CN115033634A - Data acquisition method, data acquisition device, electronic equipment and medium - Google Patents
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Abstract
The disclosure provides a data acquisition method, a data acquisition device, data acquisition equipment, a storage medium and a program product, relates to the technical field of computers, and can be applied to the technical field of finance. The method comprises the following steps: in response to receiving a data collection request, determining a target object and a target task type corresponding to the data collection request; determining attribute information corresponding to the target task type aiming at the target object based on the object model structure; calling a script corresponding to the attribute information to obtain collected data; generating an image corresponding to the target object according to the acquired data; the object model structure comprises a plurality of objects and a plurality of attribute information respectively corresponding to the objects, the attribute information respectively has a mapping relation with the objects and the task types, and the objects comprise one or more of an operating system, a database, middleware and an application program.
Description
Technical Field
The present disclosure relates to the field of computer technology, and may be applied to the field of financial technology, and more particularly, to a data acquisition method, apparatus, device, medium, and program product.
Background
At present, when an enterprise uses an operation and maintenance system, an operation and maintenance object model is manually added on a page firstly, and then a corresponding script is written according to the defined object model. And collecting and analyzing data to obtain an analysis result, and storing the analysis result into a database for management or use.
However, such manual configuration requires a lot of time and is prone to errors. In addition, the object model is input by a user, related programs of data acquisition and processing scripts are compiled according to the added object model and are completed by a back-end programmer, communication obstacles exist on the model, the problem that the object model and actual object data are inconsistent due to the understanding difference of the model, and system problems are easily caused.
Disclosure of Invention
In view of the above, the present disclosure provides a data collection method, apparatus, device, medium, and program product, which can make the result of attribute information and collected data correspondingly consistent, avoid the problem of inconsistency between the object model and the actual object data, and have the advantages of automation, intelligence, and high accuracy of collected data.
According to a first aspect of the present disclosure, there is provided a data acquisition 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; determining attribute information corresponding to the target task type for the target object based on an object model structure; calling a script corresponding to the attribute information to obtain collected data; generating an image corresponding to the target object according to the acquired data; the object model structure comprises a plurality of objects and a plurality of attribute information respectively corresponding to the objects, the attribute information respectively has a mapping relation with the objects and the task types, and the objects comprise one or more of an operating system, a database, middleware and an application program.
According to an embodiment of the present disclosure, the determining, for the target object, attribute information corresponding to the target task type based on the object model structure includes: determining first sub-attribute information for the target object based on an object model structure; determining second sub-attribute information corresponding to the target task type; and determining third sub-attribute information according to the matching result of the first sub-attribute information and the second sub-attribute information.
According to an embodiment of the present disclosure, the generating an image corresponding to the target object according to the acquired data includes: calling an analysis rule aiming at the target object, and analyzing the acquired data to obtain an analysis result; and generating an image corresponding to the target object according to the analysis result.
According to an embodiment of the present disclosure, the data acquisition method further 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 according to the image corresponding to the target object; rendering the view to be rendered according to the rendering control to obtain a target page; and displaying the target page to a user.
According to an embodiment of the present disclosure, the object model structure includes an object model table and an acquisition script table; the object model table is used for storing the plurality of objects and a plurality of attribute information respectively corresponding to the plurality of objects, and the collection script table is used for storing a plurality of scripts respectively corresponding to the plurality of attribute information.
A second aspect of the present disclosure provides a data acquisition apparatus comprising: the receiving module is used for responding to the received data acquisition request, and determining a target object and a target task type corresponding to the data acquisition request; a determining module, configured to determine, for the target object, attribute information corresponding to the target task type based on an object model structure; the acquisition module is used for calling the script corresponding to the attribute information to obtain acquired data; the generation module is used for generating an image corresponding to the target object according to the acquired data; the object model structure comprises a plurality of objects and a plurality of attribute information respectively corresponding to the objects, the attribute information respectively has a mapping relation with the objects and the task types, and the objects comprise one or more of an operating system, a database, middleware and an application program.
A third aspect of the present disclosure provides an electronic device, comprising: one or more processors; a memory for storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the data acquisition method described above.
A fourth aspect of the present disclosure also provides a computer-readable storage medium having stored thereon executable instructions that, when executed by a processor, cause the processor to perform the above-described data acquisition method.
A fifth aspect of the present disclosure also provides a computer program product comprising a computer program which, when executed by a processor, implements the above-described data acquisition method.
The data acquisition method provided by the embodiment can enable the attribute information and the result of the acquired data to be correspondingly consistent, avoids the problem that the data of the object model is inconsistent with the data of the actual object, and has the advantages of automation, intellectualization and high accuracy of the acquired data.
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The foregoing and other objects, features and advantages of the disclosure will be apparent from the following description of embodiments of the disclosure, which proceeds with reference to the accompanying drawings, in which:
FIG. 1 schematically illustrates an application scenario diagram of a data acquisition method, apparatus, device, medium, and program product according to embodiments of the disclosure;
FIG. 2 schematically illustrates a flow chart of a data acquisition method according to an embodiment of the present disclosure;
FIG. 3 schematically shows an execution diagram of a presentation target page according to an embodiment of the present disclosure;
FIG. 4 schematically illustrates a flowchart for determining a second target virtual machine device according to an embodiment of the present disclosure;
FIG. 5 schematically illustrates a flow chart of a method of data acquisition according to another embodiment of the present disclosure; and
FIG. 6 schematically illustrates a block diagram of an electronic device suitable for implementing a data collection method in accordance with an embodiment of the disclosure.
Detailed Description
Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood that the description is illustrative only and is not intended to limit the scope of the present disclosure. In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present disclosure.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The terms "comprises," "comprising," and the like, as used herein, specify the presence of stated features, steps, operations, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, or components.
All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs, unless otherwise defined. It is noted that the terms used herein should be interpreted as having a meaning that is consistent with the context of this specification and should not be interpreted in an idealized or overly formal sense.
Where a convention analogous to "at least one of A, B and C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B and C" would include but not be limited to systems that have a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.).
The embodiment of the disclosure provides a data acquisition method and a data acquisition device, wherein a target object and a target task type corresponding to a data acquisition request are determined in response to the data acquisition request; determining attribute information corresponding to the target task type aiming at the target object based on the object model structure; calling a script corresponding to the attribute information to obtain collected data; generating an image corresponding to the target object according to the acquired data; the object model structure comprises a plurality of objects and a plurality of attribute information respectively corresponding to the objects, the attribute information respectively has a mapping relation with the objects and the task types, and the objects comprise one or more of an operating system, a database, middleware and an application program.
Fig. 1 schematically illustrates an application scenario diagram of a data acquisition method, apparatus, device, medium, and program product according to embodiments of the present disclosure.
As shown in fig. 1, 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 serves as a medium for providing communication links between the terminal devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The user may use the terminal devices 101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. The terminal devices 101, 102, 103 may have installed thereon various communication client applications, such as shopping applications, web browser applications, search applications, instant messaging tools, mailbox clients, social platform software, etc. (by way of example only).
The terminal devices 101, 102, 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 105 may be a server providing various services, such as a background management server (for example only) providing support for websites browsed by users using the terminal devices 101, 102, 103. The background management server may analyze and perform other processing on the received data such as the user request, and feed back a processing result (e.g., a webpage, information, or data obtained or generated according to the user request) to the terminal device.
It should be noted that the data collection method provided by the embodiment of the present disclosure may be generally executed by the server 105. Accordingly, the data acquisition device provided by the embodiments of the present disclosure may be generally disposed in the server 105. The data collection method provided by the embodiment of the present disclosure may also be executed by a server or a server cluster that is different from the server 105 and is capable of communicating with the terminal devices 101, 102, 103 and/or the server 105. Correspondingly, the data acquisition device provided by the embodiment of the present disclosure may also be disposed in a server or a server cluster different from the server 105 and capable of communicating with the terminal devices 101, 102, 103 and/or the server 105.
It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
The data acquisition method of the disclosed embodiment will be described in detail below with reference to fig. 2 based on the scenario depicted in fig. 1.
Fig. 2 schematically shows a flow chart of a data acquisition method according to an embodiment of the present disclosure.
As shown in fig. 2, the embodiment includes operations S210 to S240, and the data collection method may be performed by a server.
In the technical scheme of the disclosure, the data acquisition, collection, storage, use, processing, transmission, provision, disclosure, application and other processing are all in accordance with the regulations of relevant laws and regulations, necessary security measures are taken, and the public order and good custom are not violated.
In operation S210, in response to receiving the collection data request, a target object and a target task type corresponding to the collection data request are determined.
In operation S220, attribute information corresponding to the target task type is determined for the target object based on the object model structure.
The object model structure comprises a plurality of objects and a plurality of attribute information respectively corresponding to the objects, the attribute information respectively has mapping relations with the objects and the task types, and the objects comprise one or more of an operating system, a database, middleware and an application program.
In operation S230, a script corresponding to the attribute information is called to obtain the collected data.
In operation S240, an image corresponding to the target object is generated from the acquired data.
The object may be an operation and maintenance object, such as an operating system, a database, middleware, an application, and the like. The operation and maintenance object can also be as follows: 1) the infrastructure part of the environment of a certain computer room can be network communication, power resources, environment resources and the like which are necessary for ensuring the normal operation of equipment managed by a data center; 2) various devices applied in the process of providing the IT service, such as hardware resources of storage, servers, network devices, safety devices and the like; 3) may be systems and data such as software resources like operating systems, databases, middleware, applications, etc.; the data can also be various data such as service data, configuration files, logs and the like; 4) can be management tools such as infrastructure monitoring software, a workflow management platform, a report platform, a short message platform and the like.
The tasks may be set and adjusted according to actual requirements, such as a test task, a stability detection task, a performance optimization task, a capacity expansion task, a migration task, and so on.
The attribute information may represent an object model, may be defined for each attribute of an object, and may include information such as an attribute field name and a chinese meaning. Such as operating systems, middleware, switches, kylin systems, etc.
If the configuration is manually received in data acquisition, a large amount of time is easily consumed, and errors are easily caused. The collection and processing of general data depend on the entered attribute information, and if a data collection and processing script is determined only according to the attribute information added by a user, the actually collected data are easy to deviate from the actual attribute information. If the data acquisition and the attribute information are put together and maintained together, the data acquired actually corresponds to the actual attribute information, and the consistency is realized. For example, a script process may be employed 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 collecting the data. And after uploading the script, extracting information such as attribute information, objects and the like, and storing the information into a database. The script content may also be stored in a database for use in collecting data.
With respect to the object model structure, i.e., the object model database, it should be noted that the object model structure is mainly used for storing attribute information corresponding to an object. For example, in response to receiving the uploaded script, the script is analyzed, and the attributes and corresponding meanings of each field of the annotation content are extracted and stored in the database after being unified. The script file can also be stored in a database for unified processing. The script file may be a script written in a convention specification. The information contained in the script is not script execution content, and is added in a mode of annotation, so that the attribute information and the object data collected by the execution script have consistency.
For example, the acquisition task, i.e. the acquisition data request, may be triggered by a manual click, a timed task, or an automatic change trigger. After receiving the data acquisition request, determining a target object corresponding to the data acquisition request and a target task type; for example, the target object is middleware a, and the task type is a test task b.
The object structure includes a plurality of objects, and objects stored in the object structure in accordance with the target object may be determined first. In the object structure, the object corresponds to a plurality of attribute information. The attribute information respectively has mapping relations with the object and the task type, so that the attribute information corresponding to the target task type is determined for the target object. Then, a script (execution script) corresponding to the attribute information is called, and after the execution script is obtained, the execution script is sent to a remote target machine to be executed, and a result returned by the script collection is waited, so that the collected data is obtained. And furthermore, a data chart can be generated and an image can be drawn by utilizing the collected data. And storing a plurality of images corresponding to the target object for unified management, such as generating a visual platform and providing a basis for image display.
In the data acquisition method provided by this embodiment, attribute information corresponding to a target task type is determined for a target object based on an object model structure; calling a script corresponding to the attribute information to obtain collected data; the attribute information and the result of the collected data are correspondingly consistent, the problem that the data of the object model is inconsistent with the data of the actual object is avoided, and the method has the advantages of automation, intellectualization and high accuracy of the collected data.
Determining attribute information corresponding to a target task type for a target object based on an 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 according to the matching result of the first sub-attribute information and the second sub-attribute information.
For example, the object model structure includes object a, object b, object c, object d, ·, object y, object z. The attribute information corresponding to the object a includes attribute 1, attribute 2, …, and attribute 9; the attribute information corresponding to the object b includes attribute 10, attribute 11, …, and attribute 15; the attribute information corresponding to the object c includes an attribute 16, an attribute 17, ·, an attribute 31; … (e.g., attributes corresponding to object y include attributes 107, 108,. and 123; e.g., attribute information corresponding to object z includes attributes 124, 125, …, and 150). Each attribute. The attribute information and the task type have a mapping relation, for example, the attribute information corresponding to the task b (such as a test task) comprises attributes 1, 7, 9, 21 and 31; the attribute information corresponding to the task c includes attributes 5, 6, 32, 111, and the like.
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). A first sub-attribute information result, such as attribute 1, attribute 2,. and attribute 9, may be determined based on the object model structure according to the convention described above; then determining a second sub-attribute information result, such as attributes 1, 7, 9, 21 and 31; and matching the attribute information according to the first sub-attribute information and the second sub-attribute information, and determining third attribute information, such as attributes 1, 7 and 9. Thus, when the execution script is subsequently called, scripts corresponding to the attributes 1, 7, and 9 are called.
The data acquisition method provided by this embodiment may 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 acquired actual data is matched with the actual object and has consistency.
Generating an image corresponding to the target object from the acquired data, comprising: calling an analysis rule for the target object, and analyzing the acquired data to obtain an analysis result; and generating an image corresponding to the target object according to the analysis result.
For example, the data parsing rule is configured for each object, and data may be extracted from a predetermined format, for example, by using a regular expression, an extended markup language, a json data parsing rule, or the like.
Through analysis of the collected data, information hidden behind the disordered collected data can be extracted, and a conclusion helpful for the business can be formed according to the extracted key information. Meanwhile, the processing and arrangement of the analysis result, such as drawing of chart images, are beneficial to providing a foundation for data visualization.
In the data acquisition method provided by this embodiment, the analysis rule for the target object is called, and the acquired data is analyzed to obtain an analysis result; and generating an image corresponding to the target object according to the analysis result, thereby bringing convenience to intelligent data acquisition and display.
The data acquisition method further comprises the following steps: 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 the image corresponding to the target object; rendering the view to be rendered according to the rendering control to obtain a target page; and presenting the target page to the user.
Fig. 3 schematically shows an execution diagram of a presentation target page according to an embodiment of the present disclosure, see fig. 3. First, a user sends a page presentation request through the client 310. The server 320 responds to receiving the page show request and relays the request to the data collection device 330. The data acquisition device 330 may determine, in response to receiving the request, a target object corresponding to the page display request; then, an image database storing images corresponding to a plurality of objects is searched, and an image corresponding to a target object, for example, an image having the smallest time difference from the time stamps is determined. Then, a rendering control for rendering a blank view (view to be rendered) may be determined based on the image with the minimum time difference, and the view to be rendered may be rendered to obtain a target page. The data collection device 330 may send the target page to the client 310, i.e., temporarily target the page to the user.
For the rendering control, it should be noted that the rendering control may be a native rendering control in an operating system, such as a Surface View control, a UI View control, and the like. But also application engines such as Uniy engines, Cocos engines, etc. The identifier corresponding to the target object can be transmitted 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.
Fig. 4 schematically shows a flowchart for determining a second target virtual machine device according to an embodiment of the present disclosure.
As shown in fig. 4, this embodiment includes operations S401 to S408.
In operation S401, a plurality of collected data is stored to a database.
In operation S402, an analysis rule for the target object is called, the collected data in the database is analyzed, and a corresponding analysis result is stored.
In operation S403, an image corresponding to the target object is generated according to the analysis result.
In operation S404, a message from the user is listened to, such as a page display request received from the user.
In operation S405, in response to receiving a page presentation request from a user, a target object corresponding to the page presentation request is determined.
In operation S406, the target object is matched, and an image corresponding to the target object is determined, thereby determining a rendering control.
In operation S407, the view to be rendered is rendered by using the determined rendering control, so as to obtain a target page.
In operation S408, the destination page is transmitted to the user, and the destination page is presented.
In the data acquisition method provided by the embodiment, a target object corresponding to a page display request is determined in response to receiving the page display request from a user; determining a rendering control according to the image corresponding to the target object; rendering the view to be rendered according to the rendering control to obtain a target page; and the target page is displayed to the user, so that data visualization is realized.
The object model structure comprises an object model table and an acquisition script table; the object model table is used for storing a plurality of objects and a plurality of attribute information respectively corresponding to the objects, and the acquisition script table is used for storing a plurality of scripts respectively corresponding to the attribute information.
The object model structure may be cooperatively maintained by an object model table and an acquisition script table. The object model table may be configured to store a plurality of objects and a plurality of attribute information corresponding to the plurality of objects, respectively, and the collection script table may be configured to store a plurality of scripts corresponding to the plurality of attribute information, respectively.
The data acquisition method provided by the embodiment maintains the execution script and the attribute information by using the object model table and the acquisition script table, is favorable for reducing the cost of maintaining complex data, and realizes simple and efficient operations of modifying, adding or deleting the script and the attribute information.
Based on the data acquisition method, the disclosure also provides a data acquisition device. The apparatus will be described in detail below with reference to fig. 5.
Fig. 5 schematically shows a block diagram of a data acquisition device according to an embodiment of the present disclosure.
As shown in fig. 5, the data acquisition apparatus 500 of this embodiment includes a receiving module 510, a determining module 520, an acquiring module 530, and a generating module 540.
A receiving module 510, configured to, in response to receiving a data acquisition request, determine a target object and a target task type corresponding to the data acquisition request; a determining module 520, configured to determine, for the target object, attribute information corresponding to the target task type based on an object model structure; the acquisition module 530 is used for calling the script corresponding to the attribute information to obtain acquired data; and a generating module 540, configured to generate an image corresponding to the target object according to the acquired data; the object model structure comprises a plurality of objects and a plurality of attribute information respectively corresponding to the objects, the attribute information respectively has a mapping relation with the objects and the task types, and the objects comprise one or more of an operating system, a database, middleware and an application program.
In some embodiments, the determining module comprises: a first determining submodule, configured to determine first sub-attribute information for the target object based on an object model structure; the second determining submodule is used for determining second sub-attribute information corresponding to the target task type; and a third determining submodule, configured to determine third sub-attribute information according to a matching result of the first sub-attribute information and the second sub-attribute information.
In some embodiments, the generating module comprises: the data analysis submodule is used for calling an analysis rule aiming at the target object and analyzing the acquired data to obtain an analysis result; and an image generation sub-module which generates an image corresponding to the target object according to the analysis result.
In some embodiments, the apparatus further comprises: the fourth determining submodule is used for responding to a page display request received from a user and determining a target object corresponding to the page display request; a fifth determining submodule, configured to determine a rendering control according to the image corresponding to the target object; the rendering module renders the view to be rendered according to the rendering control to obtain a target page; and the display module is used for displaying the target page to a user.
In some embodiments, the object model structure includes an object model table and an acquisition script table; the object model table is used for storing a plurality of objects and a plurality of attribute information respectively corresponding to the objects, and the acquisition script table is used for storing a plurality of scripts respectively corresponding to the attribute information.
According to an embodiment of the present disclosure, any plurality of the receiving module 510, the determining module 520, the collecting module 530 and the generating module 540 may be combined into one module to be implemented, or any one of the modules may be split into a plurality of modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality 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 acquiring module 530, and the generating module 540 may be implemented at least partially 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 may be implemented in hardware or firmware in any other reasonable manner of integrating or packaging a circuit, or in any one of three implementations of software, hardware, and firmware, or in a suitable combination of any of them. Alternatively, at least one of the receiving module 510, the determining module 520, the acquiring module 530 and the generating module 540 may be at least partially implemented as a computer program module, which when executed may perform the respective functions.
Fig. 6 schematically shows a block diagram of an electronic device suitable for implementing a data acquisition method according to an embodiment of the present disclosure.
As shown in fig. 6, an 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 section 608 into a Random Access Memory (RAM) 603. Processor 601 may include, for example, a general purpose microprocessor (e.g., a CPU), an instruction set processor and/or associated chipset, and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), among others. The processor 601 may also include onboard memory for caching purposes. Processor 601 may include a single processing unit or multiple processing units for performing different actions of a method flow according to embodiments of the disclosure.
In the RAM 603, various programs and data necessary for the operation of the electronic apparatus 600 are stored. The processor 601, the ROM602, and the RAM 603 are connected to each other via a bus 604. The processor 601 performs various operations of the method flows according to the embodiments of the present disclosure by executing programs in the ROM602 and/or RAM 603. It is to be noted that the programs may also be stored in one or more memories other than the ROM602 and RAM 603. The processor 601 may also perform various operations of the method flows according to embodiments of the present disclosure by executing programs stored in the one or more memories.
The present disclosure also provides a computer-readable storage medium, which may be contained in the apparatus/device/system described in the above embodiments; or may exist separately and not be assembled into the device/apparatus/system. The computer-readable storage medium carries one or more programs which, when executed, implement a method according to an embodiment of the disclosure.
According to embodiments of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, which may include, for example but is not limited to: a portable computer diskette, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. For example, according to an embodiment of the present disclosure, a computer-readable storage medium may include ROM602 and/or RAM 603 and/or one or more memories other than ROM602 and RAM 603 described above.
Embodiments of the present disclosure also include a computer program product comprising a computer program containing program code for performing the method illustrated in the flow chart. When the computer program product runs in a computer system, the program code is used for causing the computer system to realize the data acquisition method provided by the embodiment of the disclosure.
The computer program performs the above-described functions defined in the system/apparatus of the embodiments of the present disclosure when executed by the processor 601. The systems, apparatuses, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the present disclosure.
In one embodiment, the computer program may be hosted on a tangible storage medium such as an optical storage device, a magnetic storage device, and the like. In another embodiment, the computer program may also be transmitted, distributed in the form of a signal on a network medium, downloaded and installed through the communication section 609, and/or installed from the removable medium 611. The computer program containing program code may be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.
In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 609, and/or installed from the removable medium 611. The computer program, when executed by the processor 601, performs the above-described functions defined in the system of the embodiments of the present disclosure. The above described systems, devices, apparatuses, modules, units, etc. may be implemented by computer program modules according to embodiments of the present disclosure.
In accordance with embodiments of the present disclosure, program code for executing computer programs provided by embodiments of the present disclosure may be written in any combination of one or more programming languages, and in particular, these computer programs may be implemented using high level procedural and/or object oriented programming languages, and/or assembly/machine languages. The programming language includes, but is not limited to, programming languages such as Java, C + +, python, the "C" language, or the like. The program code may execute entirely on the user computing device, partly on the user device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Those skilled in the art will appreciate that various combinations and/or combinations of features recited in the various embodiments and/or claims of the present disclosure can be made, even if such combinations or combinations are not expressly recited in the present disclosure. In particular, various combinations and/or combinations of the features recited in the various embodiments and/or claims of the present disclosure may be made without departing from the spirit or teaching of the present disclosure. All such combinations and/or associations are within the scope of the present disclosure.
The embodiments of the present disclosure have been described above. However, these examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments are described separately above, this does not mean that the measures in the embodiments cannot be used advantageously in combination. The scope of the disclosure is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be devised by those skilled in the art without departing from the scope of the present disclosure, and such alternatives and modifications are intended to be within the scope of the present disclosure.
Claims (10)
1. A method of data acquisition comprising:
in response to receiving a data collection request, determining a target object and a target task type corresponding to the data collection request;
determining attribute information corresponding to the target task type for the target object based on an object model structure;
calling a script corresponding to the attribute information to obtain collected data; and
generating an image corresponding to the target object according to the acquired data;
the object model structure comprises a plurality of objects and a plurality of attribute information respectively corresponding to the objects, the attribute information respectively has a mapping relation with the objects and the task types, and the objects comprise one or more of an operating system, a database, middleware and an application program.
2. The method of claim 1, wherein the determining, based on an object model structure, attribute information corresponding to the target task type for the target object comprises:
determining first sub-attribute information for the target object based on an object model structure;
determining second sub-attribute information corresponding to the target task type; and
and determining third sub-attribute information according to the matching result of the first sub-attribute information and the second sub-attribute information.
3. The method of claim 1, wherein the generating an image corresponding to the target object from the acquisition data comprises:
calling an analysis rule aiming at the target object, and analyzing the acquired data to obtain an analysis result; and
and generating an image corresponding to the target object according to the analysis result.
4. The method of 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 the image corresponding to the target object;
rendering the view to be rendered according to the rendering control to obtain a target page; and
and displaying the target page to a user.
5. The method of claim 1, wherein the object model structure comprises an object model table and an acquisition script table;
the object model table is used for storing the plurality of objects and a plurality of attribute information respectively corresponding to the plurality of objects, and the collection script table is used for storing a plurality of scripts respectively corresponding to the plurality of attribute information.
6. A data acquisition device comprising:
the receiving module is used for responding to the received data acquisition request, and determining a target object and a target task type corresponding to the data acquisition request;
a determining module, configured to determine, for the target object, attribute information corresponding to the target task type based on an object model structure;
the acquisition module is used for calling the script corresponding to the attribute information to obtain acquired data; and
the generation module is used for generating an image corresponding to the target object according to the acquired data;
the object model structure comprises a plurality of objects and a plurality of attribute information respectively corresponding to the objects, the attribute information respectively has a mapping relation with the objects and the task types, and the objects comprise one or more of an operating system, a database, middleware and an application program.
7. The apparatus of claim 6, wherein the means for determining comprises:
a first determining submodule, configured to determine first sub-attribute information for the target object based on an object model structure;
the second determining submodule is used for determining second sub-attribute information corresponding to the target task type; and
and the third determining submodule is used for determining third sub-attribute information according to the matching result of the first sub-attribute information and the second sub-attribute information.
8. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs,
wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the method of any of claims 1-5.
9. A computer readable storage medium having stored thereon executable instructions which, when executed by a processor, cause the processor to perform the method of any one of claims 1 to 5.
10. A computer program product comprising a computer program which, when executed by a processor, implements a method according to any one of claims 1 to 5.
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