Data processing method and device, electronic equipment and storage medium

Abstract

The present disclosure relates to a data processing method and device, electronic equipment and storage medium. The method comprises: in the case that the object identifier of the object to which the to-be-processed operation data belongs meets a preset condition, determining the data type of the to-be-processed operation data based on the data information of the to-be-processed operation data; obtaining historical cumulative processing information of a preset flow dimension corresponding to the data type; the historical cumulative processing information is obtained based on historical operation data processed by a first processing instruction; updating the historical cumulative processing information according to the to-be-processed operation data to obtain current cumulative processing information; and when the current cumulative processing information meets a threshold condition corresponding to the data type, processing the to-be-processed data by the first processing instruction. The method can control the cumulative processing information within a lower level range, so that the influence range when a problem occurs is controllable.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of Internet, and particularly relates to a data processing method and device, electronic equipment, storage medium and program product. BACKGROUND

[0002] In the project development process in the field of e-commerce after-sales, switching between two technical solutions is often needed, and in the switching process, the stability of the online system needs to be ensured to avoid loss as much as possible.

[0003] At present, when switching between two processing solutions of operation data, the commonly used method is generally based on user ID (Identity document, identity number) switching, such as setting users with the last three digits of ID in the 000-100 interval to adopt the new solution, and users with the last three digits of ID not in the 000-100 interval to adopt the old solution, that is, a certain percentage of users will adopt the new solution. However, the granularity of this switching method is large, and when the new solution has a problem, the operation data processed by the new solution will also have a problem, which cannot guarantee the controllability of the impact range. SUMMARY

[0004] The present disclosure provides a data processing method, device, electronic equipment, storage medium and program product to at least solve the technical problem that the switching method of the processing solution of data in the related art has large granularity and cannot guarantee the controllability of the impact range. The technical solution of the present disclosure is as follows:

[0005] According to a first aspect of an embodiment of the present disclosure, a data processing method is provided, comprising:

[0006] In a case where an object identifier of an object to which the operation data to be processed belongs meets a preset condition, determining a data type of the operation data to be processed based on data information of the operation data to be processed; the preset condition is that the object identifier is within a preset identifier range;

[0007] Obtaining historical cumulative processing information of a preset flow dimension corresponding to the data type; the historical cumulative processing information is obtained based on historical operation data processed by a first processing instruction;

[0008] Updating the historical cumulative processing information according to the operation data to be processed to obtain current cumulative processing information;

[0009] When the current cumulative processing information meets a threshold condition corresponding to the data type, processing the operation data to be processed by the first processing instruction.

[0010] In an example embodiment, the determining the data type of the to-be-processed operation data based on the data information of the to-be-processed operation data comprises:

[0011] determining an initial type of the to-be-processed operation data under a preset attribute based on the data information of the to-be-processed operation data;

[0012] performing a combination processing on each of the initial types to obtain the data type of the to-be-processed operation data.

[0013] In an example embodiment, the determining the initial type of the to-be-processed operation data under a preset attribute based on the data information of the to-be-processed operation data comprises:

[0014] determining information corresponding to each of the attributes from the data information of the to-be-processed operation data;

[0015] determining the initial type of the to-be-processed operation data under each of the attributes according to the information corresponding to each of the attributes and a classification condition corresponding to each of the attributes.

[0016] In an example embodiment, the preset flow-dimension has a plurality of dimensions, and the updating the historical cumulative processing information based on the to-be-processed operation data to obtain a current cumulative processing information comprises:

[0017] updating the historical cumulative processing information of each of the preset flow-dimensions based on the to-be-processed operation data to obtain a current cumulative processing information corresponding to each of the preset flow-dimensions;

[0018] The method further comprises:

[0019] when the current cumulative processing information corresponding to each of the preset flow-dimensions meets a threshold condition corresponding thereto, processing the to-be-processed operation data by using the first processing instruction.

[0020] In an example embodiment, the method further comprises:

[0021] when an object identifier of an object to which the to-be-processed operation data belongs does not meet the preset condition, or the current cumulative processing information does not meet a threshold condition corresponding to the data type, processing the to-be-processed operation data by using a second processing instruction.

[0022] In an example embodiment, after processing the to-be-processed operation data by using the first processing instruction, the method further comprises:

[0023] updating the current cumulative processing information as a new historical cumulative processing information corresponding to the data type;

[0024] Determine a processing instruction for processing next operation data of the data type based on the new historical cumulative processing information.

[0025] According to a second aspect of the embodiments of the present disclosure, a data processing apparatus is provided, comprising:

[0026] A type determining unit configured to determine a data type of the operation data to be processed based on data information of the operation data to be processed when an object identifier of an object to which the operation data to be processed belongs meets a preset condition; the preset condition is that the object identifier is within a preset identifier range;

[0027] An information obtaining unit configured to obtain historical cumulative processing information of a preset flow dimension corresponding to the data type; the historical cumulative processing information is obtained based on historical operation data processed by a first processing instruction;

[0028] An information updating unit configured to update the historical cumulative processing information based on the operation data to be processed to obtain current cumulative processing information;

[0029] A first processing unit configured to process the operation data to be processed by the first processing instruction when the current cumulative processing information meets a threshold condition corresponding to the data type.

[0030] In an example embodiment, the type determining unit is further configured to determine initial types of the operation data to be processed under a plurality of preset attributes based on the data information of the operation data to be processed; and perform combination processing on each of the initial types to obtain the data type of the operation data to be processed.

[0031] In an example embodiment, the type determining unit is further configured to determine information corresponding to each of the attributes from the data information of the operation data to be processed; and determine initial types of the operation data to be processed under each of the attributes based on the information corresponding to each of the attributes and classification conditions corresponding to each of the attributes.

[0032] In an example embodiment, the preset flow dimension has a plurality of flow dimensions, and the information updating unit is further configured to update historical cumulative processing information of each of the flow dimensions based on the operation data to be processed to obtain current cumulative processing information corresponding to each of the flow dimensions;

[0033] The first processing unit is further configured to process the operation data to be processed by the first processing instruction when the current cumulative processing information corresponding to each of the flow dimensions meets a threshold condition corresponding to each of the flow dimensions.

[0034] In an example embodiment, the apparatus further comprises a second processing unit configured to perform processing of the to-be-processed operation data by a second processing instruction when the object identifier of the object to which the to-be-processed operation data belongs does not meet the preset condition, or the current cumulative processing information does not meet the threshold condition corresponding to the data type.

[0035] In an example embodiment, the apparatus further comprises an instruction determination unit configured to perform determination of a new historical cumulative processing information corresponding to the data type by taking the current cumulative processing information as the new historical cumulative processing information; and determination of a processing instruction for processing of next to-be-processed operation data belonging to the data type based on the new historical cumulative processing information.

[0036] According to a third aspect of embodiments of the present disclosure, an electronic device is provided, comprising:

[0037] a processor;

[0038] a memory for storing instructions executable by the processor;

[0039] wherein the processor is configured to execute the instructions to implement the method according to any one of the preceding aspects.

[0040] According to a fourth aspect of embodiments of the present disclosure, a computer-readable storage medium is provided, when instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to perform the method according to any one of the preceding aspects.

[0041] According to a fifth aspect of embodiments of the present disclosure, a computer program product is provided, the computer program product comprises instructions, when the instructions are executed by a processor of an electronic device, the electronic device is enabled to perform the method according to any one of the preceding aspects.

[0042] The technical solutions provided by the embodiments of the present disclosure at least bring the following beneficial effects:

[0043] In the case where the object identifier of the object to which the to-be-processed operation data belongs meets the preset condition, the data type of the to-be-processed operation data is determined based on the data information of the to-be-processed operation data, and then the historical cumulative processing information of the preset flow dimension corresponding to the data type is obtained. The current cumulative processing information obtained by updating the historical cumulative processing information according to the to-be-processed operation data is compared with the threshold condition corresponding to the data type, so as to determine which processing instruction is used to process the to-be-processed operation data. The method controls the flow granularity at the preset flow dimension, and controls the processing information in a lower level range by setting the data type and the threshold condition, so that the influence range when a problem occurs is controllable.

[0044] It should be understood that the general description and the following detailed description are only exemplary and explanatory, and are not intended to limit the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0045] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and serve to explain the principles of the present disclosure, and do not limit the present disclosure.

[0046] Figure 1 is a flowchart of a data processing method according to an exemplary embodiment.

[0047] Figure 2 is a flowchart of a data type determination step according to an exemplary embodiment.

[0048] Figure 3 is a flowchart of a data processing method according to another exemplary embodiment.

[0049] Figure 4 is a flowchart of a resource return order processing method according to an exemplary embodiment.

[0050] Figure 5 is a structural block diagram of a data processing apparatus according to an exemplary embodiment.

[0051] Figure 6 is a block diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0052] In order for those skilled in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be described clearly and completely below with reference to the drawings.

[0053] It should be noted that the implementations described in the following exemplary embodiments do not represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0054] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present disclosure described herein can be implemented in an order other than that illustrated or described herein. It should also be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for display, analyzed data, etc.) involved in the present disclosure are all information and data authorized by the user or authorized by all parties.

[0055] In an exemplary embodiment, as shown in Figure 1 A data processing method is provided, and the present embodiment is exemplified by applying the method to a terminal. It should be understood that the method can also be applied to a server, and can also be applied to a system including a terminal and a server, and can be realized through the interaction of the terminal and the server. The terminal can be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers, Internet of Things devices, and portable wearable devices. The Internet of Things device can be a smart speaker, a smart television, a smart air conditioner, a smart vehicle device, etc. The portable wearable device can be a smart watch, a smart bracelet, a head-mounted device, etc. The server can be realized by an independent server or a server cluster composed of multiple servers. In the present embodiment, the method includes the following steps:

[0056] In step S110, in a case where the object identifier of the object to which the to-be-processed operation data belongs meets a preset condition, the data type of the to-be-processed operation data is determined based on the data information of the to-be-processed operation data; the preset condition is that the object identifier is within a preset identifier range.

[0057] The operation data refers to data of a resource withdrawal operation for a target resource transfer, such as a resource return order, and the to-be-processed operation data can be a to-be-processed resource return order.

[0058] The object identifier is a unique identifier of the object, for example, the object identifier can be ID400234614661.

[0059] The data information can include various types of information, for example, the data information can include transferred resources, returned resources, transferred resource time, returned time, component information of the transferred resources, etc.

[0060] The data type is determined based on the data information, and the data type can be composed of multiple attributes, which can specifically include "whether to return all resources", "whether to return after resource transfer", "whether to include additional resources", and "include discount type", etc.

[0061] The preset identification range can be a value range of several digits of the object identification, for example, the preset identification range is a range of the last two digits of the object identification: 00-30, and the preset condition can be that the last two digits of the object identification are in the interval (00, 30).

[0062] In a specific implementation, when the terminal receives the to-be-processed operation data, the object identification of the object to which the to-be-processed operation data belongs can be acquired first, and it is determined whether the object identification meets the preset condition, that is, whether the object identification is in the preset identification range. When it is confirmed that the object identification is in the preset identification range, the data type of the to-be-processed operation data is determined based on the initial type of the data information of the to-be-processed operation data under the preset multiple attributes.

[0063] More specifically, the preset multiple attributes can include: “whether to return all resources”, “whether to return after resource transfer”, “whether to contain additional resources”, and “containing discount type”, and a data type composed of the initial type under each attribute can be “return all resources & return after resource transfer & contain additional resources & contain platform discount”.

[0064] In step S120, the historical cumulative processing information corresponding to the preset flow dimension of the data type is acquired; the historical cumulative processing information is obtained based on historical operation data processed by the first processing instruction.

[0065] The preset flow dimension can include at least one of returned resources and the number of operation data, and correspondingly, the historical cumulative processing information can be the sum of returned resources of the historical operation data processed by the first processing instruction, or the total number of the historical operation data.

[0066] In a specific implementation, taking a preset flow dimension as an example, after the data type of the to-be-processed operation data is determined, according to a preset statistical period, a plurality of historical operation data processed by the first processing instruction is acquired from a starting time point of the current period to a current time point, and processing information of each historical operation data under the preset flow dimension is determined. The processing information of each historical operation data under the preset flow dimension is summed up to obtain the historical cumulative processing information of the historical operation data under the preset flow dimension, as the historical cumulative processing information corresponding to the data type of the to-be-processed operation data.

[0067] For example, when the preset flow dimension is returned resources, the historical cumulative processing information is the cumulative returned resources of the historical operation data processed by the first processing instruction. The returned resources of each historical operation data can be determined from the data information, the sum of the returned resources corresponding to each historical operation data is calculated, and the sum is taken as the historical cumulative processing information of the returned resource flow dimension corresponding to the data type of the to-be-processed operation data.

[0068] When the preset dimension of flow cutting is the number of operation data, the historical cumulative processing information is the cumulative number of historical operation data processed by the first processing instruction, and the number of each operation data is 1. The total number of historical operation data can be calculated as the historical cumulative processing information of the data type corresponding operation data number dimension of the to-be-processed operation data.

[0069] In step S130, the historical cumulative processing information is updated according to the to-be-processed operation data to obtain current cumulative processing information.

[0070] In specific implementation, the processing information of the to-be-processed operation data in the preset dimension of flow cutting can be determined first, and then the sum of the processing information and the historical cumulative processing information is calculated as the current cumulative processing information of the data type of the to-be-processed operation data, thereby updating the historical cumulative processing information.

[0071] For example, the historical cumulative processing information is a, and the processing information of the to-be-processed operation data in the preset dimension of flow cutting is b. The current cumulative processing information can be represented as: a+b.

[0072] It can be understood that when there are multiple preset dimensions of flow cutting, the historical cumulative processing information of each corresponding dimension of flow cutting is updated according to the processing information of the to-be-processed operation data in each dimension of flow cutting, to obtain the current cumulative processing information corresponding to each dimension of flow cutting.

[0073] In step S140, when the current cumulative processing information meets the threshold condition corresponding to the data type, the to-be-processed operation data is processed by the first processing instruction.

[0074] The threshold condition can be that the current cumulative processing information is less than a threshold value.

[0075] In specific implementation, different dimensions of flow cutting can correspond to different threshold values, and different data types can also correspond to different threshold values in the same dimension of flow cutting. In order to avoid the historical cumulative processing information of the historical operation data being equal to the threshold value, which leads to the to-be-processed operation data not meeting the threshold condition after processing, the historical cumulative processing information is updated according to the to-be-processed operation data to obtain the current cumulative processing information before comparing with the threshold condition. When the current cumulative processing information is less than the threshold value corresponding to the data type, it is determined that the current cumulative processing information meets the threshold condition corresponding to the data type, and then the to-be-processed operation data can be processed by the first processing instruction.

[0076] In the data processing method, in a case where the object identifier of the object to which the operation data to be processed belongs meets a preset condition, the data type of the operation data to be processed is determined based on the data information of the operation data to be processed, and then the historical accumulated processing information of the preset flow dimension corresponding to the data type is obtained. The current accumulated processing information obtained after the historical accumulated processing information is updated according to the operation data to be processed is compared with the threshold condition corresponding to the data type, so as to determine which processing instruction is used to process the operation data to be processed. The method controls the flow granularity at the preset flow dimension, and controls the processing information in a lower level range through the setting of the data type and the threshold condition, so that the influence range when a problem occurs is controllable.

[0077] In an example embodiment, as shown in FIG. 1, in step S110, the data type of the operation data to be processed is determined based on the data information of the operation data to be processed. Specifically, the following steps can be implemented: Figure 2

[0078] In step S110a, the initial type of the operation data to be processed under a plurality of preset attributes is determined based on the data information of the operation data to be processed.

[0079] In step S110b, the initial types are combined to obtain the data type of the operation data to be processed.

[0080] The plurality of preset attributes can include four attributes: whether to cancel all resources, whether to cancel after resource transfer, whether to contain additional resources, and whether to contain a discount type.

[0081] In a specific implementation, the information corresponding to each attribute can be determined from the data information of the operation data to be processed. The initial type of the operation data to be processed under each attribute is determined according to the information corresponding to each attribute and the classification condition corresponding to each attribute. Further, in order to ensure the accuracy of the representation result of the data type of the operation data to be processed, the initial types of the operation data to be processed under each attribute are combined, and the combined type is taken as the data type of the operation data to be processed.

[0082] For example, if the type of the operation data to be processed under the attribute "whether to cancel all resources" is "cancel all resources", the type under the attribute "whether to cancel after resource transfer" is "cancel before resource transfer", the type under the attribute "whether to contain additional resources" is "contain additional resources", and the type under the attribute "whether to contain a discount type" is "contain platform discount", then after the types under each attribute are combined, the data type of the operation data to be processed is "cancel all resources & cancel before resource transfer & contain additional resources & contain platform discount".

[0083] ​In the embodiment, by presetting multiple attributes, after determining the initial types of the to-be-processed operation data under each attribute based on the data information of the to-be-processed operation data, the initial types under each attribute are combined to represent the data type of the to-be-processed operation data, thereby realizing classification of the to-be-processed operation data from multiple angles, making the granularity of the obtained data type of the to-be-processed operation data finer, and ensuring quick fault positioning when a problem occurs in the switching process of the processing instruction.

[0084] Further, in an exemplary embodiment, the step S110a of determining the initial types of the to-be-processed operation data under the preset multiple attributes based on the data information of the to-be-processed operation data comprises: determining information corresponding to each attribute from the data information of the to-be-processed operation data; and determining the initial types of the to-be-processed operation data under each attribute according to the information corresponding to each attribute and the classification conditions corresponding to each attribute.

[0085] In a specific implementation, the initial types under different attributes need to be determined by different information, and therefore, before determining the initial types of the to-be-processed operation data under each attribute, information corresponding to each of the preset attributes needs to be determined from the data information of the to-be-processed operation data. More specifically, when the data information of the to-be-processed operation data comprises transferred resources, requested resources, transferred resource time, requested time, and component information of the transferred resources, the initial type under the attribute "whether to request all resources" can be determined by the transferred resources and the requested resources; the initial type under the attribute "whether to request after resource transfer" can be determined by the transferred resource time and the requested time; and the initial types under the attributes "whether to contain additional resources" and "containing discount type" can be determined by the component information of the transferred resources.

[0086] Further, after determining the information corresponding to each attribute in the data information of the operation data to be processed, the initial type of the operation data to be processed under each attribute can be determined according to the information corresponding to each attribute and the classification condition corresponding to each attribute. More specifically, for the attribute "whether to return all resources", the corresponding information is the transferred resources and the returned value, and the corresponding classification condition is: when the transferred resources are equal to the returned resources, the initial type is to return all resources; when the transferred resources are greater than the returned resources, the initial type is to return part of the resources. For the attribute "whether to return after resource transfer", the corresponding information is the transfer resource time, and the corresponding classification condition is: when the transfer resource time is earlier than the return time, the initial type is to return after resource transfer; otherwise, the initial type is to return before resource transfer. For the attribute "whether to contain additional resources", the corresponding information is the composition of the transferred resources, and the corresponding classification condition is: when the composition of the transferred resources contains additional resources, the initial type is to contain additional resources; otherwise, the initial type is not to contain additional resources. For the attribute "containing discount type", the corresponding information is the composition of the transferred resources, and the corresponding classification condition is: when the composition of the transferred resources contains platform discount resources, the initial type is to contain platform discounts; when the composition of the transferred resources contains distribution object discount resources, the initial type is to contain distribution object discounts; when the composition of the transferred resources does not contain any discount resources, the initial type is not to contain discounts.

[0087] In this embodiment, the initial type of the operation data to be processed under each attribute is determined by combining the information corresponding to each attribute determined from the operation data to be processed and the classification condition corresponding to each attribute, so as to determine the data type of the operation data to be processed according to each initial type, so that the granularity of the obtained data type of the operation data to be processed is finer, and subsequent fault positioning and loss control are facilitated.

[0088] In an exemplary embodiment, the preset flow cutting dimensions are multiple, and in the step S130, the historical cumulative processing information is updated according to the operation data to be processed to obtain the current cumulative processing information, including: updating the historical cumulative processing information of each flow cutting dimension respectively according to the operation data to be processed to obtain the current cumulative processing information corresponding to each flow cutting dimension.

[0089] The method further includes: when the current cumulative processing information corresponding to each flow cutting dimension all meets the threshold condition corresponding thereto, processing the operation data to be processed by the first processing instruction.

[0090] In a specific implementation, taking the number of returned resources and the number of operation data in the preset flow dimension as an example, the historical accumulated returned resources of the returned resource flow dimension can be updated according to the returned resources in the data information of the operation data to be processed, to obtain the current accumulated returned resources of the returned resource flow dimension, and the historical accumulated number of operation data of the number of operation data flow dimension can be updated according to the number of operation data to be processed, to obtain the current accumulated number of operation data of the number of operation data flow dimension.

[0091] Further, when the current returned resources corresponding to the returned resource flow dimension are less than the first threshold value corresponding to the returned resource flow dimension, and the current accumulated number of operation data corresponding to the number of operation data flow dimension is less than the second threshold value corresponding to the number of operation data flow dimension, the operation data to be processed is processed by the first processing instruction. On the contrary, when the current accumulated processing information corresponding to the returned resource flow dimension or the number of operation data flow dimension does not meet the corresponding threshold condition, the operation data to be processed is processed by the second processing instruction.

[0092] In this embodiment, by setting multiple categories of threshold limits for each data type, it can be ensured that at the initial stage of switching of the processing instruction, the level of the transferred resources of the switched operation data is reduced, so as to ensure that the loss is below a certain amount, thereby reducing the influence range to the minimum when the processing instruction fails.

[0093] In an exemplary embodiment, the above method further includes: when the object identifier of the object to which the operation data to be processed belongs does not meet the preset condition, or the current accumulated processing information does not meet the threshold value condition corresponding to the data type, processing the operation data to be processed by the second processing instruction.

[0094] In a specific implementation, when the object identifier of the object to which the operation data to be processed belongs meets the preset condition, i.e., the object identifier is within the preset identifier range, the technical solutions of steps S110-S140 are executed, and when the object identifier of the object to which the operation data to be processed belongs does not meet the preset condition, i.e., the object identifier is not within the preset identifier range, the operation data to be processed is processed by the second processing instruction.

[0095] In addition, in step S140, when the current accumulated processing information meets the threshold value condition corresponding to the data type of the operation data to be processed, the operation data to be processed is processed by the first processing instruction. On the contrary, when the current accumulated processing information does not meet the threshold value condition corresponding to the data type of the operation data to be processed, the operation data to be processed is processed by the second processing instruction.

[0096] Furthermore, when there are multiple preset flow-cutting dimensions, the data to be processed can be processed via a first processing instruction if the current cumulative processing information corresponding to each preset flow-cutting dimension meets its respective threshold condition. If the current cumulative processing information corresponding to at least one preset flow-cutting dimension does not meet its corresponding threshold condition, the data to be processed can be processed via a second processing instruction.

[0097] In this embodiment, the data to be processed is first divided into processing instructions based on preset conditions. If the data does not meet the preset conditions, it is processed by a second processing instruction. If the data meets the preset conditions, it is further judged. During the judgment process, the processing instructions are divided based on the threshold conditions of the data type. By further judging the data to be processed that meets the preset conditions, the smoothness of the switching of processing instructions is ensured.

[0098] In an exemplary embodiment, after processing the operation data to be processed by the first processing instruction in step S140, the method further includes: using the current cumulative processing information as new historical cumulative processing information corresponding to the data type; and determining the processing instruction for the next operation data to be processed belonging to the data type based on the new historical cumulative processing information.

[0099] In specific implementation, in order to ensure the real-time nature of historical cumulative processing information for various data types, after processing the data to be processed by the first processing instruction, it is also necessary to use the current cumulative processing information obtained after updating the processing of the data to be processed as the new historical cumulative processing information, so as to determine the processing instruction for the next data to be processed that belongs to the data type of the data to be processed based on the new historical cumulative processing information.

[0100] Furthermore, when there are multiple preset flow cutting dimensions, the current cumulative processing information corresponding to each preset flow cutting dimension is used as the new historical cumulative processing information for each flow cutting dimension. Based on the new historical cumulative processing information of each flow cutting dimension, the processing instruction for the next pending operation data belonging to the data type of pending operation data is determined.

[0101] In this embodiment, after the data to be processed is processed by the first processing instruction, the historical cumulative processing information corresponding to the data type of the data to be processed is updated in real time, so as to determine the processing instruction for the next data to be processed that belongs to the data type of the data to be processed based on the new historical cumulative processing information, and to ensure the accuracy of the determination result.

[0102] In another exemplary embodiment, such as Figure 3 The diagram shown is a flowchart illustrating a data processing method according to an exemplary embodiment. In this embodiment, the method includes the following steps:

[0103] In step S310, if the object identifier of the object to which the operation data to be processed belongs meets a preset condition, the initial type of the operation data to be processed under each attribute is determined based on the information corresponding to the operation data to be processed under the preset multiple attributes and the classification condition corresponding to each attribute.

[0104] In step S320, the initial types of the operation data to be processed under each attribute are combined to obtain the data type of the operation data to be processed.

[0105] In step S330, the historical cumulative processing information of each preset flow dimension corresponding to the data type is obtained, and the historical cumulative processing information is obtained based on historical operation data processed by the first processing instruction.

[0106] In step S340, the historical cumulative processing information of each flow dimension is updated according to the operation data to be processed, and the current cumulative processing information corresponding to each flow dimension is obtained.

[0107] In step S350a, when the current cumulative processing information corresponding to at least one flow dimension does not meet the corresponding threshold condition, the operation data to be processed is processed by the second processing instruction.

[0108] In step S350b, when the current cumulative processing information corresponding to each flow dimension meets the corresponding threshold condition, the operation data to be processed is processed by the first processing instruction.

[0109] In step S360, the current cumulative processing information is used as the new historical cumulative processing information corresponding to the data type.

[0110] In step S370, the new historical cumulative processing information is used to determine the processing instruction for the next operation data to be processed belonging to the data type.

[0111] The data processing method provided in the embodiment can ensure that the cumulative processing information under the preset flow dimension is set to a lower level at the initial stage of switching of the processing instruction, so as to ensure that the loss is below a certain amount and the influence range of the problem is minimized. On the other hand, by distinguishing the data types of the operation data, the system can be quickly located when a problem occurs, and the processing instruction can be switched for each data type, so that when a problem occurs in switching a certain data type, it can be quickly understood that the problem is caused by which attribute of the data, thereby quickly solving the problem. At the same time, since the switching of the processing instruction is for the data type, if type A has no problem and type B has a problem, only type B can be limited to use the second processing instruction for processing, and type A can still use the first processing instruction for processing, thereby ensuring the minimum range of rollback.

[0112] In an exemplary embodiment, in order to facilitate the understanding of the embodiments of the present application by those skilled in the art, the following will take the resource return order to be processed as an example, and the application examples of the accompanying drawings will be combined to specifically describe the present application. Figure 4 The flowchart of the resource return order processing method in an application example is shown in FIG. 1, and the processing flow is as follows: Figure 4 The flowchart of the resource return order processing method in an application example is shown in FIG. 1, and the processing flow is as follows:

[0113] (1) Obtain the user identifier (or user ID) of the user to which the resource return order to be processed belongs, and determine whether the user identifier is within a preset identifier range. Specifically, if the user identifier is not within the preset identifier range, the resource return order to be processed is directly processed by the old scheme (i.e., the second processing instruction); if the user identifier is within the preset identifier range, proceed to step (2) for fine-grained switching judgment of the new and old schemes (i.e., switching judgment of the first processing instruction and the second processing instruction).

[0114] (2) Determine the resource return order type of the resource return order to be processed according to the data information of the resource return order to be processed. The data information includes transferred resources, returned resources, transferred resource time, and composition information of the transferred resources. The resource return order type can be divided according to four attributes:

whether to return all resources

whether to return after resource transfer

whether to contain additional resources

whether to contain a discount type

[0115] (2a) For the attribute

whether to return all resources

[0116] (2b) For the attribute

whether to return after resource transfer

[0117] (2c) For the attribute

whether to contain additional resources

[0118] (2d) For the attribute

contains the discount type

[0119] Through the judgment logic of (2a)-(2d), the to-be-processed resource return order can be classified into one of the 24 resource return order types.

[0120] (3) According to the resource return order type to which the to-be-processed resource return order belongs, the pre-set redis (remote dictionary server, which is an open source database) is read to obtain the

historical cumulative number of orders

historical cumulative return resources

daily order number upper limit

daily return resource upper limit

[0121] Specifically, the

daily order number upper limit

daily return resource upper limit

daily order number upper limit

daily return resource upper limit

[0122] (4) According to the

historical cumulative number of orders

historical cumulative return resources

daily order number upper limit

daily return resource upper limit

[0123] Specifically, let the

daily order number upper limit

daily return resource upper limit

historical cumulative number of orders

historical cumulative return resources

[0124] If X1+1<=X and Y1+S<=Y, the new scheme is adopted to process the to-be-processed resource return order, otherwise, the old scheme is adopted to process the to-be-processed resource return order.

[0125] At the same time, in order to maintain the historical cumulative number of orders and the historical cumulative return resources of the day, if the new scheme is adopted, the redis (an open source database) needs to be updated, and X1’=X1+1, Y1’=Y1+S.

[0126] For example, for a resource return order of the type

return all resources & return before resource transfer & not contain additional resources & not contain preferential treatment

upper limit of daily number of orders

upper limit of daily returned resources

upper limit of daily number of orders

upper limit of daily returned resources

[0127] First order: transfer resources = 50, return resources = 50, transfer resource time is 2020.12.31, and return time is 2020.12.30.

[0128] Resource return order classification:

return all resources & return before resource transfer & not contain additional resources & not contain preferential treatment

historical cumulative number of orders

historical cumulative returned resources

[0129] Second order: transfer resources = 100, return resources = 100, transfer resource time is 2020.12.31, and return time is 2020.12.30.

[0130] Resource return order classification:

return all resources & return before resource transfer & not contain additional resources & not contain preferential treatment

historical cumulative number of orders

historical cumulative returned resources

[0131] Third order: transfer resources = 20, return resources = 20, transfer resource time is 2020.12.31, and return time is 2020.12.30.

[0132] Resource return order classification:

return all resources & return before resource transfer & not contain additional resources & not contain preferential treatment

historical cumulative number of orders

historical cumulative returned resources

[0133] Fourth order: transfer resources = 100, resource return order return resources = 100, transfer resource time is 2020.12.30, and return time is 2020.12.31.

[0134] Resource return order classification:

return all resources & return after resource transfer & not contain additional resources & not contain preferential treatment

historical cumulative number of orders

historical cumulative returned resources

[0135] The resource return order processing method provided in the embodiment has the following technical effects:

[0136] (1) Ensure the controllability of the capital loss. Through the limitation of the daily request for returning resources, it is ensured that the capital loss can be controlled below a certain amount in the initial stage of the switching of the old and new schemes, and the problem can be solved by limiting the daily request for returning resources to ten or one hundred levels, so as to minimize the impact range of the problem.

[0137] (2) Resource request for returning type scheme switching. Through the differentiation of the resource request for returning type, the problem can be quickly located when the system has a problem. Generally, each type of resource request for returning is switched step by step, and if there is a problem in switching a certain type, it can be quickly understood that which attribute of the resource request for returning causes the problem, so as to quickly solve the problem. At the same time, since the scheme switching is for the resource request for returning type, if type A has no problem and type B has a problem, type B can only use the old scheme, and type A can still use the new scheme, so as to ensure the minimum range of rollback.

[0138] It should be understood that, although each step in the flowchart involved in each embodiment as described above is displayed in sequence according to the arrow, these steps are not necessarily executed in sequence according to the arrow. Unless otherwise specified herein, the execution of these steps has no strict sequence limitation, and these steps can be executed in other orders. Moreover, at least part of the steps in the flowchart involved in each embodiment as described above can include multiple steps or stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution sequence of these steps or stages is not necessarily sequential, but can be executed in rotation or alternation with at least part of other steps or steps or stages in other steps.

[0139] It should be understood that the same / similar parts between each embodiment of the above method in the specification can be mutually referred to, and each embodiment focuses on the differences from other embodiments, and the related parts can be referred to the description of other method embodiments.

[0140] Based on the same inventive concept, the disclosure embodiments also provide a data processing apparatus for implementing the above-mentioned data processing method.

[0141] Figure 5 is a structural block diagram of a data processing apparatus according to an exemplary embodiment. Referring to Figure 5 , the apparatus comprises a type determination unit 510, an information acquisition unit 520, an information updating unit 530 and a first processing unit 540, wherein:

[0142] The type determining unit 510 is configured to determine the data type of the operation data to be processed based on the data information of the operation data to be processed when the object identifier of the object to which the operation data to be processed belongs meets a preset condition; the preset condition is that the object identifier is within a preset identifier range.

[0143] The information obtaining unit 520 is configured to obtain historical cumulative processing information of a preset cut-flow dimension corresponding to the data type; the historical cumulative processing information is obtained based on historical operation data processed by a first processing instruction.

[0144] The information updating unit 530 is configured to update the historical cumulative processing information according to the operation data to be processed to obtain current cumulative processing information.

[0145] The first processing unit 540 is configured to process the operation data to be processed by the first processing instruction when the current cumulative processing information meets a threshold condition corresponding to the data type.

[0146] In an example embodiment, the type determining unit 510 is further configured to determine initial types of the operation data to be processed under a plurality of preset attributes based on the data information of the operation data to be processed; and combine the initial types to obtain the data type of the operation data to be processed.

[0147] In an example embodiment, the type determining unit 510 is further configured to determine information corresponding to each attribute from the data information of the operation data to be processed; and determine initial types of the operation data to be processed under each attribute according to the information corresponding to each attribute and a classification condition corresponding to each attribute.

[0148] In an example embodiment, there are a plurality of preset cut-flow dimensions, and the information updating unit 530 is further configured to update the historical cumulative processing information of each cut-flow dimension according to the operation data to be processed to obtain current cumulative processing information corresponding to each cut-flow dimension.

[0149] The first processing unit 540 is further configured to process the operation data to be processed by the first processing instruction when the current cumulative processing information corresponding to each cut-flow dimension meets a threshold condition corresponding to each cut-flow dimension.

[0150] In an example embodiment, the apparatus further includes a second processing unit configured to process the operation data to be processed by a second processing instruction when the object identifier of the object to which the operation data to be processed belongs does not meet the preset condition, or when the current cumulative processing information does not meet the threshold condition corresponding to the data type.

[0151] In an exemplary embodiment, the apparatus further includes an instruction determination unit configured to perform determination of a processing instruction for the next operation data belonging to the data type based on the new historical cumulative processing information.

[0152] As to the apparatus in the above embodiments, the specific manners in which the respective modules perform operations have been described in detail in the embodiments of the method, and thus will not be described in detail here.

[0153] Figure 6 FIG. 6 is a block diagram of an electronic device 600 for implementing a data processing method according to an exemplary embodiment. The electronic device 600 can be, for example, a mobile phone, a computer, a digital broadcasting terminal, a message transmitting / receiving device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, or the like.

[0154] Referring to Figure 6 , the electronic device 600 can include one or more of the following components: a processing component 602, a memory 604, a power supply component 606, a multimedia component 608, an audio component 610, an input / output (I / O) interface 612, a sensor component 614, and a communication component 616.

[0155] The processing component 602 generally controls the overall operations of the electronic device 600, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 602 can include one or more processors 620 to execute instructions to complete all or part of steps of the above-described methods. In addition, the processing component 602 can include one or more modules to facilitate the interaction between the processing component 602 and other components. For example, the processing component 602 can include a multimedia module to facilitate the interaction between the multimedia component 608 and the processing component 602.

[0156] The memory 604 is configured to store various types of data to support the operations of the electronic device 600. Examples of these data include instructions for any application or method operating on the electronic device 600, contact data, phonebook data, messages, pictures, videos, and the like. The memory 604 can be implemented by any type of volatile or non-volatile storage devices or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disc, optical disc, or graphene memory.

[0157] The power component 606 provides power to the various components of the electronic device 600. The power component 606 can include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power for the electronic device 600.

[0158] The multimedia component 608 includes a screen providing an output interface between the electronic device 600 and a user. In some embodiments, the screen can include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes the touch panel, the screen can be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense a touch, a slide, and a gesture on the touch panel. The touch sensor can not only sense a boundary of a touching or a sliding action, but also detect duration and pressure related to the touching or sliding action. In some embodiments, the multimedia component 608 includes a front camera and / or a rear camera. When the electronic device 600 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera can receive external multimedia data. Each of the front camera and the rear camera can be a fixed optical lens system or have a focal length and optical zoom capability.

[0159] The audio component 610 is configured to output and / or input an audio signal. For example, the audio component 610 includes a microphone (MIC) configured to receive an external audio signal when the electronic device 600 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signal can be further stored in the memory 604 or transmitted via the communication component 616. In some embodiments, the audio component 610 also includes a speaker for outputting an audio signal.

[0160] The I / O interface 612 provides an interface between the processing component 602 and peripheral interface modules, which can be a keypad, a click wheel, buttons, and the like. The buttons can include, but are not limited to, a home button, a volume button, a start button, and a lock button.

[0161] The sensor component 614 includes one or more sensors for providing status assessments for various aspects of the electronic device 600. For example, the sensor component 614 can detect an open / closed position of the electronic device 600, relative positioning of components, such as a display and a keypad of the electronic device 600, a change in position of the electronic device 600 or a component of the electronic device 600, presence or absence of user contact with the electronic device 600, orientation or acceleration / deceleration / g-force and temperature of the electronic device 600. The sensor component 614 can include an optical sensor for detecting ambient light, a proximity sensor configured to detect proximity of an object, a motion sensor, a temperature sensor, a magnetic sensor, an acceleration sensor, a gyroscope sensor, a pressure sensor, or the like.

[0162] The communication component 616 is configured to facilitate wired or wireless communication between the electronic device 600 and other devices. The electronic device 600 can access a wireless network based on a corresponding communication standard, such as WiFi, a cellular network (e.g., 2G, 3G, 4G, or 5G), or a combination thereof. In an example embodiment, the communication component 616 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In an example embodiment, the communication component 616 further includes a Near Field Communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on Radio Frequency Identification (RFID) techniques, infrared data association (IrDA) techniques, ultra-wideband (UWB) techniques, Bluetooth (BT) techniques, and other techniques.

[0163] In an example embodiment, the electronic device 600 can be implemented using one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, micro-controllers, microprocessors, or other electronic elements to perform the above-described methods.

[0164] In an example embodiment, a computer-readable storage medium, such as the memory 604 including instructions stored thereon, is also provided. The instructions may, for example, be executable by the processor 620 of the electronic device 600 to perform the above-described methods. The computer-readable storage medium can be, for example, a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disc, and an optical data storage device, among others.

[0165] In an example embodiment, a computer program product is also provided, which comprises instructions executable by the processor 620 of the electronic device 600 to perform the above method.

[0166] It should be noted that the above apparatus, electronic device, computer readable storage medium, computer program product and the like according to the description of the method embodiments can also include other implementation manners, and the specific implementation manners can be referred to the description of the related method embodiments, which will not be repeated here.

[0167] Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the concepts disclosed herein. The disclosure is intended to cover any variations, uses or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice in the art to which the disclosure pertains. The specification and examples are to be regarded as illustrative only, and the true scope and spirit of the disclosure are indicated by the appended claims.

[0168] It should be understood that the present disclosure is not limited to the precise structures herein described and illustrated in the drawings, and that various modifications and changes can be made without departing from the scope thereof. The scope of the present disclosure is limited only by the claims that follow.

Claims

1. A data processing method, characterized by, The method comprises the following steps: In a case where an object identifier of an object to which the to-be-processed operation data belongs meets a preset condition, data information of the to-be-processed operation data under a plurality of preset attributes is respectively classified and processed, so as to obtain a data type of the to-be-processed operation data; the preset condition is that the object identifier is within a preset identifier range; the to-be-processed operation data at least comprises a to-be-processed resource return order; the plurality of attributes at least comprise whether all resources are returned, whether resources are transferred and then returned, whether additional resources are included, and a discount type included; An aggregate of processing information of historical operation data under a preset flow dimension and processed by a first processing instruction is obtained as historical cumulative processing information of the data type corresponding to the preset flow dimension; The preset flow dimension comprises at least one of returned resources and a number of operation data; The historical cumulative processing information is updated according to the to-be-processed operation data, so as to obtain current cumulative processing information; When the current cumulative processing information meets a threshold condition corresponding to the data type, the to-be-processed operation data is processed by the first processing instruction; The method further comprises: when the object identifier of the object to which the to-be-processed operation data belongs does not meet the preset condition, or the current cumulative processing information does not meet the threshold condition corresponding to the data type, the to-be-processed operation data is processed by a second processing instruction.

2. The method of claim 1, wherein, The method further comprises: Based on the data information of the to-be-processed operation data under each attribute, an initial type of the to-be-processed operation data under each attribute is determined; Each initial type is combined and processed, so as to obtain the data type of the to-be-processed operation data.

3. The method of claim 2, wherein, The method further comprises: Information corresponding to each attribute is respectively determined from the data information of the to-be-processed operation data; According to the information corresponding to each attribute and a classification condition corresponding to each attribute, an initial type of the to-be-processed operation data under each attribute is determined.

4. The method of claim 1, wherein, There are a plurality of preset flow dimensions, and the method further comprises: According to the to-be-processed operation data, historical cumulative processing information of each preset flow dimension is respectively updated, so as to obtain current cumulative processing information corresponding to each preset flow dimension. The method further comprises: When the current cumulative processing information corresponding to each preset flow dimension meets a threshold condition corresponding to each preset flow dimension, the to-be-processed operation data is processed by the first processing instruction.

5. The method of claim 1, wherein, After the to-be-processed operation data is processed by the first processing instruction, the method further comprises: The current cumulative processing information is taken as new historical cumulative processing information corresponding to the data type. Based on the new historical cumulative processing information, a determination of a processing instruction for a next to-be-processed operation data belonging to the data type is performed.

6. A data processing apparatus, characterized by, The method comprises: a type determination unit configured to perform classification processing on data information of the to-be-processed operation data under a plurality of preset attributes respectively in a case where an object identifier of an object to which the to-be-processed operation data belongs meets a preset condition, to obtain a data type of the to-be-processed operation data; the preset condition is that the object identifier is within a preset identifier range; the to-be-processed operation data at least comprises a to-be-processed resource return order; the plurality of attributes at least comprise whether all resources are returned, whether the resource is transferred and then returned, whether additional resources are included, and a discount type included; an information acquisition unit configured to perform acquisition of a sum of processing information of historical operation data under a preset flow dimension processed by a first processing instruction as historical cumulative processing information of the data type corresponding to the preset flow dimension; the preset flow dimension comprises at least one of a returned resource and a number of operation data; an information updating unit configured to perform updating of the historical cumulative processing information according to the to-be-processed operation data to obtain current cumulative processing information; a first processing unit configured to perform processing of the to-be-processed operation data by the first processing instruction when the current cumulative processing information meets a threshold condition corresponding to the data type; The device further comprises a second processing unit configured to perform processing of the to-be-processed operation data by a second processing instruction when an object identifier of an object to which the to-be-processed operation data belongs does not meet the preset condition, or when the current cumulative processing information does not meet the threshold condition corresponding to the data type.

7. The apparatus of claim 6, wherein, The type determination unit is further configured to perform determination of an initial type of the to-be-processed operation data under the plurality of preset attributes based on data information of the to-be-processed operation data; combination processing of each of the initial types is performed to obtain the data type of the to-be-processed operation data.

8. The apparatus of claim 7, wherein, The type determination unit is further configured to perform determination of information corresponding to each of the attributes from the data information of the to-be-processed operation data; and determination of an initial type of the to-be-processed operation data under each of the attributes according to the information corresponding to each of the attributes and a classification condition corresponding to each of the attributes.

9. The apparatus of claim 6, wherein, There are a plurality of preset flow dimensions, and the information updating unit is further configured to perform updating of historical cumulative processing information of each of the preset flow dimensions according to the to-be-processed operation data to obtain current cumulative processing information corresponding to each of the preset flow dimensions; The first processing unit is further configured to perform processing of the to-be-processed operation data by the first processing instruction when the current cumulative processing information corresponding to each of the preset flow dimensions meets a threshold condition corresponding to each of the preset flow dimensions.

10. The apparatus of claim 6, wherein, The device further comprises an instruction determination unit configured to perform determination of the current cumulative processing information as new historical cumulative processing information corresponding to the data type. Based on the new historical cumulative processing information, a determination is made of a processing instruction for next operation data of the data type.

11. An electronic device, comprising: Comprise: a processor; a memory for storing instructions executable by the processor; wherein the processor is configured to execute the instructions to implement the data processing method of any one of claims 1 to 5.

12. A computer-readable storage medium, characterized in that, When the instructions in the computer-readable storage medium are executed by the processor of the electronic device, the electronic device is enabled to perform the data processing method of any one of claims 1 to 5.

13. A computer program product, comprising instructions therein, wherein the computer program product is, The instructions are executed by the processor of the electronic device, and the electronic device is enabled to perform the data processing method of any one of claims 1 to 5.

Images