Data display method and device, computer device and computer readable storage medium

Abstract

The application discloses a data display method and device, computer equipment and a computer readable storage medium, and relates to the technical field of big data, wherein the method comprises the following steps: acquiring historical data corresponding to the type of to-be-displayed data; determining the data change rule of the historical data; generating predicted data of the to-be-displayed data according to the data change rule and the historical data; filling the predicted data into the data missing time period of the to-be-displayed data to obtain filled to-be-displayed data; and rendering and displaying the filled to-be-displayed data. The application can improve the continuity of data display and improve the data display effect.

Description

Technical Field

[0001] The present invention relates to the field of big data technology, and in particular to a data display method, apparatus, computer equipment, and computer-readable storage medium. Background Art

[0002] This section is intended to provide a background or context to the embodiments of the invention that are recited in the claims. No statement herein is admitted to be prior art by virtue of its inclusion in this section.

[0003] As society develops, we've entered the era of big data. Whether companies can fully utilize data and extract useful insights from it is crucial. Furthermore, companies' external communications require extensive, real-world data, which plays a crucial role in establishing their corporate image and brand. This has spawned a variety of large-screen applications, leveraging impressive multimedia, network technologies, and even 3D virtual reality to achieve stunning live effects. These applications aim to make data presentations more vivid, lifelike, and easy to understand. However, in the data presentation process, real-world data often fails to achieve satisfactory results.

[0004] In the process of realizing the above requirements, due to network bottlenecks, data transmission distortion or data loss problems, the data to be displayed is often partially missing, making it impossible to guarantee the continuity of the data during display, and thus easily causing the problem of poor data display effect due to partial data loss during the data display process.

[0005] There is currently no solution to the above problems. Summary of the Invention

[0006] An embodiment of the present invention provides a data display method, which relates to the field of big data technology and is used to enhance the continuity of data display and improve the data display effect. The method includes:

[0007] Obtain historical data corresponding to the type of data to be displayed;

[0008] Determine the data change pattern of the historical data;

[0009] Generate forecast data for the data to be displayed based on the data change pattern and the historical data;

[0010] Filling the predicted data into the data missing time period of the data to be displayed to obtain the filled data to be displayed;

[0011] The filled data to be displayed is rendered and displayed.

[0012] An embodiment of the present invention further provides a data display device, which relates to the field of big data technology and is used to enhance the continuity of data display and improve the data display effect. The device includes:

[0013] A historical data acquisition module is used to acquire historical data corresponding to the type of data to be displayed;

[0014] A data change rule determination module is used to determine the data change rule of the historical data;

[0015] A prediction data generation module is used to generate prediction data of the data to be displayed based on the data change law and the historical data;

[0016] The data-to-be-displayed filling module is used to fill the predicted data into the data-missing time period of the data-to-be-displayed to obtain the filled data-to-be-displayed;

[0017] The data rendering and display module is used to render and display the filled data to be displayed.

[0018] An embodiment of the present invention further provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned data display method when executing the computer program.

[0019] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for executing the above-mentioned data display method.

[0020] In an embodiment of the present invention, historical data corresponding to the type of data to be displayed is obtained; a data change pattern of the historical data is determined; based on the data change pattern and the historical data, predicted data of the data to be displayed is generated; the predicted data is filled into the data missing time period of the data to be displayed to obtain the filled data to be displayed; the filled data to be displayed is rendered and then displayed, thereby ensuring the integrity of the data to be displayed by supplementing the data in the data missing time period of the data to be displayed, solving the problem in the prior art that the continuity of data display cannot be guaranteed due to partial missing of the data to be displayed, thereby improving the continuity of data display and the data display effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0022] Figure 1 Schematic diagram of a data display method according to an embodiment of the present invention;

[0023] Figure 2 This is a specific example diagram of a data display method in an embodiment of the present invention;

[0024] Figure 3 This is a specific example diagram of a data display method in an embodiment of the present invention;

[0025] Figure 4 This is a specific example diagram of a data display method in an embodiment of the present invention;

[0026] Figure 5 This is a specific example diagram of a data display method in an embodiment of the present invention;

[0027] Figure 6 This is a specific example diagram of a data display method in an embodiment of the present invention;

[0028] Figure 7 This is a structural diagram of a data display device according to an embodiment of the present invention;

[0029] Figure 8 This is a specific example diagram of a data display device in an embodiment of the present invention;

[0030] Figure 9 This is a specific example diagram of a data display device in an embodiment of the present invention;

[0031] Figure 10 Schematic diagram of a computer device used for data display in an embodiment of the present invention. DETAILED DESCRIPTION

[0032] To make the purpose, technical solutions and advantages of the embodiments of the present invention more clear, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. Here, the exemplary embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0033] Currently, in the process of data presentation, real data often fails to achieve satisfactory display effects. The following problems are often encountered in demand implementation:

[0034] 1. Data sources vary widely. The technical architecture of the data source platform is limited, resulting in low data integrity.

[0035] 2. Poor data continuity. Due to network bottlenecks or other technical anomalies, data continuity cannot be guaranteed and cannot be transmitted to the display application in a timely manner.

[0036] 3. Frequent data errors. The data source system is unstable, causing the real data to occasionally deviate from the normal data range, or even to be empty in extreme cases.

[0037] The inevitable data source issues mentioned above can significantly impact presentation quality and can even lead to unacceptable presentation errors, negatively impacting a company's image. To address these issues, a highly available presentation solution is urgently needed to ensure data continuity and validity during presentation.

[0038] To this end, an embodiment of the present invention provides a data display method, which relates to the field of big data technology and is used to improve the continuity of data display and the effect of data display. Figure 1 As shown, the method may include:

[0039] Step 101: Obtain historical data corresponding to the type of data to be displayed;

[0040] Step 102: Determine the data change pattern of the historical data;

[0041] Step 103: Generate forecast data of the data to be displayed based on the data change pattern and the historical data;

[0042] Step 104: Fill the predicted data into the data missing time period of the data to be displayed, to obtain the filled data to be displayed;

[0043] Step 105: Render and display the filled data to be displayed.

[0044] During specific implementation, first obtain historical data corresponding to the type of data to be displayed.

[0045] In the embodiment, obtaining historical data corresponding to the type of data to be displayed helps to determine the data variation pattern of the historical data in subsequent steps, thereby generating predicted data of the data to be displayed based on the data variation pattern and the historical data.

[0046] In a specific implementation, after obtaining historical data corresponding to the type of data to be displayed, the data change pattern of the historical data is determined.

[0047] In this embodiment, the data change patterns of different historical data can be determined based on the data interface update frequency of the historical data. Such data change patterns may include: periodic data reset, continuous data growth, real-time data update, and random data fluctuation. The periodic data reset may include daily data clearing and monthly data clearing; continuous data growth may include data auto-increment; and real-time data update may include data segmentation at the second level.

[0048] In the above embodiment, determining the data variation pattern of the historical data helps to generate prediction data for the data to be displayed based on the data variation pattern and the historical data in subsequent steps.

[0049] In a specific implementation, after determining the data change pattern of the historical data, prediction data of the data to be displayed is generated based on the data change pattern and the historical data.

[0050] In an embodiment, the data to be displayed in the current cycle or the current data display stage can be predicted based on the data change pattern and combined with historical data to prevent the problem of incomplete data affecting the data display effect.

[0051] In one embodiment, the data change rules include: periodic data reset;

[0052] According to the data change rules and the historical data, the forecast data of the data to be displayed is generated, such as Figure 2 As shown, this may include:

[0053] Step 201: When the data change pattern is periodic data reset, obtain the start time and end time of the current update cycle of the data to be displayed;

[0054] Step 202: Analyze the historical data to determine the time distribution pattern of the historical data to be displayed;

[0055] Step 203: Generate prediction data of the data to be displayed based on the start time, the end time and the distribution pattern of the information over time.

[0056] In this embodiment, by obtaining the start and end times of the current update cycle of the data to be displayed, the start and end times can be directly obtained from the data to be displayed. Combined with the time distribution pattern of the historical data of the display data, the predicted data of the data to be displayed within this update cycle can be predicted.

[0057] In the above embodiment, periodic data resets may include daily and monthly data clearing, representing the changing patterns of data that periodically increases and resets over a period of time. For this type of data, the data to be displayed can be sampled based on the start and end times of historical business operations, thereby obtaining node data at the start and end times. The data to be displayed within the current period is then segmented according to the distribution patterns of data at corresponding points in previous periods, pre-populating the data for each point in time required for display within the current period.

[0058] In one embodiment, periodic data reset may include daily data clearing and monthly data clearing, such as real-time transaction volume data. This type of data often has a certain periodic trend. When it is difficult to actually count the data at every moment, the data can be displayed according to the previous data trend and the data can be cleared according to the period and pre-buried according to the latest historical trend.

[0059] In one embodiment, the data change rules include: continuous growth of data;

[0060] According to the data change rules and the historical data, the forecast data of the data to be displayed is generated, such as Figure 3 As shown, this may include:

[0061] Step 301: Determine the start and end display times of the data to be displayed;

[0062] Step 302: determining an average data growth rate of the historical data within a preset time period based on the historical data;

[0063] Step 303: Generate predicted data of the data to be displayed according to the start display time, the end display time and the average data growth amount.

[0064] In this embodiment, the preset time period is the current display time period of the data to be displayed. By determining the average data growth rate of the historical data within the preset time period, as well as the start and end display times of the data to be displayed, the data of the data to be displayed at each time within the preset time period can be predicted, thereby obtaining predicted data for the data to be displayed.

[0065] In the above embodiment, the data continues to grow, which can be used to describe the type of data that is mainly cumulatively growing. According to the growth trend of the past, the real-time growth interval of the data to be displayed is calculated, and it is accumulated continuously in a random manner. If the data accumulated according to the trend deviates from the value of the next data acquisition point, the difference can be compensated to slow down or increase the speed of data change in the next cycle.

[0066] In one embodiment, the data continues to grow, for example, it can be the cumulative visit data. Such data often accumulates and increases according to a certain growth trend. When it is difficult to actually count the data at every moment, it can be displayed gradually in an increasing manner according to the increasing trend of the last interval. If the data is different at the next observation point, the growth trend can be adjusted in the next stage to compensate for it.

[0067] In one embodiment, the data change rules include: real-time data update;

[0068] According to the data change rules and the historical data, the forecast data of the data to be displayed is generated, such as Figure 4 As shown, this may include:

[0069] Step 401: Determine the data update frequency of the historical data;

[0070] Step 402: Generate prediction data of the data to be displayed based on the data update frequency and the randomly selected update node data in the historical data.

[0071] In the embodiment, by randomly extracting data of multiple updated nodes in the historical data and the data update frequency of the historical data, the data of each node of the data to be displayed within the time period of the data to be displayed can be predicted.

[0072] In the above embodiment, the data update frequency may include second-level segmentation, which can mainly target the data to be displayed itself, sample data from the two most recent time points according to the data update frequency, and segment the data within the interval according to the historical data distribution, and split the data in seconds.

[0073] In one embodiment, the data update frequency may include second-level segmentation. For example, for data on real-time access counts, the data update time of such data itself may be refreshed once a minute. Subsequently, the thread may fetch the latest data once a minute and generate data within one minute into the memory together with the last result, and return it according to the segmented time granularity.

[0074] In one embodiment, the data variation rules include: random oscillation of data;

[0075] According to the data change rules and the historical data, the forecast data of the data to be displayed is generated, such as Figure 5 Said may include:

[0076] Step 501: Receive the random oscillation pattern of the data to be displayed;

[0077] Step 502: Generate prediction data for the data to be displayed based on the random oscillation rule and the historical data.

[0078] In the embodiment, the predicted data of the data to be displayed can be randomly predicted based on the random oscillation law of the data to be displayed.

[0079] In the above embodiment, the random oscillation can be mainly used for the data itself, which changes randomly within a certain interval. In this case, within the data oscillation interval of the data to be displayed, the data to be displayed is randomly scattered to finally obtain the predicted data.

[0080] In one embodiment, the data to be displayed that conforms to the law of random oscillation may be, for example, real-time fraud data. Since real-time fraud events are randomly generated within a numerical range, random functions can be used to randomly generate data within a certain range and return them, ultimately obtaining predicted data.

[0081] In a specific implementation, after generating predicted data of the data to be displayed according to the data change rule and the historical data, the predicted data is filled into the data missing time period of the data to be displayed to obtain the filled data to be displayed.

[0082] In an embodiment, the predicted data corresponding to the data missing time period may be filled in during the data missing time period of the data to be displayed to obtain the filled data to be displayed.

[0083] In one embodiment, the integrity of the data to be displayed can be ensured by supplementing the data during the data missing time period, solving the problem in the prior art that the continuity of data display cannot be guaranteed due to partial missing of the data to be displayed. This can improve the continuity of data display and the data display effect.

[0084] In the above embodiment, if the data to be displayed encounters an anomaly and cannot be displayed, the predicted data can be used as a backup. For example, a specific time point can be selected as a snapshot for the data to be displayed. If the data corresponding to this time point cannot be obtained, the predicted data can be used to ensure that the display proceeds normally.

[0085] In a specific implementation, after the predicted data is filled into the data missing time period of the data to be displayed to obtain the filled data to be displayed, the filled data to be displayed is rendered and then displayed.

[0086] In the above embodiment, by rendering and displaying the filled data to be displayed, the problem of the inability to ensure the continuity of data display due to partial missing of the data to be displayed under the existing technology can be solved, the continuity of data display can be improved, and the data display effect can be improved.

[0087] Under existing technologies, real data often fails to achieve satisfactory presentation results during data presentation. This often leads to frequent data errors during demand implementation. Due to unstable data source systems, real data can occasionally deviate from the normal range, or even be empty.

[0088] In order to solve the above problems, in specific implementation, an embodiment of the present invention provides a data display method, such as Figure 6 As shown, it may also include:

[0089] Step 601: Compare the predicted data and the data to be displayed at the same time;

[0090] Step 602: If the difference between the predicted data at that moment and the data to be displayed exceeds a preset threshold, an alarm message indicating that there is a deviation between the data to be displayed at that moment and the predicted data is issued, and data display is stopped.

[0091] In an embodiment, by determining the difference between the predicted data and the data to be displayed at that moment, it can be compared with a preset threshold value. When the difference between the predicted data and the data to be displayed at that moment exceeds the preset threshold value, it can be determined that there is a deviation between the data to be displayed and the predicted data at that moment; by issuing an alarm message that there is a deviation between the data to be displayed and the predicted data at that moment, it helps the staff to understand the data display situation and improve the data display process.

[0092] In the above embodiment, the predicted data can be compared with the data to be displayed. If the data is not within the expected range, an early warning and reset of the data to be displayed can be issued. At the same time, the data administrator can manually intervene and pre-embed the data when necessary to prevent data from getting out of control.

[0093] In specific implementation, a data display method provided by an embodiment of the present invention may further include:

[0094] The predicted data whose difference with the data to be displayed exceeds a preset threshold is used to replace the data to be displayed at the corresponding moment, thereby generating the data to be displayed after the replacement data.

[0095] In the above embodiment, the data to be displayed may be corrected by replacing the data to be displayed at the corresponding moment with the predicted data whose difference with the data to be displayed exceeds a preset threshold to generate the replaced data to be displayed.

[0096] In specific implementation, a data display method provided by an embodiment of the present invention may further include:

[0097] The predicted data and the data to be displayed are recorded to generate a record file.

[0098] In the above embodiment, by generating a record file, management personnel can be assisted in retrieving and reading the above process at any time, which helps management personnel to discover loopholes and drawbacks in the above process; at the same time, staff can also retrieve and read the record file to trace the data in the above process, which helps to verify the authenticity and accuracy of the data and improve the accuracy of the above process.

[0099] In specific implementation, a data display method provided by an embodiment of the present invention may further include:

[0100] Get the data to be displayed from the HTTP protocol WEB interface and / or the asynchronous long connection interface based on the WebSocket protocol.

[0101] In an embodiment, the method provided by the embodiment of the present invention can be applied to obtain data by polling a WEB interface based on the HTTP protocol or by long connection asynchronous push based on the websocket protocol.

[0102] In the above embodiment, different types of data to be displayed can be received through different data interfaces.

[0103] In an embodiment of the present invention, historical data corresponding to the type of data to be displayed is obtained; a data change pattern of the historical data is determined; based on the data change pattern and the historical data, predicted data of the data to be displayed is generated; the predicted data is filled into the data missing time period of the data to be displayed to obtain the filled data to be displayed; the filled data to be displayed is rendered and then displayed, thereby ensuring the integrity of the data to be displayed by supplementing the data in the data missing time period of the data to be displayed, solving the problem in the prior art that the continuity of data display cannot be guaranteed due to partial missing of the data to be displayed, thereby improving the continuity of data display and the data display effect.

[0104] As described above, the embodiments of the present invention have the following advantages compared with the original method, which ensures the effect of data display and the reliability of the display effect, so that in the subsequent data visualization step, compared with traditional reports and simple data query systems, the data display can be more intuitive, fast and easy to accept.

[0105] The present invention also provides a data display device, as described in the following embodiments. Since the principle of the device to solve the problem is similar to that of the data display method, the implementation of the device can refer to the implementation of the data display method, and the repeated parts will not be repeated.

[0106] The embodiment of the present invention also provides a data display device, which relates to the field of big data technology and is used to improve the continuity of data display and the effect of data display, such as Figure 7 As shown, the device includes:

[0107] A historical data acquisition module 701 is used to acquire historical data corresponding to the type of data to be displayed;

[0108] The data change rule determination module 702 is used to determine the data change rule of the historical data;

[0109] The prediction data generation module 703 is used to generate prediction data of the data to be displayed based on the data change law and the historical data;

[0110] The data to be displayed filling module 704 is used to fill the predicted data into the data missing time period of the data to be displayed to obtain the filled data to be displayed;

[0111] The data rendering and display module 705 is used to render and display the filled data to be displayed.

[0112] In one embodiment, the data change rules include: periodic data reset;

[0113] The prediction data generation module can be used to:

[0114] When the data change pattern is periodic data reset, obtain the start time and end time of the current update cycle of the data to be displayed;

[0115] Analyze the historical data to determine the time distribution pattern of the historical data to be displayed;

[0116] According to the start time, the end time and the distribution pattern of the information over time, prediction data of the data to be displayed is generated.

[0117] In one embodiment, the data change rules include: continuous growth of data;

[0118] The prediction data generation module can be used to:

[0119] Determine the start and end times of displaying the data to be displayed;

[0120] Determine, based on the historical data, an average data growth rate of the historical data within a preset time period;

[0121] According to the start display time, the end display time and the average data growth amount, prediction data of the data to be displayed is generated.

[0122] In one embodiment, the data change rules include: real-time data update;

[0123] The prediction data generation module can be used to:

[0124] Determine the data update frequency of the historical data;

[0125] According to the data update frequency and the update node data randomly extracted from the historical data, the predicted data of the data to be displayed is generated.

[0126] In one embodiment, the data variation rules include: random oscillation of data;

[0127] The prediction data generation module can be used to:

[0128] Receive the random oscillation pattern of the data to be displayed;

[0129] Based on the random oscillation law and the historical data, the predicted data of the data to be displayed is generated.

[0130] In one embodiment, the present invention provides a data display device, such as Figure 8 As shown, it may also include:

[0131] The comparison module 706 is configured to:

[0132] Compare the predicted data and the data to be displayed at the same time;

[0133] If the difference between the predicted data at that moment and the data to be displayed exceeds a preset threshold, an alarm message indicating that there is a deviation between the data to be displayed at that moment and the predicted data is issued, and data display is suspended.

[0134] In one embodiment, the present invention provides a data display device, such as Figure 9 As shown, it may also include:

[0135] The data replacement module 707 is used to:

[0136] The predicted data whose difference with the data to be displayed exceeds a preset threshold is used to replace the data to be displayed at the corresponding moment, thereby generating the data to be displayed after the replacement data.

[0137] In one embodiment, a data display device provided by an embodiment of the present invention may further include:

[0138] Data logging module for:

[0139] The predicted data and the data to be displayed are recorded to generate a record file.

[0140] In one embodiment, a data display device provided by an embodiment of the present invention may further include:

[0141] Data acquisition module, used to:

[0142] Get the data to be displayed from the HTTP protocol WEB interface and / or the asynchronous long connection interface based on the WebSocket protocol.

[0143] An embodiment of the present invention provides an embodiment of a computer device for implementing all or part of the content of the above-mentioned data display method. The computer device specifically includes the following content:

[0144] A processor, a memory, a communications interface, and a bus; wherein the processor, the memory, and the communications interface communicate with each other via the bus; the communications interface is used to implement information transmission between related devices; the computer device can be a desktop computer, a tablet computer, a mobile terminal, etc., but this embodiment is not limited thereto. In this embodiment, the computer device can be implemented with reference to the embodiment for implementing the data display method and the embodiment for implementing the data display device, the contents of which are incorporated herein and repeated parts are not repeated.

[0145] Figure 10 1 is a schematic block diagram of the system structure of the computer device 1000 according to an embodiment of the present application. Figure 10 As shown, the computer device 1000 may include a central processor 1001 and a memory 1002; the memory 1002 is coupled to the central processor 1001. Figure 10 is exemplary; other types of structures may also be used to supplement or replace this structure to implement telecommunication functions or other functions.

[0146] In one embodiment, the data display function may be integrated into the central processing unit 1001. The central processing unit 1001 may be configured to perform the following control:

[0147] Obtain historical data corresponding to the type of data to be displayed;

[0148] Determine the data change pattern of the historical data;

[0149] Generate forecast data for the data to be displayed based on the data change pattern and the historical data;

[0150] Filling the predicted data into the data missing time period of the data to be displayed to obtain the filled data to be displayed;

[0151] The filled data to be displayed is rendered and displayed.

[0152] In another embodiment, the data display device may be configured separately from the central processing unit 1001. For example, the data display device may be configured as a chip connected to the central processing unit 1001, and the data display function is realized under the control of the central processing unit.

[0153] like Figure 10 As shown, the computer device 1000 may further include: a communication module 1003, an input unit 1004, an audio processor 1005, a display 1006, and a power supply 1007. It is worth noting that the computer device 1000 does not necessarily have to include Figure 10In addition, the computer device 1000 may also include all components shown in Figure 10 For components not shown, reference may be made to the prior art.

[0154] like Figure 10 As shown, the central processing unit 1001 is sometimes also referred to as a controller or an operation control unit, and may include a microprocessor or other processor device and / or logic device. The central processing unit 1001 receives inputs and controls the operations of various components of the computer device 1000 .

[0155] Memory 1002 can be, for example, one or more of a cache, flash memory, hard drive, removable media, volatile memory, non-volatile memory, or other suitable devices. It can store the aforementioned failure-related information and a program that executes the relevant information. The CPU 1001 can execute the program stored in memory 1002 to implement information storage or processing.

[0156] Input unit 1004 provides input to CPU 1001. Input unit 1004 may be, for example, a keypad or touch input device. Power supply 1007 is used to provide power to computer device 1000. Display 1006 is used to display objects such as images and text. This display may be, for example, an LCD display, but is not limited thereto.

[0157] The memory 1002 may be a solid-state memory, such as a read-only memory (ROM), random access memory (RAM), or SIM card. Alternatively, it may be a memory that retains information even when power is off, can be selectively erased, and is provided with more data. Examples of such memory are sometimes referred to as EPROMs. The memory 1002 may also be some other type of device. The memory 1002 includes a buffer memory 1021 (sometimes referred to as a buffer). The memory 1002 may include an application / function storage unit 1022 for storing application programs and function programs or processes used by the central processing unit 1001 to execute the operations of the computer device 1000.

[0158] The memory 1002 may also include a data storage unit 1023 for storing data, such as contacts, digital data, pictures, sounds, and / or any other data used by the computer device. The driver storage unit 1024 of the memory 1002 may include various driver programs for the computer device for communication functions and / or for executing other functions of the computer device (such as messaging applications, address book applications, etc.).

[0159] The communication module 1003 is a transmitter / receiver 1003 that sends and receives signals via the antenna 1008. The communication module (transmitter / receiver) 1003 is coupled to the central processor 1001 to provide input signals and receive output signals, which may be the same as the case of a conventional mobile communication terminal.

[0160] Based on different communication technologies, multiple communication modules 1003 can be provided in the same computer device, such as a cellular network module, a Bluetooth module, and / or a wireless local area network module. The communication module (transmitter / receiver) 1003 is also coupled to a speaker 1009 and a microphone 1010 via an audio processor 1005 to provide audio output via the speaker 1009 and receive audio input from the microphone 1010, thereby implementing common telecommunication functions. The audio processor 1005 may include any suitable buffer, decoder, amplifier, etc. Furthermore, the audio processor 1005 is coupled to the central processing unit 1001, enabling local recording via the microphone 1010 and playback of stored audio via the speaker 1009.

[0161] An embodiment of the present invention further provides a computer-readable storage medium storing a computer program for executing the above-mentioned data display method.

[0162] In an embodiment of the present invention, historical data corresponding to the type of data to be displayed is obtained; a data change pattern of the historical data is determined; based on the data change pattern and the historical data, predicted data of the data to be displayed is generated; the predicted data is filled into the data missing time period of the data to be displayed to obtain the filled data to be displayed; the filled data to be displayed is rendered and then displayed, thereby ensuring the integrity of the data to be displayed by supplementing the data in the data missing time period of the data to be displayed, solving the problem in the prior art that the continuity of data display cannot be guaranteed due to partial missing of the data to be displayed, thereby improving the continuity of data display and the data display effect.

[0163] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0164] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0165] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0166] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0167] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A data display method, characterized in that: include: Obtain historical data of the type of data to be displayed in the corresponding enterprise; Determine the data change pattern of the historical data; According to the data interface update frequency of the historical data, the data change rules of different historical data are determined; The above data change patterns may include: periodic data reset, continuous data growth, real-time data update, and random data fluctuations. Among them, periodic data reset includes daily data clearing and monthly data clearing; continuous data growth includes data auto-increment; real-time data update includes data segmentation in seconds. Generate forecast data for the data to be displayed based on the data change pattern and the historical data; Filling the predicted data into the data missing time period of the data to be displayed to obtain the filled data to be displayed; Render and display the filled data to be displayed; The data change pattern includes: periodic data reset; generating predicted data for the data to be displayed based on the data change pattern and the historical data, including: when the data change pattern is periodic data reset, obtaining the start time and end time of the current update cycle of the data to be displayed; analyzing the historical data to determine a distribution pattern of information of the historical data to be displayed over time; and generating predicted data for the data to be displayed based on the start time, the end time, and the distribution pattern of the information over time; The method further includes: obtaining the data to be displayed from a WEB interface of the HTTP protocol and / or an asynchronous long connection interface based on the websocket protocol; The data change law includes: continuous data growth; based on the data change law and the historical data, generating predicted data of the data to be displayed, including: determining the starting display time and the ending display time of the data to be displayed; determining the average data growth of the historical data within a preset time period based on the historical data; generating predicted data of the data to be displayed based on the starting display time, the ending display time and the average data growth; the preset time period is the current display time period of the data to be displayed; continuous data growth is used to describe a type of data that has been accumulating and growing, and the real-time growth range of the data to be displayed is calculated based on the growth trend of the past period, and is continuously accumulated in a random manner. If the data accumulated according to the trend deviates from the value of the next data acquisition point, the difference compensation can be performed to slow down or increase the speed of data change in the next cycle; The data change rules include: real-time data updates; generating predicted data for the data to be displayed based on the data change rules and the historical data, including: determining the data update frequency of the historical data; generating predicted data for the data to be displayed based on the data update frequency and randomly sampled update node data from the historical data; the data update frequency may include second-level segmentation, sampling the data of the two most recent time points according to the data update frequency, and segmenting the data within a time interval according to the distribution of historical data; the data update frequency includes second-level segmentation of real-time access count data, the data of which is refreshed once every minute, and the latest data is retrieved once a minute by a thread and generated into data within one minute together with the previous result in memory, and returned according to the segmented time granularity; The data variation pattern includes random oscillation of data; generating predicted data of the data to be displayed based on the data variation pattern and the historical data, including: receiving the random oscillation pattern of the data to be displayed; generating predicted data of the data to be displayed based on the random oscillation pattern and the historical data; random oscillation is a pattern of random occurrence of data variation within a certain interval, and the data to be displayed is randomly scattered within the data oscillation interval applied to the data to be displayed, thereby finally obtaining predicted data; It also includes: comparing the predicted data and the data to be displayed at the same time; If the difference between the predicted data and the data to be displayed at that moment exceeds the preset threshold, an alarm message will be issued indicating that the data to be displayed at that moment is deviated from the predicted data, and data display will be suspended. The predicted data will be compared with the data to be displayed. If the data is not within the expected range, an alert will be issued and the data to be displayed will be reset. The method further includes: replacing the data to be displayed at the corresponding moment with the predicted data whose difference with the data to be displayed exceeds a preset threshold, thereby generating data to be displayed after the replaced data; The method further includes: recording the predicted data and the data to be displayed, and generating a record file.

2. A data display device, characterized in that: include: A historical data acquisition module is used to acquire historical data of the type of data to be displayed in the corresponding enterprise; A data change rule determination module is used to determine the data change rule of the historical data; Based on the data interface update frequency of the historical data, determine the data change patterns of different historical data; the above data change patterns may include: periodic data reset, continuous data growth, real-time data update, and random data fluctuation; among which, periodic data reset includes daily data clearing and monthly data clearing; continuous data growth includes data auto-increment; real-time data update includes data segmentation in seconds; A prediction data generation module is used to generate prediction data of the data to be displayed based on the data change law and the historical data; The data-to-be-displayed filling module is used to fill the predicted data into the data-missing time period of the data-to-be-displayed to obtain the filled data-to-be-displayed; The data rendering and display module is used to render and display the filled data to be displayed; The data change pattern includes: data periodic reset; the prediction data generation module is specifically used to: when the data change pattern is data periodic reset, obtain the start time and end time of the current update cycle of the data to be displayed; analyze the historical data to determine the distribution pattern of the information of the historical data to be displayed over time; and generate prediction data for the data to be displayed based on the start time, the end time and the distribution pattern of the information over time; It also includes: a data acquisition module, which is used to: obtain the data to be displayed from the HTTP protocol WEB interface and / or the asynchronous long connection interface based on the websocket protocol; The data change rules include: continuous data growth; a prediction data generation module is specifically used to: determine the starting display time and the ending display time of the data to be displayed; determine the average data growth of the historical data within a preset time period based on the historical data; generate predicted data for the data to be displayed based on the starting display time, the ending display time and the average data growth; the preset time period is the current display time period of the data to be displayed; continuous data growth is used to describe the type of data that has been accumulating and growing, calculate the real-time growth range of the data to be displayed based on the growth trend of the past, and continuously accumulate in a random manner. If the data accumulated according to the trend deviates from the value of the next data acquisition point, the difference can be compensated to slow down or increase the speed of data change in the next cycle; The data change rules include: real-time data updates; a prediction data generation module specifically configured to: determine the data update frequency of the historical data; generate prediction data for the data to be displayed based on the data update frequency and randomly sampled update node data from the historical data; the data update frequency may include second-level segmentation, sampling the data of the two most recent time points according to the data update frequency, and segmenting the data within a time interval according to the distribution of historical data; the data update frequency includes second-level segmentation of the real-time access count data, where the data itself is updated once every minute, and the latest data is fetched once a minute through a thread and generated into data within one minute together with the previous result, stored in memory, and returned according to the segmented time granularity; The data variation pattern includes random oscillation of data; a prediction data generation module is specifically configured to: receive the random oscillation pattern of the data to be displayed; and generate prediction data of the data to be displayed based on the random oscillation pattern and the historical data; random oscillation is a random occurrence of the data variation pattern within a certain interval, so the data to be displayed is randomly scattered within the data oscillation interval applied to the data to be displayed to ultimately obtain prediction data; Also included: a comparison module for: Compare the predicted data and the data to be displayed at the same time; If the difference between the predicted data and the data to be displayed at that moment exceeds the preset threshold, an alarm message will be issued indicating that the data to be displayed at that moment is deviated from the predicted data, and data display will be suspended. The predicted data will be compared with the data to be displayed. If the data is not within the expected range, an alert will be issued and the data to be displayed will be reset. Also included: a data replacement module for: The predicted data whose difference with the data to be displayed exceeds a preset threshold is replaced with the data to be displayed at the corresponding time, thereby generating the data to be displayed after the replacement data; It also includes: a data recording module, which is used to record the predicted data and the data to be displayed and generate a record file.

3. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method according to claim 1 is implemented.

4. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program for executing the method according to claim 1 .

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