Batch task dynamic processing method and device, equipment, medium and product

Abstract

The embodiment of the invention provides a batch task dynamic processing method and device, equipment, a medium and a product, and the method comprises the steps that at least one target system meeting preset conditions is determined, and the at least one target system is an online system used for processing batch tasks; for at least one target system, reading batch task configuration information corresponding to the current moment, and according to the batch task configuration information, determining a batch task processing interval duration of the target system; and controlling the target system to process the batch tasks based on the processing interval duration. According to the technical scheme, after the processing interval duration of the batch tasks is determined on the basis of the batch task configuration information, the online system is controlled to process the batch tasks on the basis of the processing interval duration, concurrent tasks can be dynamically adjusted, resources can be reasonably distributed, computing power can be fully utilized, and the processing efficiency is improved. The effect of improving the stability and task processing efficiency of the online system is achieved.

Description

Technical Field

[0001] This disclosure relates to the field of data processing technology, and in particular to a method, apparatus, device, medium, and product for dynamic processing of batch tasks. Background Technology

[0002] In actual system operation, batch tasks in the batch system may require the use of some of the online system's surplus computing power for processing. To maximize the utilization of the online system's surplus computing power, the batch system must be able to control the concurrency level.

[0003] Currently, the main method for controlling concurrency in batch systems is to control the number of task nodes initiated. However, if the number of task nodes to be initiated needs to be adjusted during batch task processing, the batch task processing must be paused, and the number of task nodes to be executed must be reallocated. This results in insufficient utilization of computing power and low efficiency in batch task processing. Summary of the Invention

[0004] This disclosure provides a method, apparatus, device, medium, and product for dynamic processing of batch tasks, so as to achieve dynamic adjustment of concurrent tasks, reasonable allocation of resources, and full utilization of computing power, thereby improving the stability and data processing efficiency of online systems.

[0005] In a first aspect, embodiments of this disclosure provide a method for dynamic processing of batch tasks, the method comprising:

[0006] Identify at least one target system that meets preset conditions, wherein the at least one target system is an online system for processing batch tasks;

[0007] For the at least one target system, read the batch task configuration information corresponding to the current time, and determine the processing interval of the batch tasks by the target system based on the batch task configuration information;

[0008] The target system is controlled to process the batch tasks based on the processing interval duration.

[0009] Secondly, embodiments of the present invention also provide a batch task dynamic processing device, the device comprising:

[0010] The target system determination module is used to determine at least one target system that meets preset conditions, wherein the at least one target system is an online system used for processing batch tasks;

[0011] An interval duration processing module is used to read batch task configuration information corresponding to the current time for the at least one target system, and determine the processing interval duration of the target system for batch tasks based on the batch task configuration information.

[0012] The task execution module is used to control the target system to process the batch tasks based on the processing interval duration.

[0013] Thirdly, embodiments of the present invention also provide an electronic device, the electronic device comprising:

[0014] One or more processors;

[0015] Storage device for storing one or more programs.

[0016] When the one or more programs are executed by the one or more processors, the one or more processors implement the batch task dynamic processing method as described in any of the embodiments of the present invention.

[0017] Fourthly, embodiments of the present invention also provide a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform the batch task dynamic processing method as described in any of the embodiments of the present invention.

[0018] Fifthly, embodiments of the present invention also provide a computer program product, including a computer program, characterized in that, when executed by a processor, the computer program implements the batch task dynamic processing method as described in any of the embodiments of the present invention.

[0019] The technical solution of this disclosure identifies at least one target system that meets preset conditions, wherein the at least one target system is an online system for processing batch tasks. Then, for the at least one target system, batch task configuration information corresponding to the current time is read, and the processing interval for batch tasks by the target system is determined based on the batch task configuration information. Finally, the processing of batch tasks by the target system is controlled based on the processing interval, solving the problems of insufficient computing power utilization and low batch task processing efficiency in the prior art, which controls concurrency by controlling the number of initiated task nodes. This disclosure realizes that after determining the processing interval for batch tasks based on batch task configuration information, the online system is controlled to process batch tasks based on the processing interval, which can dynamically adjust concurrent tasks, rationally allocate resources, and fully utilize computing power, thereby improving the stability and data processing efficiency of the online system. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of exemplary embodiments of the present invention, the accompanying drawings used in describing the embodiments are briefly introduced below. Obviously, the accompanying drawings described are only a portion of the drawings of the embodiments to be described in this invention, and not all of the drawings. For those skilled in the art, other drawings can be obtained from these drawings without any creative effort.

[0021] Figure 1 This is a flowchart illustrating a batch task dynamic processing method provided in an embodiment of this disclosure;

[0022] Figure 2 This is a flowchart illustrating a batch task dynamic processing method provided in an embodiment of this disclosure;

[0023] Figure 3 This is a schematic diagram of the structure of a batch task dynamic processing device provided in an embodiment of the present disclosure;

[0024] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0025] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.

[0026] Before introducing the technical solutions provided in the embodiments of this disclosure, the application scenarios can be illustrated first. The technical solutions provided in the embodiments of this disclosure can be applied to scenarios where a system processes batch tasks. For example, they can be applied to scenarios where the surplus computing power of an online system is used to process batch tasks of a batch system. Based on the technical solutions of the embodiments of this disclosure, after determining the processing interval for batch tasks based on batch task configuration information, the online system is controlled to process batch tasks based on the processing interval. This allows for dynamic adjustment of concurrent tasks, reasonable allocation of resources, and full utilization of computing power, thereby improving the stability and data processing efficiency of the online system.

[0027] Example 1

[0028] Figure 1This is a flowchart illustrating a batch task dynamic processing method provided in this embodiment. This embodiment is applicable to situations where the surplus computing power of an online system is used to process batch tasks of a batch system. The method can be executed by a batch task dynamic processing device, which can be implemented in the form of software and / or hardware. The hardware can be a mobile electronic device, which can execute the batch task dynamic processing method provided in this technical solution.

[0029] like Figure 1 As shown, the method includes:

[0030] S110. Determine at least one target system that meets the preset conditions.

[0031] At least one target system is an online system used for processing batch tasks. It should be noted that a target system refers to a system with processing bottlenecks such as CPU, memory, storage, or network bandwidth. The preset conditions refer to the bottlenecks in CPU, memory, storage, or network bandwidth when processing batch tasks. When the target system encounters bottlenecks in CPU, memory, storage, or network bandwidth, it proves that the target system meets the preset conditions. For example, when processing batch tasks on a batch system based on the surplus computing power of an online system, at least one target system can be determined based on the CPU, memory, storage, or network bandwidth of the target system and the preset conditions.

[0032] Specifically, when an online system processes real-time transactions and utilizes its surplus computing power to handle batch tasks, real-time monitoring tools can be used to detect the usage of the online system's CPU, memory, storage, or network bandwidth. When the CPU, memory, storage, or network bandwidth of the online system exceeds its corresponding threshold, it indicates that the task processing capacity of the online system is limited, thereby identifying at least one target system.

[0033] For example, when the CPU utilization of the online system exceeds 80%, it indicates that the target system meets the preset conditions; when the memory utilization of the online system is higher than 75%, it indicates that the target system meets the preset conditions; when the available storage space of the online system is lower than 15%, it indicates that the target system meets the preset conditions; when the network bandwidth utilization of the online system exceeds 80%, it indicates that the target system meets the preset conditions. Based on whether the preset conditions are met, at least one target system is determined.

[0034] S120. For at least one target system, read the batch task configuration information corresponding to the current time, and determine the processing interval of the batch tasks by the target system based on the batch task configuration information.

[0035] The batch task configuration information refers to the pre-configured parameters and settings for how batch tasks are processed in different time periods. This information includes at least one time period and the corresponding target throughput information for that period. The target throughput information refers to the number of tasks the system is expected to complete per unit of time, determined based on historical data. A batch task can contain multiple tasks, and the processing interval refers to the idle time between executing two consecutive tasks.

[0036] Optionally, the target throughput information in the batch task configuration information can be substituted into the task interval processing function to determine the processing interval duration of the target system when processing batch tasks at the current time.

[0037] The task interval processing function is as follows:

[0038] t' = N / m' - t;

[0039] Where t' refers to the processing interval of the target system when processing batch tasks at the current moment; N refers to the number of target systems; m' refers to the target throughput information; and t refers to the execution time of a single task in the batch.

[0040] It should be noted that by substituting the target throughput information, the number of target systems, and the execution time of each individual task in the batch task configuration information at the current moment into the task interval processing function, the processing interval duration of the target system when processing the batch task at the current moment can be obtained.

[0041] It's also worth noting that an aspect can be created within the application. Aspect-oriented programming (AOP) uses pre-compilation and runtime dynamic proxies to achieve unified maintenance of program functionality. Before each task begins processing, it retrieves the current target throughput information based on the current moment, calculates the processing interval duration using the task interval processing function, and executes the processing interval within the aspect. After the processing interval duration expires, the next task continues execution.

[0042] Specifically, after identifying at least one target system that meets the preset conditions, the number of target systems is determined. A predefined data structure can be traversed to read the batch task configuration information corresponding to the current time. Then, the target throughput information, the number of target systems, and the execution time of each individual task in the batch task configuration information are substituted into the task interval processing function to determine the processing interval duration of the target system when processing the batch task at the current time.

[0043] S130. The target system processes batch tasks based on the processing interval duration.

[0044] It should be noted that after determining the processing interval, the target system can execute batch tasks periodically according to the set processing interval. For example, if the target system calculates and determines the processing interval for batch tasks to be 1 minute after reading the batch task configuration information corresponding to the current time, then the processing interval between any two tasks during the process of the target system processing batch tasks according to the target throughput information is 1 minute.

[0045] In this embodiment, in response to changes in the current date and current time, the batch task configuration information corresponding to the changes is readjusted.

[0046] It's important to note that a date change event refers to a change in the date itself. For example, transitioning from the last day of this month to the first day of the next month, or from the last day of one quarter to the first day of the next quarter. A time change event refers to a change in the time of day. For example, the time changes from 23:59 to 00:00, or from 09:59 to 10:00. Reasons for needing to adjust batch task configuration information when a change event occurs may include: different dates or time periods may have different business requirements, or the resources of the target system may change during a specific time period.

[0047] It should also be noted that when a change event occurs, the batch task configuration information corresponding to the change event is readjusted, and then the adjusted batch task configuration information is published to the distributed configuration center. At this time, in the application's aspect, since the new batch task configuration information is read, the new processing interval duration can be calculated in real time based on the new target throughput information. Because components such as the distributed configuration center have hot refresh capabilities, the target throughput information can be adjusted in real time without pausing batch task processing or restarting the online system.

[0048] Specifically, after determining the processing interval of the target system when processing batch tasks at the current moment, the target system is controlled based on the processing interval, and the target system processes the batch tasks according to the processing interval.

[0049] The technical solution of this disclosure identifies at least one target system that meets preset conditions, wherein the at least one target system is an online system for processing batch tasks. Then, for the at least one target system, batch task configuration information corresponding to the current time is read, and the processing interval for batch tasks by the target system is determined based on the batch task configuration information. Finally, the processing of batch tasks by the target system is controlled based on the processing interval, solving the problems of insufficient computing power utilization and low batch task processing efficiency in the prior art, which controls concurrency by controlling the number of initiated task nodes. This disclosure realizes that after determining the processing interval for batch tasks based on batch task configuration information, the online system is controlled to process batch tasks based on the processing interval, which can dynamically adjust concurrent tasks, rationally allocate resources, and fully utilize computing power, thereby improving the stability and data processing efficiency of the online system.

[0050] Example 2

[0051] Figure 2 This is a flowchart illustrating the batch task dynamic processing method provided in this embodiment of the invention. Based on the foregoing embodiments, it provides a more detailed explanation of determining batch task configuration information for at least one time period associated with the current date. Specific implementation methods can be found in the technical solution of this embodiment. Technical terms that are the same as or corresponding to those in the above embodiments will not be repeated here.

[0052] like Figure 2 As shown, the method specifically includes the following steps:

[0053] S210. Based on the current date and the transaction throughput information associated with the current date, determine the target throughput information corresponding to at least one time period.

[0054] Transaction throughput information refers to the number of tasks the target system is expected to complete within a unit of time related to the current date. Determining the target throughput information for at least one time period means setting the number of tasks the target system is expected to complete within a unit of time for one or more specific time periods on the current date. For example, if the current date is October 1st, the target throughput information for 9:00 AM to 10:00 AM on October 1st can be determined based on the current date and the transaction throughput information associated with the current date; that is, the number of tasks the target system is expected to complete during this time period of 9:00 AM to 10:00 AM on October 1st can be set.

[0055] Optionally, the target throughput information corresponding to at least one time period is determined based on the transaction throughput information of at least one time period within a preset duration prior to the current date; or, the target throughput information corresponding to at least one time period is determined based on the week information corresponding to the current date and the transaction throughput information of at least one time period with the same week information within a historical duration.

[0056] It should be noted that the preset duration refers to a preset time period prior to the current date. For example, the preset duration could be 3 days. For at least one time period, the mean and variance of all transaction throughput information within that preset duration can be calculated, and then the target throughput information for that time period can be determined based on the mean and variance. Alternatively, the mean of all transaction throughput information within that preset duration can be calculated, and the target throughput information for that time period can be determined based on the mean and a preset margin. For example, assuming the current date is October 1st and the preset duration is 3 days, to determine the target throughput information for the time period from 10:00 AM to 11:00 AM, the transaction throughput information for each day from September 28th to September 30th from 10:00 AM to 11:00 AM can be obtained. Then, based on the transaction throughput information for each day from September 28th to September 30th from 10:00 AM to 11:00 AM, the mean and variance of the corresponding transaction throughput information can be determined. Finally, the target throughput information for the time period from 10:00 AM to 11:00 AM can be obtained by adding twice the variance to the mean of the transaction throughput information.

[0057] It should also be noted that the weekday information corresponding to the current date refers to the day of the week the current date falls on. For example, the weekday information corresponding to the current date could be Monday. Historical duration refers to a period of time preceding the current date. For example, the historical duration could be 30 days. For at least one time period, the mean and variance of all transaction throughput information within the historical duration that shares the same weekday information can be calculated, and then the target throughput information for that time period can be determined based on the mean and variance. Alternatively, the mean of all transaction throughput information within the historical duration that shares the same weekday information can be calculated, and then the target throughput information for that time period can be determined based on the mean and a preset margin. For example, assuming the weekday information corresponding to the current date is Monday, and the historical duration is the past 10 weeks, for the time period from 10:00 AM to 11:00 AM, the transaction throughput information from Mondays from 10:00 AM to 11:00 AM in the past 10 weeks can be obtained. Then, by statistically analyzing the mean and variance of this transaction throughput information, the target throughput information for the time period from 10:00 AM to 11:00 AM can be determined.

[0058] Specifically, for each time period, the target throughput information for each time period can be determined based on the current date and all transaction throughput information of the corresponding time period associated with the current date, according to relevant algorithms.

[0059] S220. Determine the batch task configuration information based on at least one time period corresponding to the current date and the corresponding target throughput information.

[0060] It should be noted that a data structure can be predefined to store batch task configuration information determined based on at least one time period corresponding to the current date and the corresponding target throughput information. Typically, this data structure can be defined using a hash map, an object, or a list. The data structure can include batch task configuration information, i.e., multiple time periods and their corresponding target throughput information.

[0061] It should also be noted that interfaces can be provided for reading, updating, and deleting batch task configuration information, providing a mechanism to update the data structure when the batch task configuration information needs to be changed. As a service for centrally managing and distributing application configuration information, the distributed configuration center provides a centralized storage location for multiple services or applications to access and update this batch task configuration information.

[0062] Optionally, based on the time period identifier corresponding to at least one time period of the current date and the corresponding target throughput information, generate the target format to be invoked information; use the to be invoked information as the batch task configuration information of the target system.

[0063] It should be noted that the time period identifier can be represented by a string, which can consist of the start and end times of the time period, or it can consist solely of the start time. For example, "00" can represent the time period 00:00-01:00; "09" can represent the time period 09:00-10:00. The target format can be defined as a key-value pair, representing each time period and its corresponding target throughput information. For example, the target format can be: 'Time Period Identifier': Target Throughput Information. The information to be invoked can be a structured list containing the time period identifier and the corresponding target throughput information. For example, the information to be invoked can include '00': 1000, indicating that within the time period 00:00-01:00, the target system expects to complete 1000 tasks per unit time period determined based on historical data; the information to be invoked can also include '09': 500, indicating that within the time period 09:00-10:00, the target system expects to complete 500 tasks per unit time period determined based on historical data.

[0064] It should also be noted that when generating the target format of the callable information based on the time period identifier corresponding to at least one time period of the current date and the corresponding target throughput information, firstly, the target throughput information corresponding to at least one time period is determined based on the current date and the transaction throughput information associated with the current date. Statistical analysis methods, such as mean and variance, can be used to derive the target throughput information. Then, the callable information is generated based on the time period identifier of the current date and the target throughput information. This can be achieved by iterating through each time period to build a list of the corresponding callable information. Finally, after generating the callable information, it can be submitted to the target system as configuration information for batch tasks. The specific invocation method may depend on the target system's API or other interfaces.

[0065] The technical solution of this disclosure determines target throughput information corresponding to at least one time period based on the current date and transaction throughput information associated with the current date. Then, based on the at least one time period corresponding to the current date and the corresponding target throughput information, batch task configuration information is determined, which can allocate resources more rationally, avoid overuse or idleness of resources in certain time periods, and improve the overall task processing efficiency.

[0066] Example 3

[0067] As an optional embodiment of the present invention, an example is provided to further illustrate the invention.

[0068] It should be noted that during the actual operation of the system, some batch systems rely on data from the online system. When it is not possible to completely separate the batch system and the online system through the data synchronization mechanism, there will be situations where the tasks of the batch system need to occupy a portion of the computing power of the online system.

[0069] Online systems, as a type of computer system, can process user requests and batch tasks in real time, and are characterized by high availability and high concurrency. The surplus computing power of an online system refers to the currently available but unused computing resources within the system. These resources can include CPU, memory, storage, and network bandwidth. The surplus computing power of an online system can be considered as its potential data processing capacity at a specific moment, which can be dynamically allocated to other tasks to improve overall resource utilization.

[0070] It's important to note that batch systems, as another type of computer system, are primarily used for the centralized processing of large amounts of tasks and data, which are typically submitted in a non-real-time environment. Batch systems collect and process these tasks within a specific timeframe, usually without requiring real-time user interaction. A batch task in a batch system refers to a set of tasks that need to be processed, and these tasks are typically processed centrally within a specific time period.

[0071] In this embodiment of the invention, batch tasks may include batch accounting, summary accounting, completing customer transaction instructions, periodic reconciliation, and generating customer account statements, etc.

[0072] It should also be noted that the resource consumption of batch tasks can be measured using the computing power consumed per unit time, with the specific formula being: MIPS = N * m * X / 10 6 In this embodiment, MIPS refers to the computing power consumed per unit time; N can represent the number of target systems; m refers to transaction throughput information, i.e., the number of tasks executed by the target system per unit time; X refers to the number of instructions consumed by each task. In this invention, after determining the number of target systems, the number of target systems can be temporarily fixed, and X is also fixed. Therefore, the computing power consumed per unit time can be adjusted by adjusting the transaction throughput information. Parameters affecting transaction throughput information include the execution time of a single task, and usually, the execution time of a single task is also fixed. In this invention, by increasing the processing interval between two tasks, the transaction throughput information is changed, thereby adjusting the computing power consumed per unit time and ultimately changing the concurrency of the batch system.

[0073] In this embodiment of the invention, the factors affecting the number of tasks executed by the target system within a unit of time include the individual task execution time t, and the value of t is fixed. Therefore, it is possible to increase the interval time t' between task executions, thereby reducing m and obtaining the adjusted number of tasks m' executed by the target system within a unit of time. The formula is:

[0074] m' = 1 / (t+t')*N;

[0075] That is, the direct relationship between the number of tasks m' executed by the target system within the adjusted unit time and the interval t' between task executions is obtained. By reversing the formula, the function f(m') of t' with respect to m' can be obtained. That is:

[0076] t' = N / m' - t;

[0077] Based on f(m'), only the desired m' sequence needs to be configured to obtain the corresponding t' sequence, thereby achieving the goal of consuming resources differently at different times of the day.

[0078] Specifically, identify system bottlenecks based on operational data; for example, the bottleneck might be system A. Then, estimate the transaction throughput of system A across different time periods. For instance, the transaction throughput of system A from 0:00 to 6:00 could be 1000 TPS, from 6:00 to 18:00 could be 500 TPS, and from 18:00 to 24:00 could be 300 TPS. Finally, define a data structure and publish it to a distributed configuration center. For example, a hash table could be used to publish the transaction throughput information to the distributed configuration center.

[0079] For example, if you want the concurrency to be different for each hour of the day, you can define the parameter as follows: where the key represents the hour, and the value represents the number of tasks expected to be completed per second, i.e., the value of m'. For example, '00': 1000 means that between 00:00 and 01:00, you want to complete 1000 tasks per second. '09': 500 means that between 09:00 and 10:00, you want to complete 500 tasks per second.

[0080] It's worth noting that an aspect can be created in the application. Before each task begins, the current expected value m' is obtained based on the current time, and t' is calculated using the function t' = N / m' - t. The aspect then executes sleep(t'). After the sleep period, the task continues execution. This achieves the goal of macroscopically reducing concurrency to the expected value. Concurrency can also be dynamically adjusted. When the bottleneck system resources change, or when the bottleneck system shifts, the concurrency parameters can be adjusted to adapt to the new system bottleneck.

[0081] For example, if system A achieves a throughput of 2000 TPS from 0:00 to 6:00 by scaling up, then only the parameter from 00:00 to 05 needs to be adjusted to 2000 TPS to increase the overall concurrency. If system B on the link becomes a new bottleneck due to heavy workload, with an estimated throughput of only 50 TPS from 15:00 to 18:00, then only the parameter from 15:00 to 17 needs to be adjusted to 50 TPS to reduce concurrency and meet system B's requirements. The adjusted parameters are then published to the distributed configuration center. At this point, the application's aspects, upon reading the new concurrency parameters, can calculate the new sleep time in real time based on these new parameters. Components such as the distributed configuration center have hot-refresh capabilities, enabling real-time adjustment of concurrency without requiring batch or application restarts.

[0082] The technical solution of this disclosure innovatively transforms the conventional practice of scheduling nodes in batch tasks into scheduling individual tasks by minimizing the granularity of resource usage to a single task. By controlling the interval of individual tasks, it achieves macroscopic concurrency adjustment. Since scheduling is performed on a task-by-task basis, the precision of control is significantly improved, enabling more flexible responses to resource allocation needs. It supports expansion across multiple control dimensions, facilitating adjustments based on specific requirements and meeting different application scenarios. Decoupling the acquisition of concurrency targets from achieving those targets ensures independent optimization during adjustment, improving the overall system performance and responsiveness.

[0083] Example 4

[0084] Figure 3 This is a schematic diagram of the structure of the batch task dynamic processing device provided in the embodiments of this disclosure, as shown below. Figure 3 As shown, the device includes: a target system determination module 310, an interval duration processing module 320, and a task execution module 330.

[0085] The target system determination module is used to determine at least one target system that meets preset conditions, wherein the at least one target system is an online system for processing batch tasks; the interval duration processing module is used to read the batch task configuration information corresponding to the current time for the at least one target system, and determine the processing interval duration of the target system for the batch tasks according to the batch task configuration information; the task execution module is used to control the target system to process the batch tasks based on the processing interval duration.

[0086] The technical solution of this disclosure identifies at least one target system that meets preset conditions, wherein the at least one target system is an online system for processing batch tasks. Then, for the at least one target system, batch task configuration information corresponding to the current time is read, and the processing interval for batch tasks by the target system is determined based on the batch task configuration information. Finally, the processing of batch tasks by the target system is controlled based on the processing interval, solving the problems of insufficient computing power utilization and low batch task processing efficiency in the prior art, which controls concurrency by controlling the number of initiated task nodes. This disclosure realizes that after determining the processing interval for batch tasks based on batch task configuration information, the online system is controlled to process batch tasks based on the processing interval, which can dynamically adjust concurrent tasks, rationally allocate resources, and fully utilize computing power, thereby improving the stability and data processing efficiency of the online system.

[0087] Based on the above technical solutions, the device further includes: a batch task configuration information determination module, used to determine batch task configuration information for at least one time period associated with the current date.

[0088] Based on the above technical solutions, the batch task configuration information determination module includes: a target throughput information determination submodule and a batch task configuration information calculation submodule.

[0089] The target throughput information determination submodule is used to determine the target throughput information corresponding to at least one time period based on the current date and the transaction throughput information associated with the current date;

[0090] The batch task configuration information calculation submodule is used to determine the batch task configuration information based on at least one time period corresponding to the current date and the corresponding target throughput information.

[0091] Based on the above technical solutions, the target throughput information calculation submodule includes: a date processing unit, used to determine the target throughput information corresponding to the at least one time period based on the transaction throughput information of the current date and at least one time period within a preset duration before the current date; or, to determine the target throughput information corresponding to the at least one time period based on the week information corresponding to the current date and the transaction throughput information of at least one time period with the same week information within a historical duration.

[0092] Based on the above technical solutions, the batch task configuration information calculation submodule includes a callable information generation unit and a batch task configuration information configuration unit.

[0093] The call-to-be-called information generation unit is used to generate call-to-be-called information in a target format based on the time period identifier of at least one time period corresponding to the current date and the corresponding target throughput information;

[0094] A batch task configuration information configuration unit is used to use the information to be invoked as the batch task configuration information of the target system.

[0095] Based on the above technical solutions, the interval duration processing module 320 includes a task interval processing function processing submodule.

[0096] The task interval processing function submodule is used to substitute the target throughput information in the batch task configuration information into the task interval processing function to determine the processing interval duration when the target system processes the batch tasks at the current time.

[0097] Based on the above technical solutions, the method further includes: a batch task configuration information adjustment module, used to readjust the batch task configuration information corresponding to the change event in response to the change event of the current date and the current time.

[0098] The batch task dynamic processing device provided in this disclosure can execute the batch task dynamic processing method provided in any embodiment of this disclosure, and has the corresponding functional modules and beneficial effects of the method execution.

[0099] It is worth noting that the various units and modules included in the above-mentioned device are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be realized; in addition, the specific names of each functional unit are only for easy differentiation and are not used to limit the protection scope of the embodiments of this disclosure.

[0100] Example 5

[0101] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Refer to the following... Figure 4 It illustrates an electronic device suitable for implementing embodiments of the present disclosure (e.g., Figure 4 The diagram below shows the structure of the terminal device or server 500. The terminal device in this embodiment may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and vehicle terminals (e.g., vehicle navigation terminals). Figure 4 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0102] like Figure 4 As shown, electronic device 500 may include a processing unit (e.g., central processing unit, graphics processor, etc.) 501, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 502 or a program loaded from storage device 508 into random access memory (RAM) 503. The RAM 503 also stores various programs and data required for the operation of electronic device 500. The processing unit 501, ROM 502, and RAM 503 are interconnected via bus 504. An edit / output (I / O) interface 505 is also connected to bus 504.

[0103] Typically, the following devices can be connected to I / O interface 505: input devices 506 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 507 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 508 including, for example, magnetic tapes, hard disks, etc.; and communication devices 509. Communication device 509 allows electronic device 500 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 4 An electronic device 500 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively.

[0104] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 509, or installed from a storage device 508, or installed from a ROM 502. When the computer program is executed by the processing device 501, it performs the functions defined in the methods of embodiments of this disclosure.

[0105] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0106] The electronic device provided in this embodiment and the batch task dynamic processing method provided in the above embodiments belong to the same inventive concept. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0107] Example 6

[0108] This disclosure provides a computer storage medium storing a computer program that, when executed by a processor, implements the batch task dynamic processing method provided in the above embodiments.

[0109] It should be noted that the computer-readable medium described in this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0110] In some implementations, the server may communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and may interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and end-to-end networks (e.g., ad hoc end-to-end networks), as well as any currently known or future-developed networks.

[0111] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0112] The aforementioned computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to:

[0113] Identify at least one target system that meets preset conditions, wherein the at least one target system is an online system for processing batch tasks;

[0114] For the at least one target system, read the batch task configuration information corresponding to the current time, and determine the processing interval of the batch tasks by the target system based on the batch task configuration information;

[0115] The target system is controlled to process the batch tasks based on the processing interval duration.

[0116] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including but not limited to object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0117] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0118] The units described in the embodiments of this disclosure can be implemented in software or hardware. The names of the units are not, in some cases, intended to limit the specific unit.

[0119] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0120] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0121] The above description is merely a preferred embodiment of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features disclosed in this disclosure that have similar functions.

[0122] Furthermore, while the operations are described in a specific order, this should not be construed as requiring these operations to be performed in the specific order shown or in a sequential order. In certain environments, multitasking and parallel processing may be advantageous. Similarly, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of this disclosure. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

[0123] Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely illustrative examples of implementing the claims.

Claims

1. A method for dynamic processing of batch tasks, characterized in that, include: Identify at least one target system that meets preset conditions, wherein the at least one target system is an online system for processing batch tasks; For the at least one target system, read the batch task configuration information corresponding to the current time, and determine the processing interval of the batch tasks by the target system based on the batch task configuration information; The target system is controlled to process the batch tasks based on the processing interval duration.

2. The method according to claim 1, characterized in that, Also includes: Determine the batch task configuration information for at least one time period associated with the current date; The determination of batch task configuration information for at least one time period associated with the current date includes: Based on the current date and the transaction throughput information associated with the current date, determine the target throughput information corresponding to at least one time period; The batch task configuration information is determined based on at least one time period corresponding to the current date and the corresponding target throughput information.

3. The method according to claim 2, characterized in that, The step of determining the target throughput information corresponding to at least one time period based on the current date and the transaction throughput information associated with the current date includes: Based on the transaction throughput information of the current date and at least one time period within a preset duration prior to the current date, determine the target throughput information corresponding to the at least one time period; or, Based on the weekday information corresponding to the current date and the transaction throughput information of at least one time period with the same weekday information within the historical time frame, the target throughput information corresponding to the at least one time period is determined.

4. The method according to claim 2, characterized in that, The step of determining the batch task configuration information based on at least one time period corresponding to the current date and the corresponding target throughput information includes: Based on the time period identifier of at least one time period corresponding to the current date and the corresponding target throughput information, generate the target format of the call information; The information to be invoked is used as the batch task configuration information of the target system.

5. The method according to claim 1, characterized in that, The step of determining the processing interval for batch tasks by the target system based on the batch task configuration information includes: Substitute the target throughput information from the batch task configuration information into the task interval processing function to determine the processing interval duration of the target system when processing the batch tasks at the current time.

6. The method according to claim 1, characterized in that, The method further includes: In response to changes in the current date and time, the batch task configuration information corresponding to the changes is readjusted.

7. A batch task dynamic processing device, characterized in that, include: The target system determination module is used to determine at least one target system that meets preset conditions, wherein the at least one target system is an online system used for processing batch tasks; An interval duration processing module is used to read batch task configuration information corresponding to the current time for the at least one target system, and determine the processing interval duration of the target system for batch tasks based on the batch task configuration information. The task execution module is used to control the target system to process the batch tasks based on the processing interval duration.

8. An electronic device, characterized in that, The electronic device includes: One or more processors; Storage device for storing one or more programs. When one or more programs are executed by one or more processors, the one or more processors implement the batch task dynamic processing method as described in any one of claims 1-6.

9. A storage medium containing computer-executable instructions, characterized in that, The computer-executable instructions, when executed by a computer processor, are used to perform the batch task dynamic processing method as described in any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the batch task dynamic processing method as described in any one of claims 1-6.

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