CN111813535A - Resource configuration determining method and device and electronic equipment - Google Patents
Resource configuration determining method and device and electronic equipment Download PDFInfo
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Abstract
The embodiment of the application relates to a resource configuration determining method and device and electronic equipment. The method comprises the following steps: determining the use data of the resource item corresponding to the target object in the first statistical period; evaluating the use trend of the target object aiming at the resource item based on the use data of the resource item corresponding to the target object in the first statistical period to obtain an evaluation result; and determining a resource configuration strategy of the target object for the resource item based on the evaluation result. According to the scheme of the embodiment of the application, the use trend of the target object for the resource items is evaluated through the use data of the resource items corresponding to the target object in the statistical period, and the resource configuration strategy of the target object for the resource items is specified according to the evaluation result, so that a reasonable resource configuration conclusion is given, such as whether the resources are recovered or expanded, the intelligent telescopic scheduling of the resources is realized, and the purpose of resource allocation as required is achieved.
Description
Technical Field
The embodiment of the application relates to the technical field of data processing, in particular to a resource configuration determining method and device and electronic equipment.
Background
With the development of cloud computing technology, people use cloud applications more and more frequently in daily life. For the field of cloud resource management, particularly for enterprise-level cloud systems, how to reasonably allocate and recycle resources to achieve efficient utilization of the resources is a technical problem to be solved urgently at present.
Disclosure of Invention
The embodiment of the application aims to provide a resource allocation determining method, a resource allocation determining device and electronic equipment, which can analyze the use trend of a resource item corresponding to a target object, so as to specify a reasonable resource allocation strategy.
In order to achieve the above purpose, the embodiments of the present application are implemented as follows:
in a first aspect, a method for determining resource configuration is provided, including:
determining the use data of the resource item corresponding to the target object in the first statistical period;
evaluating the use trend of the target object aiming at the resource item based on the use data of the resource item corresponding to the target object in the first statistical period to obtain an evaluation result;
and determining a resource configuration strategy of the target object for the resource item based on the evaluation result.
In a second aspect, a resource configuration apparatus is provided, including:
the determining module is used for determining the use data of the resource item corresponding to the target object in the first statistical period;
the evaluation module is used for evaluating the use trend of the target object aiming at the resource items based on the use data of the resource items corresponding to the target object in the first statistical period to obtain an evaluation result;
and the resource configuration module is used for determining a resource configuration strategy of the target object aiming at the resource item based on the evaluation result.
In a third aspect, an electronic device is provided that includes: a memory, a processor, and a computer program stored on the memory and executable on the processor, the computer program being executed by the processor to:
determining the use data of the resource item corresponding to the target object in the first statistical period;
evaluating the use trend of the target object aiming at the resource item based on the use data of the resource item corresponding to the target object in the first statistical period to obtain an evaluation result;
and determining a resource configuration strategy of the target object for the resource item based on the evaluation result.
In a fourth aspect, a computer-readable storage medium is provided, having stored thereon a computer program which, when executed by a processor, performs the steps of:
determining the use data of the resource item corresponding to the target object in the first statistical period;
evaluating the use trend of the target object aiming at the resource item based on the use data of the resource item corresponding to the target object in the first statistical period to obtain an evaluation result;
and determining a resource configuration strategy of the target object for the resource item based on the evaluation result.
According to the scheme of the embodiment of the application, the use trend of the target object for the resource items is evaluated through the use data of the resource items corresponding to the target object in the statistical period, and the resource configuration strategy of the target object for the resource items is specified according to the evaluation result, so that a reasonable resource configuration conclusion is given, such as whether the resources are recovered or expanded, the intelligent telescopic scheduling of the resources is realized, and the purpose of resource allocation as required is achieved.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only some embodiments described in the embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without any creative efforts.
Fig. 1 is a first flowchart illustrating a resource allocation determining method according to an embodiment of the present application.
Fig. 2 is a second flowchart of a resource allocation determining method according to an embodiment of the present application.
Fig. 3 is a schematic structural flow diagram of a resource allocation determining apparatus according to an embodiment of the present application.
Fig. 4 is a schematic structural flow diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make those skilled in the art better understand the technical solutions in the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, 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 fall within the protection scope of the present application.
With the increasing popularity of cloud applications, how to efficiently utilize cloud resources becomes a technical problem to be solved urgently at present.
To this end, the present application provides a resource allocation determination scheme that can rationalize allocation or recovery of cloud resources (not limited to cloud resources).
In one aspect, as shown in fig. 1, an embodiment of the present application provides a method for determining resource configuration, including:
step S102, determining the use data of the resource item corresponding to the target object in the first statistical period.
The target object may be a device, a system, an individual, or a cluster. The resource items may be, but are not limited to, IT resources such as CPUs, memory, disks, etc.
And step S104, evaluating the use trend of the target object aiming at the resource item based on the use data of the resource item corresponding to the target object in the first statistical period to obtain an evaluation result.
In this step, the usage data of the resource item corresponding to the target object in the first statistical period may be compared with the usage data of the resource item corresponding to the sample object in the second statistical period, so as to determine a variation range of the usage data of the resource item corresponding to the target object in the first statistical period relative to the usage data of the resource item corresponding to the sample object in the second statistical period. And then, evaluating the use trend of the target object corresponding to the resource item based on the change amplitude.
For example, if the variation amplitude indicates that the usage data of the resource item corresponding to the target object in the first statistical period shows a negative increase, and the variation amplitude exceeds the preset threshold, it may reflect that the usage trend of the target object for the resource item is a decrease in usage demand.
It should be noted that, as a reasonable evaluation scheme, future use should be inferred based on historical use. Therefore, the second statistical period should not correspond to a time later than the first statistical period. Further, the sample object may be a target object, or may be another object belonging to the same type as the target object.
And step S106, determining a resource allocation strategy of the target object for the resource item based on the evaluation result.
It should be understood that operations such as expansion, reclamation, etc. may be performed on the target object for the resources of the resource item based on the resource configuration policy.
As can be known from the resource allocation determination method shown in fig. 1: according to the scheme of the embodiment of the application, the use trend of the target object for the resource items is evaluated through the use data of the resource items corresponding to the target object in the statistical period, and the resource configuration strategy of the target object for the resource items is specified according to the evaluation result, so that a reasonable resource configuration conclusion is given, such as whether the resources are recovered or expanded, the intelligent telescopic scheduling of the resources is realized, and the purpose of resource allocation as required is achieved.
The method of the embodiments of the present application is described in detail below.
The core of the embodiment of the application is to find out busy hour periods and idle hour periods for resource use, and predict the future use change trend based on the utilization rates of the busy hour periods and the idle hour periods of the resources, so as to make a resource configuration strategy with prospective property.
As shown in fig. 2, the main process includes:
step S201, determining the busy hour utilization rate and the idle hour utilization rate of the resource item corresponding to the first statistical period of the target object.
In this step, the busy-time usage rate and the idle-time usage rate of the target object for the resource item corresponding to each unit time interval in the first statistical cycle may be specifically determined.
And then, performing curve fitting on the utilization rate of the resource items corresponding to the target object in each unit time interval in the first statistical cycle based on a least square method (the curve fitting based on the least square method belongs to the prior art and is not repeated herein by way of example), and obtaining a fitting curve. It should be understood that the fitted curve is a two-dimensional image of the unit time period and the usage rate of the target object for the resource items for the unit time period.
And then, analyzing the information presented by the fitting curve, and determining the busy-time utilization rate and the idle-time utilization rate of the resource item corresponding to the target object in the first statistical period.
As one of the schemes for determining the busy hour usage rate.
The method of the embodiment of the application can determine the unit time interval in which the utilization rate of the resource items corresponding to the target object in the first statistical cycle is greater than the first preset threshold value as the busy hour unit time interval. And then, determining the utilization rate of the target object in the busy hour of the resource item corresponding to the first statistical cycle based on the utilization rate of the resource item corresponding to the target object in the busy hour unit period presented in the fitting curve. For example, the usage rate of the resource item corresponding to the target object in the busy hour unit period may be an average busy hour usage rate of the resource item corresponding to the target object in the first statistical cycle.
It should be understood that the first preset threshold may be flexibly set as a determination criterion for the busy hour unit period, and this is not specifically limited in this embodiment of the application. By way of exemplary introduction, the first preset threshold value is ═ maximum usage rate of the corresponding resource item of the target object in the first statistical period — average usage rate of the resource item corresponding to the target object in the first statistical period) × coefficient + average usage rate of the resource item corresponding to the target object in the first statistical period.
Similarly, the method is used as a scheme for determining the idle time utilization rate.
The method of the embodiment of the application can determine the unit time interval in which the utilization rate of the resource items corresponding to the target object in the first statistical period is smaller than the second preset threshold value as the idle unit time interval. And then, determining the idle time utilization rate of the resource item corresponding to the target object in the first statistical cycle based on the utilization rate of the resource item corresponding to the target object in the idle time unit period presented in the fitting curve. For example, the usage rate of the resource item corresponding to the target object in the idle time unit period may be an average idle time usage rate of the resource item corresponding to the target object in the first statistical period.
Similarly, the second preset threshold is not specifically limited in the embodiment of the present application. By way of exemplary introduction, the second preset threshold is equal to the average usage rate of the resource items corresponding to the target object in the first statistical period- (the average usage rate of the resource items corresponding to the target object in the first statistical period-the minimum usage rate of the corresponding resource items corresponding to the target object in the first statistical period) × coefficient.
It should be understood that the busy-time usage rate of the resource item corresponding to the first statistical cycle by the target object may be regarded as the minimum required amount of the target object for the resource item in the busy-time period, and the idle-time usage rate of the resource item corresponding to the first statistical cycle by the target object may be regarded as the minimum required amount of the target object for the resource item in the idle-time period.
In step S202, a usage trend of the target object for the resource item is evaluated based on the busy-time usage rate and the idle-time usage rate of the resource item corresponding to the first statistical period.
In this step, the busy-time usage rate and the idle-time usage rate of the resource item corresponding to the second statistical period of the sample object may be provided for reference.
If the usage data of the target object in the busy hour of the resource item corresponding to the first statistical period is positively increased relative to the usage data of the sample object in the busy hour of the resource item corresponding to the second statistical period, and the positive increase amplitude is greater than the preset threshold, it can be determined that the usage trend of the target object for the resource item in the busy hour period is in an increase state. On the contrary, if the usage data of the target object in the busy hour of the resource item corresponding to the first statistical period is increased negatively relative to the usage data of the sample object in the busy hour of the resource item corresponding to the second statistical period, and the magnitude of the negative increase is greater than the preset threshold, it may be determined that the usage trend of the target object for the resource item in the busy hour period is in a reduced state.
Similarly, if the idle usage data of the resource item corresponding to the target object in the first statistical period is in positive growth relative to the idle usage data of the resource item corresponding to the sample object in the second statistical period, and the positive growth amplitude is greater than the preset threshold, it may be determined that the usage trend of the target object for the resource item in the idle period is in a growth state. On the contrary, if the usage data of the target object in idle time of the resource item corresponding to the first statistical period is in negative increase relative to the busy usage data of the resource item corresponding to the sample object in the second statistical period, and the magnitude of the negative increase is greater than the preset threshold, it may be determined that the usage trend of the target object for the resource item in idle time period is in a reduced state.
Of course, in addition to the above comparison method, the usage area of the target object for the resource direction may be estimated based on the variation width of the target object relative to the busy time period (sum of busy time unit periods) and the idle time period (sum of idle time unit periods) corresponding to the sample object. For example, if the busy hour period of the resource item corresponding to the first statistical cycle of the target object is positively increased compared to the busy hour period of the resource item corresponding to the second statistical cycle of the sample data, and the positive increase is greater than the preset threshold, it may be determined that the usage trend of the target object for the resource item in the busy hour period is a reduced state. On the contrary, the target object is in a negative increase in the busy hour period of the resource item corresponding to the first statistical cycle compared with the busy hour period of the resource item corresponding to the second statistical cycle, and the magnitude of the negative increase is greater than the preset threshold, it can be determined that the usage trend of the target object for the resource item in the busy hour period is in a reduced state.
Step S203, based on the evaluation result, a resource allocation strategy of the target object for the resource item is formulated.
In this step, if the usage trend of the target object for the resource item in the busy hour period is a growing state, the corresponding resource allocation policy may expand the resource of the target object for the resource item in the busy hour period. On the contrary, if the usage trend of the target object for the resource item in the busy hour period is a reduced state, the corresponding resource allocation policy may recycle the resource of the target object for the resource item in the busy hour period.
Similarly, if the usage trend of the target object for the resource item in the idle period is in a growing state, the corresponding resource allocation policy may expand the resource of the target object for the resource item in the idle period. On the contrary, if the usage trend of the target object for the resource item in the busy hour period is a reduced state, the corresponding resource allocation policy may recycle the resource of the target object for the resource item in the idle hour period.
Therefore, the method of the embodiment of the application realizes automatic calculation when the resources are busy and comprehensive evaluation of the resource use condition and provides a scientific basis for resource allocation. The model for executing analysis has strong expansibility, such as the evaluation object and the evaluation index can be customized. In addition, the adaptability can be adjusted according to different evaluation objects and scenes, and personalized evaluation results and suggestions are output, so that the resources are distributed according to needs and maximum values, and the use benefits of the resources are guaranteed. The whole scheme is particularly suitable for a platform with limited resources, such as a cloud service system.
For the convenience of understanding the method of the embodiments of the present application, the following description is given by way of example with reference to practical applications.
In the practical application, a set of cloud resource analysis model is established, an intelligent analysis algorithm is adopted to analyze historical performance data and associated business health degree of cloud resources, and the practical use condition and use trend of the resources are comprehensively evaluated, so that a set of scientific scheme and data reference are provided for cloud resource allocation, and efficient utilization of the cloud resources is realized.
The cloud resource analysis model can automatically analyze the busy time period of the cloud resource running every day, analyze the periodic variation of the maximum value, the minimum value and the average value of the busy time period, and give a reasonable analysis evaluation report by combining the value of a service system, the estimated scale and the actual scale of the service system and the like, so that operators can make resource recovery, adjustment and redistribution decisions according to the change, and the traditional manual analysis and offline communication cost can be greatly reduced.
Assuming that the target object is host a, the usage evaluation scheme of the resource item corresponding to host a is as follows:
and establishing an evaluation model for the host A, and defining the indexes to be evaluated, such as CPU utilization rate, memory utilization rate, CPU utilization rate variation amplitude, memory utilization rate variation amplitude and the like.
And calculating the average utilization rate of the CPU and the average utilization rate of the memory in each time point every day by adopting an intelligent analysis algorithm, fitting a curve by a least square method, and determining the utilization rate of the CPU in busy hours and the utilization rate of the CPU in idle hours, the utilization rate of the memory in busy hours and the utilization rate of the memory in idle hours in one week of the host A from the fitted curve.
Then comparing the data with the CPU busy hour utilization rate, the CPU idle hour utilization rate, the memory busy hour utilization rate and the memory idle hour utilization rate of the host B to determine the variation amplitude of the CPU busy hour utilization rate, the CPU idle hour utilization rate, the memory busy hour utilization rate and the memory idle hour utilization rate of the host A relative to the host B
And finally, analyzing based on the variation amplitude of the CPU busy hour utilization rate, the variation amplitude of the CPU idle hour utilization rate, the variation amplitude of the memory busy hour utilization rate and the variation amplitude of the memory idle hour utilization rate of the host A relative to the host B, and outputting a CPU resource configuration strategy and a memory resource configuration strategy of the host A. For example, the analysis results indicate: the CPU utilization of the host a is high and continuously increases, and the memory usage of the host a is stable, so the corresponding resource allocation policy can expand the CPU resources for the host a. The administrator can rapidly adjust the CPU resources according to the suggestion, and can check detail comparison data of the analysis result to make further analysis and judgment.
If the target object is a cluster, the usage data of the resource item corresponding to the cluster in the first statistical period is determined based on the number of cores corresponding to the hosts of the cluster and the usage data of the resource item corresponding to the single core of each host of the cluster in the statistical period.
Generally, a cluster is composed of physical machines and virtual machines together, and the method of the embodiment of the present application needs to group and separately evaluate the physical machines and the virtual machines of the cluster, and then may further calculate the overall situation of the cluster.
The evaluation scheme for the cluster M is as follows:
and respectively establishing an evaluation model for the physical machine and the virtual machine in the cluster M, and calculating the CPU busy hour utilization rate and the CPU idle hour utilization rate, the memory busy hour utilization rate and the memory idle hour utilization rate in one week of the physical machine. The utilization rate of the virtual machine in a busy hour of a CPU and the utilization rate of the virtual machine in an idle hour of the CPU, the utilization rate of the virtual machine in a busy hour of a memory and the utilization rate of the virtual machine in an idle hour of the memory.
And then comparing the utilization rate of the cluster M in the last week during the busy hour of the CPU, the utilization rate of the CPU in the idle state, the utilization rate of the busy hour of the memory and the utilization rate of the memory in the idle state, and determining the variation amplitude of the cluster M in the week relative to the utilization rate of the last week during the busy hour of the CPU, the variation amplitude of the utilization rate of the CPU in the idle state, the variation amplitude of the utilization rate of the memory in the busy hour and the variation amplitude of the utilization rate of the memory in the idle.
And finally, analyzing based on the variation amplitude of the utilization rate of the cluster M in the current week relative to the busy hour in the last week, the variation amplitude of the utilization rate of the CPU in idle, the variation amplitude of the utilization rate of the memory in busy hour and the variation amplitude of the utilization rate of the memory in idle, and outputting a CPU resource configuration strategy and a memory resource configuration strategy of the cluster M.
Of course, in addition to determining the idle utilization rate and the busy utilization rate of the CPU and the memory of the cluster M, the average utilization rate of the CPU and the memory of the cluster M relative to the whole statistical period may also be determined. Correspondingly, the output evaluation result contains two parts of contents of the physical machine and the virtual machine, such as: compared with the previous statistical period, the average utilization rate of the CPU of the physical machine of the cluster M is low, and the average utilization rate of the memory is low; and if the average utilization rate of the CPU and the average utilization rate of the memory of the virtual machine are normal, the corresponding resource allocation strategy suggestion is as follows: and expanding CPU resources and memory resources of the physical machine. The administrator can expand the physical CPU resources and memory resources of the cluster M according to the suggestion of the resource configuration policy.
On the other hand, an embodiment of the present application further provides a resource allocation determining apparatus, as shown in fig. 3, including:
a determining module 301, configured to determine usage data of a resource item corresponding to a target object in a first statistical period;
the evaluation module 302 is configured to evaluate, based on usage data of a resource item corresponding to the target object in a first statistical period, a usage trend of the target object for the resource item to obtain an evaluation result;
a resource configuration module 303, configured to determine, based on the evaluation result, a resource configuration policy of the target object for the resource item.
As can be appreciated by the resource configuration determining apparatus shown in fig. 3: according to the scheme of the embodiment of the application, the use trend of the target object for the resource items is evaluated through the use data of the resource items corresponding to the target object in the statistical period, and the resource configuration strategy of the target object for the resource items is specified according to the evaluation result, so that a reasonable resource configuration conclusion is given, such as whether the resources are recovered or expanded, the intelligent telescopic scheduling of the resources is realized, and the purpose of resource allocation as required is achieved.
Optionally, the evaluation module 302 is specifically configured to:
and determining the variation amplitude of the usage data of the resource item corresponding to the target object in the first statistical period relative to the usage data of the resource item corresponding to the sample object in the second statistical period. And the time corresponding to the second statistical period is not later than the time corresponding to the first statistical period.
And evaluating the usage trend of the resource item corresponding to the target object based on the variation amplitude.
Optionally, the usage data of the resource item corresponding to the target object in the first statistical period includes: the target object is used at the busy time of the resource item corresponding to the first statistical period; and/or the target object is used at the idle time of the resource item corresponding to the first statistic period.
The determining module 301 is specifically configured to:
determining the utilization rate of the resource items corresponding to the target object in each unit time interval in the first statistical cycle;
performing curve fitting on the utilization rate of the resource items corresponding to each unit time interval of the target object in the first statistical cycle based on a least square method to obtain a fitting curve;
and determining the busy hour utilization rate and/or idle hour utilization rate of the resource item corresponding to the first statistical period of the target object based on the fitted curve.
As an exemplary introduction.
The determining module 301 specifically determines, as a busy hour unit period, a unit period in which the usage rate of the resource item corresponding to the target object in the first statistical cycle is greater than a first preset threshold (the first preset threshold is determined based on the average usage rate of the resource item corresponding to the target object in the first statistical cycle). And then determining the utilization rate of the target object in the busy hour of the resource item corresponding to the first statistical cycle based on the utilization rate of the resource item corresponding to the target object in the busy hour unit period presented in the fitting curve.
In addition, the determining module 301 may further determine, as an idle unit time period, a unit time period in which the usage rate of the resource item corresponding to the target object in the first statistical cycle is less than a second preset threshold (the second preset threshold is determined based on the average usage rate of the resource item corresponding to the target object in the first statistical cycle). And then, determining the idle time utilization rate of the resource item corresponding to the target object in the first statistical cycle based on the utilization rate of the resource item corresponding to the target object in the idle time unit period presented in the fitting curve.
Optionally, the usage data of the resource item corresponding to the target object in the first statistical cycle is determined based on the number of cores corresponding to each host of the cluster and the usage data of the resource item corresponding to a single core of each host of the cluster in the first statistical cycle.
Obviously, the resource allocation determining apparatus according to the embodiment of the present application may be used as the executing main body of the resource allocation determining method shown in fig. 1, and therefore, the resource allocation determining apparatus can implement the functions of the resource allocation determining method implemented in fig. 1 and fig. 2. Since the principle is the same, the detailed description is omitted here.
Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application. Referring to fig. 4, at a hardware level, the electronic device includes a processor, and optionally further includes an internal bus, a network interface, and a memory. The Memory may include a Memory, such as a Random-Access Memory (RAM), and may further include a non-volatile Memory, such as at least 1 disk Memory. Of course, the electronic device may also include hardware required for other services.
The processor, the network interface, and the memory may be connected to each other via an internal bus, which may be an ISA (Industry Standard Architecture) bus, a PCI (peripheral component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 4, but that does not indicate only one bus or one type of bus.
And the memory is used for storing programs. In particular, the program may include program code comprising computer operating instructions. The memory may include both memory and non-volatile storage and provides instructions and data to the processor.
The processor reads a corresponding computer program from the nonvolatile memory into the memory and then runs the computer program to form the question-answer pair data mining device on a logic level. The processor is used for executing the program stored in the memory and is specifically used for executing the following operations:
determining the use data of the resource item corresponding to the target object in the first statistical period;
evaluating the use trend of the target object aiming at the resource item based on the use data of the resource item corresponding to the target object in the first statistical period to obtain an evaluation result;
and determining a resource configuration strategy of the target object for the resource item based on the evaluation result.
The electronic device of the embodiment of the application evaluates the use trend of the target object for the resource items through the use data of the resource items corresponding to the target object in the statistical period, and specifies the resource configuration strategy of the target object for the resource items according to the evaluation result, so that a reasonable resource configuration conclusion is given, such as whether the resource is recovered or expanded, the intelligent flexible scheduling of the resource is realized, and the purpose of resource allocation according to needs is achieved.
The resource allocation determination method disclosed in the embodiment of fig. 1 of the present application may be applied to a processor, or may be implemented by a processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.
It should be understood that the electronic device according to the embodiment of the present application may implement the functions of the resource configuration determining apparatus in the embodiments shown in fig. 1 and fig. 2, which are not described herein again.
Of course, besides the software implementation, the electronic device of the present application does not exclude other implementations, such as a logic device or a combination of software and hardware, and the like, that is, the execution subject of the following processing flow is not limited to each logic unit, and may also be hardware or a logic device.
Furthermore, an embodiment of the present application also provides a computer-readable storage medium storing one or more programs, where the one or more programs include instructions, which when executed by a portable electronic device including a plurality of application programs, can cause the portable electronic device to perform the method of the embodiment shown in fig. 1, and specifically to perform the following method:
determining the use data of the resource item corresponding to the target object in the first statistical period;
evaluating the use trend of the target object aiming at the resource item based on the use data of the resource item corresponding to the target object in the first statistical period to obtain an evaluation result;
and determining a resource configuration strategy of the target object for the resource item based on the evaluation result.
It should be understood that the above-mentioned instructions, when executed by a portable electronic device including a plurality of application programs, can enable the resource configuration determining apparatus described above to implement the functions of the embodiments shown in fig. 1 and fig. 2, and will not be described in detail herein.
As will be appreciated by one skilled in the art, embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, the description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The above description is only an example of the present specification, and is not intended to limit the present specification. Various modifications and alterations to this description will become apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present specification should be included in the scope of the claims of the present specification.
Claims (10)
1. A method for determining resource allocation, comprising:
determining the use data of the resource item corresponding to the target object in the first statistical period;
evaluating the use trend of the target object aiming at the resource item based on the use data of the resource item corresponding to the target object in the first statistical period to obtain an evaluation result;
and determining a resource configuration strategy of the target object for the resource item based on the evaluation result.
2. The method of claim 1,
evaluating the usage trend of the target object for the resource item based on the usage data of the resource item corresponding to the target object in the first statistical period, including:
determining the variation amplitude of the usage data of the resource item corresponding to the target object in the first statistical period relative to the usage data of the resource item corresponding to the sample object in the second statistical period; the time corresponding to the second statistical period is not later than the time corresponding to the first statistical period;
and evaluating the usage trend of the resource item corresponding to the target object based on the variation amplitude.
3. The method according to claim 1 or 2,
the usage data of the resource item corresponding to the target object in the first statistical period comprises:
the target object is used at the busy time of the resource item corresponding to the first statistical period; and/or the presence of a gas in the gas,
and the target object is used at the idle time of the resource item corresponding to the first statistical period.
4. The method of claim 3,
the first statistical cycle comprises at least one unit period of time;
determining usage data of a resource item corresponding to the target object in the first statistical period, including:
determining the utilization rate of the resource items corresponding to the target object in each unit time interval in the first statistical cycle;
performing curve fitting on the utilization rate of the resource items corresponding to the target object in each unit time interval in the first statistical cycle based on a least square method to obtain a fitting curve;
and determining the busy hour utilization rate and/or idle hour utilization rate of the resource item corresponding to the first statistical period of the target object based on the fitted curve.
5. The method of claim 4,
determining the busy hour utilization rate of the resource item corresponding to the target object in the first statistical period based on the fitted curve, including:
determining a unit time interval in which the utilization rate of the resource items corresponding to the target object in the first statistical cycle is greater than a first preset threshold value as a busy hour unit time interval; the first preset threshold is determined based on the average utilization rate of the resource items corresponding to the target object in a first statistical period;
and determining the utilization rate of the target object in the busy hour of the resource item corresponding to the first statistical cycle based on the utilization rate of the resource item corresponding to the target object in the busy hour unit period presented in the fitting curve.
6. The method of claim 4,
determining the idle utilization rate of the resource item corresponding to the target object in the first statistical period based on the fitted curve, including:
determining a unit time interval in which the utilization rate of the resource items corresponding to the target object in the first statistical cycle is smaller than a second preset threshold value as an idle unit time interval; the second preset threshold is determined based on the average utilization rate of the resource items corresponding to the target object in the first statistical period;
and determining the idle utilization rate of the resource item corresponding to the target object in the first statistical cycle based on the utilization rate of the resource item corresponding to the target object in the idle unit time period presented in the fitting curve.
7. The method of claim 1,
the usage data of the resource item corresponding to the target object in the first statistical period is determined based on the number of cores corresponding to each host of the cluster and the usage data of the resource item corresponding to a single core of each host of the cluster in the first statistical period.
8. An apparatus for resource configuration determination, comprising:
the determining module is used for determining the use data of the resource item corresponding to the target object in the first statistical period;
the evaluation module is used for evaluating the use trend of the target object aiming at the resource items based on the use data of the resource items corresponding to the target object in the first statistical period to obtain an evaluation result;
and the resource configuration module is used for determining a resource configuration strategy of the target object aiming at the resource item based on the evaluation result.
9. An electronic device includes: a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the computer program is executed by the processor to:
determining the use data of the resource item corresponding to the target object in the first statistical period;
evaluating the use trend of the target object aiming at the resource item based on the use data of the resource item corresponding to the target object in the first statistical period to obtain an evaluation result;
and determining a resource configuration strategy of the target object for the resource item based on the evaluation result.
10. A computer-readable storage medium having a computer program stored thereon, the computer program when executed by a processor implementing the steps of:
determining the use data of the resource item corresponding to the target object in the first statistical period;
evaluating the use trend of the target object aiming at the resource item based on the use data of the resource item corresponding to the target object in the first statistical period to obtain an evaluation result;
and determining a resource configuration strategy of the target object for the resource item based on the evaluation result.
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Application publication date: 20201023 |