Data processing method and device
By acquiring and simulating the execution of event tracking logs, and updating event tracking information in conjunction with preset evaluation criteria, the problem of event tracking management was solved, and the accuracy of event tracking and the effectiveness of anomaly monitoring and performance optimization of business software were improved.
Patent Information
- Application Number
- CN202511940472.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-22
- Publication Date
- 2026-03-27
AI Technical Summary
In the field of digital cultural product production software, the management of data tracking points is difficult, and it is easy to cause failures or redundancy, affecting anomaly monitoring and performance optimization.
By obtaining initial event tracking information and target business code files, reference event tracking information is determined, the event tracking to be processed is simulated to obtain simulated event tracking logs, and the event tracking to be processed is evaluated according to preset evaluation criteria. The initial event tracking information is then updated to obtain target event tracking information.
It improves the convenience of event tracking management, avoids event tracking chaos, failure and redundancy caused by multiple technical personnel developing and updating business, and improves the accuracy of anomaly monitoring and performance optimization.
Smart Images
Figure CN121742882A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of computer technology, and in particular to data processing methods. This application also relates to a data processing apparatus, a computing device, a computer-readable storage medium, and a computer program product. Background Technology
[0002] In the fields of digital cultural product creation software and digital cultural creative software, related business software such as game software can be developed and operated. Among these, event tracking is a key method for anomaly monitoring and performance optimization of business software. Event tracking refers to the proactive insertion of data collection logic, or event tracking logic, into the corresponding business code of the business software. This logic is used to collect user behavior, business processes, system status, or anomaly information, and can generate event tracking logs.
[0003] However, since business code is usually developed collaboratively by multiple technical personnel, each person's modifications to the tracking points can differ, making tracking point management quite difficult. Furthermore, as business processes are updated, the business code is also updated, which can easily lead to tracking point failures or redundancy, further increasing the difficulty of tracking point management and hindering anomaly monitoring and performance optimization of the business software. Summary of the Invention
[0004] In view of the above, embodiments of this application provide a data processing method to address the technical deficiencies existing in the prior art. Embodiments of this application also provide a data processing apparatus, a computing device, a computer-readable storage medium, and a computer program product.
[0005] According to a first aspect of the embodiments of this application, a data processing method is provided, including: Obtain initial event tracking information and target business code file. Event tracking information includes the event tracking identifier and the business code file where the event tracking is located. Based on the target business code file, determine the reference tracking point information; Based on the initial tracking information and the reference tracking information, the tracking points to be processed are determined from the tracking points corresponding to the reference tracking information, and the target business code file is simulated to obtain the simulated tracking logs of the tracking points to be processed. The simulation tracking logs and preset evaluation criteria are used to evaluate the tracking points to be processed, and evaluation information is obtained. The initial embedding information is updated based on the evaluation information to obtain the target embedding information.
[0006] According to a second aspect of the embodiments of this application, a data processing apparatus is provided, comprising: The acquisition module is configured to acquire initial event tracking information and target business code file, wherein the event tracking information includes the event tracking identifier and the business code file where the event tracking is located; The determination module is configured to determine reference tracking information based on the target business code file; The simulation module is configured to determine the event to be processed from the event points corresponding to the reference event point information based on the initial event point information and the reference event point information, and to simulate running the target business code file to obtain the simulated event point logs of the event to be processed. The acquisition module is configured to evaluate the tracking points to be processed based on the simulated tracking point logs and preset evaluation criteria, and obtain evaluation information. The update module is configured to update the initial tracking information based on the evaluation information to obtain the target tracking information.
[0007] According to a third aspect of the embodiments of this application, a computing device is provided, including: a memory and a processor; The memory is used to store computer programs / instructions, and the processor is used to execute the computer programs / instructions. When the computer programs / instructions are executed by the processor, they implement data processing methods.
[0008] According to a fourth aspect of the embodiments of this application, a computer-readable storage medium is provided that stores a computer program / instructions, which, when executed by a processor, implement a data processing method.
[0009] According to a fifth aspect of the embodiments of this application, a computer program product is provided, including a computer program / instructions, which, when executed by a processor, implement a data processing method.
[0010] The data processing method provided in this application can obtain initial tracking information and a target business code file, wherein the tracking information includes the tracking identifier of the tracking point and the business code file where the tracking point is located; determine reference tracking information based on the target business code file; determine the tracking point to be processed from the tracking points corresponding to the reference tracking information based on the initial tracking information and the reference tracking information, and simulate running the target business code file to obtain the simulated tracking log of the tracking point to be processed; evaluate the tracking point to be processed based on the simulated tracking log and a preset evaluation standard to obtain evaluation information; update the initial tracking information based on the evaluation information to obtain target tracking information.
[0011] The data processing methods provided in this manual enable the management of event tracking points, improving the convenience of such management. First, event tracking points to be processed are initially screened. Then, the simulated event tracking logs obtained by simulating the processing of these points are used to update the event tracking information. This avoids issues such as event tracking point confusion, failure, and redundancy caused by multiple technicians developing event tracking points and frequent business updates, thus improving the accuracy of event tracking and consequently enhancing the accuracy of anomaly monitoring and performance optimization for business software. Attached Figure Description
[0012] Figure 1 This is a flowchart of a data processing method provided in an embodiment of this application; Figure 2 This is a schematic diagram illustrating a business logic and the execution logic of the target business code provided in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of a data processing device provided in an embodiment of this application; Figure 4 This is a structural block diagram of a computing device provided in one embodiment of this application. Detailed Implementation
[0013] Many specific details are set forth in the following description to provide a full understanding of this application. However, this application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of this application; therefore, this application is not limited to the specific embodiments disclosed below.
[0014] The terminology used in one or more embodiments of this application is for the purpose of describing particular embodiments only and is not intended to limit the scope of one or more embodiments of this application. The singular forms “a,” “the,” and “the” used in one or more embodiments of this application and in the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” used in one or more embodiments of this application refers to and includes any or all possible combinations of one or more associated listed items.
[0015] It should be understood that although the terms first, second, etc., may be used to describe various information in one or more embodiments of this application, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, first may also be referred to as second without departing from the scope of one or more embodiments of this application, and similarly, second may also be referred to as first.
[0016] As described in the background section, in the fields of digital cultural product creation software and digital cultural creative software, related business software such as game software can be developed and operated. During business project development, event tracking is a crucial tool for identifying and fixing business anomalies and code errors. The accuracy and completeness of event tracking are key to ensuring business development efficiency and product quality. However, current business projects face several problems. Business code is developed collaboratively by multiple technical personnel, leading to frequent updates and deletions of event tracking. Furthermore, each technical staff member has a different writing style, making event tracking management difficult. Business updates also lead to corresponding updates to the business code, which can cause event tracking to become invalid or redundant. This results in a large amount of redundant or erroneous information being reported, affecting normal business operations and reducing user experience. Simultaneously, it is impossible to quickly locate abnormal event tracking points and obtain related information through event tracking logs, resulting in low detection efficiency.
[0017] Based on this, this specification provides a data processing method that can obtain initial tracking information and a target business code file, wherein the tracking information includes the tracking identifier of the tracking point and the business code file where the tracking point is located; determine reference tracking information based on the target business code file; determine the tracking point to be processed from the tracking points corresponding to the reference tracking information based on the initial tracking information and the reference tracking information, and simulate running the target business code file to obtain the simulated tracking log of the tracking point to be processed; evaluate the tracking point to be processed based on the simulated tracking log and a preset evaluation standard to obtain evaluation information; update the initial tracking information based on the evaluation information to obtain target tracking information.
[0018] The data processing methods provided in this manual enable the management of event tracking points, improving the convenience of such management. First, event tracking points to be processed are initially screened. Then, the simulated event tracking logs obtained by simulating the processing of these points are used to update the event tracking information. This avoids issues such as event tracking point confusion, failure, and redundancy caused by multiple technicians developing event tracking points and frequent business updates, thus improving the accuracy of event tracking and consequently enhancing the accuracy of anomaly monitoring and performance optimization for business software.
[0019] In practical applications, the data processing methods provided in this manual can solve the existing problems of chaotic tracking point management, uncontrollable quality, low troubleshooting efficiency, and lack of quantitative evaluation, and realize automated management of the entire lifecycle of business code tracking points and closed-loop repair of anomalies.
[0020] It should be noted that the business project can be a game application project, a payment application project, or an enterprise-level application project. This manual does not impose specific restrictions on the business project and can be determined based on the actual situation. In other words, the data processing methods provided in this manual are applicable to any business development project that needs to achieve business observability, business anomaly tracking, and behavior analysis through data tracking.
[0021] This application provides a data processing method. This application also relates to a data processing apparatus, a computing device, a computer-readable storage medium, and a computer program product, which will be described in detail in the following embodiments.
[0022] Figure 1 A flowchart of a data processing method according to an embodiment of this application is shown. The data processing method is applied to a target terminal and specifically includes the following steps: Step 102: Obtain the initial tracking information and the target business code file. The tracking information includes the tracking identifier and the business code file where the tracking is located.
[0023] The subject executing the technical solution in this specification can be any computing device with computing capabilities, such as a terminal, server, etc. This specification does not impose any specific restrictions.
[0024] In one or more embodiments of this specification, a tracking point can be understood as code used to collect information such as user behavior, business processes, system status, or abnormal information. Tracking point information may include a tracking point identifier and the business code file where the tracking point is located. Of course, tracking point information may also include the business function where the tracking point is located, the tracking point field, the function of the tracking point, the function of the business function, the function of the business code file, etc.
[0025] The tracking point identifier can be understood as a marker used to identify different tracking points. The tracking point identifier can be a pre-set character, letter, or a combination of both, etc. This manual does not impose specific restrictions and can be set according to actual needs.
[0026] Typically, a business project corresponds to one or more business code files, and each business code file can implement a portion of the business project's logic. A business code file can contain one or more business functions. In one or more embodiments of this specification, a business code file can be understood as the code file corresponding to a business project, and a business function can be understood as a function called within a business code file.
[0027] As mentioned earlier, the business code corresponding to a business project needs to be updated along with business updates. Therefore, for each update, the initial tracking information represents the tracking information corresponding to the business code file before the update, and the target business code file refers to the updated business code file. Alternatively, the initial tracking information refers to the tracking information to be updated, and the target business code file refers to the updated business code file, or the business code file for which the initial tracking information needs to be updated. The initial tracking information corresponds to the initial business code file, and after the initial business code file is updated, it corresponds to the target business code file, requiring the initial tracking information to be updated based on the target business code.
[0028] In one or more embodiments of this specification, the embedded points and the embedded point information corresponding to the embedded points can be stored in a storage unit, so that the embedded point information can be obtained from the storage unit.
[0029] In one or more embodiments of this specification, business code files can be obtained first from the business code library corresponding to the business project. Furthermore, initial tracking information can be obtained; specifically, this initial tracking information can be obtained from the storage unit.
[0030] Based on the above, initial tracking information and target business code files can be obtained, thus providing a data foundation for updating the initial tracking information according to the target business code files, enabling tracking management, avoiding problems such as tracking redundancy or failure due to business updates, improving the accuracy and completeness of tracking, improving business execution efficiency and accuracy, and also improving the efficiency of anomaly investigation and the accuracy of anomaly repair.
[0031] Step 104: Determine the reference tracking information based on the target business code file.
[0032] In one or more embodiments of this specification, determining reference tracking information based on the target business code file includes: parsing the target business code file using a large language model to obtain reference tracking information.
[0033] In practical applications, the target business code file can be input into a large language model, allowing the model to parse the file and obtain reference tracking information. This reference tracking information can be understood as the tracking information corresponding to the tracking points within the target business code file.
[0034] In one or more embodiments of this specification, parsing prompt text can also be constructed. This parsing prompt text includes a tracking point definition text and a parsing target text. The tracking point definition text is used to prompt the large language model to understand the tracking point definition, enabling the large language model to know what a tracking point is. The parsing target text is used to prompt the large language model to parse the business code file based on the tracking point definition text in order to extract the tracking point information from the target business code file. Therefore, the parsing prompt text and the target business code file can be input into the large language model, so that the large language model can parse the target business code file according to the parsing prompt text to extract reference tracking point information from the target business code file.
[0035] Based on the above, reference tracking information can be extracted from the target business code file, thus providing a data foundation for updating the initial tracking information based on the reference tracking information in subsequent steps. This enables the management of tracking points, avoids problems such as tracking point redundancy or failure due to business updates, improves the accuracy and completeness of tracking points, improves the efficiency and accuracy of business execution, and also improves the efficiency of anomaly investigation and the accuracy of anomaly repair.
[0036] Step 106: Based on the initial tracking information and the reference tracking information, determine the tracking points to be processed from the tracking points corresponding to the reference tracking information, and simulate running the target business code file to obtain the simulated tracking logs of the tracking points to be processed.
[0037] In one or more embodiments of this specification, determining the tracking point to be processed from the tracking points corresponding to the reference tracking point information based on the initial tracking point information and the reference tracking point information includes: By comparing the initial embedding information and the reference embedding information, differential embedding information is obtained, wherein the differential embedding information is the embedding information in the reference embedding information that is different from the initial embedding information; The points corresponding to the difference in the embedding information are taken as the embedding points to be processed.
[0038] The event tracking points to be processed can include those that exist simultaneously in both the initial event tracking point information and the reference event tracking point information, where the initial event tracking point information and the reference event tracking point information are different. They can also include those that exist in the reference event tracking point information but not in the initial event tracking point information. Furthermore, they can include those that exist in the initial event tracking point information but not in the reference event tracking point information.
[0039] In practical applications, the initial and reference tracking information can be compared using a large language model to determine the differences between them and obtain the differential tracking information. This differential tracking information can be understood as the tracking information in the reference information that differs from the initial tracking information, or in other words, the information in the reference tracking information that is different from the initial tracking information.
[0040] In one or more embodiments of this specification, when comparing the initial tracking information and the reference tracking information to obtain differential tracking information and tracking points to be processed, if it is determined that a tracking point exists in the tracking points corresponding to the reference tracking information but does not exist in the tracking points corresponding to the initial tracking information, then the tracking point can be determined as a tracking point to be processed, and the reference tracking information corresponding to the tracking point to be processed is differential tracking information. Alternatively, if it is determined that a tracking point exists in both the tracking points corresponding to the reference tracking information and the tracking points corresponding to the initial tracking information, and the reference tracking information and the initial tracking information corresponding to the tracking point are different, then the tracking point can be determined as a tracking point to be processed, and the tracking information corresponding to the tracking point to be processed is differential tracking information.
[0041] It should be noted that if a tracking point exists in the tracking points corresponding to the reference tracking point information but not in the tracking points corresponding to the initial tracking point information, this is referred to as a tracking point addition in this specification. That is, this tracking point does not exist in the initial tracking point information and is added to the business code file after a business update. If a tracking point exists in both the tracking points corresponding to the reference tracking point information and the tracking points corresponding to the initial tracking point information, and the reference tracking point information and the initial tracking point information are different, this is referred to as a tracking point update in this specification. That is, after a business update, the tracking point remains unchanged, or its purpose or function remains unchanged, but the tracking point information corresponding to the tracking point changes. This change in tracking point information could be an update of the business code file containing the tracking point, an update of the business function containing the tracking point, etc. If a tracking point exists in the tracking points corresponding to the initial tracking point information but not in the tracking points corresponding to the reference tracking point information, this is referred to as a tracking point deletion in this specification. That is, after a business update, the previously used tracking point is deleted due to reasons such as being invalid or having little effect, and does not exist in the tracking points corresponding to the target business code file.
[0042] In one or more embodiments of this specification, to manage event tracking points and avoid issues such as tracking point confusion, failure, and redundancy caused by business updates and development by multiple technical personnel, the initial tracking point information and the tracking points within the initial information can be adjusted based on the tracking points to be processed and the differential tracking point information. During the adjustment process, the tracking points to be processed need to be evaluated to determine whether the tracking points in the initial tracking point information should be adjusted based on the tracking points to be processed, thus ensuring that the adjustment is optimal for the business project. To evaluate the tracking points to be processed, the tracking point logs corresponding to the tracking points to be processed need to be obtained, as these logs are crucial for reflecting the correctness, completeness, and effectiveness of the tracking points. Therefore, in one or more embodiments of this specification, simulated tracking point logs of the tracking points to be processed can be obtained by simulating the execution of the target business code file.
[0043] In one or more embodiments of this specification, simulating the execution of the target business code file to obtain simulated event logs for the event points to be processed includes: Obtain the execution logic of the target business code, wherein the execution logic of the target business code represents the execution order of the target business code file; Based on the execution logic of the target business code, simulate the execution of the target business code file to obtain the simulated event logs of the event points to be processed.
[0044] It should be noted that the execution logic of the target business code can be understood as the execution logic or execution order of the target business code, that is, the execution logic of the target business code represents the execution order of the target business code file.
[0045] In practical applications, the execution logic of the target business code can be determined based on the business logic or business architecture corresponding to the business project. Business logic or business architecture can be understood as a sequence describing the order in which the business project performs its tasks; the execution logic of the target business code can be understood as the execution order of the business code files that implement the business logic. For example... Figure 2 The diagram illustrates a business logic and target business code execution logic provided in one embodiment of this specification. As can be seen, the business project can be a game project, and the business logic of the game project can be user login, game main page rendering, and game execution. Therefore, the target business code execution logic can be obtained as the user login code file, the game main page rendering code file, and the game execution code file. Thus, the business logic corresponding to the business project can be directly obtained to obtain the target business code execution logic.
[0046] In practical applications, the business logic corresponding to a business project can be stored in a configuration file, such as a JSON or YAML file, or it can be automatically generated by the business project architecture document. In other words, the business logic corresponding to a business project can be pre-configured.
[0047] In one or more embodiments of this specification, when obtaining the business code execution logic, the target business code file and the business logic can be input into a large language model, enabling the large language model to generate the business code execution logic of the target business code file corresponding to the business logic. Specifically, the large language model can parse the business logic and, based on the target business code file's mapping to directory structure, business function call graph, and naming conventions, identify the target business code file corresponding to each business stage, thereby constructing a mapping relationship from business actions to business code locations.
[0048] In one or more embodiments of this specification, the execution logic of the target business code can be represented as a knowledge graph. That is, a knowledge graph corresponding to the business code file can be constructed based on the business logic corresponding to the business project, and this knowledge graph represents the execution order of the target business code file.
[0049] In one or more embodiments of this specification, simulating the execution of the target business code file to obtain simulated event logs for the event points to be processed, based on the target business code execution logic, includes: The target business code execution logic and the target business code file are input into a large language model, so that the large language model simulates the execution of the target business code file according to the target business code execution logic, and generates simulated event logs for the event points to be processed.
[0050] In practical applications, the target business code file can be simulated by using a large language model. Alternatively, other simulation tools or platforms can be used to simulate the execution logic of the target business code file to obtain simulated event logs for the event points to be processed.
[0051] It should be noted that when simulating the execution of the target business code file to obtain the simulated event logs for the event points to be processed, you can run all target business code files to obtain the event logs for the event points corresponding to those target business code files, and then select the simulated event logs for the event points to be processed from them. Alternatively, you can only simulate the execution of the business code file containing the event point to be processed. Obtaining the simulated event logs corresponding to the event point to be processed improves the simulation execution efficiency.
[0052] Furthermore, since the actual business scenarios are different, or rather, the user's operations on the business application are not the same for the business project, such as the operation process of user A on the business application being different from that of user B on the business application, the generated event logs will be different. Therefore, in one or more embodiments of this specification, when simulating the running of the business code file, multiple scenarios can be simulated to obtain multiple simulated event logs corresponding to the event to be processed, thereby improving the accuracy of subsequent evaluation.
[0053] Step 108: Evaluate the tracking points to be processed based on the simulated tracking point logs and preset evaluation criteria to obtain evaluation information.
[0054] In practical applications, simulated event logs generated by simulation and preset evaluation criteria can be used to automatically evaluate the event points to be processed, thereby obtaining evaluation information for the event points. Specifically, in one or more embodiments of this specification, the simulated event logs and preset evaluation criteria can be input into a large language model, so that the large language model can evaluate the event points to be processed according to the preset evaluation criteria and simulated event logs, and obtain the evaluation score, i.e., the evaluation information, for the event points to be processed.
[0055] In one or more embodiments of this specification, the preset evaluation criteria may include coverage, accuracy, usability, and impact. Correspondingly, the evaluation scores include coverage evaluation score, accuracy evaluation score, usability evaluation score, and impact evaluation score. The sum of the coverage evaluation score, accuracy evaluation score, usability evaluation score, and impact evaluation score can be used as the final evaluation score for the event tracking point to be processed. Alternatively, based on preset weights, the weighted sum of the coverage evaluation score, accuracy evaluation score, usability evaluation score, and impact evaluation score can be used as the final evaluation score for the event tracking point to be processed. This allows updating the initial event tracking information based on the final evaluation score to obtain the target event tracking information.
[0056] Coverage can be understood as the completeness of the tracking points corresponding to the critical business code files, or whether tracking points have been deployed in the critical business code files. Specifically, the presence of valid tracking points in the critical business code files can be checked based on the business logic. If tracking points are missing in the critical business code files, the coverage evaluation score will be low. The critical business code files can be pre-set, that is, which one or more business code files can be pre-set as critical business code files, or the correspondence between critical business code files and tracking points can be pre-set.
[0057] Accuracy can be understood as assessing whether the content of the event tracking logs is consistent with business expectations. Specifically, it can compare simulated event tracking logs with standard event tracking logs to determine whether there are problems such as missing, misaligned, incorrect type, or semantic deviation in the event tracking fields in the simulated event tracking logs. If these exist, the accuracy evaluation score is low, and if they do not exist, the accuracy evaluation score is high. Standard event tracking logs can be set in advance.
[0058] Usability can be understood as reflecting the effectiveness of event tracking logs in actual problem investigation. This usability is used to assess whether the event tracking logs contain sufficient contextual information, such as user ID, device model, and status snapshots, and whether they are well-structured, so that the logs can be directly used for downstream anomaly investigation and analysis. A well-structured log results in a higher usability score, while a poorly structured log, such as vague, redundant, or missing key identifiers, results in a lower usability score.
[0059] The impact score can be understood as assessing the potential impact of the event tracking on business performance. Specifically, it can be determined whether the event tracking might cause lag, memory usage, or network congestion based on the event tracking trigger frequency, single execution time, data volume, and the execution logic (execution path) of the corresponding business code. High-frequency, high-overhead event tracking results in a lower impact score, while low-frequency, low-overhead event tracking results in a higher impact score.
[0060] By using the aforementioned preset evaluation criteria and employing a large language model to evaluate the event tracking points, the large language model can improve the accuracy of the evaluation information, thereby improving the accuracy of updating the initial event tracking point information.
[0061] Furthermore, in one or more embodiments of this specification, after evaluating the tracking point to be processed according to the preset evaluation criteria, if the evaluation score corresponding to the tracking point to be processed is less than the preset evaluation score threshold, optimization suggestion text for the tracking point to be processed can be generated by a large language model or manually, so that the tracking point to be processed can be modified according to the optimization suggestion text.
[0062] Step 110: Update the initial embedding information based on the evaluation information to obtain the target embedding information.
[0063] In one or more embodiments of this specification, updating the initial tracking information based on the evaluation information to obtain target tracking information includes: If the evaluation information meets the preset evaluation conditions, the initial embedding information is updated according to the reference embedding information corresponding to the embedding point to be processed, and the target embedding information is obtained.
[0064] Among them, the preset evaluation conditions can be preset evaluation score thresholds.
[0065] Specifically, as described in step 108, the evaluation information includes an evaluation score. Therefore, in step 110, if the evaluation score corresponding to the tracking information to be processed is greater than the preset evaluation score threshold, the initial tracking information can be updated according to the tracking information corresponding to the tracking point to be processed to obtain the target tracking information.
[0066] Accordingly, if the evaluation information does not meet the preset evaluation conditions, there is no need to update the initial tracking information; the initial tracking information can be directly used as the target tracking information. Specifically, if the evaluation score corresponding to the tracking information to be processed is less than or equal to a preset evaluation score threshold, the initial tracking information can be used as the target tracking information.
[0067] In one or more embodiments of this specification, updating the initial embedding information based on the reference embedding information corresponding to the embedding point to be processed includes: If it is determined that the pending event does not exist in the initial event information, the reference event information corresponding to the pending event is added to the initial event information. If it is determined that the pending event exists in the initial event tracking information, the event tracking information corresponding to the pending event in the initial event tracking information is updated to include the reference event tracking information corresponding to the pending event.
[0068] In one or more embodiments of this specification, the tracking status may include tracking point addition and tracking point update. If it is determined that the tracking point to be processed does not exist in the initial tracking information, reference tracking point information corresponding to the tracking point to be processed is added to the initial tracking information. This can also be understood as, if it is determined that the tracking status of the tracking point to be processed is tracking point addition, reference tracking point information corresponding to the tracking point to be processed can be added to the initial tracking information. If it is determined that the tracking point to be processed exists in the initial tracking information, the tracking point information corresponding to the tracking point to be processed in the initial tracking information is updated to include reference tracking point information corresponding to the tracking point to be processed. This can also be understood as, if the tracking status of the tracking point to be processed is tracking point update, the tracking point information corresponding to the tracking point to be processed in the initial tracking information is updated to include reference tracking point information corresponding to the tracking point to be processed.
[0069] It should be noted that for event tracking deletion—that is, if an event tracking point exists in the initial event tracking information but not in the reference event tracking information—you can choose to delete the event tracking point in the initial event tracking information or retain it. The specific decision should be made based on the actual situation. Alternatively, you can use the aforementioned evaluation method to assess whether the evaluation score corresponding to the event tracking point in the initial event tracking information is greater than a preset evaluation score threshold under the target business logic. If it is, retain the event tracking point; otherwise, delete it.
[0070] In summary, the data processing method provided in this manual enables the management of event tracking points, improving the convenience of event tracking point management. First, event tracking points to be processed are initially screened. Then, by simulating the operation of these points, the event tracking information is updated. This avoids problems such as event tracking point confusion, failure, and redundancy caused by multiple technical personnel developing event tracking points and frequent business updates, thus improving the accuracy of event tracking points and consequently enhancing the accuracy of anomaly monitoring and performance optimization of business software.
[0071] Furthermore, in one or more embodiments of this specification, the feature vector of the simulated event log of the event to be processed can be determined, and the first feature vector of the simulated event log of the event to be processed can be stored. Obtain the target event logs corresponding to the actual running target business code file, and determine the second feature vector corresponding to the event to be processed based on the target event logs; The abnormal state of the embedded point to be processed is determined based on the first feature vector and the second feature vector.
[0072] In practical applications, after a business project goes live, event logs can be collected, specifically the target event logs corresponding to the actual execution of the target business code file. Then, a first feature vector corresponding to the simulated event logs of the event to be processed and a second feature vector corresponding to the target event logs can be determined. Based on the first and second feature vectors, the abnormal state of the event to be processed can be determined.
[0073] It should be noted that features of the simulated event logs and the target event logs of the event to be processed can be extracted according to the relevant encoder or feature extraction model to obtain the first feature vector and the second feature vector.
[0074] Specifically, in one or more embodiments of this specification, determining the abnormal state of the tracking point to be processed based on the first feature vector and the second feature vector includes: Determine the similarity between the first feature vector and the second feature vector; If the similarity is greater than a preset similarity threshold, the data point to be processed is determined to be normal. If the similarity is less than or equal to a preset similarity threshold, the unprocessed embedding point is determined to be abnormal.
[0075] In other words, if the first feature vector and the second feature vector have a high similarity, it can be determined that the tracking point to be processed is normal; if the first feature vector and the second feature vector have a low similarity, it can be determined that the tracking point to be processed is abnormal.
[0076] It should be noted that, when determining the similarity between the first feature vector and the second feature vector, the Euclidean distance between them can be calculated to obtain the similarity. Alternatively, the cosine similarity between them can be calculated to obtain the similarity. This specification does not specifically limit how the similarity between the first feature vector and the second feature vector is determined.
[0077] In one or more embodiments of this specification, the tracking information, tracking logs, and feature vectors of the tracking logs can be stored together, so that the tracking information, tracking logs, and feature vectors of the tracking logs can be located based on the tracking identifier.
[0078] Furthermore, when the similarity is determined to be greater than the preset similarity threshold, the target event log and the second feature vector can be stored, or the target event log and the second feature vector can be stored in the event log corresponding to the event, so as to improve the accuracy of subsequent event anomaly location.
[0079] Furthermore, in one or more embodiments of this specification, after determining the anomaly of the tracking point to be processed, the method further includes: Generate anomaly repair suggestions for the unprocessed embedding point, and repair the unprocessed embedding point according to the anomaly repair suggestions.
[0080] In practical applications, when an anomaly is determined in the event that the similarity is less than or equal to a preset similarity threshold, the anomaly can be input into a large language model. This allows the large language model to repair the anomaly and generate anomaly repair suggestions. Specifically, the large language model can analyze and repair the anomaly based on the error messages and business function content corresponding to the anomaly, generating a normal event tracking code example and repair suggestions.
[0081] Based on the above, it is possible to detect whether the embedded points are normal or abnormal, thereby enabling the location of abnormal embedded points and the repair of abnormal embedded points based on repair suggestions, thus improving repair efficiency.
[0082] In one or more embodiments of this specification, the event tracking points can also be managed visually. Specifically, a visual management unit for event tracking points can be set up to support the management of a global event tracking point dashboard, daily event tracking analysis reports, and manual event tracking point marking, etc.
[0083] Based on the above data processing methods, digital cultural and creative software or game and animation software corresponding to business projects can be developed, which can provide users with game digital content services and provide data tracking to detect the status of business services and improve user experience.
[0084] Corresponding to the above method embodiments, this application also provides data processing apparatus embodiments. Figure 3 A schematic diagram of the structure of a data processing apparatus according to an embodiment of this application is shown. Figure 3 As shown, the device includes: The acquisition module 302 is configured to acquire initial tracking information and target business code file, wherein the tracking information includes the tracking identifier of the tracking point and the business code file where the tracking point is located; The determination module 304 is configured to determine reference tracking information based on the target business code file. The simulation module 306 is configured to determine the event to be processed from the event points corresponding to the reference event points based on the initial event point information and the reference event point information, and simulate running the target business code file to obtain the simulated event point logs of the event to be processed. The module 308 is configured to evaluate the tracking point to be processed based on the simulated tracking point logs and preset evaluation criteria, and obtain evaluation information. The update module 310 is configured to update the initial embedding information based on the evaluation information to obtain the target embedding information.
[0085] Optionally, the determining module 304 is further configured to: parse the target business code file through a large language model to obtain reference tracking information.
[0086] Optionally, the simulation module 306 is further configured to: compare the initial embedding information and the reference embedding information to obtain differential embedding information, wherein the differential embedding information is embedding information in the reference embedding information that is different from the initial embedding information; and take the embeddings corresponding to the differential embedding information as embeddings to be processed.
[0087] Optionally, the simulation module 306 is further configured to: obtain the execution logic of the target business code, wherein the execution logic of the target business code represents the execution order of the target business code file; and simulate running the target business code file according to the execution logic of the target business code to obtain the simulated event log of the event to be processed.
[0088] Optionally, the simulation module 306 is further configured to: input the target business code execution logic and the target business code file into a large language model, so that the large language model simulates the execution of the target business code file according to the target business code execution logic, and generates the simulated event log of the event to be processed.
[0089] Optionally, the update module 310 is further configured to: when the evaluation information meets the preset evaluation conditions, update the initial embedding information according to the reference embedding information corresponding to the embedding point to be processed, and obtain the target embedding information.
[0090] Optionally, the update module 310 is further configured to: add reference tracking information corresponding to the tracking point to be processed to the initial tracking information when it is determined that the tracking point to be processed does not exist in the initial tracking information; If it is determined that the pending event exists in the initial event tracking information, the event tracking information corresponding to the pending event in the initial event tracking information is updated to include the reference event tracking information corresponding to the pending event.
[0091] Optionally, the device further includes: a detection module; The detection module is configured to: determine the feature vector of the simulated event log of the event to be processed, and store the first feature vector of the simulated event log of the event to be processed; obtain the target event log corresponding to the actual running of the target business code file, and determine the second feature vector corresponding to the event to be processed based on the target event log; and determine the abnormal state of the event to be processed based on the first feature vector and the second feature vector.
[0092] Optionally, the detection module is further configured to: determine the similarity between the first feature vector and the second feature vector; determine that the tracking point to be processed is normal if the similarity is greater than a preset similarity threshold; and determine that the tracking point to be processed is abnormal if the similarity is less than or equal to the preset similarity threshold.
[0093] Optionally, the detection module is further configured to: generate anomaly repair suggestions for the unprocessed embedding point, and repair the unprocessed embedding point according to the anomaly repair suggestions.
[0094] The data processing apparatus provided in this embodiment can acquire initial tracking point information and a target business code file. The tracking point information includes the tracking point identifier and the business code file where the tracking point is located. Based on the target business code file, reference tracking point information is determined. Based on the initial tracking point information and the reference tracking point information, a tracking point to be processed is determined from the tracking points corresponding to the reference tracking point information, and the target business code file is simulated to obtain a simulated tracking point log for the tracking point to be processed. The tracking point to be processed is evaluated based on the simulated tracking point log and a preset evaluation standard to obtain evaluation information. The initial tracking point information is updated based on the evaluation information to obtain target tracking point information.
[0095] The data processing device provided in the embodiments of this specification enables the management of event tracking points, improving the convenience of event tracking point management. First, event tracking points to be processed are initially screened. Then, the event tracking point information is updated by simulating the running of these points and obtaining simulated event tracking point logs. This avoids problems such as event tracking point confusion, failure, and redundancy caused by multiple technicians developing event tracking points and frequent business updates, improving the accuracy of event tracking points and thus enhancing the accuracy of anomaly monitoring and performance optimization of business software.
[0096] The above is an illustrative scheme of a data processing apparatus according to this embodiment. It should be noted that the technical solution of this data processing apparatus and the technical solution of the aforementioned data processing method belong to the same concept. Details not described in detail in the technical solution of the data processing apparatus can be found in the description of the technical solution of the aforementioned data processing method. Furthermore, the components in the apparatus embodiment should be understood as functional modules necessary to implement each step of the program flow or each step of the method; these functional modules are not actual functional divisions or separations. An apparatus claim defined by such a set of functional modules should be understood as a functional module architecture that primarily implements the solution through the computer program described in the specification, and not as a physical device that primarily implements the solution through hardware.
[0097] Figure 4 A structural block diagram of a computing device 400 according to an embodiment of this application is shown. The components of the computing device 400 include, but are not limited to, a memory 410 and a processor 420. The processor 420 is connected to the memory 410 via a bus 430, and a database 450 is used to store data.
[0098] The computing device 400 also includes an access device 440, which enables the computing device 400 to communicate via one or more networks 460. Examples of these networks include PSTN (Public Switched Telephone Network), LAN (Local Area Network), WAN (Wide Area Network), PAN (Personal Area Network), or combinations of communication networks such as the Internet. The access device 440 may include one or more of any type of wired or wireless network interface (e.g., NIC (Network Interface Controller)), such as an IEEE 802.11 WLAN (Wireless Local Area Network) wireless interface, Wi-MAX (Worldwide Interoperability for Microwave Access) interface, Ethernet interface, USB (Universal Serial Bus) interface, cellular network interface, Bluetooth interface, and NFC (Near Field Communication).
[0099] In one embodiment of this application, the aforementioned components of the computing device 400 and Figure 4 Other components, not shown, can also be connected to each other, for example, via a bus. It should be understood that... Figure 4 The block diagram of the computing device shown is for illustrative purposes only and is not intended to limit the scope of this application. Those skilled in the art can add or replace other components as needed.
[0100] Computing device 400 can be any type of stationary or mobile computing device, including mobile computers or mobile computing devices (e.g., tablet computers, personal digital assistants, laptop computers, notebook computers, netbooks, etc.), mobile phones (e.g., smartphones), wearable computing devices (e.g., smartwatches, smart glasses, etc.) or other types of mobile devices, or stationary computing devices such as desktop computers or PCs (Personal Computers). Computing device 400 can also be a mobile or stationary server.
[0101] The processor 420 is used to execute computer-executable instructions for the data processing method.
[0102] The above is an illustrative scheme of a computing device according to this embodiment. It should be noted that the technical solution of this computing device and the technical solution of the data processing method described above belong to the same concept. For details not described in detail in the technical solution of the computing device, please refer to the description of the technical solution of the data processing method described above.
[0103] One embodiment of this application also provides a computer-readable storage medium storing a computer program / instructions which, when executed by a processor, are used for a data processing method.
[0104] The above is an illustrative scheme of a computer-readable storage medium according to this embodiment. It should be noted that the technical solution of this storage medium and the technical solution of the data processing method described above belong to the same concept. For details not described in detail in the technical solution of the storage medium, please refer to the description of the technical solution of the data processing method described above.
[0105] An embodiment of this application also provides a computer program product, including a computer program / instructions that, when executed by a processor, are used for a data processing method.
[0106] The above is an illustrative scheme of a computer program product according to this embodiment. It should be noted that the technical solution of this computer program product and the technical solution of the data processing method described above belong to the same concept. For details not described in detail in the technical solution of the computer program product, please refer to the description of the technical solution of the data processing method described above.
[0107] The computer program / instructions include computer program code, which may be in the form of source code, object code, executable file, or certain intermediate forms. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, ROM (Read-Only Memory), RAM (Random Access Memory), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium may be appropriately added to or subtracted according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media may not include electrical carrier signals and telecommunication signals.
[0108] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.
[0109] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.
[0110] The preferred embodiments disclosed above are merely illustrative of this application. The optional embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of this application. These embodiments are selected and specifically described in this application to better explain the principles and practical applications of this application, thereby enabling those skilled in the art to better understand and utilize this application. This application is limited only by the claims and their full scope and equivalents.
Claims
1. A data processing method, characterized in that, include: Obtain initial event tracking information and target business code file. Event tracking information includes the event tracking identifier and the business code file where the event tracking is located. Based on the target business code file, determine the reference tracking point information; Based on the initial tracking information and the reference tracking information, the tracking points to be processed are determined from the tracking points corresponding to the reference tracking information, and the target business code file is simulated to obtain the simulated tracking logs of the tracking points to be processed. The simulation tracking logs and preset evaluation criteria are used to evaluate the tracking points to be processed, and evaluation information is obtained. The initial embedding information is updated based on the evaluation information to obtain the target embedding information.
2. The method according to claim 1, characterized in that, Based on the target business code file, determine the reference tracking information, including: The target business code file is parsed using a large language model to obtain reference tracking information.
3. The method according to claim 1, characterized in that, Based on the initial embedding information and the reference embedding information, determine the embedding points to be processed from the embedding points corresponding to the reference embedding information, including: By comparing the initial embedding information and the reference embedding information, differential embedding information is obtained, wherein the differential embedding information is the embedding information in the reference embedding information that is different from the initial embedding information; The points corresponding to the difference in the embedding information are taken as the embedding points to be processed.
4. The method according to claim 1, characterized in that, Simulate running the target business code file to obtain simulated event logs for the event points to be processed, including: Obtain the execution logic of the target business code, wherein the execution logic of the target business code represents the execution order of the target business code file; Based on the execution logic of the target business code, simulate the execution of the target business code file to obtain the simulated event logs of the event points to be processed.
5. The method according to claim 4, characterized in that, Based on the execution logic of the target business code, simulate the execution of the target business code file to obtain simulated event logs for the event points to be processed, including: The target business code execution logic and the target business code file are input into a large language model, so that the large language model simulates the execution of the target business code file according to the target business code execution logic, and generates simulated event logs for the event points to be processed.
6. The method according to claim 1, characterized in that, Update the initial tracking information based on the evaluation information to obtain the target tracking information, including: If the evaluation information meets the preset evaluation conditions, the initial embedding information is updated according to the reference embedding information corresponding to the embedding point to be processed, and the target embedding information is obtained.
7. The method according to claim 6, characterized in that, Update the initial tracking information according to the reference tracking information corresponding to the tracking point to be processed, including: If it is determined that the pending event does not exist in the initial event information, the reference event information corresponding to the pending event is added to the initial event information. If it is determined that the pending event exists in the initial event tracking information, the event tracking information corresponding to the pending event in the initial event tracking information is updated to include the reference event tracking information corresponding to the pending event.
8. The method according to any one of claims 1 to 7, characterized in that, The method further includes: Determine the feature vector of the simulated event log of the event to be processed, and store the first feature vector of the simulated event log of the event to be processed; Obtain the target event logs corresponding to the actual running target business code file, and determine the second feature vector corresponding to the event to be processed based on the target event logs; The abnormal state of the embedded point to be processed is determined based on the first feature vector and the second feature vector.
9. The method according to claim 8, characterized in that, Determining the abnormal state of the tracking point to be processed based on the first feature vector and the second feature vector includes: Determine the similarity between the first feature vector and the second feature vector; If the similarity is greater than a preset similarity threshold, the data point to be processed is determined to be normal. If the similarity is less than or equal to a preset similarity threshold, the unprocessed embedding point is determined to be abnormal.
10. The method according to claim 9, characterized in that, After determining the anomaly of the embedded point to be processed, the method further includes: Generate anomaly repair suggestions for the unprocessed embedding point, and repair the unprocessed embedding point according to the anomaly repair suggestions.
11. A data processing apparatus, characterized in that, include: The acquisition module is configured to acquire initial event tracking information and target business code file, wherein the event tracking information includes the event tracking identifier and the business code file where the event tracking is located; The determination module is configured to determine reference tracking information based on the target business code file; The simulation module is configured to determine the event to be processed from the event points corresponding to the reference event point information based on the initial event point information and the reference event point information, and to simulate running the target business code file to obtain the simulated event point logs of the event to be processed. The acquisition module is configured to evaluate the tracking points to be processed based on the simulated tracking point logs and preset evaluation criteria, and obtain evaluation information. The update module is configured to update the initial tracking information based on the evaluation information to obtain the target tracking information.
12. A computing device, characterized in that, include: Memory and processor; The memory is used to store computer programs / instructions, and the processor is used to execute the computer programs / instructions, wherein when the computer programs / instructions are executed by the processor, they implement the method according to any one of claims 1 to 10.
13. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program / instructions that, when executed by a processor, implement the method described in any one of claims 1 to 10.
14. A computer program product, characterized in that, Includes a computer program / instruction that, when executed by a processor, implements the method according to any one of claims 1 to 10.