A data processing method and device, electronic equipment and storage medium

Abstract

This application discloses a data processing method, apparatus, electronic device, and storage medium. The method includes: acquiring relevant data of a first reverse order in online data where a reverse fulfillment process has occurred; determining a first abnormal event strategy matched with the first reverse order, determining that the first store to which the first reverse order belongs matches the target merchant set associated with the first abnormal event strategy, and generating a first negative control work order for the first store; setting a delayed execution time for executing the rules associated with the first abnormal event strategy for the first negative control work order; at the delayed execution time, performing rule matching on the first negative control work order based on the rules associated with the first abnormal event strategy and historical abnormal data, and performing corresponding control actions on the first store based on the execution result. Using this method, the problem of accurately monitoring reverse fulfillment processes and timely and effective control of merchants is solved.

Description

Technical Field

[0001] This application relates to the field of computer processing technology, specifically to a data processing method, apparatus, electronic device, and storage medium. Background Technology

[0002] In the online shopping transaction process, the fulfillment process from successful payment to receipt of goods or services is a crucial link in ensuring the smooth operation of the transaction, making its monitoring particularly important. As more and more users choose to shop online through platforms, such as ordering food or buying clothes online, this places higher demands on platforms to accurately and effectively monitor the fulfillment process.

[0003] Platform monitoring of the fulfillment process typically includes identifying anomalies to determine reverse fulfillment flows and identifying the responsible party. Fulfillment usually involves multiple parties, including users, delivery resources (such as riders), merchants, and the platform. When one party initiates cancellation, and subsequent nodes in the transaction process agree or refuse, this constitutes a reverse fulfillment flow. While existing technologies can identify abnormal fulfillment behaviors such as order cancellations or refunds initiated by users, riders, merchants, or the platform, and the factors leading to these abnormal behaviors (e.g., merchant stock shortages, insufficient logistics capacity, or inability to contact the user), thus determining reverse fulfillment flows, there is a lack of timely and accurate monitoring of these reverse fulfillment flows to allow for timely and effective control measures for the corresponding merchants.

[0004] Therefore, how to accurately monitor performance setbacks during the fulfillment process and effectively regulate merchants in a timely manner is a problem that needs to be solved.

[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this application, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] The data processing method provided in this application solves the problem of accurately monitoring the reversal of performance in the performance process and making timely and effective adjustments to merchants.

[0007] This application provides a data processing method, including: acquiring relevant data of a first reverse order in online data where a reverse fulfillment process has occurred; wherein, the reverse fulfillment process refers to a fulfillment anomaly handling process triggered by an abnormal event during the fulfillment process; determining a first abnormal event strategy matched according to the first reverse order, determining that the first store to which the first reverse order belongs matches the target merchant set associated with the first abnormal event strategy, and generating a first negative control work order for the first store; setting a delayed execution timing for executing the rules associated with the first abnormal event strategy for the first negative control work order; acquiring historical abnormal data of the first store, and at the delayed execution timing, performing rule matching on the first negative control work order based on the rules associated with the first abnormal event strategy and the historical abnormal data, and performing corresponding control actions on the first store according to the execution result of the rule matching.

[0008] Optionally, setting the delayed execution timing of the rule associated with the first abnormal event strategy for the first negative control work order includes: treating the rule associated with the first abnormal event strategy for the first negative control work order as an event to be executed; processing the event to be executed using a message middleware, storing the event to be executed in a first delay queue, obtaining the delay duration of the delayed execution preset for the first abnormal event strategy, and setting the delay attribute of the first delay queue or setting the delay attribute of the event to be executed according to the delay duration of the delayed execution.

[0009] Optionally, setting the delayed execution timing of the rule associated with the first abnormal event strategy for the first negative control work order includes: treating the rule associated with the first abnormal event strategy for the first negative control work order as an event to be executed; processing the event to be executed using a message middleware, storing the event to be executed in a second delay queue, obtaining the delay duration preset for the first abnormal event strategy, starting a timed task to process the second delay queue according to the delay duration, retrieving the event to be executed from the second delay queue after the timed task starts, recreating a delayed execution message corresponding to the event to be executed and sending it to a target queue, wherein the delayed execution message in the target queue carries the delayed event to be executed.

[0010] Optionally, it also includes: obtaining a second store with abnormal merchant behavior from offline data, and a second abnormal event strategy matching the abnormal data of the store; wherein, the second store refers to the store in the offline data where the responsible party for the order is the merchant due to cancellation or refund in the fulfillment process; generating a second negative control work order for the second store, and performing corresponding control actions on the second negative control work order based on the rules associated with the second abnormal event strategy.

[0011] Optionally, acquiring relevant data of the first reverse order in the online data where a reverse fulfillment process occurs includes: acquiring an abnormal order request provided by the merchant client, acquiring corresponding order data and merchant abnormal behavior data based on the abnormal order request, as relevant data of the first reverse order; and / or, monitoring fulfillment messages generated by at least one of the order forward processing equipment, waybill center equipment, delivery center equipment, order reverse processing equipment, inventory change processing equipment, and distribution resource center equipment, and identifying abnormal fulfillment messages carrying merchant abnormal behavior data; or, monitoring abnormal fulfillment messages generated by at least one of the above-mentioned equipment; using the order data corresponding to the abnormal fulfillment message as the first reverse order, and the order data and merchant abnormal behavior data as relevant data of the first reverse order.

[0012] Optionally, the abnormal performance message includes: order status change information caused by order cancellation or refund after payment is completed, and / or waybill status change information caused by waybill cancellation or refund after waybill generation; the step of using the order data corresponding to the abnormal performance message as the first reverse order includes: if it is determined that the order status change information and / or the waybill status change information are related to merchant behavior, then the order data corresponding to the abnormal performance message is used as the first reverse order.

[0013] Optionally, obtaining the historical abnormal data of the first store includes: obtaining historical abnormal data from a real-time data warehouse and / or an external service domain based on the time window of the first reverse order matching, wherein the historical abnormal data is historical data associated with the online data; clustering the obtained data according to the store dimension, and querying the historical abnormal data of the first store from the clustered data according to the first store to which the first reverse order belongs.

[0014] Optionally, the rule associated with the first abnormal event strategy performs rule matching on the first negative control work order based on the historical abnormal data, and performs corresponding control actions on the first store based on the execution result of the rule matching, including: if it is determined that the abnormal frequency of abnormal data occurring in the first store within the time window exceeds the abnormal frequency threshold or the number of consecutive abnormal data occurrences exceeds the abnormal number threshold, then the corresponding control action is executed.

[0015] Optionally, it further includes: receiving configuration information for the sub-policy, the configuration information including at least the delay duration for delayed execution, the matching characteristics of at least one rule, and the logical relationship between the rules; associating sub-policies applied to the same merchant set with the same abnormal event policy, and associating the abnormal event policy with the merchant set; the abnormal event policy includes a first abnormal event policy; the merchant set includes the target merchant set.

[0016] Optionally, determining the first abnormal event strategy matched based on the first reverse order includes: determining a target sub-strategy in the first abnormal event strategy matched based on the first reverse order; setting a delayed execution timing for the rules associated with the first abnormal event strategy for the first negative control work order includes: setting the delayed execution timing based on the delay duration of the delayed execution of the target sub-strategy; and performing rule matching on the first negative control work order based on the rules associated with the first abnormal event strategy according to the historical abnormal data, and performing corresponding control actions on the first store based on the execution result of the rule matching, includes: performing rule matching on the first negative control work order based on the rules associated with the target sub-strategy according to the historical abnormal data, and performing corresponding control actions on the first store based on the execution result of the rule matching.

[0017] Optionally, it also includes: setting merchants in the whitelist or timed whitelist of the first abnormal event policy based on the HBase database, and using the value of 0 or 1 in the key-value pair to identify whether the merchant is a merchant in the whitelist or timed whitelist; the merchant includes the first store; determining that the first store to which the first reverse order belongs matches the target merchant set associated with the first abnormal event policy includes: querying the value corresponding to the key corresponding to the first store to determine whether the first store is a merchant in the whitelist or timed whitelist.

[0018] This application embodiment also provides a data processing method, including: in response to triggering a configuration sub-policy, displaying a sub-policy editing interface; the sub-policy editing interface is used to create new sub-policies or edit information of existing sub-policies; receiving at least one of the following configuration information input in the sub-policy editing interface: sub-policy identifier, delay duration for delayed execution, matching characteristics of at least one rule, logical relationship between rules, and adjustment action on rule matching under the corresponding sub-policy, and sending the configuration information to a server, causing the server to generate a new sub-policy or modify information of an existing sub-policy; in response to associating one or more configured sub-policies with an exception event policy, sending a rule refresh instruction to the server, causing the server to... The abnormal event policy is generated or refreshed according to the sub-policy; in response to applying the abnormal event policy to the merchant set, a policy application instruction is sent to the server, so that the server establishes an association between the abnormal event policy and the merchant set; the merchant set includes merchants whose fulfillment processes are to be monitored; the association is used to determine whether the merchant to which the reverse order belongs matches the merchant set associated with the abnormal event policy after determining the abnormal event policy on the reverse order; wherein, the reverse order refers to an order in which a reverse fulfillment process occurs in the data or offline data that is providing online services, and the reverse fulfillment process refers to the fulfillment exception handling process triggered by an abnormal event in the fulfillment process.

[0019] Optionally, it also includes: receiving information on the effective period of the input exception event policy, wherein the effective period is used by the server to determine the exception event policy for reverse order matching based on the effective period of the exception event policy.

[0020] This application embodiment also provides a data processing apparatus, including: an online data acquisition unit, used to acquire relevant data of a first reverse order in online data where a reverse fulfillment process has occurred; wherein, the reverse fulfillment process refers to a fulfillment anomaly handling process triggered by an abnormal event during the fulfillment process; a strategy matching unit, used to determine a first abnormal event strategy matched according to the first reverse order, determine that the first store to which the first reverse order belongs matches the target merchant set associated with the first abnormal event strategy, and generate a first negative control work order for the first store; a delayed execution unit, used to set a delayed execution timing for executing the rules associated with the first abnormal event strategy for the first negative control work order; and a control unit, used to acquire historical abnormal data of the first store, and at the delayed execution timing, perform rule matching on the first negative control work order based on the rules associated with the first abnormal event strategy and the historical abnormal data, and perform corresponding control actions on the first store according to the execution result of the rule matching.

[0021] This application embodiment also provides a data processing apparatus, including: a configuration interface unit, used to display a sub-policy editing interface in response to triggering a configuration sub-policy; the sub-policy editing interface is used to create new sub-policies or edit information of existing sub-policies; a configuration information input unit, used to receive at least one of the following configuration information input in the sub-policy editing interface: sub-policy identifier, delay duration for delayed execution, matching characteristics of at least one rule, logical relationship between rules, and control action on rule matching under the corresponding sub-policy, and send the configuration information to a server, so that the server generates a new sub-policy or modifies information of an existing sub-policy; and a sub-policy association unit, used to send rules to the server in response to associating one or more configured sub-policies with an exception event policy. A refresh command causes the server to generate or refresh the abnormal event policy according to the sub-policy; a policy application unit is used to send a policy application command to the server in response to applying the abnormal event policy to the merchant set, so that the server establishes an association between the abnormal event policy and the merchant set; the merchant set includes merchants whose fulfillment processes are to be monitored; the association is used to determine whether the merchant to which the reverse order belongs matches the merchant set associated with the abnormal event policy after determining the abnormal event policy for the reverse order; wherein, the reverse order refers to an order in the data or offline data that is providing online services and has a reverse fulfillment process, and the reverse fulfillment process refers to the fulfillment exception handling process triggered by an abnormal event in the fulfillment process.

[0022] This application embodiment also provides a merchant control system for performance monitoring, including: an online data monitoring subsystem, a historical data acquisition subsystem associated with online data, and a control subsystem; wherein, the online data monitoring subsystem is used to listen for abnormal performance messages of canceled or refunded orders initiated by merchant clients, and / or to listen for abnormal performance messages related to merchant behavior transmitted by message middleware; and to acquire order data corresponding to the abnormal performance messages as a first reverse order; the historical data acquisition subsystem associated with online data is used to provide historical abnormal data associated with online data based on a time window matching the first reverse order; the control subsystem is used to adjust the order data according to the first reverse order... A first abnormal event strategy is determined for matching, and the first store to which the first reverse order belongs is determined to match the target merchant set associated with the first abnormal event strategy, generating a first negative control work order for the first store; a delayed execution timing is set for executing the rules associated with the first abnormal event strategy for the first negative control work order; historical abnormal data of the first store is obtained based on historical abnormal data provided by the historical data acquisition subsystem associated with online data, and at the delayed execution timing, rule matching is performed on the first negative control work order based on the rules associated with the first abnormal event strategy and the historical abnormal data, and the corresponding control action is performed on the first store based on the execution result of the rule matching.

[0023] Optionally, it also includes: an offline data monitoring subsystem; wherein, the offline data monitoring subsystem is used to identify a second store with abnormal merchant behavior based on offline data, determine a matching second abnormal event strategy based on the abnormal merchant behavior data of the second store, determine that the second store matches a second set of merchants associated with the second abnormal event strategy, and send the information of the second store and the second abnormal event strategy to the control subsystem; the control subsystem is further used to generate a second negative control work order for the second store based on the information of the second store and the second abnormal event strategy; determine that the second abnormal event strategy is an offline type strategy, and perform corresponding control actions on the second store based on the rules associated with the second abnormal event strategy.

[0024] This application also provides an electronic device, including: a memory and a processor; the memory is used to store a computer program, which, when run by the processor, executes the method provided in this application.

[0025] This application also provides a computer storage medium storing computer execution instructions, which, when executed by a processor, are used to implement the method provided in this application.

[0026] Compared with the prior art, this application has the following advantages:

[0027] This application provides a data processing method, apparatus, electronic device, and storage medium. It acquires relevant data of a first reverse order in online data where a reverse fulfillment process has occurred. The reverse fulfillment process refers to a fulfillment anomaly handling process triggered by an abnormal event during the fulfillment process. Based on the first reverse order, a first abnormal event strategy is determined, and the first store to which the first reverse order belongs is matched with the target merchant set associated with the first abnormal event strategy, generating a first negative control work order for the first store. A delayed execution timing is set for the first negative control work order to execute the rules associated with the first abnormal event strategy. Historical abnormal data of the first store is acquired, and at the delayed execution timing, rule matching is performed on the first negative control work order based on the rules associated with the first abnormal event strategy and the historical abnormal data. Based on the execution result of the rule matching, corresponding control actions are performed on the first store. By delaying execution and using relevant historical abnormal data to match rules, timely and accurate monitoring of the occurring reverse fulfillment process and timely and effective control of merchants are achieved, improving the accuracy of reverse fulfillment process monitoring and the timeliness of control.

[0028] Another data processing method, apparatus, electronic device, and storage medium provided in this application embodiment, in response to triggering a configuration sub-policy, displays a sub-policy editing interface; the sub-policy editing interface is used to create new sub-policies or edit information of existing sub-policies; the sub-policy editing interface receives at least one of the following configuration information input: sub-policy identifier, delay duration for delayed execution, matching characteristics of at least one rule, logical relationships between rules, and control actions for rule matching under the corresponding sub-policy, and sends the configuration information to the server, causing the server to generate new sub-policies or modify information of existing sub-policies; in response to associating one or more configured sub-policies with an exception event policy, A rule refresh instruction is sent to the server, causing the server to generate or refresh the abnormal event policy according to the sub-policy. In response to applying the abnormal event policy to a merchant set, a policy application instruction is sent to the server, causing the server to establish an association between the abnormal event policy and the merchant set. The merchant set includes merchants whose fulfillment processes are to be monitored. The association is used to determine whether the merchant to which the reverse order belongs matches the merchant set associated with the abnormal event policy after determining the abnormal event policy for matching reverse orders. The reverse order refers to an order in online or offline data where the fulfillment process is canceled or cancelled, resulting in a reverse fulfillment process. This provides a scheme for configuring and applying abnormal event policies. The configured information is used to implement delayed execution of detected reverse fulfillment processes and to perform rule matching using relevant historical abnormal data, which helps to achieve timely and accurate monitoring of reverse fulfillment processes and timely and effective regulation of merchants.

[0029] This application provides a merchant control system for performance monitoring, comprising: an online data monitoring subsystem, a historical data acquisition subsystem associated with online data, and a control subsystem; the online data monitoring subsystem is configured to listen for abnormal performance messages of canceled or refunded orders initiated by merchant clients, and / or listen for abnormal performance messages related to merchant behavior transmitted by message middleware; acquire order data corresponding to the abnormal performance messages as a first reverse order; the historical data acquisition subsystem associated with online data is configured to provide historical abnormal data associated with online data based on a time window matching the first reverse order; the control subsystem is configured to adjust the order data according to the first reverse order. A first abnormal event strategy is determined, and the first store to which the first reverse order belongs matches the target merchant set associated with the first abnormal event strategy, generating a first negative control work order for the first store. A delayed execution timing is set for the rules associated with the first abnormal event strategy executed on the first negative control work order. Historical abnormal data of the first store is obtained based on historical abnormal data provided by the historical data acquisition subsystem associated with online data. At the delayed execution timing, rule matching is performed on the first negative control work order based on the rules associated with the first abnormal event strategy and the historical abnormal data. Based on the execution result of the rule matching, corresponding control actions are performed on the first store. By monitoring the fulfillment reverse process occurring in online data, delayed execution and rule matching using relevant historical abnormal data are achieved, enabling timely and accurate monitoring of the fulfillment reverse process and timely and effective control of the corresponding merchants. Attached Figure Description

[0030] Figure 1 This is a flowchart of a data processing method provided in the first embodiment of this application;

[0031] Figure 2 This is a schematic diagram of a system environment for applying the data processing method provided in the first embodiment of this application;

[0032] Figure 3 This is a flowchart of a merchant control system provided in the first embodiment of this application;

[0033] Figure 4 This is a flowchart of a data processing method provided in the second embodiment of this application;

[0034] Figure 5 This is a schematic diagram of a strategy configuration provided in the second embodiment of this application;

[0035] Figure 6 This is a schematic diagram of a data processing device provided in the third embodiment of this application;

[0036] Figure 7 This is a schematic diagram of another data processing device provided in the fourth embodiment of this application;

[0037] Figure 8 This is a schematic diagram of a merchant control system for performance monitoring provided in the fifth embodiment of this application;

[0038] Figure 9 This is a schematic diagram of the electronic device provided in this application. Detailed Implementation

[0039] Many specific details are set forth in the following description to provide a full understanding of this application. However, this application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of this application; therefore, this application is not limited to the specific embodiments disclosed below.

[0040] This application provides a data processing method, apparatus, electronic device, and storage medium. This application also provides another data processing method, apparatus, electronic device, and storage medium. Furthermore, this application provides a merchant control system for performance monitoring. These will be described in detail in the following embodiments.

[0041] To facilitate understanding, the relevant concepts and application scenarios of the method provided in this application are first given. The information disclosed below is only used to enhance the understanding of the method provided in this application and does not constitute prior art known to those skilled in the art.

[0042] The fulfillment process is a crucial part of online shopping transactions. Fulfillment refers to the process from successful payment to receipt of goods or services, typically involving multiple parties including the user, delivery resources (such as riders), merchants, and the platform. Monitoring this process is essential to ensuring smooth transactions. In the fulfillment chain, the normal order of fulfillment is the forward flow, generally from order creation → user payment → merchant order acceptance → rider delivery → order completion. When abnormal behavior and / or factors lead to order cancellation or refunds, a reverse fulfillment flow occurs. For example, if a merchant is out of stock, logistics capacity is insufficient, or the user cannot be contacted, causing any party (user, rider, merchant, or platform) to initiate an order cancellation or refund, and other nodes agree or refuse, this constitutes a reverse fulfillment flow. Orders entering a reverse fulfillment flow often result in losses for users, delivery resources (such as riders), and the platform. One application scenario is the food delivery scenario. In this scenario, factors such as merchants not accepting orders, maliciously refusing orders, slow food preparation, slow delivery, and delivery riders arriving at the store to find it closed can all lead to fulfillment anomalies. The method described in this application can be implemented in the food delivery scenario to monitor the fulfillment process of food delivery orders in real time and to make timely and effective adjustments to the corresponding food delivery merchants. It is understood that the application scenario is merely illustrative and does not constitute a limitation on the method.

[0043] The data processing method provided in this application embodiment can be applied to a merchant control system for fulfillment monitoring and regulating merchants experiencing fulfillment reversals. It acquires reverse orders from online data indicating such reversals and executes corresponding control actions on the store to which the reverse order belongs based on a matched anomaly event strategy. This enables real-time monitoring of the fulfillment process and timely and effective control of the corresponding store. This improves the experience for users and riders, reduces losses for all parties, and enhances merchants' service awareness. The anomaly event strategy matching allows for flexible strategy settings to add identification and control capabilities for unreasonable scenarios. In this embodiment, "merchant" can be understood as a merchant store.

[0044] The following combination Figures 1 to 3 The data processing method provided in the first embodiment of this application will be described. Figure 1 The data processing method shown includes steps S101 to S104.

[0045] Step S101: Obtain relevant data of the first reverse order in the online data where a reverse fulfillment process has occurred; wherein, the reverse fulfillment process refers to the fulfillment exception handling process triggered by an abnormal event in the fulfillment process.

[0046] An abnormal event refers to an event in the online shopping fulfillment process that causes fulfillment anomalies due to abnormal behavior and / or abnormal factors. For example, order cancellations or refunds caused by abnormal behavior and / or abnormal factors. Another example is order fulfillment delays due to slow food preparation or delivery. In reality, when abnormal factors such as merchant stock shortages, insufficient logistics capacity, or inability to contact users exist, it may cause any party—user, rider, merchant, or platform—to initiate order cancellations or refunds, thus causing the order to enter a reverse fulfillment process. Once an order enters a reverse fulfillment process, other nodes in the fulfillment chain can agree or refuse. Preferably, if the factor triggering the reverse fulfillment process is the merchant's abnormal behavior or unreasonable operation, or other merchant-related factors, then a negative impact on the merchant occurs, and the merchant is subject to regulation. For example, if a merchant does not accept orders, maliciously refuses orders, cancels or refunds orders, has slow food preparation, or a rider finds the store closed upon arrival, the merchant is the responsible party for the reverse fulfillment process.

[0047] A reverse order refers to an order whose fulfillment process reverses during the fulfillment process. For example, an order that is canceled or refunded during the fulfillment process, resulting in a reverse fulfillment process, is considered a reverse order. It can be understood that the first type of reverse order refers to an order whose fulfillment process reverses within the data currently being provided as an online service.

[0048] This step involves monitoring the first reverse order in the online data where a reverse fulfillment process occurs. Preferably, the first reverse order specifically refers to a reverse order triggered by abnormal merchant behavior. During implementation, data generated by computing devices used at relevant nodes in the fulfillment process is monitored. This includes monitoring data from computing devices providing online services, such as those used for order forward processing, waybill centers, delivery centers, reverse order processing, inventory change processing, and delivery resource centers (e.g., rider operation centers). This monitoring includes listening to data related to the forward and reverse fulfillment processes, inventory changes, and changes in the status of merchant-related order waybills. It also includes listening to data related to merchant-triggered order cancellations or merchant-clicked order rejections sent by the merchant's client. This data generated by computing devices can be transmitted through a message middleware, entering corresponding message queues according to pre-designed message topics or types. The entity executing the data processing method provided in this embodiment acts as a message consumer, listening to messages in the message middleware's message queues. For example, fulfillment-related messages enter a fulfillment message queue as a fulfillment message type. Alternatively, a separate message queue can be used for abnormal fulfillment messages. Specifically, the step of acquiring relevant data for the first reverse order in which abnormal behavior occurred in online data includes: acquiring abnormal order requests provided by the merchant client, acquiring corresponding order data and merchant abnormal behavior data based on the abnormal order requests, and using these as relevant data for the first reverse order; and / or, monitoring fulfillment messages generated by at least one of the order forward processing equipment, waybill center equipment, delivery center equipment, order reverse processing equipment, inventory change processing equipment, and distribution resource center equipment, and identifying abnormal fulfillment messages carrying merchant abnormal behavior data; or, monitoring abnormal fulfillment messages generated by at least one of the aforementioned equipment; further, using the order data corresponding to the abnormal fulfillment message as the first reverse order, and using the order data and merchant abnormal behavior data as relevant data for the first reverse order. The abnormal fulfillment message includes: order status change information caused by order cancellation or refund after payment is completed, and / or waybill status change information caused by waybill cancellation or refund after waybill generation; correspondingly, using the order data corresponding to the abnormal fulfillment message as the first reverse order includes: if it is determined that the order status change information and / or the waybill status change information are related to merchant behavior, then the order data corresponding to the abnormal fulfillment message is used as the first reverse order. In implementation, if the abnormal fulfillment message does not use a separate message queue, it is necessary to identify whether the listened-to fulfillment message is an abnormal fulfillment message carrying abnormal merchant behavior data. For example, if a fulfillment message reported by a rider is listened to, and information indicating that the merchant has closed or that the merchant is slow in preparing food is parsed from it, then the fulfillment message is not an abnormal fulfillment message.For example, if a fulfillment message contains information indicating order cancellation due to insufficient inventory, then the fulfillment message is not considered an abnormal fulfillment message. Conversely, if a merchant rejects an order or clicks to cancel it, then it is considered an abnormal fulfillment message. In reality, data generated by at least one of the following: order forward processing equipment, waybill center equipment, delivery center equipment, order reverse processing equipment, inventory change processing equipment, and distribution resource center equipment, will also be entered into the real-time data warehouse.

[0049] Furthermore, in subsequent steps, historical abnormal data associated with the first reverse order is collected. According to the set collection rules, the corresponding historical abnormal data is queried from the real-time data warehouse or related historical abnormal data is obtained from the interfaces of other business domains to determine whether the merchant control conditions are met. The merchant control conditions can be understood as the matching characteristics of the rules contained in the abnormal event strategy.

[0050] Step S102: Based on the first abnormal event strategy determined by the first reverse order, determine that the first store to which the first reverse order belongs matches the target merchant set associated with the first abnormal event strategy, and generate the first negative control work order for the first store.

[0051] The first abnormal event strategy is associated with one or more rules, and the rules include matching features and corresponding control actions.

[0052] An abnormal event strategy, in particular, includes one or more rules for handling merchants or stores experiencing reverse fulfillment processes, enabling timely intervention to mitigate negative impacts on merchants. For example, the rules are used to match abnormal fulfillment information of the store to which the reverse order belongs; if a match is found, the corresponding intervention action is executed on that store. In implementation, an abnormal event strategy can include one or more sub-strategies, each of which can be associated with one or more rules. The intervention actions can be set based on the abnormal event strategy, or based on the sub-strategies; a finer granularity can be achieved by setting actions based on each individual rule.

[0053] This step involves determining that the first reverse order matches the first abnormal event strategy, and that the first store to which it belongs is within the user set where the strategy is effective. Then, a first negative control work order is generated for that store. In one implementation, determining the first abnormal event strategy matched by the first reverse order includes: determining the first abnormal event strategy matched by the first reverse order based on the strategy type and / or strategy priority. The strategy type is defined according to the scenario to which the abnormal event strategy applies. A corresponding strategy type can be defined when configuring abnormal event strategies or rules. For example, a strategy applied to a real-time metric scenario is an online strategy type; a strategy applied to an offline metric scenario corresponding to offline data is an offline strategy type. The online strategy type is used to control the store corresponding to the reverse order that has a reverse fulfillment process in the real-time metric scenario; the offline strategy type is used to control the store that has a reverse fulfillment process recorded in the offline metric scenario. The strategy priority refers to the order in which various strategies are compared during the process of determining the specific abnormal event strategy matched by the reverse order. For example, if the first reverse order is an order from online data, then the online strategy type will be matched first. Then, the online strategy type will be compared one by one according to priority to determine the first matching abnormal event strategy. The online strategy type is used to regulate the stores corresponding to reverse orders that have reverse fulfillment processes in real-time indicator scenarios.

[0054] In this embodiment, a matching abnormal event strategy can also be determined based on the abnormal behavior and / or abnormal factors that trigger the reverse fulfillment process. Specifically, determining the matching first abnormal event strategy based on the first reverse order includes: determining the abnormal behavior and / or abnormal factors that trigger the reverse fulfillment process of the first reverse order, and determining the matching first abnormal event strategy based on the abnormal behavior and / or abnormal factors. If monitoring is performed on stores where a reverse fulfillment process occurs in offline data, then an abnormal event strategy of the matching offline strategy type is determined based on the abnormal behavior and / or abnormal factors that trigger the negative (i.e., negative) reverse fulfillment process of that store. Further, the relevant data on the reverse fulfillment process in the offline data based on the store dimension (or merchant dimension) is categorized, and the reverse fulfillment process of each store is further categorized according to the triggering cause (i.e., abnormal behavior or abnormal factors), thereby determining the priority reverse fulfillment processes for each store, and determining the specific matching abnormal event strategy for the triggering cause of the priority reverse fulfillment process.

[0055] Of course, in the absence of conflict, the matching abnormal event strategy can be determined based on the strategy type and / or strategy priority, and the matching abnormal event strategy can be determined based on the abnormal behavior and / or abnormal factors that trigger the reverse performance process. The two matching methods can be implemented in combination.

[0056] Since each event exception policy operation involves identifying whether a merchant is in the target merchant set, to improve identification efficiency, an HBase database is used to store merchant information. Data is quickly located using a key, and the value can be set to 0 or 1 to indicate whether the merchant is on the blacklist or whitelist. Specifically, this includes: setting merchants in the whitelist or timed whitelist of the first exception event policy based on the HBase database, using a value of 0 or 1 in the key-value pair to identify whether the merchant is in the whitelist or timed whitelist; the merchants include the first store; correspondingly, determining whether the first store to which the first reverse order belongs matches the target merchant set associated with the first exception event policy includes: querying the value corresponding to the key corresponding to the first store to determine whether the first store is a merchant in the whitelist or timed whitelist. If the first store is a merchant in the whitelist or timed whitelist, then if the first store meets the matching characteristics of the policy rule, the control action is executed; otherwise, the rule matching and rule control action are not executed on the first store.

[0057] In this embodiment, a pre-configured exception event policy is applied to the merchant set. To reduce storage pressure, sub-policies applied to the same merchant set are associated with the same exception event policy, and the exception event policy is associated with the merchant set.

[0058] Step S103: Set the delayed execution timing for the rules associated with the first abnormal event strategy for the first negative control work order.

[0059] In this embodiment, it is necessary to statistically analyze historical abnormal data associated with the first reverse order over a certain period. Based on the statistical data of this historical abnormal data, it is determined whether it matches the matching characteristics of the rules in the first abnormal event strategy. If a match is found, the regulatory action of that rule is executed. The historical abnormal data associated with the first reverse order refers to abnormal data within the same time window as the first reverse order. The granularity of the time window is not limited, such as within the same day or the same week. For example, the number of times a reverse fulfillment process caused by the same or similar abnormal behavior or abnormal factors as the first reverse order occurs within a day or a week is counted. The number of occurrences per unit time or the number of consecutive occurrences per unit time is calculated. If the matching characteristics are met, such as five consecutive instances of reverse fulfillment due to merchant order rejection, the regulatory action of the rule is executed. Historical data includes historical abnormal data, which can be data stored in a real-time data warehouse.

[0060] In practice, a series of events occurring in chronological order that affect the fulfillment progress during the fulfillment process constitute timeline events. Taking order fulfillment in a food delivery scenario as an example, events such as user payment, merchant order acceptance, merchant order notification, and rider order acceptance are timeline events. The same event that triggers a reverse fulfillment process and occurs within the reverse fulfillment process can be consumed by both the merchant control system and the real-time data warehouse. For example, when the merchant control system executes the method described above, both the merchant control system and the real-time data warehouse consume the abnormal event that triggers the reverse fulfillment process. After the merchant control system determines that the first reverse order matches the first abnormal event strategy, it queries the real-time data warehouse for historical abnormal data of the first store associated with the first reverse order. This requires ensuring that the real-time data warehouse has already processed the abnormal event. Furthermore, querying the real-time data warehouse for historical abnormal data of the first store associated with the first reverse order also takes time. To ensure a reasonable dependency between the merchant control system and the real-time data warehouse and to accommodate the time required for data queries, the method described in this embodiment also includes a delayed execution implementation. In one implementation, a delay mechanism provided by a message middleware is used, wherein setting the delayed execution timing of the rule associated with the first abnormal event strategy for the first negative control work order includes: treating the rule associated with the first abnormal event strategy for the first negative control work order as an event to be executed; processing the event to be executed using the message middleware, storing the event to be executed in a first delay queue, obtaining the delay duration of the delayed execution preset for the first abnormal event strategy, and setting the delay attribute of the first delay queue or setting the delay attribute of the event to be executed according to the delay duration of the delayed execution. In one implementation, the delay is achieved through a scheduled task. The step of setting the delayed execution timing for the rule associated with the first abnormal event strategy for the first negative control work order includes: treating the rule associated with the first abnormal event strategy for the first negative control work order as a pending event; processing the pending event using a message middleware; storing the pending event in a second delay queue; obtaining the pre-set delay duration for the first abnormal event strategy; starting a scheduled task to process the second delay queue according to the delay duration; after the scheduled task starts, retrieving the pending event from the second delay queue; recreating a delayed execution message corresponding to the pending event and sending it to a target queue; the delayed execution message in the target queue carries the delayed pending event.

[0061] Step S104: Obtain historical abnormal data of the first store. At the delayed execution time, perform rule matching on the first negative control work order based on the rule associated with the first abnormal event strategy and the historical abnormal data. Perform corresponding control actions on the first store according to the execution result of the rule matching.

[0062] The aforementioned control actions refer to the control actions included in the pre-configured rules. In this embodiment, the purpose of executing the control actions is to manage merchants who frequently exhibit negative behavior. The control actions include, but are not limited to, notifications to merchants (such as SMS, outbound calls, pop-up reminders, etc.), penalties (such as demotion in search rankings, store closure, or being placed on busy lists), and other controls (such as increasing food preparation time or increasing user time).

[0063] This step involves performing rule matching and rule adjustment actions at the delayed execution time. The step of obtaining historical anomaly data for the first store includes: obtaining historical anomaly data from a real-time data warehouse and / or an external service domain based on the time window of the first reverse order matching; the historical anomaly data being historical data associated with the online data; clustering the obtained data according to the store dimension; and querying the historical anomaly data of the first store according to the first store to which the first reverse order belongs from the clustered data. The purpose of retrieving data based on the time window of the first reverse order matching is to statistically analyze historical anomaly data within the same time period as the first reverse order, using this as associated historical anomaly data, and determining whether it matches the matching characteristics of the rules in the first anomaly event strategy based on the statistical data of this historical anomaly data. The granularity of the time window is not limited, such as within the same day or the same week. For example, it can count the number of times a reverse fulfillment process caused by the same or similar abnormal behavior or abnormal factors as the first reverse order occurs in the data within a day or a week. Historical anomaly data can be data stored in a real-time data warehouse or data provided by an external domain service.

[0064] Furthermore, the rules associated with the first abnormal event strategy are used to perform rule matching on the first negative control work order based on the historical abnormal data. Based on the execution result of the rule matching, corresponding control actions are performed on the first store. This includes: if it is determined that the frequency of abnormal data occurring in the first store within the time window exceeds an abnormal frequency threshold or the number of consecutive abnormal data occurrences exceeds an abnormal number threshold, then the corresponding control action is executed. For example, the number of times a fulfillment reversal process occurs in the first store within the time window or within a unit of time within the time window, or the number of consecutive occurrences within a unit of time, is calculated. If the matching characteristics are met, such as five consecutive instances of fulfillment reversals due to merchant order rejection, then the rule control action is executed.

[0065] In this embodiment, it also includes: the historical abnormal data of the first store obtained based on the time window of the first reverse order matching includes the slow food preparation report information of the first store reporting slow food preparation; accordingly, if the number of consecutive occurrences of the slow food preparation report information of the first store within the time window exceeds the slow food preparation threshold, the corresponding control action is executed.

[0066] This embodiment also includes monitoring the reverse fulfillment process within offline data, specifically including: obtaining a second store exhibiting abnormal merchant behavior from offline data, and a second abnormal event strategy matching the abnormal data of the store; wherein, the second store refers to a store in the offline data where the responsible party for orders canceled or refunded during the fulfillment process is the merchant; generating a second negative control work order for the second store, and executing corresponding control actions on the second negative control work order based on the rules associated with the second abnormal event strategy. For example, statistical analysis is performed on offline data from the week or month adjacent to the current date, combined with the strategy type of the offline strategy, to calculate whether the matching characteristics of the rules set by the strategy are met. In implementation, the matching of abnormal event strategies can be performed in the offline data monitoring center to calculate the second store that needs to be controlled, and the data of the second store and the executed control actions can be sent to the merchant control system for direct control. For example, the offline data monitoring center calculates that stores with a merchant responsibility cancellation rate greater than 10% in the previous week are designated as the second stores that need to be controlled. The offline data monitoring center can obtain pre-configured abnormal event strategies through scheduled tasks and match them with the corresponding offline data.

[0067] Please refer to Figure 2The diagram illustrates the system environment for applying the data processing method, including: a merchant control system 201, a merchant client 202, an order and waybill message middleware 203, an implementation data warehouse 204, an external domain service 205, and an offline data monitoring center 206. The offline data monitoring center can exist as a subsystem of the merchant control system or be separate from it. The merchant control system listens for merchant clicks to reject or cancel orders sent by the merchant client. This merchant action corresponds to a first reverse order, allowing the merchant control system to obtain relevant data for the first reverse order. The merchant control system monitors order forward data, waybill center data, delivery center data, order reverse data, inventory change data, and rider operation center data from the order and waybill message middleware, especially monitoring information on changes in the status of orders and waybills associated with the merchant. The real-time data warehouse listens to order forward data, waybill center data, delivery center data, order reverse data, inventory change data, and rider operation center data from the order and waybill message middleware. It then clusters and stores this data according to the store dimension. Therefore, the merchant control system and the real-time data warehouse may consume the same event transferred from the message middleware. The merchant control system implements delayed execution to ensure reasonable dependency in consuming the same event. The merchant control system queries the real-time data warehouse for historical anomaly data of the store to which the first reverse order belongs, especially anomaly data within the same time window as that reverse order. Alternatively, the merchant control system queries the interface of external domain services to obtain historical anomaly data. External domain services refer to other business domain services different from the merchant control system. Based on this historical anomaly data and the relevant data of the first reverse order, the merchant control system calculates the number of fulfillment anomalies within the time window or within a unit of time within the time window. If the matching characteristics of the rules are met, such as the merchant being reported by riders for slow food preparation twice consecutively, then the control action is executed. The offline data monitoring center can identify stores that match certain rules in offline data, such as a 10% cancellation rate for business liability insurance. It can then send these stores and their corresponding control actions to the merchant control system to implement control actions on the stores.

[0068] Please refer to this again. Figure 3The diagram illustrates a control process for a merchant control system, including: S301, Event Strategy Matching. Determine the first abnormal event strategy matched with the first reverse order. S302, Target Merchant Screening. Determine whether the first store to which the first reverse order belongs is a merchant in the target merchant set where the first abnormal event strategy is effective. If so, proceed to S303. S303, Generate a negative work order for the first store. S304, Register Delayed Execution Timing. Register a delayed execution timing based on the delay duration of the delayed execution of the first abnormal event strategy, or based on the delay duration of the delayed execution of a sub-strategy or rule within the strategy matched with the first store. S305, Perform Rule Matching at the Delayed Execution Timing. S306, If the matching characteristics of the rule are met, execute a control action on the first store.

[0069] The method provided in this embodiment can monitor the reverse fulfillment process in online data in real time, thereby enabling timely regulatory actions to be taken against merchants. Furthermore, it can also statistically analyze data of merchants experiencing reverse fulfillment processes based on offline data and execute regulatory actions against them. This achieves continuous monitoring of reverse fulfillment, identification of abnormal merchant data, and precise management of merchants.

[0070] This embodiment also includes the configuration and enabling of abnormal event policies and sub-policies. Specifically, it further includes: receiving configuration information for sub-policies, the configuration information including at least the delay duration for delayed execution, the matching characteristics of at least one rule, and the logical relationship between rules; associating sub-policies applied to the same merchant set with the same abnormal event policy, and associating the abnormal event policy with the merchant set; the abnormal event policy includes a first abnormal event policy; the merchant set includes the target merchant set. Correspondingly, in the matching of abnormal event strategies, determining the first abnormal event strategy matched based on the first reverse order includes: determining the target sub-strategy in the first abnormal event strategy matched based on the first reverse order; setting the delayed execution timing of the rules associated with the first abnormal event strategy for the first negative control work order includes: setting the delayed execution timing based on the delay duration of the delayed execution of the target sub-strategy; and performing rule matching on the first negative control work order based on the rules associated with the first abnormal event strategy according to the historical abnormal data, and performing corresponding control actions on the first store based on the execution result of the rule matching, includes: performing rule matching on the first negative control work order based on the rules associated with the target sub-strategy according to the historical abnormal data, and performing corresponding control actions on the first store based on the execution result of the rule matching. It should be noted that, unless otherwise specified, the features given in this embodiment and other embodiments of this application can be combined with each other, and steps S101 and S102 or similar terms do not limit the steps to be executed sequentially.

[0071] This concludes the description of the method provided in this embodiment. By delaying execution and using relevant historical anomaly data matching rules, the method enables timely and accurate monitoring of reversal of performance and timely and effective regulation of merchants, thereby improving the accuracy of reversal monitoring and the timeliness of regulation.

[0072] Based on the above embodiments, the second embodiment of this application provides another data processing method; please refer to the corresponding descriptions for relevant parts. The following is in conjunction with... Figure 4 and Figure 5 The method described herein is explained below. Please refer to [link / reference]. Figure 4 The data processing method shown in the figure includes:

[0073] Step S401: In response to triggering the configuration of a sub-policy, the sub-policy editing interface is displayed; the sub-policy editing interface is used to create new sub-policies or edit the information of existing sub-policies.

[0074] Step S402: Receive at least one of the following configuration information input in the sub-policy editing interface: sub-policy identifier, delay duration for delayed execution, matching characteristics of at least one rule, logical relationship between rules, and control action on rule matching under the corresponding sub-policy, and send the configuration information to the server so that the server generates a new sub-policy or changes the information of an existing sub-policy.

[0075] Step S403: In response to associating one or more configured sub-policies with the exception event policy, a rule refresh instruction is sent to the server, so that the server generates or refreshes the exception event policy according to the sub-policies.

[0076] Step S404: In response to applying the abnormal event policy to the merchant set, a policy application instruction is sent to the server, causing the server to establish an association between the abnormal event policy and the merchant set; the merchant set includes merchants whose fulfillment processes are to be monitored; the association is used to determine whether the merchant to which the reverse order belongs matches the merchant set associated with the abnormal event policy after determining the abnormal event policy for matching reverse orders; wherein, the reverse order refers to an order in which a reverse fulfillment process occurs in data providing online services or offline data, and the reverse fulfillment process refers to a fulfillment exception handling process triggered by an abnormal event occurring during the fulfillment process.

[0077] The data processing method provided in this embodiment is applied to the management client of a merchant control system. The server refers to the server of the merchant control system. The management client receives input configuration information and sends it to the server, which generates the configured policy. Furthermore, the server makes the policy effective on the merchant set according to the application policy instructions sent by the management client. It can also specify the effective time period for the abnormal event policy on the corresponding merchant set. Specifically, it includes: receiving information about the effective time period of the input abnormal event policy, whereby the server determines the abnormal event policy for reverse order matching based on the effective time period of the abnormal event policy.

[0078] In this embodiment, the logical relationship between the rules under the sub-policy can be "or" and / or "and".

[0079] Please refer to Figure 5 The diagram illustrates a configuration example, including: a policy configuration interface 501, which provides an example of sub-policy configuration. This interface includes configuring policy names, policy IDs, and other policy identifiers; selecting associated configured sub-policies or rules; specifying the effective period; and selecting the merchant set to apply to, etc. The merchant set refers to the merchants selected on the merchant set page, or a specified whitelist or timed whitelist, etc. It is understandable that... Figure 5 The elements shown are merely illustrative, and their size, layout, appearance, etc., do not constitute a limitation on the method described in this application.

[0080] This concludes the description of the method provided in this embodiment. The method offers a scheme for configuring and applying abnormal event strategies. The configured information is used to implement the detected delayed execution of performance reversals and to perform rule matching using relevant historical abnormal data. This helps to achieve timely and accurate monitoring of performance reversals during the performance process and to make timely and effective adjustments to merchants.

[0081] Corresponding to the first embodiment, the third embodiment of this application provides a data single processing device; for related parts, please refer to the description of the corresponding method embodiment. Figure 6 The data processing apparatus shown in the figure includes:

[0082] The online data acquisition unit 601 is used to acquire relevant data of the first reverse order in the online data where a reverse fulfillment process has occurred; wherein, the reverse fulfillment process refers to the fulfillment anomaly handling process triggered by an abnormal event in the fulfillment process;

[0083] The strategy matching unit 602 is used to determine the first abnormal event strategy matched according to the first reverse order, determine that the first store to which the first reverse order belongs matches the target merchant set associated with the first abnormal event strategy, and generate the first negative control work order for the first store.

[0084] The delayed execution unit 603 is used to set the delayed execution timing of the rule associated with the first abnormal event strategy for the first negative control work order;

[0085] The control unit 604 is used to acquire historical abnormal data of the first store, and at the delayed execution time, perform rule matching on the first negative control work order based on the rule associated with the first abnormal event strategy according to the historical abnormal data, and perform corresponding control actions on the first store according to the execution result of the rule matching.

[0086] Optionally, the delayed execution unit 603 is specifically used to: take the rule associated with the execution of the first abnormal event strategy for the first negative control work order as the event to be executed; process the event to be executed using a message middleware, store the event to be executed in a first delay queue, obtain the delay duration of the delayed execution preset for the first abnormal event strategy, and set the delay attribute of the first delay queue or the delay attribute of the event to be executed according to the delay duration of the delayed execution.

[0087] Optionally, the delayed execution unit 603 is specifically used to: take the rule associated with the first abnormal event strategy for the first negative control work order as the event to be executed; process the event to be executed using a message middleware, store the event to be executed in a second delayed queue, obtain the delay duration of the delayed execution preset for the first abnormal event strategy, start a timed task to process the second delayed queue according to the delay duration, after the timed task starts, retrieve the event to be executed from the second delayed queue, recreate a delayed execution message corresponding to the event to be executed and send it to a target queue, and the delayed execution message in the target queue carries the delayed event to be executed.

[0088] Optionally, the control unit 604 is further configured to: obtain a second store with abnormal merchant behavior from offline data, and a second abnormal event strategy matching the abnormal data of the store; wherein, the second store refers to a store in the offline data where the responsible party for an order that has been cancelled or refunded during the fulfillment process is the merchant; generate a second negative control work order for the second store, and perform corresponding control actions on the second negative control work order based on the rules associated with the second abnormal event strategy.

[0089] Optionally, the online data acquisition unit 601 is specifically used for: acquiring abnormal order requests provided by the merchant client, acquiring corresponding order data and merchant abnormal behavior data based on the abnormal order requests, as relevant data for the first reverse order; and / or, monitoring fulfillment messages generated by at least one of the order forward processing equipment, waybill center equipment, delivery center equipment, order reverse processing equipment, inventory change processing equipment, and distribution resource center equipment, and identifying abnormal fulfillment messages carrying merchant abnormal behavior data; or, monitoring abnormal fulfillment messages generated by at least one of the above-mentioned equipment; using the order data corresponding to the abnormal fulfillment message as the first reverse order, and the order data and merchant abnormal behavior data as relevant data for the first reverse order.

[0090] Optionally, the abnormal performance message includes: order status change information caused by order cancellation or refund after payment is completed, and / or waybill status change information caused by waybill cancellation or refund after waybill generation; the online data acquisition unit 601 is specifically used to: if it is determined that the order status change information and / or the waybill status change information are related to merchant behavior, then the order data corresponding to the abnormal performance message is taken as the first reverse order.

[0091] Optionally, the control unit 604 is specifically used to: obtain historical abnormal data from a real-time data warehouse and / or an external service domain based on the time window of the first reverse order matching, wherein the historical abnormal data is historical data associated with the online data; cluster the obtained data according to the store dimension, and query the historical abnormal data of the first store from the clustered data according to the first store to which the first reverse order belongs.

[0092] Optionally, the control unit 604 is specifically used to: if it is determined that the frequency of abnormal data occurring in the first store within the time window exceeds the abnormal frequency threshold or the number of consecutive abnormal data occurrences exceeds the abnormal number threshold, then execute the corresponding control action.

[0093] Optionally, the device further includes a configuration unit, which is configured to: receive configuration information for a sub-policy, the configuration information including at least a delay duration for delayed execution, a matching feature of at least one rule, and a logical relationship between rules; associate sub-policies applied to the same merchant set with the same abnormal event policy, and associate the abnormal event policy with the merchant set; the abnormal event policy includes a first abnormal event policy; and the merchant set includes the target merchant set.

[0094] Optionally, the strategy matching unit 602 is specifically used to: determine the target sub-strategy in the first abnormal event strategy matched according to the first reverse order; the delayed execution unit 603 is specifically used to: set the delayed execution timing according to the delay duration of the delayed execution of the target sub-strategy; the control unit 604 is specifically used to: perform rule matching on the first negative control work order based on the rules associated with the target sub-strategy and the historical abnormal data, and perform corresponding control actions on the first store according to the execution result of the rule matching.

[0095] Optionally, the policy matching unit 602 is specifically used to: set merchants in the whitelist or timed whitelist of the first abnormal event policy based on the HBase database, and use the value of 0 or 1 in the key-value pair to identify whether the merchant is a merchant in the whitelist or timed whitelist; the merchant includes the first store; query the value corresponding to the key corresponding to the first store to determine whether the first store is a merchant in the whitelist or timed whitelist.

[0096] Corresponding to the second embodiment, the fourth embodiment of this application provides another data single-processing device; for relevant parts, please refer to the description of the corresponding method embodiment. Figure 7 The data processing apparatus shown in the figure includes:

[0097] The configuration interface unit 701 is used to display the sub-strategy editing interface in response to the triggering of the configuration sub-strategy; the sub-strategy editing interface is used to create new sub-strategies or edit the information of existing sub-strategies.

[0098] The configuration information input unit 702 is used to receive at least one of the following configuration information input in the sub-policy editing interface: sub-policy identifier, delay duration of delayed execution, matching characteristics of at least one rule, logical relationship between rules and control action on rule matching under the corresponding sub-policy, and send the configuration information to the server so that the server generates a new sub-policy or changes the information of an existing sub-policy.

[0099] The sub-policy association unit 703 is used to send a rule refresh instruction to the server in response to associating one or more configured sub-policies with an exception event policy, so that the server generates or refreshes the exception event policy according to the sub-policy.

[0100] The strategy application unit 704 is used to send a strategy application instruction to the server in response to applying the abnormal event strategy to the merchant set, so that the server establishes an association between the abnormal event strategy and the merchant set; the merchant set includes merchants whose fulfillment processes are to be monitored; the association is used to determine whether the merchant to which the reverse order belongs matches the merchant set associated with the abnormal event strategy after determining the abnormal event strategy for the reverse order; wherein, the reverse order refers to an order in the data or offline data that is providing online services and has a reverse fulfillment process, and the reverse fulfillment process refers to the fulfillment exception handling process triggered by an abnormal event in the fulfillment process.

[0101] Optionally, the configuration information input unit 701 is further configured to: receive information on the effective period of the input abnormal event policy, wherein the effective period is used by the server to determine the abnormal event policy for reverse order matching based on the effective period of the abnormal event policy.

[0102] The fifth embodiment of this application provides a merchant control system for performance monitoring. Please refer to [link / reference]. Figure 8 The merchant control system for performance monitoring shown in the figure includes: an online data monitoring subsystem 801, a historical data acquisition subsystem 802 associated with the online data, and a control subsystem 803; wherein,

[0103] The online data monitoring subsystem is used to listen for abnormal fulfillment messages of canceled or refunded orders initiated by merchant clients, and / or to listen for abnormal fulfillment messages related to merchant behavior transmitted by message middleware; and to obtain the order data corresponding to the abnormal fulfillment messages as the first reverse order.

[0104] The historical data acquisition subsystem associated with online data is used to provide historical abnormal data associated with online data based on a time window matched with the first reverse order;

[0105] The control subsystem is configured to: determine a first abnormal event strategy based on the first reverse order; determine that the first store to which the first reverse order belongs matches the target merchant set associated with the first abnormal event strategy; generate a first negative control work order for the first store; set a delayed execution time for executing the rules associated with the first abnormal event strategy for the first negative control work order; obtain historical abnormal data of the first store based on historical abnormal data provided by the historical data acquisition subsystem associated with online data; at the delayed execution time, perform rule matching on the first negative control work order based on the rules associated with the first abnormal event strategy and the historical abnormal data; and perform corresponding control actions on the first store based on the execution result of the rule matching.

[0106] The system provided in this embodiment further includes an offline data monitoring subsystem; wherein, the offline data monitoring subsystem is used to identify a second store with abnormal merchant behavior based on offline data, determine a matching second abnormal event strategy based on the abnormal merchant behavior data of the second store, determine that the second store matches a second set of merchants associated with the second abnormal event strategy, and send the information of the second store and the second abnormal event strategy to the control subsystem; correspondingly, the control subsystem is also used to generate a second negative control work order for the second store based on the information of the second store and the second abnormal event strategy; determine that the second abnormal event strategy is an offline type strategy, and perform corresponding control actions on the second store based on the rules associated with the second abnormal event strategy.

[0107] It should be noted that the features given in this embodiment and other embodiments can be combined with each other without conflict.

[0108] This concludes the description of the system provided in this embodiment. The system is used to monitor the reverse fulfillment process occurring in online data, implement delayed execution, and use relevant historical abnormal data for rule matching. This enables timely and accurate monitoring of the reverse fulfillment process and timely and effective regulation of the corresponding merchants.

[0109] Based on the above embodiments, the sixth embodiment of this application provides an electronic device. For relevant parts, please refer to the corresponding descriptions in the above embodiments. Figure 9 The electronic device shown in the figure includes a memory 901 and a processor 902; the memory is used to store a computer program, which, after being run by the processor, executes the method provided in the embodiments of this application.

[0110] Based on the above embodiments, the seventh embodiment of this application provides a computer storage medium. For relevant parts, please refer to the corresponding descriptions in the above embodiments. The schematic diagram of the computer storage medium is similar. Figure 9 The memory in the figure can be understood as the storage medium. The computer storage medium stores computer execution instructions, which, when executed by a processor, are used to implement the method provided in the embodiments of this application.

[0111] In a typical configuration, an electronic device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0112] Memory may include non-persistent storage 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.

[0113] 1. Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information by 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, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by electronic devices. As defined herein, computer-readable media does not include non-transitory computer-readable media, such as modulated data signals and carrier waves.

[0114] 2. 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.

[0115] Although this application discloses preferred embodiments as described above, it is not intended to limit this application. Any person skilled in the art can make possible changes and modifications without departing from the spirit and scope of this application. Therefore, the scope of protection of this application should be determined by the scope defined in the claims of this application.

Claims

1. A data processing method, characterized in that, include: Acquire relevant data of the first reverse order in the online data where a reverse fulfillment process occurs; wherein, the reverse fulfillment process refers to the fulfillment anomaly handling process triggered by an abnormal event during the fulfillment process, and the abnormal event is an order cancellation or refund event caused by abnormal merchant behavior; the abnormal merchant behavior includes any merchant behavior such as merchant not accepting orders, maliciously refusing orders, merchant canceling or refunding, or the store being closed after the rider arrives at the store; Based on the first reverse order, determine the first abnormal event strategy that is matched, determine that the first store to which the first reverse order belongs matches the target merchant set associated with the first abnormal event strategy, and generate the first negative control work order for the first store. Set a delayed execution timing for the rule associated with the first abnormal event strategy for the first negative control work order; wherein, the abnormal event is the same event consumed by the merchant control system and the real-time data warehouse that can execute the method, and the delayed execution timing is set according to the reasonable dependency between the merchant control system and the real-time data warehouse on consuming the same event and the data query time requirement; Historical abnormal data of the first store is obtained from the real-time data warehouse. At the delayed execution time, the rule associated with the first abnormal event strategy is used to perform rule matching on the first negative control work order based on the historical abnormal data. According to the execution result of the rule matching, the corresponding control action is performed on the first store. This includes: if it is determined that the frequency of abnormal data occurring in the first store within the time window of the first reverse order matching exceeds the abnormal frequency threshold or the number of consecutive abnormal data occurrences exceeds the abnormal number threshold, then the corresponding control action is performed at the delayed execution time. The control action includes any of the following actions: notification to the merchant, demotion of search ranking, store closure, busy status, increase of food preparation time, and increase of user time.

2. The method according to claim 1, characterized in that, The setting of the delayed execution timing for the rule associated with the first abnormal event strategy for the first negative control work order includes: The rule associated with the first abnormal event strategy for the first negative control work order will be used as the event to be executed; The application message middleware processes the event to be executed, stores the event to be executed in the first delay queue, obtains the delay duration for delayed execution preset for the first abnormal event strategy, and sets the delay attribute of the first delay queue or sets the delay attribute of the event to be executed according to the delay duration for delayed execution.

3. The method according to claim 1, characterized in that, The setting of the delayed execution timing for the rule associated with the first abnormal event strategy for the first negative control work order includes: The rule associated with the first abnormal event strategy for the first negative control work order will be used as the event to be executed; The application message middleware processes the pending event, stores the pending event in the second delay queue, obtains the delay duration preset for the first abnormal event strategy, starts a timed task to process the second delay queue according to the delay duration, retrieves the pending event from the second delay queue after the timed task starts, recreates the delayed execution message corresponding to the pending event and sends it to the target queue, the delayed execution message in the target queue carries the delayed pending event.

4. The method according to claim 1, characterized in that, Also includes: The system retrieves a second store from offline data that exhibits abnormal merchant behavior, and a second abnormal event strategy that matches the abnormal data of the second store. The second store refers to a store in the offline data where the merchant is the responsible party for orders that have been cancelled or refunded during the fulfillment process, resulting in a reverse fulfillment process. A second negative control work order is generated for the second store, and the corresponding control action is executed on the second negative control work order based on the rules associated with the second abnormal event strategy.

5. The method according to claim 1, characterized in that, The acquisition of relevant data for the first reverse order in the online data where a reverse fulfillment process occurs includes: Obtain abnormal order requests from the merchant's client, and based on these abnormal order requests, obtain the corresponding order data and merchant abnormal behavior data as relevant data for the first reverse order; and / or, Monitor fulfillment messages generated by at least one of the following: order forward processing equipment, waybill center equipment, delivery center equipment, order reverse processing equipment, inventory change processing equipment, and distribution resource center equipment; identify abnormal fulfillment messages that carry abnormal merchant behavior data; or monitor abnormal fulfillment messages generated by at least one of the above-mentioned equipment. The order data corresponding to the abnormal performance message is used as the first reverse order, and the order data and the merchant's abnormal behavior data are used as the relevant data of the first reverse order.

6. The method according to claim 5, characterized in that, The abnormal performance messages include: order status change information caused by order cancellation or refund after payment is completed, and / or waybill status change information caused by waybill cancellation or refund after waybill generation; The step of using the order data corresponding to the abnormal fulfillment message as the first reverse order includes: If it is determined that the order status change information and / or the waybill status change information are related to the merchant's behavior, then the order data corresponding to the abnormal fulfillment message is taken as the first reverse order.

7. The method according to claim 1, characterized in that, The step of obtaining historical abnormal data of the first store from the real-time data warehouse includes: Based on the time window of the first reverse order matching, historical abnormal data is obtained from the real-time data warehouse, and the historical abnormal data is historical data associated with the online data; The acquired data is clustered according to the store dimension, and the historical abnormal data of the first store to which the first reverse order belongs is queried from the clustered data.

8. The method according to claim 1, characterized in that, Also includes: Receive configuration information for the sub-policy, the configuration information including at least the delay duration for delayed execution, the matching characteristics of at least one rule, and the logical relationship between the rules; Sub-policies applied to the same merchant set are associated with the same exception event policy, and the exception event policy is associated with the merchant set; the exception event policy includes a first exception event policy; the merchant set includes the target merchant set.

9. The method according to claim 8, characterized in that, The strategy for determining the first abnormal event matching based on the first reverse order includes: The target sub-strategy in the first abnormal event strategy matched with the first reverse order is determined; The setting of the delayed execution timing for the rule associated with the first abnormal event strategy for the first negative control work order includes: The delayed execution timing is set according to the delay duration of the delayed execution of the target sub-strategy; The rule based on the first abnormal event strategy association performs rule matching on the first negative control work order according to the historical abnormal data, and performs corresponding control actions on the first store according to the rule matching execution result, including: Based on the rules associated with the target sub-strategy, the first negative control work order is matched according to the historical abnormal data, and the corresponding control action is performed on the first store according to the execution result of the rule matching.

10. The method according to claim 1, characterized in that, Also includes: Merchants in the whitelist or timed whitelist of the first abnormal event policy are set based on the HBase database, and the value in the key-value pair is 0 or 1 to indicate whether the merchant is in the whitelist or timed whitelist; the merchant includes the first store. The step of determining whether the first store to which the first reverse order belongs matches the target merchant set associated with the first abnormal event strategy includes: Based on the key corresponding to the first store, query the value corresponding to that key to determine whether the first store is a merchant in the whitelist or timed whitelist.

11. A data processing method, characterized in that, include: In response to the triggering of a configuration sub-policy, the sub-policy editing interface is displayed; the sub-policy editing interface is used to create new sub-policies or edit the information of existing sub-policies. The sub-strategy editing interface receives at least one of the following configuration information: sub-strategy identifier, delay duration for delayed execution, matching characteristics of at least one rule, logical relationship between rules, and control actions for rule matching under the corresponding sub-strategy. The configuration information is then sent to the server, causing the server to generate a new sub-strategy or modify information about an existing sub-strategy. The control actions are executed at the delayed execution time when the frequency of abnormal data occurring within the time window of the reverse order matching for the store to which the reverse order to the sub-strategy belongs exceeds an abnormal frequency threshold or the number of consecutive abnormal data occurrences exceeds an abnormal number threshold. The control actions include any of the following: notification to the merchant, demotion in search ranking, store closure, busy status, increased food preparation time, and increased user time. In response to associating one or more configured sub-policies with an exception event policy, a rule refresh instruction is sent to the server, causing the server to generate or refresh the exception event policy according to the sub-policies; In response to applying the abnormal event policy to the merchant set, a policy application instruction is sent to the server, causing the server to establish an association between the abnormal event policy and the merchant set; the merchant set includes merchants whose fulfillment processes are to be monitored; the association is used to determine whether the merchant to which the reverse order belongs matches the merchant set associated with the abnormal event policy after determining the abnormal event policy for matching reverse orders; wherein, the reverse order refers to an order in which a reverse fulfillment process occurs in data providing online services or offline data, and the reverse fulfillment process... This refers to the fulfillment anomaly handling process triggered by abnormal events during the fulfillment process; wherein, the abnormal event is an order cancellation or refund event caused by abnormal merchant behavior; wherein, the abnormal event is the same event that can be consumed by the merchant control system and the real-time data warehouse, and the delay duration of the delayed execution is set according to the reasonable dependence between the merchant control system and the real-time data warehouse on consuming the same event and the data query time requirements; the abnormal merchant behavior includes any merchant behavior among merchant not accepting orders, maliciously refusing orders, merchant cancellation or refund, and the store being closed after the rider arrives at the store.

12. The method according to claim 11, characterized in that, Also includes: The system receives information about the effective period of the input exception event policy, which is used by the server to determine the exception event policy for reverse order matching based on the effective period of the exception event policy.

13. A data processing apparatus, characterized in that, include: The online data acquisition unit is used to acquire relevant data of the first reverse order in the online data where a reverse fulfillment process occurs; wherein, the reverse fulfillment process refers to the fulfillment anomaly handling process triggered by an abnormal event during the fulfillment process, and the abnormal event is an order cancellation or refund event caused by abnormal merchant behavior; the abnormal merchant behavior includes any merchant behavior such as merchant not accepting orders, maliciously refusing orders, merchant canceling or refunding orders, and the store being closed after the rider arrives at the store; The strategy matching unit is used to determine the first abnormal event strategy matched based on the first reverse order, determine that the first store to which the first reverse order belongs matches the target merchant set associated with the first abnormal event strategy, and generate the first negative control work order for the first store. The delayed execution unit is used to set the delayed execution timing of the rules associated with the first abnormal event strategy for the first negative control work order; wherein, the abnormal event is the same event consumed by the merchant control system and the real-time data warehouse that can be used for performance monitoring, and the delayed execution timing is set according to the reasonable dependency between the merchant control system and the real-time data warehouse on consuming the same event and the data query time requirement; The control unit is used to obtain historical abnormal data of the first store from the real-time data warehouse, and at the delayed execution time, perform rule matching on the first negative control work order based on the rules associated with the first abnormal event strategy and the historical abnormal data, and perform corresponding control actions on the first store according to the execution result of the rule matching; including: if it is determined that the abnormal frequency of abnormal data occurring in the first store within the time window of the first reverse order matching exceeds the abnormal frequency threshold or the number of consecutive abnormal data occurrences exceeds the abnormal number threshold, then perform the corresponding control action at the delayed execution time; the control action includes any of the following actions: reaching and notifying the merchant, degrading search ranking, closing the store, setting the store to busy, increasing the food preparation time, and increasing the user time.

14. A data processing apparatus, characterized in that, include: The configuration interface unit is used to display the sub-policy editing interface in response to the triggering of the configuration sub-policy; The sub-strategy editing interface is used to create new sub-strategies or edit information about existing sub-strategies. The configuration information input unit is used to receive at least one of the following configuration information input in the sub-policy editing interface: sub-policy identifier, delay duration of delayed execution, matching characteristics of at least one rule, logical relationship between rules and control action on rule matching under the corresponding sub-policy, and send the configuration information to the server so that the server generates a new sub-policy or changes the information of an existing sub-policy. The sub-policy association unit is used to send a rule refresh instruction to the server in response to associating one or more configured sub-policies with an anomaly event policy, so that the server generates or refreshes the anomaly event policy according to the sub-policy; wherein, the control action is executed at a delayed execution time when the frequency of anomalies in the reverse order to which the store to which the reverse order to which the sub-policy belongs exceeds the anomaly frequency threshold or the number of consecutive anomalies in the reverse order to which the anomaly number exceeds the anomaly number threshold within the time window of the reverse order matching; the control action includes any of the following actions: reaching the merchant, degrading search ranking, closing the store, setting the store to busy, increasing the food preparation time, and increasing the user time; The strategy application unit is used to respond to applying the abnormal event strategy to the merchant set by sending a strategy application instruction to the server, causing the server to establish an association between the abnormal event strategy and the merchant set; the merchant set includes merchants whose fulfillment processes are to be monitored; the association is used to determine whether the merchant to which the reverse order belongs matches the merchant set associated with the abnormal event strategy after determining the abnormal event strategy for matching reverse orders; wherein, the reverse order refers to an order in which a reverse fulfillment process occurs in data providing online services or offline data, and the reverse fulfillment process This refers to the fulfillment anomaly handling process triggered by an abnormal event during the fulfillment process; wherein, the abnormal event is an order cancellation or refund event caused by abnormal merchant behavior; wherein, the abnormal event is the same event consumed by the merchant control system and the real-time data warehouse that can be used for fulfillment monitoring, and the delay duration of the delayed execution is set according to the reasonable dependence between the merchant control system and the real-time data warehouse on consuming the same event and the data query time requirements; the abnormal merchant behavior includes any merchant behavior among not accepting orders, maliciously refusing orders, canceling or refunding orders, and the store being closed after the rider arrives at the store.

15. A merchant control system for performance monitoring, characterized in that, include: The system includes an online data monitoring subsystem, a historical data acquisition subsystem associated with online data, and a control subsystem; among which, The online data monitoring subsystem is used to listen for abnormal fulfillment messages of canceled or refunded orders caused by abnormal merchant behavior; obtain the order data corresponding to the abnormal fulfillment message as the first reverse order; the abnormal event corresponding to the first reverse order is an order cancellation event or a refund event, and the abnormal event is the same event that can be consumed by the merchant control system and the real-time data warehouse; the abnormal merchant behavior includes any merchant behavior such as merchant not accepting orders, maliciously refusing orders, merchant canceling or refunding orders, and the store being closed after the rider arrives at the store. The historical data acquisition subsystem associated with online data is used to provide historical abnormal data associated with online data based on a time window matched with the first reverse order; The control subsystem is configured to: determine a matching first abnormal event strategy based on the first reverse order; determine if the first store to which the first reverse order belongs matches the target merchant set associated with the first abnormal event strategy; generate a first negative control work order for the first store; set a delayed execution timing for executing the rules associated with the first abnormal event strategy for the first negative control work order, wherein the delayed execution timing is set based on the reasonable dependency between the merchant control system and the real-time data warehouse on consuming the same event and the time required for data querying; and obtain the first store's data from the real-time data warehouse based on historical abnormal data provided by the historical data acquisition subsystem associated with online data. Historical abnormal data, at the delayed execution time, based on the rules associated with the first abnormal event strategy, is used to perform rule matching on the first negative control work order according to the historical abnormal data, and corresponding control actions are performed on the first store according to the execution result of the rule matching; including: if it is determined that the frequency of abnormal data occurring in the first store within the time window of the first reverse order matching exceeds the abnormal frequency threshold or the number of consecutive abnormal data occurrences exceeds the abnormal number threshold, then the corresponding control action is performed at the delayed execution time; the control action includes any of the following actions: reaching and notifying the merchant, degrading search ranking, closing the store, setting the store to busy, increasing the food preparation time, and increasing the user time.

16. The system according to claim 15, characterized in that, Also includes: Offline data monitoring subsystem; among which, The offline data monitoring subsystem is used to identify a second store with abnormal merchant behavior based on offline data, determine a matching second abnormal event strategy based on the abnormal merchant behavior data of the second store, determine that the second store matches the second merchant set associated with the second abnormal event strategy, and send the information of the second store and the second abnormal event strategy to the control subsystem. The control subsystem is also used to generate a second negative control work order for the second store based on the information of the second store and the second abnormal event strategy. The second abnormal event strategy is determined to be an offline type strategy, and corresponding control actions are performed on the second store based on the rules associated with the second abnormal event strategy.

17. An electronic device, characterized in that, include: A memory and a processor; the memory is used to store a computer program, which, when executed by the processor, performs the method according to any one of claims 1-12.

18. A computer storage medium, characterized in that, The device stores computer execution instructions, which, when executed by a processor, are used to implement the method described in any one of claims 1-12.

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