Task processing method and system, electronic equipment and medium

Abstract

The invention provides a task processing method and system, electronic equipment and a medium, and the specific implementation scheme comprises the steps: obtaining task description information for a scene task in response to the creation of the scene task; determining sub-atlas data related to the scene task according to the task description information and the atlas data, the sub-graph data comprises a plurality of target operator nodes, a plurality of target attribute nodes, a first association relationship among the plurality of target operator nodes, a second association relationship between the plurality of target operator nodes and the plurality of target attribute nodes, and a third association relationship among the plurality of target attribute nodes; obtaining a plurality of first task operators corresponding to the plurality of target operator nodes; generating a target task flow corresponding to the scene task based on the sub-graph data and the plurality of first task operators; and executing the scene task based on the target task flow.

Description

Technical Field

[0001] The present invention relates to the fields of data processing and remote sensing technology, and in particular to a task processing method, a task processing system, an electronic device, a storage medium and a computer program product. Background Art

[0002] In order to ensure that geographic data processing tasks can be executed efficiently, geographic data processing tasks can usually be arranged into task flows including multiple operator nodes, and task automation can be achieved by executing task flows. However, in the process of arranging task flows, due to the diversity and complexity of operators, the complexity of the arrangement is increased, the efficiency of the task flow arrangement is reduced, and thus the task processing efficiency is affected. Summary of the invention

[0003] The invention provides a task processing method, a task processing system, an electronic device, a storage medium and a computer program product.

[0004] According to one aspect of the present invention, a task processing method is provided, comprising: in response to creating a scenario task, obtaining task description information for the scenario task; determining sub-graph data related to the scenario task based on the task description information and graph data, the sub-graph data comprising multiple target operator nodes, multiple target attribute nodes, a first association relationship between the multiple target operator nodes, a second association relationship between the multiple target operator nodes and the multiple target attribute nodes, and a third association relationship between the multiple target attribute nodes; obtaining multiple first task operators corresponding to the multiple target operator nodes; generating a target task process corresponding to the scenario task based on the sub-graph data and the multiple first task operators; and executing the scenario task based on the target task process.

[0005] According to another aspect of the present invention, a task processing system is provided, including: a creation module, used to obtain task description information for a scenario task in response to creating a scenario task; a first determination module, used to determine sub-graph data related to the scenario task based on the task description information and graph data, the sub-graph data including multiple target operator nodes, multiple target attribute nodes, a first association relationship between multiple target operator nodes, a second association relationship between multiple target operator nodes and multiple target attribute nodes, and a third association relationship between multiple target attribute nodes; a first acquisition module, used to obtain multiple first task operators corresponding to multiple operator nodes; a generation module, used to generate a target task process corresponding to the scenario task based on the sub-graph data and the multiple first task operators; and a first execution module, used to execute the scenario task based on the target task process.

[0006] According to another aspect of the present invention, an electronic device is provided, comprising: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors execute the method as described above.

[0007] According to another aspect of the present invention, a computer-readable storage medium is provided, on which executable instructions are stored. When the instructions are executed by a processor, the processor executes the method as described above.

[0008] According to another aspect of the present invention, a computer program product is provided, comprising a computer program, which implements the method described above when executed by a processor. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0010] Figure 1 is a schematic diagram of a system architecture to which a task processing method can be applied according to an embodiment of the present invention;

[0011] Figure 2 is a flowchart of a task processing method according to an embodiment of the present invention;

[0012] Figure 3A is a schematic diagram of multiple candidate task processes according to an embodiment of the present invention;

[0013] Figure 3B Shown according to Figure 3A A partial schematic diagram of graph data constructed by multiple candidate task processes shown;

[0014] Figure 4 is a block diagram of a task processing system according to an embodiment of the present invention;

[0015] Figure 5 is a block diagram of an electronic device suitable for implementing a task processing method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0016] The technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention and the drawings in the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field belong to the scope of protection of the present invention.

[0017] It should be noted that the sequence numbers of the operations in the following method are only used as representations of the operations for the purpose of description, and should not be regarded as representing the execution order of the operations. Unless explicitly stated, the method does not need to be executed completely in the order shown.

[0018] In addition, in the description of the present invention, the terms “first”, “second”, “third”, etc. (if any) are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0019] In the technical solution of the present invention, the collection, storage, use, processing, transmission, provision, disclosure and application of the data involved (for example, including but not limited to user personal information) shall comply with the relevant laws and regulations of relevant countries and regions and shall not violate public order and good morals.

[0020] In the technical solution of the present invention, before obtaining or collecting relevant data, the authorization or consent of the data owner is obtained.

[0021] Embodiments of the present invention provide a task processing method, a task processing system, an electronic device, a storage medium, and a computer program product. The task processing method includes: in response to creating a scenario task, obtaining task description information for the scenario task; determining sub-graph data related to the scenario task according to the task description information and graph data, the sub-graph data including multiple target operator nodes, multiple target attribute nodes, a first association relationship between multiple target operator nodes, a second association relationship between multiple target operator nodes and multiple target attribute nodes, and a third association relationship between multiple target attribute nodes; obtaining multiple first task operators corresponding to multiple target operator nodes; generating a target task flow corresponding to the scenario task based on the sub-graph data and the multiple first task operators; and executing the scenario task based on the target task flow.

[0022] According to an embodiment of the present invention, by constructing graph data to manage various candidate operators and the relationship between candidate operators, the relationship between candidate operators and operator attribute information, and the relationship between operator attribute information and operator attribute information, it is possible to quickly and accurately search for sub-graph data related to the scene task in the graph data based on the task description information of the created scene task, so that the task operator associated with the scene task can be obtained based on the sub-graph data, and the task operator associated with the scene task can be further used to construct the target task process corresponding to the scene task, so that in the process of constructing the target task process corresponding to the scene task, the interference of operators unrelated to the scene task is avoided, the efficiency and accuracy of constructing the target task process is improved, and then the task processing efficiency and accuracy are improved.

[0023] Figure 1is a schematic diagram of a system architecture to which a task processing method according to an embodiment of the present invention can be applied. It should be noted that: Figure 1 The examples shown are merely examples of system architectures to which the embodiments of the present invention may be applied, to help those skilled in the art understand the technical content of the present invention, but do not mean that the embodiments of the present invention may not be used in other devices, systems, environments or scenarios.

[0024] like Figure 1 As shown, the system architecture 100 according to this embodiment may include a terminal 101, a server 102, and a network 103. The network 103 is used to provide a medium for a communication link between the terminal 101 and the server 102. The network 103 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc. A user may use the terminal 101 to interact with the server 102 through the network 103 for data.

[0025] The terminal 101 may include, but is not limited to, a smart phone, a laptop, a tablet computer, a VR / AR device, a vehicle-mounted terminal, and other intelligent terminals with data processing functions. The terminal 101 of the embodiment of the present invention may, for example, run an application program. Various client applications may be installed on the terminal 101, such as search applications, geographic information system applications, web browser applications, etc. (only as examples). When the client runs on the terminal 101, data may be exchanged with the server 102.

[0026] Server 102 can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers. It can also be 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, CDN, as well as big data and artificial intelligence platforms.

[0027] In one example, the server 102 can obtain and store the graph data, the terminal 101 can run the client corresponding to the task processing system, the user can create a scene task through the client, and configure the task description information corresponding to the scene task, the client transmits the task description information corresponding to the scene task to the server 102, and after receiving the task description information corresponding to the scene task, the server 102 can determine the sub-graph data related to the scene task according to the task description information and the graph data. Among them, the sub-graph data includes a plurality of target operator nodes, a plurality of target attribute nodes, a first association relationship between a plurality of target operator nodes, a second association relationship between a plurality of target operator nodes and a plurality of target attribute nodes, and a third association relationship between a plurality of target attribute nodes. Afterwards, a plurality of first task operators corresponding to the plurality of target operator nodes are obtained. Afterwards, based on the sub-graph data and the plurality of first task operators, a target task flow corresponding to the scene task is generated, and the scene task is executed based on the target task flow.

[0028] It should be understood that Figure 1 The number of terminals, networks and servers in the embodiment is only for illustration. Any number of terminals, networks and servers may be provided according to actual needs.

[0029] Figure 2 is a flowchart of a task processing method according to an embodiment of the present invention.

[0030] like Figure 2 As shown, the task processing method 200 includes operations S210 to S250. The task processing method provided by the embodiment of the present invention may be executed by the server 102.

[0031] In operation S210 , in response to creating a scenario task, task description information for the scenario task is acquired.

[0032] In operation S220, sub-graph data related to the scene task is determined based on the task description information and the graph data, wherein the sub-graph data includes multiple target operator nodes, multiple target attribute nodes, a first association relationship between the multiple target operator nodes, a second association relationship between the multiple target operator nodes and the multiple target attribute nodes, and a third association relationship between the multiple target attribute nodes.

[0033] In operation S230 , a plurality of first task operators corresponding to a plurality of target operator nodes are acquired.

[0034] In operation S240, a target task process corresponding to the scenario task is generated based on the sub-graph data and the plurality of first task operators.

[0035] In operation S250 , a scenario task is performed based on the target task flow.

[0036] According to an embodiment of the present invention, when a scenario task needs to be created, the user can click on the user interaction interface on the client to display the user interaction interface. The user interaction interface includes a "New" control, and the user clicks the "New" control to display the configuration interface. The user can enter the task description information related to the scenario task to be created through the configuration interface. For example, the task description information related to the scenario task includes, but is not limited to, the scenario task name, the scenario task type, the task description content, and the task label used to identify the scenario task. For example, when the scenario task created by the user is "training inversion model", the task description information related to the scenario task may include, for example: the scenario task name is "training inversion model", the scenario task type is "remote sensing inversion", the task description content is, for example, "using xxx sample data to train xxx deep learning network to obtain an inversion model, wherein the parameters in the model training process are parameters xxx", and the task label includes, for example, "inversion model", "model training", "deep learning", "sample data", etc. When the task description information is configured, the creation of the scenario task is completed. The user interaction interface may also include a "modify" control and a "view" control. After the scenario task is successfully created, the user can view the task description information of the created scenario task by clicking the "View" control, or modify the task description information of the created scenario task by clicking the "Modify" control to adapt to the user's current scenario task creation needs.

[0037] According to an embodiment of the present invention, after a user creates a scene task through a client, the client may transmit task description information corresponding to the scene task to the server 102. After receiving the task description information corresponding to the scene task, the server 102 may perform associated operator information retrieval based on the task description information and graph data to obtain sub-graph data related to the scene task.

[0038] Combine the following Figure 3A and Figure 3B The process of constructing the atlas data is exemplified. It should be noted that: Figure 3A , 3B The candidate task processes shown in are only exemplary, and the technical solutions of the present invention are not limited thereto.

[0039] First, multiple candidate task processes are obtained.

[0040] According to an embodiment of the present invention, a plurality of candidate operators and a plurality of candidate task processes are stored in a pre-built operator library. The plurality of candidate operators may include, for example, data input, data output, data conversion, data cleaning, data quality inspection, data repair, spatial analysis (e.g., overlay analysis, buffer analysis, etc.), model training, graphics processing, and other types of operators. Each candidate task process is obtained by arranging at least one candidate operator, and it can be used to execute a corresponding candidate scenario task to obtain a corresponding task execution result.

[0041] Multiple candidate task processes can be obtained from the operator library, and graph data can be constructed based on these candidate task processes, so as to manage each candidate operator and the relationship between the candidate operators, the relationship between the candidate operators and the operator attribute information, and the relationship between the operator attribute information and the operator attribute information based on the graph data, so that the required associated operator information can be obtained quickly and accurately according to the actual scenario task requirements for subsequent processing.

[0042] like Figure 3A As shown, multiple candidate task flows may include, for example, candidate task flow 1, candidate task flow 2, ..., candidate task flow n. Among them, candidate task flow 1, candidate task flow 2, ..., candidate task flow n are used to execute candidate scenario task 1, candidate scenario task 2, ..., candidate scenario task n, respectively, and n is, for example, an integer greater than or equal to 50. Each candidate task flow includes at least one candidate operator and a candidate execution dependency relationship between at least one candidate operator. In an embodiment of the present invention, each candidate operator has corresponding operator attribute information. For example, the operator attribute information may include, but is not limited to, operator name, operator identifier, operator category, operator input parameter, operator output parameter, operator parameter type, operator function description information, status and version information, etc.

[0043] In some embodiments, the candidate execution dependencies may include data dependencies and operator parameter dependencies. The data dependency refers to the dependency between the input and output data of at least two candidate operators, and the operator parameter dependency refers to the dependency between the operator input parameters and operator output parameters of at least two candidate operators. Figure 3A For example, the candidate task flow 2 in the example includes five candidate operators, namely, operator 21, operator 12, operator 24, operator 23 and operator 25, wherein operator 21 and operator 12, operator 12 and operator 24, operator 12 and operator 23, operator 24 and operator 25, and operator 23 and operator 25 have data dependency relationships ( Figure 3A ), there is an operator parameter dependency relationship between operator 21 and operator 12, and between operator 12 and operator 24 ( Figure 3A Indicated by dashed arrow line).

[0044] In other embodiments, the candidate execution dependencies may include only data dependencies, for example. Figure 3A For example, the candidate task flow 1 in the example includes four candidate operators, namely, operator 11, operator 12, operator 13 and operator 14, wherein there is a data dependency relationship between operator 11 and operator 12, operator 12 and operator 13, and operator 13 and operator 14, and there is no operator parameter dependency relationship between the candidate operators.

[0045] Based on each candidate operator contained in each of the above candidate task processes, the operator attribute information corresponding to each candidate operator, and the candidate execution dependency relationship between the candidate operators, graph data can be constructed.

[0046] Next, candidate operator extraction is performed on multiple candidate task flows to obtain candidate operators included in multiple candidate task flows. Then, entity extraction is performed on the operator attribute information of each candidate operator in the multiple candidate task flows to obtain candidate entity attribute information included in the multiple candidate task flows. After that, relationship extraction is performed on the multiple candidate task flows to obtain a first candidate association relationship between candidate operators, a second candidate association relationship between candidate operators and candidate entity attribute information, and a third candidate association relationship between candidate entity attribute information.

[0047] According to an embodiment of the present invention, the first candidate association relationship is determined based on the dependency relationship between the input and output data of each candidate operator included in a plurality of candidate task processes, and it is used to indicate the data dependency relationship between each candidate operator included in a plurality of candidate task processes. The second candidate association relationship is determined based on the mapping relationship between each of the above-mentioned candidate operators and the candidate entity attribute information corresponding to each candidate operator, and it is used to indicate the correspondence between each of the candidate operators and the operator attribute information included in a plurality of candidate task processes. The third candidate association relationship is determined based on the association relationship between the candidate entity attribute information corresponding to each of the above-mentioned candidate operators, and it can be used to characterize the association relationship between the operator attribute information of each of the candidate operators included in a plurality of candidate task processes, such as including but not limited to the operator parameter dependency relationship between the candidate operators, the relationship between the operator categories of the candidate operators, and the relationship between the operator functions of the candidate operators.

[0048] Next, based on the extracted candidate operators, candidate entity attribute information, first candidate association relationships, second candidate association relationships, and third candidate association relationships, graph data is constructed.

[0049] Before constructing the graph data, the extracted candidate operators, the candidate entity attribute information of each candidate operator, the first candidate association relationship, the second candidate association relationship, and the third candidate association relationship can be deduplicated to ensure the uniqueness of the graph elements. Afterwards, the candidate operators are used as the data of the operator nodes, and the candidate entity attribute information is used as the data of the attribute nodes. The edges between the operator nodes, the edges between the operator nodes and the attribute nodes, and the edges between the attribute nodes are constructed according to the first candidate association relationship, the second candidate association relationship, and the third candidate association relationship, respectively, so as to construct the following: Figure 3B In some embodiments, in the process of constructing the graph data, operator nodes, attribute nodes, and edges between nodes from the same candidate task flow can also be uniquely identified, so as to facilitate rapid positioning and tracking of corresponding nodes and edges.

[0050] It should be noted that in the above process of constructing graph data, the edge between operator nodes is a directed edge, and the direction of the edge is determined according to the data dependency between the corresponding candidate operators. The edge between the operator node and the attribute node can be an undirected edge. In addition, when the edge between the attribute nodes represents the operator parameter dependency, the edge between the attribute nodes is a directed edge, and the direction of the edge is determined according to the operator parameter dependency between the corresponding candidate operators. When the edge between the attribute nodes represents a non-operator parameter dependency, the edge between the attribute nodes can be an undirected edge.

[0051] According to an embodiment of the present invention, based on the task description information and graph data for the scenario task, determining the sub-graph data related to the scenario task includes the following process.

[0052] First, entity extraction is performed on the task description information to obtain multiple entity information contained in the task description information.

[0053] In an embodiment of the present invention, for example, a pre-trained entity extraction model (such as a BERT model) may be used to perform entity extraction processing on the task description information so as to obtain multiple entity information contained in the task description information.

[0054] Next, the graph data is searched for operator nodes related to multiple entity information and attribute nodes corresponding to the related operator nodes to generate sub-graph data.

[0055] In an embodiment of the present invention, when querying related operator nodes in the graph data using multiple entity information, the first operator node and the second operator node can be determined in the graph data based on the multiple entity information. Among them, the first operator node refers to the operator node or operator node set that needs to be reached when searching for related operator nodes in the graph data, and the second operator node refers to the operator node or operator node set that needs to be passed in the above search process. After determining the first operator node and the second operator node, then based on the search algorithm, such as but not limited to the depth first search algorithm, the breadth first search algorithm or the A* search algorithm, the shortest path from the second operator node to the first operator node is determined in the graph data, and the sub-graph data is generated according to the operator nodes on the shortest path and the attribute nodes corresponding to the operator nodes. The sub-graph data includes the sub-graph data including multiple target operator nodes, multiple target attribute nodes, the first association relationship between multiple target operator nodes, the second association relationship between multiple target operator nodes and multiple target attribute nodes, and the third association relationship between multiple target attribute nodes. Among them, the first association relationship is used to indicate the data dependency relationship between multiple target operator nodes, the second association relationship is used to indicate the correspondence between multiple target operator nodes and multiple target attribute nodes, and the third association relationship includes the operator parameter dependency relationship between multiple target operator nodes.

[0056] Through the above method, sub-graph data related to the scenario task can be quickly and accurately searched in the graph data, and the sub-graph data can be used to construct a target task process corresponding to the scenario task.

[0057] After obtaining the sub-graph data, the candidate operators corresponding to the multiple target operator nodes stored in the sub-graph data can be obtained from the operator library to obtain multiple first task operators. After that, the target task process corresponding to the scene task can be generated according to the above sub-graph data and multiple first task operators. This process is described below.

[0058] According to an embodiment of the present invention, based on the above-mentioned sub-graph data and multiple first task operators, generating a target task flow corresponding to the scene task includes the following process.

[0059] First, in response to a parameter configuration operation for a plurality of first task operators, first parameter configuration information for the plurality of first task operators is determined.

[0060] According to an embodiment of the present invention, multiple first task operators can be displayed on a user interaction interface. After receiving a parameter configuration operation for multiple first task operators from a user, a configuration interface for multiple first task operators can be displayed on the user interaction interface so that the user can set first parameter configuration information for multiple first task operators. The first parameter configuration information may include, for example, input data configuration information, output data configuration information, and operator parameter configuration information. Among them, the input data configuration information includes, for example, but is not limited to, the resource service address of the input data or the target service resource identifier (the target service resource identifier is associated with the target service resource), the input data type, etc. The output data configuration information includes, for example, but is not limited to, the storage path of the output data, the output data type, etc. The operator parameter configuration information includes, for example, but is not limited to, the operator parameter value, the operator parameter type, the storage path, etc.

[0061] Next, based on the first parameter configuration information, the first association relationship, the third association relationship and the plurality of first task operators, a target task process corresponding to the scenario task is generated.

[0062] In an embodiment of the present invention, the target task process can be obtained in the following manner.

[0063] First, multiple target task operators are obtained according to the first parameter configuration information and multiple first task operators, wherein each first task operator corresponds to one target task operator.

[0064] Next, according to the first association relationship and the third association relationship, a first execution dependency relationship between the multiple target task operators is determined.

[0065] According to an embodiment of the present invention, the data dependency and operator parameter dependency (if any) between multiple target task operators can be determined according to the first association relationship and the third association relationship respectively, thereby obtaining the first execution dependency between the multiple target task operators.

[0066] Next, multiple target task operators are arranged according to the first execution dependency to obtain a target task flow.

[0067] According to an embodiment of the present invention, it is assumed that a plurality of target task operators include target task operator a, target task operator b, target task operator c and target task operator d (for example only). Based on the first execution dependency, it can be determined that there is a data dependency between target task operator a and target task operator c, target task operator b and target task operator c, target task operator c and target task operator d (for example, target task operator a→target task operator c, target task operator b→target task operator c, target task operator c→target task operator d), and there is an operator parameter dependency between target task operator a and target task operator d (for example, operator parameter a of target task operator a→operator parameter d of target task operator d), wherein the direction of the arrow indicates the data / parameter transfer direction. According to the data dependency between each target task operator, these four target task operators can be connected in a directed manner through a first type of connecting line to obtain an operator chain. Then, based on the operator chain, according to the operator parameter dependency relationship between the target task operator a and the target task operator d, the operator parameter a of the target task operator a and the operator parameter d of the target task operator d are connected in a directed manner through the second type of connection line, thereby obtaining the target task flow. The target task flow is used to execute the scenario task. When running the target task flow, it can flow from the target task operators a and b to the target task operator c, and then from the target task operator c to the target task operator d. At the same time, the operator parameter a of the target task operator a also flows to the target task operator d.

[0068] After obtaining the target task flow, next, the scenario task can be executed based on the target task flow.

[0069] In an embodiment of the present invention, the target service resources associated with each of the multiple target task operators in the target task flow can be called to perform scenario task processing based on the target task flow to obtain the first task execution result for the scenario task. Each target task operator includes a target service resource identifier, and the target service resource identifier is used to characterize the association relationship between the target task operator and the target service resource.

[0070] According to an embodiment of the present invention, after obtaining the target task process, a user interaction interface can also be displayed, and the target task process can be displayed through the user interaction interface for the user to view and confirm. In some embodiments, the target task process or each target task operator can also be debugged according to the user's interactive operation to verify whether there is an abnormality in the target task process. For example, when a trigger operation is received for the first target task operator in the target task process or the running control associated with the first target task operator, the state information of the first target task operator is obtained. The state information is used to indicate whether the first target task operator is executable. In an embodiment of the present invention, the first target task operator can be, for example, one or more target task operators specified by the user through a trigger operation.

[0071] In some embodiments, if the status information indicates that the first target task operator is executable, it means that the execution dependency for the first target task operator is correct. At this time, the first target service resource associated with the first target task operator can be called to execute the first target task operator to obtain the second task execution result associated with the first target task operator. In some embodiments of the present invention, the second task execution result can also be compared with the preset task execution result to determine whether the parameter configuration information corresponding to the first target task operator and the first target task operator are compatible. If the difference between the second task execution result and the preset task execution result is greater than the preset value, it means that the parameter configuration information corresponding to the first target task operator is incompatible with the first target task operator, and the user can change the parameter configuration information of the first target task operator to meet the user's needs.

[0072] In other embodiments, if the status information indicates that the first target task operator is not executable, it means that there is an abnormality in the first target task operator (for example, there is an abnormality in the execution dependency of the first target task operator). At this time, subtask description information for the first target task operator can be obtained, and at least one to-be-executed function can be determined based on the subtask description information of the first target task operator. Among them, the subtask description information can be determined based on the parameter configuration information corresponding to the first target task operator in the first parameter configuration information and the operator function of the first target task operator. Then, at least one second task operator associated with at least one to-be-executed function is obtained from the operator library so as to replace the first target task operator with at least one second task operator.

[0073] In an embodiment of the present invention, replacing a first target task operator in a target task flow with at least one second task operator includes the following operations.

[0074] First, in response to a parameter configuration operation for at least one second task operator, second parameter configuration information for at least one second task operator is determined, and at least one second target task operator is obtained based on the second parameter configuration information and the at least one second task operator.

[0075] Next, based on the graph data, a second execution dependency relationship between at least one second target task operator and other target task operators and a third execution dependency relationship between at least one second target task operator are determined, wherein other target task operators are target task operators other than the first target task operator in the target task flow.

[0076] Afterwards, at least one second target task operator and other target task operators are orchestrated based on the second execution dependency relationship and the third execution dependency relationship to obtain a new target task flow, and the scenario task is executed based on the new target task flow.

[0077] In the embodiment of the present invention, the definition of the second parameter configuration information is similar to that of the first parameter configuration information, and the second execution dependency relationship and the third execution dependency relationship are similar to the first execution dependency relationship, which will not be repeated here.

[0078] Through the above method, the user can timely locate the abnormal operator nodes in the target task process according to the status of each target task operator in the target task process, so that the target task process can be adjusted in time to meet the user's current needs, thereby improving the task processing efficiency and quality.

[0079] Figure 4 is a block diagram of a task processing system according to an embodiment of the present invention.

[0080] like Figure 4 As shown, the task processing system 400 includes: a creation module 410 , a first determination module 420 , a first acquisition module 430 , a generation module 440 and a first execution module 450 .

[0081] The creation module 410 is used to obtain task description information for the scenario task in response to creating the scenario task.

[0082] The first determination module 420 is used to determine sub-graph data related to the scene task based on the task description information and the graph data, the sub-graph data including multiple target operator nodes, multiple target attribute nodes, a first association relationship between multiple target operator nodes, a second association relationship between multiple target operator nodes and multiple target attribute nodes, and a third association relationship between multiple target attribute nodes.

[0083] The first acquisition module 430 is used to acquire multiple first task operators corresponding to multiple operator nodes.

[0084] The generation module 440 is used to generate a target task process corresponding to the scenario task based on the sub-graph data and multiple first task operators.

[0085] The first execution module 450 is used to execute the scenario task based on the target task process.

[0086] According to an embodiment of the present invention, the first determination module 420 includes: an extraction unit, used to perform entity extraction processing on the task description information to obtain multiple entity information contained in the task description information; a first generation unit, used to search the graph data for operator nodes related to multiple entity information and attribute nodes corresponding to the related operator nodes to generate sub-graph data.

[0087] According to an embodiment of the present invention, the task processing system 400 further includes: a second acquisition module, which is used to acquire multiple candidate task processes before determining the sub-graph data related to the scenario task based on the task description information and the graph data, each candidate task process includes at least one candidate operator and at least one candidate execution dependency relationship between the candidate operators, wherein each candidate operator has corresponding operator attribute information, the operator attribute information at least includes operator input parameters, operator output parameters and operator function description information, and the candidate execution dependency relationship includes at least one data dependency relationship and operator parameter dependency relationship between the candidate operators; a first extraction module, which is used to perform candidate operator extraction processing on the multiple candidate task processes to obtain the candidate operators contained in the multiple candidate task processes; a second extraction module, which is used to extract each candidate operator in the multiple candidate task processes; The operator attribute information is subjected to entity extraction processing to obtain the candidate entity attribute information contained in multiple candidate task processes; the third extraction module is used to perform relationship extraction processing on the multiple candidate task processes to obtain the first candidate association relationship between the candidate operators, the second candidate association relationship between the candidate operators and the candidate entity attribute information, and the third candidate association relationship between the candidate entity attribute information, wherein the first candidate association relationship is used to indicate the data dependency relationship between the candidate operators, the second candidate association relationship is used to indicate the corresponding relationship between the candidate operators and the candidate entity attribute information, and the third candidate association relationship includes the operator parameter dependency relationship between the candidate operators; the construction module is used to construct the graph data based on the extracted candidate operators, the candidate entity attribute information, the first candidate association relationship, the second candidate association relationship, and the third candidate association relationship.

[0088] According to an embodiment of the present invention, the first association relationship is used to indicate the data dependency relationship between multiple target operator nodes, the second association relationship is used to indicate the correspondence between multiple target operator nodes and multiple target attribute nodes, and the third association relationship includes the operator parameter dependency relationship between multiple target operator nodes; the generation module 440 includes: a determination unit, which is used to determine the first parameter configuration information for multiple first task operators in response to parameter configuration operations for multiple first task operators; a second generation unit, which is used to generate a target task process corresponding to the scenario task based on the first parameter configuration information, the first association relationship, the third association relationship and multiple first task operators.

[0089] According to an embodiment of the present invention, the second generation unit includes: a first determination subunit, used to obtain multiple target task operators based on the first parameter configuration information and multiple first task operators; a second determination subunit, used to determine the first execution dependency relationship between the multiple target task operators based on the first association relationship and the third association relationship; and an orchestration subunit, used to orchestrate the multiple target task operators according to the first execution dependency relationship to obtain a target task process.

[0090] According to an embodiment of the present invention, the first execution module 450 includes: a processing unit, used to call the target service resources associated with each of the multiple target task operators in the target task process to perform scenario task processing based on the target task process, and obtain a first task execution result for the scenario task; wherein each target task operator includes a target service resource identifier, and the target service resource identifier is used to characterize the association relationship between the target task operator and the target service resource.

[0091] According to an embodiment of the present invention, the task processing system 400 also includes: a first display module, used to display a user interaction interface; a second display module, used to display the target task process through the user interaction interface; a third acquisition module, used to obtain the status information of the first target task operator in response to a trigger operation on the first target task operator in the target task process; a second execution module, used to call the first target service resource associated with the first target task operator to execute the first target task operator when the status information indicates that the first target task operator is executable, and obtain the second task execution result associated with the first target task operator.

[0092] According to an embodiment of the present invention, the task processing system 400 also includes: a fourth acquisition module, which is used to obtain subtask description information for the first target task operator in response to the status information indicating that the first target task operator is not executable, and determine at least one to-be-executed function based on the subtask description information of the first target task operator; a fifth acquisition module, which is used to obtain at least one second task operator associated with at least one to-be-executed function; a second determination module, which is used to determine the second parameter configuration information for at least one second task operator in response to the parameter configuration operation for at least one second task operator, and obtain at least one second target task operator based on the second parameter configuration information and at least one second task operator; a third determination module, which is used to determine the second execution dependency between at least one second target task operator and other target task operators and the third execution dependency between at least one second target task operator based on the graph data, wherein the other target task operators are target task operators other than the first target task operator in the target task flow; an orchestration module, which is used to orchestrate at least one second target task operator and other target task operators based on the second execution dependency and the third execution dependency to obtain a new target task flow; and a third execution module, which is used to execute the scenario task based on the new target task flow.

[0093] It should be noted that the implementation methods, technical problems solved, functions realized, and technical effects achieved of each module in the device part embodiment are the same or similar to the implementation methods, technical problems solved, functions realized, and technical effects achieved of each corresponding step in the method part embodiment, and will not be repeated here.

[0094] Figure 5 A block diagram of an electronic device suitable for implementing a task processing method according to an embodiment of the present invention is schematically shown.

[0095] like Figure 5 As shown, the electronic device 500 according to an embodiment of the present invention includes a processor 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage part 508 into a random access memory (RAM) 503. The processor 501 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 501 may also include an onboard memory for caching purposes. The processor 501 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present invention.

[0096] In RAM 503, various programs and data required for the operation of electronic device 500 are stored. Processor 501, ROM 502 and RAM 503 are connected to each other via bus 504. Processor 501 performs various operations of the method flow according to the embodiment of the present invention by executing the program in ROM 502 and / or RAM 503. It should be noted that the program can also be stored in one or more memories other than ROM 502 and RAM 503. Processor 501 can also perform various operations of the method flow according to the embodiment of the present invention by executing the program stored in the one or more memories.

[0097] According to an embodiment of the present invention, the electronic device 500 may further include an input / output (I / O) interface 505, which is also connected to the bus 504. The electronic device 500 may further include one or more of the following components connected to the I / O interface 505: an input portion 506 including a keyboard, a mouse, etc.; an output portion 507 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 508 including a hard disk, etc.; and a communication portion 509 including a network interface card such as a LAN card, a modem, etc. The communication portion 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the I / O interface 505 as needed. A removable medium 511, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 510 as needed, so that a computer program read therefrom is installed into the storage portion 508 as needed.

[0098] The present invention also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiment; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the task processing method according to the embodiment of the present invention is implemented.

[0099] According to an embodiment of the present invention, the computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, an apparatus or a device. For example, according to an embodiment of the present invention, the computer-readable storage medium may include the ROM 502 and / or RAM 503 described above and / or one or more memories other than ROM 502 and RAM 503.

[0100] The embodiment of the present invention also includes a computer program product, which includes a computer program, and the computer program contains program code for executing the method shown in the flowchart. When the computer program product is run in a computer system, the program code is used to enable the computer system to implement the task processing method provided by the embodiment of the present invention.

[0101] The computer program executes the above functions defined in the system / device of the embodiment of the present invention when it is executed by the processor 501. According to the embodiment of the present invention, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0102] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 509, and / or installed from the removable medium 511. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0103] In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 509, and / or installed from the removable medium 511. When the computer program is executed by the processor 501, the above functions defined in the system of the embodiment of the present invention are performed. According to the embodiment of the present invention, the system, device, means, module, unit, etc. described above can be implemented by a computer program module.

[0104] According to an embodiment of the present invention, the program code for executing the computer program provided by the embodiment of the present invention can be written in any combination of one or more programming languages, specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, such as Java, C++, python, "C" language or similar programming languages. The program code can be executed completely on the user computing device, partially on the user device, partially on the remote computing device, or completely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (e.g., using an Internet service provider to connect through the Internet).

[0105] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0106] It will be appreciated by those skilled in the art that the features described in the various embodiments of the present invention may be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in the present invention. In particular, without departing from the spirit and teachings of the present invention, the features described in the various embodiments of the present invention may be combined and / or combined in various ways. All of these combinations and / or combinations fall within the scope of the present invention.

[0107] The embodiments of the present invention are described above. However, these embodiments are only for the purpose of illustration, and are not intended to limit the scope of the present invention. Although each embodiment is described above, it does not mean that the measures in each embodiment cannot be used in combination advantageously. Without departing from the scope of the present invention, those skilled in the art may make various substitutions and modifications, which should all fall within the scope of the present invention.

Claims

1. A task processing method, characterized in that: include: In response to creating a scenario task, obtaining task description information for the scenario task; Determine sub-graph data related to the scenario task according to the task description information and the graph data, wherein the sub-graph data includes a plurality of target operator nodes, a plurality of target attribute nodes, a first association relationship between the plurality of target operator nodes, a second association relationship between the plurality of target operator nodes and the plurality of target attribute nodes, and a third association relationship between the plurality of target attribute nodes; Acquire multiple first task operators corresponding to the multiple target operator nodes; Based on the sub-graph data and the plurality of first task operators, generating a target task process corresponding to the scenario task; The scenario task is executed based on the target task process.

2. The method according to claim 1, characterized in that: Determining the sub-graph data related to the scene task according to the task description information and the graph data includes: Performing entity extraction processing on the task description information to obtain multiple entity information contained in the task description information; The graph data is searched for operator nodes related to the plurality of entity information and attribute nodes corresponding to the related operator nodes to generate the sub-graph data.

3. The method according to claim 2, characterized in that Before determining the sub-graph data related to the scene task according to the task description information and the graph data, the method further includes: Acquire multiple candidate task processes, each candidate task process includes at least one candidate operator and a candidate execution dependency relationship between the at least one candidate operator, wherein each candidate operator has corresponding operator attribute information, the operator attribute information includes at least operator input parameters, operator output parameters and operator function description information, and the candidate execution dependency relationship includes a data dependency relationship and an operator parameter dependency relationship between the at least one candidate operator; Performing candidate operator extraction processing on the multiple candidate task flows to obtain candidate operators included in the multiple candidate task flows; Performing entity extraction processing on the operator attribute information of each candidate operator in the multiple candidate task flows to obtain candidate entity attribute information contained in the multiple candidate task flows; Performing relationship extraction processing on the multiple candidate task processes to obtain a first candidate association relationship between candidate operators, a second candidate association relationship between candidate operators and candidate entity attribute information, and a third candidate association relationship between candidate entity attribute information, wherein the first candidate association relationship is used to indicate a data dependency relationship between candidate operators, the second candidate association relationship is used to indicate a corresponding relationship between candidate operators and candidate entity attribute information, and the third candidate association relationship includes an operator parameter dependency relationship between candidate operators; The graph data is constructed based on the extracted candidate operators, candidate entity attribute information, the first candidate association relationship, the second candidate association relationship and the third candidate association relationship.

4. The method according to any one of claims 1 to 3, characterized in that The first association relationship is used to indicate a data dependency relationship between the multiple target operator nodes, the second association relationship is used to indicate a corresponding relationship between the multiple target operator nodes and the multiple target attribute nodes, and the third association relationship includes an operator parameter dependency relationship between the multiple target operator nodes; The step of generating a target task process corresponding to the scenario task based on the sub-graph data and the plurality of first task operators includes: In response to a parameter configuration operation for the plurality of first task operators, determining first parameter configuration information for the plurality of first task operators; Based on the first parameter configuration information, the first association relationship, the third association relationship and the plurality of first task operators, a target task process corresponding to the scenario task is generated.

5. The method according to claim 4, characterized in that The step of generating a target task process corresponding to the scenario task based on the first parameter configuration information, the first association relationship, the third association relationship, and the plurality of first task operators includes: Obtaining multiple target task operators according to the first parameter configuration information and the multiple first task operators; Determining a first execution dependency relationship between the plurality of target task operators according to the first association relationship and the third association relationship; The multiple target task operators are arranged according to the first execution dependency to obtain the target task process.

6. The method according to claim 5, characterized in that The executing the scenario task based on the target task process includes: Calling target service resources respectively associated with a plurality of target task operators in the target task process to perform scenario task processing based on the target task process to obtain a first task execution result for the scenario task; Each target task operator includes a target service resource identifier, and the target service resource identifier is used to represent the association relationship between the target task operator and the target service resource.

7. The method according to claim 6, characterized in that The method further comprises: Display the user interaction interface; Displaying the target task process through the user interaction interface; In response to a trigger operation on a first target task operator in the target task process, acquiring state information of the first target task operator; When the state information indicates that the first target task operator is executable, a first target service resource associated with the first target task operator is called to execute the first target task operator to obtain a second task execution result associated with the first target task operator.

8. The method according to claim 7, characterized in that The method further comprises: In response to the state information indicating that the first target task operator is not executable, obtaining subtask description information for the first target task operator, and determining at least one to-be-executed function according to the subtask description information of the first target task operator; Acquire at least one second task operator associated with the at least one function to be executed; In response to the parameter configuration operation for the at least one second task operator, determine second parameter configuration information for the at least one second task operator, and obtain at least one second target task operator according to the second parameter configuration information and the at least one second task operator; Determine, based on the graph data, a second execution dependency relationship between the at least one second target task operator and other target task operators and a third execution dependency relationship between the at least one second target task operators, wherein the other target task operators are target task operators other than the first target task operator in the target task process; Based on the second execution dependency relationship and the third execution dependency relationship, the at least one second target task operator and the other target task operators are arranged to obtain a new target task process; The scenario task is executed based on the new target task process.

9. A task processing system, characterized in that: include: A creation module, configured to obtain task description information for the scenario task in response to creating the scenario task; A first determination module, used to determine sub-graph data related to the scenario task according to the task description information and the graph data, wherein the sub-graph data includes a plurality of target operator nodes, a plurality of target attribute nodes, a first association relationship between the plurality of target operator nodes, a second association relationship between the plurality of target operator nodes and the plurality of target attribute nodes, and a third association relationship between the plurality of target attribute nodes; A first acquisition module, used to acquire a plurality of first task operators corresponding to the plurality of operator nodes; A generation module, used to generate a target task process corresponding to the scenario task based on the sub-graph data and the multiple first task operators; The first execution module is used to execute the scenario task based on the target task process.

10. An electronic device, characterized in that: include: one or more processors; a memory for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors are caused to execute the method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that: Executable instructions are stored thereon, and when the instructions are executed by a processor, the processor is caused to perform the method according to any one of claims 1 to 8.

12. A computer program product, characterized in that A computer program is included which, when executed by a processor, implements the method according to any one of claims 1 to 8.

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