CN116578466A - Method, device, equipment and medium for calculating storage performance index data reference value - Google Patents
Method, device, equipment and medium for calculating storage performance index data reference value Download PDFInfo
- Publication number
- CN116578466A CN116578466A CN202310589617.0A CN202310589617A CN116578466A CN 116578466 A CN116578466 A CN 116578466A CN 202310589617 A CN202310589617 A CN 202310589617A CN 116578466 A CN116578466 A CN 116578466A
- Authority
- CN
- China
- Prior art keywords
- data
- performance index
- sampling
- moment
- calculating
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 41
- 238000005070 sampling Methods 0.000 claims abstract description 92
- 230000000737 periodic effect Effects 0.000 claims abstract description 58
- 238000004590 computer program Methods 0.000 claims description 11
- 238000004364 calculation method Methods 0.000 claims description 10
- 230000004044 response Effects 0.000 claims description 9
- 238000012360 testing method Methods 0.000 abstract description 16
- 238000002474 experimental method Methods 0.000 abstract description 15
- 238000010586 diagram Methods 0.000 description 9
- 230000006870 function Effects 0.000 description 6
- 230000002159 abnormal effect Effects 0.000 description 5
- 230000003287 optical effect Effects 0.000 description 4
- 238000013461 design Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 239000000835 fiber Substances 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000007430 reference method Methods 0.000 description 1
- 238000000638 solvent extraction Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Classifications
-
- 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
-
- 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
- G06F11/3466—Performance evaluation by tracing or monitoring
- G06F11/3476—Data logging
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Computer Hardware Design (AREA)
- General Physics & Mathematics (AREA)
- Quality & Reliability (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Probability & Statistics with Applications (AREA)
- Evolutionary Biology (AREA)
- Bioinformatics & Computational Biology (AREA)
- Life Sciences & Earth Sciences (AREA)
- Debugging And Monitoring (AREA)
Abstract
The invention provides a method, a device, equipment and a readable medium for calculating a reference value of storage performance index data, wherein the method comprises the following steps: acquiring historical data for storing performance index data, and dividing the historical data into a plurality of periodic units in a time unit; sampling historical data in each periodic unit point by point in a sliding window mode to obtain sampling data of each periodic unit at each moment; calculating a sample mean value and a standard deviation of the sampling data at each moment; and calculating a reference value of the stored performance index data at each moment according to a preset formula. By using the scheme of the invention, a large number of experiments or tests can be prevented from being carried out in advance to obtain the threshold value, the requirement on specific environments can be reduced, and when any environment such as software, hardware, configuration and the like is changed, the experiment test can be omitted, so that the consumption of manpower, financial resources and time is greatly reduced.
Description
Technical Field
The present invention relates to the field of computers, and more particularly, to a method, apparatus, device, and readable medium for calculating a reference value of stored performance index data.
Background
The storage performance index data is an important index for measuring the storage performance, and in order to judge whether the performance index data is normal or not in a certain time period, the following modes are adopted: the first is through manual experience judgment, but this approach requires high technical, empirical capability and energy of the operation and maintenance personnel, and is not suitable for application in automatic identification of the system. The second is to set a threshold value, the mode requires a user to conduct a large amount of experiments or tests in advance, the user can obtain threshold value data, the experiment test needs to consume certain manpower, financial resources and time, and certain requirements are met on the professional technical ability of testers, the threshold value data detected through the experiment or test is only effective on specific environments, when any environment such as software, hardware or configuration changes, the experiment test needs to be conducted again, and the re-experiment and test means that the manpower, financial resources and time need to be repeatedly input.
Disclosure of Invention
In view of the above, an object of the embodiments of the present invention is to provide a method, apparatus, device and readable medium for calculating a reference value of stored performance index data, by using the technical solution of the present invention, a large number of experiments or tests can be prevented from being performed in advance to obtain a threshold value, requirements for a specific environment can be reduced, and when any environment such as software, hardware or configuration changes, the experiment test can be omitted, thereby greatly reducing the consumption of manpower, financial resources and time.
In view of the above, an aspect of an embodiment of the present invention provides a method of calculating a reference value of stored performance index data, including the steps of:
acquiring historical data for storing performance index data, and dividing the historical data into a plurality of periodic units in a time unit;
sampling historical data in each periodic unit point by point in a sliding window mode to obtain sampling data of each periodic unit at each moment;
calculating a sample mean value and a standard deviation of the sampling data at each moment;
and calculating a reference value of the stored performance index data at each moment according to a preset formula.
According to one embodiment of the invention, the stored performance index data includes IOPS, latency, and bandwidth.
According to one embodiment of the present invention, acquiring history data storing performance index data and dividing the history data into a plurality of periodic units in time units includes:
acquiring historical data in a preset time period in the storage performance index data;
the history data is divided into a plurality of periodic units in units of days.
According to one embodiment of the present invention, sampling historical data in each periodic unit point by point in a sliding window manner to obtain sampling data of each periodic unit at each moment includes:
setting one historical data per minute as a sampling point at one moment;
setting a range of sampling data at each moment;
and calculating the maximum value or the minimum value in the sampling data range corresponding to the sampling data at each moment in each period unit, and taking the maximum value or the minimum value as the sampling data at each moment.
According to one embodiment of the present invention, calculating the sample mean and standard deviation of the sampled data at each instant in time includes:
and calculating the sample mean value and standard deviation of the sampling data at the same time in all the periodic units.
According to one embodiment of the present invention, calculating the reference value of the stored performance index data for each time according to the preset formula includes:
in response to using the maximum value as the sampling data for each time instant, the formula referencevalue=μ is used 3 +k*σ 3 Calculating a reference value of the stored performance index data at each moment, wherein reference value is the reference value of the stored performance index data, mu 3 For sampling the sample mean value, sigma of the data at one moment 3 The standard deviation of the data is sampled for one instant, where k e {1,2,3}.
According to one embodiment of the present invention, calculating the reference value of the stored performance index data for each time according to the preset formula includes:
in response to using the minimum value as the sampling data for each time instant, the formula referencevalue=μ is used 3 -k*σ 3 Calculating a reference value of the stored performance index data at each moment, wherein reference value is the reference value of the stored performance index data, mu 3 For sampling the sample mean value, sigma of the data at one moment 3 The standard deviation of the data is sampled for one instant, where k e {1,2,3}.
In another aspect of the embodiment of the present invention, there is also provided an apparatus for calculating a reference value of stored performance index data, the apparatus including:
the dividing module is configured to acquire historical data for storing performance index data and divide the historical data into a plurality of periodic units in time units;
the sampling module is configured to sample historical data in each periodic unit point by point in a sliding window mode so as to obtain sampling data of each periodic unit at each moment;
the first calculating module is configured to calculate a sample mean value and a standard deviation of the sampling data at each moment;
and the second calculation module is configured to calculate a reference value of the stored performance index data at each moment according to a preset formula.
In another aspect of the embodiments of the present invention, there is also provided a computer apparatus including:
at least one processor; and
and a memory storing computer instructions executable on the processor, the instructions when executed by the processor performing the steps of any of the methods described above.
In another aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium storing a computer program which, when executed by a processor, implements the steps of any of the methods described above.
The invention has the following beneficial technical effects: according to the method for calculating the reference value of the storage performance index data, the historical data of the storage performance index data are obtained, and the historical data are divided into a plurality of periodic units in a time unit; sampling historical data in each periodic unit point by point in a sliding window mode to obtain sampling data of each periodic unit at each moment; calculating a sample mean value and a standard deviation of the sampling data at each moment; according to the technical scheme of calculating the reference value of the stored performance index data at each moment according to the preset formula, a large number of experiments or tests can be prevented from being carried out in advance to obtain the threshold value, the requirement on a specific environment can be reduced, and when any environment such as software, hardware or configuration is changed, the experiment test can be omitted, so that the consumption of manpower, financial resources and time is greatly reduced.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are necessary for the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention and that other embodiments may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart diagram of a method of calculating a stored performance metric data reference value in accordance with one embodiment of the invention;
FIG. 2 is a schematic diagram of period partitioning according to one embodiment of the present invention;
FIG. 3 is a schematic diagram of calculating a reference value for a time instant according to one embodiment of the present invention;
FIG. 4 is a schematic diagram of calculating a reference value for each time of each cycle according to one embodiment of the invention;
FIG. 5 is a schematic diagram of an apparatus for calculating a reference value of stored performance level data according to one embodiment of the present invention;
FIG. 6 is a schematic diagram of a computer device according to one embodiment of the invention;
fig. 7 is a schematic diagram of a computer-readable storage medium according to one embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the following embodiments of the present invention will be described in further detail with reference to the accompanying drawings.
In view of the above object, a first aspect of the embodiments of the present invention proposes an embodiment of a method of calculating a reference value of stored performance index data. Fig. 1 shows a schematic flow chart of the method.
As shown in fig. 1, the method may include the steps of:
s1, acquiring historical data for storing performance index data, and dividing the historical data into a plurality of periodic units in a time unit.
S2, sampling historical data in each periodic unit point by point in a sliding window mode to obtain sampling data of each periodic unit at each moment.
S3, calculating a sample mean value and a standard deviation of the sampling data at each moment.
S4, calculating a reference value of the stored performance index data at each moment according to a preset formula.
By using the technical scheme of the invention, a large number of experiments or tests can be prevented from being carried out in advance to obtain the threshold value, the requirement on specific environments can be reduced, and when any environment such as software, hardware, configuration and the like is changed, the experiment test can be omitted, so that the consumption of manpower, financial resources and time is greatly reduced.
In a preferred embodiment of the present invention, the stored performance index data includes IOPS, latency, and bandwidth. The invention is described in terms of IOPS, and other performance index data may be calculated using the same method.
In a preferred embodiment of the present invention, acquiring the history data storing the performance index data and dividing the history data into a plurality of periodic units in time units includes:
acquiring historical data in a preset time period in the storage performance index data;
the history data is divided into a plurality of periodic units in units of days. A Period of history data is selected, and divided into a plurality of Period units, for example, a month of history data, where the Period is the Period unit of day, and the Period of history data is divided into 30 Period units of period= { Period1, period2, … Period }, where n=30.
In a preferred embodiment of the present invention, sampling the historical data in each periodic unit point by point in a sliding window manner to obtain the sampled data of each time of each periodic unit includes:
setting one historical data per minute as a sampling point at one moment;
setting a range of sampling data at each moment;
and calculating the maximum value or the minimum value in the sampling data range corresponding to the sampling data at each moment in each period unit, and taking the maximum value or the minimum value as the sampling data at each moment. Index data taken in a certain time unit exists in each period unit, for example, one index data point per minute is taken as a sampling point at each moment, and 60 minutes by 24 hours=1440 index data points exist in any index data period unit, namely, period= { a1, a2, … am }, in this example, m=1440, so that the historical data of the sampling point at each moment in each period unit is shown in fig. 2. The present embodiment describes using the maximum value as the sampling data, and the sampling data are all derived from the same-time sampling data of 30 cycle units. The sample data at any time in a certain period unit is derived from the maximum value of the sample interval centered at that time. The sample interval, i.e. the size of the time sliding window, may show different determining ranges of granularity according to the system index, in this example, five minutes are taken as an example of the sliding time window size, that is, the range of sampling data at each moment is set to be five minutes, and the maximum reference value of the third index data of the new period unit (new period) is calculated as an example (the maximum reference values of the first two index data or the last two index data may be respectively connected with the index data of the previous period unit and the index data of the later period unit, or calculated by adopting other special modes). As shown in FIG. 3, new period weeksPhase unit a 3 The time index data sampling steps are as follows: random period unit period i In a, a 3 Selecting 5-minute sample interval data windowData as center i3 ＝{a 1 ,a 2 ,a 3 ,a 4 ,a 5 And selects the interval maximum Max (windowData) i3 ) As a 3 Time index data reference value ith calculation sample sampleData i . Namely: sampleData i ＝Max({a 1 ,a 2 ,a 3 ,a 4 ,a 5 -selecting a) for all periodic units 3 Calculating a sample of the time index to obtain all periodic units a 3 Time index calculation sample set, sampledata= { sampleData = { 1 ,sampleData 2 ,…,sampleData n }. The sample set is a performance index data reference value at a3 time in each period unit, and other times can be calculated by using the same method.
In a preferred embodiment of the present invention, calculating the sample mean and standard deviation of the sampled data at each instant in time comprises:
and calculating the sample mean value and standard deviation of the sampling data at the same time in all the periodic units. All the periodic units a have been obtained in the above step 3 The time index data maximum reference value calculates a sample set sampleData, and the sample mean mu thereof can be directly calculated 3 Standard deviation sigma 3 ：
μ 3 ＝Avg(sampleData)；σ 3 ＝SampleStandardDeviation(sampleData)。
In a preferred embodiment of the present invention, calculating the reference value of the stored performance index data for each time according to the preset formula includes:
in response to using the maximum value as the sampling data for each time instant, the formula referencevalue=μ is used 3 +k*σ 3 Calculating a reference value of the stored performance index data at each moment, wherein the efference value is the reference value of the stored performance index data, mu 3 For sampling the sample mean value, sigma of the data at one moment 3 The standard deviation of the data is sampled for one instant, where k e {1,2,3}. Reference statisticsAnd (3-sigma rule) and considering that the upper limit and the lower limit of the reference value are respectively obtained by adopting different calculation sample data, the maximum or minimum reference value is calculated by adopting a half-rule-of-thumb mode, namely, the maximum reference value is calculated by adopting a +sigma mode, and the minimum reference value is calculated by adopting a-sigma mode. According to the rule of thumb abnormal data probability, half rule of thumb test abnormal data probability can be obtained through analysis, and the addition and subtraction sigma quantity can be selected according to the condition of detecting abnormal index data of different systems, so that the calculation mode of the index data reference value at the time a3 is as follows: maxrereferencevalue 3 ＝μ 3 +k*σ 3 Wherein k is {1,2,3}, a can be obtained by the above formula 3 Time index data maxReferencevalue 3 . The calculation of the reference value of all time index data of the new period unit can be referred to as a 3 The method for calculating the reference value of the time index data comprises the steps of calculating the reference value of the time index data point by point along with the downward movement of a sliding window in any time index data reference value calculating mode, and finally obtaining the maximum reference value of the time index data at each time, as shown in fig. 4.
In a preferred embodiment of the present invention, calculating the reference value of the stored performance index data for each time according to the preset formula includes:
in response to using the minimum value as the sampling data for each time instant, the formula referencevalue=μ is used 3 -k*σ 3 Calculating a reference value of the stored performance index data at each moment, wherein reference value is the reference value of the stored performance index data, mu 3 For sampling the sample mean value, sigma of the data at one moment 3 The standard deviation of the data is sampled for one instant, where k e {1,2,3}.
The invention is described using the IOPS as an example of storing performance index data, and other performance index data may be calculated in the same manner.
The method can automatically implement calculation through the system, can be used as a reference value for judging whether the performance index is abnormal, and provides a reference method for automatically detecting the abnormal performance index for the system. On the other hand, a large number of experiments or tests can be prevented from being carried out in advance to obtain the threshold value, the requirement on specific environments is reduced, and when any environment such as software, hardware, configuration and the like is changed, the experiment test is not required to be carried out again, so that the consumption of manpower, financial resources and time is greatly reduced.
It should be noted that, it will be understood by those skilled in the art that all or part of the procedures in implementing the methods of the above embodiments may be implemented by a computer program to instruct related hardware, and the above program may be stored in a computer readable storage medium, and the program may include the procedures of the embodiments of the above methods when executed. Wherein the storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), or the like. The computer program embodiments described above may achieve the same or similar effects as any of the method embodiments described above.
Furthermore, the method disclosed according to the embodiment of the present invention may also be implemented as a computer program executed by a CPU, which may be stored in a computer-readable storage medium. When executed by a CPU, performs the functions defined above in the methods disclosed in the embodiments of the present invention.
In view of the above object, a second aspect of the embodiments of the present invention provides an apparatus for calculating a reference value of stored performance index data, as shown in fig. 5, an apparatus 200 includes:
the dividing module is configured to acquire historical data for storing performance index data and divide the historical data into a plurality of periodic units in time units;
the sampling module is configured to sample historical data in each periodic unit point by point in a sliding window mode so as to obtain sampling data of each periodic unit at each moment;
the first calculating module is configured to calculate a sample mean value and a standard deviation of the sampling data at each moment;
and the second calculation module is configured to calculate a reference value of the stored performance index data at each moment according to a preset formula.
Based on the above object, a third aspect of the embodiments of the present invention proposes a computer device. FIG. 6 is a schematic diagram of an embodiment of a computer device provided by the present invention. As shown in fig. 6, an embodiment of the present invention includes the following means: at least one processor 21; and a memory 22, the memory 22 storing computer instructions 23 executable on the processor, the instructions when executed by the processor performing the method of:
acquiring historical data for storing performance index data, and dividing the historical data into a plurality of periodic units in a time unit;
sampling historical data in each periodic unit point by point in a sliding window mode to obtain sampling data of each periodic unit at each moment;
calculating a sample mean value and a standard deviation of the sampling data at each moment;
and calculating a reference value of the stored performance index data at each moment according to a preset formula.
In a preferred embodiment of the present invention, the stored performance index data includes IOPS, latency, and bandwidth.
In a preferred embodiment of the present invention, acquiring the history data storing the performance index data and dividing the history data into a plurality of periodic units in time units includes:
acquiring historical data in a preset time period in the storage performance index data;
the history data is divided into a plurality of periodic units in units of days.
In a preferred embodiment of the present invention, sampling the historical data in each periodic unit point by point in a sliding window manner to obtain the sampled data of each time of each periodic unit includes:
setting one historical data per minute as a sampling point at one moment;
setting a range of sampling data at each moment;
and calculating the maximum value or the minimum value in the sampling data range corresponding to the sampling data at each moment in each period unit, and taking the maximum value or the minimum value as the sampling data at each moment.
In a preferred embodiment of the present invention, calculating the sample mean and standard deviation of the sampled data at each instant in time comprises:
and calculating the sample mean value and standard deviation of the sampling data at the same time in all the periodic units.
In a preferred embodiment of the present invention, calculating the reference value of the stored performance index data for each time according to the preset formula includes:
in response to using the maximum value as the sampling data for each time instant, the formula referencevalue=μ is used 3 +k*σ 3 Calculating a reference value of the stored performance index data at each moment, wherein reference value is the reference value of the stored performance index data, mu 3 For sampling the sample mean value, sigma of the data at one moment 3 The standard deviation of the data is sampled for one instant, where k e {1,2,3}.
In a preferred embodiment of the present invention, calculating the reference value of the stored performance index data for each time according to the preset formula includes:
in response to using the minimum value as the sampling data for each time instant, the formula referencevalue=μ is used 3 -k*σ 3 Calculating a reference value of the stored performance index data at each moment, wherein reference value is the reference value of the stored performance index data, mu 3 For sampling the sample mean value, sigma of the data at one moment 3 The standard deviation of the data is sampled for one instant, where k e {1,2,3}.
Based on the above object, a fourth aspect of the embodiments of the present invention proposes a computer-readable storage medium. FIG. 7 is a schematic diagram illustrating an embodiment of a computer-readable storage medium provided by the present invention. As shown in fig. 7, the computer-readable storage medium 31 stores a computer program 32 that, when executed by a processor, performs the following method:
acquiring historical data for storing performance index data, and dividing the historical data into a plurality of periodic units in a time unit;
sampling historical data in each periodic unit point by point in a sliding window mode to obtain sampling data of each periodic unit at each moment;
calculating a sample mean value and a standard deviation of the sampling data at each moment;
and calculating a reference value of the stored performance index data at each moment according to a preset formula.
In a preferred embodiment of the present invention, the stored performance index data includes IOPS, latency, and bandwidth.
In a preferred embodiment of the present invention, acquiring the history data storing the performance index data and dividing the history data into a plurality of periodic units in time units includes:
acquiring historical data in a preset time period in the storage performance index data;
the history data is divided into a plurality of periodic units in units of days.
In a preferred embodiment of the present invention, sampling the historical data in each periodic unit point by point in a sliding window manner to obtain the sampled data of each time of each periodic unit includes:
setting one historical data per minute as a sampling point at one moment;
setting a range of sampling data at each moment;
and calculating the maximum value or the minimum value in the sampling data range corresponding to the sampling data at each moment in each period unit, and taking the maximum value or the minimum value as the sampling data at each moment.
In a preferred embodiment of the present invention, calculating the sample mean and standard deviation of the sampled data at each instant in time comprises:
and calculating the sample mean value and standard deviation of the sampling data at the same time in all the periodic units.
In a preferred embodiment of the present invention, calculating the reference value of the stored performance index data for each time according to the preset formula includes:
in response to using the maximum value as the sampling data for each time instant, the formula referencevalue=μ is used 3 +k*σ 3 Calculating a reference value of the stored performance index data at each time, wherein reference value is the reference value of the stored performance index data,μ 3 for sampling the sample mean value, sigma of the data at one moment 3 The standard deviation of the data is sampled for one instant, where k e {1,2,3}.
In a preferred embodiment of the present invention, calculating the reference value of the stored performance index data for each time according to the preset formula includes:
in response to using the minimum value as the sampling data for each time instant, the formula referencevalue=μ is used 3 -k*σ 3 Calculating a reference value of the stored performance index data at each moment, wherein reference value is the reference value of the stored performance index data, mu 3 For sampling the sample mean value, sigma of the data at one moment 3 The standard deviation of the data is sampled for one instant, where k e {1,2,3}.
Furthermore, the method disclosed according to the embodiment of the present invention may also be implemented as a computer program executed by a processor, which may be stored in a computer-readable storage medium. The above-described functions defined in the methods disclosed in the embodiments of the present invention are performed when the computer program is executed by a processor.
Furthermore, the above-described method steps and system units may also be implemented using a controller and a computer-readable storage medium storing a computer program for causing the controller to implement the above-described steps or unit functions.
Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the disclosure herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as software or hardware depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.
In one or more exemplary designs, the functions may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one location to another. A storage media may be any available media that can be accessed by a general purpose or special purpose computer. By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a general purpose or special purpose computer or general purpose or special purpose processor. Further, any connection is properly termed a computer-readable medium. For example, if the software is transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital Subscriber Line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. Disk and disc, as used herein, includes Compact Disc (CD), laser disc, optical disc, digital Versatile Disc (DVD), floppy disk, blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.
The foregoing is an exemplary embodiment of the present disclosure, but it should be noted that various changes and modifications could be made herein without departing from the scope of the disclosure as defined by the appended claims. The functions, steps and/or actions of the method claims in accordance with the disclosed embodiments described herein need not be performed in any particular order. Furthermore, although elements of the disclosed embodiments may be described or claimed in the singular, the plural is contemplated unless limitation to the singular is explicitly stated.
It should be understood that as used herein, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly supports the exception. It should also be understood that "and/or" as used herein is meant to include any and all possible combinations of one or more of the associated listed items.
The foregoing embodiment of the present invention has been disclosed with reference to the number of embodiments for the purpose of description only, and does not represent the advantages or disadvantages of the embodiments.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program for instructing relevant hardware, and the program may be stored in a computer readable storage medium, where the storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
Those of ordinary skill in the art will appreciate that: the above discussion of any embodiment is merely exemplary and is not intended to imply that the scope of the disclosure of embodiments of the invention, including the claims, is limited to such examples; combinations of features of the above embodiments or in different embodiments are also possible within the idea of an embodiment of the invention, and many other variations of the different aspects of the embodiments of the invention as described above exist, which are not provided in detail for the sake of brevity. Therefore, any omission, modification, equivalent replacement, improvement, etc. of the embodiments should be included in the protection scope of the embodiments of the present invention.
Claims (10)
1. A method of calculating a stored performance index data reference value, comprising the steps of:
acquiring historical data for storing performance index data, and dividing the historical data into a plurality of periodic units in a time unit;
sampling historical data in each periodic unit point by point in a sliding window mode to obtain sampling data of each periodic unit at each moment;
calculating a sample mean value and a standard deviation of the sampling data at each moment;
and calculating a reference value of the stored performance index data at each moment according to a preset formula.
2. The method of claim 1, wherein storing performance index data comprises IOPS, latency, and bandwidth.
3. The method of claim 1, wherein obtaining historical data storing performance metric data and dividing the historical data into a number of periodic units in units of time comprises:
acquiring historical data in a preset time period in the storage performance index data;
the history data is divided into a plurality of periodic units in units of days.
4. The method of claim 1, wherein sampling the historical data in each periodic unit point by point using a sliding window method to obtain the sampled data for each time of each periodic unit comprises:
setting one historical data per minute as a sampling point at one moment;
setting a range of sampling data at each moment;
and calculating the maximum value or the minimum value in the sampling data range corresponding to the sampling data at each moment in each period unit, and taking the maximum value or the minimum value as the sampling data at each moment.
5. The method of claim 1, wherein calculating the sample mean and standard deviation of the sampled data at each time instant comprises:
and calculating the sample mean value and standard deviation of the sampling data at the same time in all the periodic units.
6. The method of claim 4, wherein calculating the reference value of the stored performance index data for each time according to the preset formula comprises:
responsive to use of a maximum value asFor the sampled data at each instant, the formula referencevalue=μ is used 3 +k*σ 3 Calculating a reference value of the stored performance index data at each moment, wherein reference value is the reference value of the stored performance index data, mu 3 For sampling the sample mean value, sigma of the data at one moment 3 The standard deviation of the data is sampled for one instant, where k e {1,2,3}.
7. The method of claim 4, wherein calculating the reference value of the stored performance index data for each time according to the preset formula comprises:
in response to using the minimum value as the sampling data for each time instant, the formula referencevalue=μ is used 3 -k*σ 3 Calculating a reference value of the stored performance index data at each moment, wherein reference value is the reference value of the stored performance index data, mu 3 For sampling the sample mean value, sigma of the data at one moment 3 The standard deviation of the data is sampled for one instant, where k e {1,2,3}.
8. An apparatus for calculating a stored performance index data reference value, the apparatus comprising:
the dividing module is configured to acquire historical data for storing performance index data and divide the historical data into a plurality of periodic units in time units;
the sampling module is configured to sample historical data in each periodic unit point by point in a sliding window mode so as to obtain sampling data of each periodic unit at each moment;
the first calculation module is configured to calculate a sample mean value and a standard deviation of the sampling data at each moment;
and the second calculation module is configured to calculate a reference value of the stored performance index data at each moment according to a preset formula.
9. A computer device, comprising:
at least one processor; and
a memory storing computer instructions executable on the processor, which when executed by the processor, perform the steps of the method of any one of claims 1-7.
10. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method of any one of claims 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310589617.0A CN116578466A (en) | 2023-05-19 | 2023-05-19 | Method, device, equipment and medium for calculating storage performance index data reference value |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310589617.0A CN116578466A (en) | 2023-05-19 | 2023-05-19 | Method, device, equipment and medium for calculating storage performance index data reference value |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116578466A true CN116578466A (en) | 2023-08-11 |
Family
ID=87539379
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310589617.0A Pending CN116578466A (en) | 2023-05-19 | 2023-05-19 | Method, device, equipment and medium for calculating storage performance index data reference value |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116578466A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117193676A (en) * | 2023-11-08 | 2023-12-08 | 苏州元脑智能科技有限公司 | Method, system, equipment and medium for evaluating performance of storage equipment |
-
2023
- 2023-05-19 CN CN202310589617.0A patent/CN116578466A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117193676A (en) * | 2023-11-08 | 2023-12-08 | 苏州元脑智能科技有限公司 | Method, system, equipment and medium for evaluating performance of storage equipment |
| CN117193676B (en) * | 2023-11-08 | 2024-02-09 | 苏州元脑智能科技有限公司 | Method, system, equipment and medium for evaluating performance of storage equipment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108304324B (en) | Test case generation method, device, equipment and storage medium | |
| EP3306475B1 (en) | System and method for predicting disk failure | |
| US10223190B2 (en) | Identification of storage system elements causing performance degradation | |
| US20200183946A1 (en) | Anomaly Detection in Big Data Time Series Analysis | |
| CN110059894B (en) | Equipment state evaluation method, device, system and storage medium | |
| CN111143102A (en) | Abnormal data detection method and device, storage medium and electronic equipment | |
| US10073866B2 (en) | Dynamic test case prioritization for relational database systems | |
| CN111104342B (en) | Method, electronic device and computer program product for storage | |
| CN112882889A (en) | Abnormality monitoring method, abnormality monitoring system, electronic device, and storage medium | |
| CN113837596B (en) | Fault determination method and device, electronic equipment and storage medium | |
| CN116578466A (en) | Method, device, equipment and medium for calculating storage performance index data reference value | |
| US8832839B2 (en) | Assessing system performance impact of security attacks | |
| CN111241155B (en) | Time sequence data abnormality detection method, device, equipment and storage medium | |
| US7617313B1 (en) | Metric transport and database load | |
| CN112527601A (en) | Monitoring early warning method and device | |
| US9824001B2 (en) | System and method for steady state performance testing of a multiple output software system | |
| US20160350692A1 (en) | Measuring Change in Software Developer Behavior Under Pressure | |
| US11068826B2 (en) | Enterprise skills development using cognitive computing | |
| CN110602207A (en) | Method, device, server and storage medium for predicting push information based on off-network | |
| US20220083816A1 (en) | Regression detection and correction in relationships between performance indicators and ai metrics | |
| CN109960626A (en) | Recognition methods, device, equipment and the medium of port exception | |
| JP2004078780A (en) | Method, device, and program for prediction, and recording medium recording the prediction program | |
| JP2020035297A (en) | Apparatus state monitor and program | |
| CN114266501A (en) | Automatic prediction and root cause analysis method and system for hospital operation index | |
| US20170053291A1 (en) | Optimal time scale and data volume for real-time fraud analytics |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |