Task priority arrangement method, device, equipment and computer program product

Abstract

The invention discloses a task priority arrangement method, device and equipment and a computer program product, and relates to the technical field of financial science and technology, and the method comprises the steps: obtaining a weight task set; performing priority arrangement on the weight task set based on a priority arrangement algorithm and a task timeliness classification rule to obtain a priority task set; and dynamically adjusting the priority task set based on a dynamic adjustment algorithm to obtain a task priority arrangement result. According to the task scheduling method and device, priority scheduling is carried out on the weight task set through the task timeliness classification rule and the priority scheduling algorithm, the overall task progress is improved, then dynamic adjustment is carried out on the priority task set through the dynamic adjustment algorithm, the task priority scheduling result is obtained, and the task timeliness is guaranteed. Therefore, the problem that a financial warehouse task priority arrangement method is poor in rationality is solved, and the timeliness of a single task is guaranteed while the overall task progress is improved.

Description

Technical Field

[0001] The present application relates to the field of financial technology, and in particular to a task priority scheduling method, device, equipment and computer program product. Background Art

[0002] In the field of financial technology, there are more and more data extraction, transformation and loading tasks (ETL tasks) applied to data lakes. Due to the different timeliness requirements of different data, each task has different importance, such as regulatory data, important reports, etc. Therefore, the priority of determining the importance of tasks is also an issue that needs to be considered in each task scheduling.

[0003] Priority is usually determined when the task is developed, but the ETL task scenario of the financial data warehouse is characterized by large scale, deep layers, and complex links. It is impossible to give a reasonable priority only by ordinary manpower or traditional priority arrangement. At the same time, with the business putting forward higher and higher timeliness requirements for data, the existing priority cannot ensure the high throughput of the system while ensuring that the data with high timeliness requirements can be in place in time, and the rationality of priority arrangement is poor.

[0004] The above contents are only used to assist in understanding the technical solution of the present application and do not constitute an admission that the above contents are prior art. Summary of the invention

[0005] The main purpose of this application is to provide a task priority scheduling method, device, equipment and computer program product, aiming to solve the technical problem that the existing financial data warehouse task priority scheduling method is relatively unreasonable.

[0006] To achieve the above objectives, the present application proposes a task priority scheduling method, the method comprising:

[0007] Obtain a pre-generated weighted task set, wherein the weighted task set includes a plurality of weighted task data, each weighted task data includes a task to be scheduled and corresponding weight data;

[0008] Based on a preset priority scheduling algorithm and task timeliness classification rules, the weighted task set is prioritized to obtain a priority task set;

[0009] Based on a preset dynamic adjustment algorithm, the priority task set is dynamically adjusted to obtain a task priority scheduling result.

[0010] In one embodiment, before the step of obtaining the pre-generated weighted task set, the step further includes:

[0011] Acquire a task link, wherein the task link includes a plurality of initial tasks and corresponding link relationships;

[0012] According to the task link, a plurality of weighted task data are obtained;

[0013] The weighted task set is established according to a plurality of the weighted task data.

[0014] In one embodiment, the step of obtaining a plurality of weighted task data according to the task link comprises:

[0015] Task selection step: selecting any of the initial tasks as the task to be scheduled;

[0016] Link positioning step: performing link positioning on the task to be scheduled according to the link relationship to obtain single link position data;

[0017] Weight calculation step: calculating the weight data according to the single link position data;

[0018] The weighted task data generating step: generating the weighted task data according to the task to be arranged and the weight data;

[0019] The steps of task selection, link positioning, weight calculation, and weight task data generation are repeated until the task link is traversed to obtain a plurality of weight task data.

[0020] In one embodiment, the task timeliness classification rule includes a timeliness level classification rule and a data output time classification rule. The step of performing priority scheduling on the weighted task set based on the preset priority scheduling algorithm and the task timeliness classification rule, and obtaining the priority task set includes:

[0021] Based on the timeliness level classification rule, the weighted task set is classified and sorted according to the timeliness level to obtain a plurality of first classification task sets;

[0022] Based on the data output time classification rule, classify and sort the first classification task sets according to the data output time to obtain a plurality of second classification task sets;

[0023] Based on the priority arrangement algorithm, a plurality of the second classification task sets are prioritized to obtain the priority task set.

[0024] In one embodiment, the step of performing priority arrangement on a plurality of second classification task sets based on the priority arrangement algorithm and obtaining the priority task set comprises:

[0025] Selecting each of the second classification task sets in a plurality of the second classification task sets in turn as a target task set;

[0026] Based on the priority scheduling algorithm, the priority of the target task set is calculated to obtain priority data;

[0027] The priority task set is established according to a plurality of the second classification task sets and a corresponding plurality of priority data.

[0028] In one embodiment, the priority scheduling algorithm includes a set priority calculation algorithm and a single task priority calculation algorithm. The step of calculating the priority of the target task set based on the priority scheduling algorithm and obtaining the priority data includes:

[0029] Based on the set priority calculation algorithm, the priority of the target task set is calculated to obtain set priority data;

[0030] Based on the single task priority calculation algorithm, according to a plurality of target weight data in the target task set, the priorities of a plurality of target tasks in the target task set are calculated to obtain a task priority data set;

[0031] The priority data is obtained according to the set priority data and the task priority data set.

[0032] In one embodiment, the step of dynamically adjusting the priority task set based on a preset dynamic adjustment algorithm to obtain a task priority scheduling result includes:

[0033] Based on the preset link relationship, a plurality of priority tasks in the priority task set are sorted to obtain a plurality of link sequence tasks;

[0034] Selecting each of the plurality of link sequence tasks in turn as a task to be adjusted;

[0035] Obtaining the predicted completion time data of the task to be adjusted, and judging whether the predicted completion time of the task to be adjusted is greater than the preset output time according to the predicted completion time data, and obtaining a judgment result;

[0036] Based on the dynamic adjustment algorithm, according to the judgment result, the priority of the task to be adjusted is dynamically adjusted to obtain a dynamic adjustment result;

[0037] The task priority scheduling result is generated according to the priority task set and a plurality of dynamic adjustment results.

[0038] In one embodiment, the dynamic adjustment result is a first dynamic adjustment result, the priority task set includes a plurality of second classification task sets and a plurality of corresponding set priority data, and the step of dynamically adjusting the priority of the task to be adjusted based on the dynamic adjustment algorithm and the judgment result includes:

[0039] When the judgment result is that the predicted completion time of the task to be adjusted is greater than the preset output time, determining the second classified task set where the task to be adjusted is located, and taking the maximum value of the set priority data corresponding to the second classified task set as the target priority data;

[0040] Based on the dynamic adjustment algorithm, the task priority data corresponding to the task to be adjusted is adjusted to the target priority data to obtain the first dynamic adjustment result.

[0041] In addition, to achieve the above purpose, the present application also proposes a task priority scheduling device, the task priority scheduling device comprising:

[0042] A set acquisition module is used to acquire a pre-generated weight task set, wherein the weight task set includes a plurality of weight task data, each of which includes a task to be scheduled and corresponding weight data;

[0043] A priority scheduling module is used to schedule the weighted task set based on a preset priority scheduling algorithm and task timeliness classification rules to obtain a priority task set;

[0044] The dynamic adjustment module is used to dynamically adjust the priority task set based on a preset dynamic adjustment algorithm to obtain a task priority scheduling result.

[0045] In addition, to achieve the above-mentioned objectives, the present application also proposes a task priority scheduling device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the task priority scheduling method described above.

[0046] In addition, to achieve the above objectives, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the task priority scheduling method described above are implemented.

[0047] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the task priority scheduling method described above are implemented.

[0048] The present application provides a task priority scheduling method, which uses the task time classification rules to classify and sort the tasks to be scheduled, and uses the priority scheduling algorithm to prioritize the classified tasks to improve the overall task progress. Finally, the priority task set is dynamically adjusted through the dynamic adjustment algorithm to obtain the task priority scheduling result and ensure the timeliness of the task. Thus, the technical problem of the poor rationality of the existing financial data warehouse task priority scheduling method is solved, and the timeliness of a single task is guaranteed while improving the overall task progress. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0050] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0051] Figure 1 A flowchart of the first embodiment of the task priority arrangement method of the present application is provided;

[0052] Figure 2 A schematic diagram of the structure of the task link provided in Example 1 of the task priority arrangement method of the present application;

[0053] Figure 3 A schematic diagram of the content of the predicted completion time data provided in Example 1 of the task priority arrangement method of this application;

[0054] Figure 4 A flowchart of the second embodiment of the task priority arrangement method of the present application is provided;

[0055] Figure 5 This is a schematic diagram of the module structure of the task priority arrangement device according to an embodiment of the present application;

[0056] Figure 6 Schematic diagram of the device structure of the hardware operating environment involved in the task priority arrangement method in the embodiment of the present application.

[0057] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0058] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0059] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0060] The main solutions of the embodiments of this application are:

[0061] Obtain a pre-generated weighted task set, wherein the weighted task set includes a plurality of weighted task data, each weighted task data includes a task to be scheduled and corresponding weight data;

[0062] Based on a preset priority scheduling algorithm and task timeliness classification rules, the weighted task set is prioritized to obtain a priority task set;

[0063] Based on a preset dynamic adjustment algorithm, the priority task set is dynamically adjusted to obtain a task priority scheduling result.

[0064] In the existing technology, the ETL task scenarios of financial data warehouses are characterized by large scale, deep layers, and complex links. It is impossible to give reasonable priorities by ordinary manpower or traditional priority scheduling. At the same time, with the increasingly high timeliness requirements of business for data, the existing priorities cannot ensure the high throughput of the system while ensuring that the data with high timeliness requirements can be in place in time, and the rationality of priority scheduling is poor.

[0065] This application provides a solution, which uses the task time classification rules to classify and sort the tasks to be scheduled, and uses the priority scheduling algorithm to prioritize the classified tasks to improve the overall task progress. Finally, the priority task set is dynamically adjusted through the dynamic adjustment algorithm to obtain the task priority scheduling result and ensure the timeliness of the task. In this way, the technical problem of the poor rationality of the existing financial data warehouse task priority scheduling method is solved, and the timeliness of a single task is guaranteed while improving the overall task progress.

[0066] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a task priority scheduling system, etc. The following takes the task priority scheduling system as an example to illustrate this embodiment and the following embodiments.

[0067] Based on this, the present application embodiment provides a task priority scheduling method, referring to Figure 1 , Figure 1 This is a flowchart of the first embodiment of the task priority arrangement method of the present application.

[0068] In this embodiment, the task priority arrangement method includes steps S10 to S40:

[0069] Step S10, obtaining a pre-generated weighted task set, wherein the weighted task set includes a plurality of weighted task data, each weighted task data includes a task to be scheduled and corresponding weight data;

[0070] The task priority scheduling system obtains a pre-generated weighted task set, wherein the weighted task set contains a number of weighted task data, each weighted task data includes a task to be scheduled and corresponding weight data, and the weight data is a weight value associated with the task. The weight value is usually used to indicate the relative importance or urgency of the task. The weight of a task may be an integer or a floating point number.

[0071] In a feasible implementation manner, before step S10, steps S401 to S403 may also be included:

[0072] Step S401, obtaining a task link, wherein the task link includes a plurality of initial tasks and corresponding link relationships;

[0073] Step S402, obtaining a plurality of weighted task data according to the task link;

[0074] Step S403: establishing the weighted task set according to a plurality of the weighted task data.

[0075] The task priority scheduling system obtains a task link, which includes several initial tasks and corresponding link relationships, and then obtains several weighted task data based on the task link. Finally, based on the several weighted task data, a weighted task set is established.

[0076] It should be noted that the task link is a structural diagram that describes the order and dependency relationship between tasks. By obtaining the task link, you can understand which tasks need to rely on the completion of other tasks. The link relationship is used to describe the dependency order between tasks. For example, task A must be completed before task B.

[0077] In this implementation, by acquiring task links, the relationship and order between tasks are clarified, providing a systematic framework for task management. By acquiring weighted task data, the problem of uneven distribution of task weights is solved. The reasonable distribution of weighted data can ensure that important tasks are given priority and improve the effect and efficiency of task processing. By establishing a weighted task set, the problem of incomplete task set construction or inconsistent data is solved. The establishment of a weighted task set ensures the integrity and consistency of all task data, providing a reliable data basis for subsequent priority calculations. As a result, the system can more effectively arrange and optimize the order of task execution, improving the overall efficiency of the system.

[0078] In another feasible implementation, step S402 may include steps S4021 to S4025:

[0079] Step S4021, task selection step: selecting any of the initial tasks as the task to be scheduled;

[0080] Step S4022, link positioning step: performing link positioning on the task to be scheduled according to the link relationship to obtain single link position data;

[0081] Step S4023, weight calculation step: calculating and obtaining the weight data according to the single link position data;

[0082] Step S4024, weighted task data generation step: generating the weighted task data according to the task to be arranged and the weight data;

[0083] Step S4025, repeat the steps of task selection, link positioning, weight calculation, and weight task data generation until the task link is traversed and a number of weight task data are obtained.

[0084] The task priority scheduling system selects an initial task from the task chain as the task to be scheduled, determines the basic task for subsequent operations, and then checks the dependencies and sequences between the tasks in the task chain. Based on the task chain relationship, the specific position of the task to be scheduled in the chain is determined to obtain single-link position data. The link position data includes the predecessor task, successor task and the relative position of the task in the entire chain of the task to be scheduled. Then, according to the link position data, the preset rules or formulas are applied to calculate the weight of each task to obtain weight data. Then, the task to be scheduled and the weight data are integrated to generate the weighted task data. Finally, the steps of task selection, chain positioning, weight calculation and weighted task data generation are repeated until the task chain is traversed to obtain a number of weighted task data.

[0085] Among them, the calculation weight data rules may include:

[0086] Impact of predecessor tasks: The completion of predecessor tasks may affect the weight of the task to be scheduled.

[0087] Dependency of successor tasks: the importance and impact of the task to be scheduled on the successor task.

[0088] In this embodiment, the task analysis process is started by selecting the initial task, and the position of the task in the link is obtained through link positioning, so as to understand the context and relative position of the task in detail. By calculating the weight data, the importance or priority of the task can be quantitatively evaluated based on the link position data. By combining the weight data with the task information, weighted task data is generated to make the priority information of the task clearer. By repeating the above steps, it is ensured that the system can process all tasks and generate corresponding weighted task data. This systematic processing method ensures the comprehensiveness and consistency of task sorting, so that the system can flexibly respond to changes in the task link and optimize task scheduling. In this way, the systematic, accurate, comprehensive and dynamic adaptability of task processing is ensured, thereby optimizing task sorting and resource management, solving some common technical problems existing in traditional task management, and improving the system's adaptability and response speed to changes.

[0089] For example, refer to Figure 2 , Figure 2 A structural diagram of the task link provided in Example 1 of the task priority arrangement method of the present application.

[0090] In the field of financial data warehouses, the number of ETL tasks is huge and the links are complex. Often one task affects multiple downstreams, and one downstream also depends on multiple upstreams.

[0091] from Figure 2 It can be seen that there are many scenarios for links, such as serial, parallel, and branch operation. Many different data link scenarios constitute a complex data relationship network. For each task t, there is an affected direct downstream number D and an affected downstream number AD. Without considering the timeliness requirements of the data itself, the larger the D and AD, the greater the impact of the task and the higher its weight globally.

[0092] In order to highlight the role of data links in the mission operation process, without considering the timeliness of data, the following two principles are determined:

[0093] For jobs on the same link, the weights increase from bottom to top;

[0094] For a scenario with one upstream and multiple downstreams, the weight of the upstream task = the sum of all the weights of the downstream tasks.

[0095] Therefore, the weight Q of task t is t =Q t-1 +D.

[0096] Among them, Q t-1 is the weight of the previous task, Q1=1.

[0097] Step S20, based on a preset priority scheduling algorithm and task timeliness classification rules, the weighted task set is prioritized to obtain a priority task set;

[0098] Based on the preset priority scheduling algorithm and task timeliness classification rules, the task priority scheduling system prioritizes the weighted task set to obtain a priority task set, wherein the task timeliness classification rules specify the impact of the urgency or deadline of the task on the priority. For example, a task with a near deadline may be given a higher priority.

[0099] Step S30: dynamically adjust the priority task set based on a preset dynamic adjustment algorithm to obtain a task priority scheduling result.

[0100] The task priority scheduling system uses a dynamic adjustment algorithm to adjust the task priority of individual tasks in the priority task set according to task execution status or external changes. For example, some tasks may need to re-evaluate their priorities due to new information or changes.

[0101] In a feasible implementation, step S30 may include steps S301 to S305:

[0102] Step S301, based on a preset link relationship, sorting a number of priority tasks in the priority task set to obtain a number of link sequence tasks;

[0103] Step S302, selecting each of the link sequence tasks in turn as a task to be adjusted;

[0104] Step S303, obtaining the predicted completion time data of the task to be adjusted, and judging whether the predicted completion time of the task to be adjusted is greater than the preset output time according to the predicted completion time data, and obtaining a judgment result;

[0105] Step S304, based on the dynamic adjustment algorithm and according to the judgment result, dynamically adjust the priority of the task to be adjusted to obtain a dynamic adjustment result;

[0106] Step S305: generating the task priority scheduling result according to the priority task set and a plurality of dynamic adjustment results.

[0107] The task priority scheduling system sorts several priority tasks in the priority task set based on the preset link relationship to obtain several link sequence tasks. For example, if there are task 1, task 2 and task 3, the link relationship stipulates that task 2 must be completed after task 1, and task 3 must be completed after task 2, then the link sequence tasks that may be generated include: (task 1->task 2->task 3), and then each of the several link sequence tasks is selected in turn as the task to be adjusted, and then the predicted completion time data of the task to be adjusted is obtained from the task management system or the prediction model. These data are usually time predictions based on historical data, task complexity, resource allocation and other factors, and may include task start time, estimated completion time or task progress and other information, and judge whether the predicted completion time of the task to be adjusted is greater than the preset output time based on the predicted completion time data, and obtain the judgment result, and then based on the dynamic adjustment algorithm, according to the judgment result, the priority of the task to be adjusted is dynamically adjusted to obtain the dynamic adjustment result, and finally the priority task set and several dynamic adjustment results are integrated to generate the task priority scheduling result.

[0108] In this implementation, by sorting the priority tasks based on the link relationship and generating the link sequence tasks, a preliminary priority sorting is provided to ensure that the tasks are processed in a reasonable order. By comparing the predicted completion time with the preset time and applying the dynamic adjustment algorithm, the task scheduling is ensured to be more timely and accurate, effectively avoiding delays caused by prediction errors. The final task scheduling result is generated according to the dynamically adjusted priority, ensuring that all tasks are processed according to the latest priority, thereby optimizing resource allocation and task execution. The dynamic adjustment algorithm can adjust the task priority according to the actual data and solve the scheduling problem caused by the prediction error. As a result, the system can update the task processing order in real time according to the actual situation, realize the dynamic adjustment of the task priority, and improve the real-time and efficiency of task processing.

[0109] In another feasible implementation, the dynamic adjustment result is a first dynamic adjustment result, the priority task set includes a plurality of second classification task sets and a plurality of corresponding set priority data, and step S304 may include steps S3041 to S3042:

[0110] Step S3041, when the judgment result is that the predicted completion time of the task to be adjusted is greater than the preset output time, determine the second classified task set where the task to be adjusted is located, and use the maximum value of the set priority data corresponding to the second classified task set as the target priority data;

[0111] Step S3042: Based on the dynamic adjustment algorithm, the task priority data corresponding to the task to be adjusted is adjusted to the target priority data to obtain the first dynamic adjustment result.

[0112] When the judgment result is that the predicted completion time of the task to be adjusted is greater than the preset output time, the task priority scheduling system finds the second classification task set where the task to be adjusted is located. The second classification task set is a set in which tasks are grouped according to specific standards, usually based on the nature or priority level of the task. The priority data of the second classification task set where the task to be adjusted is located is then checked, and the maximum value of the priority data in the set is determined as the target priority data. This maximum value usually represents the most important task priority in the set. Finally, based on the preset dynamic adjustment algorithm, the priority data of the task to be adjusted is adjusted to the target priority data to obtain the first dynamic adjustment result.

[0113] It should be noted that the dynamic adjustment algorithm may involve adjusting the priority strategy, algorithm model or rules to ensure that the priority of the task is reasonably improved.

[0114] In this embodiment, by identifying the second classification task set to which the task to be adjusted belongs, and using the maximum priority value of the set as the target priority data, it is ensured that when the predicted completion time of the task exceeds the preset time, the task will be assigned a suitable priority for priority processing, and the task priority data is updated to the target priority data using a dynamic adjustment algorithm, thereby optimizing the priority arrangement of the task, so that the task priority can be reasonably sorted according to the real-time data, ensuring that the task is executed according to the priority, and at the same time, the dynamic adjustment algorithm is adjusted according to the target priority data, so that the system can adapt to the changing task completion time, and can more flexibly handle tasks that need to be reordered because the predicted completion time exceeds the preset time. In this way, the intelligence and automation level of task priority adjustment can be effectively improved, so that the system can better respond to dynamically changing task requirements, and accurate priority adjustment helps the system optimize resource allocation, ensure that key tasks are processed first, reduce resource waste and imbalance in task processing, thereby improving the overall resource utilization efficiency and improving the flexibility and efficiency of overall scheduling.

[0115] In addition, the priority scheduling algorithm and dynamic adjustment algorithm in this embodiment both belong to the priority algorithm. The basic idea of ​​the priority algorithm is: set a priority for each task, and then when scheduling tasks, select the task with the highest priority from all tasks in the ready state to run.

[0116] Priority algorithms can be divided into preemptive and non-preemptive methods. The difference is that when a task is running and a higher priority task comes, the preemptive method will immediately preempt resources to execute the higher priority task, while the non-preemptive method will wait until the current task is finished before executing. ETL task scheduling mostly uses the non-preemptive method to run tasks.

[0117] The way to determine task priority can be divided into static and dynamic methods.

[0118] Static priority method: The priority of the task is determined when the task is created and remains unchanged until the task is completed.

[0119] Dynamic priority mode: The priority of a task can be changed dynamically during the task execution.

[0120] The priority algorithm mentioned in this embodiment adopts a global static + local dynamic approach to provide the best data timeliness guarantee capability.

[0121] For example, refer to Figure 3 , Figure 3 A schematic diagram of the content of the predicted completion time data provided in Example 1 of the task priority scheduling method of this application.

[0122] The dynamic adjustment algorithm is based on the priority scheduling algorithm. It monitors the task operation status in real time and dynamically adjusts the link operation priority according to the terminal data availability to better ensure data timeliness.

[0123] Dynamic adjustment is mainly divided into the following two steps:

[0124] 1. Prediction of terminal data timeliness.

[0125] The average end time, average execution time, average waiting time and link relationship of each node in the link are calculated in advance.

[0126] For the timeliness prediction of a single-point job, the PT (predicted completion time) of this point is equal to the maximum value of the PT of the node's direct upstream node Max (PT father ) plus its own average execution time N avgeRunTime and the average waiting time N avgeWaitTime . The predicted completion time of the source operation is PT origin is the average end time N avgeFinishTime , specifically:

[0127] Estimated completion time of source operation: PT origin =N avgeFinishTime ;

[0128] Predicted completion time of other single-point operations: PT = Max (PT father )+N avgeRunTime +N avgeWaitTime .

[0129] In the case of dynamic links, when a node is completed, the actual completion time T realFinishTime To replace the previously calculated PT, which is more in line with the current dynamic context, specifically: predicted completion time PT = T realFinishTime .

[0130] 2. Dynamically adjust priorities.

[0131] When the predicted completion time PT of a certain point is calculated to be greater than T (job data timeliness), it means that the current link can no longer meet the data timeliness requirements according to the normal progress. According to the link relationship, the current blocked task node t is found and the priority of the node is increased to the maximum value max (P LK ).

[0132] This embodiment provides a task priority scheduling method, which uses task timeliness classification rules to classify and sort the tasks to be scheduled, and uses a priority scheduling algorithm to prioritize the classified tasks to improve the overall task progress, and finally uses a dynamic adjustment algorithm to dynamically adjust the priority task set to obtain a task priority scheduling result to ensure the timeliness of the task. Thus, the technical problem of the poor rationality of the existing financial data warehouse task priority scheduling method is solved, and the timeliness of a single task is guaranteed while improving the overall task progress.

[0133] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can refer to the above introduction, and will not be repeated later. Figure 4 The task timeliness classification rule includes timeliness level classification rule and output time classification rule. Step S20 may include steps S201 to S203:

[0134] Step S201, based on the timeliness level classification rule, classify and sort the weighted task sets according to timeliness level to obtain a plurality of first classification task sets;

[0135] Step S202: Based on the data output time classification rule, a plurality of first classification task sets are classified and sorted according to the data output time to obtain a plurality of second classification task sets;

[0136] Step S203: Prioritize a plurality of the second classification task sets based on the priority scheduling algorithm to obtain the priority task set.

[0137] At present, financial data warehouses store massive amounts of data and need to run large batches of ETL tasks every day. However, the key data that affects business decisions generally accounts for about 10% to 20%. In order to ensure the progress of global tasks while giving priority to high-security data, the task priority scheduling system divides the weighted task set into several different timeliness levels according to the predetermined task timeliness classification rules. For example, tasks can be divided into "high priority", "medium priority" and "low priority", and then further sorted according to the specific processing requirements of the tasks within each timeliness level. For example, within the "high priority" category, tasks can be sorted according to their specific deadlines to obtain several first-classified task sets, and then within each first-classified task set, the task's output time information is obtained, and then the output time classification rules are applied to classify the tasks according to the output time, and within each output time category, the tasks are further sorted to obtain several second-classified task sets to ensure that more urgent tasks are processed first. Finally, based on the priority scheduling algorithm, several second-classified task sets are prioritized to obtain priority task sets.

[0138] It should be noted that the timeliness level classification rules are standards for dividing tasks into different levels or categories according to the urgency of the tasks and the processing time requirements. These rules are usually based on factors such as the task deadline, processing time requirements, and importance. They are used to divide tasks into different levels according to timeliness so that urgent or important tasks can be given priority in subsequent processing. The delivery time refers to the completion or processing time requirements of the task. The delivery time classification rules are standards for dividing tasks based on these time requirements, which can ensure that tasks are prioritized according to their completion time requirements, thereby reasonably allocating processing resources.

[0139] In a feasible implementation, step S203 may include steps S2031 to S2033:

[0140] Step S2031, sequentially selecting each of the second classification task sets in a plurality of the second classification task sets as a target task set;

[0141] Step S2032, based on the priority scheduling algorithm, calculating the priority of the target task set to obtain priority data;

[0142] Step S2033: establishing the priority task set according to the plurality of the second classification task sets and the corresponding plurality of priority data.

[0143] The task priority scheduling system selects each of the second classification task sets in turn as the target task set, and then calculates the priority of the target task set based on the priority scheduling algorithm to obtain priority data, and finally integrates the second classification task sets and the corresponding priority data to obtain a priority task set.

[0144] In this embodiment, by selecting each second classification task set and calculating the priority, the calculation of the task priority is ensured to be more refined and accurate. This refinement improves the accuracy of task sorting, and accurately sorts the task set according to the priority arrangement algorithm, so that the task processing order can meet the actual needs to the greatest extent, and improve resource utilization efficiency. As a result, the system can ensure that the order and processing order of tasks are consistent with actual needs, avoid the problem of mismatch between task sorting and actual processing, and improve the overall performance and response speed of the system.

[0145] In another feasible implementation, the priority scheduling algorithm includes a set priority calculation algorithm and a single task priority calculation algorithm, and step S2032 may include steps S20321 to S20323:

[0146] Step S20321, based on the set priority calculation algorithm, calculating the priority of the target task set to obtain set priority data;

[0147] Step S20322, based on the single task priority calculation algorithm, according to the plurality of target weight data in the target task set, calculating the priorities of the plurality of target tasks in the target task set, and obtaining a task priority data set;

[0148] Step S20323, obtaining the priority data according to the set priority data and the task priority data set.

[0149] The task priority scheduling system is based on a set priority calculation algorithm. It comprehensively evaluates the overall priority of the target task set to obtain the set priority data. Then, according to several target weight data in the target task set, it calculates the priority of several target tasks in the target task set, evaluates the relevant attributes and target weight data of each target task, which may include the urgency of the task, its contribution to the overall goal, the expected completion time, etc., to obtain the task priority data set. Finally, the set priority data and the task priority data set are integrated to obtain the priority data.

[0150] It should be noted that the set priority calculation algorithm is used to calculate the priority of the entire task set, such as the weighted sum model, the analytic hierarchy process (AHP) or the priority matrix, etc., which usually considers the importance and urgency of the set as a whole. The single task priority calculation algorithm is used to calculate the priority of each task, such as the weighted scoring method, the priority sorting algorithm, the analytic hierarchy process (AHP), etc., which is usually based on the specific importance and urgency of the task.

[0151] In this implementation, by separately processing the calculation of the set and single-task priorities, the problem of insufficient precision that may be caused by a single algorithm is solved, and the accuracy of priority calculation is improved. By comprehensively considering the set priority and the single-task priority, the problem that the task sorting may not match the overall set priority is solved, ensuring that the task processing order is consistent with the actual priority data. Thus, more accurate priority sorting information is provided, and the task processing order is made more in line with actual needs.

[0152] Exemplarily, an implementation of step S20 is as follows:

[0153] For a task set T, the total number of tasks is N T , the weight of each task is Q t .

[0154] First, the task set is divided into 5 sets T1 to T5 according to the timeliness level. The data timeliness level is divided into five levels from L1 to L5, with decreasing importance, where L1 is the highest level and L5 is the lowest level. In any case, L1 tasks have absolute priority and need to be guaranteed to run first.

[0155] Then, for every set T L , divided according to the output time T L1 ~T LK The data output time refers to the time when the business needs the data, such as 08:00, 15:00, etc. The system must be able to ensure that the data can be output before this time point to meet the needs of the business.

[0156] Finally, for some set T LK , if the maximum priority of the task is p, then the priority of the set is P LK , specifically:

[0157]

[0158] min(P LK )=max(P LK-1 )+1;

[0159] Among them, min(P L1 )=1.

[0160] For each task t, its priority is p t , specifically:

[0161]

[0162] Where p1 = min(P LK ).

[0163] Among them, N Tn Indicates T L1 ~T LK The number of tasks in any task set, P LK-1 T LK The priority of the previous task set, P L1 is the task set T L1 The priority of Q NT is the weight of the last task in the task set T, Q1 is the weight of the first task in the task set T, and p1 is the priority of the first task in the task set T.

[0164] In this embodiment, the task set is divided into multiple first-classified task sets by the timeliness level classification rule, ensuring that the tasks are preliminarily sorted according to importance and timeliness; the first-classified task set is further sorted according to the time of output through the data output time classification rule, and the processing order of the tasks is optimized to meet the actual time of output requirements. The system can sort the tasks comprehensively and carefully according to the two dimensions of timeliness level and output time, improve the accuracy and efficiency of task processing, and then use the priority arrangement algorithm to adjust the priority of the second-classified task set, so that the final task set can accurately reflect the processing priority of the task. In this way, the system can achieve more efficient and accurate task management and improve the overall processing capacity and response speed.

[0165] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the task priority scheduling method of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0166] This application also provides a task priority scheduling device, please refer to Figure 5 , the task priority arrangement device comprises:

[0167] A set acquisition module 10 is used to acquire a pre-generated weight task set, wherein the weight task set includes a plurality of weight task data, each of which includes a task to be scheduled and corresponding weight data;

[0168] A priority scheduling module 20 is used to schedule the weighted task set based on a preset priority scheduling algorithm and task timeliness classification rules to obtain a priority task set;

[0169] The dynamic adjustment module 30 is used to dynamically adjust the priority task set based on a preset dynamic adjustment algorithm to obtain a task priority scheduling result.

[0170] Optionally, before the step of obtaining a pre-generated weighted task set, the step further includes:

[0171] Acquire a task link, wherein the task link includes a plurality of initial tasks and corresponding link relationships;

[0172] According to the task link, a plurality of weighted task data are obtained;

[0173] The weighted task set is established according to a plurality of the weighted task data.

[0174] Optionally, the step of obtaining a plurality of weighted task data according to the task link includes:

[0175] Task selection step: selecting any of the initial tasks as the task to be scheduled;

[0176] Link positioning step: performing link positioning on the task to be scheduled according to the link relationship to obtain single link position data;

[0177] Weight calculation step: calculating the weight data according to the single link position data;

[0178] The weighted task data generating step: generating the weighted task data according to the task to be arranged and the weight data;

[0179] The steps of task selection, link positioning, weight calculation, and weight task data generation are repeated until the task link is traversed to obtain a plurality of weight task data.

[0180] Optionally, the task timeliness classification rule includes a timeliness level classification rule and a data output time classification rule, and the priority arrangement module 20 is further used to:

[0181] Based on the timeliness level classification rule, the weighted task set is classified and sorted according to the timeliness level to obtain a plurality of first classification task sets;

[0182] Based on the data output time classification rule, classify and sort the first classification task sets according to the data output time to obtain a plurality of second classification task sets;

[0183] Based on the priority arrangement algorithm, a plurality of the second classification task sets are prioritized to obtain the priority task set.

[0184] Optionally, the step of performing priority arrangement on a plurality of the second classification task sets based on the priority arrangement algorithm to obtain the priority task set includes:

[0185] Selecting each of the second classification task sets in a plurality of the second classification task sets in turn as a target task set;

[0186] Based on the priority scheduling algorithm, the priority of the target task set is calculated to obtain priority data;

[0187] The priority task set is established according to a plurality of the second classification task sets and a corresponding plurality of priority data.

[0188] Optionally, the priority scheduling algorithm includes a set priority calculation algorithm and a single task priority calculation algorithm, and the step of calculating the priority of the target task set based on the priority scheduling algorithm and obtaining priority data includes:

[0189] Based on the set priority calculation algorithm, the priority of the target task set is calculated to obtain set priority data;

[0190] Based on the single task priority calculation algorithm, according to a plurality of target weight data in the target task set, the priorities of a plurality of target tasks in the target task set are calculated to obtain a task priority data set;

[0191] The priority data is obtained according to the set priority data and the task priority data set.

[0192] Optionally, the dynamic adjustment module 30 is further used for:

[0193] Based on the preset link relationship, a plurality of priority tasks in the priority task set are sorted to obtain a plurality of link sequence tasks;

[0194] Selecting each of the plurality of link sequence tasks in turn as a task to be adjusted;

[0195] Obtaining the predicted completion time data of the task to be adjusted, and judging whether the predicted completion time of the task to be adjusted is greater than the preset output time according to the predicted completion time data, and obtaining a judgment result;

[0196] Based on the dynamic adjustment algorithm, according to the judgment result, the priority of the task to be adjusted is dynamically adjusted to obtain a dynamic adjustment result;

[0197] The task priority scheduling result is generated according to the priority task set and a plurality of dynamic adjustment results.

[0198] Optionally, the dynamic adjustment result is a first dynamic adjustment result, the priority task set includes a plurality of second classification task sets and a plurality of corresponding set priority data, and the step of dynamically adjusting the priority of the task to be adjusted based on the dynamic adjustment algorithm and the judgment result includes:

[0199] When the judgment result is that the predicted completion time of the task to be adjusted is greater than the preset output time, determining the second classified task set where the task to be adjusted is located, and taking the maximum value of the set priority data corresponding to the second classified task set as the target priority data;

[0200] Based on the dynamic adjustment algorithm, the task priority data corresponding to the task to be adjusted is adjusted to the target priority data to obtain the first dynamic adjustment result.

[0201] The task priority arrangement device provided by the present application adopts the task priority arrangement method in the above-mentioned embodiment, which can solve the technical problem that the existing financial data warehouse task priority arrangement method is less rational. Compared with the prior art, the beneficial effects of the task priority arrangement device provided by the present application are the same as the beneficial effects of the task priority arrangement method provided by the above-mentioned embodiment, and the other technical features in the task priority arrangement device are the same as the features disclosed in the above-mentioned embodiment method, which will not be repeated here.

[0202] The present application provides a task priority orchestration device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the task priority orchestration method in the above-mentioned embodiment 1.

[0203] Reference below Figure 6 , which shows a schematic diagram of the structure of a task priority arrangement device suitable for implementing the embodiment of the present application. The task priority arrangement device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 6The task priority scheduling device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0204] like Figure 6 As shown, the task priority arrangement device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the task priority arrangement device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the task priority arrangement device to communicate wirelessly or wired with other devices to exchange data. Although the figure shows a task priority arrangement device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or provided instead.

[0205] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0206] The task priority scheduling device provided by the present application adopts the task priority scheduling method in the above embodiment, which can solve the technical problem that the existing financial data warehouse task priority scheduling method is less rational. Compared with the prior art, the beneficial effects of the task priority scheduling device provided by the present application are the same as the beneficial effects of the task priority scheduling method provided by the above embodiment, and the other technical features in the task priority scheduling device are the same as the features disclosed in the previous embodiment method, which will not be repeated here.

[0207] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0208] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0209] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, wherein the computer-readable program instructions are used to execute the task priority scheduling method in the above-mentioned embodiment.

[0210] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0211] The computer-readable storage medium may be included in the task priority scheduling device; or may exist independently without being assembled into the task priority scheduling device.

[0212] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the task priority scheduling device, the task priority scheduling device:

[0213] Obtain a pre-generated weighted task set, wherein the weighted task set includes a plurality of weighted task data, each weighted task data includes a task to be scheduled and corresponding weight data;

[0214] Based on a preset priority scheduling algorithm and task timeliness classification rules, the weighted task set is prioritized to obtain a priority task set;

[0215] Based on a preset dynamic adjustment algorithm, the priority task set is dynamically adjusted to obtain a task priority scheduling result.

[0216] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0217] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0218] The modules involved in the embodiments of the present application may be implemented by software or hardware, wherein the name of the module does not limit the unit itself in some cases.

[0219] The readable storage medium provided in this application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned task priority scheduling method, and can solve the technical problem that the existing financial data warehouse task priority scheduling method is less rational. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the task priority scheduling method provided in the above-mentioned embodiment, and will not be elaborated here.

[0220] The present application also provides a computer program product, including a computer program, which implements the steps of the task priority scheduling method as described above when executed by a processor.

[0221] The computer program product provided by this application can solve the technical problem that the existing financial data warehouse task priority scheduling method is less rational. Compared with the prior art, the beneficial effects of the computer program product provided by this application are the same as the beneficial effects of the task priority scheduling method provided by the above embodiment, which will not be repeated here.

[0222] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A task priority scheduling method, It is characterized in that The method comprises: Obtain a pre-generated weighted task set, wherein the weighted task set includes a plurality of weighted task data, each weighted task data includes a task to be scheduled and corresponding weight data; Based on a preset priority scheduling algorithm and task timeliness classification rules, the weighted task set is prioritized to obtain a priority task set; Based on a preset dynamic adjustment algorithm, the priority task set is dynamically adjusted to obtain a task priority scheduling result.

2. The method according to claim 1, It is characterized in that Before the step of obtaining the pre-generated weight task set, the following steps are also included: Acquire a task link, wherein the task link includes a plurality of initial tasks and corresponding link relationships; According to the task link, a plurality of weighted task data are obtained; The weighted task set is established according to a plurality of the weighted task data.

3. The method according to claim 2, It is characterized in that The step of obtaining a plurality of weighted task data according to the task link comprises: Task selection step: selecting any of the initial tasks as the task to be scheduled; Link positioning step: performing link positioning on the task to be scheduled according to the link relationship to obtain single link position data; Weight calculation step: calculating the weight data according to the single link position data; The weighted task data generating step: generating the weighted task data according to the task to be arranged and the weight data; The steps of task selection, link positioning, weight calculation, and weight task data generation are repeated until the task link is traversed to obtain a plurality of weight task data.

4. The method according to claim 1, It is characterized in that The task timeliness classification rule includes a timeliness level classification rule and a data output time classification rule. The step of performing priority scheduling on the weighted task set based on the preset priority scheduling algorithm and task timeliness classification rule to obtain the priority task set includes: Based on the timeliness level classification rule, the weighted task set is classified and sorted according to the timeliness level to obtain a plurality of first classification task sets; Based on the data output time classification rule, classify and sort the first classification task sets according to the data output time to obtain a plurality of second classification task sets; Based on the priority arrangement algorithm, a plurality of the second classification task sets are prioritized to obtain the priority task set.

5. The method according to claim 4, It is characterized in that The step of performing priority arrangement on a plurality of the second classification task sets based on the priority arrangement algorithm to obtain the priority task sets comprises: Selecting each of the second classification task sets in a plurality of the second classification task sets in turn as a target task set; Based on the priority scheduling algorithm, the priority of the target task set is calculated to obtain priority data; The priority task set is established according to a plurality of the second classification task sets and a corresponding plurality of priority data.

6. The method according to claim 5, It is characterized in that The priority scheduling algorithm includes a set priority calculation algorithm and a single task priority calculation algorithm. The step of calculating the priority of the target task set based on the priority scheduling algorithm and obtaining the priority data includes: Based on the set priority calculation algorithm, the priority of the target task set is calculated to obtain set priority data; Based on the single task priority calculation algorithm, according to a plurality of target weight data in the target task set, the priorities of a plurality of target tasks in the target task set are calculated to obtain a task priority data set; The priority data is obtained according to the set priority data and the task priority data set.

7. The method according to claim 1, It is characterized in that The step of dynamically adjusting the priority task set based on a preset dynamic adjustment algorithm to obtain a task priority scheduling result includes: Based on the preset link relationship, a plurality of priority tasks in the priority task set are sorted to obtain a plurality of link sequence tasks; Selecting each of the plurality of link sequence tasks in turn as a task to be adjusted; Obtaining the predicted completion time data of the task to be adjusted, and judging whether the predicted completion time of the task to be adjusted is greater than the preset output time according to the predicted completion time data, and obtaining a judgment result; Based on the dynamic adjustment algorithm, according to the judgment result, the priority of the task to be adjusted is dynamically adjusted to obtain a dynamic adjustment result; The task priority scheduling result is generated according to the priority task set and a plurality of dynamic adjustment results.

8. The method according to claim 7, It is characterized in that The dynamic adjustment result is a first dynamic adjustment result, the priority task set includes a plurality of second classification task sets and a plurality of corresponding set priority data, and the step of dynamically adjusting the priority of the task to be adjusted based on the dynamic adjustment algorithm and the judgment result includes: When the judgment result is that the predicted completion time of the task to be adjusted is greater than the preset output time, determining the second classified task set where the task to be adjusted is located, and taking the maximum value of the set priority data corresponding to the second classified task set as the target priority data; Based on the dynamic adjustment algorithm, the task priority data corresponding to the task to be adjusted is adjusted to the target priority data to obtain the first dynamic adjustment result.

9. A task priority arrangement device, It is characterized in that The device comprises: A set acquisition module is used to acquire a pre-generated weight task set, wherein the weight task set includes a plurality of weight task data, each of which includes a task to be scheduled and corresponding weight data; A priority scheduling module is used to schedule the weighted task set based on a preset priority scheduling algorithm and task timeliness classification rules to obtain a priority task set; The dynamic adjustment module is used to dynamically adjust the priority task set based on a preset dynamic adjustment algorithm to obtain a task priority scheduling result.

10. A task priority scheduling device, It is characterized in that The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the task priority scheduling method according to any one of claims 1 to 8.

11. A computer program product, It is characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the task priority scheduling method according to any one of claims 1 to 8 are implemented.

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