Data processing method, system and equipment and storage medium

Abstract

The invention provides a data processing method, system and device and a storage medium, and relates to the technical field of data processing, and the method comprises the steps: receiving a plurality of task creation requests sent by a business system, and creating a plurality of business tasks; generating a first processing sequence of the plurality of business tasks in combination with the processing priority and the association index of each business task; adjusting the first processing sequence according to the resource occupation amount of each business task to generate a second processing sequence; calculating a delay risk index of each business task, and adjusting the second processing sequence according to the delay risk index to generate a target processing sequence; the delay risk index is used for representing the influence degree of the processing delay of each business task on the business; and processing the plurality of service tasks according to the target processing sequence through a preset global task monitor. The method has the technical effects that the scheduling efficiency in a complex service scene is improved, so that the overall performance of the system is improved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a data processing method, system, device and storage medium. Background Art

[0002] In current enterprise-level business process management systems, workflow engines (such as Flowable) typically need to handle a large number of concurrent task requests. The order in which tasks are processed directly affects the efficiency of business execution and resource utilization. How to efficiently handle a large number of concurrent tasks has become a technical problem that needs to be solved urgently.

[0003] Currently, static priority scheduling is commonly used to manage the order of task execution. For example, an initial execution queue is generated by pre-setting task priority rules. While this approach is simple to implement and has low computational overhead, it lacks the ability to dynamically adjust to the actual runtime state of the system. This results in inefficient scheduling in complex business scenarios, impacting overall system performance. Summary of the Invention

[0004] The present application provides a data processing method, system, device and storage medium for improving scheduling efficiency in complex business scenarios, thereby improving the overall performance of the system.

[0005] In the first aspect, the present application provides a data processing method, which includes: receiving multiple task creation requests sent by a business system, and creating multiple business tasks; obtaining the processing priority of each of the business tasks and the correlation index between each of the business tasks, and generating a first processing order for the multiple business tasks by combining the processing priority and the correlation index; obtaining the resource occupancy of each of the business tasks, and adjusting the first processing order according to the resource occupancy to generate a second processing order; calculating the delay risk index of each of the business tasks, and adjusting the second processing order according to the delay risk index to generate a target processing order; the delay risk index is used to characterize the degree of impact of the processing delay of each of the business tasks on the business; and processing the multiple business tasks according to the target processing order through a preset global task listener.

[0006] By adopting the above technical solutions, a multi-dimensional task scheduling mechanism is constructed by comprehensively considering the processing priority of business tasks, the correlation index between tasks, the resource usage, and the delay risk index, thus realizing the intelligent optimization of the processing order of business tasks. The solution first establishes an initial order based on the importance of the business, then ensures the coordinated processing of related tasks through correlation analysis, and then combines resource usage adjustment to avoid system resource bottlenecks. Finally, the processing order is further optimized according to the delay risk index, comprehensively balancing multiple factors such as business priority, task correlation, system resource utilization efficiency, and business impact. This optimized target processing order is executed through a preset global task listener, which significantly improves the scheduling efficiency in complex business scenarios, thereby improving the overall performance of the system.

[0007] Optionally, obtaining the processing priority of each of the business tasks and the correlation index between each of the business tasks includes: obtaining the preset priority of each of the business tasks and the processing rules of each of the business tasks, adjusting the preset priority according to the processing rules to obtain the processing priority of each of the business tasks; collecting the preset correlation level between each of the business tasks, and determining the correlation index between each of the business tasks according to the preset correlation level, wherein the correlation index is positively correlated with the correlation level.

[0008] By adopting the above technical solution, the preset priority is dynamically adjusted through processing rules, and the correlation index between tasks is quantified based on the preset correlation level, which realizes the refined management of task priority and correlation. It enables the system to more accurately identify the critical path and dependency chain of task processing, avoid the misalignment of highly correlated task processing, improve the flexibility of task scheduling and processing coordination efficiency, reduce delays caused by improper handling of dependencies, and make business processes smoother and more efficient.

[0009] Optionally, the combination of the processing priority and the association index to generate a first processing order for the plurality of the business tasks includes: determining an initial processing order for the plurality of the business tasks based on the processing priority; determining business task pairs whose association index is greater than an association threshold; adjusting the positions of the business task pairs whose association index is greater than the association threshold to be adjacent in the initial processing order; and generating a first processing order for the plurality of the business tasks based on the adjusted order.

[0010] By adopting the above technical solution, we effectively balance task priority and relevance requirements by first determining the initial processing order of business tasks and then identifying and adjusting the relative positions of highly correlated task pairs. The solution first establishes an initial processing order based on processing priority, then screens business task pairs with a relevance index greater than the relevance threshold. These highly correlated task pairs are adjusted to adjacent positions within the initial order, ultimately generating the first processing order. This processing mechanism ensures that highly correlated tasks can be executed in close proximity, reducing switching costs and waiting time between tasks while still maintaining a basic respect for overall priority. This improves the consistency and efficiency of task processing and reduces the risk of resource waste and processing delays caused by the fragmented processing of related tasks.

[0011] Optionally, the first processing sequence is adjusted according to the resource occupancy to generate a second processing sequence, including: obtaining the total amount of system resources, calculating the ratio of the resource occupancy of each business task to the total amount of system resources; determining high-resource-consuming tasks whose resource occupancy rate is greater than the resource threshold; in the first processing sequence, reordering the high-resource-consuming tasks so that tasks whose resource occupancy rate is less than the resource threshold are inserted between multiple adjacent high-resource-consuming tasks; and generating a second processing sequence based on the adjusted sequence.

[0012] By adopting the above technical solution, by identifying high-resource-consuming tasks and optimizing their distribution in the processing sequence, the system resource bottleneck problem that may be caused by the continuous execution of resource-intensive tasks is effectively resolved. The solution first calculates the resource utilization rate of the tasks, identifies high-resource-consuming tasks whose resource utilization rate exceeds the resource threshold, and then adjusts the first processing order to insert tasks with lower resource utilization rates between adjacent high-resource-consuming tasks to form a second processing order. This resource-balancing sorting strategy avoids the concentrated execution of high-resource-consuming tasks, making the system resource load more balanced, preventing the risk of instantaneous tension or exhaustion of system resources, improving the overall throughput and stability of the system, and reducing task processing delays caused by resource competition.

[0013] Optionally, the calculation of the delay risk index of each of the business tasks includes: obtaining a preset business impact level of each of the business tasks, the business impact level being used to characterize the degree of impact of business task delays on business processes; obtaining a remaining processing time limit of each of the business tasks, and calculating the delay risk index of each of the business tasks based on the business impact level and the remaining processing time limit, wherein the business impact level is positively correlated with the delay risk index, and the remaining processing time limit is inversely correlated with the delay risk index.

[0014] By adopting the above technical solution, a dynamic delay risk assessment mechanism was established by comprehensively considering the business impact level and remaining processing time limit of business tasks. The solution obtains the preset business impact level of the task, which reflects the impact of task delay on the business process, and also obtains the remaining processing time limit. Based on this, the delay risk index is calculated, so that the business impact level is positively correlated with the delay risk index, and the remaining processing time limit is negatively correlated with the delay risk index. This mechanism enables the system to accurately identify critical tasks that have both high business impact and tight time constraints, providing a scientific basis for adjusting the subsequent processing sequence and effectively preventing serious business impacts caused by processing delays on high-value business tasks.

[0015] Optionally, the second processing sequence is adjusted according to the delay risk index to generate a target processing sequence, including: arranging each of the business tasks in the second processing sequence in descending order according to the delay risk index to generate an initial risk ranking; identifying urgent tasks in the initial risk ranking whose delay risk index is greater than a risk threshold; and advancing the execution position of the urgent tasks in the second processing sequence to generate a target processing sequence.

[0016] By employing the above technical solution, the business tasks in the second processing sequence are arranged in descending order of delay risk index to form an initial risk ranking. Urgent tasks with delay risk indices greater than the risk threshold are then identified and their execution positions are advanced in the second processing sequence, ultimately generating the target processing sequence. This mechanism ensures that tasks facing high delay risk receive more timely processing, effectively reducing the likelihood of task timeouts and mitigating the potential business impact of task processing delays. While ensuring overall processing efficiency, it also improves the system's responsiveness to business timeliness requirements and implements the risk-prioritized principle of task processing.

[0017] Optionally, after processing multiple business tasks in accordance with the target processing order through the preset global task listener, it also includes: real-time monitoring of the actual execution progress of each business task; when it is detected that the actual execution progress of any business task lags behind the preset progress, adjusting the target processing order to generate a final processing order.

[0018] By adopting the above technical solution and introducing a real-time monitoring and dynamic adjustment mechanism, the task processing process is continuously optimized. While executing the target processing sequence through the global task listener, the solution monitors the actual execution progress of each business task in real time. When it is found that the execution progress of any task lags behind the preset progress, the system will promptly adjust the target processing sequence and generate the final processing sequence. This closed-loop feedback mechanism enables the task scheduling system to have adaptive capabilities, and can respond and correct abnormal situations that occur during the execution process in real time, prevent chain delays caused by task execution deviating from expectations, and ensure that the overall task processing continues to maintain the optimal state, further improving the reliability and adaptability of the system's task processing. In particular, when facing complex and changing business environments, it can respond more flexibly to various execution anomalies.

[0019] In a second aspect, the present application provides a data processing system, comprising: a receiving module, a first acquisition module, a second acquisition module, a calculation module, and an adjustment module; wherein, The receiving module is used to receive multiple task creation requests sent by the business system and create multiple business tasks; the first acquisition module is used to obtain the processing priority of each business task and the correlation index between each business task, and generate a first processing order for the multiple business tasks in combination with the processing priority and the correlation index; the second acquisition module is used to obtain the resource occupancy of each business task, and adjust the first processing order according to the resource occupancy to generate a second processing order; the calculation module is used to calculate the delay risk index of each business task, and adjust the second processing order according to the delay risk index to generate a target processing order; the delay risk index is used to characterize the degree of impact of the processing delay of each business task on the business; the adjustment module is used to process the multiple business tasks according to the target processing order through a preset global task listener.

[0020] In a third aspect, the present application provides an electronic device that adopts the following technical solution: it includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes a computer program such as any of the above-mentioned data processing methods.

[0021] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: storing a computer program that can be loaded by a processor and execute any of the above-mentioned data processing methods.

[0022] In summary, this application includes at least one of the following beneficial technical effects: By comprehensively considering the processing priority of business tasks, the correlation index between tasks, resource usage, and the delay risk index, a multi-dimensional task scheduling mechanism was constructed to achieve intelligent optimization of the processing order of business tasks. The solution first establishes an initial order based on business importance, then ensures the coordinated processing of related tasks through correlation analysis, and then combines resource usage adjustments to avoid system resource bottlenecks. Finally, the processing order is further optimized based on the delay risk index, comprehensively balancing multiple factors such as business priority, task correlation, system resource utilization efficiency, and business impact. This optimized target processing order is executed through a preset global task listener, significantly improving scheduling efficiency in complex business scenarios, thereby improving the overall performance of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 This is a flow chart of a data processing method provided in an embodiment of the present application; Figure 2 This is a structural diagram of a data processing system provided in an embodiment of the present application; Figure 3 This is a structural diagram of an electronic device provided in an embodiment of the present application.

[0024] Description of reference numerals: 1000, electronic device; 1001, processor; 1002, communication bus; 1003, user interface; 1004, network interface; 1005, memory. DETAILED DESCRIPTION

[0025] In order to enable people skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0026] In the description of the embodiments of this application, words such as "exemplary," "for example," or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary," "for example," or "for example" in the embodiments of this application should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary," "for example," or "for example" is intended to present the relevant concepts in a concrete manner.

[0027] The application scenarios of this application include but are not limited to a telecom operator using the Flowable workflow engine to manage a customer order processing system, which faces thousands of business processing tasks of different types, priorities and resource requirements every day, such as number portability, package changes, complaint handling, etc. The system originally used a simple first-in-first-out strategy to process tasks, resulting in delays in high-value services, uneven allocation of system resources, and fragmented processing of related services. By deploying a global task listener, this application enables the system to automatically analyze the processing priority, correlation index, resource usage and delay risk index of each order, and dynamically generate the optimal processing sequence, so that VIP customer orders are given priority, related businesses are executed coherently, high-resource consumption tasks are arranged in a staggered manner, and tasks approaching timeout are promptly advanced. While ensuring balanced utilization of system resources, it improves task processing efficiency and customer satisfaction. Especially during business peak periods, the system no longer crashes due to resource competition, realizing intelligent, automated and refined management of business processing.

[0028] Figure 1 This is a flow chart of a data processing method provided by an embodiment of the present application. Figure 1 As shown, the method includes S101-S105: S101, receiving multiple task creation requests sent by a business system, and creating multiple business tasks.

[0029] In this embodiment, business systems can be various business applications such as internal OA systems, customer relationship management systems, and smart city management platforms. These systems generate a large number of business tasks during their daily operations, such as customer order processing, document approval, complaint handling, and city event work orders. In traditional workflows, these tasks are typically processed in a simple chronological order or with fixed priorities, lacking intelligent scheduling mechanisms. This leads to uneven utilization of system resources and potentially delays in processing high-value tasks.

[0030] To address this issue, this application receives task creation requests from these business systems through a system interface. Each request contains key information such as task type, business data, priority identifier, and expected completion time. The system then converts these requests into standardized business task objects, each containing attribute fields such as a unique identifier, business type, creation time, expected completion time, and task status. At the same time, it establishes an association between the task and the original business data, ensuring that business information can be accurately traced and updated during subsequent processing.

[0031] In actual implementation, the system can capture these task creation events through a global task listener based on the Flowable workflow engine. The listener is configured to listen to the TaskCreatedEvent event type in the Flowable engine to achieve centralized monitoring and processing of all user task creation processes.

[0032] Flowable is an open-source business process management platform that provides a complete workflow engine and business process execution environment for designing, executing, and monitoring business processes. Based on the BPMN 2.0 (Business Process Model and Notation) standard, it supports core functions such as process definition, task assignment, and event monitoring, and is widely used in enterprise workflow automation.

[0033] TaskCreatedEvent is an event type in the Flowable workflow engine and is part of the Flowable event mechanism. The Flowable engine automatically triggers this event when a new user task is created in a workflow. The system can configure event listeners to capture and handle these events, enabling centralized monitoring and management of the task creation process.

[0034] S102 : Obtain the processing priority of each business task and the correlation index between each business task, and generate a first processing order of the plurality of business tasks by combining the processing priority and the correlation index.

[0035] In the specific implementation, the system first obtains the preset priority of each business task from the task attributes or business rule library, such as the basic priority value set according to the task type (urgent task, routine task, batch task, etc.) or business source (VIP customer, ordinary customer, etc.); then the system retrieves the task processing rule library and adjusts the preset priority according to dynamic factors such as the current business scenario and system load to obtain the final processing priority of each business task. The processing priority can be expressed as a value from 1 to 10, and the larger the value, the higher the urgency of task processing. At the same time, the system analyzes the correlation between each business task and calculates the correlation index between tasks.

[0036] The correlation index refers to a numerical value that characterizes the degree of correlation between two business tasks. It can be determined in a variety of ways: first, it is explicitly defined based on business rules, such as multiple requests from the same customer have a high correlation; second, it is to mine implicit correlations through data analysis, such as event work orders in geographically close cities may be correlated; third, it is to learn correlation patterns based on historical processing data. The correlation index can be expressed as a value between 0 and 1, and the larger the value, the higher the correlation between tasks. After obtaining these two sets of parameters, the system first preliminarily sorts the tasks according to the processing priority and determines the initial processing order; then it identifies task pairs whose correlation index exceeds a preset threshold (such as 0.7), and adjusts the positions of these highly correlated tasks in the initial order so that they are arranged as adjacent as possible, thereby forming the final first processing order.

[0037] Based on the above embodiment, as an optional implementation, in S102, obtaining the processing priority of each business task and the correlation index between each business task specifically includes S21-S22: S21 , obtaining the preset priority of each business task and the processing rule of each business task, adjusting the preset priority according to the processing rule, and obtaining the processing priority of each business task.

[0038] The system obtains the preset priority of each business task and the processing rules for each business task, and adjusts the preset priority based on the processing rules to determine the processing priority of each business task. The preset priority is usually a basic priority value pre-set by the business system when creating a task based on basic information such as business type, customer level, and transaction amount. However, these static preset values ​​often cannot fully reflect the actual urgency of the task in the current business environment and need to be dynamically adjusted in conjunction with the processing rules.

[0039] Processing rules refer to a combination of conditions and actions pre-configured in the system, forming a set of policies used to adjust task priorities in specific business scenarios. Processing rules can include time decay rules, load balancing rules, business continuity rules, and other types. The system first obtains the preset priority of each business task from the task database or business system interface, then retrieves the set of processing rules applicable to the current business environment from the rule library and applies these rules to adjust the preset priority. For example, for tasks approaching their deadlines, the system applies the time decay rule to increase their priority; for multiple requests from the same important customer, the system applies the customer aggregation rule to appropriately increase their priority; and during peak system load periods, the system may apply the load balancing rule to reduce the priority of certain non-critical tasks. Through this dynamic adjustment, the system obtains processing priorities that better reflect actual business value, providing more accurate basic data for subsequent task sorting.

[0040] S22 , collecting preset correlation levels between the business tasks, and determining correlation indexes between the business tasks based on the preset correlation levels, where the correlation index is positively correlated with the correlation level.

[0041] The system collects the preset correlation levels between business tasks and determines the correlation index between them based on the preset correlation levels. The correlation index is positively correlated with the correlation level. The correlation between business tasks is a key consideration for intelligent task sorting. Consecutive processing of highly correlated tasks can significantly improve processing efficiency and business continuity.

[0042] Pre-set correlation levels are categorized to characterize the degree of correlation between business tasks. These can be explicitly defined by business rules or extracted from historical data. The system collects these levels through various channels: first, explicitly defined correlations are obtained from the business rule library, such as different business requests from the same customer or multiple work items from the same project; second, implicit correlations are extracted from task metadata, such as geographically close work orders or tasks using the same resources; and third, empirical correlations are analyzed from historical processing records, such as task types frequently handled by the same person. The system then converts the pre-set correlation levels into standardized correlation indices. The correlation index is a numerical value between 0 and 1 that quantifies the degree of correlation between two tasks, with higher values ​​indicating a higher degree of correlation. This conversion typically utilizes a mapping function, such as a linear mapping or a piecewise function, to ensure a positive correlation between the correlation index and the correlation level. Furthermore, the system considers the transitive and directionality of correlations. For task groups with transitive correlations, a graph algorithm is used to calculate the degree of indirect correlation between tasks, resulting in a more comprehensive correlation index matrix.

[0043] To determine the correlation index between business tasks, the following fixed method can be used: First, the preset correlation level is divided into five standard levels: no correlation (Level 1), weak correlation (Level 2), moderate correlation (Level 3), strong correlation (Level 4), and close correlation (Level 5). A linear mapping function is then applied to convert the correlation level into a correlation index, using the following formula: Correlation Index = (Correlation Level - 1) × 0.25. Thus, no correlation corresponds to a correlation index of 0, weak correlation to 0.25, moderate correlation to 0.5, strong correlation to 0.75, and close correlation to 1.0. For implicit correlations, the system quantitatively evaluates them using four core dimensions: data sharing, business process continuity, resource usage similarity, and spatiotemporal correlation. Each dimension is weighted from 0 to 0.25, and the cumulative scores are used to determine the final correlation index.

[0044] Based on the above embodiment, as an optional implementation, in S102, combining the processing priority and the relevance index to generate a first processing sequence of multiple business tasks specifically includes S23-S26: S23: Determine the initial processing order of the multiple business tasks according to the processing priorities.

[0045] S24: Determine a business task pair whose correlation index is greater than a correlation threshold.

[0046] The correlation threshold refers to a system-preset correlation index threshold. When the correlation index between two business tasks exceeds this threshold, it indicates that the two tasks are significantly related and should be processed adjacently to improve processing efficiency. Based on the correlation index matrix calculated in step S22, the system compares the correlation index of each pair of business tasks with a preset correlation threshold (e.g., 0.75), identifies all task pairs with correlation indices exceeding the threshold, and sorts them from high to low by correlation index to form a list of highly correlated task pairs. This step ensures that the system can identify closely related tasks that truly require sequential processing, providing a basis for subsequent order adjustments.

[0047] S25 , in the initial processing sequence, adjusting the positions of the business task pairs whose correlation index is greater than the correlation threshold to be adjacent.

[0048] In the initial processing order, the system adjusts the positions of business task pairs with a correlation index greater than the correlation threshold to be adjacent. For identified highly correlated task pairs, the system needs to adjust their positions to be adjacent while maintaining the initial priority order as much as possible.

[0049] The specific adjustment strategy involves first processing pairs of highly correlated tasks one by one, from highest to lowest, according to their correlation index. For each pair of highly correlated tasks, their positions in the initial processing order are compared, and the later-placed task is adjusted to the position immediately following the earlier task. If conflicts arise during the adjustment process (i.e., multiple tasks need to be adjusted to the same position), the order is determined by the correlation index. To prevent tasks with low priority from being excessively advanced due to their correlation, the system also sets a priority tolerance parameter, limiting the maximum number of positions a task can be advanced during the adjustment process.

[0050] S26: Generate a first processing sequence of the plurality of business tasks based on the adjusted sequence.

[0051] S103: Obtain resource usage of each business task, adjust the first processing sequence according to the resource usage, and generate a second processing sequence.

[0052] During implementation, the system first uses the resource assessment module to obtain information about the resource usage of each business task. Resource usage refers to the total amount of resources consumed to complete a specific business task, which can be represented as a multi-dimensional resource vector. This includes, but is not limited to, processor time, memory space, storage capacity, network bandwidth, special equipment usage time, and human resources.

[0053] Resource usage is obtained through: first, analyzing historical execution records of similar tasks based on historical statistical data to extract average resource consumption; second, estimating resource requirements based on task feature predictions, such as task type, data volume, and complexity; and third, obtaining resource requirements directly from the business system through resource requirement declarations. After obtaining resource usage, the system calculates the resource usage distribution of adjacent tasks in the first processing order, identifying areas with "spikes" in resource usage—i.e., areas where multiple resource-intensive tasks are concentrated. The system then adjusts the processing order of these areas: identifying high-resource-consuming tasks whose resource usage exceeds a preset threshold. While maintaining the relative priority order and the relative position of highly correlated tasks, these tasks are appropriately dispersed and inserted into lower-resource-consuming tasks, creating a more balanced second processing order. During this adjustment, the system employs a resource smoothing algorithm that comprehensively considers peak resource usage, task importance, and correlation, and uses dynamic programming to find the task ordering solution that most evenly balances resource usage.

[0054] Based on the above embodiment, as an optional implementation, in S103, the first processing sequence is adjusted according to the resource usage, and the second processing sequence is generated, which specifically includes S31-S34: S31, obtaining the total amount of system resources, and calculating the ratio of the resource usage of each business task to the total amount of system resources.

[0055] S32: Determine a high resource consumption task whose resource occupancy rate is greater than a resource threshold.

[0056] S33 , in the first processing sequence, reordering the high resource consumption tasks so that a task with a resource occupancy rate less than the resource threshold is inserted between a plurality of adjacently executed high resource consumption tasks.

[0057] S34: Generate a second processing order based on the adjusted order.

[0058] In the first processing sequence, the system reorders high-resource-consuming tasks, inserting tasks with resource utilization rates below the resource threshold between consecutive high-resource-consuming tasks. The system first analyzes the distribution of high-resource-consuming tasks in the first processing sequence and identifies all consecutive clusters of high-resource-consuming tasks. For each such cluster, the system calculates the peak resource utilization that would result if the original sequence were executed. If the peak resource utilization exceeds the system's acceptable safety limit (e.g., 80%), the tasks in the cluster need to be split and reordered.

[0059] The reordering strategy is to disperse consecutive high-resource-consuming tasks while maintaining the overall framework of the first processing order, inserting tasks with lower resource usage between them as a "buffer." The selection of inserted tasks takes into account several factors, including resource complementarity (i.e., selecting tasks that occupy different resource types), processing priority (preferring higher-priority, low-resource tasks), and correlation index (trying to avoid disrupting highly correlated task pairs).

[0060] S104 , calculating the delay risk index of each business task, adjusting the second processing sequence according to the delay risk index, and generating a target processing sequence; the delay risk index is used to represent the degree of impact of the processing delay of each business task on the business.

[0061] In real-world business environments, the consequences of delayed processing vary significantly. Some delayed tasks can lead to severe business losses, compliance risks, or even chain reactions, while others have a higher time tolerance. While the secondary processing order based on priority, relevance index, and resource usage takes into account task importance and system resource balance, it fails to fully reflect the actual impact of task delays on the business. This can cause some time-sensitive tasks to be delayed due to scheduling, resulting in unnecessary business losses.

[0062] This step introduces the delay risk index, a key parameter, to make a final optimization of the processing sequence, aiming to minimize the negative impact of task delays on the overall business and maximize business value. The delay risk index is a quantitative indicator that characterizes the degree to which delays in business task processing have a negative impact on related businesses. It is a comprehensive assessment of the time sensitivity of tasks. When calculating the delay risk index, the system takes into account a variety of factors: first, the time sensitivity of the task, that is, the rate at which the value of the task decreases over time. Some tasks, such as emergency handling and real-time transactions, have extremely high time sensitivity; second, the business impact scope of the task, which assesses the scope of business that may be affected by the delay of the task. Tasks with a wide range of business implications have a higher risk of delays; third, the chain reaction risk. The delay of certain tasks may trigger a series of subsequent problems, forming a chain effect; finally, it also includes compliance risks, customer satisfaction impact and other factors.

[0063] The system uses a comprehensive assessment algorithm to calculate a delay risk index, which can be expressed as a value from 0 to 100, with higher values ​​indicating greater delay risk. After obtaining the delay risk index for each task, the system optimizes the second processing order: first, it identifies high-risk tasks with a delay risk index exceeding a preset threshold (e.g., 85 points) and schedules these tasks in advance while maintaining the aforementioned constraints. It then applies a time value decay calculation to the remaining tasks, calculating the expected loss from delayed processing based on the task's expected processing time and delay risk index. The processing order is then adjusted accordingly to form the final target processing order.

[0064] Based on the above embodiment, as an optional implementation, in S104, calculating the delay risk index of each business task specifically includes S41-S42: S41 , obtaining a preset business impact level of each business task, where the business impact level is used to represent the degree of impact of a business task delay on a business process.

[0065] The system obtains the preset business impact level for each business task, which is used to characterize the degree of impact that a delay in a business task will have on the business process. The business impact level is a grading indicator pre-defined by business experts or the system based on task characteristics and business rules, reflecting the degree of negative impact that a delayed task would have on the enterprise. The system typically divides business impact levels into multiple tiers, such as critical (Level 5), highly important (Level 4), important (Level 3), general (Level 2), and low impact (Level 1). The system obtains business impact levels through multiple channels: first, extracting default impact levels based on task types from the business rule library; second, obtaining impact ratings for specific tasks from business departments or customer feedback; and third, automatically deriving impact levels based on historical data analysis of the correlation between task delays and business indicators. The introduction of business impact levels enables the system to differentiate the risk differences associated with delays in different tasks, providing key input for calculating the delay risk index.

[0066] S42, obtaining the remaining processing time limit of each business task, and calculating the delay risk index of each business task based on the business impact level and the remaining processing time limit, wherein the business impact level is positively correlated with the delay risk index, and the remaining processing time limit is inversely correlated with the delay risk index.

[0067] The system obtains the remaining processing time of each business task and calculates the delay risk index of each business task based on the business impact level and the remaining processing time. The remaining processing time refers to the time interval between the current time point and the deadline by which the task must be completed, usually in hours or minutes. The system first extracts the scheduled deadline from the task metadata and calculates the remaining processing time based on the current system time. For tasks without a clear deadline, the system determines the standard processing time based on the service level agreement (SLA) and task type. The delay risk index refers to a comprehensive indicator that quantifies the size of the business risk that may be brought about by delayed task processing. The value range is usually 0-100, and the higher the value, the greater the delay risk.

[0068] The system uses the following calculation formula: Delay Risk Index = Business Impact Weight × (1 - Remaining Time Adjustment Factor), where the Business Impact Weight is the weight of the business impact level mapped to a range of 0-100, such as 100 for the Critical level, 80 for the Highly Important level, and so on. The Remaining Time Adjustment Factor is a value between 0 and 1 calculated by applying an inverse proportional function to the remaining processing time. For example, the calculation method can be Remaining Time Adjustment Factor = min(1, Remaining Processing Time / Standard Processing Time). This calculation method ensures that the business impact level and the delay risk index are positively correlated, that is, the higher the impact level, the greater the delay risk index; at the same time, the remaining processing time and the delay risk index are inversely correlated, that is, the shorter the remaining time, the greater the delay risk index. For special types of tasks, the system also considers additional factors, such as the impact of time factors such as nighttime batch processing windows, business peak periods, and system maintenance periods on delay risk, by introducing correction coefficients into the basic formula.

[0069] Based on the above embodiment, as an optional implementation, in S104, adjusting the second processing order according to the delay risk index to generate the target processing order specifically includes S43-S45: S43: Arrange the business tasks in the second processing sequence in descending order according to the delay risk index to generate an initial risk ranking.

[0070] S44, identifying urgent tasks whose delay risk index is greater than the risk threshold in the initial risk ranking.

[0071] S45: Advance the execution position of the urgent task in the second processing sequence to generate a target processing sequence.

[0072] The system advances the execution position of the urgent task in the second processing sequence to generate the target processing sequence. The system needs to appropriately advance the urgent task identified in S44 to reduce its delay risk while maintaining the overall structure of the second processing sequence as much as possible.

[0073] The specific adjustment strategy includes: first, processing each urgent task from high to low according to the delay risk index; for each urgent task, the system calculates the minimum number of positions it needs to be advanced based on its current position in the second processing sequence and the estimated time required to complete it, so that it can be completed before the deadline; the system adopts the principle of minimum intervention when making adjustments, that is, while meeting the risk control objectives, it minimizes disruption to the original sequence, especially avoiding disruption to the optimized related task pairs and balanced resource distribution; if multiple urgent tasks need to be adjusted to similar positions, the system determines the final position based on the delay risk index, with tasks with higher risk indexes being ranked higher. The system also sets an upper limit parameter for position advancement to prevent low-priority but high-risk tasks from being excessively advanced, resulting in damage to the overall business value.

[0074] After this fine-grained position adjustment, the system generates the final target processing order, which is further optimized based on the second processing order, maintaining the basic framework of priority, relevance, and resource balance, while effectively reducing the possibility of delays in high-risk tasks.

[0075] S105: Process multiple business tasks in a target processing order through a preset global task listener.

[0076] The system processes multiple business tasks according to the target processing sequence through a pre-set global task listener. In traditional task processing mechanisms, task processing is often decentralized and executed independently across various business systems. This lacks unified monitoring and scheduling capabilities, making it impossible to effectively execute the optimized processing sequence generated in the aforementioned steps. This leads to problems such as irrational resource allocation and low processing efficiency.

[0077] By introducing a global task listener as a unified coordination mechanism for task processing, the goal is to effectively apply the optimized target processing sequence to actual business processing, ensuring that tasks are executed in the optimal order, thereby maximizing the system's overall processing efficiency and business value. The global task listener is a system-level component that monitors and coordinates task processing flows across multiple business systems, providing functions such as task status monitoring, resource scheduling, and execution sequence control.

[0078] In the specific implementation, the global task listener is first integrated with the workflow engine, and the whole task life cycle is monitored by configuring the task events in the listening workflow engine. After receiving the target processing sequence generated by the above steps, the listener converts it into a task processing instruction sequence and stores it in the system's scheduling queue, and then coordinates the processing of each task according to the queue sequence. The coordination methods include: first, controlling the task allocation mechanism of the workflow engine to ensure that the system allocates tasks to executors or automatic processing components according to the target processing sequence; second, reasonably scheduling task execution resources to ensure that high-priority tasks can obtain sufficient processing resources; third, real-time monitoring of task processing status, early warning and intervention of delayed tasks, and adjusting the processing order of subsequent tasks when necessary to adapt to real-time situation changes.

[0079] The global task listener also maintains inter-task dependencies and resource usage. When a resource-intensive task completes, the listener immediately releases the associated resources and allocates them to subsequent tasks, ensuring continuous and efficient resource utilization. Furthermore, the listener collects and records data from the entire task processing process, including task start and completion times, resource usage, and execution results, providing data support for subsequent task processing optimization.

[0080] After processing multiple business tasks in the target processing order through the preset global task listener, it also includes: Monitor the actual execution progress of each business task in real time; when it is detected that the actual execution progress of any business task lags behind the preset progress, adjust the target processing sequence and generate the final processing sequence.

[0081] The actual execution progress of each business task is monitored in real time through the global task listener. The global task listener is a special component preset in the system, which is responsible for collecting and analyzing status data during the task execution process. The listener obtains execution progress information in a variety of ways: first, it obtains task status update events from the task execution engine; second, it periodically polls the status data of the task execution environment; third, it receives progress information actively reported by the task processing component. The system sets an expected execution path and time node for each task to form a preset progress baseline. The preset progress refers to the ideal execution time plan formulated by the system for each task based on historical execution data and task characteristic analysis, including time points such as the expected start time, key stage completion time and expected end time. The global task listener compares the task execution data collected in real time with the preset progress, calculates the progress deviation, and evaluates the potential impact of the deviation on the overall processing flow.

[0082] When the system detects that the actual execution progress of any business task lags behind the preset progress, it will trigger a dynamic adjustment of the processing order. The system first performs an impact analysis on the tasks that are behind schedule, and evaluates the impact of their delays on subsequent tasks and overall business goals. The assessment takes into account multiple factors: first, the criticality of the delayed task, to determine whether it is on the critical path of the business; second, the severity of the delay, to calculate the deviation between the actual progress and the preset progress; third, the scope of associated impact, to analyze how many subsequent tasks depend on the completion of this task; fourth, the remaining processing time limit, to evaluate whether the task can be completed as originally planned within the remaining time. Based on these analyses, the system calculates and adjusts the urgency index for each delayed task to guide subsequent sequence adjustments.

[0083] The system adopts corresponding processing strategies based on the adjustment urgency. For tasks with high adjustment urgency, the system may take the following measures: First, resource optimization, allocating more system resources to the task to speed up processing; second, sequence adjustment, bringing the task to the front of the current execution queue; third, parallel processing, if conditions permit, splitting the task into subtasks that can be executed in parallel; fourth, task replacement, temporarily shelving non-critical tasks currently being executed and giving priority to high-urgency tasks. For tasks with medium adjustment urgency, the system may adopt moderate adjustment strategies, such as fine-tuning their position in the queue to be executed, or reserving necessary system resources for them in advance. For tasks with low adjustment urgency, the system may temporarily maintain the original plan, but increase the frequency of monitoring their execution status to prepare for possible future adjustments.

[0084] Through these dynamic adjustment strategies, the system generates a final processing order. This final processing order refers to the business task processing sequence actually adopted by the system after real-time monitoring and dynamic adjustment. It optimizes the target processing order to adapt to actual changes during execution. The system applies the final processing order to the task scheduling engine to guide the execution allocation and resource scheduling of subsequent tasks. Simultaneously, the system continuously monitors the performance of the adjusted execution and feeds relevant data back to the prediction model and rule base to optimize future processing order generation processes.

[0085] Based on the above method, the present application also discloses a data processing system, such as Figure 2 As shown, Figure 2 : is a structural diagram of a data processing system provided in an embodiment of the present application, the system includes: a receiving module, a first acquisition module, a second acquisition module, a calculation module and an adjustment module; wherein, A receiving module is used to receive multiple task creation requests sent by the business system and create multiple business tasks; a first acquisition module is used to obtain the processing priority of each business task and the correlation index between each business task, and generate a first processing order for multiple business tasks in combination with the processing priority and the correlation index; a second acquisition module is used to obtain the resource occupancy of each business task, and adjust the first processing order according to the resource occupancy to generate a second processing order; a calculation module is used to calculate the delay risk index of each business task, and adjust the second processing order according to the delay risk index to generate a target processing order; the delay risk index is used to characterize the degree of impact of the processing delay of each business task on the business; an adjustment module is used to process multiple business tasks in accordance with the target processing order through a preset global task listener.

[0086] It should be noted that the above embodiments provide systems that implement their functions using only the division of the above functional modules as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the system and method embodiments provided in the above embodiments are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0087] See Figure 3 , is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 3 As shown, the electronic device 1000 may include: at least one processor 1001 , at least one network interface 1004 , a user interface 1003 , a memory 1005 , and at least one communication bus 1002 .

[0088] The communication bus 1002 is used to implement the connection and communication between these components.

[0089] The user interface 1003 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 1003 may also include a standard wired interface and a wireless interface.

[0090] The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0091] Processor 1001 may include one or more processing cores. Using various interfaces and circuits, processor 1001 connects to various components within the server. It executes instructions, programs, code sets, or instruction sets stored in memory 1005, as well as accesses data stored in memory 1005, to perform various server functions and process data. Optionally, processor 1001 may be implemented using at least one of the following hardware forms: a digital signal processing (DSP), a field-programmable gate array (FPGA), or a programmable logic array (PLA). Processor 1001 may integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. The CPU primarily processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing content displayed on the display; and the modem handles wireless communications. It is understood that the modem may not be integrated into processor 1001 but implemented as a separate chip.

[0092] Among them, the memory 1005 may include a random access memory (RAM) or a read-only memory (Read-Only Memory). Optionally, the memory 1005 includes a non-transitory computer-readable storage medium. The memory 1005 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 1005 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 1005 may optionally be at least one storage device located away from the aforementioned processor 1001. As Figure 3 As shown, the memory 1005 as a computer storage medium may include an operating system, a network communication module, a user interface module and an application program of a data processing method.

[0093] exist Figure 3In the electronic device 1000 shown, the user interface 1003 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 1001 can be used to call an application program storing a data processing method in the memory 1005. When executed by one or more processors, the electronic device executes one or more methods described in the above embodiments.

[0094] An electronic device readable storage medium stores instructions, which, when executed by one or more processors, enable the electronic device to execute one or more of the methods described in the above embodiments.

[0095] It should be noted that for the aforementioned method embodiments, for simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for this application.

[0096] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0097] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of the devices or units can be electrical or other forms.

[0098] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0099] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0100] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of this application, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of this application. The aforementioned memory includes various media that can store program code, such as USB flash drives, mobile hard drives, magnetic disks, or optical disks.

[0101] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the specification and practicing the disclosure herein, those skilled in the art will easily think of other embodiments of the present disclosure. This application is intended to cover any variations, uses or adaptations of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary technical means in the art that are not recorded in the present disclosure. The description and examples are to be regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A data processing method, characterized in that: The method comprises: Receive multiple task creation requests sent by the business system and create multiple business tasks; Obtaining a processing priority of each of the business tasks and a correlation index between the business tasks, and generating a first processing order of the plurality of business tasks by combining the processing priority and the correlation index; Obtaining resource usage of each of the business tasks, and adjusting the first processing sequence according to the resource usage to generate a second processing sequence; Calculating a delay risk index for each of the business tasks, and adjusting the second processing sequence based on the delay risk index to generate a target processing sequence; the delay risk index is used to represent the degree of impact of processing delays on the business of each of the business tasks; The plurality of business tasks are processed in the target processing order by a preset global task listener.

2. The data processing method according to claim 1, wherein: The obtaining of the processing priority of each business task and the correlation index between the business tasks includes: Obtaining a preset priority of each of the business tasks and a processing rule for each of the business tasks, and adjusting the preset priority according to the processing rule to obtain a processing priority of each of the business tasks; The preset correlation levels between the business tasks are collected, and a correlation index between the business tasks is determined according to the preset correlation levels, wherein the correlation index is positively correlated with the correlation level.

3. The data processing method according to claim 1, wherein: The step of combining the processing priority and the relevance index to generate a first processing order for the plurality of business tasks includes: determining an initial processing order of the plurality of business tasks according to the processing priority; Determine a business task pair whose correlation index is greater than a correlation threshold; In the initial processing sequence, positions of the business task pairs whose correlation index is greater than a correlation threshold are adjusted to be adjacent; Based on the adjusted sequence, a first processing sequence of the plurality of business tasks is generated.

4. The data processing method according to claim 1, wherein: The adjusting the first processing order according to the resource occupancy to generate a second processing order includes: Obtaining the total amount of system resources, and calculating the ratio of the resource usage of each business task to the total amount of system resources; Determine a high resource consumption task whose resource occupancy rate is greater than a resource threshold; In the first processing sequence, the high resource consumption tasks are reordered so that a task with a resource occupancy rate less than the resource threshold is inserted between a plurality of adjacently executed high resource consumption tasks; Based on the adjusted order, a second processing order is generated.

5. The data processing method according to claim 1, wherein: Calculating the delay risk index of each business task includes: Obtaining a preset business impact level for each of the business tasks, where the business impact level is used to represent the degree of impact of a business task delay on a business process; Obtain the remaining processing time limit of each of the business tasks, and calculate the delay risk index of each of the business tasks based on the business impact level and the remaining processing time limit, wherein the business impact level is positively correlated with the delay risk index, and the remaining processing time limit is inversely correlated with the delay risk index.

6. The data processing method according to claim 1, wherein: The adjusting the second processing sequence according to the delay risk index to generate a target processing sequence includes: Arrange the business tasks in the second processing sequence in descending order according to the delay risk index to generate an initial risk ranking; Identifying urgent tasks whose delay risk index is greater than a risk threshold in the initial risk ranking; In the second processing sequence, the execution position of the urgent task is advanced to generate a target processing sequence.

7. The data processing method according to claim 1, wherein: After the preset global task listener processes the plurality of business tasks in accordance with the target processing order, the method further includes: Real-time monitoring of the actual execution progress of each of the business tasks; When it is detected that the actual execution progress of any business task lags behind the preset progress, the target processing sequence is adjusted to generate a final processing sequence.

8. A data processing system, characterized in that: The system includes: a receiving module, a first obtaining module, a second obtaining module, a calculating module and an adjusting module; wherein, The receiving module is used to receive multiple task creation requests sent by the business system and create multiple business tasks; The first acquisition module is configured to acquire a processing priority of each of the business tasks and a correlation index between the business tasks, and generate a first processing order of the plurality of business tasks based on the processing priority and the correlation index; The second acquisition module is configured to acquire the resource usage of each of the business tasks, and adjust the first processing sequence according to the resource usage to generate a second processing sequence; The calculation module is configured to calculate a delay risk index for each of the business tasks, and adjust the second processing sequence based on the delay risk index to generate a target processing sequence; the delay risk index is used to characterize the degree of impact of the processing delay of each of the business tasks on the business; The adjustment module is used to process the plurality of business tasks according to the target processing order through a preset global task listener.

9. An electronic device, characterized in that: The electronic device comprises a processor, a memory, a user interface and a network interface, wherein the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that A computer program is stored which can be loaded by a processor and execute the method according to any one of claims 1 to 7.

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