CN113835893A - Data processing method, device, equipment, storage medium and program product - Google Patents
Data processing method, device, equipment, storage medium and program product Download PDFInfo
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Abstract
The present disclosure provides a data processing method, apparatus, device, storage medium, and program product, which relate to the field of artificial intelligence, and in particular, to the fields of intelligent transportation, big data, cloud computing, software testing, and the like. The specific implementation scheme is as follows: by presetting a plurality of data processing scenes and data processing logics corresponding to each data processing scene, different data processing scenes correspond to different software performance data processing requirements, and the corresponding data processing logics are different. Responding to a request for processing data of a target scene to the application software, and acquiring a tracking file of the application software; converting the contents of the trace file into structured data; according to the structured data, the data processing logic corresponding to the target scene is executed to obtain a data processing result, the data processing result is output, and the customized data processing of various software performance data processing scenes can be automatically realized according to the tracking file, so that the processing efficiency of the software performance data is improved.
Description
Technical Field
The present disclosure relates to the fields of intelligent transportation, big data, cloud computing, software testing, and the like in artificial intelligence, and in particular, to a method, an apparatus, a device, a storage medium, and a program product for data processing.
Background
The performance consumption of the application software is one of important indexes for pushing the application software to a client for use, and for the vehicle-mounted application software, due to the fact that hardware of the vehicle-mounted application software is slow in updating iteration and high in upgrading cost, the performance of the vehicle-mounted application software is accurately and efficiently analyzed and tested, and the vehicle-mounted application software is of great importance for improving the overall performance of the vehicle-mounted application software.
At present, manual analysis is carried out on a tracking file operated by application software to determine modules with more performance consumption or stuck in the application software, so that the process is very complicated and the efficiency is very low.
Disclosure of Invention
The present disclosure provides a method, apparatus, device, storage medium, and program product for data processing.
According to a first aspect of the present disclosure, there is provided a method of data processing, comprising:
responding to a request for processing data of a target scene to application software, and acquiring a tracking file of the application software;
converting the contents of the tracking file into structured data;
executing data processing logic corresponding to the target scene according to the structured data to obtain a data processing result;
and outputting the data processing result.
According to a second aspect of the present disclosure, there is provided an apparatus for data processing, comprising:
the tracking file acquisition module is used for responding to a request for carrying out data processing on a target scene on the application software and acquiring a tracking file of the application software;
the data conversion module is used for converting the content of the tracking file into structured data;
the data processing module is used for executing data processing logic corresponding to the target scene according to the structured data to obtain a data processing result;
and the result output module is used for outputting the data processing result.
According to a third aspect of the present disclosure, there is provided an electronic device comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of the first aspect.
According to a fourth aspect of the present disclosure, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of the first aspect.
According to a fifth aspect of the present disclosure, there is provided a computer program product comprising: a computer program, stored in a readable storage medium, from which at least one processor of an electronic device can read the computer program, execution of the computer program by the at least one processor causing the electronic device to perform the method of the first aspect.
The technology according to the present disclosure solves the problem of improving the efficiency of software performance data processing.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
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The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
FIG. 1 is an exemplary diagram of a trace file opened by a browser provided by the present disclosure;
FIG. 2 is a flow chart of a method of data processing provided by a first embodiment of the present disclosure;
FIG. 3 is a flow chart of a method of data processing provided by a second embodiment of the present disclosure;
FIG. 4 is a block diagram of an example of a method of data processing provided by the present disclosure;
fig. 5 is a schematic diagram of a data processing apparatus according to a third embodiment of the disclosure;
fig. 6 is a schematic diagram of a data processing apparatus according to a fourth embodiment of the disclosure;
FIG. 7 is a block diagram of an electronic device for implementing a method of data processing of an embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
The performance consumption of the application software is one of important indexes for pushing the application software to a client for use, and for the vehicle-mounted application software, due to the fact that hardware of the vehicle-mounted application software is slow in updating iteration and high in upgrading cost, the performance of the vehicle-mounted application software is accurately and efficiently analyzed and tested, and the vehicle-mounted application software is of great importance for improving the overall performance of the vehicle-mounted application software.
At present, the performance consumed by each module in the application software can be determined by acquiring a trace file, namely a trace file, of the application software, opening the trace file by using a browser, and manually checking and analyzing the trace file. However, the trace file records information consumed by the performance of each module, and the content is various and very complex, as shown in fig. 1, fig. 1 shows an example of a trace file opened by a browser, the content of the trace file is various and is not described in detail, a novice developer may not understand the trace file, and even though the developer familiar with the trace file, the process of manually analyzing the trace file is very complicated and inefficient.
The present disclosure provides a data processing method, apparatus, device, storage medium, and program product, which are applied to the fields of intelligent transportation, big data, cloud computing, software testing, etc. in the field of artificial intelligence, so as to improve the efficiency and accuracy of software performance data processing.
According to the data processing method provided by the disclosure, a plurality of data processing scenes and data processing logics corresponding to each data processing scene are preset, different data processing scenes correspond to different software performance data processing requirement scenes, and the corresponding data processing logics are different. Acquiring a tracking file of application software; converting the contents of the trace file into structured data; according to the structured data, the data processing logic corresponding to the target scene is executed, the data processing result is obtained, the data processing result is output, customized data processing of various software performance data processing scenes can be automatically realized according to the tracking file, and the efficiency of software performance data processing is improved.
Fig. 2 is a flowchart of a data processing method according to a first embodiment of the disclosure. The data processing method provided in this embodiment may be specifically applied to an electronic device for performing software performance data processing, where the electronic device may be a terminal device such as a smart phone and a tablet computer, or a server, and may also be other electronic devices in other embodiments, and this embodiment is not specifically limited herein.
As shown in fig. 2, the method comprises the following specific steps:
step S201, in response to a request for performing data processing of a target scene on the application software, acquiring a trace file of the application software.
The application software refers to target software to be subjected to performance data processing. The application software may be application software deployed on any device, such as an application software on a vehicle machine, an application software on a mobile terminal, and the like.
In this embodiment, the target scenario refers to a data processing scenario for performing performance data processing on the application software according to a specified performance data processing requirement. For different performance data processing requirements, the data processing scenarios corresponding to the performance data processing requirements are different.
For example, in connection with an actual application scenario of the application software, at least one of the following data processing scenarios may be set: scene 1: modules with high performance consumption are determined. Scene 2: a module with low performance consumption is determined. Scene 3: the performance differences between the same modules in two different versions of the application software are compared.
In addition, other data processing scenarios may also be set, for example, scenario 4: and sequencing the modules according to the performance consumption. Scene 5: and outputting the value of the performance consumption index specified by each module, wherein the specified performance consumption index can be an index concerned by developers and can be set as required. Scene 6: and outputting the index with the highest performance consumption of each module. Scene 7: and randomly searching the performance consumption of each module and sequencing. The setting of the data processing scenario may be set and adjusted in combination with an actual application scenario of the application software, and is not specifically limited herein.
In this embodiment, in order to perform performance data processing on a target scene for application software, a trace file of the application software is first obtained, where the trace file records performance consumption information of a plurality of modules in the application software.
Usually, the trace file of the application software is stored on the device where the application software is located, and the trace file of the application software can be obtained from the device where the application software is located.
Step S202, converting the content of the tracking file into structured data.
After the trace file of the application software is acquired, the content of the trace file can be automatically converted into structured data, and automatic data analysis processing can be performed based on the structured data.
Illustratively, the Structured data may be Structured Query Language (SQL) based data, abbreviated SQL data. SQL data can be stored in a database, and automatic data analysis can be realized through operations such as query and statistics of the database.
And S203, executing data processing logic corresponding to the target scene according to the structured data to obtain a data processing result.
After the content of the tracking file is converted into the structured data, the structured data is analyzed and processed by executing the data processing logic corresponding to the target scene, so that a data processing result corresponding to the target scene, namely a data processing result meeting the performance data processing requirement of the target scene, is obtained.
And step S204, outputting a data processing result.
And after the data processing result is obtained, outputting the data processing result in a specified mode.
Illustratively, the data processing result can be displayed through a front page, or the data processing result is sent to a specified device and displayed by the specified device.
The designated mode of the output data processing result may be set and adjusted according to the needs of the actual application scenario, and this embodiment is not specifically limited here.
According to the embodiment of the application, a plurality of data processing scenes and data processing logics corresponding to the data processing scenes are preset, different data processing scenes correspond to different software performance data processing requirements, and the corresponding data processing logics are different. Responding to a request for processing data of a target scene to the application software, and acquiring a tracking file of the application software; converting the contents of the trace file into structured data; according to the structured data, the data processing logic corresponding to the target scene is executed to obtain a data processing result, the data processing result is output, and the customized data processing of various software performance data processing scenes can be automatically realized according to the tracking file, so that the processing efficiency of the software performance data is improved.
Fig. 3 is a flowchart of a data processing method according to a second embodiment of the disclosure. On the basis of the first embodiment described above,
in this embodiment, a plurality of preset data processing scenarios and a data processing logic corresponding to each data processing scenario are configured in advance, different data processing scenarios correspond to different software performance data processing requirements, and corresponding data processing logics are different.
Optionally, executing a data processing logic corresponding to the target scene according to the structured data, and acquiring the data processing logic corresponding to at least one data processing scene before obtaining a data processing result; the data processing logic corresponding to each data processing scene is independently deployed in the corresponding container, so that data isolation among the data processing logics corresponding to different data processing scenes is realized, and the stability of data processing is improved.
Optionally, the data processing logic corresponding to the data processing scenario is updated in response to a modification operation on the data processing logic corresponding to any data processing scenario, and when the performance data processing requirement is changed, the data processing logic can be updated, so that diversified performance data processing requirements are met.
As shown in fig. 3, the method comprises the following specific steps:
step S301, responding to a request for processing data of a target scene to the application software, and acquiring a tracking file of the application software.
The application software refers to target software to be subjected to performance data processing. The application software may be application software deployed on any device, such as an application software on a vehicle machine, an application software on a mobile terminal, and the like.
In this embodiment, the target scenario refers to a data processing scenario for performing performance data processing on the application software according to a specified performance data processing requirement. For different performance data processing requirements, the data processing scenarios corresponding to the performance data processing requirements are different.
For example, in connection with an actual application scenario of the application software, at least one of the following data processing scenarios may be set: scene 1: modules with high performance consumption are determined. Scene 2: a module with low performance consumption is determined. Scene 3: the performance differences between the same modules in two different versions of the application software are compared.
In addition, other data processing scenarios may also be set, for example, scenario 4: and sequencing the modules according to the performance consumption. The setting of the data processing scenario may be set and adjusted in combination with an actual application scenario of the application software, and is not specifically limited herein.
In this embodiment, in order to perform performance data processing on a target scene for application software, a trace file of the application software is first obtained, where the trace file records performance consumption information of a plurality of modules in the application software.
Usually, the trace file of the application software is stored on the device where the application software is located, and the trace file of the application software can be obtained from the device where the application software is located.
Step S302, converting the content of the tracking file into structured data.
After the trace file of the application software is acquired, the content of the trace file can be automatically converted into structured data, and automatic data analysis processing can be performed based on the structured data.
Alternatively, program modules capable of converting the contents of the trace file into structured data may also be acquired in advance, and this step may be implemented by running the corresponding program modules.
Optionally, after the content of the trace file is converted into the structured data, the structured data may be stored in the database, and then the data analysis processing on the structured data may be implemented through a query operation on the database.
Optionally, the step may be specifically implemented by the following method:
and taking the tracking file as input data of a specified application program interface, calling the specified application program through the specified application program interface, wherein the specified application program is used for converting the content of the tracking file into structured data and storing the structured data into a database.
Therefore, the tracking file can be automatically converted into the structured data, the structured data is stored in the database, and the structured data is provided for automatically processing the software performance data.
The designated application program is a program capable of converting the content of the trace file into structured data and storing the structured data in the database. The specified application program interface is a packaged interface program of the specified application program, and the specified application program can be called through the specified application program interface.
Illustratively, the specified application may be developed by a third-party platform that provides an external interface to the specified application (e.g., an interface in the SQL API for implementing similar functionality). The electronic device external to the third party platform may call the specified application program through the specified application program interface using the trace file as input data for the specified application program interface.
Illustratively, the Structured data may be Structured Query Language (SQL) based data, abbreviated SQL data. The SQL data can be stored in a database, and the automatic data analysis and processing of the structured data can be realized through operations such as query and statistics of the database.
In an optional implementation manner of this embodiment, the data processing logic may be implemented by a pre-developed program, and the program for implementing the data processing logic is referred to as a data analyzer, and the data analyzer includes the data processing logic. Illustratively, the data analyzer may be implemented in a script.
Illustratively, a data analyzer corresponding to at least one data processing scenario may be obtained; the data analyzers corresponding to each data processing scene are independently deployed in the corresponding containers, so that data isolation among different data analyzers is realized, and the stability of data processing is improved.
Optionally, the data analyzer corresponding to any data processing scenario is updated in response to a modification operation on the data analyzer corresponding to the data processing scenario, and when the performance data processing requirement is changed, the data analyzer can be updated, so that diversified performance data processing requirements are met.
When new performance data processing requirements exist, data processing logics with new performance data processing functions can be realized by adding data processing scenes and data analyzers corresponding to the data processing scenes, the data processing scenes can be conveniently expanded, the method and the device can be suitable for various performance data processing requirements, and the application scenes are wider.
After the content of the trace file is converted into the structured data, through steps S303 to S304, the data processing logic corresponding to the target scene is executed according to the structured data, and a data processing result is obtained.
Step S303, a data analyzer corresponding to the target scene is loaded, where the data analyzer includes data processing logic corresponding to the target scene.
In this step, according to the target scene, a data analyzer corresponding to the target scene is determined, and the data analyzer corresponding to the target scene is loaded into the memory.
And S304, executing a data analyzer corresponding to the target scene, and performing data processing on the structured data to obtain a data processing result.
Wherein, the data analyzer has defined the data processing logic for processing the performance data of the target scene.
And after the data analyzer corresponding to the target scene is loaded into the memory, performing data processing on the structured data according to data processing logic contained in the data analyzer by executing the data analyzer corresponding to the target scene to obtain a data processing result.
Optionally, the data processing logic may further include data structure information of the output result corresponding to the target scene. The step can be realized by the following method:
executing a data analyzer corresponding to the target scene, and performing data processing on the structured data to obtain a data result; and generating a data processing result according to the data structure information of the output result and the data result.
The data structure information of the output result comprises data items required to be contained by the output result according to the performance data processing requirement of the target scene, and the associated information and the arrangement sequence among the data items.
For example, for scenario 1: modules with high performance consumption are determined. The data processing logic corresponding to scenario 1 may be a module that screens out, according to the performance consumption index, that the performance consumption index is greater than or equal to the index threshold. The scene 1 corresponding data processing logic may further include data structure information of the output result as follows: outputting data items such as names of modules with high performance consumption, values of performance consumption indexes and the like; and sequentially outputting the information of each module with high performance consumption according to the sequencing of the high performance consumption to the low performance consumption.
Through the data structure information preset in the data processing logic, the data results obtained by data processing are integrated according to the set data structure information, the corresponding data processing structure is generated, the corresponding data processing results can be automatically obtained according to the data structure information of the output results corresponding to the target scene, the data processing results are more suitable for the requirement of the target scene, manual arrangement of the data results is not needed, and the data processing efficiency is improved.
Optionally, according to the structured data, the data analyzer corresponding to the target scene is concurrently executed by the multiple threads to obtain the data processing result, that is, the data processing logic corresponding to the target scene is concurrently executed by the multiple threads to obtain the data processing result, so that the efficiency of data processing can be further improved.
By sending the data analyzer into the thread pool, the data processing logic corresponding to the target scene is executed by the plurality of threads in the thread pool concurrently, and the efficiency of data processing can be further improved.
Step S305, generating a data report according to the data processing result and a report template corresponding to the target scene; and outputting a data report.
In this embodiment, a report template of each data processing scenario may be set according to the requirement of each data processing scenario, where the report template includes data items that need to be output, and at least one of the following data items in an output result: configuration information and format information.
After the data processing result is obtained, the data processing result comprises the data of the data items required in the report template, and the data of each data item is inserted into the corresponding position in the report template corresponding to the target scene to generate the data report. After the data report is generated, the data report may be output in a preset manner.
The data processing result is automatically output in a data report form according to the data report module, so that the data processing result is displayed in a structure convenient for reading, the data structure does not need to be manually arranged by related personnel, and the efficiency and the effect of data processing are improved.
Illustratively, the data report may be presented via a front-end page, or the data report may be sent to a designated device for presentation by the designated device.
The preset mode of outputting the data report may be set and adjusted according to the needs of the actual application scenario, and this embodiment is not specifically limited here.
It should be noted that, in this embodiment, the request for one data processing may include one or more target scenarios of the application software. If the request for data processing comprises a plurality of target scenes of the application software, after the trace file of the application software is obtained and the content of the trace file is converted into the structured data, the data processing logic corresponding to the plurality of target scenes can be executed in parallel in a multithreading mode, and the data processing result corresponding to each target scene is obtained. Currently, the data processing logic corresponding to a plurality of target scenes may also be executed in sequence to obtain a data processing result corresponding to each target scene.
Exemplarily, fig. 4 is a diagram of a framework example of a method for data processing provided by the present disclosure, and as shown in fig. 4, a device where an application software is located extracts performance data of the application software to generate a trace file of the application software. The electronic device for executing the data processing method acquires a trace file of application software, converts the trace file into SQL data by calling an SQL API, executes a data analyzer corresponding to a target scene, where data structure information of an output result is determined by data processing logic included in the data analyzer, and executes the data analyzer corresponding to the target scene in parallel by threads in a thread pool, so as to obtain a data processing result corresponding to each target scene, where fig. 4 exemplifies the data processing results of three target scenes 1, 2, and 3.
According to the embodiment of the application, a plurality of data processing scenes and data processing logics corresponding to the data processing scenes are preset, different data processing scenes correspond to different software performance data processing requirements, and the corresponding data processing logics are different. Responding to a request for processing data of a target scene to the application software, and acquiring a tracking file of the application software; converting the contents of the trace file into structured data; according to the structured data, the data processing logic corresponding to the target scene is executed to obtain a data processing result, the data processing result is output, and the customized data processing of various software performance data processing scenes can be automatically realized according to the tracking file, so that the processing efficiency of the software performance data is improved.
Fig. 5 is a schematic diagram of a data processing apparatus according to a third embodiment of the disclosure. The data processing device provided by the embodiment of the disclosure can execute the processing flow of the method embodiment of the data processing. As shown in fig. 5, the data processing apparatus 50 includes: a trace file acquisition module 501, a data conversion module 502, a data processing module 503 and a result output module 504.
Specifically, the trace file obtaining module 501 is configured to obtain a trace file of the application software in response to a request for performing data processing on a target scene on the application software.
A data conversion module 502, configured to convert the content of the trace file into structured data.
And the data processing module 503 is configured to execute a data processing logic corresponding to the target scene according to the structured data, so as to obtain a data processing result.
And a result output module 504, configured to output a data processing result.
The apparatus provided in the embodiment of the present disclosure may be specifically configured to execute the method flow provided in the first embodiment, and specific functions and technical effects achieved are not described herein again.
Fig. 6 is a schematic diagram of a data processing apparatus according to a fourth embodiment of the disclosure. The data processing device provided by the embodiment of the disclosure can execute the processing flow of the method embodiment of the data processing. As shown in fig. 6, the data processing apparatus 60 includes: a trace file acquisition module 601, a data conversion module 602, a data processing module 603 and a result output module 604.
Specifically, the trace file obtaining module 601 is configured to obtain a trace file of the application software in response to a request for performing data processing on a target scene on the application software.
A data conversion module 602, configured to convert the content of the trace file into structured data.
And the data processing module 603 is configured to execute a data processing logic corresponding to the target scene according to the structured data, so as to obtain a data processing result.
And a result output module 604, configured to output a data processing result.
Optionally, as shown in fig. 6, the data processing module 603 includes:
a loading unit 6031, configured to load a data analyzer corresponding to a target scene, where the data analyzer includes data processing logic corresponding to the target scene.
And a data processing unit 6032, configured to execute a data analyzer corresponding to the target scene, perform data processing on the structured data, and obtain a data processing result.
Optionally, the data processing logic includes data structure information of the output result corresponding to the target scene. As shown in fig. 6, the data processing unit includes:
and the data analyzer execution subunit is used for executing the data analyzer corresponding to the target scene, and performing data processing on the structured data to obtain a data result.
And the data integration subunit is used for generating a data processing result according to the data result and the data structure information of the output result.
Optionally, the data processing module is further configured to:
and according to the structured data, executing the data processing logic corresponding to the target scene through a plurality of threads concurrently to obtain a data processing result.
Optionally, as shown in fig. 6, the data processing apparatus 60 further includes:
a configuration module 605 configured to:
acquiring data processing logic corresponding to at least one data processing scene; and independently deploying the data processing logic corresponding to each data processing scene in the corresponding container.
Optionally, the configuration module is further configured to:
and updating the data processing logic corresponding to the data processing scene in response to the modification operation of the data processing logic corresponding to any data processing scene.
Optionally, the data conversion module is further configured to:
and taking the tracking file as input data of a specified application program interface, calling the specified application program through the specified application program interface, wherein the specified application program is used for converting the content of the tracking file into structured data and storing the structured data into a database.
Optionally, as shown in fig. 6, the result output module 604 includes:
a report generating unit 6041, configured to generate a data report according to the data processing result and a report template corresponding to the target scene.
A report output unit 6042 for outputting a data report.
The apparatus provided in the embodiment of the present disclosure may be specifically configured to execute the method flow provided in the second embodiment, and specific functions and technical effects achieved are not described herein again.
In the technical scheme of the disclosure, the collection, storage, use, processing, transmission, provision, disclosure and other processing of the personal information of the related user are all in accordance with the regulations of related laws and regulations and do not violate the good customs of the public order.
The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present disclosure.
According to an embodiment of the present disclosure, the present disclosure also provides a computer program product comprising: a computer program, stored in a readable storage medium, from which at least one processor of the electronic device can read the computer program, the at least one processor executing the computer program causing the electronic device to perform the solution provided by any of the embodiments described above.
FIG. 7 illustrates a schematic block diagram of an example electronic device 700 that can be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 7, the device 700 comprises a computing unit 701, which may perform various suitable actions and processes according to a computer program stored in a Read Only Memory (ROM)702 or a computer program loaded from a storage unit 708 into a Random Access Memory (RAM) 703. In the RAM703, various programs and data required for the operation of the device 700 can also be stored. The computing unit 701, the ROM 702, and the RAM703 are connected to each other by a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.
Various components in the device 700 are connected to the I/O interface 705, including: an input unit 706 such as a keyboard, a mouse, or the like; an output unit 707 such as various types of displays, speakers, and the like; a storage unit 708 such as a magnetic disk, optical disk, or the like; and a communication unit 709 such as a network card, modem, wireless communication transceiver, etc. The communication unit 709 allows the device 700 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, 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), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The Server can be a cloud Server, also called a cloud computing Server or a cloud host, and is a host product in a cloud computing service system, so as to solve the defects of high management difficulty and weak service expansibility in the traditional physical host and VPS service ("Virtual Private Server", or simply "VPS"). The server may also be a server of a distributed system, or a server incorporating a blockchain.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved, and the present disclosure is not limited herein.
The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Claims (19)
1. A method of data processing, comprising:
responding to a request for processing data of a target scene to application software, and acquiring a tracking file of the application software;
converting the contents of the tracking file into structured data;
executing data processing logic corresponding to the target scene according to the structured data to obtain a data processing result;
and outputting the data processing result.
2. The method of claim 1, wherein the executing the data processing logic corresponding to the target scene according to the structured data to obtain a data processing result comprises:
loading a data analyzer corresponding to the target scene, wherein the data analyzer comprises data processing logic corresponding to the target scene;
and executing a data analyzer corresponding to the target scene, and performing data processing on the structured data to obtain a data processing result.
3. The method of claim 2, wherein the data processing logic includes data structure information of output results corresponding to the target scene;
the executing the data analyzer corresponding to the target scene performs data processing on the structured data to obtain a data processing result, and the data processing result includes:
executing a data analyzer corresponding to the target scene, and performing data processing on the structured data to obtain a data result;
and generating the data processing result according to the data structure information of the output result and the data result.
4. The method according to any one of claims 1-3, wherein the executing, according to the structured data, the data processing logic corresponding to the target scene to obtain a data processing result comprises:
and according to the structured data, executing data processing logic corresponding to the target scene through a plurality of threads concurrently to obtain a data processing result.
5. The method according to any one of claims 1-4, wherein before executing the data processing logic corresponding to the target scene according to the structured data and obtaining a data processing result, the method further comprises:
acquiring data processing logic corresponding to at least one data processing scene;
and independently deploying the data processing logic corresponding to each data processing scene in the corresponding container.
6. The method of claim 5, further comprising:
and updating the data processing logic corresponding to any data processing scene in response to the modification operation of the data processing logic corresponding to the data processing scene.
7. The method of any of claims 1-6, wherein the converting the contents of the trace file into structured data comprises:
and taking the tracking file as input data of a specified application program interface, calling a specified application program through the specified application program interface, wherein the specified application program is used for converting the content of the tracking file into structured data and storing the structured data into a database.
8. The method of any of claims 1-7, wherein the outputting the data processing result comprises:
generating a data report according to the data processing result and a report template corresponding to the target scene;
and outputting the data report.
9. An apparatus for data processing, comprising:
the tracking file acquisition module is used for responding to a request for carrying out data processing on a target scene on the application software and acquiring a tracking file of the application software;
the data conversion module is used for converting the content of the tracking file into structured data;
the data processing module is used for executing data processing logic corresponding to the target scene according to the structured data to obtain a data processing result;
and the result output module is used for outputting the data processing result.
10. The apparatus of claim 9, wherein the data processing module comprises:
a loading unit, configured to load a data analyzer corresponding to the target scene, where the data analyzer includes data processing logic corresponding to the target scene;
and the data processing unit is used for executing a data analyzer corresponding to the target scene, and performing data processing on the structured data to obtain a data processing result.
11. The apparatus of claim 10, wherein the data processing logic includes data structure information of output results corresponding to the target scene;
the data processing unit comprises:
the data analyzer execution subunit is used for executing the data analyzer corresponding to the target scene, and performing data processing on the structured data to obtain a data result;
and the data integration subunit is used for generating the data processing result according to the data result and the data structure information of the output result.
12. The apparatus of any of claims 9-11, wherein the data processing module is further to:
and according to the structured data, executing data processing logic corresponding to the target scene through a plurality of threads concurrently to obtain a data processing result.
13. The apparatus of any of claims 9-12, further comprising:
a configuration module to:
acquiring data processing logic corresponding to at least one data processing scene;
and independently deploying the data processing logic corresponding to each data processing scene in the corresponding container.
14. The apparatus of claim 13, wherein the configuration module is further configured to:
and updating the data processing logic corresponding to any data processing scene in response to the modification operation of the data processing logic corresponding to the data processing scene.
15. The apparatus of any of claims 9-14, wherein the data conversion module is further to:
and taking the tracking file as input data of a specified application program interface, calling a specified application program through the specified application program interface, wherein the specified application program is used for converting the content of the tracking file into structured data and storing the structured data into a database.
16. The apparatus of any of claims 9-15, wherein the result output module comprises:
the report generating unit is used for generating a data report according to the data processing result and a report template corresponding to the target scene;
and the report output unit is used for outputting the data report.
17. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-8.
18. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-8.
19. A computer program product comprising a computer program which, when executed by a processor, carries out the steps of the method of any one of claims 1 to 8.
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