CN111933207A

CN111933207A - Slow disk identification method and device, electronic equipment and storage equipment

Info

Publication number: CN111933207A
Application number: CN202010871357.2A
Authority: CN
Inventors: 牛犇; 严勇; 刘裕勋
Original assignee: Tencent Technology Shenzhen Co Ltd
Current assignee: Tencent Technology Shenzhen Co Ltd
Priority date: 2020-08-26
Filing date: 2020-08-26
Publication date: 2020-11-13

Abstract

The disclosure provides a slow disc detection method and device, electronic equipment and a storage medium, and belongs to the technical field of storage. The method comprises the following steps: determining a slow disc identification parameter of the hard disc according to at least one of the abnormal response frequency or the abnormal response frequency deviation data; and carrying out slow disk identification on the hard disk according to the slow disk identification parameters. According to the method and the device, the response time of the hard disk is subjected to statistical analysis, the delay influence of other software and hardware nodes on an I/O link is eliminated, the slow disk with high delay risk in a cluster can be found in time, the response time is shortened, and the storage and reading efficiency is improved. And the delayed response of the hard disk is statistically analyzed by adopting a statistical angle, the screened hard disk is the hard disk with abnormal performance for a long time, the misjudgment of accidental delay on the hard disk is reduced, the detection accuracy is improved, the rate of wrong disk replacement and the rate of secondary failure are reduced, and the labor cost and the material cost are saved.

Description

Slow disk identification method and device, electronic equipment and storage equipment

Technical Field

The present disclosure relates to the field of storage technologies, and in particular, to a slow disc identification method and apparatus, an electronic device, and a storage medium.

Background

In order to meet the business processing requirement, a hard disk is usually disposed on the electronic device. The Input/Output (I/O) response time of the hard disk becomes long due to head degradation, external vibration, and the like, and becomes a slow disk. The hard disk is used as a carrier for data storage, and the performance of the hard disk directly influences the overall performance of the electronic equipment. Therefore, there is a need to identify slow discs in electronic devices.

At present, in the related technology, a detection tool is mainly adopted to identify a slow disk in electronic equipment, an I/O tracking tool such as blktrace is set up during identification to obtain the response time of hardware equipment on an I/O link, and when the response time of the hardware equipment exceeds a threshold, a hard disk is identified as the slow disk.

However, the hardware devices on the I/O link include hardware drivers, disk arrays, expander backplanes, hard disks, and other devices, the response time of the hardware devices is the total response time of each device, and the response delay of the hard disk itself cannot be accurately reflected, and considering the complexity of the operating environment, the response time of a certain time cannot reflect the performance of the hard disk itself, so the accuracy of the related technology for identifying the slow disk is low.

Disclosure of Invention

The embodiment of the disclosure provides a hard disk identification method and device, an electronic device and a storage medium, which can improve the accuracy of slow disk identification. The technical scheme is as follows:

in one aspect, a slow disc identification method is provided, and the method includes:

determining the abnormal response frequency of the hard disk according to the response time and the power-on time of the hard disk;

determining abnormal response frequency deviation data of the hard disks according to the abnormal response frequency and an average abnormal response frequency, wherein the average abnormal response frequency is determined according to the abnormal response frequencies of a plurality of hard disks in the electronic equipment, and the abnormal response frequency deviation data is used for representing the difference between the abnormal response frequency and the average abnormal response frequency;

determining a slow disk identification parameter of the hard disk according to at least one of the abnormal response frequency or the abnormal response frequency deviation data, wherein the slow disk identification parameter is used for representing the possibility that the hard disk is a slow disk;

and performing slow disk identification on the hard disk according to the slow disk identification parameters.

In another aspect, there is provided a slow disc recognition apparatus, the apparatus including:

the first determining module is used for determining the abnormal response frequency of the hard disk according to the response time and the power-on time of the hard disk;

a second determining module, configured to determine abnormal response frequency deviation data of the hard disks according to the abnormal response frequency and an average abnormal response frequency, where the average abnormal response frequency is determined according to abnormal response frequencies of a plurality of hard disks in the electronic device, and the abnormal response frequency deviation data is used to represent a difference between the abnormal response frequency and the average abnormal response frequency;

a third determining module, configured to determine a slow disc identification parameter of the hard disc according to at least one of the abnormal response frequency or the abnormal response frequency deviation data, where the slow disc identification parameter is used to indicate a possibility that the hard disc is a slow disc;

and the identification module is used for identifying the slow disk of the hard disk according to the slow disk identification parameters.

In another aspect, an electronic device is provided, which includes a processor and a memory, where at least one program code is stored, and the at least one program code is loaded and executed by the processor to implement the slow disc recognition method according to an aspect.

In another aspect, a computer readable storage medium having at least one program code stored therein is provided, the at least one program code being loaded and executed by a processor to implement a slow disc recognition method according to an aspect.

In another aspect, a computer program product or a computer program is provided, the computer program product or the computer program comprising computer instructions stored in a computer-readable storage medium, the computer instructions being read by a processor of a computer device from the computer-readable storage medium, the computer instructions being executed by the processor to cause the computer device to perform the method provided in the various alternative implementations of the above aspect.

The technical scheme provided by the embodiment of the disclosure has the following beneficial effects:

by carrying out statistical analysis on the response time of the hard disk, the delay influence of other software and hardware nodes on an I/O link is eliminated, a slow disk with high delay risk in a cluster can be found in time, the response time is shortened, and the storage and reading efficiency is improved. And the delayed response of the hard disk is statistically analyzed by adopting a statistical angle, the screened hard disk is the hard disk with abnormal performance for a long time, the misjudgment of accidental delay on the hard disk is reduced, the detection accuracy is improved, the rate of wrong disk replacement and the rate of secondary failure are reduced, and the labor cost and the material cost are saved.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present disclosure, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.

FIG. 1 is a schematic diagram of an instruction passing process at a block input/output layer according to an embodiment of the present disclosure;

fig. 2 is a flowchart of a slow disc identification method provided by an embodiment of the present disclosure;

FIG. 3 is a flow chart of another slow disc identification method provided by the embodiments of the present disclosure;

FIG. 4 is a distribution diagram of a slow disc likelihood estimation parameter provided by an embodiment of the present disclosure;

FIG. 5 is a timing diagram of slow disc recognition provided by embodiments of the present disclosure;

fig. 6 is a schematic structural diagram of a slow disc recognition device according to an embodiment of the present disclosure;

fig. 7 shows a block diagram of a terminal provided in an exemplary embodiment of the present disclosure;

fig. 8 is an illustration of a server for slow disc recognition, in accordance with an exemplary embodiment.

Detailed Description

To make the objects, technical solutions and advantages of the present disclosure more apparent, embodiments of the present disclosure will be described in detail with reference to the accompanying drawings.

Before carrying out the embodiments of the present disclosure, terms to which the embodiments of the present disclosure relate will be explained first.

The slow disk is a hard disk with long I/O response time due to magnetic head degradation, external vibration, environmental problems, and the like.

The abnormal response frequency refers to the number of times of abnormal response of the hard disk in unit time.

The abnormal response frequency deviation data represents a difference between an abnormal response frequency of the hard disk and an average abnormal response frequency that is an average of abnormal response frequencies of a plurality of hard disks in the electronic apparatus.

The slow disk identification parameter represents the possibility that the hard disk is a slow disk, and the value range of the slow disk identification parameter is [0, 1 ].

The slow disk likelihood estimation parameter represents a relationship between the possibility that the hard disk is a slow disk and the possibility that the hard disk is a non-slow disk, and is embodied by an estimation result of likelihood estimation on the hard disk.

With the development of technologies such as computers, cloud storage and cloud computing, the requirement on storage performance is higher and higher. In the storage array system, data is stored in each hard disk in parallel, if a hard disk becomes a slow disk, the response speed of the whole system is tired, and service interruption is caused in severe cases, so that the performance of electronic equipment is influenced. In addition, referring to fig. 1, an I/O request sent by a user in a storage array system may pass through a plurality of software and hardware nodes such as a file system, a page cache, a request queue, and a virtual device, and these nodes may affect the acquisition of the response time of the hard disk, thereby affecting the accuracy of the slow disk identification result.

In order to improve the accuracy of a slow disk identification result, improve the response speed of a system and ensure smooth operation of a service, the embodiment of the disclosure provides a slow disk identification method, which monitors the performance of a hard disk and screens the slow disk based on the I/O response time of a bottom hard disk, performs statistical distribution and log-likelihood analysis on each hard disk in electronic equipment by recording the I/O delay times of exceeding a threshold value in the hard disk, screens out the hard disks with low and discrete performances in the electronic equipment, and thus monitors and intercepts the slow disk which affects the service performance in advance. The embodiment of the disclosure directly performs statistical analysis on the response time of the hard disk, eliminates the influence of other nodes and software in an I/O topological link, and performs transverse comparison and statistical analysis according to the delay condition of each hard disk in the electronic equipment, thereby accurately completing monitoring and screening of the bottom-layer high-delay slow disk.

Techniques involved in embodiments of the present disclosure are described.

Cloud technology refers to a collection of Cloud technology (Cloud technology) that is a hosting technology applied based on a Cloud computing business model and is a network technology, an information technology, an integration technology, a management platform technology, an application technology and the like, which unifies series of resources such as hardware, software, networks and the like in a wide area network or a local area network to realize calculation, storage, processing and sharing of data, and can form a resource pool to be used as required, and is flexible and convenient. Cloud computing technology will become an important support. Background services of the technical network system require a large amount of computing and storage resources, such as video websites, picture-like websites and more web portals. With the high development and application of the internet industry, each article may have its own identification mark and needs to be transmitted to a background system for logic processing, data in different levels are processed separately, and various industrial data need strong system background support and can only be realized through cloud computing.

A distributed cloud storage system (hereinafter, referred to as a storage system) refers to a storage system that integrates a large number of storage devices (storage devices are also referred to as storage nodes) of different types in a network through application software or application interfaces to cooperatively work by using functions such as cluster application, grid technology, and a distributed storage file system, and provides a data storage function and a service access function to the outside.

At present, a storage method of a storage system is as follows: logical volumes are created, and when created, each logical volume is allocated physical storage space, which may be the disk composition of a certain storage device or of several storage devices. The client stores data on a certain logical volume, that is, the data is stored on a file system, the file system divides the data into a plurality of parts, each part is an object, the object not only contains the data but also contains additional information such as data identification (ID, ID entry), the file system writes each object into a physical storage space of the logical volume, and the file system records storage location information of each object, so that when the client requests to access the data, the file system can allow the client to access the data according to the storage location information of each object.

The process of allocating physical storage space for the logical volume by the storage system specifically includes: physical storage space is divided in advance into stripes according to a group of capacity measures of objects stored in a logical volume (the measures often have a large margin with respect to the capacity of the actual objects to be stored) and Redundant Array of Independent Disks (RAID), and one logical volume can be understood as one stripe, thereby allocating physical storage space to the logical volume.

The embodiment of the disclosure provides a slow disk identification method, which can be executed by an electronic device, wherein the electronic device is provided with one or more hard disks for storing data required by service operation, and can provide support in aspects of calculation, storage and the like for service execution. The electronic device may be a terminal or a server. When the electronic device is a terminal, the electronic device may be a smart phone, a tablet computer, a notebook computer, a desktop computer, a smart speaker, a smart watch, or the like, but is not limited thereto. When the electronic device is a server, the server may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server providing basic cloud computing services such as a cloud service, a cloud database, cloud computing, a cloud function, cloud storage, a Network service, cloud communication, a middleware service, a domain name service, a security service, a CDN (Content Delivery Network), a big data and an artificial intelligence platform.

It is to be understood that the terms "each," "a plurality," and "any" and the like, as used in the embodiments of the present disclosure, are intended to encompass two or more, each referring to each of the corresponding plurality, and any referring to any one of the corresponding plurality. For example, the plurality of words includes 10 words, and each word refers to each of the 10 words, and any word refers to any one of the 10 words.

The embodiment of the present disclosure provides a slow disc identification method, referring to fig. 2, a method flow provided by the embodiment of the present disclosure includes:

201. and determining the abnormal response frequency of the hard disk according to the response time and the power-on time of the hard disk.

202. And determining abnormal response frequency deviation data of the hard disk according to the abnormal response frequency and the average abnormal response frequency.

Wherein the average abnormal response frequency is determined from abnormal response frequencies of a plurality of hard disks in the electronic device, and the abnormal response frequency deviation data is used to represent a difference between the abnormal response frequency and the average abnormal response frequency.

203. And determining a slow disk identification parameter of the hard disk according to at least one of the abnormal response frequency or the abnormal response frequency deviation data.

Wherein the slow disk identification parameter is used to indicate the possibility that the hard disk is a slow disk.

204. And carrying out slow disk identification on the hard disk according to the slow disk identification parameters.

According to the method provided by the embodiment of the disclosure, through statistical analysis of the response time of the hard disk, the delay influence of other software and hardware nodes on the I/O link is eliminated, the slow disk with high delay risk in the cluster can be found in time, the response time is shortened, and the storage and reading efficiency is improved. And the delayed response of the hard disk is statistically analyzed by adopting a statistical angle, the screened hard disk is the hard disk with abnormal performance for a long time, the misjudgment of accidental delay on the hard disk is reduced, the detection accuracy is improved, the rate of wrong disk replacement and the rate of secondary failure are reduced, and the labor cost and the material cost are saved.

In another embodiment of the present disclosure, determining an abnormal response frequency of a hard disk according to a response time and a power-on time of the hard disk includes:

acquiring response times of which the response time exceeds a first threshold from the response time of the hard disk;

and determining the ratio of the response times to the power-on time as the abnormal response frequency.

In another embodiment of the present disclosure, determining abnormal response frequency deviation data of a hard disk according to an abnormal response frequency and an average abnormal response frequency includes:

acquiring a first difference value between the abnormal response frequency and the average abnormal response frequency;

and determining the ratio of the first difference to the standard deviation of the abnormal response frequency as the abnormal response frequency deviation data of the hard disks, wherein the standard deviation of the abnormal response frequency is determined according to the abnormal response frequencies of the plurality of hard disks in the electronic equipment.

In another embodiment of the present disclosure, determining a slow disc identification parameter of a hard disc according to at least one of an abnormal response frequency or abnormal response frequency deviation data includes:

responding to the abnormal response frequency smaller than the average abnormal response frequency, and determining the slow disk identification parameter of the hard disk as a first numerical value;

and determining the maximum abnormal response deviation data in the electronic equipment in response to the abnormal response frequency being greater than the average abnormal response frequency, and determining the slow disk identification parameters of the hard disk according to the abnormal response frequency deviation data and the maximum abnormal response deviation data.

In another embodiment of the present disclosure, determining maximum abnormal response deviation data in an electronic device comprises:

acquiring the maximum abnormal response frequency from the abnormal response frequencies of a plurality of hard disks in the electronic equipment;

acquiring a second difference value between the maximum abnormal response frequency and the average abnormal response frequency;

and determining the ratio of the second difference to the standard deviation of the abnormal response frequency as the maximum abnormal response deviation data, wherein the standard deviation of the abnormal response frequency is determined according to the abnormal response frequencies of the plurality of hard disks in the electronic equipment.

In another embodiment of the present disclosure, the slow disk identification of the hard disk according to the slow disk identification parameter includes:

and identifying the hard disk as the slow disk in response to the slow disk identification parameter being larger than a second threshold value.

According to the slow disk identification parameters, the slow disk identification is carried out on the hard disk, and the method comprises the following steps:

determining a slow disk likelihood estimation parameter of the hard disk according to the slow disk identification parameter, wherein the slow disk likelihood estimation parameter is used for expressing the relation between the possibility that the hard disk is a slow disk and the possibility that the hard disk is a non-slow disk;

and carrying out slow disk identification on the hard disk according to the slow disk likelihood estimation parameters.

In another embodiment of the present disclosure, determining a slow disk likelihood estimation parameter of a hard disk according to a slow disk identification parameter includes:

in response to the slow disc identification parameter being a first value, determining that the slow disc likelihood estimation parameter is negative infinity;

in response to the slow disc identification parameter being a second value, determining that the slow disc likelihood estimation parameter is positive infinity;

responding to the fact that the slow disk identification parameters are larger than the first numerical value and smaller than the second numerical value, obtaining non-slow disk identification parameters of the hard disk, determining slow disk likelihood estimation parameters of the hard disk according to the slow disk identification parameters and the non-slow disk identification parameters, and determining the non-slow disk identification parameters according to the slow disk identification parameters;

wherein the first value is less than the second value.

In another embodiment of the present disclosure, the slow disk identification of the hard disk according to the slow disk likelihood estimation parameter includes:

and identifying the hard disk as the slow disk in response to the slow disk likelihood estimation parameter being larger than a third threshold value.

All the above optional technical solutions may be combined arbitrarily to form the optional embodiments of the present disclosure, and are not described herein again.

The embodiment of the present disclosure provides a slow disc identification method, which is implemented by an electronic device, for example, and with reference to fig. 3, a flow of the method provided by the embodiment of the present disclosure includes:

301. the electronic equipment acquires the response time of the hard disk.

During the operation of the electronic device, the electronic device stores various data generated during the operation process into the hard disk log, wherein the various data includes the response time of the hard disk, the response times of the hard disk, the operation type, the power-on time and the like. The power-on time refers to the time from power-on to stable operation of the electronic device, and the unit of the power-on time may be hours. The operation types include two types of read operation and write operation, namely the response time of the hard disk includes the response time of the read operation and also includes the response time of the write operation.

Optionally, in order to save the storage space and facilitate visual checking of the response condition of each hard disk, the electronic device may divide the response time into different intervals, map the I/O response time of each hard disk into different intervals according to the divided intervals, count the response times in each interval, and store the response time of the hard disk according to the divided intervals and the response times.

Referring to table 1, table 1 is a hard disk log structure of a hard disk.

TABLE 1

Based on the data stored in the hard disk log, the electronic device can read the response time of each hard disk from the hard disk log, and perform slow disk identification on each hard disk based on the response time of each hard disk.

302. And the electronic equipment determines the abnormal response frequency of the hard disk according to the response time and the power-on time of the hard disk.

The abnormal response frequency is the abnormal response frequency of the hard disk in unit time, the abnormal response frequency can reflect the performance of the hard disk, and the higher the abnormal response frequency is, the longer the response time of the hard disk is, and the worse the performance of the hard disk is; the lower the abnormal response frequency is, the shorter the response time of the hard disk is, and the better the performance of the hard disk is.

Based on the obtained response time, when the electronic device determines the abnormal response frequency of the hard disk according to the response time and the power-on time of the hard disk, the following method can be adopted:

3021. and the electronic equipment acquires the response times of which the response time exceeds a first threshold from the response time of the hard disk.

The first threshold may be obtained according to the response time statistics of the non-slow disc and the slow disc, and may be 128ms (millisecond), 265ms, and so on, and the size of the first threshold is not specifically limited in the embodiments of the present disclosure. Generally, the response time of the hard disk is smaller than a first threshold when the hard disk is normal, and the response time of the hard disk is larger than the first threshold when the hard disk is abnormal.

For any hard disk, the electronic equipment compares the response time of the hard disk every time with a first threshold, adds 1 to the times that the response time exceeds the first threshold when the response time of any time exceeds the first threshold, and takes the finally obtained times as the response times that the response time exceeds the first threshold after the response time of all times of the hard disk is compared with the first threshold.

Optionally, if the response time of the hard disk is stored according to the divided intervals, the first threshold may be a boundary point of the interval, and when the electronic device obtains the response times that the response time exceeds the first threshold, the electronic device may directly compare the first threshold with the boundary point of the interval, and use the sum of the corresponding response times in the interval in which the boundary point is greater than the first threshold as the response times that the response time exceeds the first threshold.

3022. And the electronic equipment determines the ratio of the response times to the power-on time as the abnormal response frequency.

And based on the response times of which the obtained response time exceeds the first threshold and the power-on time of the electronic equipment, the electronic equipment calculates the ratio of the response times to the power-on time to obtain the abnormal response frequency of the hard disk. Setting the response times of the response time exceeding the first threshold as Ct, and the power-on time as POH, and then setting the abnormal response frequency Ctavg as Ct/POH.

For example, referring to table 1 above, if the first threshold is set to 256ms, the number of times that the response time exceeds 256ms is 10 times, and the power-on time of the electronic device is 4879 hours, the abnormal response frequency of the hard disk is 10/4879 ═ 0.002.

303. And the electronic equipment determines the abnormal response frequency deviation data of the hard disk according to the abnormal response frequency and the average abnormal response frequency.

Here, the abnormal response frequency deviation data is used to represent a difference between the abnormal response frequency of the hard disk and the average abnormal response frequency, and may be a Z-score or the like. The average abnormal response frequency is an average value of the abnormal response frequencies of the plurality of hard disks in the electronic device, and is used for reflecting the overall situation of the abnormal response frequencies of the hard disks in the cluster. The average abnormal response frequency may be obtained by obtaining abnormal response frequencies of a plurality of hard disks in the electronic device, and calculating an average value of the abnormal response frequencies of the plurality of hard disks, where the average value of the abnormal response frequencies may be represented by μ. For example, the electronic device includes 5 hard disks, and the abnormal response frequencies of the 5 hard disks are Ctavg1, Ctavg2, Ctavg3, Ctavg4, and Ctavg5, respectively, and then the average abnormal response frequency of the electronic device is ═ by (Ctavg1+ Ctavg2+ Ctavg3+ Ctavg4+ Ctavg 5)/5.

When the electronic device determines the abnormal response frequency deviation data of the hard disk according to the abnormal response frequency and the average abnormal response frequency, the following method may be adopted:

3031. the electronic device obtains a first difference between the anomalous response frequency and the average anomalous response frequency.

3032. The electronic equipment determines the ratio of the first difference value to the standard deviation of the abnormal response frequency as the abnormal response frequency deviation data of the hard disk

The standard deviation of abnormal response frequency is used for reflecting the difference of each hard disk in the electronic equipmentOften in response to the degree of frequency dispersion. When the standard deviation of the abnormal response frequency is obtained, the following method can be adopted: and calculating the square number of the difference value between the abnormal response frequency and the average abnormal response frequency of each hard disk to obtain the square number of the deviation from the average of the plurality of hard disks, and calculating the arithmetic square root of the square number of the deviation from the average of the plurality of hard disks to obtain the standard deviation of the abnormal response frequency. The frequency standard deviation of the anomalous response may be expressed as sigma,

wherein N is the number of hard disks in the electronic device, i represents any hard disk, and ctavg (i) represents the abnormal response frequency of any hard disk.

The electronic device may calculate the abnormal response frequency deviation data z (i) of the hard disk by applying the following formula according to the abnormal response frequency ctavg (i) of the hard disk, the average abnormal response frequency μ, and the standard deviation σ of the abnormal response frequency:

304. and the electronic equipment determines the slow disc identification parameters of the hard disc according to at least one item of the abnormal response frequency or the abnormal response frequency deviation data.

The slow disk identification parameter is used for representing the possibility that the hard disk is a slow disk, the slow disk identification parameter can be represented by rho, and the value range [0, 1] of the slow disk identification parameter is obtained.

When the electronic equipment determines the slow disc identification parameter of the hard disc according to at least one of the abnormal response frequency or the abnormal response frequency deviation data, the electronic equipment can determine according to the abnormal response frequency, the abnormal response frequency deviation data, and the abnormal response frequency deviation data.

Before the electronic device determines the slow disc identification parameter of the hard disc according to at least one of the abnormal response frequency or the abnormal response frequency deviation data, the abnormal response frequency of the hard disc may be compared with the average abnormal response frequency, and a subsequent determination process is performed based on the comparison result.

In one possible implementation, if the abnormal response frequency is less than the average abnormal response frequency, the electronic device determines the slow disc identification parameter of the hard disc to be a first value in response to the abnormal response frequency being less than the average abnormal response frequency. The first value is a value greater than or equal to 0 and less than or equal to 1, and the first value is 0 in the embodiment of the disclosure.

In another possible implementation manner, if the abnormal response frequency is greater than the average abnormal response frequency, in response to the abnormal response frequency being greater than the average abnormal response frequency, the electronic device determines maximum abnormal response deviation data in the electronic device, and determines the slow disc identification parameter of the hard disc according to the abnormal response frequency deviation data and the maximum abnormal response deviation data. Specifically, when determining the maximum abnormal response deviation data in the electronic device, the electronic device may obtain the maximum abnormal response frequency from the abnormal response frequencies of the plurality of hard disks in the electronic device, obtain a second difference between the maximum abnormal response frequency and the average abnormal response frequency, and determine a ratio of the second difference to the standard deviation of the abnormal response frequency as the maximum abnormal response deviation data.

The electronic device may determine the maximum abnormal response deviation data z (max) by applying the following formula according to the maximum abnormal response frequency ctavg (max), the average abnormal response frequency μ, and the standard deviation σ of the abnormal response frequency:

when the electronic equipment determines the slow disc identification parameter of the hard disc according to the abnormal response frequency deviation data and the maximum abnormal response deviation data, a third difference value between the abnormal response frequency deviation data and the average abnormal response frequency can be obtained, a fourth difference value between the maximum abnormal response deviation data and the average abnormal response frequency can be obtained, and the ratio of the third difference value to the fourth difference value is determined as the slow disc identification parameter of the hard disc. This calculation process can be expressed as:

wherein, combining the above two cases, the slow disc identification parameters are:

the slow disk identification parameter in the embodiment of the present disclosure is a soft decision value for identifying a slow disk, the closer the slow disk identification parameter is to 1, the higher the probability that a hard disk is a slow disk is, and the closer the slow disk identification parameter is to 0, the higher the probability that the hard disk is a non-slow disk is.

305. And the electronic equipment performs slow disk identification on the hard disk according to the slow disk identification parameters.

In an embodiment of the disclosure, based on the obtained slow disk identification parameter, the electronic device compares the slow disk identification parameter with a second threshold, and then performs slow disk identification on the hard disk according to a comparison result. In response to the slow disk identification parameter being larger than a second threshold, the electronic device determines that the hard disk is a slow disk; the electronic device determines that the hard disk is a non-slow disk in response to the slow disk identification parameter being less than a second threshold. The second threshold may be obtained by counting data of a large number of hard disks, and the first threshold may be 0.7, 0.8, and so on.

In another embodiment of the present disclosure, when the electronic device performs slow disk identification on the hard disk according to the slow disk identification parameter, the following method may also be adopted:

3051. and the electronic equipment determines the slow disk likelihood estimation parameters of the hard disk according to the slow disk identification parameters.

The slow disk likelihood estimation parameter is used for representing the relationship between the possibility that the hard disk is a slow disk and the possibility that the hard disk is a non-slow disk, and the relationship can be embodied by the estimation result of likelihood estimation of the hard disk. The slow disc likelihood estimation parameter may be expressed by LLR (Log Likely ratio).

When the electronic device determines the slow disk likelihood estimation parameter of the hard disk according to the slow disk identification parameter, the following situations are included, but not limited to:

in a first case, in response to the slow disc identification parameter being a first value, the electronics determine that the slow disc likelihood estimation parameter is negative infinity.

In the disclosed embodiment, the first value may be 0. When the slow disk identification parameter is 0, the probability that the hard disk is a slow disk is 0, the probability that the hard disk is a non-slow disk is 1, and at this time, the electronic device can determine that the slow disk likelihood estimation parameter of the hard disk is negative infinity.

In a second case, in response to the slow disc identification parameter being a second value, the electronic device determines that the slow disc likelihood estimation parameter is positive infinity.

In the disclosed embodiments, the second value may be 1. When the slow disk identification parameter is 1, the probability that the hard disk is a slow disk is 1, the probability that the hard disk is a non-slow disk is 0, and at this time, the electronic device can determine that the slow disk likelihood estimation parameter of the hard disk is positive infinity.

And in the third situation, in response to the fact that the slow disk identification parameter is larger than the first numerical value and smaller than the second numerical value, the electronic equipment acquires the non-slow disk identification parameter of the hard disk, and determines the slow disk likelihood estimation parameter of the hard disk according to the slow disk identification parameter and the non-slow disk identification parameter.

Because the event that the hard disk is a slow disk or a non-slow disk is a mutual exclusion event, when the hardware is a slow disk, the probability that the hard disk is a non-slow disk is 0; when the hard disk is a non-slow disk, the probability that the hard disk is a slow disk is 0, therefore, when the slow disk identification parameters of the hard disk are determined by adopting the steps, the electronic equipment can determine that the non-slow disk identification parameters of the hard disk are 1-slow disk identification parameters, namely the non-slow disk identification parameters are 1-rho according to the mutual exclusivity of events.

Based on the obtained non-slow disc identification parameters, the electronic equipment can calculate the ratio of the slow disc identification parameters to the non-slow disc identification parameters and calculate the logarithm of the ratio, so as to obtain the slow disc likelihood estimation parameters. The calculation process of the parameter values of the slow disc likelihood estimation parameters comprises the following steps:

the embodiment of the disclosure performs log-likelihood ratio LLR on rho, realizes quantitative guess of soft decision rho of a sampled hard disk as a slow disk, obtains inverse mapping of a hard decision, and can accurately identify the slow disk.

3052. And the electronic equipment identifies the slow disk for the hard disk according to the slow disk likelihood estimation parameters.

In response to the value of the slow disk likelihood estimation parameter being greater than the third threshold, the electronic device identifies the hard disk as a slow disk. The third threshold may be obtained by counting data of a large number of hard disks, and the third threshold may be 2, 3, 5, and so on.

Further, when the hard disk is identified as a slow disk, the electronic device sends an alarm prompt message to the user to alarm the user, so that the user can replace the hard disk in time, and the service can be ensured to be smoothly performed.

Fig. 4 is a distribution diagram of slow disk likelihood estimation parameters in an electronic device, where a positive slow disk likelihood estimation parameter represents between slow disks, a negative slow disk likelihood estimation parameter represents between non-slow disks, an amplitude of the slow disk likelihood estimation parameter represents reliability, the higher the amplitude is, the higher the reliability is, the lower the amplitude is, the lower the reliability is, for example, the amplitude is infinity, it can be determined that a hard disk is a slow disk or a non-slow disk, and when the amplitude is 0, the probability that the hard disk is a slow disk or a non-slow disk is 0.5, and it is difficult to accurately determine whether the hard disk is a slow disk or a non-slow disk. According to the distribution characteristics of hardware in the electronic equipment, the third threshold value is defined, and hard decision inverse mapping can be carried out on the slow disk likelihood estimation parameters, namely, the hard disk with the slow disk likelihood estimation parameters exceeding the third threshold value can be identified as a slow disk, so that the slow disk likelihood estimation parameters can be identified and screened in advance.

It should be noted that, for example, the identification of one hard disk is performed, and for the identification process of other hard disks, reference may be made to the identification process, which is not described herein again. In addition, operation and maintenance personnel can carry out risk grade division on the second threshold and the third threshold of the hard disk according to the sensitivity requirement of the service on the performance, and for the service with less sensitive service performance, the early warning threshold can be properly reduced, spare part storage and labor expenditure are reduced, and the cost is saved; for the service with sensitive service performance, the second threshold and the third threshold can be properly improved, so that the performance slow disk can be replaced in advance, and the service performance and the service quality of the whole system are improved.

For the above-mentioned slow disc recognition process, the following description will be made by taking fig. 5 as an example.

Referring to fig. 5, for any hard disk, the response times that the response time of the hard disk exceeds the first threshold are obtained, and based on the response times, the ratio of the response times to the power-on time is determined as the abnormal response frequency of the hard disk. Based on the abnormal response frequency, calculating the average abnormal response frequency in the cluster and the standard deviation of the abnormal response frequency to obtain the abnormal response deviation data of the hard disk, further determining the slow disk identification parameter according to the abnormal response deviation data, and further determining the slow disk likelihood estimation parameter LLR based on the slow disk identification parameter. If the LLR is larger than a third threshold value, the hard disk is identified as a slow disk, and then a slow disk alarm is carried out on the hard disk, and if the LLR is smaller than the third threshold value, a next hard disk is polled to detect the next hard disk.

Referring to fig. 6, an embodiment of the present disclosure provides a slow disc recognition apparatus, including:

a first determining module 601, configured to determine an abnormal response frequency of the hard disk according to response time and power-on time of the hard disk;

a second determining module 602, configured to determine abnormal response frequency deviation data of the hard disks according to the abnormal response frequency and an average abnormal response frequency, where the average abnormal response frequency is determined according to abnormal response frequencies of a plurality of hard disks in the electronic device, and the abnormal response frequency deviation data is used to represent a difference between the abnormal response frequency and the average abnormal response frequency;

a third determining module 603, configured to determine a slow disc identification parameter of the hard disc according to at least one of the abnormal response frequency or the abnormal response frequency deviation data, where the slow disc identification parameter is used to indicate a possibility that the hard disc is a slow disc;

and the identifying module 604 is configured to perform slow disk identification on the hard disk according to the slow disk identification parameter.

In another embodiment of the present disclosure, the first determining module 601 is configured to, in the response time of the hard disk, obtain the number of times of responses that the response time exceeds a first threshold; and determining the ratio of the response times to the power-on time as the abnormal response frequency.

In another embodiment of the present disclosure, the second determining module 602 is configured to obtain a first difference between the abnormal response frequency and the average abnormal response frequency; and determining the ratio of the first difference to the standard deviation of the abnormal response frequency as the abnormal response frequency deviation data of the hard disks, wherein the standard deviation of the abnormal response frequency is determined according to the abnormal response frequencies of the plurality of hard disks in the electronic equipment.

In another embodiment of the present disclosure, the third determining module 603 is configured to determine the slow disc identification parameter of the hard disc as the first value in response to the abnormal response frequency being less than the average abnormal response frequency;

In another embodiment of the present disclosure, the third determining module 603 is configured to obtain a maximum abnormal response frequency from abnormal response frequencies of a plurality of hard disks in the electronic device; acquiring a second difference value between the maximum abnormal response frequency and the average abnormal response frequency; and determining the ratio of the second difference to the standard deviation of the abnormal response frequency as the maximum abnormal response deviation data, wherein the standard deviation of the abnormal response frequency is determined according to the abnormal response frequencies of the plurality of hard disks in the electronic equipment.

In another embodiment of the present disclosure, the identifying module 604 is configured to identify the hard disk as a slow disk in response to the slow disk identification parameter being greater than a second threshold.

In another embodiment of the present disclosure, the identifying module 604 is configured to determine a slow disc likelihood estimation parameter of the hard disc according to the slow disc identification parameter, where the slow disc likelihood estimation parameter is used to represent a relationship between a possibility that the hard disc is a slow disc and a possibility that the hard disc is a non-slow disc; and carrying out slow disk identification on the hard disk according to the slow disk likelihood estimation parameters.

In another embodiment of the present disclosure, the identifying module 604 is configured to determine that the slow disc likelihood estimation parameter is negative infinity in response to the slow disc identification parameter being the first value; in response to the slow disc identification parameter being a second value, determining that the slow disc likelihood estimation parameter is positive infinity; responding to the fact that the slow disk identification parameters are larger than the first numerical value and smaller than the second numerical value, obtaining non-slow disk identification parameters of the hard disk, determining slow disk likelihood estimation parameters of the hard disk according to the slow disk identification parameters and the non-slow disk identification parameters, and determining the non-slow disk identification parameters according to the slow disk identification parameters; wherein the first value is less than the second value.

In another embodiment of the present disclosure, the identifying module 604 is configured to identify the hard disk as a slow disk in response to the slow disk likelihood estimation parameter being greater than a third threshold.

In summary, the device provided in the embodiment of the present disclosure eliminates the delay influence of other software and hardware nodes on the I/O link by performing statistical analysis on the response time of the hard disk, and can find the slow disk with high delay risk in the cluster in time, shorten the response time, and improve the storage and reading efficiency. And the delayed response of the hard disk is statistically analyzed by adopting a statistical angle, the screened hard disk is the hard disk with abnormal performance for a long time, the misjudgment of accidental delay on the hard disk is reduced, the detection accuracy is improved, the rate of wrong disk replacement and the rate of secondary failure are reduced, and the labor cost and the material cost are saved.

When the electronic device executing the embodiment of the present disclosure is a terminal, referring to fig. 7, fig. 7 shows a block diagram of a terminal 700 provided in an exemplary embodiment of the present disclosure. The terminal 700 may be: a smart phone, a tablet computer, an MP3 player (Moving Picture Experts Group Audio Layer III, motion video Experts compression standard Audio Layer 3), an MP4 player (Moving Picture Experts Group Audio Layer IV, motion video Experts compression standard Audio Layer 4), a notebook computer, or a desktop computer. Terminal 700 may also be referred to by other names such as user equipment, portable terminal, laptop terminal, desktop terminal, and so on.

In general, terminal 700 includes: a processor 701 and a memory 702.

The processor 701 may include one or more processing cores, such as a 4-core processor, an 8-core processor, and so on. The processor 701 may be implemented in at least one hardware form of a DSP (Digital Signal Processing), an FPGA (Field-Programmable Gate Array), and a PLA (Programmable Logic Array). The processor 701 may also include a main processor and a coprocessor, where the main processor is a processor for Processing data in an awake state, and is also called a Central Processing Unit (CPU); a coprocessor is a low power processor for processing data in a standby state. In some embodiments, the processor 701 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content required to be displayed on the display screen. In some embodiments, the processor 701 may further include an AI (Artificial Intelligence) processor for processing computing operations related to machine learning.

Memory 702 may include one or more computer-readable storage media, which may be non-transitory. Memory 702 may also include high-speed random access memory, as well as non-volatile memory, such as one or more magnetic disk storage devices, flash memory storage devices. In some embodiments, a non-transitory computer readable storage medium in memory 702 is used to store at least one instruction for execution by processor 701 to implement the slow disc recognition method provided by method embodiments herein.

In some embodiments, the terminal 700 may further optionally include: a peripheral interface 703 and at least one peripheral. The processor 701, the memory 702, and the peripheral interface 703 may be connected by buses or signal lines. Various peripheral devices may be connected to peripheral interface 703 via a bus, signal line, or circuit board. Specifically, the peripheral device includes: at least one of a radio frequency circuit 704, a display screen 705, a camera assembly 706, an audio circuit 707, a positioning component 708, and a power source 709.

The peripheral interface 703 may be used to connect at least one peripheral related to I/O (Input/Output) to the processor 701 and the memory 702. In some embodiments, processor 701, memory 702, and peripheral interface 703 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 701, the memory 702, and the peripheral interface 703 may be implemented on a separate chip or circuit board, which is not limited in this embodiment.

The Radio Frequency circuit 704 is used for receiving and transmitting RF (Radio Frequency) signals, also called electromagnetic signals. The radio frequency circuitry 704 communicates with communication networks and other communication devices via electromagnetic signals. The rf circuit 704 converts an electrical signal into an electromagnetic signal to transmit, or converts a received electromagnetic signal into an electrical signal. Optionally, the radio frequency circuit 704 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a subscriber identity module card, and so forth. The radio frequency circuitry 704 may communicate with other terminals via at least one wireless communication protocol. The wireless communication protocols include, but are not limited to: metropolitan area networks, various generation mobile communication networks (2G, 3G, 4G, and 5G), Wireless local area networks, and/or WiFi (Wireless Fidelity) networks. In some embodiments, the radio frequency circuit 704 may also include NFC (Near Field Communication) related circuits, which are not limited in this application.

The display screen 705 is used to display a UI (User Interface). The UI may include graphics, text, icons, video, and any combination thereof. When the display screen 705 is a touch display screen, the display screen 705 also has the ability to capture touch signals on or over the surface of the display screen 705. The touch signal may be input to the processor 701 as a control signal for processing. At this point, the display 705 may also be used to provide virtual buttons and/or a virtual keyboard, also referred to as soft buttons and/or a soft keyboard. In some embodiments, the display 705 may be one, providing the front panel of the terminal 700; in other embodiments, the display 705 can be at least two, respectively disposed on different surfaces of the terminal 700 or in a folded design; in still other embodiments, the display 705 may be a flexible display disposed on a curved surface or on a folded surface of the terminal 700. Even more, the display 705 may be arranged in a non-rectangular irregular pattern, i.e. a shaped screen. The Display 705 may be made of LCD (Liquid Crystal Display), OLED (Organic Light-Emitting Diode), or the like.

The camera assembly 706 is used to capture images or video. Optionally, camera assembly 706 includes a front camera and a rear camera. Generally, a front camera is disposed at a front panel of the terminal, and a rear camera is disposed at a rear surface of the terminal. In some embodiments, the number of the rear cameras is at least two, and each rear camera is any one of a main camera, a depth-of-field camera, a wide-angle camera and a telephoto camera, so that the main camera and the depth-of-field camera are fused to realize a background blurring function, and the main camera and the wide-angle camera are fused to realize panoramic shooting and VR (Virtual Reality) shooting functions or other fusion shooting functions. In some embodiments, camera assembly 706 may also include a flash. The flash lamp can be a monochrome temperature flash lamp or a bicolor temperature flash lamp. The double-color-temperature flash lamp is a combination of a warm-light flash lamp and a cold-light flash lamp, and can be used for light compensation at different color temperatures.

The audio circuitry 707 may include a microphone and a speaker. The microphone is used for collecting sound waves of a user and the environment, converting the sound waves into electric signals, and inputting the electric signals to the processor 701 for processing or inputting the electric signals to the radio frequency circuit 704 to realize voice communication. For the purpose of stereo sound collection or noise reduction, a plurality of microphones may be provided at different portions of the terminal 700. The microphone may also be an array microphone or an omni-directional pick-up microphone. The speaker is used to convert electrical signals from the processor 701 or the radio frequency circuit 704 into sound waves. The loudspeaker can be a traditional film loudspeaker or a piezoelectric ceramic loudspeaker. When the speaker is a piezoelectric ceramic speaker, the speaker can be used for purposes such as converting an electric signal into a sound wave audible to a human being, or converting an electric signal into a sound wave inaudible to a human being to measure a distance. In some embodiments, the audio circuitry 707 may also include a headphone jack.

The positioning component 708 is used to locate the current geographic Location of the terminal 700 for navigation or LBS (Location Based Service). The Positioning component 708 can be a Positioning component based on the GPS (Global Positioning System) in the united states, the beidou System in china, the graves System in russia, or the galileo System in the european union.

Power supply 709 is provided to supply power to various components of terminal 700. The power source 709 may be alternating current, direct current, disposable batteries, or rechargeable batteries. When power source 709 includes a rechargeable battery, the rechargeable battery may support wired or wireless charging. The rechargeable battery may also be used to support fast charge technology.

In some embodiments, terminal 700 also includes one or more sensors 710. The one or more sensors 710 include, but are not limited to: acceleration sensor 711, gyro sensor 712, pressure sensor 713, fingerprint sensor 714, optical sensor 715, and proximity sensor 716.

The acceleration sensor 711 can detect the magnitude of acceleration in three coordinate axes of a coordinate system established with the terminal 700. For example, the acceleration sensor 711 may be used to detect components of the gravitational acceleration in three coordinate axes. The processor 701 may control the display screen 705 to display the user interface in a landscape view or a portrait view according to the gravitational acceleration signal collected by the acceleration sensor 711. The acceleration sensor 711 may also be used for acquisition of motion data of a game or a user.

The gyro sensor 712 may detect a body direction and a rotation angle of the terminal 700, and the gyro sensor 712 may cooperate with the acceleration sensor 711 to acquire a 3D motion of the terminal 700 by the user. From the data collected by the gyro sensor 712, the processor 701 may implement the following functions: motion sensing (such as changing the UI according to a user's tilting operation), image stabilization at the time of photographing, game control, and inertial navigation.

Pressure sensors 713 may be disposed on a side frame of terminal 700 and/or underneath display 705. When the pressure sensor 713 is disposed on a side frame of the terminal 700, a user's grip signal on the terminal 700 may be detected, and the processor 701 performs right-left hand recognition or shortcut operation according to the grip signal collected by the pressure sensor 713. When the pressure sensor 713 is disposed at a lower layer of the display screen 705, the processor 701 controls the operability control on the UI interface according to the pressure operation of the user on the display screen 705. The operability control comprises at least one of a button control, a scroll bar control, an icon control and a menu control.

The fingerprint sensor 714 is used for collecting a fingerprint of a user, and the processor 701 identifies the identity of the user according to the fingerprint collected by the fingerprint sensor 714, or the fingerprint sensor 714 identifies the identity of the user according to the collected fingerprint. When the user identity is identified as a trusted identity, the processor 701 authorizes the user to perform relevant sensitive operations, including unlocking a screen, viewing encrypted information, downloading software, paying, changing settings, and the like. The fingerprint sensor 714 may be disposed on the front, back, or side of the terminal 700. When a physical button or a vendor Logo is provided on the terminal 700, the fingerprint sensor 714 may be integrated with the physical button or the vendor Logo.

The optical sensor 715 is used to collect the ambient light intensity. In one embodiment, the processor 701 may control the display brightness of the display screen 705 based on the ambient light intensity collected by the optical sensor 715. Specifically, when the ambient light intensity is high, the display brightness of the display screen 705 is increased; when the ambient light intensity is low, the display brightness of the display screen 705 is adjusted down. In another embodiment, processor 701 may also dynamically adjust the shooting parameters of camera assembly 706 based on the ambient light intensity collected by optical sensor 715.

A proximity sensor 716, also referred to as a distance sensor, is typically disposed on a front panel of the terminal 700. The proximity sensor 716 is used to collect the distance between the user and the front surface of the terminal 700. In one embodiment, when the proximity sensor 716 detects that the distance between the user and the front surface of the terminal 700 gradually decreases, the processor 701 controls the display 705 to switch from the bright screen state to the dark screen state; when the proximity sensor 716 detects that the distance between the user and the front surface of the terminal 700 is gradually increased, the processor 701 controls the display 705 to switch from the breath-screen state to the bright-screen state.

Those skilled in the art will appreciate that the configuration shown in fig. 7 is not intended to be limiting of terminal 700 and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components may be used.

According to the terminal provided by the embodiment of the disclosure, through statistical analysis of the response time of the hard disk, the delay influence of other software and hardware nodes on the I/O link is eliminated, the slow disk with high delay risk in the cluster can be found in time, the response time is shortened, and the storage and reading efficiency is improved. And the delayed response of the hard disk is statistically analyzed by adopting a statistical angle, the screened hard disk is the hard disk with abnormal performance for a long time, the misjudgment of accidental delay on the hard disk is reduced, the detection accuracy is improved, the rate of wrong disk replacement and the rate of secondary failure are reduced, and the labor cost and the material cost are saved.

When the electronic device executing the embodiment of the present disclosure is a server, referring to fig. 8, fig. 8 is a server for slow disc recognition according to an exemplary embodiment. The server 800 includes a processing component 822 further including one or more processors and memory resources, represented by memory 832, for storing instructions, such as application programs, that are executable by the processing component 822. The application programs stored in memory 832 may include one or more modules that each correspond to a set of instructions. Further, the processing component 822 is configured to execute instructions to perform the functions performed by the server in the slow disk detection method described above.

The server 800 may also include a power component 826 configured to perform power management of the server 800, a wired or wireless network interface 850 configured to connect the server 800 to a network, and an input/output (I/O) interface 858. The Server 800 may operate based on an operating system, such as Windows Server, stored in the memory 832^TM，Mac OS X^TM，Unix^TM,Linux^TM，FreeBSD^TMOr the like.

According to the server provided by the embodiment of the disclosure, through statistical analysis of the response time of the hard disk, the delay influence of other software and hardware nodes on the I/O link is eliminated, the slow disk with high delay risk in the cluster can be found in time, the response time is shortened, and the storage and reading efficiency is improved. And the delayed response of the hard disk is statistically analyzed by adopting a statistical angle, the screened hard disk is the hard disk with abnormal performance for a long time, the misjudgment of accidental delay on the hard disk is reduced, the detection accuracy is improved, the rate of wrong disk replacement and the rate of secondary failure are reduced, and the labor cost and the material cost are saved.

The disclosed embodiments provide a computer readable storage medium having at least one program code stored therein, the at least one program code being loaded and executed by a processor to implement the slow disc identification method shown in fig. 2 or fig. 3. The computer readable storage medium may be non-transitory. For example, the computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

According to the computer-readable storage medium provided by the embodiment of the disclosure, through statistical analysis of the response time of the hard disk, the delay influence of other software and hardware nodes on the I/O link is eliminated, a slow disk with high delay risk in a cluster can be found in time, the response time is shortened, and the storage and reading efficiency is improved. And the delayed response of the hard disk is statistically analyzed by adopting a statistical angle, the screened hard disk is the hard disk with abnormal performance for a long time, the misjudgment of accidental delay on the hard disk is reduced, the detection accuracy is improved, the rate of wrong disk replacement and the rate of secondary failure are reduced, and the labor cost and the material cost are saved.

The disclosed embodiments provide a computer program product or a computer program comprising computer instructions stored in a computer-readable storage medium, which are read by a processor of a computer device from the computer-readable storage medium, and which are executed by the processor to cause the computer device to perform the method provided in the various alternative implementations of slow disc recognition illustrated in fig. 2 or fig. 3.

According to the computer program product or the computer program provided by the embodiment of the disclosure, the response time of the hard disk is subjected to statistical analysis, the delay influence of other software and hardware nodes on the I/O link is eliminated, the slow disk with high delay risk in the cluster can be found in time, the response time is shortened, and the storage and reading efficiency is improved. And the delayed response of the hard disk is statistically analyzed by adopting a statistical angle, the screened hard disk is the hard disk with abnormal performance for a long time, the misjudgment of accidental delay on the hard disk is reduced, the detection accuracy is improved, the rate of wrong disk replacement and the rate of secondary failure are reduced, and the labor cost and the material cost are saved.

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 instructing relevant hardware, where the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.

The above description is intended to be exemplary only and not to limit the present disclosure, and any modification, equivalent replacement, or improvement made without departing from the spirit and scope of the present disclosure is to be considered as the same as the present disclosure.

Claims

1. A slow disc identification method, the method comprising:

2. The method of claim 1, wherein determining the abnormal response frequency of the hard disk according to the response time and the power-on time of the hard disk comprises:

3. The method of claim 1, wherein determining abnormal response frequency deviation data for the hard disk based on the abnormal response frequency and an average abnormal response frequency comprises:

acquiring a first difference between the abnormal response frequency and the average abnormal response frequency;

and determining the ratio of the first difference to an abnormal response frequency standard deviation as abnormal response frequency deviation data of the hard disks, wherein the abnormal response frequency standard deviation is determined according to abnormal response frequencies of a plurality of hard disks in the electronic equipment.

4. The method of claim 1, wherein determining a slow disk identification parameter of the hard disk based on at least one of the abnormal response frequency or the abnormal response frequency deviation data comprises:

responding to the abnormal response frequency smaller than the average abnormal response frequency, and determining a slow disk identification parameter of the hard disk as a first numerical value;

and determining maximum abnormal response deviation data in the electronic equipment in response to the abnormal response frequency being larger than the average abnormal response frequency, and determining a slow disc identification parameter of the hard disc according to the abnormal response frequency deviation data and the maximum abnormal response deviation data.

5. The method of claim 4, wherein determining maximum abnormal response deviation data in the electronic device comprises:

acquiring a second difference between the maximum abnormal response frequency and the average abnormal response frequency;

and determining the ratio of the second difference to an abnormal response frequency standard deviation as the maximum abnormal response deviation data, wherein the abnormal response frequency standard deviation is determined according to the abnormal response frequencies of a plurality of hard disks in the electronic equipment.

6. The method according to any one of claims 1 to 5, wherein the performing slow disk identification on the hard disk according to the slow disk identification parameter comprises:

and identifying the hard disk as a slow disk in response to the slow disk identification parameter being larger than a second threshold value.

7. The method according to any one of claims 1 to 5, wherein the performing slow disk identification on the hard disk according to the slow disk identification parameter comprises:

8. The method of claim 7, wherein determining the slow disk likelihood estimation parameter of the hard disk according to the slow disk identification parameter comprises:

responsive to the slow disc identification parameter being a second value, determining the slow disc likelihood estimation parameter to be positive infinity;

responding to the fact that the slow disk identification parameter is larger than the first numerical value and smaller than the second numerical value, obtaining a non-slow disk identification parameter of the hard disk, determining a slow disk likelihood estimation parameter of the hard disk according to the slow disk identification parameter and the non-slow disk identification parameter, and determining the non-slow disk identification parameter according to the slow disk identification parameter;

wherein the first value is less than the second value.

9. The method of claim 7, wherein the slow disk identification of the hard disk according to the slow disk likelihood estimation parameters comprises:

and identifying the hard disk as a slow disk in response to the slow disk likelihood estimation parameter being larger than a third threshold value.

10. A slow disc identification device, the device comprising:

11. The apparatus of claim 10, wherein the second determining module is configured to obtain a first difference between the abnormal response frequency and the average abnormal response frequency; and determining the ratio of the first difference to an abnormal response frequency standard deviation as abnormal response frequency deviation data of the hard disks, wherein the abnormal response frequency standard deviation is determined according to abnormal response frequencies of a plurality of hard disks in the electronic equipment.

12. The apparatus of claim 10, wherein the third determining module is configured to determine the slow disc identification parameter of the hard disc as a first value in response to the abnormal response frequency being less than the average abnormal response frequency; and determining maximum abnormal response deviation data in the electronic equipment in response to the abnormal response frequency being larger than the average abnormal response frequency, and determining a slow disc identification parameter of the hard disc according to the abnormal response frequency deviation data and the maximum abnormal response deviation data.

13. The apparatus according to any of claims 10 to 12, wherein the identifying module is configured to determine a slow disc likelihood estimation parameter of the hard disc according to the slow disc identification parameter, the slow disc likelihood estimation parameter being used to represent a relationship between a possibility that the hard disc is a slow disc and a possibility that the hard disc is a non-slow disc; and carrying out slow disk identification on the hard disk according to the slow disk likelihood estimation parameters.

14. An electronic device, comprising a processor and a memory, wherein at least one program code is stored in the memory, and wherein the at least one program code is loaded and executed by the processor to implement the slow disc recognition method according to any one of claims 1 to 9.

15. A computer-readable storage medium, having stored therein at least one program code, which is loaded and executed by a processor, to implement the slow disc identification method according to any one of claims 1 to 9.