CN115048266A - Storage port group I/O performance analysis method, readable storage medium and server - Google Patents

Storage port group I/O performance analysis method, readable storage medium and server Download PDF

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CN115048266A
CN115048266A CN202210682497.4A CN202210682497A CN115048266A CN 115048266 A CN115048266 A CN 115048266A CN 202210682497 A CN202210682497 A CN 202210682497A CN 115048266 A CN115048266 A CN 115048266A
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storage port
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performance
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左胜光
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Ping An Bank Co Ltd
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    • G06F11/00—Error detection; Error correction; Monitoring
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Abstract

The application provides a storage port group I/O performance analysis method, which comprises the following steps: obtaining input/output performance data of a storage port group, the performance data comprising: I/O operation times and I/O flow; standardizing the format of the performance data; collecting the I/O operation times in unit time and the I/O flow in unit time of a storage port group; calculating the standard deviation of the I/O operation times and the I/O flow; calculating the maximum variance in the I/O operation times and the I/O flow variance, wherein the maximum variance is the deviation degree between the variance of each storage port and the standard deviation of the storage port group; adjusting relevant configuration information of the I/O operation times of which the maximum standard deviation is larger than a preset variance standard value in the I/O operation times; and adjusting the relevant configuration information of the I/O flow of which the maximum standard deviation is larger than a preset standard deviation value in the I/O flow. According to the technical scheme, the I/O performance data of the storage port group can be analyzed more conveniently and intelligently.

Description

Storage port group I/O performance analysis method, readable storage medium and server
Technical Field
The present application relates to the field of mobile internet, and in particular, to a method for analyzing I/O performance of a storage port group, a computer-readable storage medium, and a server.
Background
The industries such as banking and telecommunication have extremely high requirements on the security and stability of data, so most of core system data are stored in a professional hardware Storage Area Network (SAN) storage. Currently, SAN storage is used by mapping a storage volume (a logical disk storing data) to a front-end host through a storage port group. However, the existing hardware SAN storage only provides simple I/O performance data of the storage ports in the port group, and meanwhile, data formats provided by various manufacturers are inconsistent, and a specific scheme for processing, sorting and analyzing the data is lacked.
In an actual production environment, whether a new service system is on-line or an existing production system is subjected to fault processing, I/O load performance data stored in a back-end SAN needs to be analyzed and diagnosed in time, and the analysis and diagnosis seriously depend on the performance load analysis of I/O of a storage port group.
Due to the lack of a means for analyzing the I/O load performance of the storage port groups, it is impossible to judge and predict whether the I/O in the storage port groups is balanced or not, and whether the I/O between the storage port groups is balanced or not, which may cause the failure processing of the production service system to be unable to process in time, thereby affecting the availability of the production system.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a storage port group I/O performance analysis method, a computer-readable storage medium, and a server that are more convenient and intelligent.
In a first aspect, an embodiment of the present application provides a method for analyzing I/O performance of a storage port group, where the method for analyzing I/O performance of a storage port group includes the following steps:
obtaining input/output performance data of a storage port group, the performance data comprising: I/O operation times and I/O flow;
standardizing the format of the performance data;
collecting the I/O operation times in unit time and the I/O flow in unit time of a storage port group;
calculating the standard deviation of the I/O operation times and the I/O flow;
calculating the maximum variance in the I/O operation times and the I/O flow variance, wherein the maximum variance is the deviation degree between the variance of each storage port and the standard deviation of the storage port group;
adjusting relevant configuration information of the I/O operation times of which the maximum standard deviation is larger than a preset variance standard value in the I/O operation times; and
and adjusting the relevant configuration information of the I/O flow of which the maximum standard deviation is larger than a preset standard deviation value in the I/O flow.
In a second aspect, an embodiment of the present application provides a computer-readable storage medium, where the computer-readable storage medium is configured to store program instructions, where the program instructions are executable by a processor to implement the storage port group I/O performance analysis method described above.
In a third aspect, an embodiment of the present application provides a server, where the server includes: the computer readable storage medium is used for storing program instructions, and the processor and the bus execute the program instructions to realize the storage port group I/O performance analysis method.
According to the storage port group I/O performance analysis method, the computer readable storage medium and the server, the acquired performance data are standardized, so that the acquired performance data are more conveniently analyzed, the maximum variance of the storage ports of the acquired performance data is compared, and the storage ports can be found out to be performance hotspots in time and adjusted in time.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the embodiments or the prior art descriptions will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art according to the structures shown in the drawings without creative efforts.
Fig. 1 is a flowchart of a method for analyzing I/O performance of a storage port group according to an embodiment of the present application.
Fig. 2 is a first sub-flowchart of a method for analyzing I/O performance of a storage port group according to an embodiment of the present disclosure.
Fig. 3 is a second sub-flowchart of a method for analyzing I/O performance of a storage port group according to an embodiment of the present application.
FIG. 4 is a third sub-flow of a storage port group I/O performance analysis method according to an embodiment of the present application
Fig. 5 is a fourth sub-flowchart of a storage port group I/O performance analysis method according to an embodiment of the present application.
Fig. 6 is a fifth sub-flowchart of a method for analyzing I/O performance of a storage port group according to an embodiment of the present application.
Fig. 7 is a sixth sub-flowchart of a method for analyzing I/O performance of a storage port group according to an embodiment of the present application.
Fig. 8 is a schematic internal structural diagram of a server according to an embodiment of the present application.
The implementation, functional features and advantages of the objectives of the present application will be further explained with reference to the accompanying drawings.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims of the present application and in the above-described drawings (if any) are used for distinguishing between similar items and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances, in other words that the embodiments described are to be practiced in sequences other than those illustrated or described herein. Moreover, the terms "comprises," "comprising," and any other variation thereof, may also include other things, such as processes, methods, systems, articles, or apparatus that comprise a list of steps or elements is not necessarily limited to only those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such processes, methods, articles, or apparatus.
It should be noted that the descriptions in this application referring to "first", "second", etc. are for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In addition, technical solutions between various embodiments may be combined with each other, but must be realized by a person skilled in the art, and when the technical solutions are contradictory or cannot be realized, such a combination should not be considered to exist, and is not within the protection scope of the present application.
Please refer to fig. 1 in combination, which is a flowchart illustrating an I/O performance analysis method for a storage port group according to an embodiment of the present application. The storage port group I/O performance analysis method specifically comprises the following steps S102-S114.
Step S102, obtaining input and output performance data of a storage port group, wherein the performance data comprises: I/O operation times and I/O traffic. It can be appreciated that most of the core system data in the current industry is stored in a hardware Storage Area Network (SAN) storage, and the SAN storage is used by mapping a storage volume to a front-end host through a storage port group, and a server needs to acquire input/output (I/O) performance data of a port in the storage port group through a performance collection interface provided by the hardware SAN storage. And storing the acquired performance data in a database
And step S104, carrying out standardization processing on the format of the performance data. It will be appreciated that the server may need to obtain performance data from different storage vendors. In order to better manage the data, the acquired performance data is put in storage and then standardized, and the specific standardization is described in detail below.
And step S106, collecting the I/O operation times in unit time and the I/O flow in unit time of the storage port group. It will be appreciated that the user may set a collection period to periodically collect the number of I/O operations and/or I/O traffic stored in a designated set of storage ports in the database. And the user can perform self-defined setting in the acquisition period. For example, the user sets the number of I/O operations in the storage port group a collected once an hour, and sets the I/O traffic of the storage port group a collected once a half hour. The server will begin to access the database every half hour to collect the data of the I/O traffic after the acquisition time for collecting the I/O traffic is successfully set, and the server will begin to access the database every hour after the acquisition time for collecting the I/O operation times is successfully set, collect the data of the I/O operation times in the storage port group a, and extract the data collected from the database.
And step S108, calculating the I/O operation times and the standard deviation of the I/O flow. It can be understood that, the user extracts the I/O operation times data and/or the I/O traffic data of the required storage port group from the database, stores the extracted data in an array format, and performs standard deviation calculation on the I/O operation times data and the I/O traffic data stored in the array format. The standard deviation calculations are described in detail below.
Step S110, calculating the maximum variance in the I/O operation times and the I/O flow variance, wherein the maximum variance is the deviation degree between the variance of each storage port and the standard deviation of the storage port group. It can be understood that after the standard deviation of the storage port group a is calculated, the variance calculation of each storage port in the storage port group is started to obtain the variance of each storage port, and the variance of the storage port and the standard deviation of the storage port group are compared
And step S112, adjusting the relevant configuration information of the I/O operation times of which the maximum standard deviation is greater than a preset variance standard value in the I/O operation times. It can be understood that, the user sets a preset variance standard value of the I/O operation times of the storage port by user, the server monitors whether the maximum standard deviation exceeds the preset variance standard value, when the maximum variance exceeds the preset variance standard value, the server needs to pay attention to the application corresponding to the storage port, and checks and adjusts the configuration information related to the I/O operation times in the application host
And step S114, adjusting the relevant configuration information of the I/O flow of which the maximum standard deviation is larger than a preset standard deviation value in the I/O flow. It can be understood that, the user sets a preset variance standard value of the I/O flow of the storage port by self-definition, the server monitors whether the maximum standard deviation exceeds the preset variance standard value, when the maximum variance exceeds the preset variance standard value, it is necessary to pay attention to the application corresponding to the storage port, and check and adjust the configuration information related to the I/O flow in the application host
In the embodiment, the performance data acquired from different manufacturers are standardized, so that the acquired performance data are more conveniently analyzed, and the maximum variance of the storage port of the acquired performance data is compared, so that the storage port can be found out as a performance hotspot in time and can be adjusted in time.
Please refer to fig. 2 in combination, which is a first sub-flowchart of a method for analyzing I/O performance of a storage port group according to an embodiment of the present application. Step S108 specifically includes the following steps S202-S204.
In step S202, the number of I/O operations per unit time of the storage port group is extracted. It is understood that if the number of I/O operations in each storage port in the storage port group has a value of X1, X2, X3... Xi... Xn. And accessing the database by the server to extract the value of the number of times of I/O operation of each storage port in the storage port group, and storing the extracted value of the number of times of I/O operation of each storage port in an array manner to obtain [ X1, X2, X3... Xi... Xn ].
In step S204, the standard deviation of the I/O operation times in the unit time of the storage port group is calculated. It can be understood that the average value of the values of the number of I/O operations in the storage port group extracted from the database is calculated, the variance formula is used to perform variance calculation on the values of the number of I/O operations in the storage port group, and the standard deviation of the values of the number of I/O operations in the storage port group is obtained through the variance. This process is formulated as:
Figure BDA0003698894040000061
where S is the standard deviation of the memory port set, S 2 To store the variance, x, of a port group i Is the value of the number of I/O operations for the ith memory port,
Figure BDA0003698894040000062
is the average value of the I/O operation times, and n is n storage ports.
Please refer to fig. 3 in combination, which is a second sub-flowchart of a method for analyzing I/O performance of a storage port group according to an embodiment of the present application. Step S108 specifically comprises the following steps S302-S304.
Step S302, extracting the I/O flow in the unit time of the storage port group. It is to be understood that if the value of I/O traffic in each storage port in the storage port group is Y1, Y2, Y3... Yi... Yn. Accessing the database through the server to extract the value of the I/O traffic of each storage port in the storage port group, and storing the extracted value of the I/O traffic of each storage port in an array manner to obtain [ Y1, Y2, Y3... Yi... Yn ].
Step S304, calculating the standard deviation of the I/O flow in the unit time of the storage port group. It can be understood that the average value of the I/O flow values in the storage port group extracted from the database is calculated, the variance formula is used to calculate the variance of the I/O flow values of the storage port group, and the standard deviation of the I/O flow values of the storage port group is obtained through the variance. The process is formulated as
Figure BDA0003698894040000063
Figure BDA0003698894040000064
Where F is the standard deviation of the memory port group, F 2 To store the variance, y, of a port group i Is the value of the number of I/O operations for the ith memory port,
Figure BDA0003698894040000065
is the average value of the I/O operation times, and n is n storage ports.
Please refer to fig. 4 in combination, which is a third sub-flowchart of a method for analyzing I/O performance of a storage port group according to an embodiment of the present application. Step S112 specifically includes the following steps S402 to S408.
Step S402The variance of the number of I/O operations per storage port is calculated. It is understood that the variance of the number of I/O operations of each storage port is obtained by subtracting the absolute value of the standard deviation of the number of I/O operations of the storage port group from the value of the number of I/O operations of each storage port, and dividing by the standard deviation of the number of I/O operations of the storage port group. Is expressed as C by formula i ＝|x i -S |/S (formula three), where C i Variance, x, of the number of I/O operations for the ith memory port i Is the value of the number of I/O operations for the ith storage port, and S is the standard deviation of the storage port group.
In step S404, the maximum variance value in the storage port group is set as the maximum variance. It is to be understood that the variance of the number of I/O operations per memory port is obtained by calculating for each memory port using formula three, and the maximum variance value calculated using formula three is automatically set as the maximum variance. For example, suppose there are 4 ports in the storage port group, and the number of I/O operations per port is 20 for port 1, 60 for port 2, 10 for port 3, and 30 for port 4. The standard deviation of the port group is 18.7 by formula one. And then, calculating by using a formula III to obtain that the variance of the I/O operation times of the port 1 is 0.07, the variance of the I/O operation times of the port 2 is 2.21, the variance of the I/O operation times of the port 3 is 0.47 and the variance of the I/O operation times of the port 4 is 0.60. The variance of the port 2 is the largest according to the calculation result, namely, the server automatically sets the variance of the port 2 as the maximum variance.
Step S406, the maximum variance is compared with a preset maximum variance standard value. It is understood that if the user sets the preset maximum variance criterion value of the number of I/O operations to be 3, the maximum variance of 2.21 is obtained according to step S404. 2.21<3, i.e. the maximum variance is smaller than the preset maximum variance criterion value of the number of I/O operations. If the user sets the preset maximum variance standard value of the I/O operation times to be 2, the maximum variance is 2.21 according to the step S404. 2.21>2, namely the maximum variance is larger than the preset maximum variance standard value of the I/O operation times.
In step S408, when the maximum variance is greater than the preset maximum variance standard value, the configuration information related to the storage port group is modified. It is understood that if the maximum variance is 2.21, the preset maximum variance criterion value is 2. When the server detects that the maximum variance is larger than a preset maximum variance standard value, the server starts to check the configuration information of the relevant I/O operation times of the storage port to the used host application, and performs corresponding modification to balance the I/O load among the ports in the port group.
Please refer to fig. 5 in combination, which is a fourth sub-flowchart of a method for analyzing I/O performance of a storage port group according to an embodiment of the present application. Step S114 specifically includes the following steps S502 to S508.
Step S502, calculating the variance of the I/O flow of each storage port. It is understood that the variance of the I/O traffic of each storage port is obtained by subtracting the absolute value of the standard deviation of the I/O traffic of the storage port group from the value of the I/O traffic of that storage port, and dividing by the standard deviation of the I/O traffic of the storage port group. Is expressed as M by formula i ＝|y i -F |/F (formula four), where M i Variance of I/O traffic for the ith storage port, y i Is the value of the I/O traffic for the ith storage port, and F is the standard deviation of the storage port group.
In step S504, the maximum variance value in the storage port group is set as the maximum variance. It is to be understood that the variance of the I/O traffic of each storage port is calculated by using formula four, and the maximum variance value calculated by using formula four is automatically set as the maximum variance. For example, suppose there are 4 ports in the storage port group, and the I/O traffic per port is 2000mb for port 1, 6000mb for port 2, 1000mb for port 3, and 3000mb for port 4. The standard deviation of the port group is 1870 by equation two. Then, the variance of the I/O flow of the port 1 is 0.07, the variance of the I/O flow of the port 2 is 2.21, the variance of the I/O flow of the port 3 is 0.47, and the variance of the I/O flow of the port 4 is 0.60. The variance of the port 2 is the largest according to the calculation result, namely, the server automatically sets the variance of the port 2 as the maximum variance.
Step S506, the maximum variance is compared with a preset maximum variance standard value. It is understood that if the user sets the preset maximum I/O flow variance criterion value to be 3, the maximum variance is 2.21 according to step S404. 2.21<3, i.e. the maximum variance is smaller than the preset maximum I/O flow variance criterion value. If the user sets the preset maximum I/O flow variance standard value to be 2, the maximum variance is 2.21 according to step S404. 2.21>2, namely the maximum variance is larger than the preset maximum I/O flow variance standard value.
Step S508, when the maximum variance is greater than the preset maximum variance standard value, modifying the configuration information related to the storage port group. It is understood that if the maximum variance is 2.21, the preset maximum I/O flow variance criterion value is 2. And when detecting that the maximum variance is larger than a preset maximum variance standard value, the server starts to check the configuration information of the storage port on the relevant I/O flow of the used host application, and performs corresponding modification to balance the I/O load among the ports in the port group.
Please refer to fig. 6, which is a fifth sub-flowchart of a method for analyzing I/O performance of a storage port group according to an embodiment of the present application. Step S102 specifically includes the following steps S602 to S604.
In the above embodiment, the standard deviation and the variance of each storage port group are calculated, and then the maximum variance comparison algorithm is used to obtain the performance hot spot of the current storage port, and the application corresponding to the storage port is adjusted in time, so that the I/O load in each storage port group and between the port groups is balanced.
Step S602, collecting the storage port group once per unit time. It is to be understood that, in the present embodiment, the collected data is minute-level data, that is, performance data of the storage port group is collected once every minute. The minute-level data are superimposed on the basis of data within 1 minute, data within 2 minutes, data within 5 minutes, and the like, and data within a required minute is taken.
Step S604, storing the acquired input/output performance data in a database. It is to be understood that, in the present embodiment, since the collected data is the minute-level data, the server stores the collected minute-level data in the time-series database. The whole process of the time sequence database is a time sequence database which is mainly used for processing data with time labels, and the time sequence database is characterized in that a plurality of pieces of data can be generated at each monitoring point within one second, namely, the generation frequency is high, each piece of data is required to correspond to unique time, namely, the time sequence database depends on the acquisition time seriously, a conventional real-time monitoring system has thousands of monitoring points, the monitoring points generate data every second, and the data volume of dozens of GB is generated every day. Namely, the amount of multi-information of the measuring points is large.
According to the embodiment, the performance data with the extremely large data volume is collected once per minute, and the time sequence database is used for storing, so that the numerical query based on time can be greatly improved.
Please refer to fig. 7 in combination, which is a sixth sub-flowchart of a method for analyzing I/O performance of a storage port group according to an embodiment of the present application. Step S104 specifically includes the following steps S702-S708.
Step S702, storing the obtained input/output performance data of different storage port groups in a database.
Step S704, the performance data is cleaned in the database to obtain abnormal-free data. It can be understood that the server performs data cleaning on the performance data stored in the database to find abnormal data such as incomplete data, error data, repeated data and the like in the performance data, and finally obtains the required normal data.
And step S706, sorting the cleaned performance data in a database. It can be understood that after the server finishes cleaning the collected performance data, the server starts to sort and combine the cleaned performance data stored in the database, so as to ensure the integrity of the data.
Step S708, unifying the sorted performance data according to a preset data format. It can be understood that after the performance data in the database is sorted by the server, the sorted performance data is subjected to standardized processing according to a required preset data format written by a developer, so that formats of the performance data stored in the database are unified. In this embodiment, the preset data format is:
Figure BDA0003698894040000101
Figure BDA0003698894040000102
in the above embodiment, the collected performance data of different storage port groups is subjected to the standardized processing of the format, so that the data analysis of the storage of different storage manufacturers is facilitated
Embodiments of the present application provide a computer-readable storage medium for storing a computer program, where the computer program is executed by a processor to implement part or all of the steps of any one of the methods described in the above embodiments.
Please refer to fig. 8, which is a schematic diagram of an internal structure of a server according to an embodiment of the present application. The server 10 includes a computer-readable storage medium 11, a processor 12, and a bus 13. The computer-readable storage medium 11 includes at least one type of readable storage medium, which includes a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, and the like. The computer readable storage medium 11 may in some embodiments be an internal storage unit of the server 10, such as a hard disk of the server 10. The computer readable storage medium 11 may also be, in other embodiments, an external server 10 storage device, such as a plug-in hard drive, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), or the like, provided on the server 10. Further, the computer-readable storage medium 11 may also include both an internal storage unit of the server 10 and an external storage device. The computer-readable storage medium 11 may be used not only to store application software and various types of data installed in the server 10 but also to temporarily store data that has been output or will be output.
The bus 13 may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 8, but this is not intended to represent only one bus or type of bus.
Further, the server 10 may also include a display component 14. The display component 14 can be a Light Emitting Diode (LED) display, a liquid crystal display, a touch-sensitive liquid crystal display, an Organic Light-Emitting Diode (OLED) touch panel, and the like. The display component 14 may also be referred to as a display device or a display unit, as appropriate, for displaying information processed in the server 10 and for displaying a visualized user interface.
Further, the server 10 may also include a communication component 15. The communication component 15 may optionally include a wired communication component and/or a wireless communication component, such as a WI-FI communication component, a bluetooth communication component, etc., typically used to establish communication connections between the server 10 and other intelligent control devices.
The processor 12 may be, in some embodiments, a Central Processing Unit (CPU), controller, microcontroller, microprocessor or other data Processing chip for executing program codes stored in the computer-readable storage medium 11 or Processing data. Specifically, the processor 12 executes a processing program to control the server 10 to implement the storage port group I/O performance analysis method.
It is to be understood that fig. 8 only shows the server 10 having the components 11-15 and the storage port group I/O performance analysis method, and those skilled in the art will appreciate that the structure shown in fig. 8 does not constitute a limitation of the server 10, and may include fewer or more components than shown, or combine certain components, or a different arrangement of components.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, to the extent that such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, it is intended that the present application also encompass such modifications and variations.
The above-mentioned embodiments are only examples of the present invention, and the scope of the claims of the present invention should not be limited by these examples, so that the claims of the present invention should be construed as equivalent and still fall within the scope of the present invention.

Claims (10)

1. An I/O performance analysis method for a storage port group, the I/O performance analysis method comprising:
obtaining input/output performance data of a storage port group, the performance data comprising: I/O operation times and I/O flow;
standardizing the format of the performance data;
collecting the I/O operation times in unit time and the I/O flow in unit time of a storage port group;
calculating the standard deviation of the I/O operation times and the I/O flow;
calculating the maximum variance in the I/O operation times and the I/O flow variance, wherein the maximum variance is the deviation degree between the variance of each storage port and the standard deviation of the storage port group;
adjusting relevant configuration information of the I/O operation times of which the maximum standard deviation is larger than a preset variance standard value in the I/O operation times; and
and adjusting the relevant configuration information of the I/O flow of which the maximum standard deviation is larger than a preset standard deviation value in the I/O flow.
2. The storage port group I/O performance analysis method of claim 1, wherein calculating the standard deviation of the number of I/O operations specifically comprises:
extracting the number of I/O operations in unit time of the storage port group; and
the standard deviation of the number of I/O operations per unit time of the storage port group is calculated.
3. The storage port group I/O performance analysis method of claim 1, wherein calculating the standard deviation of the I/O traffic specifically comprises:
extracting I/O flow of a storage port group in unit time; and
the standard deviation of the I/O traffic per unit time of the storage port group is calculated.
4. The method for analyzing I/O performance of a storage port set according to claim 1, wherein the adjusting the configuration information related to the I/O operation count whose maximum standard deviation is greater than a preset variance standard value among the I/O operation counts specifically includes:
calculating the variance of the I/O operation times of each storage port;
setting the maximum variance value in the storage port group as the maximum variance;
comparing the maximum variance with a preset maximum variance standard value; and
and modifying the configuration information related to the storage port group when the maximum variance is larger than a preset maximum variance standard value.
5. The method for analyzing I/O performance of a storage port set according to claim 1, wherein adjusting the configuration information related to the I/O traffic whose maximum standard deviation is greater than a preset standard deviation value among the I/O traffic specifically comprises:
calculating the variance of the I/O flow of each storage port;
setting the maximum variance value in the storage port group as the maximum variance;
comparing the maximum variance with a preset maximum variance standard value; and
when the maximum variance is larger than a preset maximum variance standard value, modifying the configuration information related to the storage port group.
6. The method for analyzing I/O performance of a storage port group according to claim 1, wherein the obtaining input/output performance data of the storage port group specifically includes:
collecting the storage port group once in unit time; and
and storing the acquired input and output performance data in a database.
7. The method for analyzing I/O performance of a storage port group according to claim 1, wherein the step of standardizing the format of the performance data specifically comprises:
storing the obtained input and output performance data of different storage port groups in a database;
cleaning the performance data in the database to obtain abnormal-free data;
sorting the cleaned performance data in a database;
unifying the sorted performance data according to a preset data format.
8. The I/O performance analysis method of a storage port group according to claim 2 or 3, wherein the reading input/output times and the flow rate of the storage port group per unit time are extracted in an array format.
9. A computer-readable storage medium for storing program instructions executable by a processor to implement the storage port group I/O performance analysis method of any of claims 1 to 8.
10. A server, characterized in that the server comprises:
a computer readable storage medium for storing program instructions; and
a processor executes the program instructions to implement the storage port group I/O performance analysis method of any of claims 1 to 8.
CN202210682497.4A 2022-06-16 2022-06-16 Storage port group I/O performance analysis method, readable storage medium and server Pending CN115048266A (en)

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