Data collection method, device, electronic device and medium

Abstract

The present disclosure provides a data collection method, device, equipment, storage medium and program product, which relates to the field of computer technology and can be applied to the field of financial technology. The method includes: in response to receiving a data collection request, determining a target object and a target task type corresponding to the data collection request; based on an object model structure, determining attribute information corresponding to the target task type for the target object; calling a script corresponding to the attribute information to obtain the collection data; and generating an image corresponding to the target object according to the collection data; wherein the object model structure includes multiple objects and multiple attribute information corresponding to the multiple objects, respectively, the attribute information has a mapping relationship with the object and the task type, and the object includes one or more of an operating system, a database, a middleware and an application.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology and can be applied to the field of financial technology. More specifically, it relates to a data collection method, device, equipment, medium and program product. Background Art

[0002] At present, when enterprises use operation and maintenance systems, they usually manually add operation and maintenance object models on the page, and then write corresponding scripts according to the defined object models. Then they collect and analyze data, obtain analysis results, and store them in the database for management or use.

[0003] However, the manual configuration method mentioned above takes a lot of time and is prone to errors. In addition, the object model is input by the user, and the relevant programs for writing data collection and processing scripts based on the added object model are completed by the back-end programmer. There are communication barriers about the model. Due to differences in understanding of the model, there will be inconsistencies between the object model and the actual object data, which can easily cause system problems. Summary of the invention

[0004] In view of the above problems, the present disclosure provides a data collection method, apparatus, equipment, medium and program product, which can make the attribute information correspond to the results of the collected data, avoid the inconsistency between the object model and the actual object data, and have the advantages of automation, intelligence, and high accuracy of collected data.

[0005] According to a first aspect of the present disclosure, a data collection method is provided, comprising: in response to receiving a data collection request, determining a target object and a target task type corresponding to the data collection request; based on an object model structure, determining attribute information corresponding to the target task type for the target object; calling a script corresponding to the attribute information to obtain collection data; and generating an image corresponding to the target object based on the collection data; wherein the object model structure comprises a plurality of objects and a plurality of attribute information respectively corresponding to the plurality of objects, the attribute information respectively having a mapping relationship with the object and the task type, and the object comprises one or more of an operating system, a database, a middleware, and an application.

[0006] According to an embodiment of the present disclosure, the attribute information corresponding to the target task type is determined for the target object based on the object model structure, including: determining first sub-attribute information for the target object based on the object model structure; determining second sub-attribute information corresponding to the target task type; and determining third sub-attribute information based on a matching result between the first sub-attribute information and the second sub-attribute information.

[0007] According to an embodiment of the present disclosure, generating an image corresponding to the target object based on the collected data includes: retrieving a parsing rule for the target object, parsing the collected data to obtain a parsing result; and generating an image corresponding to the target object based on the parsing result.

[0008] According to an embodiment of the present disclosure, the data collection method also includes: in response to receiving a page display request from a user, determining a target object corresponding to the page display request; determining a rendering control based on an image corresponding to the target object; rendering the view to be rendered based on the rendering control to obtain a target page; and displaying the target page to the user.

[0009] According to an embodiment of the present disclosure, the object model structure includes an object model table and a collection script table; wherein the object model table is used to store the multiple objects and multiple attribute information corresponding to the multiple objects, and the collection script table is used to store multiple scripts corresponding to the multiple attribute information.

[0010] The second aspect of the present disclosure provides a data acquisition device, including: a receiving module, for determining a target object and a target task type corresponding to a data acquisition request in response to receiving the data acquisition request; a determining module, for determining attribute information corresponding to the target task type for the target object based on an object model structure; an acquisition module, for calling a script corresponding to the attribute information to obtain acquisition data; and a generating module, for generating an image corresponding to the target object based on the acquisition data; wherein the object model structure includes a plurality of objects and a plurality of attribute information corresponding to the plurality of objects, respectively, the attribute information respectively having a mapping relationship with the object and the task type, and the object includes one or more of an operating system, a database, a middleware, and an application.

[0011] A third aspect of the present disclosure provides an electronic device, comprising: one or more processors; and 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 execute the above-mentioned data collection method.

[0012] The fourth aspect of the present disclosure further provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, causes the processor to execute the above-mentioned data collection method.

[0013] The fifth aspect of the present disclosure also provides a computer program product, including a computer program, which implements the above-mentioned data collection method when executed by a processor.

[0014] The data collection method provided in this embodiment can make the attribute information correspond to the result of the collected data, avoid the problem of inconsistency between the object model and the actual object data, and has the advantages of automation, intelligence, and high accuracy of collected data. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The above contents and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0016] Figure 1 The application scenario diagram of the data collection method, apparatus, device, medium and program product according to the embodiments of the present disclosure is schematically shown;

[0017] Figure 2 A flow chart schematically shows a data collection method according to an embodiment of the present disclosure;

[0018] Figure 3 The following schematically shows an execution diagram of displaying a target page according to an embodiment of the present disclosure;

[0019] Figure 4 A schematic diagram of a process for determining a second target virtual machine device according to an embodiment of the present disclosure is shown;

[0020] Figure 5 A flowchart schematically shows a data collection method according to another embodiment of the present disclosure; and

[0021] Figure 6 A block diagram of an electronic device suitable for implementing a data collection method according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0022] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0023] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0024] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification, and should not be interpreted in an idealized or overly rigid manner.

[0025] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0026] The embodiments of the present disclosure provide a data collection method and device, which, in response to receiving a data collection request, determine a target object and a target task type corresponding to the data collection request; based on an object model structure, determine attribute information corresponding to the target task type for the target object; call a script corresponding to the attribute information to obtain the collected data; and generate an image corresponding to the target object based on the collected data; wherein the object model structure includes multiple objects and multiple attribute information corresponding to the multiple objects, respectively, the attribute information has a mapping relationship with the object and the task type, and the object includes one or more of an operating system, a database, a middleware, and an application.

[0027] Figure 1 The application scenario diagram of the data collection method, apparatus, device, medium and program product according to the embodiments of the present disclosure is schematically shown.

[0028] like Figure 1 As shown, the application scenario 100 according to this embodiment may include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 is used to provide a medium for a communication link between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0029] Users can use terminal devices 101, 102, 103 to interact with server 105 through network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only examples).

[0030] The terminal devices 101 , 102 , and 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, and desktop computers.

[0031] The server 105 may be a server that provides various services, such as a background management server (only an example) that provides support for websites browsed by users using the terminal devices 101, 102, and 103. The background management server may analyze and process the received data such as user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal device.

[0032] It should be noted that the data collection method provided in the embodiment of the present disclosure can generally be executed by the server 105. Accordingly, the data collection device provided in the embodiment of the present disclosure can generally be set in the server 105. The data collection method provided in the embodiment of the present disclosure can also be executed by a server or server cluster that is different from the server 105 and can communicate with the terminal devices 101, 102, 103 and / or the server 105. Accordingly, the data collection device provided in the embodiment of the present disclosure can also be set in a server or server cluster that is different from the server 105 and can communicate with the terminal devices 101, 102, 103 and / or the server 105.

[0033] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0034] The following will be based on Figure 1 The scene described by Figure 2 The data collection method of the disclosed embodiment is described in detail.

[0035] Figure 2 The flowchart of the data collection method according to the embodiment of the present disclosure is schematically shown.

[0036] like Figure 2 As shown, this embodiment includes operations S210 to S240, and the data collection method can be executed by a server.

[0037] In the technical solution disclosed in the present invention, the acquisition, collection, storage, use, processing, transmission, provision, disclosure and application of data are in compliance with the provisions of relevant laws and regulations, necessary confidentiality measures are taken, and do not violate public order and good morals.

[0038] In operation S210 , in response to receiving a request to collect data, a target object and a target task type corresponding to the request to collect data are determined.

[0039] In operation S220 , attribute information corresponding to the target task type is determined for the target object based on the object model structure.

[0040] The object model structure includes multiple objects and multiple attribute information corresponding to the multiple objects respectively. The attribute information has a mapping relationship with the object and the task type respectively. The object includes one or more of an operating system, a database, a middleware and an application program.

[0041] In operation S230, a script corresponding to the attribute information is retrieved to obtain collected data.

[0042] In operation S240, an image corresponding to the target object is generated according to the collected data.

[0043] Objects can be operation and maintenance objects, such as operating systems, databases, middleware, applications, etc. Operation and maintenance objects can also be: 1) The infrastructure part of a certain computer room environment, which can be network communications, power resources, environmental resources, etc. required to ensure the normal operation of the equipment managed by the data center; 2) It can be various equipment used in the process of providing IT services, such as storage, servers, network equipment, security equipment and other hardware resources; 3) It can be systems and data, such as operating systems, databases, middleware, applications and other software resources; It can also be business data, configuration files, logs and other types of data; 4) It can be management tools, such as infrastructure monitoring software, monitoring software, workflow management platform, reporting platform, SMS platform, etc.

[0044] Tasks can be set and adjusted according to actual needs, such as testing tasks, stability detection tasks, performance optimization tasks, capacity expansion tasks, migration tasks, etc.

[0045] Attribute information can represent an object model, can be a definition of each attribute of an object, and can include information such as attribute field name, Chinese meaning, etc. For example, operating system, middleware, switch, Kylin system, etc.

[0046] If data collection is configured manually, it is easy to consume a lot of time and prone to errors. The collection and processing of general data depends on the input attribute information. If the data collection and processing scripts are determined only based on the attribute information added by the user, it is easy to cause the actual collected data to deviate from the actual attribute information. If data collection and attribute information are put together and maintained together, it is conducive to the actual collected data to correspond to the actual attribute information and be consistent. For example, a script process can be used to obtain a script file corresponding to a predefined specification. The file may include a description of the attribute information and an execution script for the collected data. After uploading the script, the attribute information and object information are extracted and stored in the database. The script content can also be stored in the database for use when collecting data.

[0047] Regarding the object model structure, i.e., the object model database, it should be noted that the object model structure is mainly used to store attribute information corresponding to the object. For example, in response to receiving an uploaded script, the script is parsed, and the attributes and corresponding meanings of each field of the annotation content are extracted, and stored in the database after unified arrangement. The script file can also be stored in the database for unified processing. The script file can be a script written according to the agreed specifications. The information contained in the script is not the script execution content, and is added in the form of comments to ensure consistency between the attribute information and the object data collected by executing the script.

[0048] For example, the collection task can be triggered by manual click, timed task or automatic change trigger, that is, the collection data request can be triggered. After receiving the collection data request, the target object and the target task type corresponding to the collection data request can be determined; for example, the target object is middleware a, and the task type is test task b.

[0049] The object structure includes multiple objects, and the object stored in the object structure that is consistent with the target object can be determined first. In the object structure, the object corresponds to multiple attribute information. Since the attribute information has a mapping relationship with the object and task type respectively, the attribute information corresponding to the target task type is determined for the target object. Then, the script (execution script) corresponding to the attribute information is called, and after obtaining the execution script, it can be sent to the remote target machine for execution, and the result returned by the script collection is waited for, so as to obtain the collected data. Then, the collected data can be used to generate data charts, draw images, etc. Store multiple images corresponding to the target object for unified management, such as generating a visualization platform to provide a basis for image display.

[0050] The data collection method provided in this embodiment determines the attribute information corresponding to the target task type for the target object based on the object model structure; calls the script corresponding to the attribute information to obtain the collected data; and can make the attribute information and the result of the collected data correspond to each other, avoiding the problem of inconsistency between the object model and the actual object data. The method has the advantages of automation, intelligence, and high accuracy of collected data.

[0051] Based on the object model structure, attribute information corresponding to the target task type is determined for the target object, including: based on the object model structure, first sub-attribute information is determined for the target object; second sub-attribute information corresponding to the target task type is determined; and third sub-attribute information is determined based on a matching result between the first sub-attribute information and the second sub-attribute information.

[0052] For example, the object model structure includes object a, object b, object c, object d, .., object y, and object z. The attribute information corresponding to object a includes attribute 1, attribute 2, ..., attribute 9; the attribute information corresponding to object b includes attribute 10, attribute 11, ..., attribute 15; the attribute information corresponding to object c includes attribute 16, attribute 17, ..., attribute 31; ... (such as the attribute corresponding to object y includes attribute 107, attribute 108, ..., attribute 123; such as the attribute information corresponding to object z includes attribute 124, attribute 125, ..., attribute 150). Each attribute. The attribute information has a mapping relationship with the task type, such as the attribute information corresponding to task b (such as a test task) includes attributes 1, 7, 9, 21, 31; the attribute information corresponding to task c includes attributes 5, 6, 32, 111, and so on.

[0053] In this embodiment, for example, the target object is middleware a (i.e., object a), and the task type is test task b (i.e., task b). According to the above convention, based on the object model structure, the first sub-attribute information result can be determined, such as attribute 1, attribute 2, ..., attribute 9; then the second sub-attribute information result can be determined, such as attributes 1, 7, 9, 21, 31; attribute information matching is performed based on the first sub-attribute information and the second sub-attribute information, and the third attribute information can be determined, such as attributes 1, 7, 9. Therefore, when the execution script is subsequently called, the scripts corresponding to attributes 1, 7, and 9 are called.

[0054] The data collection method provided in this embodiment can determine the third sub-attribute information according to the matching result of the first sub-attribute information and the second sub-attribute information, so that the actual data collected matches the actual object and has consistency.

[0055] Generating an image corresponding to the target object according to the collected data includes: retrieving a parsing rule for the target object, parsing the collected data to obtain a parsing result; and generating an image corresponding to the target object according to the parsing result.

[0056] For example, by configuring data parsing rules for each object, data can be extracted from a pre-defined format, such as using regular expressions, extended markup language, JSON data parsing rules, and other methods.

[0057] By analyzing the collected data, the information hidden behind the chaotic collected data can be extracted, and the extracted key information is helpful for forming conclusions that are helpful to the business. At the same time, by processing and arranging the analysis results, such as drawing charts and images, it is helpful to provide a basis for data visualization.

[0058] The data collection method provided in this embodiment obtains the analysis result by retrieving the analysis rule for the target object and generates an image corresponding to the target object based on the analysis result, which facilitates the intelligent data collection and display.

[0059] The data collection method also includes: in response to receiving a page display request from a user, determining a target object corresponding to the page display request; determining a rendering control based on an image corresponding to the target object; rendering the view to be rendered based on the rendering control to obtain a target page; and displaying the target page to the user.

[0060] Figure 3 The schematic diagram of the execution of displaying the target page according to the embodiment of the present disclosure is shown schematically. Figure 3 . First, the user sends a page display request through the client 310. The server 320 responds to receiving the page display request and conveys the request to the data acquisition device 330. The data acquisition device 330 can determine the target object corresponding to the page display request in response to receiving the request; then search the image database corresponding to multiple objects to determine the image corresponding to the target object, for example, determine the image with the smallest time difference based on the timestamp. Then, based on the image with the smallest time difference, the rendering control for rendering the blank view (the view to be rendered) can be determined, and the view to be rendered can be rendered to obtain the target page. The data acquisition device 330 can send the target page to the client 310, that is, send the temporary target page to the user.

[0061] Regarding the rendering control, it should be noted that it can be a native rendering control in the operating system, such as a SurfaceView control, a UI View control, etc. It can also be an application engine, such as a Uniy engine, a Cocos engine, etc. The identifier corresponding to the target object can be passed to the rendering control, and the rendering control reads the image corresponding to the target object according to the identifier and renders the view to be rendered.

[0062] Figure 4 The flowchart of determining the second target virtual machine device according to an embodiment of the present disclosure is schematically shown.

[0063] like Figure 4 As shown, this embodiment includes operations S401 to S408.

[0064] In operation S401 , a plurality of collected data are stored in a database.

[0065] In operation S402, the parsing rules for the target object are retrieved, the collected data in the database is parsed, and the corresponding parsing results are stored.

[0066] In operation S403, an image corresponding to the target object is generated according to the parsing result.

[0067] In operation S404, a message from a user is monitored, such as receiving a page display request from a user.

[0068] In operation S405 , in response to receiving a page display request from a user, a target object corresponding to the page display request is determined.

[0069] In operation S406 , the target object is matched, and an image corresponding to the target object is determined, thereby determining a rendering control.

[0070] In operation S407, the view to be rendered is rendered using the determined rendering control to obtain a target page.

[0071] In operation S408, the target page is sent to the user and displayed.

[0072] The data collection method provided in this embodiment determines the target object corresponding to the page display request in response to receiving a page display request from the user; determines the rendering control based on the image corresponding to the target object; renders the view to be rendered according to the rendering control to obtain the target page; and displays the target page to the user, thereby realizing data visualization.

[0073] The object model structure includes an object model table and a collection script table; wherein the object model table is used to store multiple objects and multiple attribute information corresponding to the multiple objects, and the collection script table is used to store multiple scripts corresponding to the multiple attribute information.

[0074] The object model structure can be collaboratively maintained through the object model table and the collection script table. The object model table can be used to store multiple objects and multiple attribute information corresponding to the multiple objects, and the collection script table can be used to store multiple scripts corresponding to the multiple attribute information.

[0075] The data collection method provided in this embodiment uses the object model table and the collection script table to maintain the execution script and attribute information, which is beneficial to reducing the cost of maintaining complex data and realizing simple and efficient operations such as modification, addition or deletion of scripts and attribute information.

[0076] Based on the above data collection method, the present disclosure also provides a data collection device. Figure 5 The device is described in detail.

[0077] Figure 5 The structural block diagram of the data acquisition device according to the embodiment of the present disclosure is schematically shown.

[0078] like Figure 5As shown, the data acquisition device 500 of this embodiment includes a receiving module 510 , a determining module 520 , a collecting module 530 and a generating module 540 .

[0079] A receiving module 510 is used to determine, in response to receiving a data acquisition request, a target object and a target task type corresponding to the data acquisition request; a determining module 520 is used to determine, based on an object model structure, attribute information corresponding to the target task type for the target object; an acquisition module 530 is used to call a script corresponding to the attribute information to obtain acquisition data; and a generating module 540 is used to generate an image corresponding to the target object based on the acquisition data; wherein the object model structure includes multiple objects and multiple attribute information corresponding to the multiple objects, respectively, the attribute information has a mapping relationship with the object and the task type, and the object includes one or more of an operating system, a database, a middleware, and an application.

[0080] In some embodiments, the determination module includes: a first determination submodule, used to determine first sub-attribute information for the target object based on the object model structure; a second determination submodule, used to determine second sub-attribute information corresponding to the target task type; and a third determination submodule, used to determine third sub-attribute information based on the matching result of the first sub-attribute information and the second sub-attribute information.

[0081] In some embodiments, the generation module includes: a data analysis submodule, which is used to call the analysis rules for the target object and analyze the collected data to obtain the analysis results; and an image generation submodule, which generates an image corresponding to the target object according to the analysis results.

[0082] In some embodiments, the device also includes: a fourth determination submodule, used to determine the target object corresponding to the page display request in response to receiving the page display request from the user; a fifth determination submodule, used to determine the rendering control according to the image corresponding to the target object; a rendering module, which renders the view to be rendered according to the rendering control to obtain the target page; and a display module, which is used to display the target page to the user.

[0083] In some embodiments, the object model structure includes an object model table and a collection script table; wherein the object model table is used to store multiple objects and multiple attribute information corresponding to the multiple objects, and the collection script table is used to store multiple scripts corresponding to the multiple attribute information.

[0084] According to an embodiment of the present disclosure, any multiple modules of the receiving module 510, the determining module 520, the acquisition module 530 and the generating module 540 can be combined into one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module. According to an embodiment of the present disclosure, at least one of the receiving module 510, the determining module 520, the acquisition module 530 and the generating module 540 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation modes of software, hardware and firmware or in any appropriate combination of any of them. Alternatively, at least one of the receiving module 510, the determining module 520, the acquisition module 530 and the generating module 540 can be at least partially implemented as a computer program module, and when the computer program module is run, the corresponding function can be executed.

[0085] Figure 6 A block diagram of an electronic device suitable for implementing a data collection method according to an embodiment of the present disclosure is schematically shown.

[0086] like Figure 6 As shown, the electronic device 600 according to an embodiment of the present disclosure includes a processor 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage part 608 into a random access memory (RAM) 603. The processor 601 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 601 may also include an onboard memory for caching purposes. The processor 601 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0087] In RAM 603, various programs and data required for the operation of electronic device 600 are stored. Processor 601, ROM 602 and RAM 603 are connected to each other via bus 604. Processor 601 performs various operations of the method flow according to the embodiment of the present disclosure by executing the program in ROM 602 and / or RAM 603. It should be noted that the program can also be stored in one or more memories other than ROM 602 and RAM 603. Processor 601 can also perform various operations of the method flow according to the embodiment of the present disclosure by executing the program stored in the one or more memories.

[0088] According to an embodiment of the present disclosure, the electronic device 600 may further include an input / output (I / O) interface 605, which is also connected to the bus 604. The electronic device 600 may further include one or more of the following components connected to the I / O interface 605: an input portion 606 including a keyboard, a mouse, etc.; an output portion 607 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 608 including a hard disk, etc.; and a communication portion 609 including a network interface card such as a LAN card, a modem, etc. The communication portion 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as needed, so that a computer program read therefrom is installed into the storage portion 608 as needed.

[0089] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0090] According to an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, an apparatus or a device. For example, according to an embodiment of the present disclosure, a computer-readable storage medium may include the ROM 602 and / or RAM 603 described above and / or one or more memories other than ROM 602 and RAM 603.

[0091] The embodiment of the present disclosure also includes a computer program product, which includes a computer program, and the computer program contains program code for executing the method shown in the flowchart. When the computer program product is run in a computer system, the program code is used to enable the computer system to implement the data collection method provided by the embodiment of the present disclosure.

[0092] The above functions defined in the system / device of the embodiment of the present disclosure are performed when the computer program is executed by the processor 601. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0093] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 609, and / or installed from a removable medium 611. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0094] In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 609, and / or installed from the removable medium 611. When the computer program is executed by the processor 601, the above functions defined in the system of the embodiment of the present disclosure are performed. According to the embodiment of the present disclosure, the system, device, apparatus, module, unit, etc. described above can be implemented by a computer program module.

[0095] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect through the Internet).

[0096] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0097] It will be appreciated by those skilled in the art that the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways, even if such combinations and / or combinations are not explicitly described in the present disclosure. In particular, the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways without departing from the spirit and teachings of the present disclosure. All of these combinations and / or combinations fall within the scope of the present disclosure.

[0098] The embodiments of the present disclosure are described above. However, these embodiments are only for illustrative purposes and are not intended to limit the scope of the present disclosure. Although the embodiments are described above separately, this does not mean that the measures in the various embodiments cannot be used in combination to advantage. The scope of the present disclosure is defined by the attached claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art may make a variety of substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. A data collection method, comprising: In response to receiving a data collection request, determining a target object and a target task type corresponding to the data collection request; Based on the object model structure, determining attribute information corresponding to the target task type for the target object; Retrieving a script corresponding to the attribute information to obtain collected data; as well as generating an image corresponding to the target object according to the collected data; The object model structure includes a plurality of objects and a plurality of attribute information corresponding to the plurality of objects, the attribute information respectively has a mapping relationship with the object and the task type, and the object includes one or more of an operating system, a database, a middleware, and an application program; Wherein, determining the attribute information corresponding to the target task type for the target object based on the object model structure includes: Based on the object model structure, determining first sub-attribute information for the target object; Determining second sub-attribute information corresponding to the target task type; and The third sub-attribute information is determined according to a matching result between the first sub-attribute information and the second sub-attribute information.

2. The method according to claim 1, wherein: The step of generating an image corresponding to the target object according to the collected data comprises: Retrieving the parsing rules for the target object, parsing the collected data to obtain parsing results; and An image corresponding to the target object is generated according to the analysis result.

3. The method according to claim 1, further comprising: In response to receiving a page display request from a user, determining a target object corresponding to the page display request; Determining a rendering control according to an image corresponding to the target object; Render the view to be rendered according to the rendering control to obtain a target page; as well as The target page is displayed to the user.

4. The method according to claim 1, wherein: The object model structure includes an object model table and a collection script table; The object model table is used to store the multiple objects and the multiple attribute information respectively corresponding to the multiple objects, and the acquisition script table is used to store the multiple scripts respectively corresponding to the multiple attribute information.

5. A data acquisition device, comprising: A receiving module, configured to, in response to receiving a data collection request, determine a target object and a target task type corresponding to the data collection request; A determination module, configured to determine, for the target object, attribute information corresponding to the target task type based on an object model structure; A collection module, used to call a script corresponding to the attribute information to obtain collected data; as well as A generating module, used for generating an image corresponding to the target object according to the collected data; The object model structure includes a plurality of objects and a plurality of attribute information corresponding to the plurality of objects, the attribute information respectively has a mapping relationship with the object and the task type, and the object includes one or more of an operating system, a database, a middleware, and an application program; The determining module comprises: A first determination submodule, configured to determine first sub-attribute information for the target object based on the object model structure; A second determination submodule, configured to determine second sub-attribute information corresponding to the target task type; and The third determination submodule is configured to determine third sub-attribute information according to a matching result between the first sub-attribute information and the second sub-attribute information.

6. An electronic device comprising: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors are enabled to execute the method according to any one of claims 1 to 4.

7. A computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, causes the processor to execute the method according to any one of claims 1 to 4.

8. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

Images