CN108897673A - Power system capacity appraisal procedure and device - Google Patents
Power system capacity appraisal procedure and device Download PDFInfo
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- CN108897673A CN108897673A CN201810731843.7A CN201810731843A CN108897673A CN 108897673 A CN108897673 A CN 108897673A CN 201810731843 A CN201810731843 A CN 201810731843A CN 108897673 A CN108897673 A CN 108897673A
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- G06F11/30—Monitoring
- G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
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Abstract
The disclosure provides a kind of power system capacity appraisal procedure and device.Power system capacity appraisal procedure includes：Supervisory control system running data and hardware operation data；System data capacity is determined according to the system operation data；Obtain the capacity relevance parameter of the system operation data Yu the hardware operation data；System physical capacity is determined according to the capacity relevance parameter；Power system capacity is determined according to the system data capacity and the system physical capacity.The power system capacity appraisal procedure that the disclosure provides can obtain more accurate power system capacity assessment result under conditions of not influencing system operation, not increasing cost with dynamic realtime assessment system capacity.
Description
Technical field
This disclosure relates to which field of computer technology, is capable of dynamic realtime assessment system capacity in particular to one kind
Power system capacity appraisal procedure and device.
Background technique
With the arrival of internet+epoch, SOA and micro services framework are increasingly deep, and quantity of service constantly expands, using ring
Border is increasingly complicated, and service dependence constantly changes, and understands power system capacity situation in real time, carries out assessment to power system capacity as weight
Want target.
In the related technology, mainly pushed by line presses survey method come assessment system capacity in survey method and line.Line pushes survey method
The flow on line is copied directly to testing service device by tool, is applied when bottleneck occurs in testing service device highest
QPS (Query Per Second, query rate per second), then calculate that the system in outlet is held by on-line off-line conversion coefficient
Amount.It presses survey method mainly by specifying different weights for different server when loading poll on line, and is gradually increased a certain
The weight of server makes the flow of this server much larger than other servers, until performance bottleneck occurs in the server.This
Bottleneck may be the physics bottleneck such as CPU, LOAD, memory, bandwidth, it is also possible to the softwares bottleneck such as RT, failure rate, QPS fluctuation.When
When performance bottleneck occurs in single machine performance, application QPS at this time is denoted as single-machine capacity, cluster is obtained according to cluster server quantity
Power system capacity.
Pressure survey and line pushing are surveyed time-consuming and laborious on line, and what is reflected is all the power system capacity pressed when surveying.It is fast in internet
Today of speed development, the speed of program version iteration is surprising, is all once pressed for the iteration of each version, the variation of environment
It surveys to carry out Capacity Assessment be unpractical, and does not have operability.
It should be noted that information is only used for reinforcing the reason to the background of the disclosure disclosed in above-mentioned background technology part
Solution, therefore may include the information not constituted to the prior art known to persons of ordinary skill in the art.
Summary of the invention
The disclosure be designed to provide a kind of power system capacity appraisal procedure and power system capacity assesses device, at least existing
Overcome the problems, such as caused by the limitation and defect due to the relevant technologies that pressure assessment estimates that at high cost, real-time is low to a certain extent.
According to the first aspect of the embodiments of the present disclosure, a kind of power system capacity appraisal procedure is provided, including：Supervisory control system running
Data and hardware operation data；System data capacity is determined according to the system operation data；Obtain the system operation data
With the capacity relevance parameter of the hardware operation data；System physical capacity is determined according to the capacity relevance parameter；Root
Power system capacity is determined according to the system data capacity and the system physical capacity.
It is described that system data capacity is determined according to the system operation data in a kind of exemplary embodiment of the disclosure
Including：
System operational parameters are determined according to the system operation data；
The corresponding multiple data processing bottleneck values of a running unit are determined according to the system operational parameters, it will be described more
Cell capability of the minimum value as the running unit in a data processing bottleneck value；
System resource occupation proportion is determined according to the system operation data of running units multiple in system and cell capability；
The system data capacity is determined according to the system operation data and the system resource occupation proportion.
It is described to determine a running unit according to the system operational parameters in a kind of exemplary embodiment of the disclosure
Corresponding multiple data processing bottleneck values include：
The task execution parameter for corresponding to multiple tasks type is obtained according to the system operational parameters；
The most execution numbers per second for corresponding to each task type are determined according to the task execution parameter.
In a kind of exemplary embodiment of the disclosure, the system operation data according to running units multiple in system
Determine that system resource occupation proportion includes with cell capability：
Each running unit is determined with corresponding cell capability according to the current operating value of the multiple running unit
First resource occupation proportion；
The sum of first resource occupation proportion by the multiple running unit is used as the system resource occupation proportion.
It is described to obtain the system operation data and hardware operation number in a kind of exemplary embodiment of the disclosure
According to capacity relevance parameter include：
The system operation data and the hardware operation data are fitted according to a variety of approximating methods more to obtain
A fitting result；
According to the corresponding approximating method of fitting parameter maximum value in multiple fitting results determine the system operation data with
The incidence relation of the hardware operation data, and capacity relevance parameter is set by the corresponding parameter of the approximating method.
It is described to determine that system physical holds according to the capacity relevance parameter in a kind of exemplary embodiment of the disclosure
Amount includes：
Multiple physics bottleneck values are determined according to the system operation data and the capacity relevance parameter；It will be the multiple
Minimum value in physics bottleneck value is set as the system physical capacity.
It is described to be held according to the system data capacity and the system physical in a kind of exemplary embodiment of the disclosure
It measures and determines that power system capacity includes：
Using the small value among the system data capacity and the system physical capacity as power system capacity.
According to the second aspect of an embodiment of the present disclosure, a kind of power system capacity assessment device is provided, including：
Data monitoring module is set as supervisory control system running data and hardware operation data；
Software capacity evaluation module is set as determining system data capacity according to the system operation data；
Relevance evaluation module is set as obtaining the system operation data related to the capacity of the hardware operation data
Property parameter；
Hardware capabilities evaluation module is set as determining system physical capacity according to the capacity relevance parameter；
Comprehensive assessment module is set as determining that system is held according to the system data capacity and the system physical capacity
Amount.
According to the third aspect of the disclosure, a kind of power system capacity assessment device is provided, including：Memory；And it is coupled to
The processor of affiliated memory, the processor is configured to the instruction based on storage in the memory, executes as above-mentioned
Method described in any one.
According to the fourth aspect of the disclosure, a kind of computer readable storage medium is provided, program is stored thereon with, the program
The power system capacity appraisal procedure as described in above-mentioned any one is realized when being executed by processor.
The embodiment of the present disclosure is by supervisory control system running data and hardware operation data, according to timing according to latest data pair
System performance index is calculated, to obtain the data handling capacity and physical capacity of system, can timely and effectively be calculated
The real time capacity of system out.Efficiency is surveyed due to without artificial participation, greatly reducing pressure survey cost, improving pressure, it is ensured that is counted
According to real-time, continually changing program execution environments can be successfully managed.
It should be understood that above general description and following detailed description be only it is exemplary and explanatory, not
The disclosure can be limited.
Detailed description of the invention
The drawings herein are incorporated into the specification and forms part of this specification, and shows the implementation for meeting the disclosure
Example, and together with specification for explaining the principles of this disclosure.It should be evident that the accompanying drawings in the following description is only the disclosure
Some embodiments for those of ordinary skill in the art without creative efforts, can also basis
These attached drawings obtain other attached drawings.
Fig. 1 is the flow chart of power system capacity appraisal procedure in disclosure exemplary embodiment.
Fig. 2 is the sub-process figure of power system capacity appraisal procedure in disclosure exemplary embodiment.
Fig. 3 is the sub-process figure of power system capacity appraisal procedure in disclosure exemplary embodiment.
Fig. 4 is the sub-process figure of power system capacity appraisal procedure in disclosure exemplary embodiment.
Fig. 5 is the sub-process figure of power system capacity appraisal procedure in disclosure exemplary embodiment.
Fig. 6 is the sub-process figure of power system capacity appraisal procedure in disclosure exemplary embodiment.
Fig. 7 is a kind of block diagram of power system capacity assessment device in one exemplary embodiment of the disclosure.
Fig. 8 is the block diagram of a kind of electronic equipment in one exemplary embodiment of the disclosure.
A kind of schematic diagram of computer readable storage medium in one exemplary embodiment of Fig. 9 disclosure.
Specific embodiment
Example embodiment is described more fully with reference to the drawings.However, example embodiment can be with a variety of shapes
Formula is implemented, and is not understood as limited to example set forth herein；On the contrary, thesing embodiments are provided so that the disclosure will more
Fully and completely, and by the design of example embodiment comprehensively it is communicated to those skilled in the art.Described feature, knot
Structure or characteristic can be incorporated in any suitable manner in one or more embodiments.In the following description, it provides perhaps
More details fully understand embodiment of the present disclosure to provide.It will be appreciated, however, by one skilled in the art that can
It is omitted with technical solution of the disclosure one or more in the specific detail, or others side can be used
Method, constituent element, device, step etc..In other cases, be not shown in detail or describe known solution to avoid a presumptuous guest usurps the role of the host and
So that all aspects of this disclosure thicken.
In addition, attached drawing is only the schematic illustrations of the disclosure, identical appended drawing reference indicates same or similar portion in figure
Point, thus repetition thereof will be omitted.Some block diagrams shown in the drawings are functional entitys, not necessarily necessary and object
The entity managed or be logically independent is corresponding.These functional entitys can be realized using software form, or in one or more
These functional entitys are realized in hardware module or integrated circuit, or in heterogeneous networks and/or processor device and/or microcontroller
These functional entitys are realized in device.
Disclosure example embodiment is described in detail with reference to the accompanying drawing.
Fig. 1 schematically shows the flow chart of power system capacity appraisal procedure in disclosure exemplary embodiment.With reference to Fig. 1, it is
System capacity evaluating method 100 may include：
Step S1, supervisory control system running data and hardware operation data；
Step S2 determines system data capacity according to the system operation data；
Step S3 obtains the capacity relevance parameter of the system operation data Yu the hardware operation data；
Step S4 determines system physical capacity according to the capacity relevance parameter；
Step S5 determines power system capacity according to the system data capacity and the system physical capacity.
The embodiment of the present disclosure is by supervisory control system running data and hardware operation data, according to timing according to latest data pair
System performance index is calculated, to obtain the data handling capacity and physical capacity of system, can timely and effectively be calculated
The real time capacity of system out.Efficiency is surveyed due to without artificial participation, greatly reducing pressure survey cost, improving pressure, it is ensured that is counted
According to real-time, continually changing program execution environments can be successfully managed.
In the following, each step to power system capacity appraisal procedure 100 is described in detail.
In step S1, supervisory control system running data and hardware operation data.
In the embodiments of the present disclosure, system operation data for example may include database access data, database connection number
According to, thread parameter, service logic consumption data etc.；Hardware operation data may include CPU usage, network bandwidth occupancy
Deng.
It can be according to predetermined period timing acquisition system operation data and hardware operation data, to guarantee the timely of data
Property, to run ring in continually changing programs such as other services constantly upgrading of the continuous iteration of application version, system dependence
Newest power system capacity assessment result is obtained under border in time.
In step S2, system data capacity is determined according to the system operation data.
Fig. 2 is a sub-process figure of step S2.
With reference to Fig. 2, in one exemplary embodiment of the disclosure, step S2 may include：
Step S21 determines system operational parameters according to the system operation data；
Step S22 determines the corresponding multiple data processing bottleneck values of a running unit according to the system operational parameters,
Using the minimum value in the multiple data processing bottleneck value as the cell capability of the running unit；
Step S23 determines that system resource accounts for cell capability according to the system operation data of running units multiple in system
Use ratio；
Step S24 determines that the system data holds according to the system operation data and the system resource occupation proportion
Amount.
System operational parameters are, for example, that database access number per second, database access time, service logic execute the time
Deng.It for example can be to be averaged according to the method that system operation data determines system operational parameters.For example, being run according to system
Data determine the database access number in 10 seconds be 60 times, each access time be respectively 6ms, 10ms ..., 14ms etc.,
Then 6 can be set by database access number per second, be by the average value that the database access time takes each secondary access time
10ms.System operational parameters can also there are many, those skilled in the art can according to the actual situation self-setting calculate be
The type and calculation method for operating parameter of uniting.
Fig. 3 is the sub-process figure of step S22.
With reference to Fig. 3, in the disclosed embodiment, step S22 may include：
Step S221 obtains the task execution parameter for corresponding to multiple tasks type according to the system operational parameters；
Step S222 determines the most execution per second for corresponding to each task type according to the task execution parameter
Number.
For the process of assessment system data capacity, in the embodiments of the present disclosure, it can determine that system executes first
Application program and application program in include multiple running units, running unit is, for example, the corresponding method of application program
(method).Next, determining the corresponding time-consuming detail of each method according to the calculated system operational parameters of previous step.
For example, average QPS is 200 if a method is within certain sampling time, average time-consuming is 100ms, is corresponded to
Database access number per second be 6 times, each time-consuming 10ms, that is, database total time-consuming 60ms, service logic time-consuming
40ms.Wherein database and service logic time-consuming are two different task types, 6 times, 10ms, 40ms etc. is corresponding to task
The task execution parameter of type.
If the maximum number of connections of database connection pool is 30, the thread pool for executing the method is up to 50 (for the sake of simple temporarily
When do not consider the switching surfaces of thread), then it is 30*1000/60 that database, which corresponds to single machine highest QPS (data processing bottleneck value),
=500 times, the single machine highest QPS (data processing bottleneck value) of service logic is 50*1000/40=1250 times, it is clear that this side
On the database, that is, the single machine highest QPS of this method is 500 times to the bottleneck point of method, i.e. the corresponding unit of this method holds
Amount (maximum times per second for executing this method) is 500 times.
If this method is optimized by modes such as software upgradings, database is accessed to time-consuming every time and falls below 5ms,
Average visits become 4 times, that is, database total time-consuming becomes 20ms, and service logic time-consuming is still 40ms, at this time
The single machine highest QPS of database be 30*1000/20=1500 times, it is clear that bottleneck point at this time in service logic, that is, this
Single machine highest QPS, that is, cell capability of a method is 1250 times.
Fig. 4 is the sub-process figure of step S23.
With reference to Fig. 4, in the disclosed embodiment, step S23 may include：
Step S231, it is determining each described with corresponding cell capability according to the current operating value of the multiple running unit
The first resource occupation proportion of running unit；
Step S232 occupies the sum of first resource occupation proportion of the multiple running unit as the system resource
Ratio.
It, can be corresponding current according to this method in system operation data after determining the corresponding cell capability of each method
Operating value determines its corresponding first resource occupation proportion.For example, such as the corresponding cell capability C of method iiIt is 500 times, and is somebody's turn to do
The current operating value TPS (Transaction Per Second, issued transaction amount per second) of method is 100 times, then method i is corresponding
First resource occupation proportion Pi=Ti/Ci=100/500*100%=20%, wherein TiFor the TPS value of method i.
Since an application program is corresponding with multiple methods, can by the first resource occupation proportion of each method it
With as system resource occupation proportion, P=Σ Pi=Σ [Ti/Ci], wherein P is system resource occupation proportion.For example, using journey
The P for three methods that sequence includesiIt is 20%, 15%, 25%, then system resource occupation proportion at this time is 60%.
If showing that the single machine TPS at application program current time is T according to system operation dataA, then putting aside
In the case where CPU, network bandwidth, the corresponding system data capacity, that is, single-machine capacity C of the application programA=TA/P。
In step S3, the capacity relevance parameter of the system operation data Yu the hardware operation data is obtained.
Fig. 5 is the sub-process figure of step S3.
With reference to Fig. 5, in the disclosed embodiment, step S3 may include：
Step S31 is fitted the system operation data and the hardware operation data according to a variety of approximating methods
To obtain multiple fitting results；
Step S32 determines that the system is transported according to the corresponding approximating method of fitting parameter maximum value in multiple fitting results
The incidence relation of row data and the hardware operation data, and capacity correlation ginseng is set by the corresponding parameter of the approximating method
Number.
In addition to the corresponding system data capacity of software, the corresponding system physical capacity of hardware is also the weight of system for restricting capacity
Want index.For the correlativity for determining hardware corresponding system physical capacity and power system capacity, use in the embodiments of the present disclosure
The method of fitting analyzes system operation data and hardware operation data, so that incidence formula is obtained, thus further
Determine system physical capacity.
It can be derived that accurate incidence formula for any approximating method of determination, a variety of approximating methods can be used to including
System operation data and the data matrix of hardware operation data are fitted, according to the parameter in fitting result to approximating method into
Row selection, each corresponding a kind of data type of data column in data matrix.
Function corrcoef it is, for example, possible to use MATLAB be include CPU usage data and corresponding with its moment
Data matrix including application program TPS generates sample correlation coefficient matrix, and the range of related coefficient can be set to -1 to 1：
When related coefficient is close to 1, indicate there are positive linear relationships between data column, i.e., it is positive related；
When related coefficient close -1, indicate there is negative linear relationship between data column, i.e., it is reversed related；
When related coefficient is close or equal to 0, almost without linear relationship between expression data column.
After loading data sample (such as count.dat), correlation matrix is calculated by corrcoef (count),
Assuming that the correlation matrix generated is as follows：
1.0000 0.9588
0.9588 1.0000
In above-mentioned matrix, all related coefficients then all have between each pair of data column of sample data relatively strong all close to 1
Positive correlation, sample set can be fitted using linear regression analysis predicted method.Pass through One-variable Linear Regression
The fit equation obtained can beWherein, xtIndicate value, that is, CPU utilization rate of independent variable,Indicate dependent variable
Value, that is, TPS, a, b represent the parameter of unary linear regression equation.
In some embodiments, if passing through the correlation in the correlation matrix that corrcoef (count) is calculated
Coefficient is less than threshold value (such as 0.8), indicates that strong linear relationship is not present between data column.It is quasi- that nonlinear curve can be used at this time
It closes.Can be used including but not limited to exponent approximation, Fourier approaches, Gaussian approximation, interpolation are approached, it is multi-form approach, power is forced
Closely, a variety of modes of approaching such as rational is approached, smoothly approached, sine curve approaches carry out curve fitting, and compare fitting parameter.
For example, being approached using FourierObtained fitting parameter can be with
For：
SSE:0.02709
R-square:0.9978
Adjusted R-square:0.9913
RMSE:0.1164
Wherein, R-square is the determination coefficient of curvilinear equation, it is to characterize the degree of closeness being fitted, closer 1,
The degree of closeness for then showing that the model is fitted data is higher.
If in a variety of fit approach, R-square in the above results is closest to 1, then it represents that it is pair that Fourier, which approaches,
A kind of best approximating method of sample set fitting.At this point it is possible to capacity relevance parameter is determined according to the fitting result,
That is the correlativity of system physical capacity and hardware operation data.
In step S4, system physical capacity is determined according to the capacity relevance parameter.
Fig. 6 is the sub-process figure of step S4.
With reference to Fig. 6, in the disclosed embodiment, step S4 may include：
Step S41 determines multiple physics bottleneck values according to the system operation data and the capacity relevance parameter；
The minimum value in the multiple physics bottleneck value is set the system physical capacity by step S42.
One physics bottleneck value can be calculated to each hardware operation data according to system operation data.For example, can be with
Corresponding TPS value, i.e. QPS when CPU usage is 100% is calculated according to CPU usage and capacity relevance parameter.Together
Reason, also it can be concluded that the physics bottleneck value of other physical resources such as network bandwidth, and by the minimum value in multiple physics bottleneck values
It is set as system physical capacity.
In step S5, power system capacity is determined according to the system data capacity and the system physical capacity.
In the embodiments of the present disclosure, the small value among the system data capacity and the system physical capacity can be made
For power system capacity.For example, system data capacity be 500 times, system physical capacity be 400 times, then at this time the maximum QPS of system by
It is limited to system physical capacity and is only possible to be 400 times, current physical environment powerlessly undertakes bigger QPS.
By determining power system capacity according to system data capacity and system physical capacity, which kind of factor system can analyze out is
About power system capacity, to formulate targeted improvement plan.
The embodiment of the present disclosure is by real-time monitoring system operation data and hardware operation data, dynamic computing system capacity,
Pressure survey mode can be replaced to carry out Capacity Assessment, realize real-time capacity planning.With overcoming existing pressure survey mode real-time, people
The problems such as power is at high cost, physics is at high cost, time cost is high.
Corresponding to above method embodiment, the disclosure also provides a kind of power system capacity assessment device, can be used in execution
State embodiment of the method.
Fig. 7 schematically shows a kind of block diagram of power system capacity assessment device in one exemplary embodiment of the disclosure.
With reference to Fig. 7, power system capacity assessment device 700 may include：
Data monitoring module 71 is set as supervisory control system running data and hardware operation data；
Software capacity evaluation module 72 is set as determining system data capacity according to the system operation data；
Relevance evaluation module 73 is set as obtaining the capacity phase of the system operation data with the hardware operation data
Closing property parameter；
Hardware capabilities evaluation module 74 is set as determining system physical capacity according to the capacity relevance parameter；
Comprehensive assessment module 75 is set as determining that system is held according to the system data capacity and the system physical capacity
Amount.
In a kind of exemplary embodiment of the disclosure, software capacity evaluation module 72 includes：
Parameter determination unit 721 is set as determining system operational parameters according to the system operation data；
Cell capability determination unit 722 is set as determining that a running unit is corresponding according to the system operational parameters
Multiple data processing bottleneck values are held the minimum value in the multiple data processing bottleneck value as the unit of the running unit
Amount；
Resources occupation rate determination unit 723 is set as system operation data and list according to running units multiple in system
First capacity determines system resource occupation proportion；
Data capacity determination unit 724 is set as according to the system operation data and the system resource occupation proportion
Determine the system data capacity.
In a kind of exemplary embodiment of the disclosure, cell capability determination unit 722 is set as being transported according to the system
Row parameter obtains the task execution parameter for corresponding to multiple tasks type；It is determined and is corresponded to each according to the task execution parameter
Most execution numbers per second of the task type.
In a kind of exemplary embodiment of the disclosure, resources occupation rate determination unit 723 is set as：According to the multiple
The current operating value of running unit determines the first resource occupation proportion of each running unit with corresponding cell capability；It will
The sum of first resource occupation proportion of the multiple running unit is used as the system resource occupation proportion.
In a kind of exemplary embodiment of the disclosure, relevance evaluation module 73 is set as：According to a variety of approximating methods
The system operation data and the hardware operation data are fitted to obtain multiple fitting results；It is tied according to multiple fittings
The corresponding approximating method of fitting parameter maximum value determines being associated with for the system operation data and the hardware operation data in fruit
Relationship, and capacity relevance parameter is set by the corresponding parameter of the approximating method.
In a kind of exemplary embodiment of the disclosure, hardware capabilities evaluation module 74 is set as being run according to the system
Data and the capacity relevance parameter determine multiple physics bottleneck values；By the minimum value setting in the multiple physics bottleneck value
For the system physical capacity.
In a kind of exemplary embodiment of the disclosure, comprehensive assessment module 75 be set as by the system data capacity with
Small value among the system physical capacity is as power system capacity.
Since each function of device 700 has been described in detail in its corresponding embodiment of the method, the disclosure in this not
It repeats again.
It should be noted that although being referred to several modules or list for acting the equipment executed in the above detailed description
Member, but this division is not enforceable.In fact, according to embodiment of the present disclosure, it is above-described two or more
Module or the feature and function of unit can embody in a module or unit.Conversely, an above-described mould
The feature and function of block or unit can be to be embodied by multiple modules or unit with further division.
In an exemplary embodiment of the disclosure, a kind of electronic equipment that can be realized the above method is additionally provided.
Person of ordinary skill in the field it is understood that various aspects of the invention can be implemented as system, method or
Program product.Therefore, various aspects of the invention can be embodied in the following forms, i.e.,：It is complete hardware embodiment, complete
The embodiment combined in terms of full Software Implementation (including firmware, microcode etc.) or hardware and software, can unite here
Referred to as circuit, " module " or " system ".
The electronic equipment 800 of this embodiment according to the present invention is described referring to Fig. 8.The electronics that Fig. 8 is shown
Equipment 800 is only an example, should not function to the embodiment of the present invention and use scope bring any restrictions.
As shown in figure 8, electronic equipment 800 is showed in the form of universal computing device.The component of electronic equipment 800 can wrap
It includes but is not limited to：At least one above-mentioned processing unit 810, at least one above-mentioned storage unit 820, the different system components of connection
The bus 830 of (including storage unit 820 and processing unit 810).
Wherein, the storage unit is stored with program code, and said program code can be held by the processing unit 810
Row, so that various according to the present invention described in the execution of the processing unit 810 above-mentioned " illustrative methods " part of this specification
The step of illustrative embodiments.For example, the processing unit 810 can execute step S1 as shown in fig. 1：Monitoring system
Operation data and hardware operation data；Step S2：System data capacity is determined according to the system operation data；Step S3：It obtains
Take the capacity relevance parameter of the system operation data Yu the hardware operation data；Step S4：It is related according to the capacity
Property parameter determination system physical capacity.
Storage unit 820 may include the readable medium of volatile memory cell form, such as Random Access Storage Unit
(RAM) 8201 and/or cache memory unit 8202, it can further include read-only memory unit (ROM) 8203.
Storage unit 820 can also include program/utility with one group of (at least one) program module 8205
8204, such program module 8205 includes but is not limited to：Operating system, one or more application program, other program moulds
It may include the realization of network environment in block and program data, each of these examples or certain combination.
Bus 830 can be to indicate one of a few class bus structures or a variety of, including storage unit bus or storage
Cell controller, peripheral bus, graphics acceleration port, processing unit use any bus structures in a variety of bus structures
Local bus.
Electronic equipment 800 can also be with one or more external equipments 600 (such as keyboard, sensing equipment, bluetooth equipment
Deng) communication, can also be enabled a user to one or more equipment interact with the electronic equipment 800 communicate, and/or with make
Any equipment (such as the router, modulation /demodulation that the electronic equipment 800 can be communicated with one or more of the other calculating equipment
Device etc.) communication.This communication can be carried out by input/output (I/O) interface 850.Also, electronic equipment 800 can be with
By network adapter 860 and one or more network (such as local area network (LAN), wide area network (WAN) and/or public network,
Such as internet) communication.As shown, network adapter 860 is communicated by bus 830 with other modules of electronic equipment 800.
It should be understood that although not shown in the drawings, other hardware and/or software module can not used in conjunction with electronic equipment 800, including but not
It is limited to：Microcode, device driver, redundant processing unit, external disk drive array, RAID system, tape drive and
Data backup storage system etc..
Through the above description of the embodiments, those skilled in the art is it can be readily appreciated that example described herein is implemented
Mode can also be realized by software realization in such a way that software is in conjunction with necessary hardware.Therefore, according to the disclosure
The technical solution of embodiment can be embodied in the form of software products, which can store non-volatile at one
Property storage medium (can be CD-ROM, USB flash disk, mobile hard disk etc.) in or network on, including some instructions are so that a calculating
Equipment (can be personal computer, server, terminal installation or network equipment etc.) is executed according to disclosure embodiment
Method.
In an exemplary embodiment of the disclosure, a kind of computer readable storage medium is additionally provided, energy is stored thereon with
Enough realize the program product of this specification above method.In some possible embodiments, various aspects of the invention may be used also
In the form of being embodied as a kind of program product comprising program code, when described program product is run on the terminal device, institute
Program code is stated for executing the terminal device described in above-mentioned " illustrative methods " part of this specification according to this hair
The step of bright various illustrative embodiments.
Refering to what is shown in Fig. 9, describing the program product for realizing the above method of embodiment according to the present invention
900, can using portable compact disc read only memory (CD-ROM) and including program code, and can in terminal device,
Such as it is run on PC.However, program product of the invention is without being limited thereto, in this document, readable storage medium storing program for executing can be with
To be any include or the tangible medium of storage program, the program can be commanded execution system, device or device use or
It is in connection.
Described program product can be using any combination of one or more readable mediums.Readable medium can be readable letter
Number medium or readable storage medium storing program for executing.Readable storage medium storing program for executing for example can be but be not limited to electricity, magnetic, optical, electromagnetic, infrared ray or
System, device or the device of semiconductor, or any above combination.The more specific example of readable storage medium storing program for executing is (non exhaustive
List) include：It is electrical connection, portable disc, hard disk, random access memory (RAM) with one or more conducting wires, read-only
Memory (ROM), erasable programmable read only memory (EPROM or flash memory), optical fiber, portable compact disc read only memory
(CD-ROM), light storage device, magnetic memory device or above-mentioned any appropriate combination.
Computer-readable signal media may include in a base band or as carrier wave a part propagate data-signal,
In carry readable program code.The data-signal of this propagation can take various forms, including but not limited to electromagnetic signal,
Optical signal or above-mentioned any appropriate combination.Readable signal medium can also be any readable Jie other than readable storage medium storing program for executing
Matter, the readable medium can send, propagate or transmit for by instruction execution system, device or device use or and its
The program of combined use.
The program code for including on readable medium can transmit with any suitable medium, including but not limited to wirelessly, have
Line, optical cable, RF etc. or above-mentioned any appropriate combination.
The program for executing operation of the present invention can be write with any combination of one or more programming languages
Code, described program design language include object oriented program language-Java, C++ etc., further include conventional
Procedural programming language-such as " C " language or similar programming language.Program code can be fully in user
It calculates and executes in equipment, partly executes on a user device, being executed as an independent software package, partially in user's calculating
Upper side point is executed on a remote computing or is executed in remote computing device or server completely.It is being related to far
Journey calculates in the situation of equipment, and remote computing device can pass through the network of any kind, including local area network (LAN) or wide area network
(WAN), it is connected to user calculating equipment, or, it may be connected to external computing device (such as utilize ISP
To be connected by internet).
In addition, above-mentioned attached drawing is only the schematic theory of processing included by method according to an exemplary embodiment of the present invention
It is bright, rather than limit purpose.It can be readily appreciated that the time that above-mentioned processing shown in the drawings did not indicated or limited these processing is suitable
Sequence.In addition, be also easy to understand, these processing, which can be, for example either synchronously or asynchronously to be executed in multiple modules.
Those skilled in the art after considering the specification and implementing the invention disclosed here, will readily occur to its of the disclosure
Its embodiment.This application is intended to cover any variations, uses, or adaptations of the disclosure, these modifications, purposes or
Person's adaptive change follows the general principles of this disclosure and including the undocumented common knowledge in the art of the disclosure
Or conventional techniques.The description and examples are only to be considered as illustrative, and the true scope of the disclosure and design are wanted by right
It asks and points out.
Claims (10)
1. a kind of power system capacity appraisal procedure, which is characterized in that including：
Supervisory control system running data and hardware operation data；
System data capacity is determined according to the system operation data；
Obtain the capacity relevance parameter of the system operation data Yu the hardware operation data；
System physical capacity is determined according to the capacity relevance parameter；
Power system capacity is determined according to the system data capacity and the system physical capacity.
2. the system as claimed in claim 1 capacity evaluating method, which is characterized in that described true according to the system operation data
Determining system data capacity includes：
System operational parameters are determined according to the system operation data；
The corresponding multiple data processing bottleneck values of a running unit are determined according to the system operational parameters, by the multiple number
Cell capability according to the minimum value in processing bottleneck value as the running unit；
System resource occupation proportion is determined according to the system operation data of running units multiple in system and cell capability；
The system data capacity is determined according to the system operation data and the system resource occupation proportion.
3. the system as claimed in claim 1 capacity evaluating method, which is characterized in that described true according to the system operational parameters
Determining the corresponding multiple data processing bottleneck values of a running unit includes：
The task execution parameter for corresponding to multiple tasks type is obtained according to the system operational parameters；
The most execution numbers per second for corresponding to each task type are determined according to the task execution parameter.
4. the system as claimed in claim 1 capacity evaluating method, which is characterized in that described according to running units multiple in system
System operation data determine that system resource occupation proportion includes with cell capability：
The of each running unit is determined with corresponding cell capability according to the current operating value of the multiple running unit
One resource occupation ratio；
The sum of first resource occupation proportion by the multiple running unit is used as the system resource occupation proportion.
5. the system as claimed in claim 1 capacity evaluating method, which is characterized in that it is described obtain the system operation data with
The capacity relevance parameter of the hardware operation data includes：
The system operation data and the hardware operation data are fitted according to a variety of approximating methods multiple quasi- to obtain
Close result；
According to the corresponding approximating method of fitting parameter maximum value in multiple fitting results determine the system operation data with it is described
The incidence relation of hardware operation data, and capacity relevance parameter is set by the corresponding parameter of the approximating method.
6. power system capacity appraisal procedure as claimed in claim 5, which is characterized in that described according to the capacity relevance parameter
Determine that system physical capacity includes：
Multiple physics bottleneck values are determined according to the system operation data and the capacity relevance parameter；
The system physical capacity is set by the minimum value in the multiple physics bottleneck value.
7. the system as claimed in claim 1 capacity evaluating method, which is characterized in that it is described according to the system data capacity with
The system physical capacity determines that power system capacity includes：
Using the small value among the system data capacity and the system physical capacity as power system capacity.
8. a kind of power system capacity assesses device, which is characterized in that including：
Data monitoring module is set as supervisory control system running data and hardware operation data；
Software capacity evaluation module is set as determining system data capacity according to the system operation data；
Relevance evaluation module is set as obtaining the system operation data and the capacity correlation of the hardware operation data is joined
Number；
Hardware capabilities evaluation module is set as determining system physical capacity according to the capacity relevance parameter；
Comprehensive assessment module is set as determining power system capacity according to the system data capacity and the system physical capacity.
9. a kind of electronic equipment, which is characterized in that including：
Memory；And
The processor of memory belonging to being coupled to, the processor is configured to the instruction based on storage in the memory,
Execute such as the described in any item power system capacity appraisal procedures of claim 1-7.
10. a kind of computer readable storage medium, is stored thereon with program, realized when which is executed by processor as right is wanted
Seek the described in any item power system capacity appraisal procedures of 1-7.
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| CN112365003A (en) * | 2020-11-16 | 2021-02-12 | 浙江百应科技有限公司 | Method for adjusting NLP model capacity based on big data |
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| CN108897673B (en) | 2022-04-12 |
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