CN114897372A - Task monitoring method, device, equipment and storage medium - Google Patents

Abstract

The invention relates to the technical field of cloud computing, is applied to the field of smart cities, and discloses a task monitoring method, which comprises the following steps: acquiring a task dependency relationship table of a terminal task; generating a standard execution plan for the ending task according to the task dependency relationship table and the task operation time acquired in the historical time period; generating a dynamic execution plan for the ending task according to the task dependency relationship table and the currently acquired task operation time; comparing the dynamic execution plan with a standard execution plan to judge whether a mutation task exists; and if so, outputting information related to the mutation task as early warning information. Because all tasks do not need to be monitored independently, the full-link monitoring can be realized only by focusing on the peripheral tasks, and the monitoring configuration efficiency is improved. And by generating the dynamic execution plan in real time and monitoring the sudden change of the dynamic execution plan, the abnormal sudden change task can be quickly positioned, the event processing flow is promoted, and the monitoring in the task is realized so as to discover hidden dangers in advance.

Description

A task monitoring method, device, equipment and storage medium

technical field

The present invention relates to the technical field of cloud computing, in particular to a task monitoring method, device, equipment and storage medium.

Background technique

One of the existing task monitoring methods is based on the timeliness monitoring of a single task, that is, when the task completion time exceeds the agreed time or the intermediate task completion time exceeds the latest start time of the subsequent task, an alarm is triggered; the other is for key task modules. Or the overall task progress of the data layer is monitored, and an alarm is triggered when a task is not completed within the preset time.

However, the above two task monitoring methods belong to the monitoring and early warning after the event, which is generally triggered after an abnormality occurs. For technicians, it is more about the implementation of emergency plans and the temporary scheduling of resources. Therefore, the existing task monitoring methods are not sufficient. Useful for early warning.

SUMMARY OF THE INVENTION

The purpose of the present invention is to propose a task monitoring method, device, device and storage medium for the deficiencies of the above-mentioned prior art, and the purpose is achieved through the following technical solutions.

A first aspect of the present invention proposes a task monitoring method, the method comprising:

Get the task dependency table of the stub tasks located in the lowest task layer;

generating a standard execution plan for the peripheral task according to the task dependency table and the task running time collected in the historical time period;

generating a dynamic execution plan for the peripheral task according to the task dependency table and the currently collected task running time;

Comparing the dynamic execution plan with the standard execution plan to determine whether there is a mutation task in the dynamic execution plan;

If it exists, the information related to the mutation task is output as early warning information.

In some embodiments of the present application, generating a standard execution plan for the peripheral task according to the task dependency relationship table and the task running time collected in a historical time period includes:

For each task layer, obtain at least one task located in the task layer from the task dependency table; select a task from the at least one task as the key of the task layer according to the task running time collected in the historical time period Tasks; use the critical tasks of each task layer to generate standard execution plans for the peripheral tasks.

In some embodiments of the present application, selecting a task from the at least one task as a key task of the task layer according to the task running time collected in a historical time period includes:

According to the task running time collected in the historical time period, the average running time of each task is determined; the task corresponding to the longest average running time is selected as the key task of the task layer.

In some embodiments of the present application, generating a dynamic execution plan for the peripheral task according to the task dependency relationship table and the currently collected task running time includes:

For each task layer, obtain at least one task located in the task layer from the task dependency table; select a task from the at least one task as the key task of the task layer according to the currently collected task running time; use The critical tasks of each task layer generate dynamic execution plans for the peripheral tasks.

In some embodiments of the present application, selecting a task from the at least one task as the key task of the task layer according to the currently collected task running time includes:

Select the task corresponding to the longest task running time currently collected as the key task of the task layer.

In some embodiments of the present application, comparing the dynamic execution plan with the standard execution plan to determine whether there is a mutation task in the dynamic execution plan includes:

The dynamic execution plan is compared with the key tasks belonging to the same task layer in the standard execution plan; if the comparison is inconsistent, it is determined that the key tasks belonging to the task layer included in the dynamic execution plan are mutation tasks.

In some embodiments of the present application, the method further includes:

For each task in each task layer, obtain the time difference between the task running time currently collected for the task and the task running time collected last time; if the time difference exceeds a preset threshold, the information related to the task is used as Warning information output.

A second aspect of the present invention provides a task monitoring device, the device comprising:

The acquisition module is used to acquire the task dependency table of the stub tasks located in the lowest task layer;

a first generating module, configured to generate a standard execution plan for the peripheral task according to the task dependency table and the task running time collected in the historical time period;

A second generation module, configured to generate a dynamic execution plan for the peripheral task according to the task dependency table and the currently collected task running time;

a comparison module, configured to compare the dynamic execution plan with the standard execution plan to determine whether there is a mutation task in the dynamic execution plan;

The early warning module is used for outputting the information related to the mutation task as early warning information when it is determined that there is a mutation task.

A third aspect of the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor implementing the program as described in the first aspect above when the processor executes the program steps of the method described.

A fourth aspect of the present invention provides a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, implements the steps of the method described in the above-mentioned first aspect.

Based on the task monitoring method and device described in the first aspect and the second aspect, the present invention has at least the following beneficial effects or advantages:

The invention focuses on the peripheral tasks, outputs a standard execution plan for the peripheral tasks in combination with the historical execution data and the task dependency table, and outputs a dynamic execution plan for the peripheral tasks in combination with the current execution data and the task dependency table in real time. The dynamic execution plan is compared to discover mutation tasks, so as to complete the full-link monitoring of related tasks. Since it is no longer necessary to individually evaluate and monitor all tasks, it is only necessary to focus on peripheral tasks to achieve full-link monitoring, which is conducive to quickly reaching a consensus goal and improving the efficiency of monitoring configuration. And by generating a dynamic execution plan in real time and monitoring the mutation of the dynamic execution plan, it can quickly locate abnormal mutation tasks, promote the event processing process, and realize in-process monitoring of tasks, so as to discover hidden dangers and avoid risks in advance.

The invention can be applied to the technical field of smart cities, thereby promoting the construction of smart cities.

Description of drawings

The accompanying drawings described herein are used to provide further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the attached image:

1 is a flowchart of an embodiment of a task monitoring method according to an exemplary embodiment of the present invention;

FIG. 2 is a schematic structural diagram of a task monitoring device according to an exemplary embodiment of the present invention;

3 is a schematic diagram of a hardware structure of an electronic device according to an exemplary embodiment of the present invention;

FIG. 4 is a schematic structural diagram of a storage medium according to an exemplary embodiment of the present invention.

Detailed ways

Exemplary embodiments will be described in detail herein, examples of which are illustrated in the accompanying drawings. Where the following description refers to the drawings, the same numerals in different drawings refer to the same or similar elements unless otherwise indicated. The implementations described in the illustrative examples below are not intended to represent all implementations consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with some aspects of the invention as recited in the appended claims.

The terminology used in the present invention is for the purpose of describing particular embodiments only and is not intended to limit the present invention. As used in this specification and the appended claims, the singular forms "a," "the," and "the" are intended to include the plural forms as well, unless the context clearly dictates otherwise. It will also be understood that the term "and/or" as used herein refers to and includes any and all possible combinations of one or more of the associated listed items.

It should be understood that although the terms first, second, third, etc. may be used in the present invention to describe various information, such information should not be limited by these terms. These terms are only used to distinguish the same type of information from each other. For example, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information, without departing from the scope of the present invention. Depending on the context, the word "if" as used herein can be interpreted as "at the time of" or "when" or "in response to determining."

The big data business analysis platform provides managers with data such as indicator dashboards and attribution analysis. The data processing tasks that the indicator data depends on are arranged and scheduled for execution according to the established dependencies. Each task involves hundreds of upstream dependent tasks. Therefore, the monitoring of task runtime is especially critical.

In the big data business analysis platform, all tasks mainly belong to three data layers: operational data warehouse layer (ODS), data warehouse layer (DW), and data mart layer (DM). Each data level consists of several tasks of the same type.

The task monitoring modes in the prior art are based on the key levels of tasks defined by each data layer. Each data layer mainly maintains its own monitoring system, lacks the connection between tasks of each data layer, and cannot accurately evaluate the impact of dependencies on the data layer. , resulting in the inability to unify the mission-critical level and security between the data layers, and it is also not conducive to early warning.

In order to solve the above technical problems, the present invention proposes a task monitoring method. The present invention no longer focuses on a certain key task, key module or data level, but on peripheral tasks, that is, combining historical execution data and task dependency table. Output standard execution plans for peripheral tasks, and output dynamic execution plans for peripheral tasks combined with current execution data and task dependency table in real time. By comparing the standard execution plan with the dynamic execution plan, mutation tasks are found, and the related tasks are completed. Full link monitoring. Since it is no longer necessary to individually evaluate and monitor all tasks, it is only necessary to focus on peripheral tasks to achieve full-link monitoring, which is conducive to quickly reaching a consensus goal and improving the efficiency of monitoring configuration. And by generating a dynamic execution plan in real time and monitoring the mutation of the dynamic execution plan, it can quickly locate abnormal mutation tasks, promote the event processing process, and realize in-process monitoring of tasks, so as to discover hidden dangers and avoid risks in advance.

In order to make those skilled in the art better understand the solutions of the present application, the following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application.

Example 1:

FIG. 1 is a flowchart of an embodiment of a task monitoring method according to an exemplary embodiment of the present invention. The task monitoring method can be applied to a computer device, and the computer device can be a terminal device, a mobile terminal, or a PC. , server and other equipment, as shown in Figure 1, the task monitoring method includes the following steps:

Step 101: Obtain the task dependency table of the stub tasks located in the lowest task layer.

Among them, the task dependency table is established in advance for the peripheral tasks located in the lowest task layer according to the task execution network graph, and records the relevant information of the upstream dependent tasks of the peripheral tasks, and these upstream dependent tasks are divided into other task layers.

For example, taking the first layer L0 as the lowest task layer to which the peripheral task belongs, the direct upstream dependent tasks of the peripheral task belong to the second layer L1, and the second layer L1 may contain 1-N tasks. All tasks also have their own upstream dependent tasks (indirect upstream dependent tasks belonging to stub tasks), and are separated into multiple new task branches.

Step 102: Generate a standard execution plan for the peripheral task according to the task dependency relationship table and the task running time collected in the historical time period.

Optionally, the task running time collected in the historical time period may be the task running time collected in the past week.

In a possible implementation manner, for each task layer, at least one task located in the task layer may be obtained from the task dependency table, and selected from the at least one task according to the task running time collected in the historical time period. A task is regarded as the key task of the task layer, and then a standard execution plan is generated for the peripheral task using the key task of each task layer.

Among them, the standard execution plan represents the average execution of the peripheral tasks, and reflects the average execution of each upstream dependent task of the peripheral tasks in the past period of time.

Specifically, for the process of using the key tasks of each task layer to generate a standard execution plan for peripheral tasks, the labels of the key tasks of each task layer and the task layer number are spliced together and then spliced together according to the task layer dependency order to generate the standard execution plan. plan.

For example, assuming that the tasks in each task layer are labeled with letters, and each task layer is numbered with numbers, the generated standard execution plan example is: 1A2A3D4A5C6A7A8B9C10D11A, indicating that the task layer to which the upstream dependent task of the peripheral task belongs has 11 layers, the key task of layer 1 is A, the key task of layer 2 is A, the key task of layer 3 is D, the key task of layer 4 is A, the key task of layer 5 is C, the key task of layer 6 is C The key task of layer is A, the key task of layer 7 is A, the key task of layer 8 is B, the key task of layer 9 is C, the key task of layer 10 is D, the key task of layer 11 is A.

It should be added that there may be more than one stub task located at the lowest task layer in the task execution network. In the present invention, a standard execution plan needs to be separately generated for each stub task, and the generation date of the standard execution plan is recorded at the same time. .

In a possible implementation manner, for the process of selecting a task from the at least one task as the key task of the task layer according to the task running time collected in the historical time period, the process of selecting a task as the key task of the task layer may be based on the task running time collected in the historical time period. time, determine the average running time of each task, and select the task corresponding to the longest average running time as the key task of the task layer.

Among them, the average running time of the task can be represented by calculating the average running time. The shorter the average running time is, the shorter the running time of the task is, and the longer the average running time is, the longer the running time of the task is. Under normal circumstances, the execution time of tasks belonging to the same task layer is relatively average. By selecting the longest average time consumption, it can be ensured that all tasks in this task layer are executed.

Step 103: Generate a dynamic execution plan for the peripheral task according to the task dependency relationship table and the currently collected task running time.

The currently collected task running time is the most recently collected task running time.

In a possible implementation manner, for each task layer, at least one task located in the task layer is obtained from the task dependency table, and according to the currently collected task running time, one task is selected from the at least one task as the The key tasks of the task layer are then used to generate dynamic execution plans for peripheral tasks using the key tasks of each task layer.

Among them, the dynamic execution plan represents the real-time execution of the peripheral task, and reflects the real-time execution of each upstream dependent task of the peripheral task.

Specifically, for the process of using the key tasks of each task layer to generate dynamic execution plans for peripheral tasks, after splicing together the labels of the key tasks of each task layer and the task layer number, the dynamic execution plan is generated by splicing in the order of task layer dependencies. Implementation plan.

For example, suppose the generated dynamic execution plan example is: 1A2C3D4A5C6A7A8B9C10D11A, indicating that the upstream dependent tasks of the peripheral task belong to 11 task layers, the key task of the first layer is A, the key task of the second layer is C, and the third layer is the key task of the third layer. The key task of layer is D, the key task of layer 4 is A, the key task of layer 5 is C, the key task of layer 6 is A, the key task of layer 7 is A, the key task of layer 8 is B, the key task of layer 9 is C, the key task of layer 10 is D, and the key task of layer 11 is A.

It should be added that there may be more than one task at the end task located at the lowest task layer in the task execution network. In the present invention, it is also necessary to generate a dynamic execution plan for each end task separately, and record the generation of the dynamic execution plan at the same time. time.

In a possible implementation manner, for the process of selecting a task from the at least one task as the key task of the task layer according to the currently collected task running time, the task corresponding to the currently collected longest task running time may be selected as the key task of this task layer.

Among them, the task with the longest task running time is selected as the key task, indicating that the key task in the current task running process belongs to the task that most affects the task running time.

It should be added that by executing the generation process of the dynamic execution plan at regular intervals, the task operation can be monitored in real time, abnormal mutation tasks can be detected in advance, and problems can be solved in time.

Step 104: Compare the dynamic execution plan with the standard execution plan to determine whether there is a mutation task in the dynamic execution plan.

Among them, the mutation task indicates that the task may have abnormal conditions such as sudden increase in time consumption and task death.

In an optional embodiment, by comparing the key tasks belonging to the same task layer in the dynamic execution plan and the standard execution plan, if the comparison is inconsistent, it is determined that the key tasks belonging to the task layer included in the dynamic execution plan are: For mutation tasks, if the alignment is consistent, it is determined that the key tasks belonging to the task layer included in the dynamic execution plan are normal.

It can be seen that, according to the comparison result between the dynamic execution plan and the standard execution plan, it may be determined that there are multiple mutation tasks, one mutation task, and of course, there may be no mutation tasks.

For example, suppose the generated standard execution plan example is: 1A2A3D4A5C6A7A8B9C10D11A, and the generated dynamic execution plan example is: 1A2C3D4A5C6A7A8B9C10D11A. By comparing the key tasks belonging to each task layer, it can be found that the task mutation occurs in the second layer, and the key task is determined by A Changes to C, indicating that task C may experience abnormal situations such as sudden increase in time consumption and task death.

Step 105: If there is, output the information related to the mutation task as early warning information.

Optionally, the information related to the mutation task may include information such as business owners, associated indicators, and functional impact points, which is convenient for technicians to analyze the cause of mutation and implement emergency plans.

It should be added that a task table can be established in advance to record the relevant information of each task, such as business owner, related indicators, developers, task name, whether it is a flag of a peripheral task, etc. When a task appears, the business owner and associated indicators corresponding to the mutation task can be directly read from the task table as early warning information output.

In a possible implementation manner, the early warning information may be sent to the corresponding personnel by telephone or email, so as to realize timely early warning.

Step 106: If it does not exist, continue to perform the process of Step 103.

Among them, if the dynamic execution plan is consistent with the key tasks belonging to the same task layer in the standard execution plan, it means that there is no mutation task at present, and the next monitoring can be continued.

It should be added that the running time of each task in each task layer can be monitored in real time, that is, for each task in each task layer, the task running time currently collected for the task and the task running time collected in the previous collection are obtained. The time difference between times, if the time difference exceeds the preset threshold, it means that the task has a sudden increase in time consumption, and the business owner and associated indicators of the task are output as early warning information.

So far, the task monitoring process shown in FIG. 1 is completed. The present invention no longer focuses on a certain key task, key module or data level, but on the peripheral task, that is, combined with the historical execution data and the task dependency table as the terminal. The task outputs the standard execution plan, and combines the current execution data and the task dependency table to output the dynamic execution plan for the peripheral task in real time. By comparing the standard execution plan with the dynamic execution plan, the mutation task is found, so as to complete the whole chain of related tasks. road monitoring. Since it is no longer necessary to individually evaluate and monitor all tasks, it is only necessary to focus on peripheral tasks to achieve full-link monitoring, which is conducive to quickly reaching a consensus goal and improving the efficiency of monitoring configuration. And by generating a dynamic execution plan in real time and monitoring the mutation of the dynamic execution plan, it can quickly locate abnormal mutation tasks, promote the event processing process, and realize in-process monitoring of tasks, so as to discover hidden dangers and avoid risks in advance.

The invention can be applied to the technical field of smart cities, thereby promoting the construction of smart cities.

Corresponding to the foregoing embodiments of the task monitoring method, the present invention also provides an embodiment of a task monitoring apparatus.

FIG. 2 is a schematic structural diagram of a task monitoring device according to an exemplary embodiment of the present invention. The device is configured to execute the task monitoring method provided by any of the above embodiments. As shown in FIG. 2 , the task monitoring device includes:

an acquisition module 210, for acquiring the task dependency table of the peripheral task located in the lowest task layer;

a first generating module 220, configured to generate a standard execution plan for the peripheral task according to the task dependency table and the task running time collected in the historical time period;

A second generating module 230, configured to generate a dynamic execution plan for the peripheral task according to the task dependency table and the currently collected task running time;

A comparison module 240, configured to compare the dynamic execution plan with the standard execution plan to determine whether there is a mutation task in the dynamic execution plan;

The early warning module 250 is configured to output information related to the sudden change task as early warning information when it is determined that there is a sudden change task.

For details of the implementation process of the functions and functions of each unit in the above device, please refer to the implementation process of the corresponding steps in the above method, which will not be repeated here.

For the apparatus embodiments, since they basically correspond to the method embodiments, reference may be made to the partial descriptions of the method embodiments for related parts. The device embodiments described above are only illustrative, wherein the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in One place, or it can be distributed over multiple network elements. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of the present invention. Those of ordinary skill in the art can understand and implement it without creative effort.

Embodiments of the present invention further provide an electronic device corresponding to the task monitoring method provided by the foregoing embodiments, so as to execute the above task monitoring method.

3 is a hardware structure diagram of an electronic device according to an exemplary embodiment of the present invention. The electronic device includes: a communication interface 601, a processor 602, a memory 603, and a bus 604; wherein the communication interface 601, the processor 602 and the memory 603 communicate with each other through the bus 604 . The processor 602 can execute the task monitoring method described above by reading and executing the machine-executable instructions corresponding to the control logic of the task monitoring method in the memory 603. For the specific content of the method, refer to the above-mentioned embodiment, which is not repeated here. described.

The memory 603 referred to in the present invention may be any electronic, magnetic, optical or other physical storage device that may contain stored information, such as executable instructions, data, and the like. Specifically, the memory 603 may be a RAM (Random Access Memory), a flash memory, a storage drive (such as a hard disk drive), any type of storage disk (such as an optical disc, DVD, etc.), or a similar storage medium, or their combination. The communication connection between the network element of the system and at least one other network element is realized through at least one communication interface 601 (which may be wired or wireless), which may use the Internet, a wide area network, a local network, a metropolitan area network, and the like.

The bus 604 may be an ISA bus, a PCI bus, an EISA bus, or the like. The bus can be divided into an address bus, a data bus, a control bus, and the like. The memory 603 is used for storing a program, and the processor 602 executes the program after receiving the execution instruction.

The processor 602 may be an integrated circuit chip with signal processing capability. In the implementation process, each step of the above-mentioned method may be completed by an integrated logic circuit of hardware in the processor 602 or an instruction in the form of software. The above-mentioned processor 602 may be a general-purpose processor, including a central processing unit (CPU for short), a network processor (NP for short), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware component. The methods, steps, and logic block diagrams disclosed in the embodiments of this application can be implemented or executed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in conjunction with the embodiments of the present application may be directly embodied as executed by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor.

The electronic device provided by the embodiment of the present application and the task monitoring method provided by the embodiment of the present application are based on the same inventive concept, and have the same beneficial effects as the method adopted, operated or realized.

Embodiments of the present application further provide a computer-readable storage medium corresponding to the task monitoring method provided by the foregoing embodiments, please refer to FIG. 4 , the computer-readable storage medium shown is an optical disc 30 on which is stored A computer program (ie, a program product), when the computer program is run by a processor, it will execute the task monitoring method provided by any of the foregoing embodiments.

It should be noted that examples of the computer-readable storage medium may also include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random Access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other optical and magnetic storage media will not be repeated here.

The computer-readable storage medium provided by the above embodiments of the present application and the task monitoring method provided by the embodiments of the present application are based on the same inventive concept, and have the same beneficial effects as the methods used, run or implemented by the application programs stored thereon.

Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention which follow the general principles of the present invention and include common knowledge or conventional techniques in the technical field not disclosed by the present invention . The specification and examples are to be regarded as exemplary only, with the true scope and spirit of the invention being indicated by the following claims.

It should also be noted that the terms "comprising", "comprising" or any other variation thereof are intended to encompass a non-exclusive inclusion such that a process, method, article or device comprising a series of elements includes not only those elements, but also Other elements not expressly listed, or which are inherent to such a process, method, article of manufacture, or apparatus are also included. Without further limitation, an element qualified by the phrase "comprising a..." does not preclude the presence of additional identical elements in the process, method, article of manufacture, or device that includes the element.

The above descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the present invention. within the scope of protection.

Claims (10)

1. A method for task monitoring, the method comprising:

acquiring a task dependency relationship table of a peripheral task in a lowest task layer;

generating a standard execution plan for the ending task according to the task dependency relationship table and the task operation time acquired in the historical time period;

generating a dynamic execution plan for the ending task according to the task dependency relationship table and the currently acquired task operation time;

comparing the dynamic execution plan with the standard execution plan to judge whether a mutation task exists in the dynamic execution plan;

and if so, outputting information related to the mutation task as early warning information.

2. The method of claim 1, wherein generating a standard execution plan for the tip task based on the task dependency table and task run times collected over historical time periods comprises:

aiming at each task layer, at least one task positioned at the task layer is obtained from the task dependency relationship table;

selecting one task from the at least one task as a key task of the task layer according to the task running time collected in the historical time period;

and generating a standard execution plan for the tip task by utilizing the key tasks of each task layer.

3. The method of claim 2, wherein selecting a task from the at least one task as a key task of the task layer according to the task running time collected in the historical time period comprises:

determining the average running time of each task according to the task running time collected in the historical time period;

and selecting the task corresponding to the longest average running time as the key task of the task layer.

4. The method of claim 1, wherein generating a dynamic execution plan for the tip task based on the task dependency table and a currently collected task runtime comprises:

aiming at each task layer, at least one task positioned at the task layer is obtained from the task dependency relationship table;

selecting one task from the at least one task as a key task of the task layer according to the currently acquired task running time;

and generating a dynamic execution plan for the tip task by utilizing the key tasks of each task layer.

5. The method of claim 4, wherein selecting a task from the at least one task as a critical task of the task layer according to the currently collected task running time comprises:

and selecting the task corresponding to the currently acquired longest task running time as the key task of the task layer.

6. The method of claim 1, wherein comparing the dynamic execution plan to the standard execution plan to determine whether a mutated task exists in the dynamic execution plan comprises:

comparing the dynamic execution plan with key tasks belonging to the same task layer in the standard execution plan;

and if the comparison is inconsistent, determining that the key tasks contained in the dynamic execution plan and belonging to the task layer are mutation tasks.

7. The method of claim 1, further comprising:

aiming at each task in each task layer, acquiring the time difference between the task running time currently acquired by the task and the task running time acquired last time;

and if the time difference exceeds a preset threshold value, outputting information related to the task as early warning information.

8. A task monitoring apparatus, characterized in that the apparatus comprises:

the acquisition module is used for acquiring a task dependency relationship table of a peripheral task in the lowest task layer;

the first generation module is used for generating a standard execution plan for the ending task according to the task dependency relationship table and the task operation time acquired in the historical time period;

the second generation module is used for generating a dynamic execution plan for the ending task according to the task dependency relationship table and the currently acquired task operation time;

the comparison module is used for comparing the dynamic execution plan with the standard execution plan so as to judge whether a mutation task exists in the dynamic execution plan;

and the early warning module is used for outputting information related to the mutation task as early warning information when the mutation task is judged to exist.

9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method according to any of claims 1-7 are implemented when the processor executes the program.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.

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