CN106469107A - A kind of capacity prediction methods of storage resource and device - Google Patents
A kind of capacity prediction methods of storage resource and device Download PDFInfo
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- CN106469107A CN106469107A CN201610791106.7A CN201610791106A CN106469107A CN 106469107 A CN106469107 A CN 106469107A CN 201610791106 A CN201610791106 A CN 201610791106A CN 106469107 A CN106469107 A CN 106469107A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3051—Monitoring arrangements for monitoring the configuration of the computing system or of the computing system component, e.g. monitoring the presence of processing resources, peripherals, I/O links, software programs
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- 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
- G06F11/3409—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 for performance assessment
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- 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
- G06F11/3452—Performance evaluation by statistical analysis
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Abstract
The invention discloses a kind of capacity prediction methods of storage resource and device, the method includes：Obtain the historical capacity data of storage resource, and it is interval that historical capacity data is divided into multiple continuous historical datas according to prefixed time interval；Calculated based on the interval historical capacity data of multiple historical datas, obtained the capacity anticipation function of storage resource；Capacity highest threshold value is substituted into capacity anticipation function, is calculated the time corresponding with capacity highest threshold value, and determine the capacity pot life for storage resource for the time before this time.Thus, staff is enable to realize the prediction of the capacity pot life to storage resource according to technique scheme, just to take corresponding maintenance work when storage resource does not break down, largely avoid the corresponding maintenance work that carries out again after storage resource fault occurring in background technology affects the normal situation generation running of business.
Description
Technical field
A kind of the present invention relates to operation management technical field, more particularly, it relates to capacity prediction methods of storage resource
And device.
Background technology
With science and technology and the developing rapidly of information technology, the application of high performance computer system is also more and more wider
General, the maintenance that it is run also develops into supermatic O＆M mode from manual detection, wherein, in computer system
The capacity monitor of storage resource is one of Maintenance Significant Items.
For the capacity monitor of storage resource in computer system, typically by the real-time capacity number providing storage resource
According to facilitating operation maintenance personnel to carry out corresponding maintenance work according to current state to storage resource；But, large-scale machine room institute at this stage
The business carrying is all high real-time and high concurrent business, and carrying out maintenance again when storage resource breaks down will certainly shadow
Ring the normal operation of original business.
In sum, prior art is used for the scheme presence meeting storage resource in computer system being monitored safeguard
Because storage resource fault affects the normal problem run of business.
Content of the invention
It is an object of the invention to provide a kind of capacity prediction methods of storage resource and device, it is used for solving prior art
The meeting that the scheme that storage resource in computer system is monitored with safeguard exists is normal because of storage resource fault impact business
The problem run.
To achieve these goals, the present invention provides following technical scheme：
A kind of capacity prediction methods of storage resource, including：
Obtain the historical capacity data of storage resource, and described historical capacity data is divided into according to prefixed time interval many
Individual continuous historical data is interval；
Calculated based on the interval historical capacity data of multiple described historical datas, obtained the capacity of described storage resource
Anticipation function；
Capacity highest threshold value is substituted into described capacity anticipation function, when being calculated corresponding with described capacity highest threshold value
Between, and the time before determining this time be the capacity pot life of described storage resource.
Preferably, after obtaining the historical capacity data of described storage resource, also include：
The historical capacity data being less than capacity lowest threshold in described historical capacity data is removed.
Preferably, calculated based on the interval historical capacity data of multiple described historical datas, obtained described storage money
The capacity anticipation function in source, including：
Calculate the average of all historical capacity data in each described historical data interval, obtain and each historical data area
Between corresponding capacity actual value A1To An, and it is based on A1To AnCalculate corresponding B according to the following formula1To Bn：
Bn=α An-1+(1-α)Bn-1
Wherein, α is default weight coefficient；
Based on B1To BnCalculate corresponding C according to the following formula1To Cn:
Cn=α Bn+(1-α)Bn-1
Based on BnAnd CnObtain following capacity anticipation function：
Wherein, y represents moment t corresponding resource capacity value.
Preferably, also include：
Described capacity pot life is shown.
Preferably, also include：
If described capacity pot life is more than multiple described historical datas interval corresponding time and display resource is filled
Foot, if described capacity pot life is less than described prefixed time interval, display resource is nervous.
A kind of capacity prediction meanss of storage resource, including：
Acquisition module, for obtaining the historical capacity data of storage resource, and by described historical capacity data according to default
It is interval that time interval is divided into multiple continuous historical datas；
Computing module, is calculated for the historical capacity data interval based on multiple described historical datas, obtains described
The capacity anticipation function of storage resource；
Prediction module, for capacity highest threshold value is substituted into described capacity anticipation function, is calculated with described capacity
The high threshold corresponding time, and the time before determining this time be the capacity pot life of described storage resource.
Preferably, described acquisition module also includes：
Removal unit, for removing the historical capacity data being less than capacity lowest threshold in described historical capacity data.
Preferably, described computing module includes：
Computing unit, is used for：Calculate the average of all historical capacity data in multiple described historical datas intervals, obtain with
The interval corresponding capacity actual value A of each historical data1To An, and it is based on A1To AnCalculate corresponding B according to the following formula1Extremely
Bn：
Bn=α An-1+(1-α)Bn-1
Wherein, α is default weight coefficient；
Based on B1To BnCalculate corresponding C according to the following formula1To Cn:
Cn=α Bn+(1-α)Bn-1
Based on BnAnd CnObtain following capacity anticipation function：
Wherein, y represents moment t corresponding resource capacity value.
Preferably, also include：
Display module, for showing to described capacity pot life.
Preferably, described display module also includes：
Display unit, is used for：If described capacity pot life is more than multiple described historical datas interval corresponding time
With then show that resource is sufficient, if described capacity pot life is less than described prefixed time interval, display resource is nervous.
The invention provides a kind of capacity prediction methods of storage resource and device, the method includes：Obtain storage resource
Historical capacity data, and described historical capacity data is divided into multiple continuous historical data areas according to prefixed time interval
Between；Calculated based on the interval historical capacity data of multiple described historical datas, obtained the capacity prediction of described storage resource
Function；Capacity highest threshold value is substituted into described capacity anticipation function, is calculated the time corresponding with described capacity highest threshold value,
And the time before determining this time is the capacity pot life of described storage resource.Above-mentioned technical characteristic disclosed in the present application,
By the process of the historical capacity data to storage resource and be calculated and can predict that the capacity of future capacity occupancy situation is pre-
Survey function, and then reached based on the occupancy resource that this capacity anticipation function calculates storage resource corresponding during capacity highest threshold value
Time, capacity pot life is with the time before determining this time；So that staff can be according to above-mentioned skill
Art scheme realizes the prediction of the capacity pot life to storage resource, corresponding just to take when storage resource does not break down
Maintenance work, largely avoid in background technology occur safeguarded accordingly again after storage resource fault
The normal situation about running of work influence business occurs.
Brief description
In order to be illustrated more clearly that the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
Have technology description in required use accompanying drawing be briefly described it should be apparent that, drawings in the following description be only this
Inventive embodiment, for those of ordinary skill in the art, on the premise of not paying creative work, can also basis
The accompanying drawing providing obtains other accompanying drawings.
Fig. 1 is a kind of flow chart of the capacity prediction methods of storage resource provided in an embodiment of the present invention；
Fig. 2 be a kind of storage resource provided in an embodiment of the present invention capacity prediction methods in implement the prediction of scene
Schematic diagram；
Fig. 3 is a kind of structural representation of the capacity prediction meanss of storage resource provided in an embodiment of the present invention.
Specific embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Site preparation description is it is clear that described embodiment is only a part of embodiment of the present invention, rather than whole embodiments.It is based on
Embodiment in the present invention, it is every other that those of ordinary skill in the art are obtained under the premise of not making creative work
Embodiment, broadly falls into the scope of protection of the invention.
Refer to Fig. 1, it illustrates a kind of flow process of the capacity prediction methods of storage resource provided in an embodiment of the present invention
Figure, may comprise steps of：
S11：Obtain the historical capacity data of storage resource, and historical capacity data is divided into according to prefixed time interval many
Individual continuous historical data is interval.
Wherein, the historical capacity data of storage resource is the occupied capacity feelings of storage resource before current time
Condition, i.e. the capacity occupancy data of storage resource, specifically, this data can be choice of dynamical, change when the time
When, the historical capacity data of selection is always the nearest historical capacity data of front distance current time of current time, thus protecting
Effectiveness that the data that card is chosen predict for capacity and representative naturally it is also possible to carry out other settings according to actual needs equal
Within protection scope of the present invention.
Prefixed time interval can be set according to actual needs, such as several days or a few houres etc., by historical capacity number
It is divided into multiple continuous historical datas intervals according to according to prefixed time interval, specifically, be that historical capacity data is corresponding
Time is divided into multiple prefixed time interval, and the capacity of each prefixed time interval and within a preset time interval storage resource takies
It is interval that data is corresponding historical data.
S12：Calculated based on the interval historical capacity data of multiple historical datas, obtained the capacity prediction of storage resource
Function.
Calculated based on the interval historical capacity data of historical data, be specifically as follows using exponential smoothing algorithm foundation
The interval historical capacity data of historical data obtains corresponding capacity anticipation function, is become with taking to following a period of time inner capacitiess
Change trend is fitted；Input following any time using this function, this time corresponding capacity can be obtained and take data, when
So data can also be taken using the arbitrary capacity of this function input, this capacity can be obtained and take the data corresponding time, thus
Realize the prediction of the capacity occupancy situation following to storage resource.
S13：Capacity highest threshold value is substituted into capacity anticipation function, is calculated the time corresponding with capacity highest threshold value,
And determine the capacity pot life for storage resource for the time before this time.
Wherein capacity highest threshold value can be set according to actual needs, such as 90 percent of storage resource etc., when
When the occupancy capacity of storage resource reaches capacity highest threshold value, if again to input information in this storage resource, may result in
Too high final its readwrite performance that reduces of capacity of storage resource even results in inefficacy it is therefore desirable to control the occupancy of storage resource to hold
Amount is under capacity highest threshold value.Capacity highest threshold value is substituted into capacity anticipation function, the occupancy that can obtain storage resource is held
Corresponding time when amount reaches capacity highest threshold value, and the time after current time before this time is storage resource
Capacity pot life.
Above-mentioned technical characteristic disclosed in the present application, by the process of the historical capacity data to storage resource and be calculated
The capacity anticipation function of future capacity occupancy situation can be predicted, and then storage resource is calculated based on this capacity anticipation function
Take resource corresponding time when reaching capacity highest threshold value, when capacity being with the time before determining this time can use
Between；So that staff can realize the prediction of the capacity pot life to storage resource according to technique scheme, with
Just take corresponding maintenance work when storage resource does not break down, largely avoid appearance in background technology
Carrying out corresponding maintenance work after storage resource fault again affects the normal situation generation running of business.
In addition, the above-mentioned storage resource disclosed in the embodiment of the present invention can be any storage resource, including server magnetic
Disk capacity, database table space etc., have certain versatility；And by O＆M people is decreased to the maintenance in advance of storage resource
The pressure of member, improves the stability of its correspondence system.
A kind of capacity prediction methods of storage resource provided in an embodiment of the present invention, obtain the historical capacity number of storage resource
According to afterwards, can also include：
The historical capacity data being less than capacity lowest threshold in historical capacity data is removed.
Wherein capacity lowest threshold can be determined according to actual needs, generally arranges smaller；Work as historical capacity
Data be less than capacity lowest threshold when be likely due to for this moment historical capacity data be not implemented effectively monitor into
And obtain effective data, therefore by this historical capacity data duplicate removal, the utilized history of capacity anticipation function can be calculated and hold
The effectiveness of amount data is it is ensured that the accuracy of capacity anticipation function.
A kind of capacity prediction methods of storage resource provided in an embodiment of the present invention, based on interval the going through of multiple historical datas
History capacity data is calculated, and obtains the capacity anticipation function of storage resource, can include：
Calculate the average of all historical capacity data in each historical data interval, it is right with each historical data interval to obtain
The capacity actual value A answering1To An, and it is based on A1To AnCalculate corresponding B according to the following formula1To Bn：
Bn=α An-1+(1-α)Bn-1
Wherein, α is default weight coefficient；
Based on B1To BnCalculate corresponding C according to the following formula1To Cn:
Cn=α Bn+(1-α)Bn-1
Based on BnAnd CnObtain following capacity anticipation function：
Wherein, y represents moment t corresponding resource capacity value.
Wherein default weight coefficient can be determined, when can adjust the distance current by the way according to actual needs
Carve nearer historical capacity data and give larger weight, and current time historical capacity data imparting farther out of adjusting the distance is less
Weight, thus realize for following storage resource capacity occupancy situation Accurate Prediction.
A kind of capacity prediction methods of storage resource provided in an embodiment of the present invention, can also include：
Capacity pot life is shown.
By showing to capacity pot life, enable to the capacity that staff can know storage resource in time
Prediction case, and then make corresponding maintenance work.
A kind of capacity prediction methods of storage resource provided in an embodiment of the present invention, can also include：
If capacity pot life be more than the multiple historical datas interval corresponding time and, display resource is sufficient, if
Capacity pot life is less than prefixed time interval, then show that resource is nervous.
Realize the output of above- mentioned information by automatic decision, independently judged without staff, but can choose
Directly take corresponding maintenance work when resource is nervous, and temporarily do not process when resource is sufficient, thereby ensure that storage
The normal operation of resource.
With reference to implementing scene to above-mentioned technology provided in an embodiment of the present invention taking server disk capacity as a example
Scheme is described in detail, when the business of server process tends to be steady normalization, journal file and database file
Growth linearly increases, as shown in Figure 2；This month server disk size is recorded, and is obtained by technique scheme
To a data growth curve (i.e. the linear fit of in figure) corresponding with capacity anticipation function, following disk can be held whereby
Amount is calculated, and such as can predict that September server disk capacity on the 29th is up to 550G etc..
The embodiment of the present invention additionally provides a kind of capacity prediction meanss of storage resource, as shown in figure 3, including：
Acquisition module 11, for obtaining the historical capacity data of storage resource, and by historical capacity data according to default when
Between to be divided into multiple continuous historical datas interval at interval；
Computing module 12, is calculated for the historical capacity data interval based on multiple historical datas, obtains storage money
The capacity anticipation function in source；
Prediction module 13, for capacity highest threshold value is substituted into capacity anticipation function, is calculated and capacity highest threshold value
The corresponding time, and determine the capacity pot life for storage resource for the time before this time.
A kind of capacity prediction meanss of storage resource provided in an embodiment of the present invention, acquisition module can also include：
Removal unit, for removing the historical capacity data being less than capacity lowest threshold in historical capacity data.
A kind of capacity prediction meanss of storage resource provided in an embodiment of the present invention, computing module can include：
Computing unit, is used for：Calculate the average of all historical capacity data in multiple historical data intervals, obtain and each
The interval corresponding capacity actual value A of historical data1To An, and it is based on A1To AnCalculate corresponding B according to the following formula1To Bn：
Bn=α An-1+(1-α)Bn-1
Wherein, α is default weight coefficient；
Based on B1To BnCalculate corresponding C according to the following formula1To Cn:
Cn=α Bn+(1-α)Bn-1
Based on BnAnd CnObtain following capacity anticipation function：
Wherein, y represents moment t corresponding resource capacity value.
A kind of capacity prediction meanss of storage resource provided in an embodiment of the present invention, can also include：
Display module, for showing to capacity pot life.
A kind of capacity prediction meanss of storage resource provided in an embodiment of the present invention, display module can also include：
Display unit, is used for：If capacity pot life is more than multiple historical datas interval corresponding time and shows
Resource is sufficient, if capacity pot life is less than prefixed time interval, display resource is nervous.
In a kind of capacity prediction meanss of storage resource provided in an embodiment of the present invention, the explanation of relevant portion refers to this
In the capacity prediction methods of a kind of storage resource that inventive embodiments provide, the detailed description of corresponding part, will not be described here.
Described above to the disclosed embodiments, makes those skilled in the art be capable of or uses the present invention.To this
Multiple modifications of a little embodiments will be apparent from for a person skilled in the art, and generic principles defined herein can
Without departing from the spirit or scope of the present invention, to realize in other embodiments.Therefore, the present invention will not be limited
It is formed on the embodiments shown herein, and be to fit to consistent with principles disclosed herein and features of novelty the widest
Scope.
Claims (10)
1. a kind of capacity prediction methods of storage resource are it is characterised in that include：
Obtain the historical capacity data of storage resource, and described historical capacity data is divided into multiple companies according to prefixed time interval
Continuous historical data is interval；
Calculated based on the interval historical capacity data of multiple described historical datas, obtained the capacity prediction of described storage resource
Function；
Capacity highest threshold value is substituted into described capacity anticipation function, is calculated the time corresponding with described capacity highest threshold value,
And the time before determining this time is the capacity pot life of described storage resource.
2. method according to claim 1 it is characterised in that obtain described storage resource historical capacity data after,
Also include：
The historical capacity data being less than capacity lowest threshold in described historical capacity data is removed.
3. method according to claim 1 is it is characterised in that based on the interval historical capacity number of multiple described historical datas
According to being calculated, obtain the capacity anticipation function of described storage resource, including：
Calculate the average of all historical capacity data in each described historical data interval, it is right with each historical data interval to obtain
The capacity actual value A answering1To An, and it is based on A1To AnCalculate corresponding B according to the following formula1To Bn：
Bn=α An-1+(1-α)Bn-1
Wherein, α is default weight coefficient；
Based on B1To BnCalculate corresponding C according to the following formula1To Cn:
Cn=α Bn+(1-α)Bn-1
Based on BnAnd CnObtain following capacity anticipation function：
Wherein, y represents moment t corresponding resource capacity value.
4. method according to claim 3 is it is characterised in that also include：
Described capacity pot life is shown.
5. method according to claim 4 is it is characterised in that also include：
If described capacity pot life be more than multiple described historical datas interval corresponding time and, display resource is sufficient,
If described capacity pot life is less than described prefixed time interval, display resource is nervous.
6. a kind of capacity prediction meanss of storage resource are it is characterised in that include：
Acquisition module, for obtaining the historical capacity data of storage resource, and by described historical capacity data according to Preset Time
It is interval that interval is divided into multiple continuous historical datas；
Computing module, is calculated for the historical capacity data interval based on multiple described historical datas, is obtained described storage
The capacity anticipation function of resource；
Prediction module, for capacity highest threshold value is substituted into described capacity anticipation function, is calculated and described capacity highest threshold
It is worth the corresponding time, and the time before determining this time is the capacity pot life of described storage resource.
7. device according to claim 6 is it is characterised in that described acquisition module also includes：
Removal unit, for removing the historical capacity data being less than capacity lowest threshold in described historical capacity data.
8. device according to claim 6 is it is characterised in that described computing module includes：
Computing unit, is used for：Calculate the average of all historical capacity data in multiple described historical data intervals, obtain and each
The interval corresponding capacity actual value A of historical data1To An, and it is based on A1To AnCalculate corresponding B according to the following formula1To Bn：
Bn=α An-1+(1-α)Bn-1
Wherein, α is default weight coefficient；
Based on B1To BnCalculate corresponding C according to the following formula1To Cn:
Cn=α Bn+(1-α)Bn-1
Based on BnAnd CnObtain following capacity anticipation function：
Wherein, y represents moment t corresponding resource capacity value.
9. device according to claim 8 is it is characterised in that also include：
Display module, for showing to described capacity pot life.
10. device according to claim 9 is it is characterised in that described display module also includes：
Display unit, is used for：If described capacity pot life be more than multiple described historical datas interval corresponding time and,
Display resource is sufficient, if described capacity pot life is less than described prefixed time interval, display resource is nervous.
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