Report processing method and device, storage medium and electronic equipment

Abstract

This invention discloses a report processing method, apparatus, storage medium, and electronic device, relating to the field of financial technology. The method includes: acquiring a report file to be analyzed, wherein the report file includes multiple reports to be analyzed, and the multiple reports to be analyzed include performance data of a target device; determining at least one target report to be analyzed from the multiple reports to be analyzed according to a first parsing condition, wherein the first parsing condition includes at least one of the following: report generation date, report type, and report version; determining a target parsing rule corresponding to the at least one target report to be analyzed, and parsing the at least one target report to be analyzed according to the target parsing rule to obtain a parsing result, wherein the parsing result characterizes the performance of the target device. This invention solves the technical problem of low processing efficiency in existing technologies that rely on manual collection and analysis of report data.

Description

Technical Field

[0001] This invention relates to the field of financial technology, and more specifically, to a report processing method, apparatus, storage medium, and electronic device. Background Technology

[0002] IBM mainframes are characterized by high integration, high reliability, and strong scalability, and are widely used to process large-scale transactions. Most financial institutions use mainframes to process core business operations. DB2 (relational database management system) is the core product of the mainframe system, and it has the characteristics of stability and timeliness in data storage and transaction response.

[0003] Currently, the data collection and analysis of performance monitor (PM) reports for DB2 mainframe products mainly rely on manual filtering and screening of report files, collection of performance data, and the use of tools such as Excel for comparative chart analysis. This approach suffers from low processing efficiency and a high error rate, failing to meet users' timeliness requirements. Furthermore, the data analysis process demands a high level of experience and technical expertise from users.

[0004] There is currently no effective solution to the above problems. Summary of the Invention

[0005] This invention provides a report processing method, apparatus, storage medium, and electronic device to at least solve the technical problem of low processing efficiency in the prior art where report data is collected and analyzed manually.

[0006] According to one aspect of the present invention, a report processing method is provided, comprising: acquiring a report file to be analyzed, wherein the report file to be analyzed includes multiple reports to be analyzed, and the multiple reports to be analyzed include performance data of a target device; determining at least one target report to be analyzed from the multiple reports to be analyzed according to a first parsing condition, wherein the first parsing condition includes at least one of the following: report generation date, report type, and report version; determining a target parsing rule corresponding to the at least one target report to be analyzed, and parsing the at least one target report to be analyzed according to the target parsing rule to obtain a parsing result, wherein the parsing result characterizes the performance of the target device.

[0007] Furthermore, the report processing method also includes: obtaining multiple initial reports associated with the target device; adding corresponding scene identifiers to the names of the multiple initial reports based on the scene information corresponding to the multiple initial reports to obtain multiple reports to be analyzed; and generating a report file to be analyzed based on the multiple reports to be analyzed.

[0008] Furthermore, the report type includes at least one of the following: Type 1 and Type 2, where the performance data corresponding to Type 1 and Type 2 are different. The report processing method also includes: obtaining a rule data table of parsing rules corresponding to the report version; querying the target data corresponding to the report type from the rule data table, and concatenating the target data to obtain the target parsing rules, wherein the target data includes at least one of the following: the name of the performance data, the data type of the performance data, and parsing rule data, whereby the parsing rule data represents the parsing method of the performance data.

[0009] Furthermore, the report processing method also includes: determining target performance data from the performance data of at least one target report to be analyzed based on the name and data type of the performance data; and parsing the target performance data according to the parsing rules to obtain the parsing results.

[0010] Furthermore, the report processing method also includes: after obtaining the report file to be analyzed, performing format conversion processing on the report file to be analyzed to obtain the converted report file to be analyzed, and storing the converted report file to be analyzed in the first directory.

[0011] Furthermore, the report processing method also includes: before determining at least one target report to be analyzed from multiple reports to be analyzed according to the first parsing condition, upon receiving the first target request, obtaining editing request information in the first target request, wherein the first target request is one of the following: a new editing request, a modified editing request, and the editing request information represents the editing information of the parsing rule; and generating the first parsing rule according to the editing request information.

[0012] Furthermore, the edit request information includes at least one of the following: a first report type, a first report version, a name of the first performance data, a data type of the first performance data, and first parsing rule data. The report processing method further includes: if the first target request is a new edit request, then generating a first target data table based on the first report type and the first report version; retrieving the first target data from the database based on the name and data type of the first performance data, and storing the first target data in the first target data table; adding first parsing rule data to the first target data table, and generating a first parsing rule.

[0013] Furthermore, the report processing method also includes: if the first target request is a modification / edit request, then generating a second target data table based on the first report type and the first report version; retrieving the first target data from the database based on the name and data type of the first performance data, and storing the first target data in the second target data table; and updating the parsing rules corresponding to the first target data in the second target data table according to the first parsing rule data, thereby generating the first parsing rule.

[0014] Furthermore, the report processing method also includes: before determining the target parsing rule corresponding to at least one target report to be analyzed, and before parsing the at least one target report to be analyzed according to the target parsing rule to obtain the parsing result, upon receiving a second target request, obtaining query request information from the second target request, wherein the query request information includes at least one of the following: target report generation date, target report type, target report version, and name of target performance data; obtaining target parsing result data from the database according to the query request information, and generating a target parsing result file; generating a target chart according to the target parsing result file, wherein the target chart is used to display the target parsing result data to the target object.

[0015] According to another aspect of the present invention, a report processing apparatus is also provided, comprising: an acquisition module, configured to acquire a report file to be analyzed, wherein the report file to be analyzed includes a plurality of reports to be analyzed, and the plurality of reports to be analyzed include performance data of a target device; a determination module, configured to determine at least one target report to be analyzed from the plurality of reports to be analyzed according to a first parsing condition, wherein the first parsing condition includes at least one of the following: report generation date, report type, and report version; and a processing module, configured to determine a target parsing rule corresponding to the at least one target report to be analyzed, and to perform parsing processing on the at least one target report to be analyzed according to the target parsing rule to obtain a parsing result, wherein the parsing result characterizes the performance of the target device.

[0016] According to another aspect of the present invention, a computer-readable storage medium is also provided, wherein a computer program is stored in the computer program, and the computer program is configured to execute the above-described report processing method at runtime.

[0017] According to another aspect of the present invention, an electronic device is also provided, the electronic device including one or more processors; a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors are configured to run the programs, wherein the programs are configured to execute the above-described report processing method during runtime.

[0018] In this embodiment of the invention, an automated analysis method for report performance data is employed. First, a report file to be analyzed is acquired. Then, based on a first parsing condition, at least one target report to be analyzed is determined from multiple reports to be analyzed. Next, a target parsing rule corresponding to the at least one target report to be analyzed is determined, and the at least one target report to be analyzed is parsed according to the target parsing rule to obtain a parsing result. The report file to be analyzed includes multiple reports to be analyzed, and these multiple reports include performance data of the target device. The first parsing condition includes at least one of the following: report generation date, report type, and report version. The parsing result characterizes the performance of the target device.

[0019] In the above process, by acquiring the report files to be analyzed, a data foundation is provided for subsequent parsing. Based on the first parsing condition, at least one target report to be analyzed can be identified from multiple reports to be analyzed. This allows for the determination of the target parsing rules corresponding to at least one target report to be analyzed. Consequently, the at least one target report to be analyzed can be parsed according to the target parsing rules, saving manpower and time costs, improving the efficiency and accuracy of report analysis, thereby enhancing the reliability of the system. It also effectively meets the user's need for timely and accurate performance analysis reports, providing convenience for users to perform report analysis.

[0020] Therefore, the technical solution of the present invention achieves the goal of reducing the labor and time costs of report analysis and processing, thereby improving the processing efficiency of report analysis and processing, and solving the technical problem of low processing efficiency in the prior art of manually collecting and analyzing report data. Attached Figure Description

[0021] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0022] Figure 1 This is a flowchart of an optional report processing method according to an embodiment of the present invention;

[0023] Figure 2 This is a schematic diagram of an optional report processing system according to an embodiment of the present invention;

[0024] Figure 3 This is a flowchart illustrating an optional PM report upload implementation according to an embodiment of the present invention;

[0025] Figure 4 This is a flowchart illustrating an optional implementation of PM report parsing according to an embodiment of the present invention;

[0026] Figure 5 This is an optional PM report parsing flowchart according to an embodiment of the present invention;

[0027] Figure 6 This is an implementation flowchart of an optional PM report agile secondary development and deployment according to an embodiment of the present invention;

[0028] Figure 7 This is a flowchart illustrating the modification of the indicator definition module and the parsing method module in an optional secondary development according to an embodiment of the present invention.

[0029] Figure 8 This is an optional PM report parsing result query flowchart according to an embodiment of the present invention;

[0030] Figure 9 This is a flowchart illustrating an optional one-click export of PM reports according to an embodiment of the present invention.

[0031] Figure 10 This is a schematic diagram of an optional report processing device according to an embodiment of the present invention;

[0032] Figure 11 This is a schematic diagram of an optional electronic device according to an embodiment of the present invention. Detailed Implementation

[0033] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0034] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0035] It should be noted that all relevant information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for display, data used for analysis, etc.) involved in this invention are information and data authorized by the user or fully authorized by all parties. For example, this system has an interface with the relevant user or organization. Before obtaining relevant information, it needs to send an acquisition request to the aforementioned user or organization through the interface, and obtain the relevant information after receiving consent from the aforementioned user or organization.

[0036] Example 1

[0037] According to an embodiment of the present invention, an embodiment of a report processing method is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0038] Figure 1 This is a flowchart of an optional report processing method according to an embodiment of the present invention, such as... Figure 1 As shown, the method includes the following steps:

[0039] Step S101: Obtain the report file to be analyzed, wherein the report file to be analyzed includes multiple reports to be analyzed, and the multiple reports to be analyzed include the performance data of the target device;

[0040] Step S102: Based on the first parsing condition, determine at least one target report to be analyzed from multiple reports to be analyzed, wherein the first parsing condition includes at least one of the following: report generation date, report type, and report version;

[0041] Step S103: Determine the target parsing rule corresponding to at least one target report to be analyzed, and perform parsing processing on at least one target report to be analyzed according to the target parsing rule to obtain the parsing result, wherein the parsing result characterizes the performance of the target device.

[0042] Specifically, in step S101 above, the report file to be analyzed can be obtained through application systems, processors, electronic devices, etc. Optionally, the report file to be analyzed can be obtained through a report processing system. The report to be analyzed can be a DB2 performance monitoring report (PM report), and the target device can be a mainframe. DB2 PM reports include two types: ACCOUNTING reports and STAT reports. ACCOUNTING reports focus on analyzing the number of database Data Manipulation Language (DML) entries and DML processing performance, while STAT reports focus on analyzing the performance of database CPU, memory, and other resource consumption. Optionally, the performance data can be DML processing performance data, CPU performance data, memory performance data, etc.

[0043] Figure 2 This is a schematic diagram of an optional report processing system according to an embodiment of the present invention, such as... Figure 2 As shown, it includes a PM report performance automation analysis request device (D1), a PM report performance automation analysis result storage device (D2), and a PM report performance automation analysis response device (D3). D1 includes a PM report upload request module, a PM report one-click parsing request module, a web-based multi-dimensional analysis chart display request module, a chart one-click archiving request module, and an agile development request module. D2 includes a metric field type definition module, a parsing result read / write module, and parsing method modules for various DB2 product versions. D3 includes a report storage module, a parsing module, a response module, and a new requirement module. The parsing method modules for various DB2 product versions include the metric field type definition module version and the parsing module version for a specific DB2 version.

[0044] Optionally, in this embodiment, the report processing system is composed of a full-stack architecture consisting of a Vue front-end scaffolding, a MySQL database, and a Python back-end data processing system. Specifically, the aforementioned functional modules of D1 are implemented through the Vue front-end, the aforementioned functional modules of D2 are implemented through the MySQL database, and the aforementioned functional modules of D3 are implemented through the Python back-end.

[0045] Optionally, in this embodiment, the above modules are interconnected to achieve the following functionalities:

[0046] Function 1: When a user triggers a front-end webpage request to upload the PM report, the back-end response module will link the specified URL with the report storage module to store the report file in the back-end temporary directory.

[0047] Function 2: When the user specifies the PM report generation date and DB2 product version to trigger the front-end webpage to request the PM report one-click parsing function, the back-end response module will link the specified URL to the parsing module of the DB2 product version to complete the report parsing, and link the parsing result to the data type definition module according to the indicator field type definition module to store the parsing result in the MySQL storage device. After the parsing is completed, the report storage module will be scheduled to delete the PM report in the temporary directory.

[0048] Function 3: When the user specifies the dimension, PM report generation date, DB2 product version, indicator name or table name, etc., and triggers the front-end webpage to request the multi-dimensional analysis chart display function, the back-end response module will use the specified URL combined with the response item as the composite primary key, link the parsing result reading function to output the analysis data to be displayed, and return the analysis data to the front-end webpage through the URL. The front-end webpage uses the chart drawing component to complete the rendering of the analysis data.

[0049] Function 4: When the user specifies two types of entries, namely the PM report generation date and the DB2 product version, and triggers the front-end webpage request for the one-click chart archiving function, the back-end response module will combine the specified URL with the specified entries, use the chart archiving WORD template, link the parsing result reading function, and use front-end components such as docxtemplater and file-saver to complete the one-click generation of the analysis report from the original analysis data into an archive format.

[0050] Function 5: When the DB2 product version is upgraded, affecting the PM performance report format of the DB2 product and causing changes in the indicator filtering rules or the number of indicators, the user specifies the DB2 product version, triggering the front-end webpage to request the agile development function. The back-end response module will link the specified URL with the new requirement module to complete the indicator modification. After the new requirement module completes its work, it will schedule the definition module and parsing module of the indicator field type to complete the synchronous modification, and store the modified version in the data table of the parsing method module under various DB2 product versions.

[0051] The implementation process of the above functions will be explained in detail below.

[0052] Figure 3 This is a flowchart illustrating an optional PM report upload implementation according to an embodiment of the present invention, such as... Figure 3 As shown, the implementation process for Function 1 (PM report upload) specifically includes the following steps:

[0053] Step S201: Remotely log in to the mainframe server terminal, download the DB2 product's PM report to the local path, and rename the current file to "Scene Name + Original File Name". The file name specifies which scene each file was generated from. For example, if the original file name is D221021 and the scene is the base scene, the renamed file name is scene1_BASE+D221021.

[0054] In one optional embodiment, during the process of obtaining the report file to be analyzed, firstly, multiple initial reports associated with the target device are obtained, and then, according to the scene information corresponding to the multiple initial reports, corresponding scene identifiers are added to the names of the multiple initial reports to obtain multiple reports to be analyzed. Then, based on the multiple reports to be analyzed, a report file to be analyzed is generated.

[0055] Optionally, firstly, the PM report files (i.e., multiple initial reports associated with the mainframe) are downloaded from the mainframe server to the local machine. Then, based on the scene information corresponding to the multiple initial reports, corresponding scene identifiers are added to the names of the multiple initial reports to obtain multiple reports to be analyzed (i.e., reports with modified names). That is, the current file name is changed to "scene name + original file name". For example, if the original file name is D221021 and the scene is the baseline scene, the modified file name is scene1_BASE+D221021. Further, based on the multiple reports to be analyzed, a report file to be analyzed is generated.

[0056] In step S202, the user triggers the PM report upload function. The front end calls the el-upload component to upload the file in formdata format and requests the backend report file storage service through the specified URL.

[0057] In step S203, after receiving the front-end request, the back-end converts the formdata format data passed in by the front-end into a UTF-8 format file through the specified URL.

[0058] Step S204: Save the UTF-8 format file to the temporary storage directory for the original report files specified by the backend.

[0059] In one optional embodiment, after obtaining the report file to be analyzed, the report file to be analyzed is converted to a new format to obtain a converted report file to be analyzed, and the converted report file to be analyzed is stored in the first directory.

[0060] Optionally, the first directory can be a temporary directory. After receiving the PM report upload request triggered by the target object (i.e., the user), the frontend uploads the PM report from the local path and saves it to the temporary storage directory for the original report files specified by the backend. Optionally, the report file to be analyzed is first converted into a format, for example, the formdata format data passed from the frontend is converted into a UTF-8 format file to obtain the converted report file to be analyzed, and the converted report file to be analyzed is stored in the temporary directory, that is, the UTF-8 format file is saved to the temporary storage directory for the original report files specified by the backend.

[0061] Specifically, in steps S102 and S103 above, the first parsing condition can be a parsing condition generated based on the report generation date, report type, and report version in the user's parsing request. Based on the first parsing condition, at least one target report to be analyzed can be determined from multiple reports to be analyzed. For example, the report generation date is X year X month X day, the report type is ACCOUNTING report, and the report version is DB2 1.0.

[0062] Figure 4 This is a flowchart illustrating an optional PM report parsing implementation according to an embodiment of the present invention, such as... Figure 4 As shown, the implementation process for Function 2 (PM report parsing) specifically includes the following steps:

[0063] Step S301: The front end uses the el-dialog component to create a form. The form content includes "PM report generation date", "PM report type" and "DB2 product version".

[0064] In step S302, before parsing, the user triggers the form button, fills in the "PM report generation date", "PM report type" and "DB2 product version" and clicks confirm.

[0065] In step S303, the user triggers the report parsing function, sends the form content to the backend via the specified URL, and requests the backend report parsing service.

[0066] Step S304: The backend receives the form content from the frontend, confirms the report parsing method, parses the report files in the temporary storage directory, and splits the report file names in the temporary storage directory to extract the scenario name. That is, based on the first parsing condition, at least one target report to be analyzed is determined from multiple reports to be analyzed, the target parsing rule corresponding to the at least one target report to be analyzed is determined, and the at least one target report to be analyzed is parsed according to the target parsing rule to obtain the parsing result. Optionally, if no DB2 product version is specified, the initial default DB2 version is used. The parsing method for other DB2 product versions can be generated by agile secondary development. Different types of PM reports correspond to different report parsing methods.

[0067] Step S305: After the backend completes the parsing, the received frontend form content, scene name, and parsing result fields are stored in the storage table of the MySQL storage device.

[0068] Step S306: Delete the report files uploaded from the front end to the temporary storage directory on the back end.

[0069] It should be noted that the above process saves labor and time costs, improves the efficiency and accuracy of report analysis and processing, and thus enhances the reliability of the system.

[0070] Based on the scheme defined in steps S101 to S103 above, it can be understood that in this embodiment of the invention, the method of automatically analyzing report performance data first obtains the report file to be analyzed, then determines at least one target report to be analyzed from multiple reports to be analyzed according to the first parsing condition, then determines the target parsing rule corresponding to the at least one target report to be analyzed, and performs parsing processing on the at least one target report to be analyzed according to the target parsing rule to obtain the parsing result. The report file to be analyzed includes multiple reports to be analyzed, the multiple reports to be analyzed include performance data of the target device, the first parsing condition includes at least one of the following: report generation date, report type, report version, and the parsing result characterizes the performance of the target device.

[0071] It is noteworthy that, in the above process, obtaining the report files to be analyzed provides a data foundation for subsequent parsing. Based on the first parsing condition, at least one target report to be analyzed can be identified from multiple reports to be analyzed. This allows for the determination of the target parsing rules corresponding to at least one target report, and then, based on the target parsing rules, at least one target report to be analyzed can be parsed. This saves manpower and time costs, improves the efficiency and accuracy of report analysis, thereby enhancing the reliability of the system. It also effectively meets users' needs for timely and accurate performance analysis reports, providing convenience for users to perform report analysis.

[0072] Therefore, the technical solution of the present invention achieves the goal of reducing the labor and time costs of report analysis and processing, thereby improving the processing efficiency of report analysis and processing, and solving the technical problem of low processing efficiency in the prior art of manually collecting and analyzing report data.

[0073] In one optional embodiment, the report type includes at least one of the following: a first type and a second type, wherein the performance data corresponding to the first type and the second type are different. In the process of determining the target parsing rule corresponding to at least one target report to be analyzed, firstly, a rule data table of parsing rules corresponding to the report version is obtained, then the target data corresponding to the report type is queried from the rule data table, and the target data is concatenated to obtain the target parsing rule. The target data includes at least one of the following: the name of the performance data, the data type of the performance data, and parsing rule data. The parsing rule data represents the parsing method of the performance data.

[0074] Optionally, the first type of report can be an ACCOUNTING report, and the second type of report can be a STAT report. Because the focus of the report content is different, the names, types and parsing rules of the parsed indicators are different.

[0075] Figure 5 This is an optional PM report parsing flowchart according to an embodiment of the present invention, such as... Figure 5 As shown, the specific steps include the following:

[0076] Step S401: Based on the “DB2 product version” parameter obtained from the front end, call the data table of the indicator definition and parsing method module under the corresponding version (i.e., obtain the rule data table of the parsing rules corresponding to the report version). Based on the “PM report type” parameter obtained from the front end, query the record of the corresponding indicator and its indicator type and parsing rule in the data table (i.e., query the target data corresponding to the report type from the rule data table).

[0077] Step S402: Poll the query records obtained in step S401 to obtain all performance index values. This involves concatenating the target data to obtain the target parsing rules. Specifically, take one record and concatenate it to obtain the performance index value. For example, if the index name (i.e., the name of the performance data) is CPU, the data type (i.e., the data type of the performance data) is floating-point, and the parsing rule data is line_data[i+2][15:25] (i.e., converting each line of the file into a list format), the target parsing rule obtained through concatenation is CPU = float(line_data[i+2][15:25]), where i is the row number, the first square bracket indicates the row number, and the second square bracket indicates the column number. The processing method for other records is the same. After polling all records, all performance index data is obtained.

[0078] Step S403: Read the report file in the backend temporary storage directory and obtain the scene name of the report file according to step S304.

[0079] Step S404: Place the above content ("PM report generation date", "PM report type", "DB2 product version", "scenario name", "MEMBER name", "corresponding performance index value") into a MySQL storage device table. Optionally, if the PM report type is ACCOUNTING, place it in the ACCOUNTING data table; if the PM report type is STAT, place it in the STAT data table.

[0080] It should be noted that by concatenating the target data, target parsing rules can be obtained, providing a data foundation for subsequent data analysis, thereby improving the accuracy of report analysis and processing and reducing the error rate.

[0081] In one optional embodiment, in the process of parsing at least one target report to be analyzed according to the target parsing rules to obtain the parsing result, the target performance data is first determined from the performance data of at least one target report to be analyzed based on the name and data type of the performance data. Then, the target performance data is parsed according to the parsing rule data to obtain the parsing result.

[0082] Optionally, based on the name and data type of the performance data, the target performance data can be determined from the performance data of at least one target report to be analyzed. For example, if the name of the performance data is CPU and the data type is floating point, then the target performance data can be determined as floating point CPU performance data from performance data such as DML processing performance data, CPU performance data, and memory performance data.

[0083] Furthermore, based on the parsing rule data, the target performance data is parsed to obtain the parsing result. For example, if the parsing rule data is line_data[i+2][15:25] (that is, converting each line of the file into a list format), the floating-point type CPU performance data is parsed to obtain the corresponding CPU resource performance consumption, i.e., the parsing result.

[0084] It should be noted that by parsing the target performance data, the processing efficiency of report analysis is improved. Subsequently, the required PM report performance analysis data can be obtained by filtering according to dimensions (metric level or table level), PM report generation date, DB2 product version, metric name or table name, etc. This effectively meets the user's need to obtain accurate performance analysis reports in a timely manner and provides convenience for users to perform report analysis.

[0085] In one optional embodiment, before determining at least one target report to be analyzed from a plurality of reports to be analyzed according to a first parsing condition, upon receiving a first target request, editing request information in the first target request is obtained, and then a first parsing rule is generated based on the editing request information. The first target request is one of the following: a new editing request, a modified editing request, and the editing request information represents editing information for the parsing rule.

[0086] Optionally, the first target request can be a secondary development request, i.e., a new edit request or a modification edit request, and the first parsing rule can be a new parsing rule obtained through the new edit or modification edit.

[0087] Figure 6 This is an implementation flowchart of an optional PM report agile secondary development deployment according to an embodiment of the present invention, such as... Figure 6 As shown, the implementation process for Function 5 (Agile Secondary Development Deployment) specifically includes the following steps:

[0088] Step S501: The front-end uses the el-dialog component to create a secondary development requirement form. The form items include "DB2 product version, report type (ACCOUNTING or STAT), add indicator name, indicator type and parsing rule, specify indicator name, modify indicator name, indicator type and parsing rule".

[0089] Step S502, before deploying the agile secondary development function (i.e., adding report parsing methods), the user triggers the form button, edits the corresponding items according to the requirements, and clicks confirm. The front end sends the required items to the back end through the specified URL.

[0090] In step S503, the backend receives the requirement items from the frontend (i.e., when the first target request is received, the edit request information in the first target request is obtained) and processes them respectively (i.e., the first parsing rule is generated according to the edit request information). First, a data table with the same name and parsing method is created for the DB2 product version. Second, the initial indicator definition module is copied, and the indicator definition module is modified according to the added or modified indicator name or type. Finally, the parsing method module is modified according to the requirements of adding or modifying the field filtering rules.

[0091] Step S504: The above steps complete the addition of a new parsing method. When a user calls the report parsing function, they can select the DB2 product version and report type (ACCOUNTING or STAT) to call the parsing module under the corresponding version. The parsing results will also be stored in the data table under the corresponding version.

[0092] It should be noted that the above process has enabled the agile deployment function of secondary development. When the indicators change, the development requirements can be added through the webpage to add and launch the PM report parsing method, which better meets the user's needs.

[0093] In one optional embodiment, the edit request information includes at least one of the following: a first report type, a first report version, a name of the first performance data, a data type of the first performance data, and first parsing rule data. During the process of generating the first parsing rule based on the edit request information, if the first target request is a new edit request, a first target data table is generated based on the first report type and the first report version. Then, based on the name and data type of the first performance data, the first target data is retrieved from the database and stored in the first target data table. Finally, first parsing rule data is added to the first target data table to generate the first parsing rule.

[0094] In one optional embodiment, during the process of generating the first parsing rule based on the edit request information, if the first target request is a modification / edit request, a second target data table is generated based on the first report type and the first report version. Then, based on the name and data type of the first performance data, the first target data is retrieved from the database and stored in the second target data table. In the second target data table, the parsing rule corresponding to the first target data is updated according to the first parsing rule data to generate the first parsing rule.

[0095] Figure 7 This is a flowchart illustrating the modification of the indicator definition module and the parsing method module in an optional secondary development process according to an embodiment of the present invention, as follows: Figure 7 As shown, the modification process specifically includes the following steps:

[0096] Step S601: Based on the DB2 product version entry (i.e., the first report version) in the secondary development requirements, create a data table with the same name to store the modified indicator definitions and parsing methods modules; that is, create a data table with the same name as the report corresponding to the version. Optionally, if the first target request is a new edit request, then generate the first target data table (i.e., the data table corresponding to the new edit request) based on the first report type (ACCOUNTING or STAT) and the first report version; if the first target request is a modification edit request, then generate the second target data table (i.e., the data table corresponding to the modification edit request) based on the first report type and the first report version.

[0097] Step S602: When the secondary development requirement function is triggered, copy the contents of the initial data table (i.e., the data table storing the initial indicator definition and parsing method module) (i.e., retrieve the first target data from the database based on the name and data type of the first performance data) to the newly added data table (i.e., the first target data table or the second target data table). The contents include the report type (ACCOUNTING or STAT), the name and type of each indicator (i.e., the name and data type of the first performance data, for example, the name of the first performance data is CPU, and the data type is floating-point, numeric, or string) and its parsing method (i.e., the first parsing rule data, that is, the field filtering rule, for example, the value of a certain indicator is in several columns of data containing a certain keyword). Optionally, if the first target request is a new edit request, retrieve the first target data from the database based on the name and data type of the first performance data, and store the first target data in the first target data table; if the first target request is a modify edit request, retrieve the first target data from the database based on the name and data type of the first performance data, and store the first target data in the second target data table.

[0098] Step S603: If the secondary development requirement is to add a new indicator (i.e., if the first target request is a new edit request), add a new record in the data table obtained in step S602 (i.e., the first target data table) using an SQL statement, for example, insert into tablename(name,kind,rule)values(new indicator name, new indicator name type, new indicator filtering rule)where table = 'accounting'), thus completing the insertion of the indicator definition and its parsing method data table (i.e., adding the first parsing rule data to the first target data table and generating the first parsing rule); If the secondary development requirement is to modify the original indicator (i.e., if the first target request is a modification edit request), the modified records need to be filtered and then updated (e.g., update tablename set kind = modify indicator name type, rule = indicator filtering rule where table = 'accounting' and name = modify indicator name), thus completing the update of the indicator definition and parsing method modification (i.e., in the data table obtained in step S602 (i.e., the second target data table), update the parsing rule corresponding to the first target data according to the first parsing rule data and generate the first parsing rule).

[0099] Step S604: When the report parsing function is called, the definition of the corresponding indicators and the numerical filtering rules in the corresponding data table will be filtered out by the DB2 product version and the report type (ACCOUNTING or STAT) to obtain the final parsing result.

[0100] It should be noted that the above process has enabled the agile deployment function of secondary development. When the indicators change, the development requirements can be added through the webpage to add and launch the PM report parsing method, which better meets the user's needs.

[0101] In one optional embodiment, before determining the target parsing rules corresponding to at least one target report to be analyzed, and before parsing the at least one target report to be analyzed according to the target parsing rules to obtain the parsing results, upon receiving a second target request, the query request information in the second target request is obtained. Then, based on the query request information, target parsing result data is retrieved from the database to generate a target parsing result file. Finally, based on the target parsing result file, a target chart is generated. The target chart is used to display the target parsing result data to the target object. The query request information includes at least one of the following: target report generation date, target report type, target report version, and the name of the target performance data.

[0102] Optionally, the second target request can be a query request, and the target parsing result data can be data determined based on query request information such as the target report generation date, target report type, target report version, and the name of the target performance data.

[0103] Figure 8 This is an optional PM report parsing result query flowchart according to an embodiment of the present invention, such as... Figure 8 As shown, the implementation process for function 3 (report parsing result query) specifically includes the following steps:

[0104] Step S701: The front end uses the el-form component to create filter items. The content of the filter items includes "filter dimension (metric level or table level), PM report generation date, DB2 product version, metric name or table name".

[0105] Step S702: The front end sets the warning rules for each performance indicator in multiple scenarios. The warning rules include two types: threshold alarm and trend alarm. The threshold alarm has a higher priority than the trend alarm. The threshold alarm means that when a certain performance indicator exceeds the set value in a certain scenario, the bar chart (or line chart, etc.) displayed in the chart is red. When the value of a certain performance indicator shows an upward trend in multiple scenarios, the bar chart (or line chart, etc.) displayed in the chart is orange.

[0106] Step S703: Before filtering, the user fills in the filtering items (i.e. query request information, including at least one of the following: target report generation date, target report type, target report version, and name of target performance data) on the front-end web page to trigger the query function.

[0107] Step S704: After triggering the query function, the filter items are sent to the backend through the specified URL. The filter items are used as filtering conditions to request the backend to obtain the MySQL storage table records (that is, when the second target request is received, the query request information in the second target request is obtained, and then the target parsing result data is obtained from the database according to the query request information).

[0108] In step S705, each record is in dictionary format with the format "field name: field value". The multiple records obtained are combined into a list type (i.e., the target parsing result file is generated) and returned to the front end.

[0109] Step S706: The front end uses the ECharts component to draw analysis charts for the report (i.e., generate target charts based on the target parsing result file). Regardless of whether it is at the indicator level or the table level, the data returned to the front end contains data from multiple scenarios. The processed data uses the field name as the horizontal axis and the field value as the vertical axis. Multiple bars or lines are drawn according to the scenario type for comparison and analysis. The front end displays alerts based on the multi-scenario data returned from the back end (see step S702 for details).

[0110] Figure 9 This is a flowchart illustrating an optional one-click export process for PM reports according to an embodiment of the present invention, such as... Figure 9 As shown, the implementation process for function 4 (one-click report export) includes the following steps:

[0111] In step S801, the front end uses the el-form component to create filter items. The filter items include "PM report generation date, DB2 product version". When parsing the PM report, the ACCOUNTING and STAT reports are parsed simultaneously. Under the same date and DB2 product version, analysis charts for ACCOUNTING and STAT will be generated.

[0112] Step 802: Before one-click export, the user fills in the filter items on the front-end web page to trigger the one-click export function.

[0113] Step S803: After triggering, the filter items are sent to the backend via the specified URL. The backend uses the filter items as filtering conditions and requests the backend database to obtain all data that meets the conditions (including indicator level and table level).

[0114] In step S804, each record is in dictionary format as “field name: field value”, and the multiple records obtained are combined into a list type and returned to the front end.

[0115] In step S805, the front end creates an empty WORD file in the static files, and uses the echarts, docxtemplater and file-saver components to draw the data into a multi-scenario comparison chart and display warnings (see step S702 for details), and archives it as a file to return to the user.

[0116] It should be noted that this embodiment provides an automated performance analysis method based on PM reports from DB2 mainframe products. Through backend-frontend interaction, users can easily access various processing functions for PM reports from a frontend web page perspective. One-click triggering commands enable PM report parsing, result querying, and archiving, effectively improving the efficiency of DB2 product performance data analysis and processing, saving time and manpower costs, and reducing the experience and technical skill requirements for users in the data analysis process. Furthermore, this embodiment allows for agile deployment through secondary development. For example, when indicators change, development requirements can be added via the webpage to add and deploy new PM report parsing methods, better meeting user needs.

[0117] Therefore, the technical solution of the present invention achieves the goal of reducing the labor and time costs of report analysis and processing, thereby improving the processing efficiency of report analysis and processing, and solving the technical problem of low processing efficiency in the prior art of manually collecting and analyzing report data.

[0118] Example 2

[0119] According to an embodiment of the present invention, a report processing apparatus is provided, wherein, Figure 10 This is a schematic diagram of an optional report processing device according to an embodiment of the present invention, such as... Figure 10 As shown, the device includes: an acquisition module 1001, used to acquire a report file to be analyzed, wherein the report file to be analyzed includes multiple reports to be analyzed, and the multiple reports to be analyzed include performance data of the target device; a determination module 1002, used to determine at least one target report to be analyzed from the multiple reports to be analyzed according to a first parsing condition, wherein the first parsing condition includes at least one of the following: report generation date, report type, and report version; and a processing module 1003, used to determine the target parsing rule corresponding to the at least one target report to be analyzed, and to perform parsing processing on the at least one target report to be analyzed according to the target parsing rule to obtain a parsing result, wherein the parsing result characterizes the performance of the target device.

[0120] It should be noted that the above-mentioned acquisition module 1001, determination module 1002 and processing module 1003 correspond to steps S101 to S103 in the above embodiments. The three modules and the corresponding steps implement the same examples and application scenarios, but are not limited to the content disclosed in the above embodiment 1.

[0121] Optionally, the acquisition module includes: a first acquisition module, used to acquire multiple initial reports associated with the target device; a first processing module, used to add corresponding scene identifiers to the names of the multiple initial reports according to the scene information corresponding to the multiple initial reports, to obtain multiple reports to be analyzed; and a second processing module, used to generate a report file to be analyzed based on the multiple reports to be analyzed.

[0122] Optionally, the report type includes at least one of the following: Type 1 and Type 2, where the performance data corresponding to Type 1 and Type 2 are different. The processing module includes: a second acquisition module, used to acquire a rule data table of parsing rules corresponding to the report version; and a third processing module, used to query the target data corresponding to the report type from the rule data table and perform concatenation processing on the target data to obtain the target parsing rules. The target data includes at least one of the following: the name of the performance data, the data type of the performance data, and parsing rule data, whereby the parsing rule data represents the parsing method of the performance data.

[0123] Optionally, the processing module further includes: a first determining module, used to determine target performance data from the performance data of at least one target report to be analyzed based on the name and data type of the performance data; and a fourth processing module, used to parse the target performance data according to the parsing rule data to obtain the parsing result.

[0124] Optionally, the report processing device further includes: a fifth processing module, used to perform format conversion processing on the report file to be analyzed, to obtain the converted report file to be analyzed, and to store the converted report file to be analyzed in the first directory.

[0125] Optionally, the report processing device further includes: a third acquisition module, used to acquire editing request information in the first target request when a first target request is received, wherein the first target request is one of the following: a new editing request, a modified editing request, and the editing request information represents the editing information of the parsing rule; and a sixth processing module, used to generate a first parsing rule based on the editing request information.

[0126] Optionally, the edit request information includes at least one of the following: a first report type, a first report version, a name of the first performance data, a data type of the first performance data, and first parsing rule data. The sixth processing module includes: a seventh processing module, used to generate a first target data table based on the first report type and the first report version if the first target request is a new edit request; a fourth acquisition module, used to acquire the first target data from the database based on the name and data type of the first performance data, and store the first target data in the first target data table; and an eighth processing module, used to add first parsing rule data to the first target data table and generate a first parsing rule.

[0127] Optionally, the sixth processing module further includes: a ninth processing module, used to generate a second target data table based on the first report type and the first report version if the first target request is a modification / edit request; a fifth acquisition module, used to acquire the first target data from the database based on the name and data type of the first performance data, and store the first target data in the second target data table; and a tenth processing module, used to update the parsing rules corresponding to the first target data in the second target data table according to the first parsing rule data, and generate the first parsing rule.

[0128] Optionally, the report processing device further includes: a sixth acquisition module, used to acquire query request information in the second target request upon receiving the second target request, wherein the query request information includes at least one of the following: target report generation date, target report type, target report version, and name of target performance data; a seventh acquisition module, used to acquire target parsing result data from the database based on the query request information and generate a target parsing result file; and an eleventh processing module, used to generate a target chart based on the target parsing result file, wherein the target chart is used to display the target parsing result data to the target object.

[0129] Example 3

[0130] According to another aspect of the present invention, a computer-readable storage medium is also provided, wherein a computer program is stored in the computer-readable storage medium, and the computer program is configured to execute the above-described report processing method at runtime.

[0131] Example 4

[0132] According to another aspect of the present invention, an electronic device is also provided, wherein, Figure 11 This is a schematic diagram of an optional electronic device according to an embodiment of the present invention, such as... Figure 11 As shown, the electronic device includes one or more processors; a memory for storing one or more programs, which, when executed by the one or more processors, enable the one or more processors to run the programs, wherein the programs are configured to execute the aforementioned report processing method during runtime. When the processor executes the program, it performs the following steps: obtaining a report file to be analyzed, wherein the report file includes multiple reports to be analyzed, and the multiple reports to be analyzed include performance data of the target device; determining at least one target report to be analyzed from the multiple reports to be analyzed according to a first parsing condition, wherein the first parsing condition includes at least one of the following: report generation date, report type, report version; determining the target parsing rule corresponding to the at least one target report to be analyzed, and parsing the at least one target report to be analyzed according to the target parsing rule to obtain a parsing result, wherein the parsing result characterizes the performance of the target device.

[0133] Optionally, when the processor executes the program, it also performs the following steps: obtaining multiple initial reports associated with the target device; adding corresponding scene identifiers to the names of the multiple initial reports according to the scene information corresponding to the multiple initial reports to obtain multiple reports to be analyzed; and generating a report file to be analyzed based on the multiple reports to be analyzed.

[0134] Optionally, the report type includes at least one of the following: a first type and a second type. The performance data corresponding to the first type and the second type are different. When the processor executes the program, it also performs the following steps: obtains a rule data table of parsing rules corresponding to the report version; queries the target data corresponding to the report type from the rule data table, and concatenates the target data to obtain the target parsing rule. The target data includes at least one of the following: the name of the performance data, the data type of the performance data, and parsing rule data. The parsing rule data represents the parsing method of the performance data.

[0135] Optionally, when the processor executes the program, it also performs the following steps: determining target performance data from the performance data of at least one target report to be analyzed based on the name and data type of the performance data; and parsing the target performance data according to the parsing rule data to obtain the parsing result.

[0136] Optionally, the processor may also perform the following steps when executing the program: after obtaining the report file to be analyzed, perform format conversion processing on the report file to be analyzed to obtain the converted report file to be analyzed, and store the converted report file to be analyzed in the first directory.

[0137] Optionally, when the processor executes the program, it further implements the following steps: before determining at least one target report to be analyzed from multiple reports to be analyzed according to the first parsing condition, upon receiving the first target request, obtaining the editing request information in the first target request, wherein the first target request is one of the following: a new editing request, a modified editing request, and the editing request information represents the editing information of the parsing rule; and generating the first parsing rule according to the editing request information.

[0138] Optionally, the edit request information includes at least one of the following: a first report type, a first report version, a name of the first performance data, a data type of the first performance data, and first parsing rule data. When the processor executes the program, it further implements the following steps: if the first target request is a new edit request, then a first target data table is generated according to the first report type and the first report version; the first target data is retrieved from the database according to the name and data type of the first performance data, and the first target data is stored in the first target data table; first parsing rule data is added to the first target data table, and a first parsing rule is generated.

[0139] Optionally, when the processor executes the program, it also performs the following steps: if the first target request is a modification / edit request, then a second target data table is generated according to the first report type and the first report version; the first target data is retrieved from the database according to the name and data type of the first performance data, and the first target data is stored in the second target data table; in the second target data table, the parsing rule corresponding to the first target data is updated according to the first parsing rule data, and the first parsing rule is generated.

[0140] Optionally, the processor, when executing the program, further implements the following steps: before determining the target parsing rule corresponding to at least one target report to be analyzed, and before parsing the at least one target report to be analyzed according to the target parsing rule to obtain the parsing result, upon receiving a second target request, obtaining query request information from the second target request, wherein the query request information includes at least one of the following: target report generation date, target report type, target report version, and name of target performance data; based on the query request information, retrieving target parsing result data from the database and generating a target parsing result file; and based on the target parsing result file, generating a target chart, wherein the target chart is used to display the target parsing result data to the target object.

[0141] The devices mentioned in this article can be servers, PCs, tablets, mobile phones, etc.

[0142] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0143] In the above embodiments of the present invention, 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.

[0144] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0145] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0146] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0147] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0148] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A report processing method characterized by, include: Obtain a report file to be analyzed, wherein the report file to be analyzed includes multiple reports to be analyzed, the multiple reports to be analyzed include performance data of the target device, and the name of the report to be analyzed includes at least the scene identifier corresponding to the report to be analyzed; Based on the first parsing condition, at least one target report to be analyzed is determined from the plurality of reports to be analyzed, wherein the first parsing condition includes at least one of the following: report generation date, report type, and report version; Determine the target parsing rules corresponding to the at least one target report to be analyzed, and perform parsing processing on the at least one target report to be analyzed according to the target parsing rules to obtain the parsing results, wherein the parsing results characterize the performance of the target device; The report type includes at least one of the following: a first type and a second type, wherein the performance data corresponding to the first type and the second type are different, and determining the target parsing rule corresponding to the at least one target report to be analyzed includes: Obtain the rule data table of the parsing rules corresponding to the report version; The target data corresponding to the report type is queried from the rule data table, and the target data is concatenated to obtain the target parsing rule. The target data includes at least one of the following: the name of the performance data, the data type of the performance data, and the parsing rule data, wherein the parsing rule data represents the parsing method of the performance data. Before determining at least one target report to be analyzed from the plurality of reports to be analyzed based on the first parsing condition, the method further includes: Upon receiving a first target request, the editing request information in the first target request is obtained, wherein the first target request is one of the following: a new editing request or a modified editing request, and the editing request information represents the editing information of the parsing rules; Based on the edit request information, a first parsing rule is generated.

2. The method of claim 1, wherein, Obtain the report file to be analyzed, including: Obtain multiple initial reports associated with the target device; Based on the scenario information corresponding to the multiple initial reports, add corresponding scenario identifiers to the names of the multiple initial reports to obtain the multiple reports to be analyzed; The report file to be analyzed is generated based on the multiple reports to be analyzed.

3. The method of claim 1, wherein, According to the target parsing rules, the at least one target report to be analyzed is parsed to obtain the parsing result, including: Based on the name and data type of the performance data, determine the target performance data from the performance data of the at least one target report to be analyzed; Based on the parsing rules, the target performance data is parsed to obtain the parsing result.

4. The method of claim 1, wherein, After obtaining the report file to be analyzed, the method further includes: The report file to be analyzed is converted to a new format to obtain a converted report file, which is then stored in the first directory.

5. The method of claim 1, wherein, The edit request information includes at least one of the following: a first report type, a first report version, a name of the first performance data, a data type of the first performance data, and first parsing rule data, wherein generating the first parsing rule based on the edit request information includes: If the first target request is the new edit request, then a first target data table is generated according to the first report type and the first report version; Based on the name and data type of the first performance data, retrieve the first target data from the database and store the first target data in the first target data table; Add the first parsing rule data to the first target data table to generate the first parsing rule.

6. The method of claim 5, wherein, Based on the edit request information, a first parsing rule is generated, including: If the first target request is the modification / edit request, then a second target data table is generated based on the first report type and the first report version; Based on the name and data type of the first performance data, the first target data is retrieved from the database and stored in the second target data table. In the second target data table, the parsing rule corresponding to the first target data is updated according to the first parsing rule data to generate the first parsing rule.

7. The method of claim 1, wherein, Before determining the target parsing rule corresponding to the at least one target report to be analyzed, and parsing the at least one target report to be analyzed according to the target parsing rule to obtain the parsing result, the method further includes: Upon receiving a second target request, the query request information in the second target request is obtained, wherein the query request information includes at least one of the following: target report generation date, target report type, target report version, and name of target performance data; Based on the query request information, retrieve the target parsing result data from the database and generate the target parsing result file; Based on the target parsing result file, a target chart is generated, wherein the target chart is used to display the target parsing result data to the target object.

8. A report processing apparatus characterized by comprising: include: The acquisition module is used to acquire a report file to be analyzed, wherein the report file to be analyzed includes multiple reports to be analyzed, the multiple reports to be analyzed include performance data of the target device, and the name of the report to be analyzed includes at least the scene identifier corresponding to the report to be analyzed; The determination module is used to determine at least one target report to be analyzed from the plurality of reports to be analyzed according to a first parsing condition, wherein the first parsing condition includes at least one of the following: report generation date, report type, and report version; The processing module is configured to determine the target parsing rule corresponding to the at least one target report to be analyzed, and to perform parsing processing on the at least one target report to be analyzed according to the target parsing rule to obtain the parsing result, wherein the parsing result characterizes the performance of the target device; The report type includes at least one of the following: a first type and a second type, wherein the performance data corresponding to the first type and the second type are different. The processing module includes: a second acquisition module, used to acquire a rule data table of parsing rules corresponding to the report version; and a third processing module, used to query the target data corresponding to the report type from the rule data table and perform concatenation processing on the target data to obtain the target parsing rules, wherein the target data includes at least one of the following: the name of the performance data, the data type of the performance data, and parsing rule data, wherein the parsing rule data represents the parsing method of the performance data. The report processing device further includes: a third acquisition module, used to acquire editing request information in the first target request when a first target request is received, wherein the first target request is one of the following: a new editing request, a modified editing request, and the editing request information represents the editing information of the parsing rule; and a sixth processing module, used to generate a first parsing rule based on the editing request information.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein the computer program is configured to execute the report processing method according to any one of claims 1 to 7 when it is run.

10. An electronic device, characterized in that, The electronic device includes one or more processors; A memory for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to be configured to run the programs, wherein the programs are configured to execute the report processing method as described in any one of claims 1 to 7.

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