Log processing method and system and mobile equipment

Abstract

The invention relates to a log query method and system and mobile equipment. The method comprises the following steps: receiving query information of a log; querying whether a target log associated with the query information exists in logs stored in a log database by a log storage module set by the system, wherein the stored logs are readable and are in a preset format; if yes, displaying the queried target log; if not, acquiring a target log packet associated with the query information from at least one log source through a log acquisition module set by the system; processing the target log packet through a log analysis module set by the system to obtain a target log; storing the obtained target log in the log database through a log acquisition module set by the system so as to update the log database; and displaying the target log inquired after the log database is updated. According to the scheme provided by the invention, the log processing efficiency can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of log processing, and in particular to a log processing method, system and mobile device. Background Art

[0002] With the rapid development of mobile Internet, the complexity of Android client applications is increasing. Log data has become an important basis for developers to diagnose problems, optimize performance and track user behavior. In the process of developing and maintaining Android clients, the processing of log data faces multiple challenges.

[0003] In the related technology, most of the existing log processing methods rely on manual operations. When faced with a large amount of log data, manual analysis is not only cumbersome and time-consuming, but also prone to errors, such as false positives and missed positives, which leads to low efficiency in log processing. In addition, the log data of the Android client comes from multiple centers. The log formats fed back by different centers are different, and the file sizes vary. The formats include Feishu attachments, zip, 7z, xp and other compression formats, which brings great difficulties to the unified processing of logs and further reduces the efficiency of log processing. Summary of the invention

[0004] In order to solve or partially solve the problems existing in the related art, the present application provides a log query method, system and mobile device, which can improve the log processing efficiency.

[0005] The first aspect of the present application provides a log processing method, including: receiving query information of a log; querying whether there is a target log associated with the query information in the log stored in the log database by a log storage module set by the system, and the stored log is readable and in a preset format; if so, displaying the target log obtained by the query; if not, then: obtaining a target log package associated with the query information from at least one log source through a log acquisition module set by the system; processing the target log package through a log parsing module set by the system to obtain a target log; storing the obtained target log in the log database through a log collection module set by the system to update the log database; and displaying the target log obtained by the query after the log database is updated.

[0006] The log processing method provided by the present application, the log storage module set by the system pre-stores the log through the log database, if the target log associated with the query information of the received log is in the log data, then the target log in the log database can be directly displayed, without the need to repeatedly download and decompress the log, reducing the resource consumption of the system and improving the efficiency of log processing and analysis; if the target log associated with the query information of the received log is not in the log database, then the target log package associated with the query information is obtained from at least one log source through the log acquisition module set by the system, and then the target log package is processed by the log parsing module set by the system to obtain the target log, and the target log is stored in the log database through the log collection module set by the system to update the log database, and finally the target log obtained by the log database after the update is displayed, so as to realize the automatic update of the log database according to the query information of the log, thereby realizing the query of the target log. In the present application, the log storage module, the log acquisition module, the log parsing module and the log collection module are integrated on the same system, and the efficiency of log processing and analysis is further improved through integrated module processing.

[0007] In an optional implementation, the receiving the query information of the log includes: receiving the query information of the log input by the user through a visual interface.

[0008] In an optional embodiment, the log storage module set up by the query system determines whether there is a target log associated with the query information in the logs stored in the log database, including: in response to the query information, performing a correlation query on the logs stored in the log database, the query information including log index information, vehicle identification code and / or keywords; based on the query results, determining whether the target log associated with the query information is stored.

[0009] In an optional embodiment, the log acquisition module set by the system obtains the target log package associated with the query information from at least one log source, including: according to the query information, downloading the target log package associated with the query information from at least one log source through the log source interface of the log acquisition module.

[0010] In an optional embodiment, the log source includes a client log, a local log or a user behavior log; the log acquisition module set by the system obtains a target log package associated with the query information from at least one log source, including: according to the query information, downloading the target log package associated with the query information from the client log, the local log and / or the user behavior log through the log source interface of the log acquisition module.

[0011] In an optional implementation, the processing of the target log package by a log parsing module set by the system to obtain the target log includes: performing standardization processing on the target log package by the log parsing module.

[0012] In an optional implementation, the standardized processing of the target log package by the log parsing module includes: decompressing the target log package by the log parsing module to obtain a target log file; determining by the log parsing module whether the target log file is a special format file, and if so, decrypting the target log file using a preset decryption tool, otherwise, parsing the target log file.

[0013] In an optional implementation, the log collection module set by the system stores the obtained target log in the log database to update the log database, including: indexing the obtained target log through the log collection module to obtain the target log associated with the query information; updating the log database according to the obtained target log through the log collection module.

[0014] In an optional implementation, updating the log database according to the obtained target log by the log collection module includes: writing the obtained target log into the log database by the log collection module to obtain an updated log database.

[0015] A second aspect of the present application provides a log processing system, including a log storage module, a log query management module, a log acquisition module, a log parsing module and a log collection module; the log storage module is used to store logs through a log database, wherein the stored logs are readable and in a preset format; the log query management module is used to receive log query information, query whether there is a target log associated with the query information in the log stored in the log database by the log storage module set by the system, and if so, display the target log obtained by the query, otherwise notify the log acquisition module to process, and display the target log obtained by the query after the log database is updated; the log acquisition module is used to obtain a target log package associated with the query information from at least one log source according to the notification of the log query management module; the log parsing module is used to process the target log package to obtain a target log; the log collection module is used to store the obtained target log in the log database through the log collection module set by the system to update the log database.

[0016] A third aspect of the present application provides a mobile device, including: Processor; and The memory stores executable codes thereon, and when the executable codes are executed by the processor, the processor is caused to execute the method as described above.

[0017] A fourth aspect of the present application provides a computer-readable storage medium having executable code stored thereon. When the executable code is executed by a processor of a vehicle, the processor is caused to execute the method as described above.

[0018] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The above and other objects, features and advantages of the present application will become more apparent by describing in more detail the exemplary embodiments of the present application in conjunction with the accompanying drawings, wherein the same reference numerals generally represent the same components in the exemplary embodiments of the present application.

[0020] Figure 1 It is a flow chart of the log processing method shown in the present application; Figure 2 It is a schematic diagram of the system architecture of the log processing system shown in this application; Figure 3 It is a structural schematic diagram of a log processing device shown in the present application; Figure 4 It is a schematic diagram of the structure of the mobile device shown in this application. DETAILED DESCRIPTION

[0021] The embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided to make the present application more thorough and complete, and to fully convey the scope of the present application to those skilled in the art.

[0022] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms of "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0023] It should be understood that although the terms "first", "second", "third", etc. may be used in this application to describe various information, this information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of this application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of this application, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0024] In the related technology, most of the existing log processing methods rely on manual operations. When faced with a large amount of log data, manual analysis is not only cumbersome and time-consuming, but also prone to errors, such as false positives and missed positives, which leads to low efficiency in log processing. In addition, the log data of the Android client comes from multiple centers. The log formats fed back by different centers are different, and the file sizes vary. The formats include Feishu attachments, zip, 7z, xp and other compression formats, which brings great difficulties to the unified processing of logs and further reduces the efficiency of log processing.

[0025] In order to solve the above problems, the present application provides a log processing method, which can improve the efficiency of log processing and analysis.

[0026] The technical solution of the present application is described in detail below with reference to the accompanying drawings.

[0027] See also Figure 1~Figure 2 A log processing method shown in this application is applied to a log processing system. In this embodiment, the log processing system can be an application terminal APP. The log processing system is used to manage, query and analyze log data. Users obtain or query the required log data through the log processing system. The application terminal APP is integrated with a log storage module, a log query management module, a log acquisition module, a log parsing module and a log collection module. The method includes steps S101 to S107.

[0028] Step S101: receiving log query information.

[0029] Among them, the query information of the log is received through the log query management module set by the system, and the query information can be one or more combinations of log index information, vehicle identification code and keywords. In this embodiment, the log query management module can be Kibana. This embodiment is secondary developed based on Kibana, and can provide an intuitive and easy-to-use visualization interface, which enables users to retrieve and analyze logs more conveniently and improve the user experience. Although Kibana is very popular as a visualization tool for Elasticsearch, you can also consider using other visualization platforms, such as Grafana or Superset or self-developed visualization platforms to perform corresponding functions.

[0030] Most common log management systems can realize basic log collection and retrieval, but the content of the retrieved log data is not refined enough, for example, if you want to retrieve logs related to bug A, or logs of a certain tag in bug A. Compared with the common log management systems, this embodiment provides a powerful log retrieval function, using one or more combinations of log index information, vehicle identification code and keywords as input, and implementing them in combination with AND or NOT logical operations, and can support multi-field combination retrieval and save retrieval conditions, so that users can quickly locate the required log information.

[0031] In step S101, the query information of the log input by the user through the visual interface is received. The user enters the query information in the search input box of the visual interface, and can customize the search formula according to the user's needs in the input box to expect to retrieve the required log data, that is, the target log, and then set different customized search formulas according to different business scenarios and / or log analysis requirements, support customized commands, make the log query and analysis process flexible, and meet the diverse log query and analysis needs.

[0032] Step S102: querying the log storage module set by the system whether there is a target log associated with the query information in the logs stored in the log database, and the stored logs are readable and in a preset format.

[0033] In this embodiment, the log storage module stores log data through a log database, wherein the stored log data is consistent and available, and can quickly implement tasks such as problem location after the log data is queried through the log query management module set by the system.

[0034] Further, step S102 may include: in response to query information, performing a correlation query on logs stored in the log database, the query information including log index information, vehicle identification code and / or keywords; and determining whether a target log associated with the query information is stored based on the query result.

[0035] In step S102 , different query information corresponds to different target logs. For example, if the query information is the index of log B with a tag in bug A, then the corresponding target log is log B with a tag in bug A.

[0036] In practice, taking the log data of Android client as an example, the log data comes from multiple centers and parts, and the formats are different, including multiple different compression formats and different file sizes; with the rapid development of mobile Internet, the complexity of Android client applications is increasing, and log data has become an important basis for developers to diagnose problems, optimize performance and track user behavior. Therefore, the log format stored in the database is a unified preset format, which can facilitate users to quickly retrieve the target log. However, the log processing means in the relevant technology and the problem tracking often have insufficient docking, lacking seamless docking and automatic synchronization with the problem tracking system. Therefore, the logs stored in the log database are difficult to cover all log data. Therefore, when the logs in the log database are queried for correlation, there will be two results, namely, the target log is queried and the target log is not queried. When the log data is queried in the log database, the specific execution process can refer to step S103; when the log data is not queried in the log database, the specific execution process can refer to steps S104 to S107.

[0037] In this embodiment, the log storage module can be Elasticsearch, which is a popular choice for log storage and analysis. However, according to specific needs, the log storage module can also consider using other distributed search and analysis engines to perform corresponding functions, such as Apache Solr or Splunk.

[0038] Step S103: If yes, display the target log obtained by query.

[0039] In this embodiment, the user obtains the vehicle VIN code and / or bug number through the visual interface, and the system checks whether there is cache data related to the VIN / bug in the log database. If there is, the cache data can be directly used for retrieval to obtain the target cache data. In other words, the corresponding log information can be automatically obtained by entering the bug id, link or VIN code in the log retrieval platform.

[0040] From the above description, it can be known that the logs stored in the log database are readable and in a uniform format. When there is a target log in the log database, the log obtained by the query, i.e., the target log, can be directly displayed on the visual interface according to the query information, and the format of the target log is uniform, which can facilitate the subsequent log analysis with the help of Kibana, improve the processing efficiency of the log, and thus timely discover and solve problems. In addition, this embodiment can avoid redundant operations such as repeated log downloading and decompression through the log caching mechanism, thereby reducing the resource consumption of the system.

[0041] Step S104: If not, a target log package associated with the query information is obtained from at least one log source through a log acquisition module set by the system.

[0042] In step S104, obtaining the target log package associated with the query information from at least one log source through the log acquisition module set by the system may include: downloading the target log package associated with the query information from at least one log source through the log source interface of the log acquisition module according to the query information. In this embodiment, the user obtains the vehicle VIN code and / or bug number through the visual interface, and the system checks whether there is cache data related to the VIN / bug in the log database. If not, then the attachment related to the VIN / bug can be downloaded from the specified location, that is, the log source.

[0043] The designated location may be a bug platform, a local platform or a user operation platform, and correspondingly, the log source may be a client log, a local log or a user behavior log. Further, in step S104, the target log package associated with the query information is obtained from at least one log source through the log acquisition module set by the system, which may be downloaded from the client log, the local log and / or the user behavior log through the log source interface of the log acquisition module according to the query information. In this embodiment, a log source interface that is connected to the designated platform is preset in the log acquisition module. By configuring the corresponding interface, when there is no required log in the database, the relevant log data can be obtained from the designated platform according to the query information. In this embodiment, the entrance to automated log processing is embedded in the Feishu bug page and other problem tracking system pages, which can realize one-click jump and automatic synchronization of the tracked bugs to the log database.

[0044] Step S105: Processing the target log package through the log parsing module set by the system to obtain the target log.

[0045] There are many types of logs in the Android client, so the downloaded attachments need to be decompressed and / or decrypted before they can be read. In order to facilitate the subsequent unified query and analysis of log data, step S105 may include standardizing the target log package through the log parsing module. In this embodiment, the target log package is standardized through the log parsing module, so that the processed log format is unified, which is convenient for subsequent log query and analysis.

[0046] Further, in step S105, the target log package is standardized by the log parsing module, which may include: decompressing the target log package by the log parsing module to obtain the target log file; judging whether the target log file is a special format file by the log parsing module, and if so, decrypting the target log file using a preset decryption tool, otherwise, parsing the target log file. In this embodiment, the formats of the downloaded target log package are rar, zip, 7z, tar, xp, etc. Therefore, the downloaded target log package is first decompressed or decrypted, and the target log package in xp format is processed using a preset xp decryption tool. Support for multiple compression formats such as rar, zip, 7z, tar, xp, and special format files such as xlog is increased by python scripts to ensure that various types of log files can be processed. And, special format files include xlog files, wherein the xlog files are .xlog encrypted log files output based on the log framework of WeChat XLog, and the xlog decryption tool is tencent-mars-xlog-rust. Check whether the decompressed log file is of xlog type, and if so, use the xlog decryption tool to decrypt the xlog file. Compared with Tencent's native decryption tool, it is faster. For example, for a 20M file, Tencent's native tool needs to consume 10s, while the xlog decryption tool can decrypt the xlog file in about 500ms. Finally, the log data after decompression and decryption is further processed, such as improving the timestamp, merging context error information or cutting files through shell scripts, etc., which can improve the readability and analysis efficiency of the log. The present embodiment can support a flexible log processing method of multiple compression formats and file formats, and uniformly process and convert log data of different formats and sources, ensure the format consistency and readability of log data, provide a unified log format standard and processing flow, reduce the conversion and processing costs in subsequent analysis and query processes, enable the system to adapt to different application scenarios and requirements, and enhance system flexibility and adaptability.

[0047] Step S106: The obtained target log is stored in the log database through the log collection module set by the system to update the log database.

[0048] Further, step S106 may include: indexing the obtained target log through the log collection module to obtain the target log associated with the query information; and updating the log database according to the obtained target log through the log collection module. In step S106, updating the log database according to the obtained target log through the log collection module may include: writing the obtained target log into the log database through the log collection module to obtain an updated log database.

[0049] In this embodiment, the log collection monitoring directory and the collection template (such as rows starting with A or rows and columns containing A labels) are configured through the log collection module. If the index is configured, the query information and the logs stored in the log database can be quickly matched. After that, the monitored log files are written into the log database, and the updated log database is obtained. Among them, the log collection module can be Filebeat, which performs well as a lightweight log collector. However, the log collection module includes but is not limited to Filebeat, and can also be Fluentd or Logstash, etc. These log collection modules can collect logs obtained from various data sources and send them to the designated log storage device.

[0050] Step S107: Display the target log obtained by querying the log database after updating.

[0051] Unlike step S103, which directly displays the target log obtained by the query, step S107 processes the log after obtaining the log from the log source to obtain readable log data in a preset format to store in the log database, and then retrieves and displays it from the updated log database based on the query information. For logs that are not in the original log database, the logs in the log database can be automatically updated to meet the query. This embodiment can accurately search for specific bugs. For example, users can quickly locate log data related to the bug by entering the bug number or related keywords.

[0052] Different from the traditional direct storage method, this embodiment first obtains the log, then optimizes and analyzes it, and finally stores it. In the first acquisition step, the log data is obtained from the source through a specific interface or tool (such as a VIN code and BUG number input system). This step ensures the accuracy and timeliness of the data. In the optimization and analysis step, after obtaining the log data, python, shell, etc. are used to optimize the log file log data. The optimization processing includes but is not limited to operations such as decompression of different log formats, xlog format conversion, and data aggregation. The optimization processing operation ensures that the log data stored in the log database is accurate, consistent, and useful. This step can reduce redundant data, improve storage efficiency, and lay a solid foundation for subsequent data retrieval and analysis. In the final storage step, the optimized and parsed log data is stored in the efficient Elasticsearch for subsequent retrieval and analysis.

[0053] like Figure 2 As shown, the above log processing method can be secondary developed based on the open source tool Elastic Stack, based on Elasticsearch, Filebeat, and Kibana in the Elastic Stack, and significantly improves the efficiency of log processing and analysis through module integrated processing and intelligent caching mechanism, and can adapt to different application scenarios and needs, and can solve the problems of low efficiency, high resource consumption, insufficient processing of files in specific formats, and lack of flexible user interfaces in current log processing and analysis. On this basis, this embodiment can achieve log acquisition and retrieval in the same interface, which provides great convenience for users and reduces the complexity of operations.

[0054] It should be noted that Elastic Stack can collect various logs such as servers and applications to help administrators quickly locate problems. For example, when a website fails, by analyzing access logs and application logs, it can be determined whether it is caused by network problems, code errors, or insufficient server resources.

[0055] The log processing method provided by the embodiment of the present application is that the log storage module set by the system stores the log in advance through the log database. If the target log associated with the query information of the received log is in the log data, the target log in the log database can be directly displayed, without the need to repeatedly download and decompress the log, reducing the resource consumption of the system and improving the efficiency of log processing and analysis; if the target log associated with the query information of the received log is not in the log database, then the target log package associated with the query information is obtained from at least one log source through the log acquisition module set by the system, and then the target log package is processed by the log parsing module set by the system to obtain the target log, and the target log is stored in the log database through the log collection module set by the system to update the log database, and finally the target log obtained by the log database after the update is displayed, so as to realize the automatic update of the log database according to the query information of the log, thereby realizing the query of the target log. In the present application, the log storage module, the log acquisition module, the log parsing module and the log collection module are integrated on the same system, and the efficiency of log processing and analysis is further improved through integrated module processing.

[0056] Corresponding to the aforementioned application function implementation method embodiment, the present application also provides a log processing device, a mobile device and corresponding embodiments.

[0057] Figure 3 It is a structural schematic diagram of the log processing device shown in this application.

[0058] See also Figure 3 , a log processing device 300 shown in the present application includes a log storage module 301, a log query management module 302, a log acquisition module 303, a log parsing module 304 and a log collection module 305; wherein: The log storage module 301 is used to store logs through a log database, wherein the stored logs are readable and in a preset format.

[0059] The log query management module 302 is used to receive log query information, and query whether there is a target log associated with the query information in the log stored in the log database by the log storage module set by the system. If so, the target log obtained by the query is displayed; otherwise, the log acquisition module is notified to process and display the target log obtained by the query after the log database is updated.

[0060] The log acquisition module 303 is used to acquire a target log package associated with the query information from at least one log source according to the notification of the log query management module.

[0061] The log parsing module 304 is used to process the target log package to obtain the target log.

[0062] The log collection module 305 is used to store the obtained target log into the log database through the log collection module set by the system to update the log database.

[0063] Furthermore, the log query management module 302 may be configured to receive log query information input by a user through a visual interface.

[0064] Furthermore, the log query management module 302 can be used to perform a correlation query on the logs stored in the log database in response to query information, the query information including log index information, vehicle identification code and / or keywords; and determine whether a target log associated with the query information is stored based on the query result.

[0065] Furthermore, the log acquisition module 303 may be configured to download a target log package associated with the query information from at least one log source through a log source interface of the log acquisition module 303 according to the query information.

[0066] Furthermore, the log source includes client log, local log or user behavior log; the log acquisition module 303 can be used to download the target log package associated with the query information from the client log, local log and / or user behavior log through the log source interface of the log acquisition module 303 according to the query information.

[0067] Furthermore, the log parsing module 304 can be used to perform standardization processing on the target log package. In the log parsing module 304, the target log package is decompressed to obtain the target log file; it is determined whether the target log file is a special format file, if so, the target log file is decrypted using a preset decryption tool, otherwise, the target log file is parsed.

[0068] Further, the log collection module 305 can be used to index the obtained target log to obtain the target log associated with the query information, and update the log database according to the obtained target log. Wherein, updating the log database according to the obtained target log can include: writing the obtained target log into the log database to obtain an updated log database.

[0069] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated again here.

[0070] Figure 4 It is a schematic diagram of the structure of the mobile device shown in this application.

[0071] See also Figure 4 , the mobile device 400 includes a memory 401 and a processor 402 .

[0072] The processor 402 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0073] The memory 401 may include various types of storage units, such as system memory, read-only memory (ROM), and permanent storage devices. Among them, ROM can store static data or instructions required by the processor 402 or other modules of the computer. The permanent storage device may be a readable and writable storage device. The permanent storage device may be a non-volatile storage device that does not lose the stored instructions and data even after the computer is powered off. In some embodiments, the permanent storage device uses a large-capacity storage device (such as a magnetic or optical disk, flash memory) as a permanent storage device. In some other embodiments, the permanent storage device may be a removable storage device (such as a floppy disk, an optical drive). The system memory may be a readable and writable storage device or a volatile readable and writable storage device, such as a dynamic random access memory. The system memory may store some or all instructions and data required by the processor at runtime. In addition, the memory 401 may include any combination of computer-readable storage media, including various types of semiconductor storage chips (such as DRAM, SRAM, SDRAM, flash memory, programmable read-only memory), and disks and / or optical disks may also be used. In some embodiments, the memory 401 may include a readable and / or writable removable storage device, such as a laser disc (CD), a read-only digital versatile disc (such as a DVD-ROM, a double-layer DVD-ROM), a read-only Blu-ray disc, an ultra-density optical disc, a flash memory card (such as an SD card, a mini SD card, a Micro-SD card, etc.), a magnetic floppy disk, etc. Computer-readable storage media do not include carrier waves and transient electronic signals transmitted wirelessly or wired.

[0074] The memory 401 stores executable codes, and when the executable codes are processed by the processor 402 , the processor 402 can execute part or all of the above-mentioned methods.

[0075] In some embodiments, the mobile device is an electric vehicle.

[0076] In addition, the method according to the present application may also be implemented as a computer program or a computer program product, which includes computer program code instructions for executing some or all of the steps in the above method of the present application.

[0077] Alternatively, the present application can also be implemented as a computer-readable storage medium (or a non-transitory machine-readable storage medium or a machine-readable storage medium) on which an executable code (or a computer program or a computer instruction code) is stored. When the executable code (or a computer program or a computer instruction code) is executed by a processor of a server (or a server, etc.), the processor executes part or all of the steps of the above-mentioned method according to the present application.

[0078] The embodiments of the present application also provide a computer program product or a computer program, which includes computer instructions stored in a computer-readable storage medium. The processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes any of the methods described in the above embodiments.

[0079] The computer readable storage medium may include: a read-only memory (ROM), a random access memory (RAM), a solid state drive (SSD), or an optical disk. Among them, the random access memory may include a resistance random access memory (ReRAM) and a dynamic random access memory (DRAM). The serial numbers of the above embodiments of the present application are only for description and do not represent the advantages and disadvantages of the embodiments.

[0080] A person skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware or by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a disk or an optical disk, etc.

[0081] The embodiments of the present application have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or improvements to the technology in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A log processing method, characterized in that: include: Receive log query information; The log storage module set by the query system stores a target log associated with the query information in the log stored in the log database, wherein the stored log is readable and in a preset format; If yes, then display the target log obtained by query; if no, then: Acquire a target log package associated with the query information from at least one log source through a log acquisition module set by the system; The target log package is processed by a log parsing module set by the system to obtain a target log; The log collection module set by the system stores the obtained target log into the log database to update the log database; as well as The target log obtained by querying the log database after updating is displayed.

2. The method according to claim 1, characterized in that The query information of the received log includes: Receive log query information input by the user through the visual interface.

3. The method according to claim 1, characterized in that The log storage module set by the query system determines whether there is a target log associated with the query information in the log stored in the log database, including: In response to the query information, performing a correlation query on the logs stored in the log database, the query information including log index information, vehicle identification code and / or keywords; According to the query result, it is determined whether a target log associated with the query information is stored.

4. The method according to claim 1, characterized in that The acquiring of a target log package associated with the query information from at least one log source by a log acquisition module set by the system includes: According to the query information, a target log package associated with the query information is downloaded from at least one log source through a log source interface of the log acquisition module.

5. The method according to claim 1, characterized in that The log source includes a client log, a local log or a user behavior log; the log acquisition module set by the system acquires a target log package associated with the query information from at least one log source, including: According to the query information, a target log package associated with the query information is downloaded from the client log, the local log and / or the user behavior log through the log source interface of the log acquisition module.

6. The method according to claim 1, characterized in that The log parsing module set by the system processes the target log package to obtain the target log, including: The target log package is standardized by the log parsing module.

7. The method according to claim 6, characterized in that The standardizing the target log package by the log parsing module includes: Decompressing the target log package through the log parsing module to obtain a target log file; The log parsing module determines whether the target log file is a file in a special format. If so, a preset decryption tool is used to decrypt the target log file. Otherwise, the target log file is parsed.

8. The method according to claim 1, characterized in that The log collection module set by the system stores the obtained target log into the log database to update the log database, including: The obtained target log is indexed and configured by the log collection module to obtain the target log associated with the query information; The log database is updated according to the obtained target log by the log collection module.

9. The method according to claim 8, characterized in that The updating of the log database according to the obtained target log by the log collection module includes: The obtained target log is written into the log database through the log collection module to obtain an updated log database.

10. A log processing system, characterized in that: It includes log storage module, log query management module, log acquisition module, log parsing module and log collection module; The log storage module is used to store logs through a log database, wherein the stored logs are readable and in a preset format; The log query management module is used to receive query information of the log, query whether there is a target log associated with the query information in the log stored in the log database by the log storage module set by the system, and if so, display the target log obtained by the query, otherwise notify the log acquisition module to process and display the target log obtained by the query after the log database is updated; The log acquisition module is used to acquire a target log package associated with the query information from at least one log source according to the notification of the log query management module; The log parsing module is used to process the target log package to obtain the target log; The log collection module is used to store the obtained target log into the log database through the log collection module set by the system to update the log database.

11. A mobile device, characterized in that: include: processor; as well as A memory having executable codes stored thereon, which, when executed by the processor, causes the processor to execute the method as claimed in any one of claims 1 to 9.

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