Method and device for determining asynchronous loading sequence of burying point data, equipment and medium

Abstract

The invention relates to the technical field of data acquisition, and discloses an asynchronous loading sequence determination method, device and equipment for burying point data and a medium, the method comprises the following steps: generating a cache loading task through a burying point server and a current burying point event ID; determining target cache time according to the distributed cache database and the cache loading task; and determining an asynchronous loading sequence according to the service priority and the target cache time. By means of the mode, the asynchronous loading sequence is determined according to the service priority of the current burying point event and the target cache time, it is ensured that data which are high in priority and strongly related to user operation are loaded preferentially, the cache loading task is reasonably determined according to the service priority and the target cache time, and the loading efficiency is improved. The problem of frequent database access caused by short-time cache setting due to high service priority is avoided, related pages are quickly rendered and responded, the waiting time of a user is shortened, and the efficiency of asynchronously loading burying point data by an APP rear-end server in the financial service field is improved.

Description

Technical Field

[0001] The present application relates to the field of data acquisition technology, and in particular to a method, device, equipment and medium for determining the asynchronous loading order of buried point data. Background Art

[0002] With the rapid development of mobile internet technology, the integration of financial services and apps (APPs) is becoming increasingly close. Within the financial services sector, various financial institutions have launched their own financial apps, such as online banking apps, securities trading apps, and insurance service apps, to meet users' needs for conducting financial services anytime, anywhere. During the use of financial services apps, business data statistics are crucial for financial institutions to understand user behavior, optimize business processes, and formulate marketing strategies. Currently, business data statistics mainly rely on data reported by tracking points. Tracking points are divided into impression and click events. Impression tracking records the display of page elements, such as the number of impressions of the financial product recommendation section; click tracking records user clicks on specific functions or elements, such as clicks to purchase financial products or clicks to check account balances. Using tracking data, financial institutions can intuitively understand users' frequently used functions, browsing habits, transaction behaviors, and other information at the data level, providing data support for business decision-making.

[0003] At the same time, the backend services of financial business apps need to handle a large number of data requests. To improve system performance and response speed, caching is usually set up for some commonly used data. However, the current cache time settings have certain limitations. In actual business scenarios, the number of clicks on different financial functions varies greatly. Some low-frequency financial functions, such as specific types of insurance product inquiries, even if cached, have low click volumes and low cache hit rates, resulting in wasted cache resources. For popular financial functions with high click volumes, such as popular stock trading and common fund subscriptions, setting a shorter cache time will cause frequent database access, increase database load, put significant pressure on the database, and even affect system stability and response speed. Therefore, how to improve the efficiency of asynchronous loading of buried data by the financial app backend server by optimizing the asynchronous loading order of data has become a technical problem that needs to be solved. Summary of the Invention

[0004] The present application provides a method, apparatus, device and medium for determining the asynchronous loading order of buried data, which improves the efficiency of asynchronous loading of buried data by the back-end server of a financial APP by optimizing the asynchronous loading order of data.

[0005] In a first aspect, the present application provides a method for determining the asynchronous loading order of tracking data, the method comprising:

[0006] In response to the asynchronous interface call instruction, the current tracking event ID of the current tracking event is uploaded to the preset tracking server;

[0007] Generate a cache loading task through the preset tracking server and the current tracking event ID;

[0008] Determine the target cache time corresponding to the current embedding event ID according to the preset distributed cache database and the cache loading task;

[0009] The asynchronous loading order of the current burying event is determined according to the business priority of the current burying event and the target cache time.

[0010] In a second aspect, the present application further provides a device for determining an asynchronous loading order of tracking data, the device comprising:

[0011] The tracking event ID uploading module is used to upload the current tracking event ID of the current tracking event to the preset tracking server in response to the asynchronous interface call instruction;

[0012] A cache loading task generation module is used to generate a cache loading task through the preset tracking server and the current tracking event ID;

[0013] A target cache time determination module is used to determine the target cache time corresponding to the current embedding event ID according to a preset distributed cache database and the cache loading task;

[0014] The asynchronous loading order determination module is used to determine the asynchronous loading order of the current burying event based on the business priority of the current burying event and the target cache time.

[0015] In a third aspect, the present application also provides a computer device comprising a memory and a processor; the memory is used to store a computer program; the processor is used to execute the computer program and implement the asynchronous loading order determination method of the buried point data as described above when executing the computer program.

[0016] In a fourth aspect, the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the processor implements the method for determining the asynchronous loading order of burial data as described above.

[0017] The present application discloses a method, apparatus, device and medium for determining the asynchronous loading order of burial data. The method for determining the asynchronous loading order of burial data includes uploading the current burial event ID of the current burial event to a preset burial server in response to an asynchronous interface call instruction; generating a cache loading task through the preset burial server and the current burial event ID; determining the target cache time corresponding to the current burial event ID based on a preset distributed cache database and the cache loading task; and determining the asynchronous loading order of the current burial event based on the business priority of the current burial event and the target cache time. Through the above method, this application triggers an asynchronous interface call when the user clicks on the function, uploads the tracking event ID to the preset tracking server and generates a cache loading task, determines the asynchronous loading order according to the business priority of the current tracking event and the target cache time, ensures that high-priority data that is strongly related to user operations is loaded first, and reasonably determines the cache loading task according to the business priority and target cache time, avoiding the problem of frequent database access caused by setting a short-time cache due to high business priority. When the user enters the corresponding page, since the data is already in the cache, fast rendering and response can be achieved, reducing user waiting time and improving the efficiency of asynchronous loading of tracking data by the APP back-end server in the financial business field. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0019] Figure 1 This is a schematic flow chart of a method for determining the asynchronous loading order of tracking data provided by the first embodiment of the present application;

[0020] Figure 2 This is a schematic flow chart of a method for determining the asynchronous loading order of tracking data provided by the second embodiment of the present application;

[0021] Figure 3 This is a schematic flow chart of a method for determining the asynchronous loading order of tracking data provided by the third embodiment of the present application;

[0022] Figure 4 A schematic block diagram of a device for determining an asynchronous loading order of tracking data provided in an embodiment of the present application;

[0023] Figure 5 A schematic block diagram of the structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0025] The flowcharts shown in the accompanying drawings are for illustrative purposes only and do not necessarily include all contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may be decomposed, combined, or partially merged, so the actual execution order may vary depending on the actual situation.

[0026] It should be understood that the terms used in this specification are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in this specification and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0027] It will also be understood that the term "and / or" used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0028] The embodiments of the present application provide a method, device, equipment and medium for determining the asynchronous loading order of buried data. Among them, the method for determining the asynchronous loading order of buried data can be applied to the server, by triggering an asynchronous interface call when the user clicks on the function, uploading the buried event ID to the preset buried server and generating a cache loading task, determining the asynchronous loading order according to the business priority and target cache time of the current buried event, ensuring that high-priority data that is strongly related to user operations is loaded first, and reasonably determining the cache loading task according to the business priority and target cache time, avoiding the problem of frequent database access caused by setting a short-time cache due to high business priority. When the user enters the corresponding page, since the data is already in the cache, fast rendering and response can be achieved, reducing user waiting time, and improving the efficiency of asynchronous loading of buried data by the APP back-end server in the financial business field. Among them, the server can be an independent server or a server cluster.

[0029] The following describes some embodiments of the present application in detail with reference to the accompanying drawings. Each embodiment of the present application is described using the financial services sector as an example, but does not limit the application scenario and is provided only as an example. The following embodiments and features of the embodiments may be combined with each other unless they conflict.

[0030] See also Figure 1 , Figure 1 This is a schematic flow chart of a method for determining the asynchronous loading order of buried data provided by the first embodiment of the present application. The method for determining the asynchronous loading order of buried data can be applied to a server, and is used to trigger an asynchronous interface call when a user clicks a function, upload the buried event ID to a preset buried server, and generate a cache loading task. The asynchronous loading order is determined according to the business priority and target cache time of the current buried event, ensuring that high-priority data that is strongly related to user operations is loaded first, and the cache loading task is reasonably determined according to the business priority and target cache time, avoiding the problem of frequent database access caused by setting a short-time cache due to high business priority. When the user enters the corresponding page, since the data is already in the cache, fast rendering and response can be achieved, reducing user waiting time and improving the efficiency of asynchronous loading of buried data by the APP back-end server in the financial business field.

[0031] like Figure 1 As shown, the method for determining the asynchronous loading order of the tracking data specifically includes steps S10 to S40.

[0032] Step S10: In response to the asynchronous interface call instruction, the current tracking event ID of the current tracking event is uploaded to the preset tracking server;

[0033] Specifically, on the front-end interface of the financial APP, click-through or exposure-based events are set for various financial transaction operations (such as stock purchases, fund subscriptions, asset inquiries, etc.) and page browsing functions. Each click-through event has a unique click-through event ID. When the user performs an operation (such as clicking a stock buy button) or browses the page to trigger the corresponding click-through event, the front-end will capture the event.

[0034] After capturing the tracking event, the front-end collects the basic user attribute information related to the event, such as user ID, account type, device information, etc., and associates the collected basic user attribute information with the current tracking event ID to form the tracking data to be reported. At the same time as reporting the tracking data, an asynchronous interface call instruction is triggered. In the asynchronous thread, an HTTP (Hypertext Transfer Protocol) request is constructed to upload the tracking data to the preset tracking server.

[0035] Step S20: Generate a cache loading task through the preset tracking server and the current tracking event ID;

[0036] Specifically, the interface of the preset tracking server receives the current tracking event ID sent from the front-end or back-end business logic layer. For example, when a user clicks the "Stock Trading" function button in a financial app, the front-end sends the tracking event ID corresponding to the click event (such as "event_stock_trade") to the preset tracking server.

[0037] Define a cache loading task object, containing basic task information such as the task ID, cache key list, basic cache time, and tracking event ID. The task ID can be generated using a unique identifier. The parsed cache key list, basic cache time, and tracking event ID are set to the task object. Also, set the task's initial status to "Not Started" or "Ready."

[0038] Step S30: Determine the target cache time corresponding to the current embedding event ID according to the preset distributed cache database and the cache loading task;

[0039] Specifically, based on business needs and algorithm design, determine how to combine the current number of clicks and the basic cache time to calculate the target cache time. For example, a linear weighted formula can be used:

[0040] Target cache time = basic cache time * (1 + click weight coefficient * current number of clicks / click reference value).

[0041] Substitute the extracted basic cache time and the current number of clicks into the formula to calculate the target cache time. For example, assuming that the basic cache time is 300 seconds, the current number of clicks is 100, the click weight coefficient is 0.01, and the click reference value is 100, then the target cache time is 300*(1+0.01*100 / 100)=303 seconds.

[0042] Step S40: Determine the asynchronous loading order of the current burying event based on the business priority of the current burying event and the target cache time.

[0043] Specifically, obtain the previously calculated target cache time from the cache loading task object, set the business priority weight coefficient and cache time weight coefficient according to business needs and experience, for example, the business priority weight coefficient is set to 0.7, and the cache time weight coefficient is set to 0.3, and the calculation formula of the loading order score is defined as: loading order score = business priority weight * business priority + cache time weight * target cache time, substitute the extracted business priority and target cache time into the formula to calculate the loading order score of each tracking event, collect the loading order scores of all current tracking events, and sort the tracking events according to the loading order score. The higher the score, the higher the loading order.

[0044] Assign a priority to the generated cache loading tasks based on business rules and the current system operation status. For example, cache loading tasks corresponding to stock trading functions can be given a higher priority so that they can be executed first when system resources are limited.

[0045] The present embodiment discloses a method, apparatus, device and medium for determining the asynchronous loading order of burial data. The method for determining the asynchronous loading order of burial data includes uploading the current burial event ID of the current burial event to a preset burial server in response to an asynchronous interface call instruction; generating a cache loading task through the preset burial server and the current burial event ID; determining the target cache time corresponding to the current burial event ID based on a preset distributed cache database and the cache loading task; and determining the asynchronous loading order of the current burial event based on the business priority of the current burial event and the target cache time. Through the above method, this application triggers an asynchronous interface call when the user clicks on the function, uploads the tracking event ID to the preset tracking server and generates a cache loading task, determines the asynchronous loading order according to the business priority of the current tracking event and the target cache time, ensures that high-priority data that is strongly related to user operations is loaded first, and reasonably determines the cache loading task according to the business priority and target cache time, avoiding the problem of frequent database access caused by setting a short-time cache due to high business priority. When the user enters the corresponding page, since the data is already in the cache, fast rendering and response can be achieved, reducing user waiting time and improving the efficiency of asynchronous loading of tracking data by the APP back-end server in the financial business field.

[0046] See also Figure 2 , Figure 2 This is a schematic flow chart of a method for determining the asynchronous loading order of buried data provided by the second embodiment of the present application. The method for determining the asynchronous loading order of buried data can be applied to the server, and is used to determine the preset cache key list and basic cache time through the universal data loading interface of the preset buried server and the current buried event ID, and generate a cache loading task, thereby avoiding the waste of cache resources caused by unreasonable cache settings. Through the fine management of cache time, limited cache resources are allocated to functional modules that are more in need, thereby improving the utilization rate of cache resources and improving the efficiency of asynchronous loading of buried data by APP back-end servers in the financial business field.

[0047] based on Figure 1 The embodiment shown, this embodiment Figure 2 As shown, step S20 includes steps S201 to S202.

[0048] Step S201: Determine a preset cache key list and a basic cache time based on the universal data loading interface of the preset tracking server and the current tracking event ID;

[0049] Specifically, the ID of the currently triggered tracking event is received from the front-end or back-end business logic layer. For example, when a user clicks a function button, the front-end sends the tracking event ID corresponding to the click event to the back-end, and the back-end service receives this ID.

[0050] Send the constructed query request to the pre-set tracking server's universal data loading interface. The pre-set tracking server returns the query results, which typically include information such as the pre-set cache key list and the base cache time. Parse the returned data into a usable format. For example, extract the cache key list and base cache time fields from the JSON (JavaScript Object Notation) response and store them in a temporary variable or data structure.

[0051] Step S202: Generate the cache loading task according to the preset cache key list, basic cache time and the current embedding event ID.

[0052] Specifically, design a cache loading task object that contains the basic information required for the task, such as task ID, cache key list, basic cache time, current embedded event ID, task status, task priority, etc. Instantiate the cache loading task object and set the initial state to "not started".

[0053] Add the preset cache key list to the task object, specify the cache key to be loaded, and set the basic cache time to the task object for subsequent cache data expiration management. Record the current tracking event ID in the task object for subsequent tracing and association of business operations.

[0054] The present embodiment discloses a method, device, equipment and medium for determining the asynchronous loading order of buried point data. The method for determining the asynchronous loading order of buried point data includes uploading the current buried point event ID of the current buried point event to a preset buried point server in response to an asynchronous interface call instruction; determining a preset cache key list and a basic cache time according to the universal data loading interface of the preset buried point server and the current buried point event ID; generating the cache loading task according to the preset cache key list, the basic cache time and the current buried point event ID; determining the target cache time corresponding to the current buried point event ID according to the preset distributed cache database and the cache loading task; determining the asynchronous loading order of the current buried point event according to the business priority of the current buried point event and the target cache time. Through the above-mentioned method, the present application determines the preset cache key list and the basic cache time and generates a cache loading task through the universal data loading interface of the preset buried point server and the current buried point event ID, thereby avoiding the waste of cache resources caused by unreasonable cache settings. Through the fine management of cache time, limited cache resources are allocated to functional modules that are more needed, thereby improving the utilization rate of cache resources and improving the efficiency of asynchronous loading of buried point data by the APP back-end server in the financial business field.

[0055] based on Figure 2 In the embodiment shown, in this embodiment, before step S201, the following steps are included:

[0056] Obtain each preset burying point event ID from the cache configuration table, and match the current burying point event ID with each preset burying point to determine whether the current burying point event ID is a valid ID;

[0057] Determine the current business rules of the current embedding event based on the current embedding event ID;

[0058] Obtaining preset business rules from the cache configuration table, and determining whether the current business rule is a valid business rule based on the preset business rules;

[0059] When the current embedding event ID is the legal ID and the current business rule is the legal business rule, it is determined that the current embedding event passes the verification.

[0060] Specifically, the currently triggered tracking event ID is received from the front-end or back-end business logic layer, and the current tracking event ID is matched with the preset tracking event ID list obtained from the cache configuration table. The preset tracking event ID list can be traversed to check whether the current tracking event ID exists in the list.

[0061] If the current tracking event ID exists in the preset tracking event ID list, it is marked as a legal ID; otherwise, it is marked as an illegal ID.

[0062] Establish a mapping relationship (such as a dictionary or hash table) to map the tracking event ID to the corresponding business rules. Business rules can include various business logic, such as data format requirements, access rights, and operation time limits. Based on the current tracking event ID, obtain the corresponding current business rule from the mapping relationship.

[0063] The current business rules are compared with the preset business rules to check whether they are consistent. If the current business rules are consistent with the preset business rules, they are marked as legal business rules; otherwise, they are marked as illegal business rules.

[0064] Only when the current tracking event ID is valid and the current business rules are valid is the tracking event considered to have passed verification, and the verification result is fed back to the caller. If verification passes, subsequent operations such as cache loading can continue. If verification fails, the error information is recorded and appropriate processing is performed, such as returning an error response to the front end.

[0065] In a specific embodiment, step S201 includes:

[0066] Analyze the current tracking event ID and determine the preset storage location;

[0067] According to the current burying event ID and the preset storage location, the preset cache key list and the basic cache time are determined from the preset burying server.

[0068] Specifically, according to the parsing rules, the corresponding storage location information is extracted from the current embedding event ID, and based on the parsed storage location information, the specific query path is determined, and the current embedding event ID is used as a query parameter to construct a query request.

[0069] based on Figure 2 In the embodiment shown, in this embodiment, step S202 includes:

[0070] Create target task object;

[0071] Determine a preset cache key that matches the current tracking event ID from the preset cache key list;

[0072] The basic cache time and the preset cache key are added to the target task object to generate the cache loading task.

[0073] Specifically, obtain the preset cache key list related to the current burying event ID from the cache configuration of the preset burying server, and search for the cache key that matches the current burying event ID in the preset cache key list. The matching logic can be determined according to specific business rules. For example, the cache key may contain the burying event ID as its component, or there is a mapping table that defines the correspondence between the burying event ID and the cache key. Obtain the basic cache time related to the current burying event ID from the cache configuration of the preset burying server, add the matched preset cache key and basic cache time to the corresponding fields of the target task object, and generate a cache loading task.

[0074] See also Figure 3 , Figure 3 This is a schematic flow chart of a method for determining the asynchronous loading order of point-of-sale data provided by the third embodiment of the present application. The method for determining the asynchronous loading order of point-of-sale data can be applied to a server, and is used to send cache loading tasks to an asynchronous message queue MQ by optimizing the generation of cache loading tasks, the determination of target cache time, and the asynchronous loading order, and publish the tasks to a preset distributed cache database through the asynchronous data call interface of the asynchronous MQ, thereby realizing asynchronous processing and distributed execution of tasks, improving the efficiency of task scheduling and the response speed of the system, and improving the efficiency of asynchronous loading of point-of-sale data by the APP back-end server in the financial business field.

[0075] based on Figure 1 The embodiment shown, this embodiment Figure 3 As shown, step S30 includes steps S301 to S303.

[0076] Step S301: Send the cache loading task to the asynchronous message queue MQ, and publish the cache loading task to the preset distributed cache database through the asynchronous data call interface of the asynchronous MQ;

[0077] Specifically, the cache load task object, which contains information such as the base cache time and the preset cache key, is serialized into a format suitable for network transmission and sent to the designated MQ queue. On the distributed cache database server or the corresponding consumer service, an MQ consumer program runs, listening to the queue for receiving cache load tasks. The consumer program defines the processing logic after receiving the message, such as parsing the message content and calling the distributed cache database API to load cache data.

[0078] When a consumer receives a cache loading task from MQ, it parses the task data and then loads the cache data into the specified preset cache key through the interface provided by the distributed cache database.

[0079] Step S302: Obtain the current number of clicks on the current embedding event;

[0080] Specifically, the burying point server sends a query request to the preset burying point database that stores the burying point event counting information based on the burying point event ID, queries the click count key corresponding to the burying point event ID, and the preset burying point returns the current click count value corresponding to the key, so that the burying point server obtains the current click count of the current burying point event.

[0081] Step S303: Determine the target cache time according to the current number of clicks and the basic cache time through the preset distributed cache database.

[0082] Specifically, the click weight coefficient and the basic cache time weight coefficient are set according to business needs and experience. For example, the click weight coefficient is set to 0.3, the basic cache time weight coefficient is set to 0.7, and the target cache time = basic cache time * basic cache time weight + current clicks * click weight.

[0083] Substitute the obtained basic cache time and current click count into the formula to calculate the target cache time. For example, if the basic cache time is 300 seconds, the current click count is 100, the basic cache time weight coefficient is 0.7, and the click count weight coefficient is 0.3, then the target cache time = 300 * 0.7 + 100 * 0.3 = 240 seconds.

[0084] This embodiment discloses a method, device, equipment and medium for determining the asynchronous loading order of burying data. The method for determining the asynchronous loading order of burying data includes uploading the current burying event ID of the current burying event to a preset burying server in response to an asynchronous interface call instruction; generating a cache loading task through the preset burying server and the current burying event ID; sending the cache loading task to the asynchronous message queue MQ, and publishing the cache loading task to the preset distributed cache database through the asynchronous data call interface of the asynchronous MQ; obtaining the current number of clicks of the current burying event; determining the target cache time according to the current number of clicks and the basic cache time through the preset distributed cache database; and determining the asynchronous loading order of the current burying event according to the business priority of the current burying event and the target cache time. Through the above method, this application sends the cache loading task to the asynchronous message queue MQ by optimizing the generation of cache loading tasks, the determination of the target cache time and the asynchronous loading order, and publishes the task to the preset distributed cache database through the asynchronous data call interface of asynchronous MQ, thereby realizing asynchronous processing and distributed execution of tasks, improving the efficiency of task scheduling and the response speed of the system, and improving the efficiency of asynchronous loading of buried data by the APP back-end server in the financial business field.

[0085] Based on any of the above embodiments, in this embodiment, step S40 includes:

[0086] Determine the service priority based on the current tracking event ID;

[0087] Calculate the loading order score of the current tracking event according to the preset asynchronous loading weight, the business priority and the target cache time, wherein the preset asynchronous loading weight includes the priority weight and the cache time weight;

[0088] Arrange the loading order scores of all the current embedding events in descending order to determine the asynchronous loading order.

[0089] Specifically, a mapping relationship between a tracking event ID and a business priority is obtained from a business configuration file or a database, and the corresponding business priority is searched in the mapping relationship according to the current tracking event ID.

[0090] Obtain the preset asynchronous loading weights from the configuration file or system parameters, including the priority weight and cache time weight. For example, the priority weight is 0.7 and the cache time weight is 0.3. Convert the service priority to a numerical value, for example, "High" priority corresponds to a value of 3, "Medium" priority corresponds to a value of 2, and "Low" priority corresponds to a value of 1.

[0091] Obtain the target cache time corresponding to the current tracking event from the distributed cache database and calculate the loading order score using the weighted formula as follows:

[0092] Loading order score = (business priority value * priority weight) + (target cache time * cache time weight).

[0093] Collect the loading order scores of all current tracking events into a list, sort the tracking events in descending order according to the loading order scores, and determine the asynchronous loading order based on the sorting results. The event with the highest score is loaded first, and so on.

[0094] See also Figure 4 , Figure 4 The embodiment of the present application provides a schematic block diagram of an asynchronous loading order determination device for buried data, which is used to execute the aforementioned asynchronous loading order determination method for buried data. The asynchronous loading order determination device for buried data can be configured on a server.

[0095] like Figure 4 As shown, the asynchronous loading order determination device 400 of the tracking data includes:

[0096] The tracking event ID uploading module 410 is used to upload the current tracking event ID of the current tracking event to the preset tracking server in response to the asynchronous interface call instruction;

[0097] The cache loading task generating module 420 is used to generate a cache loading task through the preset tracking server and the current tracking event ID;

[0098] The target cache time determination module 430 is used to determine the target cache time corresponding to the current embedding event ID according to the preset distributed cache database and the cache loading task;

[0099] The asynchronous loading order determination module 440 is used to determine the asynchronous loading order of the current burying event according to the business priority of the current burying event and the target cache time.

[0100] Furthermore, the cache loading task generating module 420 includes:

[0101] A cache key list and cache time determination unit, configured to determine a preset cache key list and a basic cache time according to a universal data loading interface of the preset burying point server and the current burying point event ID;

[0102] The cache loading task generating unit is used to generate the cache loading task according to the preset cache key list, the basic cache time and the current burying event ID.

[0103] Furthermore, the cache loading task generating module 420 further includes:

[0104] A legal ID judgment unit is used to obtain each preset burying point event ID from the cache configuration table, and match the current burying point event ID with each preset burying point to determine whether the current burying point event ID is a legal ID;

[0105] A current business rule determination unit, configured to determine a current business rule of the current embedding event based on the current embedding event ID;

[0106] A legal business rule judgment unit, configured to obtain a preset business rule from the cache configuration table and judge whether the current business rule is a legal business rule according to the preset business rule;

[0107] The current embedding event verification unit is used to determine that the current embedding event passes the verification when the current embedding event ID is the legal ID and the current business rule is the legal business rule.

[0108] Furthermore, the cache key list and cache time determination unit includes:

[0109] A preset storage location determination subunit is used to parse the current embedding event ID and determine the preset storage location;

[0110] The cache key list and cache time determination subunit is used to determine the preset cache key list and the basic cache time from the preset burying point server based on the current burying point event ID and the preset storage location.

[0111] Furthermore, the cache loading task generating unit includes:

[0112] A target task object creation subunit is used to create a target task object;

[0113] A preset cache key determination subunit, configured to determine a preset cache key that matches the current burying event ID from the preset cache key list;

[0114] The cache loading task generating subunit is configured to add the basic cache time and the preset cache key to the target task object to generate the cache loading task.

[0115] Furthermore, the target cache time determination module 430 includes:

[0116] A cache loading task issuing unit, configured to send the cache loading task to an asynchronous message queue MQ, and to issue the cache loading task to the preset distributed cache database through an asynchronous data call interface of the asynchronous MQ;

[0117] A current click count acquisition unit, used to acquire the current click count of the current embedding event;

[0118] The target cache time determining unit is configured to determine the target cache time according to the current number of clicks and the basic cache time through the preset distributed cache database.

[0119] Furthermore, the asynchronous loading order determination module 440 includes:

[0120] A service priority determination unit, configured to determine the service priority based on the current embedding event ID;

[0121] A loading order score calculation unit, configured to calculate a loading order score of the current tracking event based on a preset asynchronous loading weight, the service priority, and the target cache time, wherein the preset asynchronous loading weight includes a priority weight and a cache time weight;

[0122] The asynchronous loading order determination unit is used to arrange the loading order scores of all the current burying events in descending order to determine the asynchronous loading order.

[0123] It should be noted that those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and modules can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0124] The above-mentioned device can be realized in the form of a computer program. The computer program can be used in Figure 5 Runs on the computer device shown.

[0125] See also Figure 5 , Figure 5 1 is a schematic block diagram of a computer device provided in an embodiment of the present application. The computer device may be a server.

[0126] See Figure 5 The computer device includes a processor, a memory, and a network interface connected through a system bus, wherein the memory may include a non-volatile storage medium and an internal memory.

[0127] The non-volatile storage medium can store an operating system and a computer program. The computer program includes program instructions that, when executed, enable a processor to execute any method for determining an asynchronous loading order of embedded data.

[0128] The processor is used to provide computing and control capabilities and support the operation of the entire computer equipment.

[0129] The internal memory provides an environment for the operation of the computer program in the non-volatile storage medium. When the computer program is executed by the processor, the processor can execute any method for determining the asynchronous loading order of the buried data.

[0130] The network interface is used for network communication, such as sending assigned tasks, etc. Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0131] It should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0132] In one embodiment, the processor is configured to execute a computer program stored in the memory to implement the following steps:

[0133] In response to the asynchronous interface call instruction, the current tracking event ID of the current tracking event is uploaded to the preset tracking server;

[0134] Generate a cache loading task through the preset tracking server and the current tracking event ID;

[0135] Determine the target cache time corresponding to the current embedding event ID according to the preset distributed cache database and the cache loading task;

[0136] The asynchronous loading order of the current burying event is determined according to the business priority of the current burying event and the target cache time.

[0137] In one embodiment, a cache loading task is generated by using the preset tracking server and the current tracking event ID to achieve:

[0138] Determine a preset cache key list and a basic cache time according to the universal data loading interface of the preset tracking server and the current tracking event ID;

[0139] The cache loading task is generated according to the preset cache key list, basic cache time and the current embedding event ID.

[0140] In one embodiment, before determining the preset cache key list and the basic cache time based on the universal data loading interface of the preset tracing server and the current tracing event ID, it is used to implement:

[0141] Obtain each preset burying point event ID from the cache configuration table, and match the current burying point event ID with each preset burying point to determine whether the current burying point event ID is a valid ID;

[0142] Determine the current business rules of the current embedding event based on the current embedding event ID;

[0143] Obtaining preset business rules from the cache configuration table, and determining whether the current business rule is a valid business rule based on the preset business rules;

[0144] When the current embedding event ID is the legal ID and the current business rule is the legal business rule, it is determined that the current embedding event passes the verification.

[0145] In one embodiment, a preset cache key list and a basic cache time are determined based on the universal data loading interface of the preset tracing server and the current tracing event ID, so as to achieve:

[0146] Analyze the current tracking event ID and determine the preset storage location;

[0147] According to the current burying event ID and the preset storage location, the preset cache key list and the basic cache time are determined from the preset burying server.

[0148] In one embodiment, the cache loading task is generated based on the preset cache key list, the basic cache time, and the current embedding event ID to achieve:

[0149] Create target task object;

[0150] Determine a preset cache key that matches the current tracking event ID from the preset cache key list;

[0151] The basic cache time and the preset cache key are added to the target task object to generate the cache loading task.

[0152] In one embodiment, the target cache time corresponding to the current tracking event ID is determined based on a preset distributed cache database and the cache loading task, so as to achieve:

[0153] Sending the cache loading task to the asynchronous message queue MQ, and publishing the cache loading task to the preset distributed cache database through the asynchronous data call interface of the asynchronous MQ;

[0154] Get the current number of clicks for the current embedding event;

[0155] The target cache time is determined by the preset distributed cache database according to the current number of clicks and the basic cache time.

[0156] In one embodiment, the asynchronous loading order of the current burying event is determined based on the business priority of the current burying event and the target cache time, so as to achieve:

[0157] Determine the service priority based on the current tracking event ID;

[0158] Calculate the loading order score of the current tracking event according to the preset asynchronous loading weight, the business priority and the target cache time, wherein the preset asynchronous loading weight includes the priority weight and the cache time weight;

[0159] Arrange the loading order scores of all the current embedding events in descending order to determine the asynchronous loading order.

[0160] A computer-readable storage medium is also provided in an embodiment of the present application, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and the processor executes the program instructions to implement any method for determining the asynchronous loading order of burial point data provided in an embodiment of the present application.

[0161] The computer-readable storage medium may be an internal storage unit of the computer device described in the aforementioned embodiment, such as a hard disk or memory of the computer device. The computer-readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, a SmartMedia Card (SMC), a Secure Digital (SD) card, a flash memory card, etc., equipped on the computer device.

[0162] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present application, and such modifications or substitutions should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A method for determining the asynchronous loading order of buried data, characterized in that: include: In response to the asynchronous interface call instruction, the current tracking event ID of the current tracking event is uploaded to the preset tracking server; Generate a cache loading task through the preset tracking server and the current tracking event ID; Determine the target cache time corresponding to the current embedding event ID according to the preset distributed cache database and the cache loading task; The asynchronous loading order of the current burying event is determined according to the business priority of the current burying event and the target cache time.

2. The method for determining the asynchronous loading order of buried data according to claim 1, characterized in that: The generating of a cache loading task by using the preset tracking server and the current tracking event ID includes: Determine a preset cache key list and a basic cache time according to the universal data loading interface of the preset tracking server and the current tracking event ID; The cache loading task is generated according to the preset cache key list, basic cache time and the current embedding event ID.

3. The method for determining the asynchronous loading order of buried data according to claim 2, characterized in that: The preset tracking point server includes a cache configuration table. Before determining the preset cache key list and the basic cache time according to the universal data loading interface of the preset tracking point server and the current tracking point event ID, the method includes: Obtain each preset burying point event ID from the cache configuration table, and match the current burying point event ID with each preset burying point to determine whether the current burying point event ID is a valid ID; Determine the current business rules of the current embedding event based on the current embedding event ID; Obtaining preset business rules from the cache configuration table, and determining whether the current business rule is a valid business rule based on the preset business rules; When the current embedding event ID is the legal ID and the current business rule is the legal business rule, it is determined that the current embedding event passes the verification.

4. The method for determining the asynchronous loading order of buried data according to claim 3, characterized in that: The step of determining a preset cache key list and a basic cache time according to the universal data loading interface of the preset tracking point server and the current tracking point event ID includes: Analyze the current tracking event ID and determine the preset storage location; According to the current burying event ID and the preset storage location, the preset cache key list and the basic cache time are determined from the preset burying server.

5. The method for determining the asynchronous loading order of buried data according to claim 2, characterized in that: Generating the cache loading task according to the preset cache key list, the basic cache time and the current embedding event ID includes: Create target task object; Determine a preset cache key that matches the current tracking event ID from the preset cache key list; The basic cache time and the preset cache key are added to the target task object to generate the cache loading task.

6. The method for determining the asynchronous loading order of buried data according to claim 1, characterized in that: The determining, based on the preset distributed cache database and the cache loading task, a target cache time corresponding to the current embedding event ID includes: Sending the cache loading task to the asynchronous message queue MQ, and publishing the cache loading task to the preset distributed cache database through the asynchronous data call interface of the asynchronous MQ; Get the current number of clicks for the current embedding event; The target cache time is determined by the preset distributed cache database according to the current number of clicks and the basic cache time.

7. The method for determining the asynchronous loading order of buried data according to any one of claims 1 to 6, characterized in that: The determining, according to the business priority of the current burying event and the target cache time, the asynchronous loading order of the current burying event includes: Determine the service priority based on the current tracking event ID; Calculate the loading order score of the current tracking event according to the preset asynchronous loading weight, the business priority and the target cache time, wherein the preset asynchronous loading weight includes the priority weight and the cache time weight; Arrange the loading order scores of all the current embedding events in descending order to determine the asynchronous loading order.

8. A device for determining the asynchronous loading order of buried data, characterized in that: include: The tracking event ID uploading module is used to upload the current tracking event ID of the current tracking event to the preset tracking server in response to the asynchronous interface call instruction; A cache loading task generation module is used to generate a cache loading task through the preset tracking server and the current tracking event ID; A target cache time determination module is used to determine the target cache time corresponding to the current embedding event ID according to a preset distributed cache database and the cache loading task; The asynchronous loading order determination module is used to determine the asynchronous loading order of the current burying event based on the business priority of the current burying event and the target cache time.

9. A computer device, characterized in that: The computer device includes a memory and a processor; The memory is used to store computer programs; The processor is used to execute the computer program and implement the asynchronous loading order determination method for burial point data as described in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, enables the processor to implement the asynchronous loading order determination method for burial point data as described in any one of claims 1 to 7.

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