WO2023116003A1

WO2023116003A1 - Data processing method and apparatus, device, storage medium and computer program product

Info

Publication number: WO2023116003A1
Application number: PCT/CN2022/113850
Authority: WO
Inventors: 魏嘉汛; 董敏; 王鹏翔; 田泽润; 覃耀辉
Original assignee: 北京百度网讯科技有限公司
Priority date: 2021-12-24
Filing date: 2022-08-22
Publication date: 2023-06-29
Also published as: CN114416029A

Abstract

A data processing method and apparatus, a device, a storage medium and a computer program product, relating to the technical field of computer application, and in particular to the technical field of data processing for a web front-end application. The specific implementation solution comprises: determining target data to be processed, and determining a data source of the target data (S101); performing instrumentation processing between the target data and the data source to obtain global data in the process of accessing the data source by the target data (S102); and determining and outputting a dependency relationship among all data in the global data (S103). Therefore, the dependency relationship among all the data in the global data can be determined and outputted, so that the dependency relationship between the global data is analyzed.

Description

Data processing method, device, device, storage medium and computer program product

technical field

The present disclosure relates to the technical field of computer applications, in particular to the technical field of data processing of web front-end applications.

Background technique

For web front-end applications under the MVVM (Model-View-View Model) framework, the details of view changes can be hidden by adopting a data-driven approach, so that developers only need to focus on data changes In the process of processing, you don't need to care about the details of view change updates.

In related technologies, for the code data of the web front-end application, a specific state management tool matching the framework can be applied to analyze and manage the global data state, so as to obtain data on changes in the data state, track and locate the problems that occur in the application, and Perform correctness analysis on the data change process from model to view.

Contents of the invention

The present disclosure provides a data processing method, device, device, storage medium and computer program product.

According to an aspect of the present disclosure, a data processing method is provided, including:

Determine the target data to be processed, and determine the data source of the target data; perform stub processing between the target data and the data source, so as to obtain the global data in the process of the target data accessing the data source ; Determine and output the dependencies among the data in the global data.

According to another aspect of the present disclosure, a data processing device is provided, including:

A determination unit, configured to determine the target data to be processed, and determine a data source of the target data; a processing unit, configured to perform instrumentation processing between the target data and the data source, to obtain the target data The global data in the process of accessing the data source; an output unit configured to determine and output the dependencies among the data in the global data.

According to yet another aspect of the present disclosure, an electronic device is provided, comprising:

at least one processor; and a memory communicatively coupled to the at least one processor; wherein,

The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor, so that the at least one processor can execute the above-mentioned method.

According to yet another aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause the computer to execute the above-mentioned method.

According to yet another aspect of the present disclosure, a computer program product is provided, including a computer program, and the computer program implements the above-mentioned method when executed by a processor.

Through the present disclosure, the stub processing is performed between the target data and the data source, and then the global data in the process of the target data accessing the data source can be obtained, so a more efficient data processing device can be provided.

It should be understood that what is described in this section is not intended to identify key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will be readily understood through the following description.

Description of drawings

The accompanying drawings are used to better understand the present solution, and do not constitute a limitation to the present disclosure. in:

FIG. 1 is a flow chart of a data processing method shown in an exemplary embodiment of the present disclosure;

Fig. 2 shows a schematic diagram of a global data production and consumption relationship shown in an exemplary embodiment of the present disclosure;

Fig. 3 shows a schematic diagram of instrumentation between producers and consumers according to an exemplary embodiment of the present disclosure;

Fig. 4 is a flow chart of a data processing method shown in an exemplary embodiment according to the present disclosure;

Fig. 5 is a block diagram of a data processing device provided according to the present disclosure;

FIG. 6 shows a schematic block diagram of an example electronic device 600 that may be used to implement embodiments of the present disclosure.

Detailed ways

Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and they should be regarded as exemplary only. 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 disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

The data processing method provided in the present disclosure is applied to a scene of analyzing and processing data of web front-end applications. For example, it can be applied to data analysis and processing of modern web front-end applications based on the MVVM framework.

In related technologies, a front-end program analysis tool may be used to analyze the global data of the web front-end application. At present, various analysis tools for analyzing the global data of web front-end applications, the program analysis capabilities are mainly concentrated in a specific state management solution, and provide data change tracking capabilities for specific solutions. This kind of data change tracking capability mainly starts from the change of a single data state itself, and analyzes the data change relationship involved in the data operation process through dynamic operation mode, so as to locate the problem of the program and analyze the correctness of the program. However, this kind of solution only focuses on the tracking of data changes, and lacks analysis of data dependencies and consumption characteristics. Especially for data subscriptions and data dependencies, it lacks analysis capabilities and cannot completely solve business problems. The problems encountered will affect the efficiency of research and development. In other words, the solutions for managing the data state of global data in the related art only support the tracking of data changes, and do not involve analysis of dependencies between data, nor do they involve which view elements the data is consumed by. Moreover, the output result of data state management in the related art is a log with a linear structure, which cannot reflect the relationship between output results between components, that is, the interactive relationship between logs, the serial relationship of component operations, and the like.

In view of this, the present disclosure provides a data processing method. In this method, the global data involved in the process of accessing the data source of the data with consumption characteristics is obtained through the stub processing method, and the global data in the global data are determined. The dependency relationship between data is output to realize the analysis of the dependence and consumption characteristics of each data in the global data.

Fig. 1 is a flowchart of a data processing method shown in an exemplary embodiment of the present disclosure. Referring to FIG. 1, the data processing method includes the following steps S101 to S103.

In step S101, target data to be processed is determined, and a data source of the target data is determined.

In step S102, instrumentation is performed between the target data and the data source, so as to obtain global data in the process of the target data accessing the data source.

In step S103, determine and output the dependencies among the data in the global data.

The data involved in the present disclosure may be global data in the producer-consumer pattern. Among them, the data in the producer-consumer mode includes producers and consumers. There is only one producer of global data, but usually there are multiple consumers. That is, a producer can correspond to multiple consumers, but a consumer can only correspond to one producer. Each producer and each consumer corresponds to an address, occupies a network node, and belongs to predetermined data. Fig. 2 shows a schematic diagram of a global data production and consumption relationship according to an exemplary embodiment of the present disclosure. Referring to Figure 2, the producer's data can be consumed by consumer 1 and consumer 2. The target data to be processed involved in the present disclosure may be a consumer in the producer-consumer pattern, for example, data with consumption characteristics such as view elements. The target data to be processed can also be referred to as a consumer. In the present disclosure, the data source of the target data may be a producer in the producer-consumer pattern.

In the present disclosure, the instrumentation process between the target data and the data source can be understood as adding instrumentation codes to the source code of the global data. Through the instrumentation code, the global data in the process of the target data accessing the data source can be obtained, and then the content information with data dependencies between the global data can be obtained.

In an exemplary embodiment of the present disclosure, a proxy may be inserted between a data source (producer) and target data to be processed (consumer). Fig. 3 shows a schematic diagram of instrumentation between a producer and a consumer according to an exemplary embodiment of the present disclosure. As shown in Figure 3, a proxy is inserted between the data and consumer 1 and consumer 2, where the consumer needs to access and modify the data of the data source through the proxy and save it in the access library. Among them, consumers cannot directly access the real data in the data source, but access it through an agent.

In the present disclosure, global data in the process of target data accessing a data source can be obtained by obtaining access to data by any consumer through a proxy. In the present disclosure, whenever a consumer accesses data, information such as the path of the component to which the current consumer belongs, the name of the component, and the data content of the current data are calculated, and then the dependencies between the data are determined.

In the present disclosure, the dependency relationship between the data in the global data is determined, and the dependency relationship between the data in the global data can be output, so as to realize the monitoring of the dependency relationship between the data and reflect the correlation relationship between the data. For example, in the present disclosure, the dependency relationship among the data in the global data can be stored in the data access library.

The data processing method provided by this disclosure, through the stub processing between the target data to be processed and the data source, the global data in the process of accessing the data source from the target data can be obtained through the stub, and each data in the global data can be obtained. The content information of the dependency relationship between the data outputs the dependency relationship between the data in the global data, which can realize the analysis of the dependency relationship between the global data.

In this disclosure, when the global data is obtained through the instrumentation code added in the source code of the data source, the statement of the data, the update of the data, the subscription method of the data to the component, etc. can be obtained, so that the obtained global data depends on relationship, which can cover the data state of a more comprehensive global data.

Fig. 4 is a flow chart of a data processing method shown in an exemplary embodiment of the present disclosure. Referring to FIG. 4, the data processing method includes the following steps S201 to S203.

In step S201, the data structure returned by the data declaration API (Application Programming Interface, application programming interface) is obtained, so as to obtain the global data declaration information of the target data access data source.

In step S202, the subscription information of calling the data subscription API for data subscription is obtained, so as to obtain the global data subscription information of the target data access data source.

In step S203, the update information for calling the data update API to update the data is obtained, so as to obtain the global data update information of the target data access data source.

It can be understood that the present disclosure does not limit the order of execution of steps S201, S202, and S203, as long as the statement of data, update of data, subscription method of data to components, etc. can be obtained.

In related technologies, although the APIs provided by the view layer frameworks applied to different front-end MVVMs have different forms, the functions provided by the APIs are the same in terms of data declaration, update, and subscription. For example, the functions provided by createStore in the Redux (React) framework, atom in the Recoil (React) framework, and Class@observable in the Mobx (React/Vue) framework are all data declaration API functions. The functions provided by dispatchAction in the Redux (React) framework, useRecoilState/getter in the Recoil (React) framework, and Property accessor in the Mobx (React/Vue) framework are all data update API functions. The functions provided by useSelector in the Redux (React) framework, useRecoilState/setter in the Recoil (React) framework, and Property setter in the Mobx (React/Vue) framework are all data subscription API functions. Therefore, in this disclosure, by obtaining the data declaration API, data update API, and data subscription API through stub insertion, relevant information of applications applied to different front-end MVVM frameworks at runtime can be obtained, and more comprehensive global data data can be covered state.

In an exemplary implementation, the present disclosure uses the Redux framework as an example to illustrate acquiring global data and determining dependencies between the global data.

In the present disclosure, when it is necessary to acquire the relevant information of the global data declaration, based on the instrumentation scheme involved in the above embodiment, the data structure finally returned by the data declaration API of the framework is obtained. Under the Redux framework, the store object returned by createStore is obtained through instrumentation. This object holds the global data of the web front-end application, so the statement information of all global data can be obtained in the instrumented agent.

In the present disclosure, when it is necessary to acquire the subscription relationship to data in the component, based on the instrumentation scheme involved in the above-mentioned embodiments, the relevant calls to the data subscription API in the component are hijacked. Under the Redux framework, when using the useSelector call, the access information of the selector function to the object properties is obtained in the access library of the proxy by means of stub insertion, and then the connection between the global data state and the subscription state component can be established, and It can clearly determine the object properties specifically accessed inside the component.

In the present disclosure, in the case where the update relationship of the data needs to be acquired, based on the instrumentation solution involved in the above embodiments, the update API is hijacked by instrumentation. Under the Redux framework, the global data updated by a component is updated by calling the dispatchAction method to dispatch an action to update the global data. Therefore, by getting the dispatchAction call through the stub, you can get the changes made by any component to the global data, and then you can use it before and after the call. Changes in global data determine which components trigger which data updates, and then clearly record the status of data updates throughout the process.

In this disclosure, the data declaration API, data update API, and data subscription API are hijacked by instrumentation, and then the complete dependency relationship between data and components during application operation can be constructed, and the update process of components can be clearly described, which can help Developers understand the project and make technical decisions.

The data dependency involved in the present disclosure includes at least one of the following: data status, data status change information, and subscription relationship between data and components.

In this disclosure, when global data is obtained based on stub insertion, the consumer's access to data is obtained from the proxy, and whenever a consumer accesses data, the current consumer's component path, component ID, and current data data are calculated content and other information. Save the obtained component path, component ID, data content, etc. Further, in this disclosure, it is possible to compare the component paths, component identifiers, data content and other information corresponding to each consumer access data to determine the changed and updated content, store the changed and updated content, and the reasons for the changed and updated content. In turn, the data status, the update of changes in the data status, and the subscription relationship between data components can be determined.

In the present disclosure, when determining the dependency relationship between data, it is possible to determine the component identifier of the component to which each data belongs in the obtained global data, and determine the data dependency associated with the component identifier, and assemble the data dependency associated with the component identifier. The relationship can connect the data states of each component in series to obtain the dependency relationship between the data.

In this disclosure, the data dependencies associated with the component identifiers are assembled to record the data status and the reasons for the data status changes. Compared with the data status analysis results of the linear structure log method in the traditional technology, it is possible to clarify the relationship between components. The correlation between the output results is more conducive to the subscription analysis of the data status of the global data.

Furthermore, based on the data dependencies between the output data in this disclosure, developers can use the global data subscription analysis to easily understand which components consume the global data, obtain the dependencies of different components, and target components with the same dependencies Encapsulation is possible, and the encapsulated components can be reused.

In the present disclosure, components with the same data dependency may be determined and encapsulated. The same dependency includes at least one of the following: the same component path, the same component identifier, and the same data content. Encapsulating the same data dependencies in the present disclosure can facilitate developers to reuse the encapsulated data dependencies, perform code reconstruction, and improve code reuse.

Furthermore, based on the data dependencies between output data in this disclosure, developers can use global data subscription analysis, based on recorded component identifiers, and the propagation links between component identifiers, to determine the relatively stable propagation links corresponding to Component ID, as cacheable data.

In the present disclosure, a cacheable component identifier may be determined, and based on the component identifier, it is determined that there is component-dependent data. Among them, the data with component dependencies may be the data with the same component path, or it may be understood as the data with the same propagation links involved in the data propagation process.

In this disclosure, for data with component dependencies, the component identifiers corresponding to the data with component dependencies can be cached, and then the cached component identifiers can be directly used to determine the corresponding component paths and improve Component performance optimization. In other words, through the present disclosure, caching can quickly locate whether the data that the component depends on is cacheable, and the transmission link of the cacheable data, so as to improve the performance by increasing the cache.

Further, in the present disclosure, based on the data dependency relationship between the output data, the output data is a subscription relationship distribution graph subscribed by components. The subscription relationship distribution diagram represents the subscription relationship between data and components, constructs a complete data-component dependency relationship graph during application operation, and can clearly describe the update process of components. Therefore, object attributes and nesting levels between objects can be determined through the subscription relationship distribution diagram provided in this disclosure, and based on the nesting level, it can be judged whether the module division is accurate, and then the code maintainability can be judged.

For example, through the subscription relationship distribution diagram of data subscribed by components, developers can further observe the depth of data subscriptions, and then analyze whether the current module division is reasonable. For example, the subscription relationship distribution diagram involves the writing of the global data model in the comment area of the global data. Since the comment area can only be subscribed and cannot be divided, the developer can conclude that it is unreasonable to divide the comment area into modules in this case.

Based on the same idea, the embodiment of the present disclosure also provides a data processing device.

It can be understood that, in order to realize the above-mentioned functions, the data processing apparatus provided by the embodiments of the present disclosure includes corresponding hardware structures and/or software modules for performing various functions. Combining the units and algorithm steps of each example disclosed in the embodiments of the present disclosure, the embodiments of the present disclosure can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed by hardware or computer software drives hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art may use different methods to implement the described functions for each specific application, but such implementation should not be regarded as exceeding the scope of the technical solutions of the embodiments of the present disclosure.

As an exemplary implementation, Fig. 5 is a block diagram of a data processing device provided according to the present disclosure. Referring to FIG. 5 , a data processing apparatus 500 provided in the present disclosure includes a determination unit 501 , a processing unit 502 and an output unit 503 .

The determination unit 501 is used to determine the target data to be processed, and determine the data source of the target data; the processing unit 502 is used to perform stub processing between the target data and the data source, so as to obtain the target data in the process of accessing the data source Global data; an output unit 503, configured to determine and output the dependency relationship among the data in the global data.

Wherein, the processing unit 502 is used to: obtain the data structure returned by the data declaration API to obtain the global data declaration information of the target data access data source; obtain the subscription information for calling the data subscription API for data subscription to obtain the target data Access the global data subscription information of the data source; obtain the update information of calling the data update application program interface for data update, so as to obtain the global data update information of the target data access data source.

Wherein, the output unit 503 is used to: determine the component identification of the component to which each data in the global data belongs; determine the data dependency relationship associated with the component identification, and the data dependency relationship includes at least one of the following: data status, data status change information, and data Subscription relationship with components;

Assembling components identifies associated data dependencies.

In an exemplary embodiment of the present disclosure, the output unit 503 is further configured to: determine the same data dependency, the same dependency includes at least one of the following: the same component path, the same component identifier, and the same data content; encapsulation Same data dependencies.

In an exemplary embodiment of the present disclosure, the output unit 503 is further configured to: based on the component identifier, determine that there is component-dependent data, and the component-dependent data includes the same component path to which the data belongs; and cache the component identifier corresponding to the component-dependent data.

In an exemplary embodiment of the present disclosure, the output unit 503 is further configured to: output a subscription relationship distribution graph, where the subscription relationship distribution graph is used to represent the subscription relationship between data and components.

Regarding the above-mentioned apparatus of the present disclosure, the specific manner in which each module executes operations has been described in detail in the embodiment of the method, and will not be described in detail here.

In the technical solution of the present disclosure, the acquisition, storage and application of the user's personal information involved are in compliance with relevant laws and regulations, and do not violate public order and good customs.

According to the embodiments of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium, and a computer program product.

FIG. 6 shows a schematic block diagram of an example electronic device 600 that may be used to implement embodiments of the present disclosure. Electronic device is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other suitable computers. Electronic devices 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 by way of example only, and are not intended to limit implementations of the disclosure described and/or claimed herein.

As shown in FIG. 6, the device 600 includes a computing unit 601 that can execute according to a computer program stored in a read-only memory (ROM) 602 or loaded from a storage unit 608 into a random-access memory (RAM) 603. Various appropriate actions and treatments. In the RAM 603, various programs and data necessary for the operation of the device 600 can also be stored. The computing unit 601, ROM 602, and RAM 603 are connected to each other through a bus 604. An input/output (I/O) interface 605 is also connected to the bus 604 .

Multiple components in the device 600 are connected to the I/O interface 605, including: an input unit 606, such as a keyboard, a mouse, etc.; an output unit 607, such as various types of displays, speakers, etc.; a storage unit 608, such as a magnetic disk, an optical disk, etc. ; and a communication unit 609, such as a network card, a modem, a wireless communication transceiver, and the like. The communication unit 609 allows the device 600 to exchange information/data with other devices over a computer network such as the Internet and/or various telecommunication networks.

The computing unit 601 may be various general-purpose and/or special-purpose processing components having processing and computing capabilities. Some examples of computing units 601 include, but are not limited to, central processing units (CPUs), graphics processing units (GPUs), various dedicated artificial intelligence (AI) computing chips, various computing units that run machine learning model algorithms, digital signal processing processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 601 executes various methods and processes described above, such as data processing methods. For example, in some embodiments, the data processing method may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as the storage unit 608 . In some embodiments, part or all of the computer program may be loaded and/or installed on the device 600 via the ROM 602 and/or the communication unit 609. When the computer program is loaded into RAM 603 and executed by computing unit 601, one or more steps of the data processing method described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to execute the data processing method in any other suitable manner (for example, by means of firmware).

Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips Implemented in a system of systems (SOC), load programmable logic device (CPLD), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include being implemented in one or more computer programs executable and/or interpreted on a programmable system including at least one programmable processor, the programmable processor Can be special-purpose or general-purpose programmable processor, can receive data and instruction from storage system, at least one input device, and at least one output device, and transmit data and instruction to this storage system, this at least one input device, and this at least one output device an output device.

Program codes 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, a special purpose computer, or other programmable data processing devices, so that the program codes, when executed by the processor or controller, make the functions/functions specified in the flow diagrams and/or block diagrams Action is implemented. 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 the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A 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, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media would include one or more wire-based electrical connections, portable computer discs, hard drives, random access memory (RAM), read only memory (ROM), erasable programmable read only memory (EPROM or flash memory), optical fiber, compact disk read only memory (CD-ROM), optical storage, magnetic storage, or any suitable combination of the foregoing.

To provide for interaction with the user, the systems and techniques described herein 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 the user. ); and a keyboard and pointing device (eg, a mouse or a trackball) through which a user can provide input to the computer. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and can be in any form (including Acoustic input, speech input or, tactile input) to receive input from the user.

The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., as a a user computer having a graphical user interface or web browser through which a user can interact with embodiments of the systems and techniques described herein), or including such backend components, middleware components, Or any combination of front-end components in a computing system. The components of the system can be interconnected by any form or medium of digital data communication, eg, a communication network. Examples of communication networks include: Local Area Network (LAN), Wide Area Network (WAN) and the Internet.

A computer system may include clients and servers. Clients and servers are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, a server of a distributed system, or a server combined with a blockchain.

It should be understood that steps may be reordered, added or deleted using the various forms of flow shown above. For example, each step described in the present disclosure may be executed in parallel, sequentially, or in a different order, as long as the desired result of the technical solution disclosed in the present disclosure can be achieved, no limitation is imposed herein.

The specific implementation manners described above do not limit the protection scope of the present disclosure. It should be apparent to those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made depending on design requirements and other factors. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present disclosure shall be included within the protection scope of the present disclosure.

Claims

A data processing method, comprising:

Determine the target data to be processed, and determine the data source of the target data;

Perform stub insertion between the target data and the data source to obtain global data in the process of the target data accessing the data source;

Determine and output the dependencies among the data in the global data.
The method according to claim 1, wherein said obtaining the global data in the process of accessing the target data to the data source comprises:

Acquiring the data structure returned by the data declaration application program interface, so as to obtain the global data declaration information for the target data to access the data source;

Obtain subscription information for calling a data subscription application program interface for data subscription, so as to obtain global data subscription information for the target data to access the data source;

Obtain update information for calling a data update application program interface to perform data update, so as to acquire global data update information for the target data to access the data source.
The method according to claim 1 or 2, wherein said determining and outputting the dependencies among the data in the global data comprises:

Determine the component identifier of the component to which each data in the global data belongs;

Determine a data dependency relationship associated with the component identifier, the data dependency relationship includes at least one of the following: data status, data status change information, and a subscription relationship between data and components;

Assembling components identifies associated data dependencies.
The method according to claim 3, further comprising:

Determine the same data dependency, the same dependency includes at least one of the following: the same component path, the same component identifier, and the same data content;

Encapsulates the same data dependencies as described.
The method according to claim 3, further comprising:

Based on the component identification, it is determined that there is component-dependent data, and the component-dependent data includes that the components to which the data belong have the same path;

The component identifier corresponding to the data on which the component depends is cached.
The method according to claim 3, further comprising:

A subscription relationship distribution graph is output, and the subscription relationship distribution graph is used to represent the subscription relationship between data and components.
A data processing device, comprising:

a determining unit, configured to determine target data to be processed, and determine a data source of the target data;

a processing unit, configured to perform instrumentation processing between the target data and the data source, so as to obtain global data in the process of the target data accessing the data source;

The output unit is configured to determine and output the dependency relationship among the data in the global data.
The device according to claim 7, wherein the processing unit is configured to:

Acquiring the data structure returned by the data declaration application program interface, so as to obtain the global data declaration information for the target data to access the data source;

Obtain subscription information for calling a data subscription application program interface for data subscription, so as to obtain global data subscription information for the target data to access the data source;

Obtain update information for calling a data update application program interface to perform data update, so as to acquire global data update information for the target data to access the data source.
The device according to claim 7 or 8, wherein the output unit is used for:

Determine the component identifier of the component to which each data in the global data belongs;

Determine a data dependency relationship associated with the component identifier, the data dependency relationship includes at least one of the following: data status, data status change information, and a subscription relationship between data and components;

Assembling components identifies associated data dependencies.
The device according to claim 9, the output unit is further used for:

Determine the same data dependency, the same dependency includes at least one of the following: the same component path, the same component identifier, and the same data content;

Encapsulates the same data dependencies as described.
The device according to claim 9, the output unit is further used for:

Based on the component identification, it is determined that there is component-dependent data, and the component-dependent data includes that the components to which the data belong have the same path;

The component identifier corresponding to the data on which the component depends is cached.
The device according to claim 9, the output unit is further used for:

A subscription relationship distribution graph is output, and the subscription relationship distribution graph is used to represent the subscription relationship between data and components.
An electronic device comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,

The memory stores instructions executable by the at least one processor, the instructions are executed by the at least one processor, so that the at least one processor can perform any one of claims 1-6. Methods.
A non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause the computer to execute the method according to any one of claims 1-6.
A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1-6.