Point issuing method and device based on task engine, equipment and storage medium

Abstract

The invention provides an integral issuing method and device based on a task engine, equipment and a storage medium. The method comprises the following steps: determining a flow action and an action element corresponding to each to-be-processed flow; constructing a traffic set based on a plurality of to-be-processed traffic corresponding to the same traffic action, and determining a target task set; determining a target task corresponding to the target traffic from the target task set based on any traffic set; and performing integral issuing operation on the corresponding target traffic based on the task integral of the target task. According to the technical scheme provided by the embodiment of the invention, the preset task can be allocated to different candidate task sets according to the task action, the matching is executed once according to the flow action to determine the target task set corresponding to the to-be-processed flow, and the target task can be determined by executing traversal in the target task set. The number of traversal times of the to-be-processed traffic is reduced, so that resource occupation is reduced, and the system jamming risk is reduced.

Description

Technical Field

[0001] The present invention relates to the field of big data technology, and in particular to a task engine-based points distribution method, device, equipment, and storage medium. Background Art

[0002] Currently, property management companies are offering a growing number of internet services to property owners, such as e-commerce services within property management apps or multimedia entertainment services like videos. These companies typically implement various reward points rules within their systems. When user behavior meets these rules, points are awarded to the corresponding user account, thereby increasing user retention.

[0003] Common user behaviors include checking in, browsing interfaces, and watching videos. User behavior is primarily measured through user traffic. After the system records each piece of user traffic, it matches the user behavior analyzed from the traffic with the points reward rules. Each piece of user traffic is likely to match multiple points reward rules. For example, a piece of traffic that stays on the current page for a period of time after checking in can trigger both points rewards for checking in and points rewards for continuous online time. Therefore, when there are a large number of active users, the amount of user traffic is very large. In related technologies, user traffic can only traverse all points reward rules one by one, occupying a large amount of system resources and easily causing system lag and affecting the user experience. Summary of the Invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art. To this end, the present invention proposes a method, device, equipment, and storage medium for issuing points based on a task engine, which can reduce the system resources occupied by issuing points through the task engine and improve the user experience.

[0005] In a first aspect, an embodiment of the present invention provides a method for issuing points based on a task engine, which is applied to a task engine, wherein the task engine includes multiple candidate task sets, each of the candidate task sets includes multiple preset tasks, each of the preset tasks is provided with a task action, a task condition, and a task point, and the task actions of the preset tasks in the same candidate task set are the same. The method includes:

[0006] Acquire multiple flows to be processed, and determine the flow actions and action elements corresponding to each of the flows to be processed, wherein the action elements include action time and / or action times, and the number of the flow actions is at least 1;

[0007] Based on any of the traffic actions, a traffic set is constructed based on the corresponding plurality of to-be-processed traffic flows, and a target task set of the traffic set is determined from the plurality of candidate task sets, wherein the task action of the target task set matches the traffic action;

[0008] Based on any of the flow sets, determining a target task corresponding to a target flow from the target task set, wherein the action element of the target flow satisfies the task condition of the target task;

[0009] Based on the task points of the target task, a points distribution operation is performed for the corresponding target traffic.

[0010] According to some embodiments of the present invention, before obtaining a plurality of to-be-processed flows, the method further includes:

[0011] In response to selecting any one of the task actions, constructing a task configuration interface based on a score field and a plurality of preset condition fields, wherein each of the condition fields corresponds to a different action element;

[0012] In response to an input operation in the task configuration interface, constructing the task condition based on the field input information corresponding to each of the condition fields, and obtaining the task points entered in the points field;

[0013] The preset task is constructed based on the selected task action, the constructed task condition, and the input task points, and the preset task is associated with the candidate task set corresponding to the task action.

[0014] According to some embodiments of the present invention, each of the preset tasks is preset with a task identifier, and the task conditions include a conditional time and a task number. After determining the target task corresponding to the target flow from the target task set, the method further includes:

[0015] Based on any of the traffic sets, determining at least one preceding traffic in the to-be-processed traffic and a candidate task corresponding to the preceding traffic, wherein the action time of the preceding traffic is shorter than the condition time of the candidate task, or the number of actions of the preceding traffic is less than the number of tasks of the candidate task;

[0016] Based on the action element of the front traffic, updating the identification content corresponding to the task identification of the candidate task in the corresponding user account;

[0017] When the identification content meets the task condition of the candidate task, the preceding traffic is determined as the target traffic, and the candidate task is determined as the target task.

[0018] According to some embodiments of the present invention, performing a points distribution operation for the corresponding target traffic based on the task points of the target task includes:

[0019] When the task number of the target task is 1, the task points are distributed to the user account corresponding to the target traffic;

[0020] Alternatively, when the task number of the target task is greater than 1, the task points are distributed to the user account corresponding to the target traffic based on the preset allocation strategy of the target task;

[0021] The allocation strategy includes at least one of the following:

[0022] Splitting the task points into a plurality of sub-points, and performing a point distribution operation based on the sub-points each time the preset task is determined as the candidate task;

[0023] After the preset task is determined as the target task, a points distribution operation is performed based on the task points.

[0024] According to some embodiments of the present invention, after determining the target task set of the traffic set from the plurality of candidate task sets, the method further includes:

[0025] Creating a corresponding processing process for each target task set;

[0026] Based on any of the processing processes, a first processing thread is created, and a second processing thread corresponding to each of the target tasks is created;

[0027] inputting the target traffic to the second processing thread corresponding to the target task through the first processing thread;

[0028] The points issuing operation is performed based on each of the second processing threads.

[0029] According to some embodiments of the present invention, each candidate task set is further preset with a plurality of candidate gain coefficients, each candidate gain coefficient corresponds to a different account level, and the points distribution operation is performed based on each second processing thread, including:

[0030] determining a target gain coefficient from the candidate gain coefficients based on the account level of the user account of each target flow;

[0031] determining a target integral based on the task integral and the target gain coefficient;

[0032] The target points are distributed to the user account corresponding to the target traffic.

[0033] According to some embodiments of the present invention, the task engine is in communication with an application system and a database, the traffic to be processed is generated by the application system and stored in the database, and obtaining a plurality of traffic to be processed includes:

[0034] When it is detected that the resource usage of the application system is less than a preset resource threshold, and the time interval between the current moment and the reference moment is greater than or equal to a preset time threshold, all of the to-be-processed traffic is obtained from the database, wherein the reference moment is the moment when the last points issuance operation was completed;

[0035] Alternatively, when the number of the pending traffic stored in the database is greater than a preset threshold, the target number is determined based on the current resource occupancy rate, and the pending traffic is obtained from the database based on the target number, wherein the resource occupancy rate is inversely proportional to the target number.

[0036] In the second aspect, an embodiment of the present invention provides a points issuance device based on a task engine, comprising at least one control processor and a memory for communicating with the at least one control processor; the memory stores instructions that can be executed by the at least one control processor, and the instructions are executed by the at least one control processor so that the at least one control processor can execute the points issuance method based on the task engine as described in the first aspect above.

[0037] In a third aspect, an embodiment of the present invention provides an electronic device comprising the task engine-based points distribution device as described in the second aspect above.

[0038] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are used to execute the task engine-based points distribution method as described in the first aspect above.

[0039] According to the embodiment of the present invention, the points issuance method based on the task engine has at least the following beneficial effects: obtaining multiple to-be-processed flows, determining the flow actions and action elements corresponding to each of the to-be-processed flows, wherein the action elements include action time and / or action times, and the number of the flow actions is at least 1; based on any of the flow actions, constructing a flow set based on the corresponding multiple to-be-processed flows, determining the target task set of the flow set from the multiple candidate task sets, wherein the task actions of the target task set match the flow actions; based on any of the flow sets, determining the target task corresponding to the target flow from the target task set, wherein the action elements of the target flow meet the task conditions of the target task; and performing point issuance operations for the corresponding target flow based on the task points of the target task. According to the technical solution of the embodiment of the present invention, the preset tasks can be assigned to different candidate task sets according to the task actions, and a match is first performed according to the flow action to determine the target task set corresponding to the to-be-processed flow, and the target task can be determined by performing a traversal within the target task set, thereby reducing the number of traversals of the to-be-processed flows, reducing the resource occupation when issuing points, and reducing the risk of system freezes. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 This is a schematic diagram of the principle of a points distribution method based on a task engine provided by one embodiment of the present invention;

[0041] Figure 2 is a flowchart of a method for issuing points based on a task engine provided by another embodiment of the present invention;

[0042] Figure 3 is a complete flow chart of a points distribution method based on a task engine provided by another embodiment of the present invention;

[0043] Figure 4 It is a structural diagram of a points distribution device based on a task engine provided in another embodiment of the present invention. DETAILED DESCRIPTION

[0044] The following describes embodiments of the present invention in detail. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended only to explain the present invention and are not to be construed as limiting the present invention.

[0045] In the description of the present invention, it should be understood that descriptions involving orientations, such as up, down, front, back, left, right, etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, they cannot be understood as limitations on the present invention.

[0046] In the description of the present invention, "several" means one or more, "many" means more than two, "greater than," "less than," and "exceed" are understood to exclude the number itself, while "above," "below," and "within" are understood to include the number itself. The use of "first" and "second" in the description is solely for the purpose of distinguishing technical features and should not be construed as indicating or implying relative importance, implicitly specifying the number of the indicated technical features, or implicitly specifying the order of the indicated technical features.

[0047] In the description of the present invention, unless otherwise clearly defined, terms such as setting, installing, and connecting should be understood in a broad sense, and technicians in the relevant technical field can reasonably determine the specific meanings of the above terms in the present invention based on the specific content of the technical solution.

[0048] An embodiment of the present invention provides a method, apparatus, device, and storage medium for issuing points based on a task engine, wherein the method for issuing points based on a task engine includes: obtaining multiple flows to be processed, determining the flow actions and action elements corresponding to each of the flows to be processed, wherein the action elements include action time and / or action times, and the number of flow actions is at least 1; based on any of the flow actions, constructing a flow set based on the corresponding multiple flows to be processed, and determining a target task set of the flow set from multiple candidate task sets, wherein the task action of the target task set matches the flow action; based on any of the flow sets, determining the target task corresponding to the target flow from the target task set, wherein the action element of the target flow satisfies the task conditions of the target task; and performing a points issuance operation for the corresponding target flow based on the task points of the target task. According to the technical solution of the embodiment of the present invention, the preset tasks can be assigned to different candidate task sets according to the task actions, and a match is first performed according to the traffic action to determine the target task set corresponding to the traffic to be processed. The target task can be determined by performing traversal within the target task set, which reduces the number of traversals of the traffic to be processed, reduces the resource occupation when points are issued, and reduces the risk of system freezes.

[0049] The following is based on the Figure 1 The principle schematic diagram shown further illustrates the technical solution of the embodiment of the present invention.

[0050] It should be noted that the technical solution of this embodiment is applied to the task engine, which includes multiple candidate task sets. Each candidate task set includes multiple preset tasks. Each preset task is set with task actions, task conditions and task points. The task actions of each preset task in the same candidate task set are the same.

[0051] In this embodiment, each point reward rule is set as a preset task. When a pending traffic can meet the preset task, the task points can be issued. The task points of each preset task can be set according to actual needs and are not limited here.

[0052] It is worth noting that both task actions and traffic actions are used to characterize user behaviors, such as common login, check-in, ad viewing, order generation, and content forwarding. The candidate task set is constructed from multiple preset tasks with the same task actions, such as Figure 1 As shown, the preset tasks include signing in every day and signing in three times a week. The candidate task set constructed for the task action of "signing in" is task set 1. Similarly, for the task action of "watching ads", different preset tasks correspond to different task conditions (watching time). Each preset task is added to task set 2, and so on.

[0053] Reference Figure 2 , Figure 2 A flowchart of a method for issuing points based on a task engine is provided in an embodiment of the present invention. The method for issuing points based on a task engine includes but is not limited to the following steps:

[0054] S10, obtaining multiple flows to be processed, and determining the flow actions and action elements corresponding to each flow to be processed, wherein the action elements include action time and / or action times, and the number of flow actions is at least 1.

[0055] It should be noted that the pending traffic can be saved in the database and can be input into the task engine in batches during the idle time period of the application system. After the task engine obtains multiple pending traffic, it parses and determines the traffic action and action elements of each pending traffic. This operation cannot be omitted. Therefore, improving the utilization of system resources needs to be achieved by reducing the number of traversals of each pending traffic.

[0056] When parsing the traffic to be processed, this embodiment distinguishes between traffic actions and action elements. The action elements include action time and / or action count. Taking the traffic action of watching videos or browsing web pages as an example, the action time can be the length of time of watching videos or browsing web pages. Taking the traffic action of logging in, signing in or generating an order as an example, since it is a one-time action, the action time is not included, only the number of actions is included. The number of actions of logging in and signing in is usually 1, and the number of actions of generating an order can be multiple. For example, in a settlement involving products provided by multiple merchants, an order is generated based on each merchant, thereby realizing multiple order generation operations in a traffic to be processed.

[0057] It should be noted that a flow to be processed can include multiple flow actions, such as Figure 1 Take traffic 1 as an example of the traffic to be processed. The user logs in and then signs in. The traffic actions involved in the traffic to be processed include login and sign in. You only need to determine the action elements corresponding to each traffic action.

[0058] S20, based on any traffic action, constructing a traffic set based on the corresponding multiple to-be-processed traffic, and determining a target task set of the traffic set from multiple candidate task sets, wherein the task action of the target task set matches the traffic action.

[0059] It should be noted that, since traffic actions can inevitably match corresponding task actions, this embodiment constructs a traffic set from multiple pending traffic with the same traffic action, and determines the candidate task set corresponding to the same action as the target task set. It can be determined that the pending traffic recorded in the traffic set can only be matched to the target task in the target task set. Of course, it may also not match any target task because it does not meet the task conditions. This embodiment uses the same action to summarize the preset tasks and pending traffic, and the number of traversals is reduced from the total number of preset tasks of the task engine to the total number of preset tasks in the target task set. In the case of massive pending traffic, the number of traversals is reduced significantly, which can effectively reduce the number of traversals and improve resource utilization.

[0060] It is worth noting that when a flow to be processed can carry multiple flow actions, this embodiment associates the flow to be processed with multiple flow sets, such as Figure 1 As shown, taking traffic 1 as an example, traffic 1 includes two traffic actions, login and ad viewing. Therefore, it is associated with both traffic set 1 created based on login and traffic set 2 created based on ad viewing. A match is performed based on traffic 1 in traffic set 1 and traffic set 2 respectively, so that traffic 1 can match two target tasks, ensuring the accuracy of points issuance.

[0061] It should be noted that this embodiment first constructs a traffic set by matching traffic actions and task actions, which can reduce the amount of data comparison. It only needs to match one information in the action dimension to classify the traffic to be processed. At this time, there is no need to match the action elements. That is, this embodiment performs two matches for a traffic to be processed, once matching the traffic set through traffic actions, and then matching the target task in the traffic set through action elements.

[0062] S30 , based on any flow set, determining a target task corresponding to the target flow from the target task set, wherein the action element of the target flow satisfies the task condition of the target task.

[0063] It should be noted that the action elements of the traffic to be processed may not necessarily be successfully matched in the target task set, and not every preset task has corresponding traffic to be processed, for example Figure 1 The task action includes preset tasks with sign-in as the task action, while there is no sign-in-related traffic action in the traffic to be processed. Therefore, the number of target traffic is less than or equal to the number of traffic to be processed. This embodiment matches the action element of each traffic to be processed in the traffic set with the task conditions of the preset task. If any task condition is not successfully matched, the traffic to be processed does not involve point rewards and can be discarded in subsequent operations. In this embodiment, each preset task corresponds to a point reward mechanism. Therefore, even if the action element of the traffic to be processed successfully matches the task condition, it will only match one of the task conditions, and there is no situation where multiple task conditions are matched at the same time.

[0064] For example, Figure 1 As shown, taking Traffic 1 in Traffic Set 1 as an example, Task Set 1 is the target Task Set. When matching within this target Task Set, the action elements are 1 time and the first time in a week, and a preset task with a daily task condition can be successfully matched. Of course, the successful match in this embodiment is a semantic match and does not necessarily mean an identical string. For another example, taking a pending traffic flow of watching an ad for 1 minute as an example, this pending traffic flow falls into Traffic Set 2 and is traversed within Task Set 2. Since 1 minute does not meet either 5 minutes or 20 minutes, it cannot be matched to any preset task, and the pending traffic flow will not be used for subsequent point distribution operations.

[0065] S40: Based on the task points of the target task, points are distributed for the corresponding target traffic.

[0066] It should be noted that, in this embodiment, after successfully matching the target traffic and target task, the points are not distributed in real time, but the corresponding association relationship is saved to form a Figure 1The lists of traffic set 1 and traffic set 2 shown record the target points corresponding to each target task through the lists, and then uniformly execute the points issuance according to the corresponding lists, which can concentrate system resources to complete all traversal operations and provide a data basis for different points reward systems. For example, the check-in points reward on special dates are doubled, or the points reward is increased according to different user levels. If points are issued directly after matching the target task, it is necessary to adjust the task points in the task engine or configure a preset task for different user levels. This will inevitably increase unnecessary operations. This embodiment divides the task matching and points issuance operations into two steps through the task engine, which can save the adjustment of the task engine. It only needs to introduce a gain coefficient in the mechanism of the points issuance operation to dynamically adjust the points of daily traffic in specific scenarios, thereby improving the flexibility of points issuance.

[0067] For example, in this embodiment, steps S10 to S30 are performed to obtain Figure 1 After the two lists of traffic set 1 and traffic set 2 are shown, the target points for each target traffic have been determined, and then the points issuance operation is performed according to the above two lists. For example, traffic 1 in traffic set 1 is issued with 10 points. When the user account level corresponding to traffic 2 is higher, it can be increased on the basis of 10 points, for example, increased to 15 points for issuance. The target points in this embodiment are basic points. Through the matching of target tasks and the decoupling of points issuance, temporary points activities or user-level reward mechanisms can be more flexibly configured to improve user experience.

[0068] In addition, in one embodiment, referring to Figure 3 Before executing step S10, the following steps are also included but not limited to:

[0069] S01, in response to selecting any task action, constructing a task configuration interface based on a score field and a plurality of preset condition fields, wherein each condition field corresponds to a different action element;

[0070] S02, in response to input operations on the task configuration interface, constructing task conditions based on field input information corresponding to each condition field, and obtaining task points entered in the points field;

[0071] S03: constructing a preset task based on the selected task action, the constructed task conditions, and the input task points, and associating the preset task with a candidate task set corresponding to the task action.

[0072] It should be noted that the preset tasks of the task engine can be configured in a visual interface. In this embodiment, multiple condition fields are configured in the task engine. The condition fields may include time, number of times, statistical period, etc., and the complete task conditions can be constructed through the condition fields.

[0073] It should be noted that since the candidate task set of this embodiment is composed of the same task actions, the currently existing task actions can be displayed in the visual interface. The manager can directly click on the task action to generate the task configuration interface without the need to configure the task action. The generated preset tasks can also be directly classified into the corresponding candidate task set.

[0074] It should be noted that the field input information of each condition field can be a number or a string. This embodiment can be achieved through semantic matching when comparing task conditions and action elements. Therefore, the field input information can accurately reflect the semantics of the task conditions. For example, if the task condition is to watch 20 minutes of ads in total, the field input information can be "20 minutes of cumulative viewing", or "20 minutes of cumulative viewing of ads", or "advertisement playback time is greater than 20 minutes". After the to-be-processed traffic has watched more than 20 minutes of ads, the corresponding action elements can match the corresponding task conditions. Task points can be entered in the points field according to actual needs, and I will not elaborate on this.

[0075] It should be noted that after completing the above input, you can directly generate task conditions based on the field input information, build a new preset task based on the selected task action, task conditions and task points, and include it in the candidate task set corresponding to the task action.

[0076] In addition, in one embodiment, referring to Figure 3 Each preset task has a preset task identifier, and the task conditions include the condition time and the task number. In step S30, after determining the target task corresponding to the target flow from the multiple preset tasks in the target task set, the following steps are also included but not limited to:

[0077] S31, based on any flow set, determining at least one preceding flow in the to-be-processed flows and a candidate task corresponding to the preceding flow, wherein the action time of the preceding flow is shorter than the condition time of the candidate task, or the number of actions of the preceding flow is less than the number of tasks of the candidate task;

[0078] S32, based on the action element of the preceding traffic, updating the identification content corresponding to the task identification of the candidate task in the corresponding user account;

[0079] S33: When the identified content meets the task conditions of the candidate task, the preceding traffic is determined as the target traffic, and the candidate task is determined as the target task.

[0080] It should be noted that this embodiment further determines at least one preceding traffic flow, which is used to match preset tasks that require the accumulation of multiple traffic flows, such as preset tasks that require the accumulation of multiple days of sign-ins, or preset tasks with a longer cumulative viewing time of advertisements. The preceding task can be any pending task, and a pending task can be determined as a target task and a preceding task at the same time.

[0081] It should be noted that after being determined as the front-end traffic, since the candidate task corresponding to the front-end traffic needs to be executed multiple times or for a long time, one front-end traffic may not necessarily meet the task conditions. Therefore, this embodiment adds the task identifier of the candidate task in the corresponding user account, and updates the identification content corresponding to the task identifier according to the action elements of the front-end traffic, so that the identification content is the cumulative value of the action elements of multiple front-end traffic. When the identification content meets the task conditions, the front-end traffic this time can be determined as the target traffic, the candidate task can be determined as the target task and subsequent operations can be performed.

[0082] For example, Figure 1 As shown, taking Task 1 as an example of a login task of 10 times a week, in Traffic Set 1, Traffic 2 is determined as the target task. At the same time, since the number of actions of Traffic 2 is 1, which is less than 10 times of Task 1, it is determined as a predecessor task. The task identifier of Task 1 is added to the corresponding user account, and the corresponding identifier content is the number of logins. When Traffic 2 is the 10th login, the login content is updated from 9 logins to 10 logins, thereby determining Task 1 as the target task, and adding a record of Traffic 2 corresponding to Task 1 in Traffic Set 1.

[0083] In addition, in one embodiment, referring to Figure 3 Step S40 specifically includes but is not limited to the following steps:

[0084] S41, when the number of tasks of the target task is 1, the task points are distributed to the user account corresponding to the target traffic;

[0085] S42, when the task count of the target task is greater than 1, the task points are distributed to the user account corresponding to the target traffic based on the preset allocation strategy of the target task;

[0086] The allocation strategy includes at least one of the following:

[0087] Split the task points into multiple sub-points, and perform a point distribution operation based on the sub-points each time the preset task is determined as a candidate task;

[0088] After the preset task is determined as the target task, the points distribution operation is performed based on the task points.

[0089] It should be noted that the number of tasks for the target task can be multiple times, such as rewards for multiple sign-ins within a week. This embodiment sets an allocation strategy for the target task with a number of tasks greater than 1. The allocation strategy determines whether the task points are issued once after the target task is completed, or whether the task points are issued once each time the front traffic is detected, and the total amount of points issued multiple times is equal to the task points.

[0090] It should be noted that in order to achieve batch release, the splitting method of task points can be recorded in the allocation strategy, for example Figure 1 Taking Task 2 of watching ads for a total of 20 minutes as an example, after traffic 1 completes watching for 5 minutes, the preset task corresponding to watching for 5 minutes can be determined as the target task, or 5 minutes can be accumulated in Task 2 (refer to the description of the preceding task for details). At this time, the 40 points of the task points can be split proportionally, and 5 minutes can be split into sub-points of 8 points each, and the 8 points can be distributed to the corresponding user account.

[0091] It is worth noting that some tasks can also be set to be paid out in one lump sum after completion. For example, for Task 1, which requires 10 cumulative logins in a week, if there are only 9 logins in a week, the task will not be considered completed due to insufficient number of times. Since the points reward is used to encourage users to log in more often, it cannot be split into multiple sub-points for multiple distributions. Instead, it must be paid out in one lump sum after the 10th completion, that is, it must be distributed after the target task is determined based on the above-mentioned prerequisite tasks.

[0092] In addition, in one embodiment, referring to Figure 3 After executing step S20, the following steps are also included but not limited to:

[0093] S21, creating a corresponding processing process for each target task set;

[0094] S22, based on any processing process, creating a first processing thread and creating a second processing thread corresponding to each target task;

[0095] S23, inputting the target traffic to the second processing thread corresponding to the target task through the first processing thread;

[0096] S24: executing a points distribution operation based on each second processing thread.

[0097] It should be noted that the task engine can implement parallel processing, thereby improving the efficiency of information processing. Some candidate task sets may not be determined as target task sets. Therefore, this embodiment creates a processing process for each target task set and dynamically determines the number of processing processes, so that one processing process corresponds to one target task set. There is no need to identify task actions in the processing process, thereby eliminating repeated data processing.

[0098] It should be noted that in each processing process, a target task may have multiple target traffic. Therefore, this embodiment creates a second processing thread for each target task, and distributes the target traffic through the first processing thread, so that the same second processing thread processes the same target task of different user accounts. For example, in the scenario of massive daily active user traffic, one second processing thread processes the sign-in points reward, and another second processing thread processes the points reward for watching advertisements. In this way, based on the above-mentioned decoupling of traffic identification and points issuance, parallel points issuance is realized on the basis of high traffic, thereby improving the concurrent processing capability of the system.

[0099] For example, in Figure 1 In the traffic set 1 shown, two second processing threads are created, and the target task of traffic 1, traffic 2 and traffic 3 logging in once is sent to one second processing thread for point issuance, and the target task of traffic 2 logging in 10 times within a week is sent to another second processing thread for point issuance, thereby improving the flexibility of issuing points in different scenarios.

[0100] In addition, in one embodiment, referring to Figure 3 Each candidate task set also presets multiple candidate gain coefficients, each candidate gain coefficient corresponds to a different account level. Step S24 specifically includes but is not limited to the following steps:

[0101] S241 , determining a target gain coefficient from candidate gain coefficients based on the account level of the user account of each target flow;

[0102] S242, determining a target integral based on the task integral and the target gain coefficient;

[0103] S243: Distribute the target points to the user account corresponding to the target traffic.

[0104] It should be noted that, based on having different second processing threads, this embodiment further sets multiple candidate gain coefficients in the candidate task set. For example, the higher the account level, the larger the corresponding candidate gain coefficient, so that high-level users can obtain more points. The specific values ​​of the candidate gain coefficients are not limited here.

[0105] It's worth noting that each time the second processing thread acquires a target flow rate, it determines a target gain coefficient from the candidate gain coefficients based on the user account's account level. The target points are then determined based on the task points and the target gain coefficient, for example, by multiplication or addition. The specific calculation method can be set based on actual needs. After determining the target points, the second processing thread distributes the target points to the corresponding user account. The second processing thread also adjusts the points based on the account level, thereby increasing the flexibility of the tiered reward points system.

[0106] In addition, in one embodiment, referring to Figure 3 The task engine is connected to the application system and the database. The traffic to be processed is generated by the application system and stored in the database. Step S10 specifically includes but is not limited to the following steps:

[0107] S11, when the resource utilization rate of the detected application system is less than a preset resource threshold, and the time interval between the current time and the reference time is greater than or equal to a preset time threshold, all pending traffic is obtained from the database, where the reference time is the time when the last points issuance operation was completed;

[0108] S12, when the amount of to-be-processed traffic stored in the database is greater than a preset threshold, a target amount is determined based on the current resource occupancy rate, and the to-be-processed traffic is obtained from the database based on the target amount, wherein the resource occupancy rate is inversely proportional to the target amount.

[0109] It should be noted that the points in this embodiment are not distributed in real time, which will inevitably occupy system resources for a long time. Therefore, the points in this embodiment are distributed periodically or conditionally in a centralized manner, thereby improving the utilization rate of system resources.

[0110] It should be noted that although the task engine does not need to execute the points issuance in real time, in order to determine the time when the resource utilization rate is low, the resource utilization rate of the application system can be monitored in real time. When it is detected that the resource utilization rate is lower than the resource threshold and the duration threshold is met, the to-be-processed traffic is pulled from the database once. The introduction of the duration threshold in this embodiment can avoid the frequent triggering of points issuance when the load of the application system is low, thereby achieving an effect similar to the real-time issuance of points. For example, in a scenario where fewer users use the application system at night, the resource utilization rate is lower than the resource threshold for a long time. Therefore, the introduction of the duration threshold in this embodiment can realize the intermittent issuance of points, which can reduce the frequency of points issuance and thus improve the concentration of resource utilization.

[0111] It should be noted that for some application systems with a large number of users, the resource utilization rate is likely to be greater than the resource threshold for a long time. In this case, the issuance of points can be triggered based on the number of pending flows in the database. For example, if the number threshold is set to 1 million, a data pull operation will be performed for every 1 million pending flows added to the database. At the same time, the number of pending flows pulled is determined based on the resource utilization rate. For example, if the resource utilization rate is 90%, 100,000 pending flows are pulled, and if the resource utilization rate is 70%, 500,000 pending flows are pulled. This ensures that the resource utilization rate is inversely proportional to the target number. This allows the task engine to issue points in smaller quantities in scenarios with high resource utilization, avoiding the impact of high concurrent processing of pending flows on the normal operation of the application system.

[0112] like Figure 4 As shown, Figure 4 This is a structural diagram of a points distribution device based on a task engine provided by an embodiment of the present invention. The present invention also provides a points distribution device based on a task engine, comprising:

[0113] The processor 401 may be implemented as a general-purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is configured to execute relevant programs to implement the technical solutions provided in the embodiments of the present application.

[0114] Memory 402 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). Memory 402 can store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in memory 402 and is called by processor 401 to execute the task engine-based points issuance method of the embodiments of this application.

[0115] Input / output interface 403, used to implement information input and output;

[0116] Communication interface 404, used to implement communication interaction between this device and other devices, which can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WiFi, Bluetooth, etc.);

[0117] Bus 405 , which transmits information between various components of the device (e.g., processor 401 , memory 402 , input / output interface 403 , and communication interface 404 );

[0118] The processor 401 , the memory 402 , the input / output interface 403 and the communication interface 404 are connected to each other in communication within the device via a bus 405 .

[0119] An embodiment of the present application also provides an electronic device, including the task engine-based points distribution device as described above.

[0120] An embodiment of the present application also provides a storage medium, which is a computer-readable storage medium. The storage medium stores a computer program, and when the computer program is executed by a processor, it implements the above-mentioned task engine-based points issuance method.

[0121] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory optionally includes a memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of the above-mentioned networks include but are not limited to the Internet, an intranet, a local area network, a mobile communication network and a combination thereof. The device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and are located in one place, or may be distributed to multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment.

[0122] Those skilled in the art will appreciate that all or some of the steps and systems in the method disclosed above can be implemented as software, firmware, hardware, and appropriate combinations thereof. Some physical components or all physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, and the computer-readable medium can include computer storage media (or non-transitory media) and communication media (or temporary media). As known to those skilled in the art, the term computer storage media is included in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data) and is volatile and non-volatile, removable, and non-removable. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory, or other memory technology, CD-ROM, digital versatile disks (DVD), or other optical disk storage, magnetic cassettes, magnetic tapes, disk storage, or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, as is well known to those skilled in the art, communication media typically includes computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0123] The above is a specific description of the preferred implementation of the present invention, but the present invention is not limited to the above implementation. Those skilled in the art can also make various equivalent modifications or substitutions under the shared conditions that do not violate the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of the present invention.

Claims

1. A points distribution method based on a task engine, characterized in that: Applied to a task engine, the task engine includes multiple candidate task sets, each candidate task set includes multiple preset tasks, each preset task is set with a task action, a task condition, and a task score, and the task actions of the preset tasks in the same candidate task set are the same, the method includes: Acquire multiple flows to be processed, and determine the flow actions and action elements corresponding to each of the flows to be processed, wherein the action elements include action time and / or action times, and the number of the flow actions is at least 1; Based on any of the traffic actions, a traffic set is constructed based on the corresponding plurality of to-be-processed traffic flows, and a target task set of the traffic set is determined from the plurality of candidate task sets, wherein the task action of the target task set matches the traffic action; Based on any of the flow sets, determining a target task corresponding to a target flow from the target task set, wherein the action element of the target flow satisfies the task condition of the target task; The task points of the target task are used to distribute points to the corresponding target traffic.

2. The method for issuing points based on a task engine according to claim 1, characterized in that: Before obtaining a plurality of to-be-processed flows, the method further includes: In response to selecting any one of the task actions, constructing a task configuration interface based on a score field and a plurality of preset condition fields, wherein each of the condition fields corresponds to a different action element; In response to an input operation in the task configuration interface, constructing the task condition based on the field input information corresponding to each of the condition fields, and obtaining the task points entered in the points field; The preset task is constructed based on the selected task action, the constructed task condition, and the input task points, and the preset task is associated with the candidate task set corresponding to the task action.

3. The method for issuing points based on a task engine according to claim 1, characterized in that: Each of the preset tasks is preset with a task identifier, and the task conditions include a conditional time and a task number. After determining the target task corresponding to the target flow from the target task set, the method further includes: Based on any of the traffic sets, determining at least one preceding traffic in the to-be-processed traffic and a candidate task corresponding to the preceding traffic, wherein the action time of the preceding traffic is shorter than the condition time of the candidate task, or the number of actions of the preceding traffic is less than the number of tasks of the candidate task; Based on the action element of the front traffic, updating the identification content corresponding to the task identification of the candidate task in the corresponding user account; When the identification content meets the task condition of the candidate task, the preceding traffic is determined as the target traffic, and the candidate task is determined as the target task.

4. The method for issuing points based on a task engine according to claim 3, characterized in that: The task points of the target task are used to distribute points to the corresponding target traffic, including: When the task number of the target task is 1, the task points are distributed to the user account corresponding to the target traffic; Alternatively, when the task number of the target task is greater than 1, the task points are distributed to the user account corresponding to the target traffic based on the preset allocation strategy of the target task; The allocation strategy includes at least one of the following: Splitting the task points into a plurality of sub-points, and performing a point distribution operation based on the sub-points each time the preset task is determined as the candidate task; After the preset task is determined as the target task, a points distribution operation is performed based on the task points.

5. The method for issuing points based on a task engine according to claim 1, characterized in that: After determining the target task set of the traffic set from the plurality of candidate task sets, the method further includes: Creating a corresponding processing process for each target task set; Based on any of the processing processes, a first processing thread is created, and a second processing thread corresponding to each of the target tasks is created; inputting the target traffic to the second processing thread corresponding to the target task through the first processing thread; The points issuing operation is performed based on each of the second processing threads.

6. The method for issuing points based on a task engine according to claim 5, characterized in that: Each candidate task set is further preset with a plurality of candidate gain coefficients, each candidate gain coefficient corresponding to a different account level, and a points distribution operation is performed based on each second processing thread, including: determining a target gain coefficient from the candidate gain coefficients based on the account level of the user account of each target flow; determining a target integral based on the task integral and the target gain coefficient; The target points are distributed to the user account corresponding to the target traffic.

7. The method for issuing points based on a task engine according to claim 1, characterized in that: The task engine is in communication with the application system and the database. The traffic to be processed is generated by the application system and stored in the database. A plurality of traffic to be processed is obtained, including: When it is detected that the resource usage of the application system is less than a preset resource threshold, and the time interval between the current moment and the reference moment is greater than or equal to a preset time threshold, all of the to-be-processed traffic is obtained from the database, wherein the reference moment is the moment when the last points issuance operation was completed; Alternatively, when the number of the pending traffic stored in the database is greater than a preset threshold, the target number is determined based on the current resource occupancy rate, and the pending traffic is obtained from the database based on the target number, wherein the resource occupancy rate is inversely proportional to the target number.

8. A points distribution device based on a task engine, characterized in that: comprising at least one control processor and a memory for communicatively coupling with the at least one control processor; The memory stores instructions that can be executed by the at least one control processor, and the instructions are executed by the at least one control processor to enable the at least one control processor to execute the task engine-based points issuance method as described in any one of claims 1 to 7.

9. An electronic device, characterized in that: Including the task engine-based points distribution device as described in claim 8.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the task engine-based points issuance method as described in any one of claims 1 to 7.

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