CN106492459B - Data processing system, data processing method and data processing device - Google Patents
Data processing system, data processing method and data processing device Download PDFInfo
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- CN106492459B CN106492459B CN201610905533.3A CN201610905533A CN106492459B CN 106492459 B CN106492459 B CN 106492459B CN 201610905533 A CN201610905533 A CN 201610905533A CN 106492459 B CN106492459 B CN 106492459B
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
- A63F13/30—Interconnection arrangements between game servers and game devices; Interconnection arrangements between game devices; Interconnection arrangements between game servers
- A63F13/35—Details of game servers
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
- A63F13/70—Game security or game management aspects
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F2300/00—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game
- A63F2300/50—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game characterized by details of game servers
- A63F2300/55—Details of game data or player data management
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Abstract
In the data processing system provided by the embodiment of the invention, the game server is used for sending the game service data to the data processing device. The data processing device is used for acquiring game service data of each game server in real time. And then preprocessing the game service data to generate target game data, wherein the target game data comprise the online number of people and time of the game in the same game area, and then performing regression analysis on the target game data according to a preset algorithm to obtain a polynomial function corresponding to the time and the online predicted value. Therefore, the online number of the players of the game can be predicted in real time, and resource waste of the game server is reduced.
Description
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to a data processing system, a data processing method, and a data processing apparatus.
Background
With the continuous development of science and technology, various network applications are rapidly developed, wherein the network applications comprise video applications, game applications and the like. In the online game, the number of online players is the main reference for engineers to manage and maintain the daily server.
The inventor finds that the online people number prediction of the current online game refers to historical data by engineers and predicts the online people number according to own experience. The method completely depends on the experience of engineers, and results obtained by different engineers are different greatly, which may cause waste or paralysis of server resources due to inaccurate online people prediction.
Therefore, how to provide a system for predicting the online number of people in the online game in real time to ensure the accuracy of the online number prediction of the game becomes a major technical problem to be solved at present.
Disclosure of Invention
In view of this, embodiments of the present invention provide a data processing system, a data processing method, and a data processing apparatus, which can predict the number of online players of a game in real time, thereby reducing resource waste of a game server.
In order to achieve the above purpose, the embodiments of the present invention provide the following technical solutions:
a data processing system comprises a game server and a data processing device,
the game server is used for sending game service data to the data processing device;
the data processing apparatus is configured to:
the method comprises the steps of obtaining game service data of each game server in real time, wherein the game service data comprise the number of online players of the game;
preprocessing the game service data to generate target game data, wherein the target game data comprise the number of online players and time of the game in the same game area;
and performing regression analysis on the target game data according to a preset algorithm to obtain a polynomial function corresponding to the time and the online predicted value.
A method of data processing, comprising:
the method comprises the steps of obtaining game service data of each game server in real time, wherein the game service data comprise the number of online players of the game;
preprocessing the game service data to generate target game data, wherein the target game data comprise the number of online players and time of the game in the same game area;
and performing regression analysis on the target game data according to a preset algorithm to obtain a polynomial function corresponding to the time and the online predicted value.
A data processing apparatus comprising:
the first acquisition module is used for acquiring game service data of each game server in real time, wherein the game service data comprises the online number of people in the game;
the data generation module is used for preprocessing the game service data to generate target game data, and the target game data comprise the number of online players and time of the game in the same game area;
and the first calculation module is used for performing regression analysis on the target game data according to a preset algorithm to obtain a polynomial function corresponding to the time and the online predicted value.
Based on the above technical solution, in the data processing system provided in the embodiment of the present invention, the game server is configured to send the game service data to the data processing device. The data processing device is used for acquiring game service data of each game server in real time. And then preprocessing the game service data to generate target game data, wherein the target game data comprise the online number of people and time of the game in the same game area, and then performing regression analysis on the target game data according to a preset algorithm to obtain a polynomial function corresponding to the time and the online predicted value. Therefore, the online number of the players of the game can be predicted in real time, and resource waste of the game server is reduced.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a block diagram of a data processing system according to an embodiment of the present invention;
FIG. 2 is a signaling flow diagram of a data processing system according to an embodiment of the present invention;
FIG. 3 is a signaling flow diagram of yet another data processing system in accordance with an embodiment of the present invention;
FIG. 4 is a signaling flow diagram of another data processing system in accordance with an embodiment of the present invention;
FIG. 5 is a signaling flow diagram of yet another data processing system in accordance with an embodiment of the present invention;
FIG. 6 is a diagram illustrating an example of a data processing system according to an embodiment of the present invention;
FIG. 7 is a pictorial representation of a practical application of yet another data processing system in accordance with an embodiment of the present invention;
FIG. 8 is a pictorial representation of a practical application of yet another data processing system in accordance with an embodiment of the present invention;
FIG. 9 is a pictorial representation of a practical application of yet another data processing system in accordance with an embodiment of the present invention;
FIG. 10 is a block diagram of another data processing apparatus according to an embodiment of the present invention;
fig. 11 is a schematic diagram of a terminal hardware structure according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall correspond to the protection scope of the present invention.
In the data processing system provided by the embodiment of the invention, the game server is used for sending the game service data to the data processing device. The data processing device is used for acquiring game service data of each game server in real time. And then preprocessing the game service data to generate target game data, wherein the target game data comprise the online number of people and time of the game in the same game area, and then performing regression analysis on the target game data according to a preset algorithm to obtain a polynomial function corresponding to the time and the online predicted value. Therefore, the online number of the players of the game can be predicted in real time, and resource waste of the game server is reduced.
Referring to fig. 1, fig. 1 is a block diagram of a data processing system according to an embodiment of the present invention, where a data processing method according to an embodiment of the present invention may be implemented based on the system shown in fig. 1, and referring to fig. 1, the data processing system according to an embodiment of the present invention may include: a data processing device 10, at least one game server 20;
the data processing apparatus 10 may be a device for data processing provided on a network side, and the data processing apparatus 10 may be a single server, a server group composed of a plurality of servers, or a cloud computing service center. The data processing device 10 may be a computer having a data calculation function.
At least one game server 20 is a device for transmitting game service data on the user side.
Based on the system shown in fig. 1, fig. 2 shows a signaling flow diagram of a data processing system provided by an embodiment of the present invention, where the data processing system includes: the game server and the data processing device, as shown in fig. 1 and fig. 2, the signaling interaction process may include:
and step S100, sending game service data to the data processing device.
In the scheme, the game service data comprises the number of the actual game online people and the corresponding relation between the number of the actual game online people and time, and besides, the game service data also can comprise information such as a server area where the game is located, the model type of the server and the like. Wherein, the time can be set according to the actual needs, for example, every five minutes, the number of the actual online players is collected. Since the number of online games is usually large, the game users are allocated to server areas where different games are located, which results in the number of online actual games on multiple servers in the same time, for example, in 2016, 6, 17, 11: 00, in the area of the server A, the number of the actual online players of the game with the server model type M1 is 50574; in 2016, 6, 17, 11: 00, in the area of the server A, the number of the actual online game players with the server model type M2 is 8518; in 2016, 6, 17, 11: 00, in the A server area, the number of the actual online players of the game with the server model type D12-60-200 is 110647, then statistics are carried out in 2016, 6, 17, 11: 00, the number of the actual online game persons in the A server area is 169739 sum of the three, namely 8518+50574+ 110647.
The step is the process that each game business server sends the real online number of people in the game collected in real time to the data processing device.
And step S101, acquiring game service data of each game server in real time.
The game service data of the game server is obtained here, and it is introduced above that the game service data may include the number of people who are online in the actual game, the corresponding time, the server area where the game is located, and the server type, and the data processing device may store the corresponding relationship of each parameter in the game service data.
And S102, preprocessing the game service data to generate target game data, wherein the target game data comprise the number of online players and time of the game in the same game area.
In combination with the above steps, the emphasis here is on the process of processing the game service data, such as cleaning the acquired game service data, eliminating unnecessary data and processing the game service data into a preset format. For example, the obtained game service data includes a plurality of parameter values, and this step may leave specific parameters according to a preset format, such as the area of the server where the game is located, the model type of the server, the time, and the sequence of the number of online people in the actual game.
And S103, performing regression analysis on the target game data according to a preset algorithm to obtain a polynomial function corresponding to the time and the online predicted value.
In the scheme, preferably, a least square algorithm is adopted, the collected online number of the actual game people at each moment is input, regression analysis is carried out to obtain a polynomial function, and the polynomial function records the corresponding relation between the online predicted value and the time point. It should be noted that the obtained polynomial function is different according to the difference of the input actual online data and the difference of the time.
Among them, the least square method is a method for regression analysis. The defined error function is the sum of the squares of the differences between the predicted and true values (the sum of the squares of the residuals). By using a least squares method implemented by a matrix, we can fit a curve (polynomial image) with the least error to the given data. The function can be considered to represent the overall online trend in a certain definition domain, so that the online condition which is possibly achieved in a short time can be evaluated.
The specific fitting steps are as follows:
1. let the fitting polynomial be:
y＝a0+a1x+...+akxk，
2. the sum of the distances from each point to this curve, i.e. the sum of the squared deviations, is as follows:
3. to find the value of a that meets the condition, the partial derivative of ai is found on the right side of the equation:
.......
4. the following equation should then be obtained by simplifying the equation to the left as follows:
.......
5. by expressing these equations in the form of a matrix, the following matrix can be obtained:
6. this vandermonde matrix is reduced to yield:
7. that is, X ═ a ═ Y, then a ═ (X '× X) -1 ×', Y, the coefficient matrix a was obtained, along with the fitted curve.
Preferably, the actual online number of the game from the zero point of the day to the current time is input, and the data is subjected to regression analysis by a least square method to generate a polynomial function corresponding to the time. That is, at each time point, because the data of the number of the online persons of the actual game are input differently, the polynomial function is updated at each time point, and the online predicted values obtained by the corresponding polynomial function after the current time is input are also different.
Therefore, the online number of the game can be predicted in real time, and the difference caused by the prediction of the online number of the game through human experience in the prior art is avoided, so that more accurate online number prediction can be provided for engineers, the engineers can increase and decrease the capacity of the server according to the predicted value, and the resource waste of the game server is reduced.
In another embodiment of the present application, on the basis of the foregoing embodiment, as shown in fig. 3, fig. 3 is a schematic signaling interaction diagram of another data processing system according to an example of the present application, where the signaling interaction process includes:
and step S200, calculating the difference value between the online predicted value at the same time and the online number of people in the game.
Step S201, judging whether the difference value is smaller than a first preset value, if so, storing and displaying the online predicted value; and if not, determining that the online predicted value is an abnormal value.
In the embodiment, in order to verify the accuracy of the online prediction value, the inventor compares the online prediction value with the actual online number of people playing the game, and calculates whether the difference value of the online prediction value and the actual online number of people playing the game meets a preset range. When the difference exceeds the preset value, the system may determine that the current online predicted value is an abnormal data, and may perform compensation processing on the data accordingly, for example, as described in the following embodiments. And when the difference value between the predicted value and the actual value is within the preset range, the data processing system of the scheme is determined to be more accurate. If the deviation of the predicted value from the actual value within three days can be counted, the current polynomial function does not need to be adjusted if the average value of the deviation is within 7%.
The preset time and the preset range value may be set according to actual needs, and are not limited to the limitations in the above embodiments.
In addition, in another embodiment of the present application, a process of modifying the polynomial function when the difference between the online predicted value and the actual game online data exceeds the range is described. Referring to fig. 4, fig. 4 is a schematic signaling interaction diagram of another data processing system according to an example of the present application, where the signaling interaction process includes:
and step S300, creating a distribution function of the online number of the game people in a preset time period.
And S301, obtaining an extreme value of the distribution function.
In this embodiment, a function of the number of online players of the game at each moment of each day may be created for the collected historical data of the number of online players of the actual game with each day as a time period. And finding the extreme value distribution of the function on the basis of the function.
And S302, clustering the extreme values, and determining inflection point data of the distribution function.
And clustering all extreme values at the same moment, determining the corresponding relation between each extreme value and time, and defining the time corresponding to the extreme value as inflection point data. Wherein the extremum includes a maximum value and a minimum value of the daily function curve.
In this embodiment, the inflection point data is calculated to predict the trend of the number of online players at the inflection point time, for example, when the function extreme value at a certain time is maximum, the time is an inflection point, and after the time, the number of online players may be in a downward trend.
In another embodiment of the present application, as shown in fig. 5, fig. 5 is a schematic signaling interaction diagram of another data processing system according to an example of the present application, where the signaling interaction process includes:
and S400, drawing and displaying a curve of the online predicted value and the time and a curve of the online number of people in the game and the time.
It should be noted that the data processing device may store the actual value and the predicted value of the number of online players of the game, and draw a curve of the online predicted value and the time and a curve of the number of online players of the game and the time according to the values, and display the curves on the data processing device, so as to more intuitively display the online predicted data of the game and the number of online players of the actual game.
Referring to the embodiment, the data processing system provided by the present disclosure is introduced, as shown in fig. 6, a data processing device obtains game service data of each game server in real time, where the game service data at least includes the following fields: the server area where the game is located, the server type, the corresponding time, and the actual number of online players of the game. Then, according to the data in fig. 6, the data are merged into the actual number of online games at each time in a single large area, as shown in fig. 7, that is, the values of the actual number of online games at different server types at the same time in fig. 6 are added, as shown in 2016-06-1711: 00 game online people pcu of types M2, M1, and D12-60-200 are added.
Then, performing regression analysis on the number of online people in the actual game by using a least square method, for example, inputting the number of online people in the actual game from the current 0 point to the current time into an algorithm to obtain a polynomial function at the time, wherein the polynomial function is a functional relation between the online predicted number of people and time, and for example, the fitting polynomial function can be:
a0...5＝-387216235.6662412,16154411.678539163,-269208.8346228992,2240.241119044617,-9.307030356963782
when the time value is input into the current fitting polynomial function, the predicted value of the number of people in the current online game is obtained, as shown in fig. 8. Where datetime _ point is a time series of points, arranging the time of day starting from 5 minutes, for example 00: 30 is that the time-series point is 7. pred _ pcu _ no _1 is the prediction result of the first coarse prediction. As described above, since the polynomial function is changed according to the input actual game online person number, the online person number prediction value pred _ pcu shown in fig. 8 is changed.
In addition, the data of the number of online persons and the predicted number of persons in the game can be displayed in a drawing mode, as shown in fig. 9.
The data processing device provided by the embodiment of the present application is described below, and the data processing device described below and the data processing system described above may be referred to correspondingly.
Referring to fig. 10, fig. 10 is a schematic structural diagram of a data processing system disclosed in an embodiment of the present application, where the system includes:
the first obtaining module 100 is configured to obtain game service data of each game server in real time, where the game service data includes online number of people in a game;
the data generation module 200 is configured to preprocess the game service data to generate target game data, where the target game data includes the number of online players and time of the game in the same game area;
the first calculating module 300 is configured to perform regression analysis on the target game data according to a preset algorithm to obtain a polynomial function corresponding to the time and the online predicted value.
Preferably, also comprises
The second calculation module is used for calculating the difference value between the online predicted value at the same time and the online number of people in the game;
the judging module is used for judging whether the difference value is smaller than a first preset value or not, and if so, storing and displaying the online predicted value; and if not, determining that the online predicted value is an abnormal value.
Preferably, the method further comprises the following steps:
the creating module is used for creating a distribution function of the online number of the game people in a preset time period;
the second acquisition module is used for acquiring an extreme value of the distribution function;
and the determining module is used for clustering the extreme values and determining inflection point data of the distribution function.
Preferably, the method further comprises the following steps:
and the display module is used for drawing and displaying a curve of the online predicted value and the time.
The hardware structure of the server provided by the embodiment of the present invention may be as shown in fig. 11, and includes: a processor 1, a communication interface 2, a memory 3 and a communication bus 4;
wherein, the processor 1, the communication interface 2 and the memory 3 complete the communication with each other through the communication bus 4;
optionally, the communication interface 2 may be an interface of a communication module, such as an interface of a GSM module;
a processor 1 for executing a program;
a memory 3 for storing a program;
the program may include program code including computer operating instructions.
The processor 1 may be a central processing unit CPU or an application specific Integrated circuit asic or one or more Integrated circuits configured to implement embodiments of the present invention.
The memory 3 may comprise a high-speed RAM memory, and may further comprise a non-volatile memory (non-volatile memory), such as at least one disk memory.
Among them, the procedure can be specifically used for:
the method comprises the steps of obtaining game service data of each game server in real time, wherein the game service data comprise the number of online players of the game;
preprocessing the game service data to generate target game data, wherein the target game data comprise the number of online players and time of the game in the same game area;
and performing regression analysis on the target game data according to a preset algorithm to obtain a polynomial function corresponding to the time and the online predicted value.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (11)
1. A data processing system comprising: game server and data processing device, characterized in that,
the game server is used for sending game service data to the data processing device;
the data processing apparatus is configured to:
the method comprises the steps of obtaining game service data of each game server in real time, wherein the game service data comprise the number of online game people and the corresponding relation between the number of online game people and time;
preprocessing the game service data to generate target game data, wherein the target game data comprise the number of online players and time of the game in the same game area;
performing regression analysis on the target game data according to a preset algorithm to obtain a polynomial function corresponding to the time and an online predicted value, wherein the online predicted value is the predicted online number of people in the game;
calculating the difference value between the online predicted value at the same time and the online number of people in the game;
judging whether the difference value is smaller than a first preset value or not, and if so, storing and displaying the online predicted value; if not, the online predicted value is determined to be an abnormal value, and then whether the current polynomial function is adjusted or not is determined.
2. The data processing system of claim 1, wherein the data processing apparatus is further configured to:
creating a distribution function of the online number of the game in a preset time period;
obtaining an extreme value of the distribution function;
and clustering the extreme values, and determining inflection point data of the distribution function.
3. The data processing system of claim 1, wherein the data processing apparatus is further configured to:
and drawing and displaying a curve of the online predicted value and the time and a curve of the online number of the game and the time.
4. A data processing method, comprising:
the method comprises the steps of obtaining game service data of each game server in real time, wherein the game service data comprise the number of online players of the game;
preprocessing the game service data to generate target game data, wherein the target game data comprise the number of online players and time of the game in the same game area;
performing regression analysis on the target game data according to a preset algorithm to obtain a polynomial function corresponding to the time and an online predicted value, wherein the online predicted value is the predicted online number of people in the game;
calculating the difference value between the online predicted value at the same time and the online number of people in the game;
judging whether the difference value is smaller than a first preset value or not, and if so, storing and displaying the online predicted value; if not, the online predicted value is determined to be an abnormal value, and then whether the current polynomial function is adjusted or not is determined.
5. The data processing method of claim 4, wherein the predetermined algorithm is a least squares method, a random forest regression method, or a time series method.
6. The data processing method of claim 4, further comprising:
creating a distribution function of the online number of the game in a preset time period;
obtaining an extreme value of the distribution function;
and clustering the extreme values, and determining inflection point data of the distribution function.
7. The data processing method of claim 4,
and drawing a curve of the online predicted value and the time.
8. A data processing apparatus, comprising:
the first acquisition module is used for acquiring game service data of each game server in real time, wherein the game service data comprises the number of online game people and the corresponding relation between the number of online game people and time;
the data generation module is used for preprocessing the game service data to generate target game data, and the target game data comprise the number of online players and time of the game in the same game area;
the first calculation module is used for carrying out regression analysis on the target game data according to a preset algorithm to obtain a polynomial function corresponding to the time and an online predicted value, wherein the online predicted value is the predicted online number of people in the game;
the second calculation module is used for calculating the difference value between the online predicted value at the same time and the online number of people in the game;
the judging module is used for judging whether the difference value is smaller than a first preset value or not, and if so, storing and displaying the online predicted value; if not, the online predicted value is determined to be an abnormal value, and then whether the current polynomial function is adjusted or not is determined.
9. The data processing apparatus of claim 8, wherein the predetermined algorithm is a least squares method, a random forest regression method, or a time series method.
10. The data processing apparatus of claim 8, further comprising:
the creating module is used for creating a distribution function of the online number of the game people in a preset time period;
the second acquisition module is used for acquiring an extreme value of the distribution function;
and the determining module is used for clustering the extreme values and determining inflection point data of the distribution function.
11. The data processing apparatus of claim 8, further comprising:
and the display module is used for drawing and displaying a curve of the online predicted value and the time.
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| CN107329882A (en) * | 2017-06-12 | 2017-11-07 | 腾讯科技（深圳）有限公司 | Obtain method and apparatus, storage medium and the electronic installation of online data |
| CN110830820A (en) * | 2018-08-08 | 2020-02-21 | 北京国双科技有限公司 | Emergency data processing method and device |
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