Data processing method and device

Abstract

The embodiment of the invention provides a data processing method and device.The method comprises the steps that a data query instruction for a to-be-queried item is received, and the data query instruction comprises target item information of the to-be-queried item; determining a target message corresponding to the to-be-queried item and first key information corresponding to the target message according to the target item information; determining a target initial process corresponding to the target message according to the first key information; and based on the target initial process and second key information, target log information corresponding to the target message is acquired, and the second key information is acquired according to historical target log information corresponding to a historical target message of the to-be-queried project. Determining a target initial process through the first key information, and obtaining each process passed in a target message circulation process by taking the target initial process as a starting point; through the second key information, the extraction of the target log information in the whole circulation process of the target message can be realized, and the extraction efficiency and integrity of the target log information are improved.

Description

Technical Field

[0001] This specification relates to the field of computer technology, and in particular to a data processing method and apparatus. Background Technology

[0002] During production, various processes in the production system often process multiple messages synchronously or asynchronously, generating a large amount of log data. Since the multiple messages processed by a single process often originate from different projects, and messages corresponding to a single project typically flow between multiple different processes, obtaining project log data based on process logs often requires opening multiple process log pages and viewing and filtering the project-specific log data on each page.

[0003] However, the above methods require a high level of professional skills from staff, consume significant manpower and data query time, and are prone to confusing log data from different messages and missing log data, resulting in low efficiency in problem localization and analysis. Summary of the Invention

[0004] In view of the above, embodiments of this specification provide a data processing method. One or more embodiments of this specification also relate to a data processing apparatus, a computing device, a computer-readable storage medium, and a computer program product, to address the technical deficiencies existing in the prior art.

[0005] According to a first aspect of the embodiments of this specification, a data processing method is provided, comprising:

[0006] Receive a data query instruction for the item to be queried, wherein the data query instruction includes the target item information of the item to be queried;

[0007] Based on the target project information, determine the target message corresponding to the project to be queried and the first key information corresponding to the target message;

[0008] Based on the first key information, determine the target initial process corresponding to the target message;

[0009] Based on the initial process and second key information of the target, the target log information corresponding to the target message is obtained. The second key information is obtained from the historical target log information corresponding to the historical target messages of the project to be queried.

[0010] According to a second aspect of the embodiments of this specification, a data processing apparatus is provided, comprising:

[0011] The receiving module is configured to receive a data query instruction for the item to be queried, wherein the data query instruction includes the target item information of the item to be queried;

[0012] The first determination module is configured to determine the target message corresponding to the project to be queried and the first key information corresponding to the target message based on the target project information;

[0013] The second determining module is configured to determine the target initial process corresponding to the target message based on the first key information;

[0014] The acquisition module is configured to acquire target log information corresponding to the target message based on the target initial process and second key information. The second key information is obtained from the historical target log information corresponding to the historical target messages of the project to be queried.

[0015] According to a third aspect of the embodiments of this specification, a computing device is provided, comprising:

[0016] Memory and processor;

[0017] The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions, which, when executed by the processor, implement the steps of the above-described data processing method.

[0018] According to a fourth aspect of the embodiments of this specification, a computer-readable storage medium is provided that stores computer-executable instructions, which, when executed by a processor, implement the steps of the data processing method described above.

[0019] According to a fifth aspect of the embodiments of this specification, a computer program product is provided, including a computer program / instructions that, when executed by a processor, implement the steps of the above-described data processing method.

[0020] One embodiment of this specification implements receiving a data query instruction for a project to be queried, wherein the data query instruction includes target project information of the project to be queried; determining the target message corresponding to the project to be queried and the first key information corresponding to the target message based on the target project information; determining the target initial process corresponding to the target message based on the first key information; and obtaining the target log information corresponding to the target message based on the target initial process and the second key information, wherein the second key information is obtained from the historical target log information corresponding to the historical target messages of the project to be queried.

[0021] Thus, by using the first key information corresponding to the target message, the target initial process corresponding to the target message can be determined. Starting from the target initial process, the various processes that the target message passes through during its flow can be obtained. By using the second key information, the target log information corresponding to the target message can be extracted from the process logs of each process. This enables the extraction of target log information throughout the entire flow of the target message, avoiding confusion with log information of other messages in the process logs and preventing omissions of target log information. This improves the efficiency and completeness of target log information extraction, thereby enhancing the efficiency of operations and maintenance personnel in locating and analyzing problems based on target log information. Attached Figure Description

[0022] Figure 1 This is an architecture diagram of a data processing system provided in one embodiment of this specification;

[0023] Figure 2 This is a flowchart illustrating a data processing method provided in one embodiment of this specification;

[0024] Figure 3 This is a schematic diagram of the structure of a data processing apparatus provided in one embodiment of this specification;

[0025] Figure 4 This is a structural block diagram of a computing device provided in one embodiment of this specification. Detailed Implementation

[0026] Many specific details are set forth in the following description to provide a full understanding of this specification. However, this specification can be implemented in many other ways than those described herein, and those skilled in the art can make similar extensions without departing from the spirit of this specification. Therefore, this specification is not limited to the specific implementations disclosed below.

[0027] The terminology used in one or more embodiments of this specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the one or more embodiments of this specification. The singular forms “a,” “described,” and “the” as used in one or more embodiments of this specification and 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” as used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more associated listed items.

[0028] 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 specification, 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 specification, and similarly, second may also be referred to as first. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to a determination."

[0029] Furthermore, it should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in one or more embodiments of this specification are all information and data authorized by the user or fully authorized by all parties. Moreover, the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0030] In one or more embodiments of this specification, a large model refers to a deep learning model with a large number of model parameters, typically containing hundreds of millions, tens of billions, hundreds of billions, trillions, or even tens of trillions of model parameters. A large model can also be called a foundational model. It is pre-trained using large-scale unlabeled corpora to produce a pre-trained model with hundreds of millions of parameters. Such models can adapt to a wide range of downstream tasks and have good generalization ability. Examples include Large Language Models (LLMs) and multi-modal pre-training models.

[0031] In practical applications, large models only require a small number of samples to fine-tune the pre-trained model before they can be applied to different tasks. Large models can be widely used in fields such as Natural Language Processing (NLP) and Computer Vision. Specifically, they can be applied to computer vision tasks such as Visual Question Answering (VQA), Image Captioning (IC), and Image Generation, as well as NLP tasks such as text-based sentiment classification, text summarization, and machine translation. The main application scenarios for large models include digital assistants, intelligent robots, search, online education, office software, e-commerce, and intelligent design.

[0032] First, the terms and concepts used in one or more embodiments of this specification will be explained.

[0033] A message is a complete unit of information used to transmit data, commands, or control information between two or more entities (such as computers, devices, and processes) in a network. A message typically consists of a header, a payload, and a trailer. The header may contain control information and metadata, such as source address, destination address, message length, priority, and sending timestamp, used to guide how the message is routed, processed, and to identify the sender and receiver. The payload is the core content of the message, i.e., the actual data to be transmitted, which can be text, images, audio, video, or any other form of data. The trailer may contain checksums, error detection codes, etc., used to ensure data integrity. The specific format and content of a message can be determined based on the specific communication protocol and application scenario.

[0034] A PLC (Programmable Logic Controller) is a digital electronic system designed for industrial environments, offering industrial-grade reliability, stability, and durability. Through its internal programmable memory, a PLC uses specific programming languages ​​(such as ladder diagrams, structured text, and function block diagrams) to automate the control of machinery and production processes.

[0035] During production, various processes in the production system often process multiple messages synchronously or asynchronously, generating a large amount of log data. Since the multiple messages processed by a single process often originate from different projects, and messages corresponding to a single project typically flow between multiple different processes, obtaining project log data based on process logs often requires opening multiple process log pages and viewing and filtering the project-specific log data on each page.

[0036] However, since the timestamps and other information of different messages in a process log are often very similar, staff can easily miss or confuse log information when filtering based on keywords or feature information. Furthermore, troubleshooting a problem requires opening multiple process log windows at the same time, which requires a high level of professional skills from the staff and consumes a lot of manpower and query time, resulting in low efficiency in problem localization and problem analysis.

[0037] Based on this, one embodiment of this specification provides a data processing method, which receives a data query instruction for a project to be queried, wherein the data query instruction includes target project information of the project to be queried; determines a target message corresponding to the project to be queried and a first key information corresponding to the target message based on the target project information; determines a target initial process corresponding to the target message based on the first key information; and obtains target log information corresponding to the target message based on the target initial process and the second key information, wherein the second key information is obtained based on historical target log information corresponding to historical target messages of the project to be queried.

[0038] Thus, by using the first key information corresponding to the target message, the target initial process corresponding to the target message can be determined. Starting from the target initial process, the various processes that the target message passes through during its flow can be obtained. By using the second key information, the target log information corresponding to the target message can be extracted from the process logs of each process. This enables the extraction of target log information throughout the entire flow of the target message, avoiding confusion with log information of other messages in the process logs and preventing omissions of target log information. This improves the efficiency and completeness of target log information extraction, thereby enhancing the efficiency of operations and maintenance personnel in locating and analyzing problems based on target log information.

[0039] This specification provides a data processing method, and 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.

[0040] See Figure 1 , Figure 1 An architecture diagram of a data processing system according to an embodiment of this specification is shown. Specifically, the data processing system 100 includes a data terminal 102, a log analysis module 104, and a service module 106.

[0041] A data processing system can be either an artificial intelligence system or an expert system.

[0042] Data terminal 102 can be understood as a project terminal in the production process. Iterative display functions can be integrated into the data terminal. Based on these functions, log data corresponding to each process during message flow can be obtained through data iteration.

[0043] The log analysis module 104 can include various types of processes such as the ADP process, ZPI process, routing process, GEN process, and PAI process. Among them, the ADP process is mainly used to process messages sent by the PLC; the ZPI process and routing process are mainly used for logic conversion; the GEN process is mainly used to process production data; and the PAI process is mainly used to handle printing tasks.

[0044] Service module 106 can provide various types of services such as timestamp service, message service, printing service, and log service.

[0045] By applying this embodiment and building an AI or expert system, after receiving an input message, it can automatically determine which downstream processes the process will distribute the message to, thereby identifying each process in the message flow process and aligning the timestamps of each process log to ensure consistent output for the user. In addition, it can identify alarm or error messages during the processing and determine whether reading or writing database information during process processing is successful, thereby timely locating and alerting abnormal log information, which helps improve the efficiency of log information sorting, lowers the knowledge threshold for staff, and facilitates staff operation.

[0046] See Figure 2 , Figure 2 A flowchart of a data processing method according to an embodiment of this specification is shown, which specifically includes the following steps.

[0047] Step 202: Receive a data query instruction for the item to be queried, wherein the data query instruction includes the target item information of the item to be queried.

[0048] In practical applications, it can receive data query instructions for the project to be queried, and then query project data related to the project to be queried based on the target project information included in the data query instructions.

[0049] Specifically, the project to be queried can include abnormal projects or projects with testing requirements. An abnormal project can be understood as a project that has encountered problems or malfunctions during the production process, requiring problem localization and / or anomaly root cause analysis. The data query instruction can include target project information for the project to be queried. Target project information can be understood as information related to the target project, specifically including project object information and query time information. Project object information can include the production line information to which the project belongs, the production workshop information corresponding to the project, related product information of the project (e.g., vehicle information, component information, etc.), the functions provided by the project, etc. Query time information can include the time point when the anomaly occurred, the time period during which the anomaly occurred, etc. The data query instruction is used to instruct the system to query project data related to the project to be queried. Project data can specifically include all production data during the production process of the project to be queried, message data sent or received by the PLC during the production process of the project to be queried, etc.

[0050] According to an optional embodiment of this specification, a data query instruction for a project to be queried can be received, and project data related to the project to be queried can be queried based on the target project information.

[0051] In practical applications, operations and maintenance personnel can directly input the target project information of the project to be queried into the system, thereby enabling the system to generate data query instructions for the project to be queried.

[0052] According to another optional embodiment of this specification, a log query instruction for a target message of the item to be queried can also be received. Based on the first key information carried by the log query instruction, the starting process in the target message flow process can be determined, thereby obtaining the item data related to the item to be queried based on the starting process.

[0053] In practical applications, operations and maintenance personnel can also determine the target message corresponding to the target message based on the target project information of the project to be queried, further determine the first key information corresponding to the target message, input the first key information into the system, so that the system can generate a log query command for the target message of the project to be queried.

[0054] Step 204: Based on the target project information, determine the target message corresponding to the project to be queried and the first key information corresponding to the target message.

[0055] In practical applications, the target message corresponding to the project to be queried and the first key information corresponding to the target message can be determined based on the target project information.

[0056] Specifically, a target message can be understood as data information sent to or received by the PLC during the production process corresponding to the project to be queried. A target message can include one or more. After the target message is sent to the task system via the PLC, it flows between various processes within the task system, thereby completing the data processing of the target message.

[0057] In actual implementation, as the target message flows between processes, each process records the processing data obtained from processing the target message in its own process log. The processing data recorded in the process log can also be understood as the production data of the project to be queried.

[0058] Specifically, the first key information can be used to determine the target initial process in the target message flow process. The target initial process can be understood as the starting process in the target message flow process. The first key information can be predetermined based on the historical log information corresponding to each process.

[0059] In an optional embodiment of this specification, determining the target message corresponding to the project to be queried and the first key information corresponding to the target message based on the target project information may include the following steps:

[0060] Based on the target project information, determine the target message corresponding to the project to be queried;

[0061] Based on the target project information and the message information of the target message, the first key information corresponding to the target message is generated.

[0062] Specifically, the target project information can include project object information and query time information. Project object information can include the production line information to which the project belongs, the corresponding production workshop information, related product information (e.g., vehicle information, component information, etc.), and the functions provided by the project, etc. Query time information can include the time point when the anomaly occurred, the time period during which the anomaly occurred, etc.

[0063] For example, staff can report production lines and vehicles experiencing problems during production to the system. The system can then determine the target message corresponding to the item to be queried based on the production line number and vehicle number. In addition, the time point or time period of the problem can also be reported to the system, allowing the system to determine the target message corresponding to the item to be queried based on the production line number, vehicle number, and time information.

[0064] Specifically, the first key information is used to determine the starting point of the process in which the target message flows between processes. The first key information may include keywords, key phrases, or key sentences, and can be predetermined based on historical process log information.

[0065] In practical applications, the target message corresponding to the project to be queried is determined by the target project information; based on the target project information and the message information of the target message, the first key information corresponding to the target message is generated. The first key information used to determine the starting point of the process can be obtained based on the target project information, which facilitates the subsequent acquisition of all production data of the entire production process of the project to be queried based on the first key information.

[0066] Optionally, based on determining the target message corresponding to the project to be queried, the first key information corresponding to the target message can be generated based on the target project information and the message information of the target message.

[0067] According to an optional embodiment of this specification, the target project information includes project object information and query time information, and the message information includes a target message identifier; generating the first key information corresponding to the target message based on the target project information and the message information of the target message may include the following steps:

[0068] Based on project object information, query time information, and target message identifier, the first key information corresponding to the target message is generated.

[0069] In practical applications, the first key information used to determine the starting point of the query process can be determined based on the project object where the problem occurred, the time when the problem occurred, and the target message related to the project to be queried.

[0070] Specifically, message information may include the target message identifier, or information such as key fields of the message extracted from the message content.

[0071] By applying this embodiment, the first key information corresponding to the target message is generated based on the project object information, query time information, and target message identifier. This allows for the rapid determination of the first key information used to query the starting point of the target message flow, based on the project object that has the problem, the time when the project object has the problem, and the message information of the target message corresponding to the project to be queried. This improves the efficiency of obtaining target log information.

[0072] Furthermore, generating the first key information corresponding to the target message based on project object information, query time information, and target message identifier can include the following steps:

[0073] Extract the first keyword corresponding to the project object information, and extract the second keyword corresponding to the query time information;

[0074] The first keyword, the second keyword, and the target message identifier are determined as the first key information corresponding to the target message.

[0075] Specifically, the first keyword is extracted based on project object information, and the second keyword is extracted based on query time information. The first keyword can include the object name, object identifier, etc. of the project object, such as workshop A, production line B, function a, etc.; the second keyword can include key timestamps or key time periods, etc.

[0076] Optionally, the first key information can be a keyword or a keyword group, which can be directly composed of the first keyword, the second keyword and the target message identifier. For example, the first key information can be a triple or a multi-tuple composed of (first keyword, second keyword, target message identifier); or it can be at least one keyword selected from the first keyword, the second keyword and the target message identifier.

[0077] Optionally, the first key information can also be a key sentence composed of a first keyword, a second keyword, and a target message identifier. For example, the first keyword, the second keyword, and the target message identifier can be concatenated to form a key sentence. Specifically, the concatenation can be based on a preset template or according to a preset concatenation order.

[0078] By applying this embodiment, by extracting the first keyword corresponding to the project object information and the second keyword corresponding to the query time information, and determining the first keyword, the second keyword, and the target message identifier as the first key information corresponding to the target message, the efficiency and accuracy of obtaining the first key information can be improved, which helps staff to determine the first key information corresponding to the target message and reduces the learning curve for staff.

[0079] Step 206: Based on the first key information, determine the target initial process corresponding to the target message.

[0080] In practical applications, based on determining the first key information corresponding to the target message, the target initial process corresponding to the target message can be determined.

[0081] Specifically, the target initial process can be understood as the starting point in the flow of the target message between various processes; it can also be understood as the first process to which the PLC sends the target message.

[0082] According to an optional embodiment of this specification, determining the target initial process corresponding to the target message based on the first key information may include the following steps:

[0083] Obtain a data query model, wherein the data query model is pre-trained based on a training sample set. The training sample set includes at least one training sample and a sample label corresponding to the training sample. The training sample includes the first key information corresponding to the historical messages of different projects, and the sample label includes the initial process corresponding to the historical message.

[0084] Input the first key information into the data query model to obtain the target initial process output by the data query model.

[0085] Specifically, the data query model can be pre-trained based on a training sample set. The training sample set may include at least one training sample and its corresponding sample label; the training sample may include the first key information corresponding to historical messages from different projects; and the sample label may include the initial process corresponding to the historical message.

[0086] In practical applications, historical messages within a preset historical time period, as well as historical log information from different process logs corresponding to each historical message, can be obtained. Furthermore, historical log information corresponding to historical messages can be integrated using expert experience or AI algorithms to determine the initial process corresponding to each historical message. A training sample set is constructed based on the first key information of the historical messages and the initial process corresponding to them. The first key information of the historical messages is used as the training samples, and the initial process corresponding to the historical messages is used as the sample label for the training samples. The data query model is then trained until a preset model training termination condition is met.

[0087] For example, the preset historical time period can be one year, ten years, etc., and the specific time period can be determined according to the needs of the actual application.

[0088] By applying this embodiment, a data query model can be pre-trained using historical messages and historical log information. The first key information corresponding to the target message can be input into the trained data query model to obtain the target initial process output by the model, thereby enabling the determination of the target initial process based on the first key information and improving the efficiency of determining the target initial process.

[0089] According to another optional embodiment of this specification, determining the target initial process corresponding to the target message based on the first key information may further include the following steps:

[0090] Obtain a preset matching set, wherein the preset matching set includes at least one preset matching pair, and the preset matching pair is constructed based on the first key information corresponding to the historical message and the initial process corresponding to the historical message;

[0091] Identify the target matching pair to which the first key information of the target message belongs in the preset matching set;

[0092] Based on the target matching pair, obtain the target initial process corresponding to the target message.

[0093] Specifically, the preset matching set may include at least one preset matching pair, which may be pre-constructed based on the first key information corresponding to the historical message and the initial process corresponding to the historical message.

[0094] Optionally, historical packets within a preset historical time period, as well as historical log information under different process logs corresponding to each historical packet, can be obtained. Further, all historical log information corresponding to historical packets can be integrated using expert experience or AI algorithms, and the initial process corresponding to the historical packet can be determined based on the integration result. Preset matching pairs are constructed based on the first key information of the historical packet and the initial process corresponding to the historical packet, and preset matching sets are obtained based on different preset matching pairs.

[0095] In practical applications, the target matching pair that matches the first key information of the target message can be identified in each preset matching pair of the preset matching set based on the first key information of the target message, and the target initial process corresponding to the target message can be determined based on the initial process in the target matching pair.

[0096] By applying this embodiment, by obtaining a preset matching set; identifying the target matching pair to which the first key information corresponding to the target message belongs in the preset matching set; and obtaining the target initial process corresponding to the target message based on the target matching pair, the efficiency of obtaining the target initial process can be improved.

[0097] Step 208: Based on the target initial process and the second key information, obtain the target log information corresponding to the target message. The second key information is obtained from the historical target log information corresponding to the historical target messages of the project to be queried.

[0098] In practical applications, based on the determination of the target initial process, the target log information corresponding to the target message can be obtained based on the target initial process and the second key information.

[0099] Specifically, the second key information is the key information corresponding to the target message, which is obtained based on the historical target log information corresponding to the historical target messages of the project to be queried. This second key information is used to extract target log information related to the target message from the process log.

[0100] It should be noted that during the processing of the target message, each process may also process other messages in a synchronous or asynchronous manner. Through the second key information, the target log information related to the target message can be extracted from the process log, avoiding confusion with the log information corresponding to other messages.

[0101] Optionally, through expert experience or AI algorithms, the historical log information in different process logs corresponding to each historical message during the historical production process can be analyzed. Based on timestamps, project information, etc., keywords corresponding to log information related to historical messages in different process logs can be determined; the keywords corresponding to log information related to historical messages can be determined as the second key information.

[0102] According to an optional embodiment of this specification, obtaining target log information corresponding to a target message based on the target initial process and second key information may include the following steps:

[0103] Starting from the initial process of the target, determine at least one process to be extracted from the target message flow;

[0104] Based on the second key information, the target log information corresponding to the target message is extracted from the process log of the process to be extracted.

[0105] Specifically, the process to be extracted can be understood as the process through which the target message flows. The target initial process is the starting point in the process to be extracted.

[0106] Optionally, determining at least one process to be extracted in the target message flow, starting from the target initial process, may include: determining the starting timestamp based on the target initial process; determining the target timestamp in the target message flow process based on the starting timestamp; and determining at least one process to be extracted in the target message flow based on the target timestamp.

[0107] In practical applications, AI models can be trained based on the log timestamps of each process log in the historical message flow process, thereby achieving the alignment of log timestamps based on the flow from the starting point to each process.

[0108] Optionally, starting from the target initial process, determining at least one process to be extracted in the target message flow may also include: determining the downstream process of the target message flow based on the target initial process; and determining at least one process to be extracted based on the downstream process of the target message flow.

[0109] Optionally, determining at least one process to be extracted from the target message flow, starting from the target initial process, may further include: extracting the first target log information corresponding to the target message from the process log of the target initial process based on the target initial process and the second key information; determining the next process to which the target message flows based on the first target log information, and so on, to determine at least one process to be extracted from the target message flow.

[0110] Optionally, based on the second key information, extracting the target log information corresponding to the target message from the process log corresponding to the process to be extracted may include: locating the log information segment corresponding to the target message from the process log corresponding to the process to be extracted based on the second key information; extracting the log information segment to obtain the target log information.

[0111] By applying this embodiment, starting from the initial process of the target, at least one process to be extracted in the flow of the target message can be determined. Based on a general timestamp service, the timestamps of all process logs corresponding to the target message can be aligned, thereby realizing the determination of all processes in the message flow process and the extraction of all process log information, which can effectively avoid the omission of target log information. By extracting the target log information corresponding to the target message from the process logs of the process to be extracted, the extraction efficiency of target log information can be improved, shortening the extraction and sorting process of all log information corresponding to the target message to within seconds, which can greatly improve the work efficiency of operation and maintenance personnel and project personnel.

[0112] According to an optional embodiment of this specification, after obtaining the target log information corresponding to the target message based on the target initial process and second key information, the following steps may also be included:

[0113] Identify at least one process to which the target log information belongs, wherein the process to which the target message is transferred is the process to which the message is transferred;

[0114] The target log information is categorized and integrated according to the target process, and then displayed on the target page corresponding to the target message.

[0115] Specifically, the target page can be understood as a visual interface used to display target log information.

[0116] In practical applications, target log information can be categorized and integrated according to at least one process to which it belongs, and then visualized on the target page.

[0117] Optionally, the target log information corresponding to each process to be extracted can be arranged and displayed in sequence according to the timestamp of the message flow.

[0118] For example, assuming the processes to be extracted in the target log information include process 1, process 2, and process 3, where the log timestamp of process 1 is 12:00; the log timestamp of process 2 is 12:05; and the log timestamp of process 3 is 11:50, then the target log information can be displayed on the target page as follows: first, display the log information corresponding to process 3; then, display the log information corresponding to process 1; and finally, display the log information corresponding to process 2. The log information corresponding to different processes can carry information such as process ID, process timestamp, and process name.

[0119] By applying this embodiment, target log information is categorized and integrated according to target processes and displayed on the target page corresponding to the target message. This allows all log data corresponding to the target message to be integrated and displayed on one page, making it convenient for staff to view without having to open a separate window for each process. This improves the efficiency of problem location and analysis of log data.

[0120] According to an optional embodiment of this specification, before classifying and integrating target log information according to target processes and displaying it on the target page corresponding to the target message, the method may further include:

[0121] Identify abnormal log information in the target log information;

[0122] After classifying and integrating the target log information according to the target process and displaying it on the target page corresponding to the target message, it may also include:

[0123] Annotate the abnormal log information in the target log information.

[0124] In practical applications, AI models or expert systems can be trained based on historical log information. Through machine learning, the AI ​​models or expert systems can learn to identify abnormal log information and abnormal read and write operations during process processing. This allows the AI ​​models or expert systems to identify abnormal log information in the target log information, enabling the labeling of abnormal log information on the target page and improving the efficiency of locating problems in log data.

[0125] Furthermore, problem analysis keywords can be set for abnormal log information, thereby quickly obtaining problem analysis results based on the problem analysis keywords and improving problem analysis efficiency.

[0126] One embodiment of this specification provides a data processing method, which receives a data query instruction for a project to be queried, wherein the data query instruction includes target project information of the project to be queried; determines a target message corresponding to the project to be queried and a first key information corresponding to the target message based on the target project information; determines a target initial process corresponding to the target message based on the first key information; and obtains target log information corresponding to the target message based on the target initial process and the second key information, wherein the second key information is obtained from historical target log information corresponding to historical target messages of the project to be queried.

[0127] By applying this embodiment, the target initial process corresponding to the target message can be determined through the first key information corresponding to the target message. Starting from the target initial process, each process that the target message passes through during its flow can be obtained. Through the second key information, the target log information corresponding to the target message can be extracted from the process logs of each process. This enables the extraction of target log information throughout the entire flow of the target message, avoiding confusion with log information of other messages in the process logs and preventing omissions of target log information. This improves the efficiency and completeness of target log information extraction, thereby enhancing the efficiency of operation and maintenance personnel in locating and analyzing problems based on target log information.

[0128] Corresponding to the above method embodiments, this specification also provides data processing apparatus embodiments. Figure 3 A schematic diagram of the structure of a data processing apparatus according to one embodiment of this specification is shown. Figure 3 As shown, the device includes:

[0129] Receiving module 302: configured to receive a data query instruction for a project to be queried, wherein the data query instruction includes target project information of the project to be queried.

[0130] The first determination module 304 is configured to determine the target message corresponding to the project to be queried and the first key information corresponding to the target message based on the target project information.

[0131] The second determining module 306 is configured to determine the target initial process corresponding to the target message based on the first key information.

[0132] Acquisition module 308: is configured to acquire target log information corresponding to the target message based on the target initial process and second key information, wherein the second key information is obtained based on the historical target log information corresponding to the historical target messages of the project to be queried.

[0133] Optionally, the first determining module 304 is further configured as follows:

[0134] Based on the target project information, determine the target message corresponding to the project to be queried;

[0135] Based on the target project information and the message information of the target message, the first key information corresponding to the target message is generated.

[0136] Optionally, the target project information includes project object information and query time information, and the message information includes the target message identifier;

[0137] The first determining module 304 is further configured as follows:

[0138] Based on project object information, query time information, and target message identifier, the first key information corresponding to the target message is generated.

[0139] Optionally, the first determining module 304 is further configured as follows:

[0140] Extract the first keyword corresponding to the project object information, and extract the second keyword corresponding to the query time information;

[0141] The first keyword, the second keyword, and the target message identifier are determined as the first key information corresponding to the target message.

[0142] Optionally, the second determining module 306 is further configured to:

[0143] Obtain a data query model, wherein the data query model is pre-trained based on a training sample set. The training sample set includes at least one training sample and a sample label corresponding to the training sample. The training sample includes the first key information corresponding to the historical messages of different projects, and the sample label includes the initial process corresponding to the historical message.

[0144] Input the first key information into the data query model to obtain the target initial process output by the data query model.

[0145] Optionally, the second determining module 306 is further configured to:

[0146] Obtain a preset matching set, wherein the preset matching set includes at least one preset matching pair, and the preset matching pair is constructed based on the first key information corresponding to the historical message and the initial process corresponding to the historical message;

[0147] Identify the target matching pair to which the first key information of the target message belongs in the preset matching set;

[0148] Based on the target matching pair, obtain the target initial process corresponding to the target message.

[0149] Optionally, the acquisition module 308 is further configured as follows:

[0150] Starting from the initial process of the target, determine at least one process to be extracted from the target message flow;

[0151] Based on the second key information, the target log information corresponding to the target message is extracted from the process log of the process to be extracted.

[0152] Optionally, the data processing device also includes a display module, configured as follows:

[0153] Identify at least one process to which the target log information belongs, wherein the process to which the target message is transferred is the process to which the message is transferred;

[0154] The target log information is categorized and integrated according to the target process, and then displayed on the target page corresponding to the target message.

[0155] By applying this embodiment, the target initial process corresponding to the target message can be determined through the first key information corresponding to the target message. Starting from the target initial process, each process that the target message passes through during its flow can be obtained. Through the second key information, the target log information corresponding to the target message can be extracted from the process logs of each process. This enables the extraction of target log information throughout the entire flow of the target message, avoiding confusion with log information of other messages in the process logs and preventing omissions of target log information. This improves the efficiency and completeness of target log information extraction, thereby enhancing the efficiency of operation and maintenance personnel in locating and analyzing problems based on target log information.

[0156] 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 data processing method described above belong to the same concept. For details not described in detail in the technical solution of the data processing apparatus, please refer to the description of the technical solution of the data processing method described above.

[0157] Figure 4 A structural block diagram of a computing device 400 according to one embodiment of this specification 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.

[0158] 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 such networks include a Public Switched Telephone Network (PSTN), a Local Area Network (LAN), a Wide Area Network (WAN), a Personal Area Network (PAN), or a combination of communication networks such as the Internet. Access device 440 may include one or more of any type of wired or wireless network interface (e.g., network interface card (NIC)), such as IEEE 802.11 Wireless Local Area Network (WLAN) interface, Wi-MAX (Worldwide Interoperability for Microwave Access) interface, Ethernet interface, Universal Serial Bus (USB) interface, cellular network interface, Bluetooth interface, and Near Field Communication (NFC).

[0159] In one embodiment of this specification, 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 specification. Those skilled in the art can add or replace other components as needed.

[0160] 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 personal computers (PCs). Computing device 400 can also be a mobile or stationary server.

[0161] The processor 420 is configured to execute the following computer-executable instructions, which, when executed by the processor, implement the steps of the above-described data processing method.

[0162] 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.

[0163] An embodiment of this specification also provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the above-described data processing method.

[0164] The above is an illustrative embodiment of a computer-readable storage medium. 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. Details not described in detail in the technical solution of the storage medium can be found in the description of the technical solution of the data processing method described above.

[0165] An embodiment of this specification also provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of the above-described data processing method.

[0166] 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.

[0167] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0168] The computer 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, read-only memory (ROM), random access memory (RAM), 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 or removed according to the requirements of patent practice. For example, in some regions, according to patent practice, computer-readable media may not include electrical carrier signals and telecommunication signals.

[0169] 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 the embodiments in this specification are not limited to the described order of actions, because according to the embodiments in this specification, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in this specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the embodiments in this specification.

[0170] 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.

[0171] The preferred embodiments disclosed above are merely illustrative of this specification. 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 embodiments described herein. These embodiments are selected and specifically described in this specification to better explain the principles and practical applications of the embodiments, thereby enabling those skilled in the art to better understand and utilize this specification. This specification is limited only by the claims and their full scope and equivalents.

Claims

1. A data processing method, characterized by, The method comprises: receiving a data query instruction for a to-be-queried item, wherein the data query instruction comprises target item information of the to-be-queried item; determining a target message corresponding to the to-be-queried item and first key information corresponding to the target message according to the target item information; determining a target initial process corresponding to the target message according to the first key information; obtaining target log information corresponding to the target message based on the target initial process and second key information, wherein the second key information is obtained according to historical target log information corresponding to a historical target message of the to-be-queried item.

2. The method of claim 1, wherein, The method comprises: determining a target message corresponding to the to-be-queried item according to the target item information; generating first key information corresponding to the target message based on the target item information and message information of the target message.

3. The method of claim 2, wherein, The target item information comprises item object information and query time information, and the message information comprises a target message identifier. The method comprises: generating first key information corresponding to the target message based on the item object information, the query time information, and the target message identifier.

4. The method of claim 3, wherein, The method comprises: extracting a first keyword corresponding to the item object information and a second keyword corresponding to the query time information; determining the first keyword, the second keyword, and the target message identifier as the first key information corresponding to the target message.

5. The method according to any one of claims 1 to 4, characterized in that, The method comprises: obtaining a data query model, wherein the data query model is obtained by pre-training according to a training sample set, the training sample set comprises at least one training sample and a sample label corresponding to the training sample, the training sample comprises first key information corresponding to historical messages of different items, and the sample label comprises an initial process corresponding to the historical messages; inputting the first key information into the data query model to obtain a target initial process output by the data query model.

6. The method according to any one of claims 1 to 4, characterized in that, The method comprises: obtaining a preset matching set, wherein the preset matching set comprises at least one preset matching pair, and the preset matching pair is constructed based on first key information corresponding to historical messages and an initial process corresponding to the historical messages; identifying a target matching pair to which the first key information corresponding to the target message belongs in the preset matching set; obtaining a target initial process corresponding to the target message based on the target matching pair.

7. The method of claim 1, wherein, The method comprises: Determine at least one to-be-extracted process of the target message flow based on the target initial process; Extract target log information corresponding to the target message from a process log corresponding to the to-be-extracted process based on the second key information.

8. The method of claim 1, wherein, After obtaining the target log information corresponding to the target message based on the target initial process and the second key information, the method further includes: Determine at least one to-be-extracted process to which the target log information belongs, wherein the to-be-extracted process is a process of the target message flow; Classify and integrate the target log information according to the target process, and display the target log information in a target page corresponding to the target message.

9. A data processing apparatus, characterized by, The method includes: A receiving module configured to receive a data query instruction for a to-be-queried item, wherein the data query instruction includes target item information of the to-be-queried item; A first determining module configured to determine a target message corresponding to the to-be-queried item and first key information corresponding to the target message according to the target item information; A second determining module configured to determine a target initial process corresponding to the target message according to the first key information; An obtaining module configured to obtain target log information corresponding to the target message based on the target initial process and second key information, wherein the second key information is obtained according to historical target log information corresponding to a historical target message of the to-be-queried item.

10. A computing device, comprising: The method includes: A memory and a processor; The memory is configured to store computer programs / instructions, and the processor is configured to execute the computer programs / instructions, so as to implement the steps of the data processing method according to any one of claims 1 to 8.

11. A computer readable storage medium characterized by, The memory stores computer programs / instructions, and the computer programs / instructions are executed by the processor, so as to implement the steps of the data processing method according to any one of claims 1 to 8.

12. A computer program product, characterised in that, The computer programs / instructions are executed by the processor, so as to implement the steps of the data processing method according to any one of claims 1 to 8.

Images