CN111831319A - Differential data posterior method, device, equipment and storage medium - Google Patents
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Abstract
The application discloses a difference data posterior method, a difference data posterior device, a difference data posterior equipment and a storage medium, and relates to computer vision, software development and software testing. The specific implementation scheme is as follows: acquiring difference data to be posteriori, wherein the difference data comprises a target sequence value and a plurality of target attribute values corresponding to the target sequence value; if the target sequence value exists in the preset posterior mapping relation, determining that the difference of the plurality of target attribute values is unacceptable based on the attribute information corresponding to the target sequence value in the preset posterior mapping relation, wherein the preset posterior mapping relation comprises the mapping relation between the sequence value and the attribute information; outputting the target sequence value and the plurality of target attribute values. The method and the device can automatically complete the posterior with unacceptable difference, thereby saving labor and effectively improving the posterior processing efficiency of data.
Description
Technical Field
The present application relates to computer vision, software development, and software testing in data processing technologies, and in particular, to a differential data posterior method, device, apparatus, and storage medium.
Background
The data flow services designed for the front-end engineering are continuously increased, the iteration frequency of service module reconstruction, migration and technology upgrading is high, and comparison of results obtained after processing of new and old versions of the same input becomes an important part in daily tests. However, the old and new versions have some known differences or acceptable differences, and these differences in different modules or services cannot be copied and shared at all, which results in a very high ratio of differences between data in a large number of JavaScript Object Notation (JSON) formats of different services when they are aligned.
Disclosure of Invention
The application provides a difference data posterior method, a device, equipment and a storage medium for automatically finishing posterior of whether differences are acceptable.
According to a first aspect of the present application, there is provided a difference data posterior method, comprising:
acquiring difference data to be posteriori, wherein the difference data comprises a target sequence value and a plurality of target attribute values corresponding to the target sequence value;
if the target sequence value exists in the preset posterior mapping relation, determining that the difference of the plurality of target attribute values is unacceptable based on the attribute information corresponding to the target sequence value in the preset posterior mapping relation, wherein the preset posterior mapping relation comprises the mapping relation between the sequence value and the attribute information;
outputting the target sequence value and the plurality of target attribute values.
According to a second aspect of the present application, there is provided a difference data posterior device comprising:
the system comprises an acquisition module, a verification module and a verification module, wherein the acquisition module is used for acquiring difference data to be posteriori, and the difference data comprises a target sequence value and a plurality of target attribute values corresponding to the target sequence value;
the detection module is used for detecting whether a target sequence value exists in a preset posterior mapping relation; when a target sequence value exists in the preset posterior mapping relation, a determining module is triggered to determine that the difference of a plurality of target attribute values is unacceptable based on attribute information corresponding to the target sequence value in the preset posterior mapping relation, wherein the preset posterior mapping relation comprises the mapping relation between the sequence value and the attribute information;
and the output module is used for outputting the target sequence value and the plurality of target attribute values.
According to a third aspect, 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 according to any one of the first aspect.
According to a fourth aspect, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing a computer to perform the method according to any one of the first aspect.
According to the technology of the application, whether the difference is acceptable or not can be automatically completed, so that the labor is saved, and the data posterior processing efficiency is effectively improved.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present application, nor do they limit the scope of the present application. Other features of the present application will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not intended to limit the present application. Wherein:
FIG. 1 is a schematic diagram according to a first embodiment of the present application;
FIG. 2 is a schematic diagram according to a second embodiment of the present application;
FIG. 3 is a schematic illustration according to a third embodiment of the present application;
FIG. 4 is a schematic illustration according to a fourth embodiment of the present application;
FIG. 5 is a block diagram of an electronic device for implementing the difference data posterior method of an embodiment of the present application;
fig. 6 is a diagram of a scenario in which an embodiment of the present application may be implemented.
Detailed Description
The following description of the exemplary embodiments of the present application, taken in conjunction with the accompanying drawings, includes various details of the embodiments of the application for the understanding of the same, which are to be considered 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 present application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
The JSON format is a lightweight data exchange language designed and designed by douglas-crookford, which is based on easily readable words for transmitting data objects consisting of attribute values or sequential values (hereinafter referred to as "sequence values"). Although JSON is a subset of JavaScript, JSON is a language independent text format and employs some conventions similar to the C language family. The JSON format can be read in JavaScript as an eval () function (JavaScript calls the parser through eval ()). This does not, however, mean that the JSON format cannot be used in other languages, and indeed almost all languages relevant to web page development have a JSON function library. Data in JSON format is exemplified as follows:
in the above example, the part preceding the colon is the sequence value, and the part following the colon is the attribute value. For example, "firstName": in the 'John', the firstName is a sequence value, and John is an attribute value corresponding to the sequence value of the firstName; as another example, an "address": { … … }, address is a sequence value, and the content in parentheses is an attribute value corresponding to the sequence value of address.
With respect to JSON Diff, it is understood that 2 sets (typically 2 versions) of data in JSON format are compared to yield data difference results, i.e., difference data referred to herein, including additions, subtractions and updates. The difference data can be obtained by using the existing JSON Diff tool.
But it may be acceptable to take into account some differences to which the data corresponds. By way of example, having made clear that certain content fields differ by a particular rule (expected), conventional JSON Diff tools will still yield difference data. Therefore, it is not possible to distinguish between differences in the production of difference data by the JSON Diff tool that are within expectations or outside expectations. For example, a picture sharpness algorithm is upgraded, and acceptable differences in picture sharpness are calculated as the decimal place 6 must be consistent, the old and new data 5.1111113 and 5.1111112 are considered to be in accordance with expectations, and the 5.111113 and 5.111112 are considered to be in accordance with expectations. For another example, a module language change upgrade, a "[ ]" change to "{ }" is expected, and others must be the same to be expected. As another example, some scenarios for some modules only care whether the lengths are consistent, the contents do not care, and so on. For these acceptable differences we do not need to care about, only those that are not. At present, it is necessary to manually confirm which of the difference data is acceptable and which is unacceptable, so that when the data volume of the difference data is large, it is laborious and time-consuming, and the data posterior processing efficiency is low.
It is clear that unacceptable differences include: unknown, unpredictable differences, or known but unacceptable differences, i.e. differences outside the acceptable differences.
Therefore, in view of the above problems, the present application provides a difference data posterior method, device, equipment and storage medium, which are applied to computer vision, software development and software testing in the technical field of data processing, and perform classification processing on difference data generated by comparing 2 sets of data again to obtain a conclusion whether the difference data is acceptable, that is, a difference data posterior, so as to achieve the purpose of improving the probability of data posterior processing.
The differential data posterior scheme provided by the Application is suitable for, but not limited to, software development tests aiming at web pages, applications (APP for short) and new requirements.
The following detailed examples are used to illustrate how the application performs the difference data a posteriori.
Fig. 1 is a schematic diagram according to a first embodiment of the present application. The present embodiment provides a difference data posterior method, which may be performed by a difference data posterior device, where the difference data posterior device may be specifically a client or a server such as a desktop computer, a tablet computer, a notebook computer, or the like, or the difference data posterior device may be a chip in the client or a chip in the server, or the like. The following description is given by taking a client as an execution subject.
As shown in fig. 1, the difference data posterior method includes the following steps:
s101, obtaining difference data to be posteriori, wherein the difference data comprises a target sequence value and a plurality of target attribute values corresponding to the target sequence value.
Illustratively, the data produced by the old version is:
aiming at the data produced by the new version and the old version, a traditional JSON Diff tool is used for comparison, and the produced difference data is as follows: { "score": 123.987654,123.987655, "ex _ score": 223.123456,223.123455 }.
Since the difference data generated by the traditional JSON Diff tool is further subjected to posterior processing, the difference data to be posterior is acquired firstly.
For the sake of distinction and understanding, the sequence values and the attribute values included in the difference data to be posteriori are referred to as "target sequence values" and "target attribute values", respectively. Still taking the above example as an example, the target sequence values, namely score, are associated with a plurality of target attribute values, namely 123.987654 and 123.987655; alternatively, the target sequence value is ex _ score, which corresponds to multiple target attribute values 223.123456 and 223.123455.
Since two versions are illustrated by way of example, the number of target attribute values corresponding to the same target sequence value is two, but the application is not limited thereto, and the specific number of target attribute values is determined according to the number of versions participating in comparison.
S102, if the target sequence values exist in the preset posterior mapping relation, determining that the difference of the target attribute values is unacceptable based on the attribute information corresponding to the target sequence values in the preset posterior mapping relation.
The preset posterior mapping relation comprises a mapping relation between a sequence value and attribute information. It is understood that the preset a posteriori mapping relationship is preset based on actual needs or historical experience. For the specific meaning of the attribute information, in a first specific implementation, the attribute information in the preset posterior mapping relationship is used for indicating how much or what the difference between the attribute values corresponding to a sequence value is, and then the attribute information is considered to be acceptable; or, in the second specific implementation, the attribute information in the preset posterior mapping relationship is used to indicate how much or what the difference between the attribute values corresponding to a sequence of values is, and then the attribute information is considered to be unacceptable. The present application will be described with reference to a first specific embodiment as an example.
Specifically, after the difference data to be posterior is acquired in S101, whether the target sequence value exists is detected in the preset posterior mapping relationship. And if the target sequence value exists in the preset posterior mapping relation, determining that the difference of the plurality of target attribute values is unacceptable based on the attribute information corresponding to the target sequence value in the preset posterior mapping relation. Since the attribute information indicates an acceptable difference, it can be determined whether the difference between the target attribute values corresponding to the target sequence value is unacceptable according to the attribute information corresponding to the target sequence value.
Still taking the difference data produced by the old and new versions as an example, for score, the corresponding attribute information is "acceptable with a difference of less than 0.000001", and the difference between 123.987654 and 123.987655 is 0.000001, so that the difference is not acceptable; alternatively, if the corresponding attribute information is "acceptable with a difference of less than or equal to 0.000001" for score, the difference is acceptable at this time.
The results are shown in table 1, compared with the difference data produced by the conventional JSON Diff tool:
TABLE 1
And S103, outputting the target sequence value and the plurality of target attribute values.
Because only those differences that are not acceptable need to be correlated, upon determining at S102 that differences in the plurality of target attribute values are not acceptable, the target sequence value and the plurality of target attribute values are output for review by the operator.
In the embodiment of the application, firstly, difference data to be posteriori is obtained, wherein the difference data comprises a target sequence value and a plurality of target attribute values corresponding to the target sequence value; then, when a target sequence value exists in a preset posterior mapping relation, determining that the difference of a plurality of target attribute values is unacceptable based on attribute information corresponding to the target sequence value in the preset posterior mapping relation, wherein the preset posterior mapping relation comprises the mapping relation between the sequence value and the attribute information; finally, the target sequence value and the plurality of target attribute values are output. Due to the adoption of the method and the device, the posterior with unacceptable difference can be automatically completed, so that the labor can be saved, and the data posterior processing efficiency can be effectively improved.
In practical application, the difference data posterior method provided by the application can be used as a posterior expansion tool of a traditional JSON Diff tool, and a user configuration self-defining method is supported to complete posterior.
Based on the above embodiment, further, if there is no target sequence value in the preset posterior mapping relationship, the target sequence value and the plurality of target attribute values are output. At this time, the difference corresponding to the difference data comprising the target sequence value and the plurality of target attribute values corresponding thereto can be directly considered to be unacceptable, and is output for the operator to view.
Since the attribute information is artificially set, the specific technical means adopted when determining that the difference between the plurality of target attribute values is not acceptable is also different for different attribute information, and the following description is given by way of example with reference to fig. 2.
Fig. 2 is a schematic diagram according to a second embodiment of the present application. Referring to fig. 2, determining that the difference between the plurality of target attribute values is not acceptable based on the attribute information corresponding to the target sequence value in the preset posterior mapping relationship may further include:
s201, determining whether the difference value of any two target attribute values in the plurality of target attribute values meets a preset condition.
If the difference between any two of the target attribute values does not satisfy the preset condition, S202 is executed.
S202, determining that the difference of the target attribute values is not acceptable.
In this embodiment, the difference value of the attribute information corresponding to the target sequence value in the predetermined posterior mapping relationship satisfies the predetermined condition.
Optionally, the preset conditions include, but are not limited to, at least one of:
is less than a preset value;
is zero.
Wherein, the attribute information is different, and the corresponding preset conditions are also different. Even if the attribute information is the same, the corresponding preset conditions may be different according to the different persons who set the preset conditions. For example, for the attribute values expressed by numerical values, the meanings expressed by the attribute information being "the same", "must be the same", or "the difference value is zero" are the same, but the preset conditions respectively corresponding to the attribute values are different.
In some embodiments, the difference data posterior method may further include: and if the difference value of any two target attribute values in the plurality of target attribute values meets a preset condition, determining that the difference of the plurality of target attribute values is acceptable. The target sequence value and the plurality of target attribute values may also be output when the difference in the plurality of target attribute values is acceptable. That is, the difference data with acceptable difference and the difference data with unacceptable difference are output to form two data sets, and the user only needs to care about the data set with the difference data with unacceptable difference.
Further, for a data set of difference data for which the difference is acceptable, it may also be manually reconfirmed whether the difference is acceptable.
Fig. 3 is a schematic diagram according to a third embodiment of the present application. Referring to fig. 3, the difference data posterior method may include:
s301, difference data to be posteriori is obtained, and the difference data comprises a target sequence value and a plurality of target attribute values corresponding to the target sequence value.
S302, whether a target sequence value exists in a preset posterior mapping relation is detected.
If the target sequence value exists in the preset posterior mapping relation, executing S303; if the target sequence value does not exist in the predetermined a posteriori mapping relationship, S305 is executed.
S303, determining the data types of the target attribute values. If the data type is the list, executing S304; if the data type is a dictionary, the target attribute value with the data type as the dictionary is used as new difference data to be posterior for recursive processing, that is, returning to S301.
For a plurality of target attribute values with data types as lists, the corresponding difference data are exemplified as follows:
the preset posterior mapping relationship corresponding to the above example may be as follows:
that is, when the data types of the target attribute values are lists, the attribute information of the corresponding target sequence value includes wildcards. By way of example, wildcards may be represented as "+" or like symbols.
It is understood that if the sequence value is a field of difference data, the embodiment supports sub-fields and wildcards, so that a minimum granularity field can be posteriored, full-field posterior coverage capability is provided, and versatility is provided in a content processing service scenario.
S304, determining whether the difference of the target attribute values is unacceptable or not based on the attribute information corresponding to the target sequence value in the preset posterior mapping relation.
If the difference between the target attribute values is not acceptable, executing S305; if the difference of the target attribute values is acceptable, returning to S301, and acquiring new difference data to be posteriori.
S305, outputting a target sequence value and a plurality of target attribute values.
Based on the embodiment, all difference data are traversed, the difference data with unacceptable difference are output, automatic posterior of the difference data is realized, and posterior processing efficiency of the difference data is improved; in addition, the user can configure the personalized posterior method by himself, posterior fields can support different levels of gradients, the capacity of full-field posterior coverage is achieved, and the method has universality in a content processing service scene.
Fig. 4 is a schematic diagram according to a fourth embodiment of the present application. This embodiment provides a difference data posterior device. As shown in fig. 4, the difference data posterior device 400 includes: an acquisition module 401, a detection module 402, a determination module 403 and an output module 404. Wherein:
the obtaining module 401 is configured to obtain difference data to be subjected to a posteriori, where the difference data includes a target sequence value and a plurality of target attribute values corresponding to the target sequence value.
A detecting module 402, configured to detect whether a target sequence value exists in a preset posterior mapping relationship; and triggers the determining module 403 when the target sequence value exists in the preset posterior mapping relationship.
The determining module 403 is configured to determine that the difference between the multiple target attribute values is unacceptable based on the attribute information corresponding to the target sequence value in the preset posterior mapping relationship. The preset posterior mapping relation comprises a mapping relation between a sequence value and attribute information.
An output module 404 for outputting the target sequence value and the plurality of target attribute values.
The difference data posterior device provided in this embodiment may be used to implement the method embodiments described above, and its implementation and technical effects are similar, which are not described herein again.
In some embodiments, the determining module 403 may be specifically configured to:
determining whether the difference value of any two target attribute values in the plurality of target attribute values meets a preset condition, wherein the attribute information corresponding to the target sequence value in the preset posterior mapping relation is that the difference value meets the preset condition;
and when the difference value of any two target attribute values in the plurality of target attribute values does not meet the preset condition, determining that the difference of the plurality of target attribute values is not acceptable.
Optionally, the determining module 403 is further configured to: and when the difference value of any two target attribute values in the target attribute values meets a preset condition, determining that the difference of the target attribute values is acceptable.
Wherein the preset condition may include at least one of:
is less than a preset value;
is zero;
and so on.
Further, the determining module 403 may be further configured to: determining the data types of the target attribute values before determining that the difference of the target attribute values is unacceptable based on the attribute information corresponding to the target sequence values in the preset posterior mapping relation; and when the data type is a list, determining that the difference of the target attribute values is not acceptable based on the attribute information corresponding to the target sequence value in the preset posterior mapping relation.
Optionally, the determining module 403 may be further configured to: and when the data type is a dictionary, performing recursive processing by taking the target attribute value of which the data type is the dictionary as new difference data to be posterior.
In some embodiments, the detection module 402 may be further configured to: when the target sequence value does not exist in the preset posterior mapping relationship, the output module 404 is triggered to output the target sequence value and the plurality of target attribute values.
According to an embodiment of the present application, an electronic device and a readable storage medium are also provided.
Fig. 5 is a block diagram of an electronic device for implementing the difference data posterior method according to the embodiment of the present application. 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 present application that are described and/or claimed herein.
As shown in fig. 5, the electronic apparatus includes: one or more processors 501, memory 502, and interfaces for connecting the various components, including high-speed interfaces and low-speed interfaces. The various components are interconnected using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions for execution within the electronic device, including instructions stored in or on the memory to display graphical information of a GUI on an external input/output apparatus (such as a display device coupled to the interface). In other embodiments, multiple processors and/or multiple buses may be used, along with multiple memories, as desired. Also, multiple electronic devices may be connected, with each device providing portions of the necessary operations (e.g., as a server array, a group of blade servers, or a multi-processor system). In fig. 5, one processor 501 is taken as an example.
The memory 502, which is a non-transitory computer readable storage medium, may be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules (e.g., the acquisition module 401, the detection module 402, the determination module 403, and the output module 404 shown in fig. 4) corresponding to the difference data posterior method in the embodiments of the present application. The processor 501 executes various functional applications of the server and data processing, i.e., implementing the difference data posterior method in the above-described method embodiments, by running non-transitory software programs, instructions, and modules stored in the memory 502.
The memory 502 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created by use of an electronic device used to implement the difference data posterior method, and the like. Further, the memory 502 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, memory 502 optionally includes memory located remotely from processor 501, which may be connected via a network to an electronic device that performs the differential data posterior method. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The electronic device for implementing the differential data posterior method may further include: an input device 503 and an output device 504. The processor 501, the memory 502, the input device 503 and the output device 504 may be connected by a bus or other means, and fig. 5 illustrates the connection by a bus as an example.
The input device 503 may receive input numeric or character information and generate key signal inputs related to user settings and function control of the electronic apparatus, such as a touch screen, a keypad, a mouse, a track pad, a touch pad, a pointing stick, one or more mouse buttons, a track ball, a joystick, or other input devices. The output devices 504 may include a display device, auxiliary lighting devices (e.g., LEDs), and haptic feedback devices (e.g., vibrating motors), among others. The display device may include, but is not limited to, a Liquid Crystal Display (LCD), a Light Emitting Diode (LED) display, and a plasma display. In some implementations, the display device can be a touch screen.
Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, application specific ASICs (application specific integrated circuits), 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.
These computer programs (also known as programs, software applications, or code) include machine instructions for a programmable processor, and may be implemented using high-level procedural and/or object-oriented programming languages, and/or assembly/machine languages. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.
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.
Fig. 6 is a diagram of a scenario in which an embodiment of the present application may be implemented. As shown in fig. 6, the client 601 is configured to execute the difference data posterior method according to any of the above method embodiments, the server 602 interacts with the client 601, and after the server 602 executes the difference data posterior method, the server outputs the difference data with unacceptable difference to the client 601 for display.
In fig. 6, the client 601 is illustrated as a computer, but the embodiment of the present application is not limited thereto.
According to the technical scheme of the embodiment of the application, firstly, difference data to be posteriori is obtained, wherein the difference data comprises a target sequence value and a plurality of target attribute values corresponding to the target sequence value; then, when a target sequence value exists in a preset posterior mapping relation, determining that the difference of a plurality of target attribute values is unacceptable based on attribute information corresponding to the target sequence value in the preset posterior mapping relation, wherein the preset posterior mapping relation comprises the mapping relation between the sequence value and the attribute information; finally, the target sequence value and the plurality of target attribute values are output. Due to the adoption of the method and the device, the posterior with unacceptable difference can be automatically completed, so that the labor can be saved, and the data posterior processing efficiency can be effectively improved.
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 application may be executed in parallel, sequentially, or in different orders, and the present invention is not limited thereto as long as the desired results of the technical solutions disclosed in the present application can be achieved.
The above-described embodiments should not be construed as limiting the scope of the present application. 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 application shall be included in the protection scope of the present application.
Claims (16)
1. A method of posterior of difference data, comprising:
acquiring difference data to be posteriori, wherein the difference data comprises a target sequence value and a plurality of target attribute values corresponding to the target sequence value;
if the target sequence value exists in a preset posterior mapping relation, determining that the difference of the plurality of target attribute values is unacceptable based on attribute information corresponding to the target sequence value in the preset posterior mapping relation, wherein the preset posterior mapping relation comprises the mapping relation between the sequence value and the attribute information;
outputting the target sequence value and the plurality of target attribute values.
2. The method according to claim 1, wherein the determining that the difference of the plurality of target attribute values is not acceptable based on the attribute information corresponding to the target sequence value in the preset a posteriori mapping relationship comprises:
determining whether the difference value of any two target attribute values in the plurality of target attribute values meets a preset condition, wherein the attribute information corresponding to the target sequence value in the preset posterior mapping relation is that the difference value meets the preset condition;
and if the difference value of any two target attribute values in the target attribute values does not meet a preset condition, determining that the difference of the target attribute values is not acceptable.
3. The method of claim 2, further comprising:
and if the difference value of any two target attribute values in the target attribute values meets a preset condition, determining that the difference of the target attribute values is acceptable.
4. The method of claim 2, wherein the preset condition comprises at least one of:
is less than a preset value;
is zero.
5. The method according to claim 1, wherein before determining that the difference between the plurality of target attribute values is not acceptable based on the attribute information corresponding to the target sequence value in the preset a posteriori mapping relationship, the method further comprises:
determining a data type of the plurality of target attribute values;
and if the data type is a list, executing the attribute information corresponding to the target sequence value in the preset posterior mapping relation, and determining that the difference of the target attribute values is not acceptable.
6. The method of claim 5, further comprising:
and if the data type is a dictionary, performing recursive processing by taking the target attribute value of which the data type is the dictionary as new difference data to be subjected to posterior.
7. The method of any of claims 1 to 6, further comprising:
and if the target sequence value does not exist in the preset posterior mapping relation, outputting the target sequence value and the plurality of target attribute values.
8. A differential data posterior device comprising:
the system comprises an acquisition module, a verification module and a verification module, wherein the acquisition module is used for acquiring difference data to be posteriori, and the difference data comprises a target sequence value and a plurality of target attribute values corresponding to the target sequence value;
the detection module is used for detecting whether the target sequence value exists in a preset posterior mapping relation; when the target sequence value exists in the preset posterior mapping relation, a determining module is triggered to determine that the difference of the target attribute values is unacceptable based on the attribute information corresponding to the target sequence value in the preset posterior mapping relation, wherein the preset posterior mapping relation comprises the mapping relation between the sequence value and the attribute information;
an output module for outputting the target sequence value and the plurality of target attribute values.
9. The apparatus of claim 8, wherein the determining module is specifically configured to:
determining whether the difference value of any two target attribute values in the plurality of target attribute values meets a preset condition, wherein the attribute information corresponding to the target sequence value in the preset posterior mapping relation is that the difference value meets the preset condition;
and when the difference value of any two target attribute values in the target attribute values does not meet a preset condition, determining that the difference of the target attribute values is not acceptable.
10. The apparatus of claim 9, the determination module further to:
and when the difference value of any two target attribute values in the target attribute values meets a preset condition, determining that the difference of the target attribute values is acceptable.
11. The apparatus of claim 9, the preset condition comprising at least one of:
is less than a preset value;
is zero.
12. The apparatus of claim 8, the determination module further to:
determining the data types of the target attribute values before determining that the difference of the target attribute values is not acceptable based on the attribute information corresponding to the target sequence values in the preset posterior mapping relation;
and when the data type is a list, executing the attribute information corresponding to the target sequence value in the preset posterior mapping relation, and determining that the difference of the target attribute values is not acceptable.
13. The apparatus of claim 12, the determination module further to:
and when the data type is a dictionary, performing recursive processing by taking the target attribute value of which the data type is the dictionary as new difference data to be subjected to posterior.
14. The apparatus of any of claims 8 to 13, the detection module to further:
and when the target sequence value does not exist in the preset posterior mapping relation, triggering the output module to output the target sequence value and the plurality of target attribute values.
15. 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 to 7.
16. 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 to 7.
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