CN113961610A

CN113961610A - Data processing method, device, equipment and storage medium

Info

Publication number: CN113961610A
Application number: CN202111272032.3A
Authority: CN
Inventors: 张少昂; 牛雅哲; 刘宇
Original assignee: Beijing Sensetime Technology Development Co Ltd
Current assignee: Beijing Sensetime Technology Development Co Ltd
Priority date: 2021-10-29
Filing date: 2021-10-29
Publication date: 2022-01-21

Abstract

The present disclosure provides a data processing method, apparatus, device, and storage medium, which may acquire service data reported by a service system, and add a timestamp corresponding to a time identification mode to each data item in the service data according to a setting of a user and/or a service type of the reported data, so that the data item and the timestamp are stored in a data pair form, and further, the data item may be processed corresponding to a processing operation. Like this, can provide different time identification modes, realize adding suitable timestamp to the business data that have the relevance, make different business data keep business logical unified, and multinomial data can keep logical order on the unanimity, so that realize carrying out unified management, maintenance and processing to the data that have the business relevance, help reducing data management cost, improve data management's convenient degree and accuracy, be favorable to improving the efficiency of intelligent decision optimization analysis, reduce the cost of artificial intelligence, improve artificial intelligence's efficiency.

Description

Data processing method, device, equipment and storage medium

Technical Field

The present disclosure relates to the field of computer technologies, and in particular, to a data processing method, apparatus, device, and storage medium.

Background

Following the industrialized era and the information era, people have completely entered the information era, and with the continuous development of computer technology, especially with the sufficient progress in the fields of internet of things, artificial intelligence, block chains, cloud platforms, big data and the like, the data volume increases in number, how to perform stable, effective, convenient, fast and accurate management and processing on increasingly increasing data gradually becomes a difficult problem to be solved, especially in the advanced technical field with intelligent sensing, intelligent computing and intelligent decision making capabilities such as artificial intelligence, the requirements on the aspects of rapidity, accuracy, convenience and the like of data processing are particularly outstanding.

No matter in artificial intelligence or other intelligent fields, a large amount of data can be generated and used in each link of intelligent perception, intelligent calculation and intelligent decision, and for management and maintenance of data and the like, professionals are mostly required to configure the data according to different data to realize storage and management of the data, each type of data is mostly required to be configured independently, logic dispersion among all data is caused, a large amount of preprocessing is required during subsequent use, the processing logic is complex, the workload is high, a large amount of computing resources are required to be consumed, and the data processing efficiency is low.

Disclosure of Invention

The embodiment of the disclosure at least provides a data processing method, a device, equipment and a storage medium.

The embodiment of the disclosure provides a data processing method, which comprises the following steps:

acquiring reported data, wherein the reported data comprises at least one reported service data, and the service data comprises a plurality of data items;

adding a timestamp corresponding to a time identification mode to each data item in the service data according to the setting of a user and/or the service type of the reported data, wherein the time identification mode comprises a natural time mode and a stepping time mode;

storing the data item and the timestamp added for the data item in a data pair form to a storage position corresponding to the service data;

and responding to the processing operation of the user for the data item, and performing processing corresponding to the processing operation on the data item.

Like this, can provide different time identification modes, realize adding suitable timestamp to the business data that have the relevance, make different business data keep business logical unified, and multinomial data can keep logical order on the unanimity, so that realize carrying out unified management, maintenance and processing to the data that have the business relevance, help reducing data management cost, improve data management's convenient degree and accuracy, be favorable to improving the efficiency of intelligent decision optimization analysis, reduce the cost of artificial intelligence, improve artificial intelligence's efficiency.

In an optional embodiment, the storing the data item and the timestamp added to the data item in a data pair form to a storage location corresponding to the service data includes:

generating a data storage queue for storing the service data for each type of the service data;

and writing the data items of the service data and the time stamps added to the data items into the corresponding data storage queues in a data pair mode.

In this way, the data items of the service data and the timestamps added to the data items can be written into the corresponding data storage queues in the form of data pairs, so that the data items of the same service data under different information dimensions are presented, and the data items of the service data can be conveniently processed subsequently.

In an optional embodiment, after storing the data item and the timestamp added to the data item in a data pair form to a storage location corresponding to the service data, the method includes:

acquiring a preset time window length of the data stored in the storage position, wherein the preset time window length is a preset time stamp span between a first time stamp of a first data item and a last time stamp of a last data item in a plurality of data items which can be stored in the storage position;

determining a current time window length of the stored data at the storage location after writing the data item and the timestamp to the storage location, wherein the current time window length is a current timestamp span between the first timestamp and the timestamp currently being written;

and if the current timestamp span is larger than the preset timestamp span, deleting the part of the timestamps stored in advance and the data items corresponding to the part of the timestamps according to the sequence of the timestamps stored in the storage position in the time dimension.

Therefore, when the storage data at the storage position is excessive, the deletion processing can be carried out in time, the safety of data processing is ensured, and the possibility of application crash is reduced.

In an optional implementation manner, the performing, in response to a processing operation on the data item by a user, processing the data item corresponding to the processing operation includes:

in response to a query operation of a user for the data item, the data item corresponding to the query operation and the timestamp corresponding to the data item are presented to the user.

Therefore, under the condition that the user has query requirements on the data items, the query requirements of the user can be realized, the data items needing to be queried and the timestamps corresponding to the data items are displayed to the user, and the data processing capacity is richer.

In an optional implementation manner, when the service data is data in a step time mode, in response to a query operation performed by a user on the data item, the presenting, to the user, the data item corresponding to the query operation and the timestamp corresponding to the data item, further includes:

responding to a query operation of a user for the data item, and acquiring a query time window set by the user, wherein the query time window comprises at least one stepping time unit;

and displaying the data items of which the time stamps are positioned under the query time window to the user according to the query time window set by the user.

Therefore, when the service data is data in the step time mode, under the condition that a user has a query requirement on the data item, the timestamp positioned under the query time window can be determined through the setting of the query time window, and then the data corresponding to the timestamp can be quickly positioned through the timestamp and displayed to the user.

In an optional embodiment, the method further comprises:

acquiring at least one preset stepping time unit which is adjusted according to the query time window;

based on forward operation and/or backward operation of a user for the query time window, adjusting the query time window by the forward operation and/or backward operation for the at least one stepping time unit;

and displaying the data items with the time stamps under the adjusted query time window in the data items stored at the storage position to a user according to the adjusted query time window.

Therefore, when the service data is data in the step time mode, the step time mode adds the timestamp based on the abstract discrete time of the service, so that the step jump of the timestamp can be realized based on the characteristics, the sequential query is not needed, the direct positioning is realized, the data display is convenient for a user, and the query speed and efficiency are improved.

when an assignment instruction for the data item is received, acquiring a data value of a target data item corresponding to the assignment instruction in the data item stored in the storage position at the current time;

and adjusting the data value corresponding to the target data item to the target value indicated by the assignment instruction.

Therefore, the requirement of modifying the numerical value of the data item stored in the storage position by a user can be met, the data item can be suitable for various service logics, and the subsequent processing is more flexible.

In an optional embodiment, the method further comprises:

determining at least one first statistical condition for the business data in response to a first statistically observed need input by a user;

generating statistical information of the traffic data based on the at least one first statistical condition and a plurality of the data items and the corresponding timestamps stored at the storage location.

Therefore, the user can customize the statistical observation requirement for the service data, and the statistical information of the service data can be generated by combining the plurality of data items stored in the storage position and the corresponding timestamps, so that the service data can be subjected to secondary processing, the statistical information required by the user can be obtained, and the usability and the practicability of the data items can be improved.

In an optional embodiment, after the generating statistical information of the traffic data based on the at least one first statistical condition and the plurality of data items and the corresponding timestamps stored at the storage location, the method further comprises:

responding to a second statistical observation requirement input by a user, and determining at least one second statistical condition aiming at least one service data and the time identification mode corresponding to a statistical result;

and determining a statistical result of at least one service data based on the at least one second statistical condition and the statistical information of each service data, and adding a timestamp of the time identification mode corresponding to the statistical result.

Therefore, the data in the statistical information can be further screened and sorted to obtain the statistical result which aims at the second statistical observation requirement and realizes effective dynamic observation, furthermore, different business logics can be utilized for statistics, the statistical result which is different from the data in the statistical information in the arrangement sequence and the time identification mode can be obtained, the complex statistical observation requirement can be supported, and the business data can be conveniently processed by a user.

An embodiment of the present disclosure further provides a data processing apparatus, where the apparatus includes:

an obtaining module, configured to obtain reporting data, where the reporting data includes at least one reported service data, and the service data includes multiple data items;

the adding module is used for adding a timestamp corresponding to a time identification mode to each data item in the service data according to the setting of a user and/or the service type of the reported data, wherein the time identification mode comprises a natural time mode and a stepping time mode;

the storage module is used for storing the data items and the data items of the timestamps added to the data items to storage positions corresponding to the service data in a data pair form;

and the processing module is used for responding to the processing operation of the user on the data item and carrying out processing corresponding to the processing operation on the data item.

In an optional implementation manner, the storage module is specifically configured to:

In an optional implementation manner, the apparatus further includes a deletion module, where the deletion module is configured to:

In an optional implementation manner, the processing module is specifically configured to:

In an optional implementation manner, when the processing module is configured to, when the service data is data in a step time mode, respond to a query operation of a user on the data item, and present the data item corresponding to the timestamp to the user, the processing module is specifically configured to:

In an optional embodiment, the processing module is further configured to:

In an optional embodiment, the apparatus further comprises a statistics module, the statistics module is configured to:

In an optional embodiment, the statistics module, after the generating statistics of the traffic data based on the at least one first statistics condition and the plurality of data items and the corresponding timestamps stored at the storage location, is further configured to:

An embodiment of the present disclosure further provides a computer device, including: the data processing system comprises a processor, a memory and a bus, wherein the memory stores machine readable instructions executable by the processor, the processor and the memory are communicated through the bus when a computer device runs, and the machine readable instructions are executed by the processor to execute the steps in the data processing method.

The embodiment of the present disclosure also provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program executes the steps in the data processing method.

The data processing method, the data processing device, the data processing equipment and the storage medium provided by the embodiment of the disclosure can acquire the service data reported by the service system, and add the timestamp corresponding to the time identification mode to each data item in the service data according to the setting of a user and/or the service type of the reported data, so that the data items and the timestamps are stored in a data pair form, and further, the data items can be processed corresponding to the processing operation.

In order to make the aforementioned objects, features and advantages of the present disclosure more comprehensible, preferred embodiments accompanied with figures are described in detail below.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings required for use in the embodiments will be briefly described below, and the drawings herein incorporated in and forming a part of the specification illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the technical solutions of the present disclosure. It is appreciated that the following drawings depict only certain embodiments of the disclosure and are therefore not to be considered limiting of its scope, for those skilled in the art will be able to derive additional related drawings therefrom without the benefit of the inventive faculty.

FIG. 1 is a schematic diagram of a data management system provided by an embodiment of the present disclosure;

FIG. 2 is a flow chart illustrating a data processing method provided by an embodiment of the present disclosure;

FIG. 3 is a flow chart illustrating another data processing method provided by an embodiment of the present disclosure;

FIG. 4 shows one of the schematic diagrams of a data processing apparatus provided by the embodiments of the present disclosure;

fig. 5 shows a second schematic diagram of a data processing apparatus provided in the embodiment of the present disclosure;

fig. 6 shows a schematic diagram of a computer device provided by an embodiment of the present disclosure.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present disclosure more clear, the technical solutions of the embodiments of the present disclosure will be described clearly and completely with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are only a part of the embodiments of the present disclosure, not all of the embodiments. The components of the embodiments of the present disclosure, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present disclosure, presented in the figures, is not intended to limit the scope of the claimed disclosure, but is merely representative of selected embodiments of the disclosure. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the disclosure without making creative efforts, shall fall within the protection scope of the disclosure.

It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.

The term "and/or" herein merely describes an associative relationship, meaning that three relationships may exist, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the term "at least one" herein means any one of a plurality or any combination of at least two of a plurality, for example, including at least one of A, B, C, and may mean including any one or more elements selected from the group consisting of A, B and C.

Research shows that, at present, no matter in the field of artificial intelligence or other intelligence, for example, a large amount of data can be generated and used in each link of perception intelligence, intelligent calculation, decision intelligence and the like, for management, maintenance and the like of the data, most of the data need professionals to be configured aiming at different data to realize storage and management of the data, and most of each kind of data need to be configured independently, so that logic dispersion among the data is caused, a large amount of preprocessing is needed during subsequent use, the processing logic is complex, the workload is large, a large amount of computing resources need to be consumed, and the data processing efficiency is low.

Based on the above research, the present disclosure provides a data processing method, which may obtain service data reported by a service system, and add a timestamp corresponding to a time identification mode to each data item in the service data according to a setting of a user and/or a service type of the reported data, so that the data item and the timestamp are stored in a data pair form, and further, the data item may be processed corresponding to a processing operation. Like this, can provide different time identification modes, realize adding suitable timestamp to the business data that have the relevance, make different business data keep business logical unified, and multinomial data can keep logical order on the unanimity, so that realize carrying out unified management, maintenance and processing to the data that have the business relevance, help reducing data management cost, improve data management's convenient degree and accuracy, be favorable to improving the efficiency of intelligent decision optimization analysis, reduce the cost of artificial intelligence, improve artificial intelligence's efficiency.

The above-mentioned drawbacks are the results of the inventor after practical and careful study, and therefore, the discovery process of the above-mentioned problems and the solutions proposed by the present disclosure to the above-mentioned problems should be the contribution of the inventor in the process of the present disclosure.

To facilitate understanding of the present embodiment, first, a data processing method disclosed in the embodiments of the present disclosure is described in detail, where an execution subject of the data processing method provided in the embodiments of the present disclosure is generally a computer device with certain computing capability, and the computer device includes, for example: terminal equipment or servers or other processing devices. In some possible implementations, the data processing method may be implemented by a processor calling computer readable instructions stored in a memory.

The following describes a data processing method provided by the embodiments of the present disclosure by taking an execution subject as a server.

Referring to fig. 1, fig. 1 is a schematic diagram of a data management system according to an embodiment of the disclosure. In order to assist intelligent decision analysis and optimize a data processing method, a data management system for realizing uniform intelligent processing on data with business association in the same business system can be set up. As shown in fig. 1, the data management system includes a time subsystem and a data subsystem, the time subsystem includes a natural time system and a step time system, the data subsystem comprises a data storage system and an observation statistical system, and the time subsystem, the time stamp of the same time identification mode can be added to different data with potential relevance or direct business relevance in the same business system, so that the continuous time based on nature and the abstract discrete time based on business form logic unification, and the data subsystem, different data with potential relevance or direct business relevance in the same business system can be uniformly stored, secondary processing can be carried out according to the observation statistical requirements of all data, and the different data with potential relevance or direct business relevance form business logic consistency.

In the process of data management, for different data, for example, reported data reported by different devices or users and aiming at different service contents, such as log data uploaded by the devices and collected video data, each type of reported data can be generated for the data management system in the data management system when being received for the first time, then an independent meta-model for managing the reported data is created based on the generated class, and a timestamp corresponding to a time identification mode can be configured for the meta-model through a time subsystem, further, for various service data contained in the reported data, a plurality of data storage queues can be created under the meta-model, each data storage queue is used for storing a plurality of data items in one type of service data and corresponding timestamps, so that the related data items share the same time axis, and the business logic sequence is kept consistent.

Referring to fig. 2, fig. 2 is a flowchart of a data processing method according to an embodiment of the disclosure. The data processing method provided by the embodiment of the disclosure can be applied to a data management system as shown in fig. 1. As shown in fig. 2, a data processing method provided by the embodiment of the present disclosure includes:

s201: the method comprises the steps of obtaining reported data, wherein the reported data comprise at least one type of reported service data, and the service data comprise a plurality of data items.

The service data may be data generated in a service system based on a certain service link. The different types of service data may refer to data in different information dimensions in the report data of the same service, for example, in the report data generated by the image recognition service, the information dimensions may be division factors such as a picture size and a picture brightness dimension.

In the data processing process, the service data of only one service system may be obtained, or the service data of multiple service systems may be obtained simultaneously, which is not limited herein.

The service data can be acquired from the service system based on the interface provided by the data subsystem in the data management system and capable of being connected with the service system, so that subsequent processing can be performed.

S202: and adding a timestamp corresponding to a time identification mode to each data item in the service data according to the setting of a user and/or the service type of the reported data, wherein the time identification mode comprises a natural time mode and a stepping time mode.

In this step, after the service data is obtained, in order to facilitate management of multiple data items of the service data in different information dimensions, a timestamp may be added to each data item in the service data, so that a time identification mode corresponding to the service data needs to be determined.

The timestamp of the natural time mode may be a floating point ewing timestamp set in seconds for the current time of acquiring the data item based on the continuous time in the natural sense.

The timestamp of the step time mode may be based on discrete time in service logic, and a timestamp representing current service time is set for a current service logic cycle in which the data item is obtained, such as the number of times corresponding to each data item in the last several training iterations.

Illustratively, it is suitable to add a time stamp of said natural time pattern for the temperature data in the room and a time stamp of said step time pattern for the work schedule data of the machine, such as the number of parts to be machined per work cycle.

According to the two time identification modes provided by the time subsystem in the data management system, a time stamp corresponding to a natural time mode or a stepping time mode can be added to each data item in the service data according to the time identification mode corresponding to each data item in the service data, so that the logic unification is realized based on the natural continuous time and the abstract discrete time based on the service, the associated data items share the same time axis, and the data items are consistent in the service logic sequence.

S203: and storing the data item and the timestamp added for the data item in a data pair form to a storage position corresponding to the service data.

In this step, after adding a timestamp corresponding to a time identification pattern to each data item in the service data, the data item and the timestamp added to the data item may be stored in a data pair format in a storage location corresponding to the service data, and then the data stored in the storage location may be processed.

The storage location may reside in a server for performing data processing, may be a wireless cloud based on the server for performing data processing, may be a virtual server hosted by a third party, and may be backed up on a memory card or a storage hard disk, which is not limited herein.

In a data subsystem of the data management system, a class can be generated for each type of service data, and then an independent meta-model for managing reported data is created based on the generated class, so that the data items in the service data can be stored based on the meta-model, and the storage of the service data is realized.

S204: and responding to the processing operation of the user for the data item, and performing processing corresponding to the processing operation on the data item.

In this step, when a processing operation of the user on the data item already stored in the storage location is received, the processing corresponding to the processing operation may be performed on the data item in response to the processing operation of the user on the data item, so as to implement intelligent data processing.

The processing operation may be a query operation, a filtering operation, a statistical operation, a calculating operation, an analyzing operation, and the like of the user on the data item, which is not limited herein.

The data processing method provided by the embodiment of the disclosure can acquire reported data, wherein the reported data includes at least one type of reported service data, and the service data includes a plurality of data items; adding a timestamp corresponding to a time identification mode to each data item in the service data according to the setting of a user and/or the service type of the reported data, wherein the time identification mode comprises a natural time mode and a stepping time mode; storing the data item and the timestamp added for the data item in a data pair form to a storage position corresponding to the service data; and responding to the processing operation of the user for the data item, and performing processing corresponding to the processing operation on the data item.

Referring to fig. 3, fig. 3 is a flowchart of another data processing method according to an embodiment of the disclosure. As shown in fig. 3, a data processing method provided by the embodiment of the present disclosure includes:

s301: the method comprises the steps of obtaining reported data, wherein the reported data comprise at least one type of reported service data, and the service data comprise a plurality of data items.

S302: and adding a timestamp corresponding to a time identification mode to each data item in the service data according to the setting of a user and/or the service type of the reported data, wherein the time identification mode comprises a natural time mode and a stepping time mode.

S303: and storing the data item and the timestamp added for the data item in a data pair form to a storage position corresponding to the service data.

S304: acquiring a preset time window length of the data stored in the storage position, wherein the preset time window length is a preset time stamp span between a first time stamp of a first data item and a last time stamp of a last data item in a plurality of data items which can be stored in the storage position.

In this step, after determining a storage location for storing the service data, a first timestamp of a first data item and a last timestamp of a last data item in the plurality of data items that can be stored in the storage location may be obtained, and when the first timestamp and the last timestamp are determined, a preset timestamp span between the first timestamp and the last timestamp may be determined, and the preset timestamp span is used as a preset time window length of the data stored in the storage location.

S305: determining a current time window length of the stored data at the storage location after writing the data item and the timestamp to the storage location, wherein the current time window length is a current timestamp span between the first timestamp and the timestamp currently being written.

In this step, a current data processing condition may be detected in real time to determine a condition of data stored at the storage location, a first timestamp of a first data item of a plurality of data items currently stored at the storage location and the timestamp of the currently written data item may be acquired when the data item and the timestamp are written into the storage location, a current timestamp span between the first timestamp and the currently written timestamp may be determined when the first timestamp and the currently written timestamp are determined, and the current timestamp span may be used as a current time window length of the data stored at the storage location.

S306: and if the current timestamp span is larger than the preset timestamp span, deleting the part of the timestamps stored in advance and the data items corresponding to the part of the timestamps according to the sequence of the timestamps stored in the storage position in the time dimension.

In this step, if the current timestamp span is greater than the preset timestamp span, the storage location may generate an abnormal condition, so that the current time window length of the data stored in the storage location may be detected in real time, and if the current time window length is greater than the preset time window length, that is, if the current timestamp span is greater than the preset timestamp span, according to the chronological order of the timestamps stored in the storage location in the time dimension, the previously stored part of the timestamps and the data items corresponding to the part of the timestamps may be deleted, so as to ensure the security of the data processing.

S307: and responding to the processing operation of the user for the data item, and performing processing corresponding to the processing operation on the data item.

The descriptions of steps S301 to S303 and S307 may refer to the descriptions of steps S201 to S204, and the same technical effect and the same technical problem may be achieved, which are not described herein again.

Next, this embodiment will be further described with reference to some specific embodiments.

In some possible embodiments, step S303 includes:

In this step, after adding a timestamp corresponding to a time identification pattern to each data item in the service data, it is necessary to determine storage locations of the data item and the timestamp added to the data item, and a data storage queue for storing the service data may be generated for each type of the service data, so that the data item of the service data and the timestamp added to the data item are written into the corresponding data storage queue in a data pair form.

The data pairs in the data storage queue are arranged in a certain order, for example, in a time order, a spatial order, a logical order, an orientation order, and the like, which is not limited herein.

The method comprises the steps of generating a class for each type of service data in a data subsystem in a data management system, setting data items which need to be stored and are included by the service data in the class, creating an independent meta-model for managing reported data based on the generated class, creating a plurality of data storage queues under the meta-model for a plurality of types of service data included in the reported data, wherein each data storage queue is used for storing a plurality of data items in one type of service data and corresponding timestamps, and further storing the reported data.

In some possible embodiments, step S307 includes:

In this step, when a query operation of the user on the data item is detected, the data item corresponding to the query operation and the timestamp corresponding to the data item may be determined in response to the query operation of the user, and then the data item corresponding to the query operation and the timestamp corresponding to the data item may be presented to the user.

In some possible embodiments, when the business data is data in a step time mode, the presenting, to a user, the data item corresponding to a query operation and the timestamp corresponding to the data item in response to the query operation on the data item by the user further includes:

In this step, when the service data is data in a step time mode, and when a query operation of a user for the data item is detected, a query time window including at least one step time unit set by the user may be obtained in response to the query operation of the user, and based on the query time window set by the user, the data item whose timestamp is located under the query time window may be determined, and the data item whose timestamp is located under the query time window may be displayed to the user.

For example, in the case that the service data is the number of parts processed by the machine in each work cycle, the user wants to inquire the processing number of the parts, and if the inquiry time window is set to be a step unit, the processing number of the parts in the first work cycle is displayed to the user.

Further, in some possible embodiments, the method further includes:

In this step, when the service data is data in a step time mode, due to the discrete characteristic of the step time mode, a user may query a data item in a time forward and time backward adjustment manner, may first obtain at least one preset step time unit adjusted for the query time window, then obtain a forward operation and/or a backward operation of the user for the query time window, adjust the query time window according to the forward operation and/or the backward operation and the adjusted at least one preset step time unit, and thereby determine, based on the adjusted query time window, the data item whose timestamp is located under the adjusted query time window in the data items stored at the storage location, the data items with the timestamps below the adjusted query time window may then be presented to a user.

For example, in the case that the service data is the number of parts processed by the machine in each working cycle, the user wants to query the processing number of the parts, originally sets the query time window as one step unit, displays the processing number of the parts in the first working cycle to the user, and displays the processing number of the parts in the third working cycle to the user when the query time window is adjusted to advance by two step units by the user.

In a data subsystem in the data management system, time advance and time retreat can be performed on data in a step time mode based on step time units, and as long as the number of step time units is set, the current business time can be advanced or retreated by the number of step time units, so that the number of step time units to be adjusted can be set for the query time window, and the query time window is adjusted by the number of step time units according to the forward operation or the backward operation to obtain the adjusted query time window, so that the data item with the timestamp under the adjusted query time window, which is stored at the storage position, can be displayed to a user.

In some possible embodiments, step S307 includes:

In this step, in some cases, secondary modification needs to be performed on the data item, and when an assignment instruction for the data item is detected, a data item corresponding to the assignment instruction may be determined as a target data item, so as to obtain a data value of the target data item at the current time from the data items stored at the storage location, and then, based on the assignment instruction, a target value indicated by the assignment instruction is determined, and the data value of the target data item at the current time is replaced by the target value, so that the data value corresponding to the target data item is adjusted to the target value indicated by the assignment instruction.

For example, in the case that the service data is the number of parts machined by the machine in each work cycle, a number of parts machined in the first work cycle is stored in the storage location, and when an assignment instruction for adjusting the number of parts machined in the first work cycle to b is received, the number of parts machined in the first work cycle stored in the storage location is adjusted from a number to b number.

In some possible embodiments, the method further comprises:

In this step, in some cases, further statistics and calculations need to be performed on the data items, and at least one first statistical condition for the business data may be resolved in response to a first statistical observation requirement input by a user in a case where the first statistical observation requirement is detected, so that statistical information of the business data may be generated based on the at least one first statistical condition, a plurality of data items stored at the storage location, and the corresponding timestamps.

For example, in the case where the service data is the number of parts processed by the machine per work cycle, it is detected that the first statistical observation requirement input by the user is an average number of parts processed per two work cycles, and the first statistical condition may be obtained by calculating an average number of parts processed per two work cycles, and generating the statistical information based on the number of parts processed per work cycle stored at the storage location.

The data items and the corresponding timestamps stored at the storage positions can be counted through an observation and statistics system included in a data subsystem in a data management system, so that under the condition that the first statistical observation requirement is received, secondary processing can be performed on the data items in response to the first statistical observation requirement, and the statistical information of the business data is generated.

Further, in some possible embodiments, after the generating statistical information of the traffic data based on the at least one first statistical condition and the plurality of data items and the corresponding timestamps stored at the storage location, the method further includes:

In this step, in some cases, secondary analysis and screening may be performed on the data items, and when a second statistical observation requirement input by a user is detected, at least one second statistical condition for the service data may be obtained through parsing in response to the second statistical observation requirement, and the time identification pattern corresponding to a statistical result obtained based on the at least one second statistical condition may be obtained, so that a statistical result of at least one service data may be determined based on the at least one second statistical condition and statistical information of each service data, and a time stamp of the time identification pattern corresponding to the statistical result is added to the statistical result.

Wherein, based on the second statistical condition, the timestamp of the natural time mode may be converted into the timestamp of the step time mode, and the timestamp of the step time mode may also be converted into the timestamp of the natural time mode.

Further, based on the second statistical condition, the arrangement order of the data items in the statistical result may also be changed compared to the statistical information.

Illustratively, the data items and the arrangement order in the statistical information are a, b, c, d, and each data item adds a timestamp of a natural time pattern, after the second statistical condition is filtered, the data items and the arrangement order in the obtained statistical result are c, a, d, b, and each data item is adjusted to add a timestamp of a step time pattern.

Therefore, data in the statistical information can be further screened and sorted to obtain a statistical result which is different from the data in the statistical information in the arrangement sequence and the time identification mode, so that the effective dynamic observation is realized aiming at the second statistical observation requirement.

The data processing method provided by the embodiment of the disclosure can acquire the service data reported by the service system, and add the timestamp corresponding to the time identification mode to each data item in the service data according to the setting of the user and/or the service type of the reported data, so that the data items and the timestamps are stored in a data pair form, and further, the data items can be processed corresponding to the processing operation. Like this, can provide different time identification modes, realize adding suitable timestamp to the business data that have the relevance, make different business data keep business logical unified, and multinomial data can keep logical order on the unanimity, so that realize carrying out unified management, maintenance and processing to the data that have the business relevance, help reducing data management cost, improve data management's convenient degree and accuracy, be favorable to improving the efficiency of intelligent decision optimization analysis, reduce the cost of artificial intelligence, improve artificial intelligence's efficiency.

It will be understood by those skilled in the art that in the method of the present invention, the order of writing the steps does not imply a strict order of execution and any limitations on the implementation, and the specific order of execution of the steps should be determined by their function and possible inherent logic.

Based on the same inventive concept, a data processing apparatus corresponding to the data processing method is also provided in the embodiments of the present disclosure, and because the principle of the apparatus in the embodiments of the present disclosure for solving the problem is similar to the data processing method described above in the embodiments of the present disclosure, the implementation of the apparatus may refer to the implementation of the method, and repeated details are not described again.

Referring to fig. 4 and fig. 5, fig. 4 is a first schematic diagram of a data processing apparatus according to an embodiment of the disclosure, and fig. 5 is a second schematic diagram of a data processing apparatus according to an embodiment of the disclosure. The data processing apparatus provided in the embodiment of the present disclosure is applied to the above data management system, the data processing apparatus and the data management system may be the same apparatus under different names, the data processing apparatus may also be a part of the data management system, and a module in the data processing apparatus and a subsystem of a corresponding function in the data management system may be coupled together to jointly implement the same function, as shown in fig. 4, the data processing apparatus 400 provided in the embodiment of the present disclosure includes:

an obtaining module 410, configured to obtain reporting data, where the reporting data includes at least one reported service data, and the service data includes multiple data items.

An adding module 420, configured to add a timestamp corresponding to a time identifier mode to each data item in the service data according to a setting of a user and/or a service type of the reported data, where the time identifier mode includes a natural time mode and a step time mode.

A storage module 430, configured to store the data item and the data item of the timestamp added to the data item in a data pair form to a storage location corresponding to the service data.

The processing module 440 is configured to, in response to a processing operation performed by a user on the data item, perform processing corresponding to the processing operation on the data item.

In an optional implementation manner, the storage module 430 is specifically configured to:

In an optional implementation manner, the processing module 440 is specifically configured to:

In an optional implementation manner, when the processing module 440 is configured to, when the service data is data in a step time mode, and in response to a query operation of a user on the data item, present the data item corresponding to the timestamp to the user, specifically:

In an optional implementation, the processing module 440 is further configured to:

In an alternative embodiment, the apparatus further comprises a deletion module 450 and a statistics module 460.

The deletion module 450 is configured to:

The statistics module 460 is configured to:

In an optional embodiment, the statistics module 460 is further configured to, after the generating of the statistics of the traffic data based on the at least one first statistics condition and the plurality of data items and the corresponding timestamps stored at the storage location,:

The description of the processing flow of each module in the device and the interaction flow between the modules may refer to the related description in the above method embodiments, and will not be described in detail here.

The data processing apparatus provided in the embodiment of the present disclosure may acquire service data reported by a service system, and add a timestamp corresponding to a time identifier mode to each data item in the service data according to a setting of a user and/or a service type of the reported data, so that the data item and the timestamp are stored in a data pair form, and further, the data item may be processed corresponding to a processing operation. Like this, can provide different time identification modes, realize adding suitable timestamp to the business data that have the relevance, make different business data keep business logical unified, and multinomial data can keep logical order on the unanimity, so that realize carrying out unified management, maintenance and processing to the data that have the business relevance, help reducing data management cost, improve data management's convenient degree and accuracy, be favorable to improving the efficiency of intelligent decision optimization analysis, reduce the cost of artificial intelligence, improve artificial intelligence's efficiency.

Corresponding to the data processing methods in fig. 2 and fig. 3, an embodiment of the present disclosure further provides a computer device 600, as shown in fig. 6, a schematic structural diagram of the computer device 600 provided in the embodiment of the present disclosure includes:

a processor 610, a memory 620, and a bus 630; the storage 620 is used for storing execution instructions and includes a memory 621 and an external storage 622; the memory 621 is also referred to as an internal memory, and is used for temporarily storing operation data in the processor 610 and data exchanged with an external memory 622 such as a hard disk, the processor 610 exchanges data with the external memory 622 through the memory 621, and when the computer device 600 operates, the processor 610 and the memory 620 communicate through the bus 630, so that the processor 610 can execute the steps of the data processing method.

The embodiments of the present disclosure also provide a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to perform the steps of the data processing method described in the above method embodiments. The storage medium may be a volatile or non-volatile computer-readable storage medium.

An embodiment of the present disclosure further provides a computer program product, where the computer program product includes computer instructions, and the computer instructions, when executed by a processor, may perform the steps of the data processing method in the foregoing method embodiment, which may be referred to specifically for the foregoing method embodiment, and are not described herein again.

The computer program product may be implemented by hardware, software or a combination thereof. In an alternative embodiment, the computer program product is embodied in a computer storage medium, and in another alternative embodiment, the computer program product is embodied in a Software product, such as a Software Development Kit (SDK), or the like.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the apparatus, the device, and the storage medium described above may refer to corresponding processes in the foregoing method embodiments, and are not described herein again. In the embodiments provided in the present disclosure, it should be understood that the disclosed method, apparatus, device and storage medium may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present disclosure may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such understanding, the technical solution of the present disclosure may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present disclosure. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.

Finally, it should be noted that: the above-mentioned embodiments are merely specific embodiments of the present disclosure, which are used for illustrating the technical solutions of the present disclosure and not for limiting the same, and the scope of the present disclosure is not limited thereto, and although the present disclosure is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive of the technical solutions described in the foregoing embodiments or equivalent technical features thereof within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present disclosure, and should be construed as being included therein. Therefore, the protection scope of the present disclosure shall be subject to the protection scope of the claims.

Claims

1. A method of data processing, the method comprising:

2. The method according to claim 1, wherein the storing the data item and the timestamp added to the data item in a data pair form to a storage location corresponding to the service data comprises:

3. The method according to claim 1, wherein after storing the data item and the timestamp added to the data item in a data pair form to a storage location corresponding to the service data, the method comprises:

4. The method according to claim 1, wherein the performing, in response to a processing operation of the data item by a user, processing corresponding to the processing operation on the data item comprises:

5. The method according to claim 4, wherein when the business data is data in a step time mode, the presenting the data item corresponding to the query operation and the timestamp corresponding to the data item to a user in response to the query operation of the user on the data item further comprises:

6. The method of claim 5, further comprising:

7. The method according to any one of claims 1 to 6, wherein the performing, in response to a processing operation on the data item by a user, processing on the data item corresponding to the processing operation includes:

8. The method according to any one of claims 1 to 7, further comprising:

9. The method of claim 8, wherein after the generating statistical information for the traffic data based on the at least one first statistical condition and the plurality of data items and corresponding timestamps stored at the storage location, the method further comprises:

10. A data processing apparatus, characterized in that the apparatus comprises:

11. A computer device, comprising: a processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor, the processor and the memory communicating over the bus when a computer device is run, the machine-readable instructions when executed by the processor performing the steps of the data processing method of any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, performs the steps of the data processing method according to any one of claims 1 to 9.