Cache refreshing method and device based on workflow, storage medium and electronic equipment

Abstract

The invention provides a cache refreshing method and device based on workflow, a storage medium and electronic equipment, and the method comprises the steps: determining whether a data change request is received, the data change request is a request for updating business data, and the data change request comprises update data of the business data; under the condition that a data change request is received, the data change request is input into the workflow for multi-level process node approval, a plurality of approval results are obtained, the multi-level process nodes are process nodes with different priorities, the approval results are in one-to-one correspondence with the levels of the process nodes, and the approval results are approved or not approved; and determining to refresh the cache according to the update data of the business data under the condition that all the approval results are approved, and determining to keep the current cache unchanged under the condition that at least one approval result is approved not. According to the method, the reliability of cache updating operation and the data real-time performance in a distributed environment can be effectively improved.

Description

Technical Field

[0001] This application relates to the field of computer network technology, and more specifically, to a workflow-based cache refresh method, a workflow-based cache refresh device, a computer-readable storage medium, and an electronic device. Background Technology

[0002] Traditional cache refresh methods are based on data updates or preset time refresh strategies, which suffer from poor data consistency, resource waste, high response latency, and poor adaptability to complex processes. Existing cache refresh methods refresh the cache when data is updated, which can lead to excessive refreshes in non-use scenarios due to numerous modification scenarios. Refreshing based on preset time cannot be linked to events, resulting in insufficient real-time performance and potential inconsistencies between the retrieved data and the actual data. Summary of the Invention

[0003] The main objective of this application is to provide a workflow-based cache refresh method, a workflow-based cache refresh device, a computer-readable storage medium, and an electronic device, so as to at least solve the problems of poor data consistency, resource waste, high response latency, and poor adaptability to complex processes in traditional cache refresh methods.

[0004] To achieve the above objectives, according to one aspect of this application, a workflow-based cache refresh method is provided, comprising: determining whether a data change request has been received, wherein the data change request is a request to update business data, and the data change request includes updated data of the business data; if the data change request is received, inputting the data change request into a workflow for multi-level process node approval to obtain multiple approval results, wherein the multi-level process nodes are process nodes with different priorities, and the approval results correspond one-to-one with the level of the process nodes, wherein the approval result is approval passed or approval failed; if all the approval results are approval passed, determining to refresh the cache according to the updated data of the business data; if at least one of the approval results is approval failed, determining to keep the current cache unchanged.

[0005] Optionally, the data change request is input into the workflow for multi-level process node approval to obtain multiple approval results, including: determining the priority of each level of the process node; inputting the data change request into the multi-level process nodes in order of priority from low to high for approval to obtain multiple approval results.

[0006] Optionally, the data change request is input into the workflow for multi-level process node approval to obtain multiple approval results, including: when there are multiple process nodes at the current level, the data change request is input into all process nodes at the current level in parallel for approval to obtain multiple approval sub-results, and the approval sub-results correspond one-to-one with the process nodes at the current level; when all the approval sub-results are approved, the approval result is determined to be approved; when at least one of the approval sub-results is not approved, the approval result is determined to be not approved.

[0007] Optionally, before inputting the data change request into the workflow for multi-level process node approval, the method further includes: determining the process engine, wherein the components of the process engine include: a process definition component, a process parsing component, a process driving component, and a data persistence component; the functions of the process engine include: process flowchart parsing of business process modeling symbols, process orchestration, and flow registration; and the data of the process engine includes: process definition instances, process instances, activity instances, task instances, participant instances, and parameter instances; and calling the software development kit of the process engine to establish and run the workflow.

[0008] Optionally, the workflow is established and run by calling the software development kit of the process engine, including: establishing the workflow based on the process definition component, the process parsing component, the flowchart parsing function of the business process modeling symbols, and the process orchestration function of the process engine; and controlling the operation of the workflow based on the process driving component, the data persistence component, the flow level function, the process definition instance, the process instance, the activity instance, the task instance, the participant instance, and the parameter instance of the process engine.

[0009] Optionally, after determining to refresh the cache based on the updated data of the business data, the method further includes: generating a data query service based on the updated data of the business data; after the data query service detects the updated data of the business data, sending data change information to a configuration center, so that the configuration center broadcasts the data change information to all application nodes, wherein the application nodes are nodes that execute business using the business data; and when an application node receives the data change information, storing the updated data of the business data in the data query service into the application node.

[0010] Optionally, the data change request is input into the workflow for multi-level process node approval, resulting in multiple approval results, including: inputting the data change request into the workflow for multi-level process node approval, determining whether the updated business data meets preset conditions; if the updated business data is within the preset parameter threshold range, within the business standard parameter range, and within the permission parameter range, determining that the updated business data meets the preset conditions, and the approval result is approval passed; if the updated business data meets at least one of the following conditions: the updated business data is not within the preset parameter threshold range, the updated business data is not within the business standard parameter range, or the updated business data is not within the permission parameter range, determining that the updated business data does not meet the preset conditions, and the approval result is approval failed.

[0011] According to another aspect of this application, a workflow-based cache refresh device is provided, comprising: a first determining unit, configured to determine whether a data change request has been received, the data change request being a request to update business data, the data change request including updated data of the business data; an approval unit, configured to, upon receiving the data change request, input the data change request into a workflow for multi-level process node approval, obtaining multiple approval results, wherein the multi-level process nodes are process nodes with different priorities, the approval results corresponding one-to-one with the level of the process nodes, the approval result being either approval passed or approval failed; and a second determining unit, configured to, if all the approval results are approval passed, determine to refresh the cache according to the updated data of the business data, and if at least one of the approval results is approval failed, determine to keep the current cache unchanged.

[0012] According to another aspect of this application, a computer-readable storage medium is provided, the computer-readable storage medium including a stored program, wherein, when the program is executed, it controls the device where the computer-readable storage medium is located to perform any of the described workflow-based cache refresh methods.

[0013] According to another aspect of this application, an electronic device is provided, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including methods for performing any of the workflow-based cache refresh methods described above.

[0014] Applying the technical solution of this application, the aforementioned workflow-based cache refresh method first determines whether a data change request has been received. The data change request is a request to update business data, including the updated business data. If a data change request is received, it is input into the workflow for multi-level process node approval, resulting in multiple approval results. These multi-level process nodes represent process nodes with different priorities, and the approval results correspond one-to-one with the level of the process node, either approved or rejected. If all approval results are approved, the cache is refreshed based on the updated business data. If at least one approval result is rejected, the current cache is maintained. This method effectively reduces the cache refresh frequency, decreases latency of critical business data, saves system resources, and improves the reliability and real-time performance of cache update operations in a distributed environment. It solves the problems of poor data consistency, resource waste, high response latency, and poor adaptability to complex processes inherent in traditional cache refresh methods. Attached Figure Description

[0015] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0016] Figure 1 A hardware structure block diagram of a mobile terminal performing a workflow-based cache refresh method is shown in an embodiment of this application.

[0017] Figure 2 A flowchart illustrating a workflow-based cache refresh method according to an embodiment of this application is shown.

[0018] Figure 3 A cache refresh flowchart of a workflow-based cache refresh method provided according to an embodiment of this application is shown;

[0019] Figure 4 A structural block diagram of a workflow-based cache refresh apparatus according to an embodiment of this application is shown;

[0020] The above figures include the following reference numerals:

[0021] 102. Processor; 104. Memory; 106. Transmission device; 108. Input / output device. Detailed Implementation

[0022] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0023] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0024] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0025] For ease of description, the following explains some of the nouns or terms used in the embodiments of this application:

[0026] Workflow: A workflow is a series of interconnected, automated business activities or tasks that belong to computer-supported collaborative work.

[0027] Caching is a storage mechanism designed to provide high-speed access to saved data or computation results. By storing data in a temporary storage location, this data can be quickly retrieved from the cache when needed again.

[0028] As described in the background section, traditional cache refresh methods are based on data updates or preset time refresh strategies, which suffer from poor data consistency, resource waste, high response latency, and poor adaptability to complex processes. They fail to consider refreshing based on actual business needs and events. Unlike traditional data-based or preset time refresh strategies, this method supports refreshing based on approval flow nodes. When the approval flow progresses to a preset node (e.g., approval passed), a cache update operation is automatically triggered, thereby ensuring fast cache refresh speed.

[0029] The existing cache refresh methods have the following shortcomings: 1) When data is updated, the cache is refreshed. There are many modification scenarios, and there are too many refreshes in non-use scenarios; 2) The refresh method based on preset time cannot be linked with events, resulting in insufficient real-time performance and the acquisition of data may be inconsistent with the actual data.

[0030] To address the problems of poor data consistency, resource waste, high response latency, and poor adaptability to complex processes in traditional cache refresh methods, embodiments of this application provide a workflow-based cache refresh method, a workflow-based cache refresh device, a computer-readable storage medium, and an electronic device.

[0031] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0032] The methods and embodiments provided in this application can be executed on a mobile terminal, computer terminal, or similar computing device. Taking running on a mobile terminal as an example, Figure 1 This is a hardware structure block diagram of a mobile terminal using a workflow-based cache refresh method according to an embodiment of the present invention. Figure 1 As shown, a mobile terminal may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data are also shown. The mobile terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the mobile terminal described above. For example, the mobile terminal may also include components that are more... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0033] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the workflow-based cache refresh method in this embodiment of the invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thereby implementing the above-described method. The memory 104 may include high-speed random access memory and non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the mobile terminal via a network. Examples of the aforementioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof. The transmission device 106 is used to receive or send data via a network. Specific examples of the aforementioned networks may include wireless networks provided by the mobile terminal's communication provider. In one example, the transmission device 106 includes a network interface controller (NIC), which can be connected to other network devices via a base station to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0034] This embodiment provides a workflow-based cache refresh method that runs on a mobile terminal, computer terminal, or similar computing device. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0035] Figure 2 This is a flowchart of a workflow-based cache refresh method according to an embodiment of this application. For example... Figure 2 As shown, the method includes the following steps:

[0036] Step S201: Determine whether a data change request has been received. The data change request is a request to update business data, and the data change request includes the updated data of the business data.

[0037] In a distributed system, once a business parameter is detected to need modification—that is, when a user or internal system issues a parameter update request—the validity of this request is first verified. For example, in a scenario involving updating financial product parameters, the received update request might contain information such as the product ID, parameter name, and its new value. This stage does not trigger any backend data changes; it is merely a preliminary capture and confirmation of the change request.

[0038] This confirmation step ensures that only legitimate and necessary data change requests proceed to the subsequent approval process, avoiding unnecessary consumption of system resources and potential data consistency issues.

[0039] Step S202: Upon receiving the aforementioned data change request, the data change request is input into the workflow for multi-level process node approval, resulting in multiple approval results. The multi-level process nodes are process nodes with different priorities. The approval results correspond one-to-one with the level of the process nodes. The approval results are either approved or not approved.

[0040] Once a change request is confirmed as valid, it is submitted to the workflow engine, which automatically assigns it to approvers at various levels according to a predefined process. For example, for a parameter change of high importance, the process might be designed to first pass through the junior approver at node A, and then through the senior approver at node B. Each approval node will decide whether to approve the change request based on the reasonableness, compliance, and scope of impact of the change. If approved, the process continues to the next node; if not approved, the process terminates.

[0041] This step implements a tiered approval mechanism for change requests, which can improve approval efficiency and reduce system risks caused by erroneous decisions at a single approval point while ensuring the accuracy of changes.

[0042] Step S203: If all the above approval results are "approved", determine to refresh the cache based on the updated data of the above business data; if at least one of the above approval results is "approved but not approved", determine to keep the current cache unchanged.

[0043] Specifically, a cache refresh action is only triggered when all approval levels pass. For example, if both approval nodes A and B agree to the change, the cache refresh operation will be performed to ensure that all services relying on the cache use the latest data. If either node refuses the change, the process will not proceed to the cache refresh step, keeping the existing cached data unchanged to maintain system stability and data consistency.

[0044] This step effectively reduces unnecessary cache refreshes by tightly linking cache refresh with approval results, significantly improves the accuracy of cached data and the utilization of system resources, and also enhances the real-time performance and reliability of data in a distributed environment.

[0045] The workflow-based cache refresh method described in this application first determines whether a data change request has been received. The data change request is a request to update business data, including the updated business data. If a data change request is received, it is input into the workflow for multi-level process node approval, resulting in multiple approval results. These multi-level process nodes represent process nodes with different priorities, and the approval results correspond one-to-one with the level of the process node, either approved or rejected. If all approval results are approved, the cache is refreshed based on the updated business data. If at least one approval result is rejected, the current cache is maintained. This method effectively reduces the cache refresh frequency, decreases latency of critical business data, saves system resources, and improves the reliability and real-time performance of cache update operations in a distributed environment. It solves the problems of poor data consistency, resource waste, high response latency, and poor adaptability to complex processes inherent in traditional cache refresh methods.

[0046] In this embodiment, the workflow-based cache refresh method can precisely control the timing of cache updates. By submitting a data change request containing updated business data to a workflow for multi-level approval after receiving the request, and determining whether to refresh the cache based on the approval results, this invention utilizes approval flow node events to precisely respond to cache refresh needs. If all approval nodes pass, the updated business data is confirmed and the cache is refreshed; if any level of approval fails, the current cache state is maintained, avoiding unnecessary cache updates. This method overcomes the blindness of traditional cache refresh strategies in responding to data changes, reduces the number of invalid cache refreshes caused by incomplete or failed approval processes, thereby reducing the waste of system resources, minimizing the impact of cache refresh on system performance, and effectively improving the real-time performance and accuracy of data updates. Therefore, the technical solution of this invention achieves efficient and reliable cache updates in a distributed environment, solves the problem of data consistency between the cache and the database, optimizes the cache refresh frequency, and improves the overall stability and response speed of the system.

[0047] In some embodiments, the aforementioned data change request is input into the workflow for multi-level process node approval, resulting in multiple approval results, including the following steps:

[0048] Step S301: Determine the priority of each of the above-mentioned process nodes;

[0049] Step S302: The data change requests are entered into the multi-level process nodes for approval in order of priority from low to high, resulting in multiple approval results.

[0050] In a distributed, unitized architecture, data for services is preferentially retrieved from the cache. Therefore, after data modification, the cached data needs to be refreshed to ensure that other services obtain the correct data. However, traditional cache refresh methods are based on data updates or preset time refresh strategies, resulting in poor data consistency, resource waste, high response latency, and poor adaptability to complex processes. They do not consider refreshing based on actual business needs and events. For systems that update data based on approval workflows, it is easier to control the cache refresh frequency. The specific implementation scheme needs to consider how to refresh cached data at the correct time and the cache refresh strategy used to ensure that the cache is refreshed correctly and that other applications can use the new cached data correctly.

[0051] In this embodiment, data change requests are incorporated into a workflow for hierarchical approval, encompassing multiple nodes with varying priorities. Specifically, a priority order for each approval node is first defined. Then, based on this order, the approval process for data change requests progresses upwards from the lowest priority node, with each node outputting its approval result according to its established approval criteria. This hierarchical approval mechanism ensures the rigor and transparency of the change process, with each step carefully considered to avoid the impact of errors at a single decision point. When a data change request passes approval from all nodes—that is, reaches the highest priority node and is approved—the parameter database is updated and the cache is refreshed, thus guaranteeing the validity of the final parameter change and data consistency. Compared to indiscriminate or fixed-time refresh strategies, this embodiment significantly reduces the frequency of cache refreshes, minimizing unnecessary system load. Simultaneously, by precisely controlling refresh nodes, it achieves a high degree of matching between data updates and business needs, improving the efficiency and reliability of data management in the distributed system. The application of differentiated refresh strategies in a multi-level approval process allows for more flexible responses to various complex business scenarios, ensuring the real-time accuracy of cached data in critical business processes, thereby optimizing the user's business experience.

[0052] In some embodiments, the aforementioned data change request is input into the workflow for multi-level process node approval, resulting in multiple approval results, including the following steps:

[0053] Step S401: When there are multiple process nodes at the current level, the data change request is input in parallel to all process nodes at the current level for approval, resulting in multiple approval sub-results. Each approval sub-result corresponds to a process node at the current level.

[0054] Step S402: If all of the above approval sub-results are approved, the above approval result is determined to be approved; if at least one of the above approval sub-results is not approved, the above approval result is determined to be not approved.

[0055] When a data change initiator initiates a data change request in the application, the workflow nodes are pushed forward and approved through multiple levels of process nodes. Each node has two possible outcomes: approval or rejection. Based on the approval result, it is decided whether to perform a database update operation. If the database is updated, a cache refresh operation is performed, and the parameter changes take effect. Otherwise, no update is performed.

[0056] In this embodiment, data change requests are effectively integrated into the workflow for multi-level process node approval. Specifically, when an approval level includes multiple approval nodes, data change requests are submitted in parallel to all these nodes to obtain approval sub-results. Each approval sub-result corresponds to a node and reflects each node's independent approval opinion on the request. The decision logic of the approval process is as follows: when all parallel approval nodes report approval as passed, the overall approval result is determined to be passed, thereby driving subsequent database updates and cache refresh processes. Conversely, if any approval sub-result indicates failure, even if other nodes pass, the overall approval result will be marked as failed, thus terminating the change process and preventing unnecessary updates to the database and cache. This decision mechanism based on the aggregation of multi-node approval results ensures the rigor and consistency of data changes, while also optimizing cache management strategies, avoiding invalid cache refreshes caused by the approval of a single node, reducing the consumption of system resources, and improving overall approval efficiency and data processing accuracy.

[0057] For example, when assembling a financial product, if the parameter component information of a product is modified, the approval process can go through two nodes, A and B, as follows:

[0058] When the process reaches node A:

[0059] ① Approval status: If the modified component parameters meet the modification standards, satisfy business needs, and the modified parameter information can be applied to the associated products without any inconsistency with product information, then the approval can be approved, the approval flow status will be updated, but no data operations will be triggered.

[0060] ② Approval rejection scenarios: If the configuration is not required by the business, or the modified information cannot be effectively applied to the corresponding product, a rejection operation needs to be performed, the approval workflow status updated, the version status rolled back, and the cache refresh not performed.

[0061] When the process reaches node B:

[0062] ① Approval status: The approval standards are the same as those of node A, but the process node B is different from that of node A. Node B has higher authority. If node B approves the approval, it can directly trigger the database update operation, change the version status, and refresh the cache.

[0063] ② Approval rejection: The approval standards are the same as those for node A. If this node finds that the parameter configuration does not meet expectations, it can still reject the application, roll back the version status, and not refresh the cache.

[0064] The aforementioned approval standards can also be checked using automated verification. If the automated verification passes, it triggers the process node to push forward; if the automated verification fails, it triggers the process node to roll back.

[0065] In some embodiments, before inputting the aforementioned data change request into the workflow for multi-level process node approval, the method further includes the following steps:

[0066] Step S501: Determine the process engine. The components of the process engine include: process definition component, process parsing component, process driving component, and data persistence component. The functions of the process engine include: process flow parsing of business process modeling symbols, process orchestration, and flow registration. The data of the process engine includes: process definition instance, process instance, activity instance, task instance, participant instance, and parameter instance.

[0067] Step S502: Invoke the software development kit of the process engine to establish and run the above workflow.

[0068] The aforementioned data change application is developed using Java (a software development language). It processes workflows by calling the process engine's SDK (Software Development Kit). The main components include process definition, process parsing, process driving, and data persistence. The process engine is primarily responsible for BPMN (Business Process Modeling Notation) flowchart parsing, process orchestration, and workflow registration. Through the coordinated efforts of seven modules—process definition instances, process instances, activity instances, task instances, participant instances, and parameter instances—it completes the entire transaction process.

[0069] In this embodiment, to ensure efficient and accurate processing of data change requests, the system first establishes a workflow engine. This engine integrates workflow definition, parsing, driving, and data persistence functions, capable of handling data such as workflow definition instances, workflow instances, activity instances, task instances, participant instances, and parameter instances. By calling the workflow engine's software development kit (SDK), a workflow is established and run, thereby achieving precise capture of approval node events and intelligent control of cache refresh operations during the approval process of data change requests. This solution effectively reduces the frequency of cache refreshes, minimizes latency of critical business data, saves system resources, and improves the reliability and real-time performance of cache update operations in a distributed environment. When the approval flow progresses to a preset approval node and passes approval, a cache update operation is automatically triggered, ensuring consistency between cached data and the database. It also supports differentiated refresh strategies based on the approval results of different nodes in multi-level approval processes, further optimizing system performance and resource utilization.

[0070] In some embodiments, the workflow described above is established and run by invoking the software development kit of the process engine, including the following steps:

[0071] Step S601: Establish the workflow based on the process definition component, process parsing component, flowchart parsing function of business process modeling symbols, and process orchestration function of the above-mentioned process engine.

[0072] Step S602: The workflow is controlled based on the process-driven component, data persistence component, flow level function, process definition instance, process instance, activity instance, task instance, participant instance, and parameter instance of the process engine.

[0073] The aforementioned data change application is developed using Java (a software development language). It processes workflows by calling the process engine's SDK (Software Development Kit). The main components include process definition, process parsing, process driving, and data persistence. The process engine is primarily responsible for BPMN (Business Process Modeling Notation) flowchart parsing, process orchestration, and workflow registration. Through the coordinated efforts of seven modules—process definition instances, process instances, activity instances, task instances, participant instances, and parameter instances—it completes the entire transaction process.

[0074] In this embodiment, the workflow is established and run by calling the software development kit (SDK) of the workflow engine. Specifically, the workflow is designed by integrating workflow definition, workflow parsing, BPMN flowchart parsing, and workflow orchestration functions. The execution of the workflow is coordinated by the workflow-driven component, data persistence component, and flow level function, and jointly controlled by workflow definition instances, workflow instances, activity instances, task instances, participant instances, and parameter instances. This architecture achieves tight coupling between the approval process and the cache refresh strategy, ensuring that cache updates are triggered only when preset key approval nodes are passed, thereby effectively reducing the cache refresh frequency, reducing the latency of critical business data, and saving system resources. In addition, this solution supports differentiated refresh strategies for different nodes in multi-level approval processes, making cache refresh more accurate and further improving the reliability and real-time performance of cache update operations in a distributed environment.

[0075] The definition of process nodes can be customized according to actual business needs. For example, for a financial product, which consists of many parameters, if a parameter is modified, the flowchart can be designed with two nodes, A and B. If both nodes A and B approve the modification, the modification is considered successful, and the cache can be refreshed. If either node fails to approve, the cache will not be refreshed. As another example, if the parameter modification requires approval from multiple nodes B with higher authority, the approval flow can be set up with multiple nodes A associated with multiple nodes B, allowing for parallel approval. Only when all nodes B approve is the modification considered successful, and the cache can then be refreshed. If any node fails to approve, the cache will not be refreshed.

[0076] In some embodiments, after determining that the cache should be refreshed based on the updated data of the aforementioned business data, the method further includes the following steps:

[0077] Step S701: Generate a data query service based on the updated data of the above business data;

[0078] Step S702: After the data query service detects the updated business data, it sends the data change information to the configuration center, so that the configuration center sends the data change information to all application nodes in the form of broadcast. The application nodes are the nodes that use the business data to execute business.

[0079] Step S703: When the application node receives the data change information, the updated data of the business data in the data query service is stored in the application node.

[0080] When data changes take effect and the database is updated, the data query service interface is called to refresh the cache.

[0081] 1. The data query service notifies the configuration center of the change, and the configuration center notifies the application node that uses the parameter of the change;

[0082] 2. The user application retrieves the changed parameters from the data query service and caches them locally, thus enabling it to use the changed data;

[0083] The data initialization process is as follows: when the application node starts, it retrieves data information through the data caching service and caches it in its own JVM (Java Virtual Machine). When the data is modified, the parameter query service notifies the configuration center (Apollo) (e.g., ...). Figure 3 Step 5), application nodes detect changes through the configuration center's notification mechanism (e.g., Figure 3 Step 6) Retrieve the changed parameters from the data caching service (e.g., Figure 3 Step 7) ensures that each application node can obtain the latest data after each data refresh.

[0084] In this embodiment, when the approval flow reaches a preset approval pass node, a cache update operation is triggered. Specifically, this includes generating a data query service interface to detect updates to business data. Once the data query service detects an update, it sends the data change information to the configuration center. The configuration center then broadcasts the data change notification to all application nodes, which are system components that directly use business data to perform business operations. Upon receiving the change notification, the application nodes retrieve the latest business data update information from the data query service and store it in their local cache. This ensures that all application nodes can obtain the latest data in a timely manner, avoiding problems caused by data asynchrony. It also reduces the frequency of cache refreshes, decreases system resource consumption, and improves the reliability and real-time performance of the cache update operation.

[0085] In some embodiments, the aforementioned data change request is input into the workflow for multi-level process node approval, resulting in multiple approval results, including the following steps:

[0086] Step S801: Input the above data change request into the workflow for multi-level process node approval, and determine whether the updated data of the above business data meets the preset conditions.

[0087] Step S802: If the updated data of the above business data is within the range of the above preset parameter threshold, within the range of business standard parameters, and within the range of permission parameters, it is determined that the updated data of the above business data meets the above preset conditions, and the above approval result is approval passed.

[0088] Step S803: If the updated data of the above business data meets at least one of the following conditions: the updated data of the above business data is not within the range of the above preset parameter threshold, the updated data of the above business data is not within the range of the above business standard parameters, or the updated data of the above business data is not within the range of the above permission parameters, then it is determined that the updated data of the above business data does not meet the above preset conditions, and the above approval result is that the approval is not passed.

[0089] This approach is suitable for controlling data changes through workflows. It leverages workflow event responses to determine whether data should be refreshed. For example, when a user initiates a parameter change request, a new change record is generated. However, this is only an initial, newly created state, without verification or validation, and is not necessary for the user to access. If the cache is refreshed at this point, it will result in an extra refresh. When multiple users perform this operation simultaneously, it will cause multiple invalid refreshes. Furthermore, in multi-level approvals, there will be more intermediate states, leading to even more invalid refreshes. Excessive refreshes can impact system performance. The workflow approach, however, can accurately refresh the cache at the desired state, while also considering business scenarios, ensuring users receive valid data promptly and avoiding data synchronization issues caused by delayed refreshes. A detailed cache refresh scheme is proposed to ensure smooth data refresh and normal application operation. The scheme refines the cache refresh scenarios by determining whether refresh is necessary based on different approval nodes and results, thus avoiding invalid refreshes.

[0090] In this embodiment, to implement a workflow-based cache refresh method, data change requests are first input into the workflow for multi-level process node approval, resulting in multiple approval results. Specifically, the system determines whether the updated business data meets preset conditions. These preset conditions include the updated data being within a preset parameter threshold range, conforming to business standard parameter requirements, and falling within the permission parameter range. If the updated business data simultaneously meets all three conditions, the approval result is marked as approved, triggering a cache update operation. Conversely, if the updated data fails to meet any of the above conditions, the approval result is marked as unapproved, and no cache update is triggered. This cache refresh strategy based on approval flow nodes not only effectively controls the cache update frequency and avoids unnecessary refresh operations but also ensures that the system refreshes the cache promptly when critical business data changes, improving data consistency and accuracy while optimizing resource utilization efficiency in a distributed environment. Furthermore, in scenarios involving multi-level approvals, the solution supports differentiated cache refresh strategies based on the approval results at different stages, further enhancing system stability and reliability, and reducing potential system load issues caused by frequent refreshes while meeting business specifications.

[0091] The workflow-based cache refresh scheme proposed in the above embodiments is different from previous cache refresh methods. It effectively reduces the cache refresh frequency, reduces the latency of critical business data, saves system resources, and improves the reliability and real-time performance of cache update operations in a distributed environment.

[0092] To enable those skilled in the art to better understand the technical solution of this application, the implementation process of the workflow-based cache refresh method of this application will be described in detail below with reference to specific embodiments.

[0093] This embodiment relates to a specific workflow-based cache refresh method, such as... Figure 3 As shown, it includes the following steps:

[0094] Step S1: First, make parameter changes and initiate an application to node A. If the application is approved, proceed to node B. If the application is rejected, return to parameter changes.

[0095] Step S2: When the approval reaches node B, it will be approved again. If the approval is successful, it will enter the data query service and update the database. Otherwise, it will return to parameter change.

[0096] Step S3: After entering the data query service, the changed data is retrieved, cached locally, and then sent to each application node. At the same time, the change is notified to the configuration center, which then notifies the application to send the change to each application node.

[0097] The workflow-based cache refresh mechanism ensures consistency between the cache and the database by defining and executing a series of task nodes and automatically updating cache data based on these nodes. The above embodiments fully consider the potential data inconsistencies and performance impacts from excessive refreshes during cache refresh execution. A cache refresh method strongly bound to approval workflow node events is proposed, effectively reducing cache refresh frequency, minimizing latency of critical business data, saving system resources, and improving the reliability and real-time performance of cache update operations in a distributed environment.

[0098] In the above embodiments, approval node events are strongly bound to cache refresh, reducing cache refresh frequency, decreasing latency of critical business data, saving system resources, and improving system stability. When the approval flow progresses to a preset node and the approval is passed, a cache update operation is automatically triggered; differentiated refresh strategies for different nodes in multi-level approval processes are supported.

[0099] Furthermore, the above embodiments innovatively use workflow event nodes to control whether the cache is refreshed, which differs from current cache refresh methods on the market. When the approval workflow progresses to a preset node and approval is granted, a cache update operation is automatically triggered; it supports differentiated refresh strategies for different nodes in multi-level approval processes. The above embodiments propose a detailed cache refresh scheme, enabling data to be refreshed smoothly and ensuring that the user application can be used normally. By determining whether the cache needs to be refreshed based on different approval nodes and approval results, the cache refresh scenarios are refined, avoiding invalid refreshes.

[0100] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0101] This application also provides a workflow-based cache refresh apparatus. It should be noted that the workflow-based cache refresh apparatus of this application can be used to execute the workflow-based cache refresh method provided in this application. This apparatus is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that implements a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0102] The following describes the workflow-based cache refresh device provided in the embodiments of this application.

[0103] Figure 4 This is a schematic diagram of a workflow-based cache refresh device according to an embodiment of this application. Figure 4 As shown, the device includes: a first determining unit 10, an approval unit 20, and a second determining unit 30. The first determining unit 10 is used to determine whether a data change request has been received, wherein the data change request is a request to update business data, and the data change request includes the updated data of the business data. The approval unit 20 is used to input the data change request into the workflow for multi-level process node approval when the data change request is received, and obtain multiple approval results. The multi-level process nodes are process nodes with different priorities, and the approval results correspond one-to-one with the level of the process nodes. The approval result is either approval passed or approval failed. The second determining unit 30 is used to determine to refresh the cache according to the updated data of the business data when all the approval results are approval passed, and to determine to keep the current cache unchanged when at least one of the approval results is approval failed.

[0104] The workflow-based cache refresh device of this application includes a first determining unit, an approval unit, and a second determining unit. The first determining unit determines whether a data change request has been received. The data change request is a request to update business data, and the data change request includes updated business data. The approval unit, upon receiving a data change request, inputs the data change request into the workflow for multi-level process node approval, obtaining multiple approval results. The multi-level process nodes are process nodes with different priorities, and the approval results correspond one-to-one with the level of the process node. The approval result is either approval passed or approval failed. The second determining unit, if all approval results are approval passed, determines to refresh the cache based on the updated business data; if at least one approval result is approval failed, determines to keep the current cache unchanged. This device can effectively reduce the cache refresh frequency, reduce the latency of critical business data, save system resources, and improve the reliability and real-time performance of cache update operations in a distributed environment. It solves the problems of poor data consistency, resource waste, high response latency, and poor adaptability to complex processes in traditional cache refresh methods.

[0105] In some embodiments, the approval unit includes a first determining module and a first approving module. The first determining module is used to determine the priority of each level of the aforementioned process nodes; the second determining module is used to input the aforementioned data change requests to the multiple levels of the aforementioned process nodes in order of priority from low to high for approval, resulting in multiple approval results. By precisely controlling the refresh nodes, a high degree of matching between data updates and business needs is achieved, improving the efficiency and reliability of data management in the distributed system.

[0106] In some embodiments, the approval unit further includes a second approval module and a third approval module. The first approval module is used to input the data change request in parallel to all current-level process nodes for approval when there are multiple current-level process nodes, resulting in multiple approval sub-results, each corresponding one-to-one with a current-level process node. The second approval module is used to determine the approval result as approved if all approval sub-results are approved, and to determine the approval result as rejected if at least one approval sub-result is rejected. This optimizes the cache management strategy, avoiding invalid cache refreshes caused by the approval of a single node, reducing system resource consumption, and improving overall approval efficiency and data processing accuracy.

[0107] In some embodiments, the apparatus further includes a third determining module and a fourth determining module. The third determining module is used to determine the process engine before inputting the data change request into the workflow for multi-level process node approval. The components of the process engine include: a process definition component, a process parsing component, a process driving component, and a data persistence component. The functions of the process engine include: process flow parsing of business process modeling symbols, process orchestration, and flow registration. The data of the process engine includes: process definition instances, process instances, activity instances, task instances, participant instances, and parameter instances. The fourth determining module is used to call the software development kit of the process engine to establish and run the workflow. This ensures the consistency between cached data and the database, further optimizing system performance and resource utilization.

[0108] In some embodiments, the fourth determining module includes a fifth determining module and a sixth determining module. The fifth determining module is used to establish the workflow based on the process definition component, the process parsing component, the flowchart parsing function of the business process modeling symbols, and the process orchestration function of the aforementioned process engine. The sixth determining module is used to control the operation of the workflow based on the process driving component, the data persistence component, the flow level function, the process definition instance, the process instance, the activity instance, the task instance, the participant instance, and the parameter instance of the aforementioned process engine. It supports differentiated refresh strategies for different nodes in multi-level approval processes, making cache refresh more accurate and further improving the reliability and real-time performance of cache update operations in a distributed environment.

[0109] In some embodiments, the above-described apparatus further includes a seventh determining module, an eighth determining module, and a ninth determining module. The seventh determining module is used to generate a data query service based on the updated data of the business data after determining that the cache should be refreshed according to the updated data of the business data. The eighth determining module is used to send data change information to the configuration center after the data query service detects the updated data of the business data, so that the configuration center broadcasts the data change information to all application nodes, where the application nodes are nodes that execute business using the business data. The ninth determining module is used to store the updated data of the business data in the data query service into the application node when the application node receives the data change information. This supports differentiated refresh strategies for different nodes in a multi-level approval process, making cache refresh more accurate and further improving the reliability and real-time performance of cache update operations in a distributed environment.

[0110] In some embodiments, the approval module further includes a third approval module, a fourth approval module, and a fifth approval module. The third approval module is used to input the data change request into the workflow for multi-level process node approval and determine whether the updated business data meets preset conditions. The fourth approval module is used to determine that the updated business data meets the preset conditions and the approval result is approved if the updated business data is within the preset parameter threshold range, within the business standard parameter range, and within the permission parameter range. The fifth approval module is used to determine that the updated business data does not meet the preset conditions and the approval result is disapproved if the updated business data meets at least one of the following conditions: the updated business data is not within the preset parameter threshold range, the updated business data is not within the business standard parameter range, or the updated business data is not within the permission parameter range. This cache refresh strategy based on approval flow nodes can not only effectively control the cache update frequency and avoid unnecessary refresh operations, but also ensure that the system refreshes the cache in a timely manner when critical business data changes, improving data consistency and accuracy, while optimizing resource utilization efficiency in a distributed environment.

[0111] The aforementioned workflow-based cache refresh device includes a processor and a memory. The aforementioned determining units, etc., are all stored as program units in the memory, and the processor executes these program units stored in the memory to implement the corresponding functions. All of the aforementioned modules reside in the same processor; alternatively, the aforementioned modules may be located in different processors in any combination.

[0112] The processor contains a kernel, which retrieves the corresponding program units from memory. One or more kernels can be configured, and by adjusting kernel parameters, problems such as poor data consistency, resource waste, high response latency, and poor adaptability to complex processes in traditional cache flushing methods can be solved.

[0113] The memory may include non-permanent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0114] This invention provides a computer-readable storage medium including a stored program, wherein, when the program is executed, it controls the device where the computer-readable storage medium is located to perform the workflow-based cache refresh method.

[0115] This invention provides a processor for running a program, wherein the program executes the workflow-based cache refresh method during runtime.

[0116] This invention provides a device comprising one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include steps for implementing the workflow-based cache refresh method described above. The device described herein may be a server, PC, PAD, mobile phone, etc.

[0117] This application also provides a computer program product that, when executed on a processing device, is adapted to perform a program that initializes a cache refresh method step having at least a workflow-based approach.

[0118] It is obvious to those skilled in the art that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. They can be implemented using computer-executable program code, and thus can be stored in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those described herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0119] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0120] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0121] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0122] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0123] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0124] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0125] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0126] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0127] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0128] As can be seen from the above description, the embodiments of this application achieve the following technical effects:

[0129] 1) The workflow-based cache refresh method of this application first determines whether a data change request has been received. The data change request is a request to update business data, including the updated business data. If a data change request is received, it is input into the workflow for multi-level process node approval, resulting in multiple approval results. These multi-level process nodes are process nodes with different priorities, and the approval results correspond one-to-one with the level of the process node, either approved or rejected. If all approval results are approved, the cache is refreshed based on the updated business data. If at least one approval result is rejected, the current cache is maintained. This method effectively improves the reliability and real-time performance of cache update operations in a distributed environment, solving the problems of poor data consistency, resource waste, high response latency, and poor adaptability to complex processes inherent in traditional cache refresh methods.

[0130] 2) The aforementioned workflow-based cache refresh device of this application includes a first determining unit, an approval unit, and a second determining unit. The first determining unit is used to determine whether a data change request has been received. The data change request is a request to update business data, and the data change request includes updated business data. The approval unit is used to input the data change request into the workflow for multi-level process node approval when a data change request is received, obtaining multiple approval results. The multi-level process nodes are process nodes with different priorities, and the approval results correspond one-to-one with the level of the process node. The approval result is either approval passed or approval failed. The second determining unit is used to determine to refresh the cache according to the updated business data when all approval results are approval passed, and to determine to keep the current cache unchanged when at least one approval result is approval failed. This device addresses the problems of existing cache refresh methods, which refresh the cache when data is updated, leading to excessive refreshes in non-use scenarios due to numerous modification scenarios. Furthermore, the refresh method based on preset time cannot be linked with events, resulting in insufficient real-time performance and potential inconsistencies between the acquired and actual data. This device solves the problems of poor data consistency, resource waste, high response latency, and poor adaptability to complex processes inherent in traditional cache refresh methods.

[0131] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A workflow-based cache refresh method, characterized in that, include: Determine whether a data change request has been received, wherein the data change request is a request to update business data, and the data change request includes the updated data of the business data; Upon receiving the data change request, the data change request is input into the workflow for multi-level process node approval, resulting in multiple approval results. The multi-level process nodes are process nodes with different priorities. The approval results correspond one-to-one with the level of the process node, and the approval result is either approval passed or approval failed. If all the approval results are "approved", the cache is refreshed based on the updated business data. If at least one of the approval results is "approved but not approved", the current cache is kept unchanged.

2. The method according to claim 1, characterized in that, The data change request is input into the workflow for multi-level process node approval, resulting in multiple approval results, including: Determine the priority of each process node; The data change requests are sequentially input to the multi-level process nodes according to their priority from low to high for approval, resulting in multiple approval results.

3. The method according to claim 1, characterized in that, The data change request is input into the workflow for multi-level process node approval, resulting in multiple approval results, including: When there are multiple process nodes at the current level, the data change request is input in parallel to all process nodes at the current level for approval, resulting in multiple approval sub-results, each of which corresponds one-to-one with a process node at the current level. If all of the approval sub-results are "approved", the approval result is determined to be "approved"; if at least one of the approval sub-results is "not approved", the approval result is determined to be "not approved".

4. The method according to claim 1, characterized in that, Before inputting the data change request into the workflow for multi-level process node approval, the method further includes: The process engine is defined, and its components include: process definition component, process parsing component, process driving component, and data persistence component. The functions of the process engine include: process flow parsing of business process modeling symbols, process orchestration, and flow registration. The data of the process engine includes: process definition instance, process instance, activity instance, task instance, participant instance, and parameter instance. The workflow is built and run by calling the software development kit of the process engine.

5. The method according to claim 4, characterized in that, The workflow is built and run by calling the software development kit of the process engine, including: The workflow is established based on the process definition component, the process parsing component, the flowchart parsing function of the business process modeling symbols, and the process orchestration function of the process engine. The workflow operation is controlled by the process-driven component, the data persistence component, the flow level function, the process definition instance, the process instance, the activity instance, the task instance, the participant instance, and the parameter instance of the process engine.

6. The method according to claim 1, characterized in that, After determining that the cache should be refreshed based on the updated data of the business data, the method further includes: Generate a data query service based on the updated data of the aforementioned business data; After the data query service detects the updated business data, it sends the data change information to the configuration center, so that the configuration center broadcasts the data change information to all application nodes, which are the nodes that use the business data to execute business. Upon receiving the data change information, the application node stores the updated business data from the data query service into the application node.

7. The method according to claim 1, characterized in that, The data change request is input into the workflow for multi-level process node approval, resulting in multiple approval results, including: The data change request is input into the workflow for multi-level process node approval, and it is determined whether the updated business data meets the preset conditions. If the updated business data is within the preset parameter threshold range, the business standard parameter range, and the permission parameter range, then the updated business data is determined to meet the preset conditions, and the approval result is approval passed. If the updated business data meets at least one of the following conditions: the updated business data is not within the preset parameter threshold range, the updated business data is not within the business standard parameter range, or the updated business data is not within the permission parameter range, then the updated business data is determined to not meet the preset condition, and the approval result is approval failed.

8. A workflow-based cache refresh device, characterized in that, include: The first determining unit is configured to determine whether a data change request has been received, wherein the data change request is a request to update business data, and the data change request includes the updated data of the business data. An approval unit is used to input the data change request into the workflow for multi-level process node approval upon receiving the data change request, and obtain multiple approval results. The multi-level process nodes are process nodes with different priorities. The approval results correspond one-to-one with the level of the process node. The approval result is either approval passed or approval failed. The second determining unit is configured to determine to refresh the cache based on the updated data of the business data when all the approval results are approval passed, and to determine to keep the current cache unchanged when at least one of the approval results is approval failed.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device on which the computer-readable storage medium resides to perform the workflow-based cache refresh method according to any one of claims 1 to 7.

10. An electronic device, characterized in that, include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including a workflow-based cache refresh method according to any one of claims 1 to 7.

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