ERP control system and control method

Abstract

The embodiment of the invention provides an ERP control system and method, and relates to the technical field of electronic commerce, and the system comprises an obtaining module which is used for obtaining target data based on a plurality of target protocols; the determining module is used for determining target priorities corresponding to the multiple target tasks according to the target data; and the execution module is used for executing the multiple target tasks according to the target priorities. According to the method, the compatibility of the ERP control system is improved, the orderliness of executing multiple tasks by the ERP control system is improved, and thus the applicability of the ERP control system to a multi-level task execution situation is improved.

Description

Technical Field

[0001] Embodiments of the present application relate to the technical field of e-commerce, and in particular, to an ERP control system and a control method. Background Art

[0002] The ERP system, that is, the Enterprise Resource Planning system, is used to assist an enterprise in business process management based on multiple modules. In related technologies, existing ERP control systems have problems such as poor compatibility and chaotic execution orders of multi-level tasks.

[0003] Therefore, there is an urgent need for a new technical solution to solve the above technical problems. Summary of the Invention

[0004] According to embodiments of the present application, an ERP control system and a control method are provided, which are beneficial to improving the compatibility of the ERP control system, improving the orderliness of the ERP control system in executing multiple tasks, and thus improving the applicability of the ERP control system to multi-level task execution scenarios.

[0005] In a first aspect of the present application, an ERP control system is provided, including: An acquisition module, configured to acquire target data based on multiple target protocols; A determination module, configured to determine target priorities corresponding to multiple target tasks according to the target data; An execution module, configured to execute multiple target tasks according to the target priorities.

[0006] In some feasible embodiments, the above acquisition module includes: A polling unit, configured to acquire target data based on a target polling operation in a case where it is determined that a target response speed is less than or equal to a preset response speed, where the target polling operation includes: a lightweight polling operation.

[0007] In some feasible embodiments, the above determination module includes: A preprocessing unit, configured to perform a preprocessing operation on the target data in a case where it is determined that a format difference between target data is greater than a preset format difference threshold, so that the format difference is less than or equal to the preset format difference threshold.

[0008] In some feasible embodiments, the above determination module further includes: A determination unit, configured to determine target priorities according to a preset evaluation factor; where the preset evaluation factor includes: a customer value evaluation factor, an order amount evaluation factor, a transaction time evaluation factor, and / or a rule evaluation factor.

[0009] In some feasible embodiments, the above-mentioned determination unit includes: A first determination component, configured to determine an initial priority according to a preset evaluation factor and the weight corresponding to the preset evaluation factor; A second determination component, configured to determine a target priority according to the initial priority and the objective function.

[0010] In some feasible embodiments, the above-mentioned objective function includes: , where is the target priority, is the initial priority, is a preset parameter.

[0011] In some feasible embodiments, the above-mentioned execution module includes: An execution unit, configured to perform a target operation on target data according to the target priority to generate a target data stream; A verification unit, configured to perform a target verification operation on the target data stream; A generation unit, configured to generate a corresponding plurality of target tasks according to the verified target data stream; A matching unit, configured to match target tasks to corresponding target queues according to the target data stream.

[0012] In some feasible embodiments, the above-mentioned execution module further includes: A regulation unit, configured to regulate the task input rate of the target queue according to the relevant information of the target queue, so that the absolute value of the difference between the task input rate and the target task input rate is less than or equal to a preset threshold, where the relevant information includes: the current occupied capacity of the target queue and the maximum capacity of the target queue.

[0013] In some feasible embodiments, the above-mentioned regulation unit includes: A first calculation component, configured to determine the load rate of the target queue according to the relevant information, where the load rate is equal to the ratio of the current occupied capacity to the maximum capacity; A second calculation component, configured to determine a target processing efficiency ratio according to the actual processing rate and the desired processing rate of the target queue, where the target processing efficiency ratio is the ratio of the actual processing rate to the desired processing rate; A third calculation component, configured to determine the target task input rate according to the load rate, the target processing efficiency ratio, and the desired processing rate.

[0014] In a second aspect of the present application, there is provided an ERP control method, including: Obtaining target data based on multiple target protocols; Determining the target priorities corresponding to multiple target tasks according to the target data; Execute multiple target tasks according to the target priorities.

[0015] The ERP control system and control method provided by the embodiments of the present application, wherein the system includes: an acquisition module, configured to acquire target data based on multiple target protocols; a determination module, configured to determine the target priorities corresponding to multiple target tasks according to the target data; an execution module, configured to execute multiple target tasks according to the target priorities. The present application is beneficial to improving the compatibility of the ERP control system, improving the orderliness of the ERP control system in executing multiple tasks, and thus improving the applicability of the ERP control system to multi-level task execution scenarios.

[0016] It should be understood that the content described in the Summary of the Invention section is not intended to limit the key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In combination with the drawings and with reference to the following detailed description, the above and other features, advantages, and aspects of the embodiments of the present application will become more obvious. In the drawings, the same or similar reference numerals represent the same or similar elements, where: Figure 1 is a structural schematic diagram of an ERP control system provided by an embodiment of the present application; Figure 2 is a flowchart schematic diagram of an ERP control method provided by an embodiment of the present application; Figure 3 is a structural schematic diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present disclosure clearer, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure. Apparently, the described embodiments are some, but not all, of the embodiments of the present disclosure. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present disclosure without creative efforts shall fall within the protection scope of the present disclosure.

[0019] In addition, the term "and / or" in this document is merely a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this document generally represents an "or" relationship between the associated objects before and after.

[0020] In the first aspect of the embodiments of the present application, an ERP control system is proposed. Figure 1This is a structural schematic diagram of an ERP control system 100 provided by an embodiment of the present application. As Figure 1 shown, the system 100 includes: An acquisition module 110, configured to acquire target data based on multiple target protocols.

[0021] Exemplarily, the multiple target protocols may include: WebService protocol, RESTful protocol, WebHook protocol, EDI protocol, Oauth2 protocol, Basic protocol, and / or composite protocol. Among them, the composite protocol may include: a composite protocol of API Key and Secret.

[0022] Exemplarily, the target data may include: business classification data, order data, event type data, event creation data, event change data, event deletion data, event generation time data, document number data, self-incrementing serial number data of document dimensions, data content data, check value data, etc.

[0023] Exemplarily, the acquisition operation of the target data may be implemented based on the streaming processing framework Apache Flink CDC.

[0024] Exemplarily, the acquisition module may acquire the target data based on an adapter.

[0025] Specifically, in the case where the interface standard or data format of the corresponding target interface accessed by the ERP control system changes, the corresponding adapter can be modified to receive the target data correspondingly. It is also possible to perform add or delete operations on the target interface accessed by the ERP control system by adjusting the adapter.

[0026] It should be noted that in the case where there are multiple corresponding target interfaces accessed by the ERP control system, the adapters are independent of each other to improve the scalability of the ERP control system and reduce the coupling between multiple target interfaces.

[0027] In some feasible embodiments, the acquisition module includes: a polling unit, configured to acquire target data based on a target polling operation in the case where it is determined that the target response speed is less than or equal to a preset response speed, where the target polling operation includes: a lightweight polling operation.

[0028] It should be noted that the above preset response speed can be dynamically set according to the lower limit of the processing speed of the target user for the system and / or the upper limit of the resource consumption during the operation of the system. Among them, the above preset response speed is positively correlated with the above lower limit of the processing speed, that is, the higher the above lower limit of the processing speed, the greater the above preset response speed. The above preset response speed is negatively correlated with the above upper limit of the resource consumption, that is, the smaller the above upper limit of the resource consumption, the greater the above preset response speed.

[0029] Exemplarily, in the case where the response speed of retrieving target data based on Webhook and API callback is less than or equal to the preset response speed, the above target data can be obtained based on a lightweight polling operation.

[0030] Exemplarily, in the case where the response speed of retrieving target data based on Webhook and API callback is greater than the preset response speed, the above target data can be obtained based on a timed polling operation.

[0031] Thus, by configuring the polling unit in the above obtaining module, it is beneficial to dynamically and flexibly adjust the polling mechanism of the polling unit according to the target response speed. In the case where it is determined that the target response speed is less than or equal to the preset response speed, accurately execute the lightweight polling operation to obtain the above target data, which is beneficial to reducing the latency in the process of obtaining the target data, thereby improving the determination efficiency of the target priorities corresponding to multiple target tasks and improving the operation efficiency of the above ERP control system.

[0032] The determination module 120 is configured to determine the target priorities corresponding to multiple target tasks according to the target data.

[0033] It should be noted that the above target data can correspond to a target event.

[0034] Exemplarily, the above determination module can determine the target priorities corresponding to multiple target tasks according to the target event.

[0035] In some feasible implementation manners, the above determination module includes: a preprocessing unit, configured to perform a preprocessing operation on the target data in the case where it is determined that the format difference between the target data is greater than a preset format difference threshold, so that the format difference is less than or equal to the preset format difference threshold.

[0036] Exemplarily, the above preprocessing unit can obtain the above target data by subscribing to the database binlog log.

[0037] It should be noted that the above-mentioned preset format difference threshold can be dynamically set according to the lower limit of the processing speed of the target user for the system and / or the upper limit of the resource consumption of the system operation. Among them, the above-mentioned preset format difference threshold is positively correlated with the above-mentioned lower limit of the processing speed, that is, the higher the above-mentioned lower limit of the processing speed, the smaller the above-mentioned preset format difference threshold. The above-mentioned preset format difference threshold is positively correlated with the above-mentioned upper limit of the resource consumption, that is, the larger the above-mentioned upper limit of the resource consumption, the larger the above-mentioned preset format difference threshold.

[0038] Exemplarily, in the above-mentioned preprocessing unit, the format differences between the target data can be determined according to the format, structure, field naming method, date format, boolean value, currency unit, price unit, paging mechanism, and / or error value, etc., corresponding to the target data.

[0039] Exemplarily, in the case where the preprocessing unit determines that the format difference between the target data is greater than the preset format difference threshold, a preprocessing operation can be performed on the target data to make the format difference of the target data less than or equal to the preset format difference threshold. Among them, the above-mentioned preprocessing operation can include: performing a format conversion operation on the above-mentioned target data, performing a renaming operation on the corresponding fields of the above-mentioned target data, performing a format conversion operation on the date format corresponding to the above-mentioned target data, and / or performing a format conversion operation on the boolean value, etc.

[0040] Specifically, in the case where some of the target data is transmitted based on the xml format and some of the target data is transmitted based on the json format, a format conversion operation is performed on the above-mentioned target data to make the transmission format difference between the target data less than or equal to the preset transmission format difference threshold.

[0041] Specifically, in the case where some of the target data is named based on underscores and some of the target data is named in camel case, a renaming operation is performed on the corresponding fields of the above-mentioned target data to make the naming format difference between the target data less than or equal to the preset naming format difference threshold. Among them, the above-mentioned underscore naming can include: order_no, etc.; the above-mentioned camel case naming can include: orderNo, etc.

[0042] Specifically, in the case where the date format of some of the target data is the ISO-8601 format and the date format of some of the data is the timestamp format, a format conversion operation is performed on the date format corresponding to the above-mentioned target data to make the date format difference between the target data less than or equal to the preset date format difference threshold. Among them, the corresponding date format of the above-mentioned ISO-8601 format can be: 2024-11-11T10:30:25Z; the corresponding date format of the above-mentioned timestamp format can be: 1731292225.

[0043] Specifically, in the case where the boolean values of some target data are in the format of true / false, while the boolean values of some target data are in the format of 0 / 1, format conversion operations are performed on the boolean values, etc.

[0044] It should be noted that preprocessing operations can be performed on the target data based on Table 1 below, so that the format differences of the target data are less than or equal to the preset format difference threshold.

[0045] Table 1:

[0046] Exemplarily, as shown in Table 1 above, the business classification field can be set to biz_type, the type is set to String(20), where the order field is set to order. The event type field can be set to event_type, the type is set to String(20), where the creation field is set to create, the change field is set to modify, and the deletion field is set to remove. The event generation time field can be set to priority, the type is set to String(32), and the format is in the ISO8601 format. The unique document number field can be set to code, the type is String(64), and all are required to be unified. The self-incrementing serial number field of the document dimension can be set to seq, the type is set to Int. Specifically, according to the self-incrementing serial number of the document dimension, starting from 1, whenever the document changes, the number increases, and this field can be automatically verified. If it is not continuous, it indicates that data is missing. The data content field can be set to payload, the type is set to String, where the order number is uniformly named orderNo, and the time uniformly uses the ISO 8601 format, etc. Before performing the preprocessing operation on the target data, the original data field of Delle can be set to source, the type is set to String. The verification value field can be set to sign, the type is set to String(32). Among them, for the corresponding content of items 1-7, a signature can be generated based on the MD5 algorithm for performing a complete verification on the target data, and this field can be automatically verified. In the case where the MD5 is inconsistent, it indicates that the data is incomplete.

[0047] It should be noted that the above preprocessing operations can also include: data parsing operations, data parsing operations, etc.

[0048] Among them, the target data that has completed the above preprocessing operations can be uniformly stored in the JSON format.

[0049] It should be noted that in the case where the above target data corresponds to a target event, the above preprocessing unit is used to generate a standard target event. The correspondence between the above target data and the target event can be used to drive the above ERP control system through events, so as to improve the synchronization speed of the target data, and further improve the response speed of the ERP control system.

[0050] Thus, the above determination module can accurately perform preprocessing operations on the target data by setting the preprocessing unit when it is determined that the format difference between the target data is greater than the preset format difference threshold, so that the format difference is less than or equal to the preset format difference threshold, providing a data basis for improving the determination efficiency of the target priorities corresponding to multiple target tasks, thereby improving the execution speed of the system for executing multiple target tasks and reducing the resource consumption of the system.

[0051] In some feasible embodiments, the above determination module further includes: a determination unit for determining the target priority according to a preset evaluation factor, where the preset evaluation factor includes: a customer value evaluation factor, an order amount evaluation factor, a transaction time evaluation factor, and / or a rule evaluation factor.

[0052] Exemplarily, the above target priority is positively correlated with the customer value evaluation factor, where the larger the customer value evaluation factor, the higher the target priority. The above customer value evaluation factor can be determined according to the value of the customer and / or the loyalty.

[0053] Exemplarily, the above target priority is positively correlated with the order amount evaluation factor, where the larger the order amount evaluation factor, the higher the target priority. The above order amount evaluation factor can be determined according to the amount of the order.

[0054] Exemplarily, the above target priority is negatively correlated with the transaction time evaluation factor, where the smaller the transaction time evaluation factor, the higher the target priority. The above transaction time evaluation factor can be determined according to the delivery time window.

[0055] Exemplarily, the above rule evaluation factor may include: a timeliness rule. The above timeliness rule can be determined according to the timeout duration. Among them, the above target priority is positively correlated with the timeout duration, that is, the longer the timeout duration, the higher the target priority.

[0056] It should be noted that the above target priority can be set to "priority" and the type is set to "Int", where the value range of the target priority can be set to positive integers between 1 and N, and the larger the numerical value, the higher the corresponding target priority. Among them, the value range of the above N can be configured according to business requirements and will not be specifically limited here.

[0057] Thus, the above determination unit can accurately determine the target priorities corresponding to multiple target tasks based on the above customer value evaluation factor, order amount evaluation factor, transaction time evaluation factor, and / or rule evaluation factor, based on the customer value dimension, order amount dimension, transaction time dimension, and / or rule dimension, so that the execution module can accurately execute multiple target tasks in order according to the target priorities, and preferentially execute the target tasks with higher customer value, higher order amount, earlier transaction time, and / or stricter corresponding rules.

[0058] In some feasible implementation manners, the above determination unit includes: a first determination component, configured to determine an initial priority according to a preset evaluation factor and the weight corresponding to the preset evaluation factor.

[0059] Exemplarily, the above initial priority is equal to the sum of the products of each preset evaluation factor and the corresponding weight. Among them, the value range of the above initial priority can be greater than 0 and less than 1. The determination accuracy of the above initial priority can be 0.1.

[0060] It should be noted that the weights corresponding to the above preset evaluation factors can be specifically set according to the actual usage scenario. Among them, the sum of the weights corresponding to the above preset evaluation factors is 100%.

[0061] Exemplarily, the corresponding weight of the above customer value evaluation factor can be set to 20%; the corresponding weight of the above order amount evaluation factor can be set to 20%; the corresponding weight of the above transaction time evaluation factor can be set to 10%; the corresponding weight of the above rule evaluation factor can be set to 50%.

[0062] In some feasible implementation manners, the above determination unit further includes: a second determination component, configured to determine the target priority according to the initial priority and the objective function; where the objective function includes: (1) Among them, is the target priority, is the initial priority, is a preset parameter.

[0063] It should be noted that since the initial priority is a decimal, it is necessary to perform a conversion operation on the above initial priority so that the above initial priority is a positive integer greater than 0 and less than or equal to . Among them, the preset parameter can be set by itself according to the actual situation. The above is used to represent the rounding operation on the output result of the target priority to ensure that the target priority The output result is a positive integer. The above-mentioned target priority , and / or, the above-mentioned initial priority can be stored in the corresponding "priority" field for convenient subsequent retrieval.

[0064] Thus, the above-mentioned determination unit can accurately determine the initial priority according to the preset evaluation factor and the weight corresponding to the preset evaluation factor by configuring the first determination component; by configuring the second determination component, it can accurately determine the target priorities corresponding to multiple target tasks according to the initial priority and the objective function, so that the execution module can accurately execute multiple target tasks in order according to the target priorities.

[0065] In some feasible implementation manners, the ERP control system further includes: an execution module 130, configured to execute multiple target tasks according to the target priorities.

[0066] In some feasible implementation manners, the above-mentioned execution module further includes: an execution unit, configured to perform a target operation on target data according to the target priority to generate a target data stream, so as to implement executing multiple target tasks based on the target data stream.

[0067] Exemplarily, the above-mentioned execution unit can be used to divide the target data into DataStream data streams corresponding to the target priorities according to the target priorities, so as to implement executing the above-mentioned target data streams correspondingly based on the order of the above-mentioned target priorities and executing multiple target tasks in order.

[0068] It should be noted that in the case where the feedback result of the target data stream corresponding to the highest priority is empty, the target data stream corresponding to the second highest priority is executed until all data streams are executed. During the above-mentioned execution process, if a new target data stream is generated, the above-mentioned target data streams to be executed are sequentially executed according to the target priority order of the currently to-be-executed target data stream.

[0069] In some feasible implementation manners, the above-mentioned execution module includes: a verification unit, configured to perform a target verification operation on the target data stream.

[0070] Exemplarily, a target verification operation can be performed on the target fields in the target data stream to determine the integrity and / or consistency of the target data stream. Among them, the above-mentioned target fields may include: seq field, and / or sign field, etc.

[0071] It should be noted that the continuity of the seq field can be verified according to the self-increasing serial number of the document dimension. In the case where the seq field is discontinuous, it is determined that the corresponding data of the target data stream is missing due to different transmission time sequences, and the waiting operation is continued to enable the target verification operation to be continued after determining that the above-mentioned corresponding data arrives.

[0072] It should be noted that for all transmission data in the same time series, corresponding signature values can be generated based on the MD5 digest algorithm. In the case where the signs are inconsistent, it is determined that the data corresponding to the target data stream is incomplete, and the above-mentioned target data stream is discarded to avoid system errors caused by incomplete data corresponding to the target data stream.

[0073] It should be noted that the verification operation can be uniformly performed on the target data stream when the absolute value of the difference between the data volume of the target data stream and the preset data volume is less than or equal to the preset threshold, so as to improve the verification efficiency.

[0074] Exemplarily, the target data stream can be extracted according to the target priority in sequence. Among them, when the target data stream corresponding to the highest target priority is empty, the target data stream corresponding to the second highest priority is extracted until the absolute value of the difference between the data volume of the target data stream and the preset data volume is less than or equal to the preset threshold.

[0075] In some feasible embodiments, the above-mentioned execution module further includes: a generation unit for generating a corresponding plurality of target tasks according to the target data stream.

[0076] Exemplarily, the above-mentioned target data stream can be sent to the above-mentioned generation unit in the form of MQ messages to generate a corresponding plurality of target tasks according to the above-mentioned target data stream. Among them, the above-mentioned target tasks can correspond to target events, and the above-mentioned target tasks can include: order creation, order change, order deletion, order delivery, etc., which can be set according to the actual usage scenario.

[0077] In some feasible embodiments, the above-mentioned execution module further includes: a matching unit for matching target tasks to corresponding target queues according to the target data stream.

[0078] Exemplarily, the above-mentioned matching unit can match target tasks to corresponding target queues based on the target priority corresponding to the target data stream according to the above-mentioned target data stream.

[0079] Specifically, N target queues with different topics can be created according to different target priorities. For example: target queues of Topic-1, Topic-2~Topic-N can be created, where the value of the above-mentioned N can correspond to the target priority.

[0080] Specifically, based on the value of the "priority" field in the target data stream, the target tasks can be matched to the corresponding Topic target queue to complete the distribution and matching of the target tasks.

[0081] Specifically, the relevant data of the above-mentioned target task can be stored in the target message queue MQ.

[0082] It should be noted that the above-mentioned target message queue MQ serves as the storage medium for the target task to improve the event accumulation capacity, avoid system crashes caused by excessive data volume, and enable the system to operate stably in usage scenarios with high data throughput requirements.

[0083] It should be noted that the above-mentioned verification unit can also be used to perform verification operations on the target tasks in the target queue.

[0084] Exemplarily, the verification operation can be uniformly performed on the target tasks when the absolute value of the difference between the quantity of the target tasks and the preset task quantity is less than or equal to the preset threshold, so as to improve the verification efficiency.

[0085] Exemplarily, the target tasks in the target queue can be extracted in sequence according to the target priority. Among them, when the target tasks in the queue corresponding to the highest target priority are empty, the target tasks in the queue corresponding to the second highest priority are extracted until the absolute value of the difference between the quantity of the target tasks and the preset task quantity is less than or equal to the preset threshold. Among them, the quantity of the above-mentioned target tasks can be determined by subscribing to "Topic".

[0086] Thus, by configuring the execution unit, verification unit, generation unit, and matching unit, the above-mentioned execution module can accurately perform target operations on target data according to the target priority, accurately generate target data streams in sequence, so as to preferentially execute target tasks with higher priorities based on the above-mentioned target data streams; by accurately performing data verification operations on target data, the integrity of target data can be guaranteed, thereby improving the accuracy and efficiency of generating target tasks based on the verified target data streams, and further improving the efficiency of matching target tasks to targets, so as to improve the processing efficiency of target tasks.

[0087] In some feasible implementation manners, the above-mentioned execution module further includes: a regulation unit, which is used to regulate the task input rate of the target queue according to the relevant information of the target queue, so that the absolute value of the difference between the task input rate and the target task input rate is less than or equal to the preset threshold, where the relevant information includes: the current occupied capacity of the target queue and the maximum capacity of the target queue.

[0088] It should be noted that the above preset threshold can be dynamically set according to the lower limit of the processing speed of the target user for the system and / or the upper limit of the resource consumption during the operation of the system. Among them, the above preset threshold is positively correlated with the lower limit of the processing speed of the target user for the system, that is, the smaller the lower limit of the processing speed of the target user for the system, the smaller the above preset threshold. The above preset threshold is negatively correlated with the upper limit of the resource consumption of the target user for the system operation, that is, the higher the upper limit of the resource consumption of the target user for the system operation, the smaller the above preset threshold.

[0089] In some feasible embodiments, the above-mentioned regulation unit includes: a first calculation component, configured to determine the load rate of the target queue according to relevant information, where the load rate is equal to the ratio of the current occupied capacity to the maximum capacity.

[0090] Exemplarily, the above-mentioned current occupied capacity is the current queue size of the target queue, that is, the current number of target tasks of the target queue. The above-mentioned maximum capacity is the maximum capacity of the target queue, that is, the maximum number of target tasks that the target queue can accommodate.

[0091] Specifically, when the above-mentioned current occupied capacity is 5 and the maximum capacity is 20, the load rate of the above-mentioned target queue is .

[0092] It should be noted that the higher the load rate of the current target queue, the fewer target tasks that the above-mentioned target queue can receive, that is, the larger the ratio of the current occupied capacity to the maximum capacity, the fewer target tasks that the target queue can receive.

[0093] In some feasible embodiments, the above-mentioned regulation unit further includes: a second calculation component, configured to determine the target processing efficiency ratio according to the actual processing rate and the expected processing rate of the target queue, where the target processing efficiency ratio is the ratio of the actual processing rate to the expected processing rate.

[0094] Exemplarily, the above-mentioned expected processing rate can be the number of tasks processed per second by the above-mentioned system expected by the target user.

[0095] Exemplarily, the above-mentioned actual processing rate and expected processing rate can retain only integer digits.

[0096] Specifically, when the actual processing rate is 35 and the expected processing rate is 50, the above-mentioned target processing efficiency ratio is .

[0097] It should be noted that the above-mentioned target processing efficiency ratio is used to represent the gap between the expected processing rate and the actual processing rate of the system. Among them, the smaller the above-mentioned target processing efficiency ratio, the slower the throughput efficiency of the target queue for the target task, and it is necessary to adjust the task input rate so that the absolute value of the difference between the task input rate and the target task input rate is less than or equal to the above-mentioned preset threshold.

[0098] In some feasible embodiments, the above-mentioned regulation unit further includes: a third calculation component, configured to determine the target task input rate according to the load rate, the target processing efficiency ratio, and the expected processing rate.

[0099] Exemplarily, the above-mentioned target task input rate can be determined according to the following formula: , exemplarily, when the load rate is , the above-mentioned target processing efficiency ratio is , and the above-mentioned expected processing efficiency is 50, then the above-mentioned target task input rate is 26 per second.

[0100] Thus, the above-mentioned regulation unit can accurately determine the target task input rate by configuring the first calculation component, the second calculation component, and the third calculation component, so as to dynamically and accurately regulate the task input rate of the target queue according to the relevant information of the target queue, make the absolute value of the difference between the task input rate and the target task input rate less than or equal to the preset threshold, and avoid the target queue corresponding hardware from crashing or responding slowly due to too many target tasks, thereby improving the regulation accuracy of the target queue task input rate and improving the stability of the ERP control system of the present application.

[0101] Based on this, the ERP control system provided by the present application includes: an acquisition module, configured to acquire target data based on multiple target protocols, which is beneficial to improving the applicability and compatibility of the ERP control system, meeting the omnichannel operation requirements of the ERP system, and improving the access ability of target data; a determination module, configured to determine the target priorities corresponding to multiple target tasks according to the target data, which is beneficial to improving the determination accuracy and determination efficiency of the priorities of multiple target tasks; an execution module, configured to execute multiple target tasks according to the target priorities, which is beneficial to improving the orderliness of the ERP control system in executing multiple tasks, thereby improving the applicability and accuracy of the ERP control system in executing multi-level tasks, so as to improve the response accuracy of the ERP control system.

[0102] In the second aspect of the embodiments of the present application, an ERP control method is proposed. Figure 2 It is a schematic flowchart of an ERP control method 200 provided by an embodiment of the present application. As Figure 2 shown, the method 200 includes: S210, acquiring target data based on multiple target protocols; S220. Determine the target priorities corresponding to multiple target tasks according to the target data; S230. Execute multiple target tasks according to the target priorities Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working process of the described method can refer to the corresponding process in the foregoing system embodiment, and will not be elaborated herein.

[0103] Figure 3 FIG. is a schematic structural diagram of an electronic device 300 provided by an embodiment of the present application. As Figure 3 shown, the electronic device 300 includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage section 308 into the random access memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the terminal device or server are also stored. The CPU 301, ROM 302, and RAM 303 are connected to each other via a bus 304. The input / output (I / O) interface 305 is also connected to the bus 304.

[0104] The following components are connected to the I / O interface 305: an input section 306 including a keyboard, a mouse, etc.; an output section 307 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc. and a speaker, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. The drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed, so that a computer program read from it can be installed into the storage section 308 as needed.

[0105] Specifically, according to the embodiments of the present application, the above method flow steps can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a machine-readable medium, and the computer program includes program codes for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication section 309, and / or installed from the removable medium 311. When the computer program is executed by the central processing unit (CPU) 301, the above functions defined in the system of the present application are executed.

[0106] It should be noted that the computer-readable medium described in this application can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. 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 of the above. More specific examples of a computer-readable storage medium can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this application, a computer-readable storage medium can be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution system, apparatus, or device. And in this application, a computer-readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, in which computer-readable program code is carried. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, and this computer-readable medium can send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. The program code contained on a computer-readable medium can be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0107] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram can represent a module, a program segment, or a part of code, and the foregoing module, program segment, or part of code contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks can occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks shown can actually be executed substantially in parallel, and they can sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and the combination of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0108] The units or modules involved in the embodiments of the present application can be implemented in software or in hardware. The described units or modules can also be provided in a processor. Among them, the names of these units or modules do not, in some cases, constitute a limitation on the units or modules themselves.

[0109] The above description is only a preferred embodiment of the present application and an explanation of the applied technical principles. Those skilled in the art should understand that the scope of the application involved in the present application is not limited to the technical solutions formed by the specific combination of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the foregoing application concept. For example, the technical solutions formed by mutually replacing the above features with the technical features (but not limited to) having similar functions applied in the present application.

Claims

1. An ERP control system, characterized in that: include: An acquisition module, used to acquire target data based on multiple target protocols; A determination module, used to determine target priorities corresponding to a plurality of target tasks according to the target data; An execution module is used to execute the multiple target tasks according to the target priority.

2. The ERP control system according to claim 1, characterized in that: The acquisition module comprises: The polling unit is used to obtain the target data based on a target polling operation when it is determined that the target response speed is less than or equal to a preset response speed, wherein the target polling operation includes: a lightweight polling operation.

3. The ERP control system according to claim 1, characterized in that: The determination module comprises: The preprocessing unit is used to perform a preprocessing operation on the target data when it is determined that the format difference between the target data is greater than a preset format difference threshold, so as to make the format difference less than or equal to the preset format difference threshold.

4. The ERP control system according to any one of claims 1 to 3, characterized in that: The determination module also includes: A determination unit, configured to determine the target priority according to a preset evaluation factor; The preset evaluation factors include: customer value evaluation factor, order amount evaluation factor, transaction time evaluation factor, and / or rule evaluation factor.

5. The ERP control system according to claim 4, characterized in that: The determining unit comprises: A first determining component, configured to determine an initial priority according to the preset evaluation factor and the weight corresponding to the preset evaluation factor; The second determining component is used to determine a target priority according to the initial priority and the target function.

6. The ERP control system according to claim 5, characterized in that: The objective function includes: ,in, is the target priority, is the initial priority, are preset parameters.

7. The ERP control system according to claim 6, characterized in that: The execution module includes: an execution unit, configured to execute a target operation on the target data according to the target priority to generate a target data stream; A verification unit, configured to perform a target verification operation on the target data stream; A generating unit, used for generating a plurality of corresponding target tasks according to the verified target data stream; A matching unit is used to match the target task to a corresponding target queue according to the target data stream.

8. The ERP control system according to claim 7, characterized in that: The execution module also includes: A control unit is used to control the task input rate of the target queue according to the relevant information of the target queue so that the absolute value of the difference between the task input rate and the target task input rate is less than or equal to a preset threshold, wherein the relevant information includes: the current occupied capacity of the target queue and the maximum capacity of the target queue.

9. The ERP control system according to claim 8, characterized in that: The control unit comprises: A first calculation component, configured to determine a load rate of a target queue according to the relevant information, wherein the load rate is equal to a ratio of the current occupied capacity to the maximum capacity; a second calculation component, configured to determine a target processing efficiency ratio according to an actual processing rate and an expected processing rate of the target queue, wherein the target processing efficiency ratio is a ratio of the actual processing rate to the expected processing rate; The third calculation component is used to determine the target task input rate according to the load rate, the target processing efficiency ratio and the expected processing rate.

10. An ERP control method, characterized in that: include: Obtain target data based on multiple target protocols; Determining target priorities corresponding to a plurality of target tasks according to the target data; According to the target priorities, the multiple target tasks are executed.

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