CN117270817A - Method for realizing DAG process automation based on process engine Canunda - Google Patents
Method for realizing DAG process automation based on process engine Canunda Download PDFInfo
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Abstract
The invention relates to a method for realizing DAG process automation based on a process engine Camunda, which comprises the following steps: the method and the device for achieving the intelligent driving AI training and developing the task flow solve the problems that the task scheduling implementation details of the DAG can only be actually optimized and packaged based on specific business scenes, but the whole task flow implementation of the AI training and developing model does not have universality, and meet the requirements of intelligent driving AI training and developing the whole task flow for a long time and high-frequency efficient circulation.
Description
Technical Field
The invention relates to the field of intelligent driving algorithm tasks of vehicles, in particular to a method for realizing DAG flow automation based on a flow engine Camunda.
Background
The intelligent driving AI development training of the vehicle enterprise on the market comprises the steps of cloud loading from vehicle end data, data processing, data cleaning, model training, model evaluation, model pre-brushing and the like, namely the process of a pipeline (pipeline) formed by a plurality of tasks, so that a complete set of complete flow system is gradually formed. In the process system, complex dependency relationship often exists among tasks, and in order to ensure correct execution of pipeline, the complex dependency problem among the tasks needs to be solved first.
Based on the problems faced by the above service scenarios, a DAG (Directed Acyclic Graph ) is introduced, which refers to a Graph with any Edge Directed and no loop, by modeling the problem of dependency as a DAG, the dependency becomes a Directed Edge (Directed Edge) in the Graph (Graph), by topological ordering, the non-dependent nodes are continuously traversed and removed, and whether the Directed Graph has a loop is detected to solve the problem of the dependency, however, the service scenarios are various, and if a set of process engine system is self-researched based on each service scenario to support the implementation of the DAG process, the workload is definitely huge.
In chinese patent CN108984284a, a system and a method for generating a DAG task relationship graph are provided, and in chinese patent CN116069462a, a big data DAG task flow scheduling method is provided, the invention performs visual scheduling configuration on a DAG flow based on nginx, an external system accesses a scheduling platform through a cross-platform interface, and transmits instructions to a scheduling center for processing.
The implementation schemes of the two DAG task flows are to actually optimize and package the task scheduling implementation details of the DAG based on specific service scenes, but the implementation of the whole pipeline task flow for the AI training development model has no universality.
Disclosure of Invention
The embodiment of the invention aims to provide a method for realizing DAG process automation based on a process engine Camunda, which solves the problems that the implementation scheme of the existing DAG task flow is to actually optimize and package the task scheduling implementation details of the DAG based on a specific service scene, but the implementation of the whole pipeline task flow of an AI training development model has no universality, and the specific technical scheme is as follows:
according to a first aspect of an embodiment of the present application, there is provided a method for implementing DAG process automation based on a process engine Camunda, the method including:
acquiring DAG flow drawing based on business modeling;
the attribute information of task components in the DAG flow drawing is read, and the association relation between the task components is obtained;
and generating a BPMN flow chart of the executable business process modeling symbol of the Camunda according to the attribute information of the task components and the association relation between the task components.
Optionally, after the reading the attribute information of the task components and the association relationship between the task components in the DAG flow drawing, the method further includes:
determining the component type through the attribute information of the task component;
determining the task type of the node task corresponding to the task component through the component type, wherein the task type comprises the following steps: common tasks and asynchronous tasks;
and determining the serial-parallel relationship between the node tasks through the association relationship between the task components.
Optionally, the generating the Camunda executable business process modeling symbol BPMN flowchart according to the attribute information of the task components and the association relation between the task components includes:
converting the node task belonging to the common task into a first task in the BPMN flow chart;
converting the node task belonging to an asynchronous task into a second task and message component in the BPMN flow diagram;
converting the serial relationship between the node tasks into a task connection mode of an exclusive gateway type in the BPMN flow chart;
and converting the parallel relation between the node tasks into a task connection mode of a parallel gateway type in the BPMN flow chart.
Optionally, the component types include: an input assembly, an output assembly and a template assembly;
after the creating the BPMN flowchart of the operational flow modeling symbol executable by the Camunda according to the attribute information of the task components and the association relation between the task components, the method further includes:
acquiring input stream data in the BPMN flow chart through a node task corresponding to the input component;
outputting log information and node task state information of node task execution through the node task corresponding to the template component;
and summarizing and outputting the stream data output by the node tasks corresponding to the template components through the node tasks corresponding to the output components.
Optionally, the outputting, by the node task corresponding to the template component, log information and status information when the node task is executed includes:
reading input stream data of a father node task to which the node task corresponding to the template component belongs;
and processing the input stream data of the father node task and the attribute information of the node task corresponding to the template component according to a flow.
Optionally, after the converting the node task belonging to the asynchronous task into the second task and message component in the BPMN flowchart, the method further includes:
suspending the subtask of the second task through a message component under the condition that the second task is detected to be started;
activating the message component in response to a notification that the second task processing is complete;
and performing subsequent node tasks for executing the second task through the activated message component.
According to a second aspect of embodiments of the present application, there is provided a DAG process automation device implemented based on a process engine camuda, the device comprising:
the first acquisition module is used for acquiring DAG flow drawing based on business modeling;
the first reading module is used for reading attribute information of task components and association relations among the task components in the DAG flow drawing;
and the first generation module is used for generating the business process modeling symbol BPMN flow chart executable by the Camunda according to the attribute information of the task components and the association relation between the task components.
According to a third aspect of embodiments of the present application, there is provided an electronic device, including:
a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the instructions to implement the DAG process automation method based on the process engine camuda of the first aspect.
According to a fourth aspect of embodiments of the present application, there is provided a computer readable storage medium, which when executed by a processor of a mobile terminal, causes the mobile terminal to perform the process engine Camunda-based DAG process automation method according to the first aspect of the present application.
According to a fifth aspect of embodiments of the present application, there is provided a vehicle including the flow engine camuda-based DAG flow automation device according to the second aspect of the present application.
The technical scheme provided by the embodiment of the application can comprise the following beneficial effects:
according to the invention, through acquiring the DAG flow drawing based on service modeling and reading the attribute information of the task components and the association relation between the task components in the DAG flow drawing, a service flow modeling symbol BPMN flow chart executable by the Camunda is generated according to the attribute information of the task components and the association relation between the task components, the problem that the task scheduling implementation details of the DAG can only be actually optimized and packaged based on specific service scenes is avoided, but the universality of the whole pipeline task flow implementation of an AI training development model is not realized, the requirement of intelligent driving AI training development on long-time and high-frequency efficient circulation is met, and faster iterative update and upgrade are realized.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
FIG. 1 is a flow chart illustrating a method of implementing DAG process automation based on a process engine, camuda, according to an exemplary embodiment;
FIG. 2 is a schematic diagram of a DAG flow drawing layout sample in the implementation of a DAG flow automation method based on a flow engine Camunda shown in FIG. 1, according to an exemplary embodiment;
FIG. 3 is a diagram of an input-output flow process in the implementation of a DAG process automation method based on a process engine Camunda shown in FIG. 1, according to an exemplary embodiment;
FIG. 4 is a flow chart illustrating another method of implementing DAG process automation based on a process engine, camuda, in accordance with an exemplary embodiment;
FIG. 5 is a flowchart of a process for synchronous and asynchronous tasks in another process automation method for implementing a DAG based on a process engine Camunda shown in FIG. 4, according to an exemplary embodiment;
FIG. 6 is a block diagram illustrating a process engine-based, canuda-implemented DAG process automation device in accordance with an exemplary embodiment;
fig. 7 is a block diagram of an electronic device, according to an example embodiment.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the invention. Rather, they are merely examples of apparatus and methods consistent with aspects of the invention as detailed in the accompanying claims.
A first embodiment of the present application relates to a method for implementing DAG process automation based on a process engine Camunda, and fig. 1 is a flowchart illustrating a method for implementing DAG process automation based on a process engine Camunda according to an exemplary embodiment, as shown in fig. 1, including the following steps:
step 101, obtaining DAG flow drawing based on business modeling.
In the embodiment of the invention, the DAG flow drawing based on business modeling is developed and configured by a business party, and the modeled pipeline flow DAG drawing is drawn on a system according to the existing input and output flow definition, and as shown in fig. 2, task arrangement is performed on the system, wherein the task arrangement comprises three types of components, an input component, a template component and an output component, and the input component is used for inputting different types of data and comprises the following steps: the template component comprises a preset platform template component (such as mode conversion) and a user-defined template component (such as data extraction, data de-duplication and data prediction) set by a user according to requirements, and the output component is used for truly outputting data content and comprises: the file, the data set and the scene are edited based on the above components, and the pipeline flow DAG graph is obtained by processing the data (the original single frame data and the data set) acquired by the input component through the template component (the original single frame data is subjected to data prediction and data extraction, the data set is subjected to data extraction, then the original single frame data, the original single frame data subjected to data prediction, and the original single frame data subjected to data extraction are subjected to data combination), and then the output component (file) is used for outputting.
Note that DAG (Directed Acyclic Graph ) is a special directed graph. It allows the construction of many graphs with common properties, but avoids the occurrence of loops, for managing complex task flows, computing task dependencies, and implementing algorithms.
Step 102, the attribute information of the task components and the association relation between the task components in the DAG flow drawing are read.
After the DAG flow drawing based on business modeling is obtained, each node, each side, the circulation relation and the custom attribute configuration information in the DAG flow drawing are read, wherein the nodes in the DAG flow drawing can be regarded as task components because the DAG flow drawing is constructed by different components, the connection line between two nodes in the DAG flow drawing is called as the side, the circulation relation is determined by the side, and the association relation between the task components can be determined by the side and the circulation relation in the DAG flow drawing, so in order to draw the DAG flow drawing into a business flow modeling symbol BPMN flow diagram executable by a Camunda, the attribute information of the task components in the DAG flow drawing and the association relation between the task components need to be obtained first.
And step 103, generating a business process modeling symbol BPMN flow chart executable by the Camunda according to the attribute information of the task components and the association relation between the task components.
In the embodiment of the invention, secondary drawing is performed according to the acquired attribute information of the task components and the association relation between the task components, and a business process modeling symbol BPMN flow chart executable by a Camunda is drawn, wherein before the BPMN flow chart is drawn, the component type is determined through the attribute information of the task components, specifically, the component is judged to be 3 types of input, template and output through a defined modeType field, namely, the component type comprises: an input assembly, an output assembly and a template assembly; after the BPMN flowchart is generated, different tasks can be executed through the nodes corresponding to the corresponding component types, which specifically includes:
acquiring input stream data in the BPMN flow chart through a node task corresponding to the input component;
outputting log information and node task state information of node task execution through the node task corresponding to the template component;
and summarizing and outputting the stream data output by the node tasks corresponding to the template components through the node tasks corresponding to the output components.
Wherein, the BPMN flow chart is converted by DAG flow chart drawing, the basic four element categories of the BPMN flow chart are flow object, data, connection object and track, wherein, the flow object comprises event (such as start event, middle event and end event), the activity comprises task and sub-flow, the gateway comprises: an exclusive gateway, a parallel gateway, a containing gateway and an event gateway; data is represented by four elements, namely a data object, a data input, a data output, and a data storage, wherein a connection object is used for representing that stream objects are mutually connected or connected to other information, and the method comprises the following steps: sequential flow, information flow and association, lanes are groupings of primary modeling elements that divide activities into different visualization categories to describe responsibilities and responsibilities of different participants. In the BPMN flow chart in the embodiment of the invention, which form the data is input by the node task definition corresponding to the input component, which structure the data is output by the node task definition corresponding to the output component, the task component in the DAG flow chart corresponds to the task component in the BPMN flow chart, but for distinguishing, the task component in the BPMN flow chart is called a node task.
For example, as shown in fig. 3, after the DAG flow is drawn into a business flow modeling symbol BPMN flow chart executable by Camunda, the situation of different components is described, after the flow is started, the DAG flow chart is drawn and then converted into a BPMN file executable by Camunda, and a flow definition is saved, wherein the triggering of the flow is performed in two modes, namely, manual triggering and automatic triggering. Once the trigger is successful, an independent task instance is created, when the input stream component processes, the processed external input stream data is subjected to global parameter entering setting of the process so that the subsequent process can read the data configuration of the input stream, namely, the input stream data in the BPMN flow chart can be obtained through the input stream component, when the template component processes, middle execution log information and state information change are output, namely, the log information and the node task state information of node task execution are output through the node task corresponding to the template component, when the output component processes, the output result is summarized, namely, the stream data output by the node tasks corresponding to the template components are summarized and output through the node task corresponding to the output component.
It should be noted that, in the embodiment of the present invention, when the service side processes the defined template component, the service side will read the input stream data of the parent node to which the current node belongs, for example, the current template component corresponds to the input stream 1 and the input stream 2, and then the input of the template component is the combined data of the input stream 1 and the input stream 2. After input stream data is obtained, parameters such as environment variable configuration, self attribute configuration and the like of a template assembly are obtained from the assembly, and script flow processing logic for business is carried out, and specifically comprises the following steps:
reading input stream data of a father node task to which a node task corresponding to a template component belongs;
and processing the input stream data of the parent node task and the attribute information of the node task corresponding to the template component according to the flow.
In addition, after the template component is circulated, the template component is finally summarized to the output component for data customization output. The output component obtains a plurality of template output stream data according to the template connection relation of the father node, takes the template output stream data as input parameter information, carries out final service processing, and finally flows to the ending component of the Canunda, and the flow ends. If an abnormality is detected in the middle of execution of the flow, abnormality information is recorded and the flow is terminated.
According to the invention, through acquiring the DAG flow drawing based on business modeling and reading the attribute information of the task components and the association relation between the task components in the DAG flow drawing, a business flow modeling symbol BPMN flow chart executable by the Camunda is generated according to the attribute information of the task components and the association relation between the task components, the problem that the task scheduling implementation details of the DAG can only be actually optimized and packaged based on specific business scenes is avoided, but the problem that the universality is not achieved for the whole pipeline task flow implementation of an AI training development model is solved, the requirements of intelligent driving AI training development on long-time high-frequency efficient circulation are met, and faster iterative updating and upgrading are realized.
A second embodiment of the present application relates to a method for implementing DAG process automation based on a process engine Camunda, and fig. 4 is a flowchart illustrating another method for implementing DAG process automation based on a process engine Camunda according to an exemplary embodiment, as shown in fig. 4, including the following steps:
step 201, a DAG flow graph based on business modeling is obtained.
Step 202, the attribute information of the task components and the association relation between the task components in the DAG flow drawing are read.
In the embodiment of the present invention, the steps 201 to 202 are discussed with reference to the foregoing, and are not repeated here.
In step 203, the component type is determined by the attribute information of the task component.
After the attribute information of the task components and the association relation between the task components in the DAG flow drawing are read, the secondary drawing is required to be carried out according to the read attribute, and the type of the currently read component is required to be judged firstly, namely the type of the component is judged to be 3 types of input, template and output through a defined modeType field.
Step 204, determining the task type of the node task corresponding to the task component through the component type.
After judging the type of the component, the embodiment of the invention can carry out special processing on the asynchronous task, so that time consumption is reduced, and different task types in a business process modeling symbol BPMN flow chart executable by the Camunda need to be determined according to the type of the component, wherein the task types comprise: common tasks and asynchronous tasks.
In step 205, the serial-parallel relationship between the node tasks is determined by the association relationship between the task components.
In the embodiment of the invention, the serial or parallel relation between the node tasks is determined according to the association relation (the relation of DAG flow stream line) between the task components.
Step 206, converting the node task belonging to the common task into the first task in the BPMN flowchart.
In the embodiment of the invention, after the task type of the node task corresponding to the task component is determined according to the component type in the step, the common task is converted into the first task in the BPMN flow chart, namely the synchronous task which does not need special processing.
Step 207, converting the node task belonging to the asynchronous task into a second task and message component in the BPMN flowchart.
In the embodiment of the invention, the node task belonging to the asynchronous task is converted into the second task and the message component in the BPMN flow chart, so that when the asynchronous task is executed, the subtask of the asynchronous task can be suspended through the message component, then the message notification is carried out after the processing of the third party system is finished, then the message component is activated, and the subsequent flow of the asynchronous task is continuously executed, and the specific implementation steps comprise:
suspending the subtask of the second task through the message component under the condition that the second task is detected to be started;
activating a message component in response to the notification of completion of the second task processing;
and performing subsequent node tasks for executing the second task through the activated message component.
The second task is a task displayed in a BPMN flow chart and converted from an asynchronous task in the DAG flow chart, a subtask of the second task is suspended by a message component and processed by a third party system, so that the processing speed can be increased, for example, as shown in fig. 5, after a flow is started, task configuration parameters are obtained and then tasks are executed, if the task processed synchronously is not needed, after the flow is executed to a specific first task, the subsequent flow step processing is automatically executed, if the task processed asynchronously is executed, an asynchronous task mechanism is adopted to process, namely, a message component suspending flow (the suspended subtask flow of the second task) is entered, then a time-consuming task (namely, the second task) is executed by the third party system, after the time-consuming task is processed, a message notification of task completion is received, a message component is activated, namely, the message component is received, and the asynchronous task is awakened, so that the flow can be enabled to continue to follow-up the subsequent steps, namely, the intermediate execution result is output, the subsequent node task is executed, and the final output flow is summarized.
Step 208, converting the serial relationship between the node tasks into the task connection mode of the exclusive gateway type in the BPMN flowchart.
Step 209, converting the parallel relationship between the node tasks into a task connection mode of parallel gateway type in the BPMN flowchart.
According to the relation of the DAG flow line transfer, if the relation is a serial relation, the exclusive gateway type of the Camunda is subjected to task connection, and if the relation is a parallel relation, the relation is converted into a parallel gateway type to be subjected to task connection.
According to the invention, through acquiring the DAG flow drawing based on service modeling and reading the attribute information of the task components and the association relation between the task components in the DAG flow drawing, a service flow modeling symbol BPMN flow chart executable by the Camunda is generated according to the attribute information of the task components and the association relation between the task components, the problem that the task scheduling implementation details of the DAG can only be actually optimized and packaged based on specific service scenes is avoided, but the universality of the whole pipeline task flow implementation of an AI training development model is not realized, the requirement of intelligent driving AI training development on long-time and high-frequency efficient circulation is met, and faster iterative update and upgrade are realized.
A third embodiment of the present application relates to a DAG process automation device implemented based on a process engine Camunda, and fig. 6 is a flowchart of a DAG process automation device implemented based on a process engine Camunda, as shown in fig. 6, according to an exemplary embodiment, and includes the following steps:
a first obtaining module 301, configured to obtain a DAG flow chart based on business modeling.
The first reading module 302 is configured to read attribute information of task components and association relations between task components in the DAG flowchart.
The first generating module 303 is configured to generate a BPMN flowchart of a business process modeling symbol executable by the Camunda according to attribute information of task components and association relations between task components.
Optionally, the process engine camuda-based DAG process automation device further comprises:
and the first determining module is used for determining the component type through the attribute information of the task component.
The second determining module is configured to determine, according to the component type, a task type of a node task corresponding to the task component, where the task type includes: common tasks and asynchronous tasks.
And the third determining module is used for determining the serial-parallel relationship between the node tasks through the association relationship between the task components.
Optionally, the first generating module 303 further includes:
and the first conversion sub-module is used for converting the node task belonging to the common task into a first task in the BPMN flow chart.
And the second conversion sub-module is used for converting the node task belonging to the asynchronous task into a second task and message component in the BPMN flow chart.
And the third conversion sub-module is used for converting the serial relationship between the node tasks into an exclusive gateway type task connection mode in the BPMN flow chart.
And the fourth conversion sub-module is used for converting the parallel relation between the node tasks into a task connection mode of a parallel gateway type in the BPMN flow chart.
Optionally, the component types include: an input assembly, an output assembly and a template assembly.
The device for realizing DAG process automation based on the process engine Camunda further comprises:
and the second acquisition module is used for acquiring input stream data in the BPMN flow chart through the node task corresponding to the input component.
The first output module is used for outputting log information and node task state information of node task execution through the node task corresponding to the template component.
And the second output module is used for summarizing and outputting the stream data output by the node tasks corresponding to the plurality of template components through the node tasks corresponding to the output components.
Optionally, the first output module further comprises:
and the reading sub-module is used for reading input stream data of the father node task to which the node task corresponding to the template component belongs.
And the information processing sub-module is used for processing the input stream data of the parent node task and the attribute information of the node task corresponding to the template component according to the flow.
Optionally, the process engine camuda-based DAG process automation device further comprises:
and the task suspending module is used for suspending the subtask of the second task through the message component under the condition that the second task is detected to be started.
And the activating module is used for responding to the notification of the completion of the second task processing and activating the message component.
And the execution module is used for executing the subsequent node task of the second task through the activated message component.
According to the invention, through acquiring the DAG flow drawing based on service modeling and reading the attribute information of the task components and the association relation between the task components in the DAG flow drawing, a service flow modeling symbol BPMN flow chart executable by the Camunda is generated according to the attribute information of the task components and the association relation between the task components, the problem that the task scheduling implementation details of the DAG can only be actually optimized and packaged based on specific service scenes is avoided, but the universality of the whole pipeline task flow implementation of an AI training development model is not realized, the requirement of intelligent driving AI training development on long-time and high-frequency efficient circulation is met, and faster iterative update and upgrade are realized.
The specific manner in which the various modules perform the operations in the apparatus of the above embodiments have been described in detail in connection with the embodiments of the method, and will not be described in detail herein.
A fourth embodiment of the present application relates to an electronic device, including: a processor; a memory for storing the processor-executable instructions; wherein the processor is configured to execute the instructions to implement any keyword recognition method.
Fig. 7 is a block diagram illustrating a method for an electronic device 400 according to an example embodiment. For example, electronic device 400 may be a mobile phone, computer, digital broadcast terminal, messaging device, game console, tablet device, medical device, exercise device, personal digital assistant, or the like.
Referring to fig. 7, an electronic device 400 may include one or more of the following components: a processing component 402, a memory 404, a power component 406, a multimedia component 408, an audio component 410, an input/output interface 412, a sensor component 414, and a communication component 416.
The processing component 402 generally controls the overall operation of the apparatus 400, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing component 402 may include one or more processors 420 to execute instructions to perform all or part of the steps of the methods described above. Further, the processing component 402 can include one or more modules that facilitate interaction between the processing component 402 and other components. For example, the processing component 402 may include a multimedia module to facilitate interaction between the multimedia component 408 and the processing component 402.
Memory 404 is configured to store various types of data to support operations at device 400. Examples of such data include instructions for any application or method operating on the apparatus 400, contact data, phonebook data, messages, pictures, videos, and the like. The memory 404 may be implemented by any type or combination of volatile or nonvolatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk.
The power supply component 406 provides power to the various components of the electronic device 400. The power components 406 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the electronic device 400.
The multimedia component 408 includes a screen between the electronic device 400 and the user that provides an output interface. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from a user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensor may sense not only the boundary of a touch or slide action, but also the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 408 includes a front camera and/or a rear camera. When the electronic device 400 is in an operational mode, such as a shooting mode or a video mode, the front-facing camera and/or the rear-facing camera may receive external multimedia data. Each front camera and rear camera may be a fixed optical lens system or have focal length and optical zoom capabilities.
The audio component 410 is configured to output and/or input audio signals. For example, the audio component 410 includes a Microphone (MIC) configured to receive external audio signals when the electronic device 400 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may be further stored in the memory 404 or transmitted via the communication component 416. In some embodiments, audio component 410 further includes a speaker for outputting audio signals.
The input/output interface 412 provides an interface between the processing component 402 and peripheral interface modules, which may be a keyboard, click wheel, buttons, etc. These buttons may include, but are not limited to: homepage button, volume button, start button, and lock button.
The sensor assembly 414 includes one or more sensors for providing status assessment of various aspects of the electronic device 400. For example, the sensor assembly 414 may detect an on/off state of the electronic device 400, a relative positioning of the components, such as a display and keypad of the electronic device 400, the sensor assembly 414 may also detect a change in position of the electronic device 400 or a component of the electronic device 400, the presence or absence of a user's contact with the electronic device 400, an orientation or acceleration/deceleration of the electronic device 400, and a change in temperature of the electronic device 400. The sensor assembly 414 may include a proximity sensor configured to detect the presence of nearby objects in the absence of any physical contact. The sensor assembly 414 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 414 may also include an acceleration sensor, a gyroscopic sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
The communication component 416 is configured to facilitate communication between the electronic device 400 and other devices, either wired or wireless. The electronic device 400 may access a wireless network based on a communication standard, such as WiFi, an operator network (e.g., 2G, 3G, 4G, or 5G), or a combination thereof. In one exemplary embodiment, the communication component 416 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 416 further includes a Near Field Communication (NFC) module to facilitate short range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, ultra Wideband (UWB) technology, bluetooth (BT) technology, and other technologies.
In an exemplary embodiment, the electronic device 400 may be implemented by one or more Application Specific Integrated Circuits (ASICs), digital Signal Processors (DSPs), digital Signal Processing Devices (DSPDs), programmable Logic Devices (PLDs), field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic elements for executing the methods described above.
In an exemplary embodiment, the fifth implementation of the present application also provides a non-transitory computer-readable storage medium, such as memory 404, comprising instructions executable by processor 420 of electronic device 400 to perform the above-described method. For example, the non-transitory computer readable storage medium may be ROM, random Access Memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, etc.
A sixth embodiment of the present application relates to a vehicle to implement any one of the flow engine based camuda implementation DAG flow automation devices.
For the device embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, and reference is made to the description of the method embodiments for relevant points.
Other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names. The invention is not limited to the precise construction which has been described above and shown in the drawings, and various modifications and changes may be made without departing from the scope thereof. The scope of the invention is limited only by the appended claims.
Claims (10)
1. A method for implementing DAG process automation based on a process engine camuda, the method comprising:
acquiring DAG flow drawing based on business modeling;
the attribute information of task components in the DAG flow drawing is read, and the association relation between the task components is obtained;
and generating a BPMN flow chart of the executable business process modeling symbol of the Camunda according to the attribute information of the task components and the association relation between the task components.
2. The method according to claim 1, wherein after the reading the attribute information of the task components and the association relationship between the task components in the DAG flow graph, further comprises:
determining the component type through the attribute information of the task component;
determining the task type of the node task corresponding to the task component through the component type, wherein the task type comprises the following steps: common tasks and asynchronous tasks;
and determining the serial-parallel relationship between the node tasks through the association relationship between the task components.
3. The method according to claim 2, wherein the generating the Camunda executable business process modeling symbol BPMN flowchart according to the attribute information of the task components and the association relation between task components comprises:
converting the node task belonging to the common task into a first task in the BPMN flow chart;
converting the node task belonging to an asynchronous task into a second task and message component in the BPMN flow diagram;
converting the serial relationship between the node tasks into a task connection mode of an exclusive gateway type in the BPMN flow chart;
and converting the parallel relation between the node tasks into a task connection mode of a parallel gateway type in the BPMN flow chart.
4. The method of claim 2, wherein the component types include: an input assembly, an output assembly and a template assembly;
after the creating the BPMN flowchart of the operational flow modeling symbol executable by the Camunda according to the attribute information of the task components and the association relation between the task components, the method further includes:
acquiring input stream data in the BPMN flow chart through a node task corresponding to the input component;
outputting log information and node task state information of node task execution through the node task corresponding to the template component;
and summarizing and outputting the stream data output by the node tasks corresponding to the template components through the node tasks corresponding to the output components.
5. The method according to claim 4, wherein the outputting the log information and the status information of the node task execution by the node task corresponding to the template component includes:
reading input stream data of a father node task to which the node task corresponding to the template component belongs;
and processing the input stream data of the father node task and the attribute information of the node task corresponding to the template component according to a flow.
6. The method of claim 3, further comprising, after said converting said node task belonging to an asynchronous task to a second task and message component in said BPMN flow diagram:
suspending the subtask of the second task through a message component under the condition that the second task is detected to be started;
activating the message component in response to a notification that the second task processing is complete;
and performing subsequent node tasks for executing the second task through the activated message component.
7. A process engine camuda-based DAG process automation device, comprising:
the first acquisition module is used for acquiring DAG flow drawing based on business modeling;
the first reading module is used for reading attribute information of task components and association relations among the task components in the DAG flow drawing;
and the first generation module is used for generating the business process modeling symbol BPMN flow chart executable by the Camunda according to the attribute information of the task components and the association relation between the task components.
8. An electronic device, comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to execute the instructions to implement the steps in the DAG process automation method based on the process engine camuda of any of claims 1-6.
9. A computer readable storage medium, wherein instructions in the storage medium, when executed by a processor of a mobile terminal, enable the mobile terminal to perform the steps in the DAG process automation method based on a process engine camuda according to any of claims 1-6.
10. A vehicle comprising the process engine camuda-based DAG process automation device of claim 7.
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