CN110888733A - Cluster resource use condition processing method and device and electronic equipment - Google Patents
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Abstract
The application discloses a cluster resource use condition processing method, a cluster resource use condition processing device and electronic equipment, wherein the cluster resource use condition processing method comprises the following steps: acquiring the use condition of cluster resources in a preset historical time period; analyzing the use condition of the cluster resources to determine the current residual cluster resources; and based on the current residual cluster resources, analyzing and predicting the use condition of the cluster resources in the current preset time period through a preset real-time analysis model to obtain a prediction result aiming at the use condition of the cluster resources in the current preset time period. According to the method and the device, the accurate prediction of the future use condition of the cluster resources is realized, so that the configuration of the cluster resources can be timely and effectively adjusted, the waste of the cluster resources is avoided, the utilization rate of the cluster resources is improved, and the consumption cost of the cluster resources is reduced; and through effectual discernment, reduce invalid alarm information's sending to the at utmost, promote user's use and feel.
Description
Technical Field
The present application relates to the field of application software technologies, and in particular, to a method and an apparatus for processing a cluster resource usage situation, and an electronic device.
Background
In the prior art, for allocating and using the cluster resources, corresponding cluster resource configuration is usually performed on each device in advance, so that corresponding processing can be performed by using the cluster resources configured in advance. However, with the design of configuring the cluster resources in advance, although the adjustment configuration of the cluster resources is not required to be performed when each device is processed, in such a process, the corresponding adjustment of the cluster resources cannot be performed according to the actual use condition, which may cause a large amount of waste of the cluster resources, reduce the utilization rate of the cluster resources, and increase the consumption cost of the cluster resources. Meanwhile, a large amount of invalid alarm information can be generated due to the fact that effective identification cannot be carried out, and therefore the stability of the whole cluster resource platform is affected.
Disclosure of Invention
The application provides a method and a device for processing the use condition of cluster resources and electronic equipment, so as to realize effective control and adjustment of the cluster resources.
In a first aspect, a method for processing cluster resource usage is provided, including:
acquiring the use condition of cluster resources in a preset historical time period;
analyzing the use condition of the cluster resources to determine the current residual cluster resources;
and based on the current residual cluster resources, analyzing and predicting the use condition of the cluster resources in the current preset time period through a preset real-time analysis model to obtain a prediction result aiming at the use condition of the cluster resources in the current preset time period.
In one possible implementation, obtaining cluster resource usage over a predetermined historical period of time includes:
querying a database storing cluster resource use conditions, and extracting the cluster resource use conditions in a preset historical time period from the database;
the cluster resource use conditions stored in the database are arranged according to a preset arrangement sequence.
In one possible implementation, the cluster resource usage stored in the database is arranged according to a preset arrangement order, and the method includes:
the use condition of the cluster resources is stored in the database according to the sequence of the acquisition time, and the use condition of the cluster resources is acquired based on the preset time.
In a possible implementation manner, based on the current remaining cluster resources, performing analysis and prediction processing on the usage of the cluster resources in the current preset time period through the predetermined real-time analysis model to obtain a prediction result of the usage of the cluster resources in the current preset time period, including:
judging through a preset real-time analysis model based on the current residual cluster resources and the preset cluster resource use condition of each time period, and determining whether the resource quantity of the current residual cluster resources and the resource quantity of the cluster resource use condition in the current preset time period meet a preset relation;
and if the resource quantity of the current remaining cluster resource and the resource quantity of the cluster resource use condition in the current preset time period can be determined to meet the preset relation or the resource quantity of the current remaining cluster resource and the resource quantity of the cluster resource use condition in the current preset time period can be determined not to meet the preset relation, obtaining a prediction result aiming at the cluster resource use condition in the current preset time period.
In one possible implementation, the method further includes: if it cannot be determined whether the resource amount of the current remaining cluster resource and the resource amount of the cluster resource usage in the current preset time period satisfy the preset relationship,
analyzing the use condition of the cluster resources through a preset predictive analysis model, and determining the use rule of the use condition of the cluster resources in the historical time period;
and predicting the use condition of the cluster resources in the current preset time period based on the use rule of the use condition of the cluster resources in the historical time period to obtain a prediction result aiming at the use condition of the cluster resources in the current preset time period.
In a possible implementation manner, if an abnormal cluster resource usage condition exists in the cluster resource usage conditions in the historical time period, a notification message carrying the labeling information is sent, wherein the labeling information is information for labeling the abnormal cluster resource usage condition.
In one possible implementation manner, after obtaining the prediction result of the cluster resource usage within the current preset time period, at least one of the following processes is further included:
based on a preset strategy, carrying the prediction result in a notification message for pushing;
storing the prediction result in the database.
In a second aspect, an apparatus for processing cluster resource usage is provided, including:
the acquisition unit is used for acquiring the use condition of the cluster resources in a preset historical time period;
the first processing unit is used for analyzing the use condition of the cluster resources and determining the current residual cluster resources;
and the second processing unit is used for analyzing and predicting the use condition of the cluster resources in the current preset time period through a preset real-time analysis model based on the current residual cluster resources to obtain a prediction result aiming at the use condition of the cluster resources in the current preset time period.
In a possible implementation manner, the obtaining unit is configured to query a database storing usage of cluster resources, and extract usage of cluster resources in a predetermined historical time period from the database;
and the cluster resource use conditions in the database are arranged and stored according to a preset arrangement sequence.
In one possible implementation, the cluster resource usage stored in the database is arranged according to a preset arrangement order, and the method includes:
the use condition of the cluster resources is stored in the database according to the sequence of the acquisition time, and the use condition of the cluster resources is acquired based on the preset time.
In a possible implementation manner, the second processing unit is specifically configured to determine, based on the current remaining cluster resources and the pre-configured use condition of the cluster resources in each time period, through a predetermined real-time analysis model, and determine whether the resource amount of the current remaining cluster resources and the resource amount of the use condition of the cluster resources in the current preset time period satisfy a preset relationship; and if the resource quantity of the current remaining cluster resource and the resource quantity of the cluster resource use condition in the current preset time period can be determined to meet the preset relation or the resource quantity of the current remaining cluster resource and the resource quantity of the cluster resource use condition in the current preset time period can be determined not to meet the preset relation, obtaining a prediction result aiming at the cluster resource use condition in the current preset time period.
In a possible implementation manner, the second processing unit is further configured to, if it cannot be determined whether the resource amount of the currently remaining cluster resource and the resource amount of the cluster resource usage in the current preset time period satisfy a preset relationship, analyze the cluster resource usage by using a predetermined predictive analysis model, and determine a usage rule of the cluster resource usage in the historical time period; and predicting the use condition of the cluster resources in the current preset time period based on the use rule of the use condition of the cluster resources in the historical time period to obtain a prediction result aiming at the use condition of the cluster resources in the current preset time period.
In a possible implementation manner, if there is an abnormal cluster resource usage in the historical time period, the second processing unit is configured to send a notification message carrying tagging information, where the tagging information is information for tagging the abnormal cluster resource usage.
In one possible implementation, the method further includes:
the third processing unit is used for carrying the prediction result in a notification message for pushing based on a preset strategy; and/or for storing the prediction result in the database.
In a third aspect, a computer-readable storage medium is provided, on which a computer program is stored, which when executed by a processor implements the above-mentioned cluster resource usage handling method.
In a fourth aspect, an electronic device is provided, comprising: the system comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete mutual communication through the communication bus;
the memory is used for storing at least one executable instruction, and the executable instruction enables the processor to execute the operation corresponding to the cluster resource use condition processing method.
Compared with the prior art, the method has the advantages that:
the cluster resource use condition in a preset historical time period is obtained; analyzing the obtained cluster resource use condition to determine the current residual cluster resource; and then, based on the current residual cluster resources, analyzing and predicting the use condition of the cluster resources in the current preset time period through a preset real-time analysis model to obtain a prediction result aiming at the use condition of the cluster resources in the current preset time period. The method and the device realize accurate prediction of the use condition of the future cluster resources so as to effectively adjust the configuration of the cluster resources in time, thereby avoiding the waste of the cluster resources, improving the utilization rate of the cluster resources and reducing the consumption cost of the cluster resources; and through effectual discernment, reduce invalid alarm information's sending to the at utmost, promote user's use and feel.
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Fig. 1 is a flowchart of a cluster resource usage processing method provided in an embodiment of the present application;
fig. 2 is a schematic processing flow diagram of a possible implementation manner of a cluster resource usage processing method provided in an embodiment of the present application;
FIG. 3 is a schematic diagram of a linear analysis of an analytical prediction model provided by an embodiment of the present application;
fig. 4 is a schematic structural diagram of a cluster resource usage processing apparatus according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of an electronic device based on a cluster resource usage processing method according to an embodiment of the present application.
Detailed Description
The present application provides a method and an apparatus for processing a cluster resource usage situation, and an electronic device, and the following describes in detail a specific embodiment of the present application with reference to the accompanying drawings.
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary only for the purpose of explaining the present application and are not to be construed as limiting the present application.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or wirelessly coupled. As used herein, the term "and/or" includes all or any element and all combinations of one or more of the associated listed items.
It will be understood by those within the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
To make the objects, technical solutions and advantages of the present application more clear, embodiments of the present application will be described in further detail below with reference to the accompanying drawings.
As shown in fig. 1, a schematic flow chart of a cluster resource usage processing method provided in the present application is shown, where the method includes the following steps:
step S101, obtaining the use condition of cluster resources in a preset historical time period;
step S102, analyzing the use condition of the cluster resources, and determining the current residual cluster resources;
step S103, based on the current residual cluster resources, analyzing and predicting the use condition of the cluster resources in the current preset time period through a preset real-time analysis model to obtain a prediction result aiming at the use condition of the cluster resources in the current preset time period.
In the embodiment, the accurate prediction of the future use condition of the cluster resources is realized, so that the configuration of the cluster resources can be timely and effectively adjusted, the waste of the cluster resources is avoided, the utilization rate of the cluster resources is improved, and the consumption cost of the cluster resources is reduced.
Based on the technical solution provided in the embodiment of the present application, the following explains the technical solution in detail, as shown in fig. 2, a specific processing flow chart of a possible implementation manner of the cluster resource usage processing method provided in the embodiment of the present application is provided.
In one possible implementation, the processing of the foregoing step S101 specifically includes the processing of the following step S201.
Step S201, querying a database, and extracting the cluster resource usage in a predetermined historical time period.
In this step, the database storing the cluster resource usage is queried, so that the required cluster resource usage is extracted from the database, and in this embodiment, the required cluster resource usage is a usage in a predetermined historical time period.
For the database storing the use conditions of the cluster resources, the use conditions of the stored cluster resources are stored in the database after being collected based on preset time, and the use conditions of the cluster resources stored in the database are arranged according to a preset arrangement sequence.
In one possible implementation, polling collection of the cluster resource usage of all users is performed at intervals (e.g., every 5 minutes), and the cluster resource usage of each user collected each time is stored in the database according to the sequence of collection time.
In one possible implementation, the foregoing processing of step S102 specifically includes the processing of step S202 to step S206 described below.
Step S202, analyzing the obtained cluster resource use condition, and determining the current residual cluster resource.
In this step, by analyzing the use condition of the cluster resources in the acquired historical time period, how many cluster resources are left currently can be determined.
Step S203, determining whether the resource amount of the current remaining cluster resource and the resource amount of the cluster resource usage in the current preset time period satisfy a preset relationship.
In this step, it may be specifically determined, based on the current remaining cluster resources and the pre-configured cluster resource usage in each time period, whether the resource amount of the current remaining cluster resources and the resource amount of the cluster resource usage in the current preset time period satisfy the preset relationship by using a predetermined real-time analysis model.
Specifically, if it can be determined that the resource amount of the currently remaining cluster resource and the resource amount of the cluster resource usage condition in the current preset time period satisfy the preset relationship or the resource amount of the currently remaining cluster resource and the resource amount of the cluster resource usage condition in the current preset time period do not satisfy the preset relationship, the process goes to step S204, otherwise, the process goes to step S205.
In a possible implementation manner, the determining that the preset relationship is satisfied may include determining that the resource amount of the current remaining cluster resource can support the resource amount of the cluster resource usage in the current preset time period, or determining that the resource amount of the current remaining cluster resource cannot support the resource amount of the cluster resource usage in the current preset time period at all, such as the current remaining 1T resource amount, where the current preset time period is 2 days, the maximum resource amount occupied every day is 2T, and it is obvious that the remaining 1T resource amount cannot support the resource amount occupation in the future 2 days.
If the current remaining resource amount of the cluster resource can not be determined to support the resource amount of the cluster resource usage in the current preset time period, for example, the current remaining resource amount of 3T, the current preset time period is 2 days, the maximum resource amount occupied every day is 2T, but the actual resource amount occupation every day is not determined, that is, if 1T is actually occupied every day, the remaining resource amount can meet the resource amount usage of 2 days in the future, but if 2T is occupied every two days, the remaining resource amount cannot meet the resource amount usage of 2 days in the future, which is the resource amount that the current remaining resource amount of the cluster resource can support the cluster resource usage in the current preset time period.
The real-time analysis model is a model that compares an average value of the cluster resource usage over a past period of time (e.g., 2-7 days) with an incremental value of a current preset period of time (e.g., 24, 48 hours) based on the current usage.
And step S204, obtaining a prediction result aiming at the cluster resource use condition in the current preset time period.
Step S205, analyzing the use condition of the cluster resources, and determining the use rule of the use condition of the cluster resources in the historical time period.
In this step, analysis is performed through a predetermined predictive analysis model, so that the usage rule of the cluster resource usage in the historical time period is determined.
Wherein, in one possible implementation manner, the analytical prediction model is constructed by a "linear regression/linear regression" manner.
The analytical prediction model may be represented by an equation: y + b X + e, where a denotes the intercept, b denotes the slope of the line, and e is the error term. A relationship is established between the dependent variable (Y) and one or more independent variables (X) by using the best fit straight line (i.e., the regression line), as shown in fig. 3. With this equation, the value of the target variable can be predicted from a given predictor variable(s).
And step S206, predicting based on the determined use rule to obtain a prediction result corresponding to the use condition of the cluster resources in the current preset time period.
In this step, after determining the usage rule of the cluster resource usage in the historical time period, the cluster resource usage in the current preset time period is predicted based on the usage rule, and a prediction result corresponding to the cluster resource usage in the current preset time period is obtained.
If abnormal cluster resource use conditions exist in the cluster resource use conditions in the historical time period, a notification message carrying the labeling information can be sent, wherein the labeling information is information for labeling the abnormal cluster resource use conditions.
Step S207, subsequent processing based on the prediction result.
After obtaining the prediction result of the cluster resource usage within the current preset time period, the following processing may be further performed:
(1) and storing the prediction result in a database.
In the processing, only the corresponding prediction result needs to be stored in the database, so that the corresponding check can be performed when necessary subsequently.
(2) And carrying the prediction result in the notification message for pushing based on a preset strategy.
In the processing, the corresponding prediction result is carried in a notification message and pushed to the corresponding operation user through a pre-configured strategy, so that the operation user performs corresponding adjustment processing according to the prediction result.
Wherein, the preset policy may include one of the following:
directly sending the notification message carrying the prediction result;
and sending the notification message carrying the prediction result at preset time intervals.
Of course, the preset strategy is only exemplified to illustrate two possible implementations listed in the technical solution of the present application, and is not limited thereto.
(3) And storing the prediction result in a database, and carrying the prediction result in a notification message for pushing based on a preset strategy.
In this process, not only the corresponding prediction result is stored in the database, but also the corresponding prediction result is carried in a notification message and pushed to the corresponding operation user through a pre-configured policy, so that the operation user performs the corresponding adjustment process according to the prediction result.
In the embodiment, the accurate prediction of the future use condition of the cluster resources is realized, so that the configuration of the cluster resources can be timely and effectively adjusted, the waste of the cluster resources is avoided, the utilization rate of the cluster resources is improved, and the consumption cost of the cluster resources is reduced; and through effectual discernment, reduce invalid alarm information's sending to the at utmost, promote user's use and feel.
Based on the technical solutions provided in the above-mentioned present application, a corresponding explanation is made below with a specific embodiment.
In one possible implementation, the database stores cluster resource usage of all users collected in multiple time periods, and each time period is 5 minutes, i.e., collection processing of cluster resource usage of all users is performed every 5 minutes. Extracting corresponding data of cluster resource use conditions in all historical days from the database, and performing corresponding analysis on the extracted cluster resource use conditions in all historical days, so as to determine that the resource quantity of the current remaining cluster resource is 3T, the maximum resource quantity occupation in each day is 2T, and whether the remaining resource quantity can meet the resource quantity occupation condition of 2 days in the future or not is determined, so that whether the remaining resource quantity meets the resource quantity occupation condition of 2 days in the future or not can not be accurately determined on the basis. Therefore, the predetermined analysis prediction model needs to be scheduled to perform corresponding processing, the resource amount of the cluster resources which are only 1T occupied on average each day is determined by determining the cluster resource usage for 7 days in history, based on this, the prediction result that the remaining 3T resource amount can meet the resource amount of the cluster resources required for 2 days in the future can be determined, and then the prediction result of the corresponding cluster resource usage for 2 days in the future is carried in the notification message to be sent to the operation and maintenance personnel, so that the operation and maintenance personnel can perform corresponding operation processing based on the prediction result.
An embodiment of the present application provides a cluster resource usage processing apparatus 40, as shown in fig. 4, where the information processing apparatus 40 may include: an acquisition unit 41, a first processing unit 42, a second processing unit 43 and a third processing unit 44.
An obtaining unit 41, configured to obtain a cluster resource usage in a predetermined history time period;
the first processing unit 42 is configured to analyze the usage of the cluster resources, and determine the currently remaining cluster resources;
and the second processing unit 43 is configured to perform analysis and prediction processing on the usage of the cluster resources in the current preset time period through a predetermined real-time analysis model based on the current remaining cluster resources, so as to obtain a prediction result for the usage of the cluster resources in the current preset time period.
In one possible implementation, the obtaining unit 41 is configured to query a database storing usage of cluster resources, and extract usage of cluster resources in a predetermined historical time period from the database;
and the cluster resource use conditions in the database are arranged and stored according to a preset arrangement sequence.
In one possible implementation, the cluster resource usage stored in the database is arranged according to a preset arrangement order, and the method includes:
the use condition of the cluster resources is stored in the database according to the sequence of the acquisition time, and the use condition of the cluster resources is acquired based on the preset time.
In a possible implementation manner, the second processing unit 43 is specifically configured to determine, based on the current remaining cluster resources and the pre-configured cluster resource usage in each time period, through a predetermined real-time analysis model, whether the resource amount of the current remaining cluster resources and the resource amount of the cluster resource usage in the current preset time period satisfy a preset relationship; and if the resource quantity of the current remaining cluster resource and the resource quantity of the cluster resource use condition in the current preset time period can be determined to meet the preset relation or the resource quantity of the current remaining cluster resource and the resource quantity of the cluster resource use condition in the current preset time period can be determined not to meet the preset relation, obtaining a prediction result aiming at the cluster resource use condition in the current preset time period.
In a possible implementation manner, the second processing unit 43 is further configured to, if it cannot be determined whether the resource amount of the currently remaining cluster resource and the resource amount of the cluster resource usage in the current preset time period satisfy the preset relationship, analyze the cluster resource usage by using a predetermined predictive analysis model, and determine a usage rule of the cluster resource usage in the historical time period; and predicting the use condition of the cluster resources in the current preset time period based on the use rule of the use condition of the cluster resources in the historical time period to obtain a prediction result aiming at the use condition of the cluster resources in the current preset time period.
In a possible implementation manner, if there is an abnormal cluster resource usage in the historical time period, the second processing unit 43 is configured to send a notification message carrying tagging information, where the tagging information is information for tagging the abnormal cluster resource usage.
In one possible implementation, the method further includes:
the third processing unit 44 is configured to carry the prediction result in a notification message for pushing based on a preset policy; and/or for storing the prediction result in the database.
The method and the device realize accurate prediction of the use condition of the future cluster resources so as to effectively adjust the configuration of the cluster resources in time, thereby avoiding the waste of the cluster resources, improving the utilization rate of the cluster resources and reducing the consumption cost of the cluster resources; and through effectual discernment, reduce invalid alarm information's sending to the at utmost, promote user's use and feel.
An embodiment of the present application further provides an electronic device, as shown in fig. 5. The electronic device 2000 may include, but is not limited to: a processor 2001, a memory 2002, a communication bus 2003 for connecting the different components of the device to enable communication between the different components. The memory 2002 may store computer programs and data, and the processor 2001 may execute corresponding actions and processes by calling the computer programs in the memory 2002, so as to implement the methods in the embodiments of the present application. The structure of the electronic device 2000 shown in the figure does not limit the embodiments of the present application.
The electronic device 2000 may also include a display 2004. The processor 2001 may display a user interface, prompt information, or interactive information with an end user, as desired or capable of being displayed, to the user via the display 2004 as the actions or processes are performed.
The processor 2001 may be a CPU, general purpose processor, DSP, ASIC, FPGA or other programmable logic device, transistor logic device, hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. The processor 2001 may also be a combination of computing functions, e.g., comprising one or more microprocessors, DSPs and microprocessors, and the like.
The communication bus 2003 may include a path to transfer information between the above components. The communication bus 2003 may be a PCI bus or an EISA bus, etc. The communication bus 2003 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus.
The memory 2002 may be, but is not limited to, a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, an EEPROM, a CD-ROM or other optical disk storage, optical disk storage (including compact disk, laser disk, optical disk, digital versatile disk, blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
The electronic device 2000 may also include input/output components 2005 for enabling input/output of information and user interaction with the device via the input/output components 2005.
In practical applications, the input/output component 2005 can be configured according to practical needs and can include, but is not limited to, a keyboard, a mouse, a touch screen, an audio component, a video component, and the like. For example, the electronic device may receive a trigger instruction of a user through the touch screen, and the processor may perform a corresponding action or process based on the trigger instruction of the user. The audio/video components may be configured for input and/or output of audio/video signals of the device. The audio components may include, but are not limited to, speakers, microphones, etc., and the video components may include, but are not limited to, cameras, video interfaces (HDMI, VGA, and/or DVI interfaces), etc.
It is to be appreciated that the various input/output components 2005 described above can implement the processing of information alone or in combination.
The electronic device 2000 can further include a communication component 2006, the communication component 2006 being configured for enabling communicative interaction between the electronic device 2000 and other devices (e.g., electronic devices, storage devices). The communication component 2006 can include, but is not limited to, a wired communication component (e.g., a mobile network communication unit such as 3G, 4G, 5G, etc.), a wireless communication component (e.g., a bluetooth, WIFI communication unit), a USB communication component, an audio component, a video component, and the like.
The electronic device 2000 may further include a power management module 2007, where the power management module 2007 may be configured to supply power to the device, convert power of the device, manage charging and discharging of the power, and the like, and the module may be further configured with a charging interface.
It should be noted that the electronic device according to the embodiment of the present application may be implemented as, but not limited to, a smart phone, a smart television, a Personal Digital Assistant (PDA), a tablet computer, a desktop computer, a portable electronic device (e.g., a portable computer), a vehicle-mounted device, and the like.
The embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the method for processing the cluster resource usage is implemented.
It will be understood by those within the art that each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented by computer program instructions. Those skilled in the art will appreciate that the computer program instructions may be implemented by a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, implement the aspects specified in the block or blocks of the block diagrams and/or flowchart illustrations disclosed herein.
The modules of the device can be integrated into a whole or can be separately deployed. The modules can be combined into one module, and can also be further split into a plurality of sub-modules.
Those skilled in the art will appreciate that the drawings are merely schematic representations of one preferred embodiment and that the blocks or flow diagrams in the drawings are not necessarily required to practice the present application.
Those skilled in the art will appreciate that the modules in the devices in the embodiments may be distributed in the devices in the embodiments according to the description of the embodiments, and may be correspondingly changed in one or more devices different from the embodiments. The modules of the above embodiments may be combined into one module, or further split into multiple sub-modules.
The above application serial numbers are for descriptive purposes only and do not represent the merits of the embodiments.
The disclosure of the present application is only a few specific embodiments, but the present application is not limited to these, and any variations that can be made by those skilled in the art are intended to fall within the scope of the present application.
Claims (10)
1. A cluster resource usage processing method is characterized by comprising the following steps:
acquiring the use condition of cluster resources in a preset historical time period;
analyzing the use condition of the cluster resources to determine the current residual cluster resources;
and based on the current residual cluster resources, analyzing and predicting the use condition of the cluster resources in the current preset time period through a preset real-time analysis model to obtain a prediction result aiming at the use condition of the cluster resources in the current preset time period.
2. The method of claim 1, wherein obtaining cluster resource usage over a predetermined historical period of time comprises:
querying a database storing cluster resource use conditions, and extracting the cluster resource use conditions in a preset historical time period from the database;
the cluster resource use conditions stored in the database are arranged according to a preset arrangement sequence.
3. The method of claim 2, wherein the cluster resource usage stored in the database is arranged according to a preset arrangement order, comprising:
the use condition of the cluster resources is stored in the database according to the sequence of the acquisition time, and the use condition of the cluster resources is acquired based on the preset time.
4. The method according to any one of claims 1 to 3, wherein the analyzing and predicting the usage of the cluster resources in the current preset time period through the predetermined real-time analysis model based on the current remaining cluster resources to obtain a prediction result for the usage of the cluster resources in the current preset time period comprises:
judging through a preset real-time analysis model based on the current residual cluster resources and the preset cluster resource use condition of each time period, and determining whether the resource quantity of the current residual cluster resources and the resource quantity of the cluster resource use condition in the current preset time period meet a preset relation;
and if the resource quantity of the current remaining cluster resource and the resource quantity of the cluster resource use condition in the current preset time period can be determined to meet the preset relation or the resource quantity of the current remaining cluster resource and the resource quantity of the cluster resource use condition in the current preset time period can be determined not to meet the preset relation, obtaining a prediction result aiming at the cluster resource use condition in the current preset time period.
5. The method of claim 4, further comprising: if it cannot be determined whether the resource amount of the current remaining cluster resource and the resource amount of the cluster resource usage in the current preset time period satisfy the preset relationship,
analyzing the use condition of the cluster resources through a preset predictive analysis model, and determining the use rule of the use condition of the cluster resources in the historical time period;
and predicting the use condition of the cluster resources in the current preset time period based on the use rule of the use condition of the cluster resources in the historical time period to obtain a prediction result corresponding to the use condition of the cluster resources in the current preset time period.
6. The method of claim 5, wherein if an abnormal cluster resource usage exists in the cluster resource usage in the historical time period, sending a notification message carrying annotation information, wherein the annotation information is information for annotating the abnormal cluster resource usage.
7. The method of claim 5, wherein after obtaining the prediction result for the cluster resource usage within the current preset time period, the method further comprises at least one of:
based on a preset strategy, carrying the prediction result in a notification message for pushing;
storing the prediction result in the database.
8. A cluster resource usage processing apparatus, comprising:
the acquisition unit is used for acquiring the use condition of the cluster resources in a preset historical time period;
the first processing unit is used for analyzing the use condition of the cluster resources and determining the current residual cluster resources;
and the second processing unit is used for analyzing and predicting the use condition of the cluster resources in the current preset time period through a preset real-time analysis model based on the current residual cluster resources to obtain a prediction result aiming at the use condition of the cluster resources in the current preset time period.
9. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a computer program which, when being executed by a processor, carries out the cluster resource usage handling method of any one of claims 1-7.
10. An electronic device, comprising: the system comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete mutual communication through the communication bus;
the memory is used for storing at least one executable instruction, and the executable instruction causes the processor to execute the operation corresponding to the cluster resource use condition processing method in any one of claims 1-7.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114189482A (en) * | 2021-12-14 | 2022-03-15 | 郑州阿帕斯数云信息科技有限公司 | Control method, device and system for cluster resources |
| CN115378842A (en) * | 2022-08-26 | 2022-11-22 | 中国银行股份有限公司 | Resource monitoring method, device, storage medium and equipment |
Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090187606A1 (en) * | 2008-01-21 | 2009-07-23 | Claus Allweil | Optimized modification of a clustered computer system |
| CN102427473A (en) * | 2011-11-28 | 2012-04-25 | 中国联合网络通信集团有限公司 | Method and system for constructing cross-platform resource |
| CN105468458A (en) * | 2015-11-26 | 2016-04-06 | 北京航空航天大学 | Resource scheduling method and system of computer cluster |
| CN105591809A (en) * | 2015-10-12 | 2016-05-18 | 杭州华三通信技术有限公司 | Resource distribution method and device |
| CN105589750A (en) * | 2015-07-07 | 2016-05-18 | 杭州华三通信技术有限公司 | CPU (Central Processing Unit) resource scheduling method and server |
| CN105872114A (en) * | 2016-06-22 | 2016-08-17 | 北京邮电大学 | Video monitoring cloud platform resource scheduling method and device |
| US20160292608A1 (en) * | 2015-04-03 | 2016-10-06 | Alibaba Group Holding Limited | Multi-cluster management method and device |
| CN106201661A (en) * | 2016-07-20 | 2016-12-07 | 北京百度网讯科技有限公司 | Method and apparatus for elastic telescopic cluster virtual machine |
| CN106326002A (en) * | 2015-07-10 | 2017-01-11 | 阿里巴巴集团控股有限公司 | Resource scheduling method, device and equipment |
| US20170078850A1 (en) * | 2015-09-14 | 2017-03-16 | International Business Machines Corporation | Predicting location-based resource consumption in mobile devices |
| CN107315636A (en) * | 2016-04-26 | 2017-11-03 | 中国移动通信集团河北有限公司 | A kind of resource availability method for early warning and device |
| CN107343023A (en) * | 2017-05-25 | 2017-11-10 | 北京奇艺世纪科技有限公司 | Resource allocation methods, device and electronic equipment in a kind of Mesos management cluster |
| CN108009016A (en) * | 2016-10-31 | 2018-05-08 | 华为技术有限公司 | A kind of balancing resource load control method and colony dispatching device |
| CN108073448A (en) * | 2016-11-15 | 2018-05-25 | 北京金山云网络技术有限公司 | Host resource allocation methods, device, host dispatching method and device |
| CN108427604A (en) * | 2018-02-06 | 2018-08-21 | 华为技术有限公司 | Resource adjusting method, device and the cloud platform of cluster |
-
2018
- 2018-09-11 CN CN201811057086.6A patent/CN110888733B/en active Active
Patent Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090187606A1 (en) * | 2008-01-21 | 2009-07-23 | Claus Allweil | Optimized modification of a clustered computer system |
| CN102427473A (en) * | 2011-11-28 | 2012-04-25 | 中国联合网络通信集团有限公司 | Method and system for constructing cross-platform resource |
| US20160292608A1 (en) * | 2015-04-03 | 2016-10-06 | Alibaba Group Holding Limited | Multi-cluster management method and device |
| CN106161525A (en) * | 2015-04-03 | 2016-11-23 | 阿里巴巴集团控股有限公司 | A kind of many cluster management methods and equipment |
| CN105589750A (en) * | 2015-07-07 | 2016-05-18 | 杭州华三通信技术有限公司 | CPU (Central Processing Unit) resource scheduling method and server |
| CN106326002A (en) * | 2015-07-10 | 2017-01-11 | 阿里巴巴集团控股有限公司 | Resource scheduling method, device and equipment |
| US20170078850A1 (en) * | 2015-09-14 | 2017-03-16 | International Business Machines Corporation | Predicting location-based resource consumption in mobile devices |
| CN105591809A (en) * | 2015-10-12 | 2016-05-18 | 杭州华三通信技术有限公司 | Resource distribution method and device |
| CN105468458A (en) * | 2015-11-26 | 2016-04-06 | 北京航空航天大学 | Resource scheduling method and system of computer cluster |
| CN107315636A (en) * | 2016-04-26 | 2017-11-03 | 中国移动通信集团河北有限公司 | A kind of resource availability method for early warning and device |
| CN105872114A (en) * | 2016-06-22 | 2016-08-17 | 北京邮电大学 | Video monitoring cloud platform resource scheduling method and device |
| CN106201661A (en) * | 2016-07-20 | 2016-12-07 | 北京百度网讯科技有限公司 | Method and apparatus for elastic telescopic cluster virtual machine |
| CN108009016A (en) * | 2016-10-31 | 2018-05-08 | 华为技术有限公司 | A kind of balancing resource load control method and colony dispatching device |
| CN108073448A (en) * | 2016-11-15 | 2018-05-25 | 北京金山云网络技术有限公司 | Host resource allocation methods, device, host dispatching method and device |
| CN107343023A (en) * | 2017-05-25 | 2017-11-10 | 北京奇艺世纪科技有限公司 | Resource allocation methods, device and electronic equipment in a kind of Mesos management cluster |
| CN108427604A (en) * | 2018-02-06 | 2018-08-21 | 华为技术有限公司 | Resource adjusting method, device and the cloud platform of cluster |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114189482A (en) * | 2021-12-14 | 2022-03-15 | 郑州阿帕斯数云信息科技有限公司 | Control method, device and system for cluster resources |
| CN115378842A (en) * | 2022-08-26 | 2022-11-22 | 中国银行股份有限公司 | Resource monitoring method, device, storage medium and equipment |
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