to the N.times.M task nodes, wherein N, M is a positive integer;
and S3, under the condition that at least one task flow is determined to have a target task node, determining the dependency relationship of the target task node based on the data blood edge information, so as to determine the execution time of the target task node according to the dependency relationship.
Alternatively, in the present embodiment, the storage medium may include, but is not limited to: a U-disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Alternatively, specific examples in this embodiment may refer to examples described in the foregoing embodiments and optional implementations, and this embodiment is not described herein.
It will be appreciated by those skilled in the art that the modules or steps of the application described above may be implemented in a general purpose computing device, they may be centralized on a single computing device, or distributed across a network of computing devices, or they may alternatively be implemented in program code executable by computing devices, such that they may be stored in a memory device for execution by the computing devices and, in some cases, the steps shown or described may be performed in a different order than what is shown or described, or they may be implemented as individual integrated circuit modules, or as individual integrated circuit modules. Thus, the present application is not limited to any specific combination of hardware and software.
The foregoing is merely a preferred embodiment of the present application and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present application and are intended to be comprehended within the scope of the present application.
Claims (10)
1. A method for executing a task node, comprising:
determining N task flows to be executed, and determining M task nodes carried in each task flow;
inputting N.M task nodes into a preset blood edge database, and determining data blood edge information corresponding to the N.M task nodes, wherein N, M is a positive integer;
and under the condition that at least one task flow is determined to have a target task node, determining the dependency relationship of the target task node based on the data blood-source information, so as to determine the execution time of the target task node according to the dependency relationship.
2. The method according to claim 1, wherein determining the execution timing of the target task node according to the dependency relationship includes:
determining a first execution result corresponding to an auxiliary task node in other task flows except the at least one task flow based on the dependency relationship, and acquiring a second execution result corresponding to a previous task node of a target task node in the at least one task flow, wherein the auxiliary task node is used for providing data support for the target task node;
and determining the execution time of the target task node according to the first execution result and the second execution result.
3. The method for executing the task node according to claim 2, wherein determining the execution timing of the target task node according to the first execution result and the second execution result includes:
when the first execution result indicates that the first task corresponding to the auxiliary task node is successfully completed and the second execution result indicates that the second task corresponding to the previous task node is successfully completed, determining that the execution opportunity of the target task node is a time point corresponding to the execution result acquired at the latest;
and under the condition that the first execution result indicates that the first task corresponding to the auxiliary task node fails to complete and/or the second execution result indicates that the second task corresponding to the previous task node fails to complete, initiating a repeated execution flow of the first task and/or the second task which fails to complete, and acquiring an ending time point corresponding to the repeated execution flow to determine the execution time of the target task node as the ending time point.
4. A method of executing a task node according to claim 3, wherein prior to initiating a repeated execution flow of the first task and/or the second task that failed to complete, the method further comprises: determining a target task flow to which the previous task node belongs under the condition that the first task corresponding to the auxiliary task node is determined to be completed successfully and the second execution result indicates that the second task corresponding to the previous task node fails to be completed;
generating prompt information carrying the target task flow and the second task, and sending the prompt information to a target object.
5. The method according to claim 1, wherein in a case where it is determined that at least one task flow has a target task node, determining a dependency relationship of the target task node based on the data blood-edge information includes:
analyzing the data blood-edge information and determining the association relation between different data;
acquiring first data corresponding to the target task node and a plurality of second data corresponding to the target task node and/or other task nodes in a task flow using the first data;
determining target second data associated with the first data from the plurality of second data through the association relation;
and determining the dependency relationship of the target task node based on the task node corresponding to the target second data.
6. The method for executing task nodes according to claim 1, wherein before inputting n×m task nodes into a preset blood edge database and determining data blood edge information corresponding to the n×m task nodes, the method further comprises:
acquiring historical data of a historical task flow;
analyzing and processing the historical data to obtain historical data blood edges of a plurality of task nodes existing in the historical task flow;
and adding the historical data blood edges in the preset blood edge database in a preset period.
7. The method according to claim 1, wherein after determining a dependency relationship of the target task node based on the data blood edge information to determine an execution timing of the target task node according to the dependency relationship, the method further comprises:
determining node information of different task nodes in the dependency relationship, wherein the task node information at least comprises: the method comprises the steps that first node information corresponding to an auxiliary task node and second node information corresponding to a previous task node of the target task node are carried, and the node information carries basic information of task flows to which different task nodes belong;
and adding the node information in the execution condition of the target task node.
8. An execution device of a task node, comprising:
the first determining module is used for determining N task flows to be executed and determining M task nodes carried in each task flow;
the second determining module is used for inputting the N×M task nodes into a preset blood edge database, and determining data blood edge information corresponding to the N×M task nodes, wherein N, M is a positive integer;
and the third determining module is used for determining the dependency relationship of the target task node based on the data blood edge information under the condition that the target task node exists in at least one task flow, so as to determine the execution time of the target task node according to the dependency relationship.
9. A computer readable storage medium, characterized in that the computer readable storage medium comprises a stored program, wherein the program when run performs the method of any of the preceding claims 1 to 7.
10. An electronic device comprising a memory and a processor, characterized in that the memory has stored therein a computer program, the processor being arranged to execute the method according to any of the claims 1 to 7 by means of the computer program.
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