Task management method, system, computer program and device of cloud computing platform

Abstract

The embodiments of this disclosure generally relate to the field of data analysis technology, specifically to a task processing method based on the R Shiny application, a Shiny server and client for processing tasks, a computer program, and an electronic device. The server method includes, in response to receiving a submitted task from the Shiny client, creating a task entry corresponding to the task in a task database, and configuring the task status of the created task entry to a first state. The method further includes polling the task database to initiate one or more tasks corresponding to one or more task entries in the task database whose task status is in the first state, and configuring the task status of the initiated task's corresponding task entry to a second state. The method also includes, in response to task completion, configuring the task status of the task entry corresponding to the completed task in the task database to a third state. This method can prevent the loss of calculation results when the current browser page is closed or refreshed.

Description

Technical Field

[0001] The embodiments disclosed herein generally relate to the field of cloud computing technology, and specifically to a task management method, system, computer program, and device for a cloud computing platform. Background Technology

[0002] Cloud computing platforms frequently need to process various batch tasks submitted by different users, mainly including task acquisition, task execution, and result feedback. However, cloud computing platforms handle a large number of tasks, with unpredictable task initiation times, varying resource requirements, and different computing environments offering different resources. Therefore, unified management of various tasks submitted by different users is necessary. Summary of the Invention

[0003] Embodiments of this disclosure provide a task management method, system, computer program product, and electronic device for a cloud computing platform, designed to address one or more of the problems described above and other potential problems.

[0004] According to a first aspect of this disclosure, a task management method for a cloud computing platform is provided. This method includes querying a process to poll a task data file containing one or more task entries, and adding task objects generated based on the task entries to a task queue. The task objects include a task execution path, task execution program parameters, and a task feedback address. Furthermore, the method includes a delivery thread allocating task objects from the task queue to idle worker threads, wherein the delivery thread has a corresponding worker thread pool, and the worker thread pool includes one or more worker threads.

[0005] According to a second aspect of this disclosure, a task management system for a cloud computing platform is provided. The system includes a task query module configured to poll a task data file containing one or more task entries via a query process, and add task objects generated based on the task entries to a task queue. Each task object includes a task execution path, task execution program parameters, and a task feedback address. The system also includes a task delivery module configured to allocate task objects from the task queue to idle worker threads via delivery threads. Each delivery thread has a corresponding worker thread pool, which includes one or more worker threads.

[0006] According to a third aspect of this disclosure, a computer program product is provided, comprising a computer program. When executed by a processor, the computer program implements the method of the first aspect described above.

[0007] According to a fourth aspect of this disclosure, an electronic device is provided, including one or more processors and a memory associated with the one or more processors. The memory is used to store program instructions that, when read and executed by the one or more processors, perform the steps of the method described in the first aspect. Attached Figure Description

[0008] The above and other objects, features, and advantages of embodiments of the present disclosure will become readily apparent from the following detailed description taken in conjunction with the accompanying drawings. Several embodiments of the present disclosure are illustrated in the drawings by way of example and not limitation.

[0009] Figure 1 An exemplary application scenario diagram of a task management method for a cloud computing platform according to an embodiment of the present disclosure is shown.

[0010] Figure 2 A flowchart illustrating a task management method for a cloud computing platform according to an embodiment of the present disclosure is shown.

[0011] Figure 3 A schematic diagram illustrating the working process of a query process in a task management method for a cloud computing platform according to an embodiment of the present disclosure.

[0012] Figure 4 An exemplary system diagram of a task management system for a cloud computing platform according to an embodiment of the present disclosure is shown.

[0013] Figure 5 A block diagram illustrating an electronic device according to an embodiment of the present disclosure.

[0014] In the various figures, the same or corresponding reference numerals indicate the same or corresponding parts. Detailed Implementation

[0015] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0016] In the description of embodiments of this disclosure, the term "comprising" and similar terms should be understood as open-ended inclusion, i.e., "including but not limited to". The term "based on" should be understood as "at least partially based on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The terms "first", "second", etc., may refer to different or the same objects. Other explicit and implicit definitions may also be included below.

[0017] As mentioned earlier, cloud computing platforms often need to process various batch tasks submitted by different users, mainly including task acquisition, task execution, and result feedback. However, cloud computing platforms handle a large number of tasks, with unpredictable task initiation times, varying resource requirements for different tasks, and different computing environments offering different resources.

[0018] In existing technologies, task management typically only allows users to set the resources required for a single task, which is then submitted for execution via task submission software such as qsub or bash. This submission method relies on each task being initiated by the user individually, resulting in untimely submission of batches of tasks.

[0019] In view of this, embodiments of this specification provide a task management method for a cloud computing platform. This method may include: querying a process to poll a task data file containing one or more task entries; adding task objects generated based on the task entries to a task queue, wherein the task object includes a task execution path, task execution program parameters, and a task feedback address. Furthermore, the method may also include a delivery thread allocating task objects in the task queue to idle worker threads, wherein the delivery thread has a corresponding worker thread pool, and the worker thread pool includes one or more worker threads. Using this method according to embodiments of this disclosure, various tasks submitted by different users can be uniformly managed, user tasks can be acquired and automatically delivered in real time, and task execution results can be promptly and proactively fed back based on the task feedback address.

[0020] The embodiments of this disclosure will now be described in further detail with reference to the accompanying drawings. Figure 1 An exemplary application environment for a task management method of a cloud computing platform, as illustrated in embodiments of this disclosure, is provided. Figure 1As shown, environment 100 includes a user terminal 101, a cloud computing platform 102, and server computing resources consisting of one or more computing nodes 103. The user terminal 101 is a physical or virtual device that a user can directly operate, used to initiate task requests and receive task feedback, serving as the interaction entry point for cloud services. For example, the user terminal 101 can be a personal computer, smartphone, IoT sensor, smart speaker, or other computing device with input / output capabilities that relies on a network connection and can act as an access medium. Users can remotely input user tasks to the cloud computing platform 102 through the API interface of the user terminal. In one or more embodiments of this disclosure, the user terminal 101 and the cloud computing platform 102 can also be integrated into a single computing device, and user tasks can be directly written by a local user on the cloud computing platform 102. The cloud computing platform 102 is a software system for receiving, scheduling, and managing computing tasks. It may include components such as a load balancer and a resource scheduler, responsible for receiving requests from the user terminal 101 and allocating them to specific computing nodes 103 according to a preset strategy. The server computing resources consist of one or more physical servers deployed in a data center, and each physical server can be divided into one or more computing nodes 103 through virtualization technology. Compute node 103 is the basic unit that cloud computing platform 102 can schedule and execute tasks, and it can take the form of virtual machines, containers, or bare metal servers. In environment 100, user terminal 101, cloud computing platform 102, and compute node 103 cooperate in the following manner: user terminal 101 sends a task request to cloud computing platform 102; cloud computing platform 102 parses the request and selects one or more qualified compute nodes 103 from its managed resource pool to execute the task; after the task is completed, the generated result data is returned to user terminal 101 via cloud computing platform 102.

[0021] The following is combined Figure 2 This disclosure describes a task management method 200 for a cloud computing platform 102 according to embodiments of the present disclosure. It should be understood that the numbers in the flowchart of method 200 do not indicate the order in which these steps are executed; some or all of these steps may be executed in parallel, or their execution order may be interchanged, and this disclosure does not limit this. Furthermore, Figure 1 The methods described may also include additional steps not shown and / or the steps shown may be omitted, and the scope of this disclosure is not limited in this respect.

[0022] like Figure 2As shown in block 202, method 200 may include: a query process polling a task data file, the task data file including one or more task entries. The query process generates a task correspondence based on the task entries in the task data file and adds the generated task object to the task queue. The task object includes a task execution path, task execution program parameters, and a task feedback address. In one or more embodiments of this disclosure, for each user task received by the cloud computing platform, a new task entry can be created in the task data file to store relevant information about the user task. The task data file can be a text document in a specific format or a database organized in the form of a structured table or an unstructured document. In one or more embodiments of this disclosure, the cloud computing platform can also perform permission verification. When a user submits a user task through user terminal 101, the cloud computing platform can intercept the user request and perform permission verification. Only when the user permission verification is successful, confirming that the user has the permission to execute the corresponding user task, will the user be granted write permission to the task data file, thereby allowing the user to add a user entry corresponding to the user task to the task data file. In one or more embodiments of this disclosure, the query thread can be a dedicated thread for querying user tasks in the task data file. For example, the query thread can poll the task data file at preset time intervals to obtain user tasks in a timely manner and add task objects generated based on the user tasks to the task queue, ensuring that user tasks can be processed promptly. In one or more embodiments of this disclosure, the task object is used to encapsulate the executable object corresponding to the executable task entry, containing the parameters and execution logic required during execution. For example, the task object generated based on the task entry may include a task execution path, which can be the absolute path of the binary file executing the task on the server, and can be stored as a string. The task object generated based on the task entry may also include task execution program parameters, which can be program parameters required to execute the user task. The program parameters for different user tasks may be different, and the task execution program parameters can also be stored as a string. The task object generated based on the task entry may also include a task feedback address, which is used to promptly provide feedback on the execution result of the user task. It can be an address where the user to whom the user task belongs can receive the task execution feedback result. For example, the task feedback address can be the user's email address, other link address, or storage location, so that the user can be notified promptly when the user task is executed successfully or fails. In one or more embodiments of this disclosure, a task queue is a thread-safe data structure used to store and manage task objects, and a query process can submit task objects generated based on task entries to the task queue for processing.

[0023] In box 204, method 200 may include: a delivery thread assigning task objects from a task queue to idle worker threads, wherein the delivery thread has a corresponding worker thread pool, and the worker thread pool includes multiple worker threads. In one or more embodiments of this disclosure, there may be one or more delivery threads, each delivery thread maintaining a thread pool composed of multiple worker threads, and the worker threads are responsible for actually executing user tasks. The worker thread pool implements task scheduling and load balancing through a thread pool framework. In one or more embodiments of this disclosure, the delivery thread can pull task objects from the task queue to obtain user tasks to be executed and assign them to idle worker threads in the worker thread pool. The task feedback address is passed to the worker thread along with the task object. During the execution of the user task, the worker thread can send different feedback information to the user based on whether the return value is normal (if the return value is normal, the task is completed normally; if the return value is abnormal, the task has failed), actively notifying the user of the execution progress and result of the task. In this way, the querying of task entries and the delivery of task objects are carried out independently by the querying process and the delivery process, respectively. This allows the querying of task entries to continue without waiting for the delivery and processing results of the previous task entry, thereby improving the speed at which user tasks are assigned and processed.

[0024] In one or more embodiments of this disclosure, method 200 may further include the step of receiving user tasks. In addition to the task execution path, task execution program parameters, and task feedback address, the cloud computing platform may also require the user-submitted user task to include information related to task resource requirements, facilitating the query thread to select appropriate task entries and generate task objects based on the current system load and the resource requirements of each user task. Subsequently, the cloud computing platform can create task entries corresponding to the user task in the task data file based on the received user task. The task entry includes the task execution path, task execution program, task resource requirements, task feedback address, and task status. The task status indicates the execution status of the user task. In one or more embodiments of this disclosure, the task status has four options (not executed, running, successful, failed). When a task entry is created, its task status is configured as a first state indicating not executed. When the task object generated by the query thread based on the task entry is added to the task queue, its task status is configured as a second state indicating the task is running. During the execution of user tasks based on task objects by worker threads, if the return value is normal, the task is completed normally, and its task status is configured as the third state, indicating successful task execution. If the return value is abnormal, the task has failed, and its task status is configured as the fourth state, indicating execution failure. In this way, the task data file simultaneously records the execution status of the task, making it convenient for users to actively refresh the page or actively obtain the execution status of user tasks through other query methods. In one or more embodiments of this disclosure, when the query process generates a task object based on a task entry, it can create a task object including attributes such as task execution path, task execution program parameters, task feedback address, and task status. According to the relevant information of the task entry, the task execution path of the task entry is assigned to the task execution path attribute of the task object, the task execution program parameters of the task entry are assigned to the task execution program parameter attribute of the task object, the task feedback address of the task entry is assigned to the task feedback address attribute of the task object, and the task status attribute of the task object is set to the first state, thus completing the generation of the task object. Subsequently, the generated task object is submitted to the task queue for the submission program to submit to the worker thread pool for processing.

[0025] Figure 3 This diagram illustrates the working process of a query process in a task management method for a cloud computing platform according to an embodiment of the present disclosure. Figure 3 As shown, in one or more embodiments of this disclosure, the query thread can select appropriate task entries to generate task objects and add them to the task queue based on the total system load. Specifically, at box 202:

[0026] First, query thread 302 can determine an executable task entry with a first state from one or more task entries in task data file 301. In one or more embodiments of this disclosure, the task data file stores and maintains user-submitted user tasks. Therefore, the task data file includes not only unsubmitted user tasks but also submitted user tasks. When querying the task data file, the query process needs the task state of the task entries to filter out task entries that have not yet been submitted. In one or more embodiments of this disclosure, for task data files in text file format, the query thread can read the task entry information line by line in the text file to determine whether the task state of the task entry is the first state. For task data files in database format, task entries with a task state of "not executed" (i.e., the first state) can be retrieved using SQL.

[0027] Subsequently, query thread 302 will determine whether the task entry to be executed can be submitted to the task list based on the task resource requirements of the task entry to be executed and the current total system load. If it is determined that the task entry to be executed can be submitted, a task object generated based on the task entry to be executed will be added to the task queue 303. If it is determined that the task entry to be executed cannot be submitted, the task status of the task entry will not be changed, and the query thread will perform the next query. In one or more embodiments of this disclosure, the task resource requirements can be memory requirements and thread requirements, where memory requirements refer to the amount of memory required to execute the task (in GB or MB), and thread requirements (in units of 1). In one or more embodiments of this disclosure, an information bar corresponding to the task resource requirements can be added to the window where the user submits the user task, requiring the user to report the number of memory and threads required for the task to the cloud computing platform when submitting the task. In one or more embodiments of this disclosure, the query thread can determine the task load of the task to be executed based on the task resource requirements of the task entry to be executed, and determine whether the task entry to be executed can be submitted by comparing whether the sum of the task load and the current total system load exceeds a preset load threshold.

[0028] In one or more embodiments of this disclosure, the total system load can be a global variable of the query thread, and the load threshold can be a global constant with a value of 1 for the query thread. When the query thread starts, the total system load is initialized to 0. The query thread can calculate the task load of the tasks to be executed based on the total free memory of the system, the total free threads of the system, and the task resource requirements of the tasks to be executed. The total free memory and total free threads of the system can be the sum of currently available free memory and free threads in the automatically acquired server computing resources, or they can be based on the free memory and free threads allowed to be used in the server computing resources according to pre-set parameters. By pre-setting these parameters, the server can be kept at a certain level of idle time or a predetermined degree of overload to achieve the optimal state of the server. In one or more embodiments of this disclosure, the task load of the tasks to be executed can be calculated according to Formula 1-1:

[0029]

[0030] That is, the larger of the ratio of memory requirement to total system free memory and the ratio of thread requirement to total system threads is used as the task load of the task to be executed. In one or more embodiments of this disclosure, after the query thread determines that the task to be executed can be submitted, the sum of the task load of the task to be executed and the current total system load is used as the current total system load. In this way, the query thread can monitor the system load of the cloud computing server through the total system load, promptly submit task items that meet the resource requirements to the task queue for delivery, and avoid the problem of server crashes caused by excessive server resource consumption due to isolated delivery of different tasks.

[0031] Figure 4 An exemplary system diagram of a task management system for a cloud computing platform according to an embodiment of the present disclosure is shown. The various embodiments in this specification are described in a progressive manner, with reference to each other for similar or identical parts. Each embodiment focuses on describing the differences from other embodiments. In particular, the apparatus embodiments are basically similar to the method embodiments, so the description is relatively simple, and relevant parts can be referred to in the description of the method embodiments. Figure 4As shown, in one or more embodiments of this disclosure, the task management system 400 may include a task query module 401. The task query module is configured to poll a task data file containing one or more task entries through a query process, and add task objects generated based on the task entries to a task queue. The task objects include a task execution path, task execution program parameters, and a task feedback address. In one or more embodiments of this disclosure, the task management system 400 may also include a task delivery module 402, configured to allocate task objects in the task queue to idle worker threads through a delivery thread. The delivery thread has a corresponding worker thread pool, which includes one or more of the worker threads. In this way, the querying of task entries and the delivery of task objects are performed independently by the query process and the delivery process, respectively, allowing the querying of task entries to proceed continuously without waiting for the delivery and processing results of the previous task entry, thus improving the speed of user task allocation and processing.

[0032] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this specification are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in or transmitted through a computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., Digital Versatile Discs (DVDs)), or semiconductor media (e.g., Solid State Disks (SSDs)).

[0033] Figure 5 A block diagram of an electronic device 500 that can implement various embodiments of the present disclosure is shown. For example... Figure 5As shown, the electronic device 500 includes a processor 510, a disk drive 520, an input / output interface 530, a network interface 540, and a memory 550. The processor 510, disk drive 520, input / output interface 530, network interface 540, and memory 550 can communicate with each other via a communication bus 560.

[0034] The processor 510 can be implemented using a general-purpose CPU, microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits to execute relevant programs and implement the technical solution provided in this application.

[0035] The memory 550 can be implemented in the form of ROM (Read Only Memory), RAM (Read Access Memory), static memory, dynamic storage devices, etc. The memory 550 can store the operating system 551 used to control the operation of the electronic device 500, and the basic input / output system (BIOS) 552 used to control the low-level operations of the electronic device 500. Additionally, it can store a web browser 553, a data storage management system 554, etc. In summary, when implementing the technical solution provided in this application through software or firmware, the relevant program code is stored in the memory 550 and is called and executed by the processor 510.

[0036] Input / output interface 530 is used to connect input / output modules to realize information input and output. Input / output modules can be configured as components in the device (not shown in the figure) or externally connected to the device to provide corresponding functions. Input devices may include keyboards, mice, touch screens, microphones, various sensors, etc., and output devices may include displays, speakers, vibrators, indicator lights, etc.

[0037] Network interface 540 is used to connect a communication module (not shown in the figure) to enable communication and interaction between the device and other devices. The communication module can communicate via wired means (e.g., USB, Ethernet cable) or wireless means (e.g., mobile network, Wi-Fi, Bluetooth).

[0038] Bus 560 includes a pathway for transmitting information between various components of the device, such as processor 510, disk drive 520, input / input interface 530, network interface 540, and memory 550.

[0039] It should be noted that although the above-described device only shows the processor 510, disk drive 520, input / output interface 530, network interface 540, memory 550, bus 560, etc., in specific implementations, the device may also include other components necessary for normal operation. Furthermore, those skilled in the art will understand that the above-described device may only include the components necessary for implementing the method of this application, and does not necessarily include all the components shown in the figures.

[0040] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0041] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing. Furthermore, although operations are depicted in a specific order, this should be understood as requiring that such operations be performed in the specific order shown or in sequential order, or requiring that all illustrated operations be performed to achieve the desired result. In certain environments, multitasking and parallel processing may be advantageous. Similarly, while several specific implementation details are included in the foregoing discussion, these should not be construed as limiting the scope of this disclosure. Certain features described in the context of individual embodiments may also be implemented in combination in a single implementation. Conversely, various features described in the context of a single implementation may also be implemented individually or in any suitable sub-combination in multiple implementations.

[0042] Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely illustrative examples of implementing the claims.

Claims

1. A task management method for a cloud computing platform, characterized in that, include: The process polling includes a task data file containing one or more task entries. A task object generated based on the task entry is added to the task queue. The task object includes the task execution path, task execution program parameters, and task feedback address. as well as The delivery thread assigns task objects in the task queue to idle worker threads, wherein the delivery thread has a corresponding worker thread pool, and the worker thread pool includes multiple worker threads.

2. The method according to claim 1, characterized in that, Also includes: Receive user tasks, which include task execution path, task execution program parameters, task resource requirements, and task feedback address; as well as Based on the received user task, a task entry corresponding to the user task is created in the task data file. The task entry includes the task execution path, the task execution program, the task resource requirements, the task feedback address, and the task status. The initial value of the task status is a first state.

3. The method according to claim 2, characterized in that, The query process polls a task data file containing one or more task entries, and adds a task object generated based on the task entry to the task queue, including: From one or more task entries in the task data file, determine an execution task entry with a first task status; Based on the task resource requirements of the pending task entries and the current total system load, determine whether the pending task entries can be submitted; and In response to determining that the task entry to be executed is ready to be submitted, a task object generated based on the task entry to be executed is added to the task queue.

4. The method according to claim 3, characterized in that, The process of determining whether a task entry can be submitted based on its resource requirements and the current total system load includes: Obtain the task resource requirements of the task to be executed, including memory requirements and thread requirements; Based on the memory requirements and the thread requirements, the task load of the task entries to be executed is determined; Compare whether the sum of the task load and the current total system load exceeds a load threshold; and In response to the fact that the sum of the task load and the current total system load does not exceed the load threshold, the task entry to be executed is determined to be ready for submission.

5. The method according to claim 4, characterized in that, The process of determining the task load of the task entry to be executed based on the memory requirements and the thread requirements includes: Based on the memory requirements, determine the percentage of the total free memory in the system. Based on the stated thread requirements, determine the proportion of those requirements in the total number of free threads in the system; and The larger of the memory requirement as a percentage of total system memory and the thread requirement as a percentage of total system threads is taken as the task load of the task to be executed.

6. The method according to claim 5, characterized in that, In response to determining that the task entry to be executed is ready for submission, a task object generated based on the task entry to be executed is added to the task queue: Based on the task execution path, task execution parameters, and task feedback address of the task entry to be executed, the task object is generated; Submit the task object to the task queue; as well as Configure the task status of the task entry to be submitted to the second status.

7. The method according to claim 6, characterized in that, The initial value of the total system load is 0, the load threshold is 1, and the step of adding a task object generated based on the task entry to the task queue in response to determining that the task entry to be executed can be submitted further includes: The sum of the task load and the current total system load is taken as the current system load.

8. A task management system for a cloud computing platform, characterized in that, include: The task query module is configured to poll a task data file containing one or more task entries by querying the process, and add a task object generated based on the task entry to the task queue, wherein the task object includes a task execution path, task execution program parameters and task feedback address. as well as The task delivery module is configured to assign task objects in the task queue to idle worker threads via a delivery thread, wherein the delivery thread has a corresponding worker thread pool, and the worker thread pool includes one or more of the worker threads.

9. A computer program product comprising a computer program that, when executed by a processor, implements the method according to any one of claims 1-7.

10. Electronic devices, including: One or more processors, and A memory associated with the one or more processors, the memory being used to store program instructions that, when read and executed by the one or more processors, perform the steps of the method according to any one of claims 1-7.

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