Method, system and device for processing disk performance information and readable storage medium

Abstract

This application discloses a method, system, apparatus, and readable storage medium for processing disk performance information, relating to the field of disk testing and applied to analyzing disk performance. The processing method includes: monitoring and acquiring disk performance information; determining the mapping relationship between multiple performance data and multiple disk partitions in the performance information; generating a performance heatmap based on the mapping relationship, wherein the performance heatmap displays a partition performance map of the corresponding performance data at the location of each disk partition; and generating a disk performance report based on the performance heatmap. This application generates a performance heatmap after determining the mapping relationship. This performance heatmap, in the form of a two-dimensional partition map, intuitively and accurately reflects the performance status of each disk partition in the disk. Furthermore, generating a disk performance report based on this performance heatmap provides a more accurate, effective, and valuable performance analysis.

Description

Technical Field

[0001] This invention relates to the field of disk testing, and in particular to a method, system, apparatus, and readable storage medium for processing disk performance information. Background Technology

[0002] With the explosive growth of data volume and the expansion of data center scale, the demand for efficient disk performance analysis is increasing. Current methods for disk performance analysis typically involve tools outputting disk performance results as log text. While accurate, this method is complex and voluminous, suitable for analyzing a small number of disks, but inadequate for testing large numbers of disks.

[0003] Therefore, how to provide a solution to the above-mentioned technical problems is a problem that needs to be solved by those skilled in the art. Summary of the Invention

[0004] In view of this, the purpose of this invention is to provide a method, system, apparatus, and readable storage medium for processing disk performance information capable of rapid performance analysis. The specific solution is as follows:

[0005] A method for processing disk performance information includes:

[0006] Monitor and obtain disk performance information;

[0007] Determine the mapping relationship between multiple performance data and multiple disk partitions in the performance information;

[0008] Based on the mapping relationship, a performance heatmap is generated, which displays the partition performance map with the corresponding performance data at the location of each disk partition;

[0009] A disk performance report is generated based on the performance heatmap.

[0010] Preferably, after monitoring and acquiring the disk performance information, the method further includes:

[0011] Key strings are extracted from the performance information and sorted to determine multiple performance data.

[0012] Preferably, the performance data includes:

[0013] One or more of the following: IO time, bandwidth, IOPS, and queue depth.

[0014] Preferably, the process of generating a performance heatmap based on the mapping relationship further includes:

[0015] Based on the timestamps of the performance data and the mapping relationship, a process performance heatmap that changes over time is generated.

[0016] Preferably, after generating the process performance heatmap changing over time based on the timestamps of the performance data and the mapping relationship, the method further includes:

[0017] The cumulative performance heatmap of the process within the preset time period is generated.

[0018] Preferably, the process of generating a disk performance report based on the performance heatmap includes:

[0019] Determine whether the correlation between multiple performance data in the same disk partition in the performance heatmap of the same disk meets preset conditions;

[0020] If not, generate alarm information corresponding to the disk partition.

[0021] Preferably, the process of generating a disk performance report based on the performance heatmap includes:

[0022] Compare the performance heatmaps of multiple disks and generate a disk performance comparison report corresponding to the multiple disks.

[0023] Accordingly, this application also discloses a disk performance information processing system, including:

[0024] The information module is used to monitor and obtain disk performance information;

[0025] A mapping module is used to determine the mapping relationship between multiple performance data and multiple disk partitions in the performance information;

[0026] The heatmap module is used to generate a performance heatmap based on the mapping relationship. The performance heatmap displays a partition performance map with the corresponding performance data at the location of each disk partition.

[0027] The reporting module is used to generate a disk performance report based on the performance heatmap.

[0028] Accordingly, this application also discloses a disk performance information processing apparatus, comprising:

[0029] Memory, used to store computer programs;

[0030] A processor, configured to implement the steps of the disk performance information processing method as described in any of the preceding descriptions when executing the computer program.

[0031] Accordingly, this application also discloses a readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the disk performance information processing method described in any of the above claims.

[0032] This application discloses a method for processing disk performance information, including: monitoring and acquiring disk performance information; determining the mapping relationship between multiple performance data and multiple disk partitions in the performance information; generating a performance heatmap based on the mapping relationship, wherein the performance heatmap displays a partition performance map of the corresponding performance data at the location of each disk partition; and generating a disk performance report based on the performance heatmap. This application generates a performance heatmap after determining the mapping relationship. This performance heatmap, in the form of a two-dimensional partition map, intuitively and accurately reflects the performance status of each disk partition in the disk. Furthermore, generating a disk performance report based on this performance heatmap provides a more accurate, effective, and valuable performance analysis. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0034] Figure 1 This is a flowchart illustrating the steps of a disk performance information processing method according to an embodiment of the present invention.

[0035] Figure 2 This is a schematic diagram of the performance heatmap of a disk in an embodiment of the present invention;

[0036] Figure 3 This is a structural distribution diagram of a disk performance processing system according to an embodiment of the present invention;

[0037] Figure 4 This is a structural distribution diagram of a disk performance processing device according to an embodiment of the present invention. Detailed Implementation

[0038] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] With the explosive growth of data volume and the expansion of data center scale, the demand for efficient disk performance analysis is increasing. Current methods for disk performance analysis typically involve tools outputting disk performance results as log text. While accurate, this method is complex and voluminous, suitable for analyzing a small number of disks, but inadequate for testing large numbers of disks.

[0040] After determining the mapping relationship, this application generates a performance heatmap. This performance heatmap, in the form of a two-dimensional partition map, intuitively and accurately reflects the performance status of each disk partition in the disk. Furthermore, based on this performance heatmap, a disk performance report is generated, which can provide more accurate, effective, and valuable performance analysis.

[0041] This invention discloses a method for processing disk performance information, see [link to relevant documentation]. Figure 1 As shown, the processing method in this embodiment is generally applied to Linux platforms running disks and is implemented during disk operation. The processing method in this embodiment includes:

[0042] S1: Monitor and obtain disk performance information;

[0043] It is understandable that the disk performance information obtained directly through monitoring is in log text format, which contains a lot of relevant information, but also includes a lot of text content unrelated to actual performance, such as text formatting and identifiers. Therefore, in order to obtain clearer and more effective performance information, the obtained performance information can be preliminarily processed, categorized, filtered, and statistically analyzed. Specifically, after monitoring and obtaining the disk performance information, the process also includes:

[0044] Key strings are extracted from the performance information and sorted to determine multiple performance data.

[0045] Understandably, performance data in performance information includes one or more of the following: I / O time, bandwidth, IOPS, and queue depth. I / O (Input / Output) time is the time required for a single I / O operation; bandwidth refers to the data transfer capacity provided by the bus, which is related to the chips and modules in the disk and not purely determined by the bus design, thus it can be used as one of the performance indicators of disk partitioning; IOPS (Input / Output Operations Per Second) is the number of read / write operations per second, a metric used for performance testing of computer storage devices (such as HDDs, SSDs, or Storage Area Networks); and queue depth is related to the number of threads processing tasks.

[0046] S2: Determine the mapping relationship between multiple performance data and multiple disk partitions in the performance information;

[0047] It is understandable that a disk entity is divided into multiple disk partitions based on its location distribution. The disk operation process actually involves operating on different disk partitions, including read operations, and / or write operations, and / or erase operations. Based on these fundamental characteristics, disk performance data is actually performance data for each disk partition on the disk. The performance data of each disk partition is different. This step determines the mapping relationship between different disk partitions and their corresponding performance data from the performance information, which will serve as the basis for subsequent performance heatmap plotting.

[0048] S3: Generate a performance heatmap based on the mapping relationship. The performance heatmap displays the partition performance map with the corresponding performance data at the location of each disk partition.

[0049] As can be understood, a performance heatmap is created in a two-dimensional coordinate system by locating a point on the x-axis and y-axis using the position of a disk partition. Performance data for a specific aspect is then used as the value at that point. This process is repeated for all disk partitions to obtain a partition performance map showing how that performance data is represented across different partitions. Furthermore, disk performance data can be numerically labeled within the partition, colored using varying shades, or represented using the height of bars in a three-dimensional bar chart. The specific format is not limited here.

[0050] S4: Generate a disk performance report based on the performance heatmap.

[0051] Understandably, the performance heatmaps generated above can be further used to generate more readable and intuitive disk performance reports. These reports can include multiple performance heatmaps for different performance data on the same disk, such as performance heatmaps for IO time, bandwidth, IOPS, and queue depth. They can also include multiple performance heatmaps for the same performance data across multiple disks. For example, if the server has multiple disks C, D, and E connected, the performance heatmaps for the same performance data (IO time) could be: performance heatmap C1 for disk C, performance heatmap D1 for disk D, and performance heatmap E1 for disk E. It's also understood that the multiple disks being compared can be from the same series or different types, such as HDDs and SDDs, which can be compared side-by-side. Furthermore, performance heatmaps can be generated from the performance data of the same disk at different time periods for comparison. Based on these comparisons, further conclusions can be drawn, such as whether disk partitions have failed or differences in disk performance. Specific analysis content is not limited here.

[0052] This application discloses a method for processing disk performance information, including: monitoring and acquiring disk performance information; determining the mapping relationship between multiple performance data and multiple disk partitions in the performance information; generating a performance heatmap based on the mapping relationship, wherein the performance heatmap displays a partition performance map of the corresponding performance data at the location of each disk partition; and generating a disk performance report based on the performance heatmap. This application generates a performance heatmap after determining the mapping relationship. This performance heatmap, in the form of a two-dimensional partition map, intuitively and accurately reflects the performance status of each disk partition in the disk. Furthermore, generating a disk performance report based on this performance heatmap provides a more accurate, effective, and valuable performance analysis.

[0053] This invention discloses a specific method for processing disk performance information. Compared to the previous embodiment, this embodiment further explains and optimizes the technical solution. Specifically:

[0054] In the previous embodiment, step S3: Based on the mapping relationship, a performance heatmap is generated, wherein the performance heatmap displays the partition performance map with the corresponding performance data at the location of each disk partition.

[0055] Specifically, a performance heatmap is created in a two-dimensional coordinate system by locating a point on the x-axis and y-axis using the position of a disk partition. Performance data for a specific aspect is then used as the value at that point. This process is repeated for all disk partitions to obtain a partition performance map showing how that performance data is represented across different partitions. Furthermore, disk performance data can be numerically labeled within the partition, colored using varying shades, or represented using the height of bars in a three-dimensional bar chart. The specific format is not limited here.

[0056] Furthermore, considering the possibility of performance heatmap comparisons later, numerous performance data points can be proportionally calculated using standard values ​​to eliminate the need for units. The results of this proportional calculation can then be used as the plotting data for the performance heatmap. Performance heatmaps created in this way only focus on the degree of difference between disk partitions, not the actual performance values. It is important to note that the standard values ​​used for proportional calculations of performance data on the same performance heatmap must be the same. The standard values ​​corresponding to performance data of different metrics are not the same, but the standard values ​​for performance data of the same metric are usually the same. This approach greatly facilitates comparisons if subsequent comparisons of performance heatmaps for multiple disks with the same metric are required. For example, in the proportional calculation of IO time, a standard value n ms can be selected, and the actual IO time values ​​obtained in step S1 can be divided by n to obtain the quotient for plotting. Figure 2As shown, the square chart is a performance heatmap. The values ​​in its bottom and left borders correspond to the physical coordinates of the disk partitions on the disk. The shades of the color blocks in the square chart represent the size of the performance data. The relationship between the shades of the color blocks and the proportional values ​​of the performance data is shown in the bar chart, with the value in the right border being the proportional value.

[0057] Furthermore, this embodiment also adds performance heatmap plotting and performance display along the time dimension. Specifically, the process of generating a performance heatmap based on the mapping relationship further includes:

[0058] Based on the timestamps of the performance data and the mapping relationship, a process performance heatmap that changes over time is generated.

[0059] It is understandable that step S1 detects and obtains disk performance information in the form of sampling periods. For the same disk with the same performance data of the same index, the performance data of one sampling period can make a complete performance heatmap. By arranging the performance heatmaps of multiple sampling periods according to the time axis, a process performance heatmap can be obtained. This process performance heatmap can be presented in the form of animation or video, thereby showing the process of changes of each disk partition on the disk over time.

[0060] Furthermore, this embodiment also adds the impact of time accumulation on disk partitioning. Specifically, after generating a process performance heatmap that changes over time based on the timestamps of the performance data and the mapping relationship, it also includes:

[0061] The cumulative performance heatmap of the process within the preset time period is generated.

[0062] It is understandable that the action of obtaining the type performance heatmap from the cumulative process performance heatmap can be a simple addition accumulation operation or a weighted addition operation with the less important operations first and the more important operations last. There are no specific restrictions on the accumulation action here.

[0063] In addition to accumulating the process performance heatmaps to obtain a cumulative performance heatmap, the average, mean difference, standard deviation, variance, and range of the process performance heatmaps within a predicted time period can also be calculated to obtain a performance heatmap that can characterize the performance changes of the disk partitions within the cumulative time period. There are no restrictions on the processing method for the process performance heatmaps within the preset time period.

[0064] This invention discloses a specific method for processing disk performance information. Compared to the previous embodiment, this embodiment further explains and optimizes the technical solution. Specifically:

[0065] In the previous embodiment, step S4: Generate a disk performance report based on the performance heatmap.

[0066] Understandably, the performance heatmaps generated above can be further used to generate more readable and intuitive disk performance reports. These reports can include multiple performance heatmaps for different performance data on the same disk, such as performance heatmaps for IO time, bandwidth, IOPS, and queue depth. They can also include multiple performance heatmaps for the same performance data across multiple disks. For example, if the server has multiple disks C, D, and E connected, the performance heatmaps for the same performance data (IO time) could be: performance heatmap C1 for disk C, performance heatmap D1 for disk D, and performance heatmap E1 for disk E. It's also understood that the multiple disks being compared can be from the same series or different types, such as HDDs and SDDs, which can be compared side-by-side. Furthermore, performance heatmaps can be generated from the performance data of the same disk at different time periods for comparison. Based on these comparisons, further conclusions can be drawn, such as whether disk partitions have failed or differences in disk performance. Specific analysis content is not limited here.

[0067] Therefore, the process of generating a disk performance report based on the performance heatmap in step S4 includes:

[0068] Compare the performance heatmaps of multiple disks and generate a disk performance comparison report corresponding to the multiple disks.

[0069] The disks being compared here can be from the same series or different types; for example, HDDs and SSDs can be compared side-by-side. HDDs (Hard Disk Drives, also known as Winchester hard drives) are non-volatile storage devices based on rigid rotating platters. As the primary storage device in computers or servers, they consist of components such as read / write heads, platters, motors, and control chips. They use semi-random access, allowing data to be read in any order, but the read speed may vary depending on the location of the data. SSDs (Solid State Disks) are computer storage devices that primarily use NAND flash memory as permanent storage. SSDs consist of a control unit and storage units (FLASH chips, DRAM chips) and are widely used in industrial control, video surveillance, network monitoring, network terminals, navigation equipment, and many other fields. Compared to hard disk drives (HDDs), SSDs have higher read / write speeds, but are also more expensive. The new generation of solid-state drives adopts SATA-III interface[1], PCIe x8 or mSATA, M.2, ZIF, IDE, U.2, CF, CFast and other interfaces.

[0070] Furthermore, in addition to generating disk performance reports by comparing performance heatmaps of different disks, the correlation between different performance heatmaps of different performance metrics corresponding to the same disk can be used to determine whether each disk partition is functioning normally. It is understood that the performance metrics in this embodiment include IO time, bandwidth, IOPS, and queue depth. These performance metrics are interrelated and correlated. For a normally functioning disk partition, knowing the performance data of one performance metric allows us to derive the performance data of other related performance metrics based on their theoretical correlation with other performance metrics. If the actual performance data of these performance metrics for a certain disk partition does not match the predicted values, then this disk partition may have a fault, and the user should be alerted to check. Therefore, the process of generating a disk performance report based on the performance heatmap includes:

[0071] Determine whether the correlation between multiple performance data in the same disk partition in the performance heatmap of the same disk meets preset conditions;

[0072] If not, generate alarm information corresponding to the disk partition.

[0073] Accordingly, embodiments of this application also disclose a disk performance information processing system, see [link to relevant documentation]. Figure 3 As shown, the processing system in this embodiment is generally applied to a Linux platform running a disk and operates during disk operation. The processing system in this embodiment includes:

[0074] Information module 1 is used to monitor and obtain disk performance information;

[0075] Mapping module 2 is used to determine the mapping relationship between multiple performance data and multiple disk partitions in the performance information;

[0076] Heatmap module 3 is used to generate a performance heatmap based on the mapping relationship. The performance heatmap displays a partition performance map with the corresponding performance data at the location of each disk partition.

[0077] Reporting module 4 is used to generate a disk performance report based on the performance heatmap.

[0078] This application embodiment generates a performance heatmap after determining the mapping relationship. The performance heatmap is in the form of a two-dimensional partition map, which intuitively and accurately reflects the performance status of each disk partition in the disk. Furthermore, a disk performance report is generated based on the performance heatmap, which can provide more accurate, effective and higher performance analysis.

[0079] It is understandable that the disk performance information obtained directly through monitoring is in log text format, which contains a lot of relevant information, but also includes a lot of text content unrelated to actual performance, such as text formatting and identifiers. Therefore, in order to obtain clearer and more effective performance information, the obtained performance information can be preliminarily processed, classified, filtered, and statistically analyzed. In some specific embodiments, after monitoring and obtaining the disk performance information, information module 1 also includes:

[0080] Key strings are extracted from the performance information and sorted to determine multiple performance data.

[0081] In some specific embodiments, the performance data includes:

[0082] One or more of the following: IO time, bandwidth, IOPS, and queue depth.

[0083] It is understandable that when detecting and acquiring disk performance information, sampling periods are used. For performance data of the same disk with uniform metrics, the performance data of one sampling period can generate a complete performance heatmap. Arranging the performance heatmaps of multiple sampling periods according to the time axis yields a process performance heatmap. This process performance heatmap can be presented in the form of an animation or video, thereby showing the process of changes in each disk partition over time. In some specific embodiments, the process of heatmap module 3 generating a performance heatmap according to the mapping relationship also includes:

[0084] Based on the timestamps of the performance data and the mapping relationship, a process performance heatmap that changes over time is generated.

[0085] Furthermore, this embodiment also adds the impact of time accumulation on disk partitions. In some specific embodiments, after the heatmap module 3 generates a process performance heatmap that changes over time based on the timestamps of the performance data and the mapping relationship, it further includes:

[0086] The cumulative performance heatmap of the process within the preset time period is generated.

[0087] In addition to accumulating the process performance heatmaps to obtain a cumulative performance heatmap, the average, mean difference, standard deviation, variance, and range of the process performance heatmaps within a predicted time period can also be calculated to obtain a performance heatmap that can characterize the performance changes of the disk partitions within the cumulative time period. There are no restrictions on the processing method for the process performance heatmaps within the preset time period.

[0088] Understandably, performance heatmaps can further generate more readable and intuitive disk performance reports. These reports can include multiple performance heatmaps for different performance data on the same disk, such as performance heatmaps for IO time, bandwidth, IOPS, and queue depth. They can also include multiple performance heatmaps for the same performance data across multiple disks. For example, if a server has multiple disks C, D, and E connected, the performance heatmaps for the same performance data (IO time) could be: performance heatmap C1 for disk C, performance heatmap D1 for disk D, and performance heatmap E1 for disk E. It's also understood that the multiple disks being compared can be from the same series or different types, such as HDDs and SDDs, which can be compared side-by-side. Furthermore, performance heatmaps can be generated from the performance data of the same disk at different time periods for comparison. Based on these comparisons, further conclusions can be drawn, such as whether disk partitions have failed or differences in disk performance. The specific content of the analysis is not limited here.

[0089] In some specific embodiments, the process by which the reporting module 4 generates a disk performance report based on the performance heatmap includes:

[0090] Determine whether the correlation between multiple performance data in the same disk partition in the performance heatmap of the same disk meets preset conditions;

[0091] If not, generate alarm information corresponding to the disk partition.

[0092] Furthermore, in addition to generating disk performance reports by comparing performance heatmaps of different disks, the correlation between different performance heatmaps of different performance metrics corresponding to the same disk can also be used to determine whether each disk partition is functioning normally. It is understood that the performance metrics in this embodiment include IO time, bandwidth, IOPS, and queue depth. These performance metrics are interrelated and correlated. For a normally functioning disk partition, knowing the performance data of one performance metric allows us to derive the performance data of other related performance metrics based on their theoretical correlation with other performance metrics. If the actual performance data of these performance metrics for a certain disk partition does not match the predicted values, then this disk partition may have a fault, and the user should be alerted to check. In some specific embodiments, the process by which the reporting module 4 generates a disk performance report based on the performance heatmap includes:

[0093] Compare the performance heatmaps of multiple disks and generate a disk performance comparison report corresponding to the multiple disks.

[0094] This application also discloses a disk performance information processing apparatus, see [link to relevant documentation]. Figure 4 As shown, the processing device of this embodiment is generally applied to a Linux platform running a disk and operates during disk operation. The processing device of this embodiment includes a processor 11 and a memory 12; wherein, when the processor 11 executes the computer program stored in the memory 12, it performs the following steps:

[0095] Monitor and obtain disk performance information;

[0096] Determine the mapping relationship between multiple performance data and multiple disk partitions in the performance information;

[0097] Based on the mapping relationship, a performance heatmap is generated, which displays the partition performance map with the corresponding performance data at the location of each disk partition;

[0098] A disk performance report is generated based on the performance heatmap.

[0099] This application embodiment generates a performance heatmap after determining the mapping relationship. The performance heatmap is in the form of a two-dimensional partition map, which intuitively and accurately reflects the performance status of each disk partition in the disk. Furthermore, a disk performance report is generated based on the performance heatmap, which can provide more accurate, effective and higher performance analysis.

[0100] In some specific embodiments, when the processor 11 executes the computer subroutine stored in the memory 12, it may specifically implement the following steps:

[0101] Key strings are extracted from the performance information and sorted to determine multiple performance data.

[0102] In some specific embodiments, the performance data includes:

[0103] One or more of the following: IO time, bandwidth, IOPS, and queue depth.

[0104] In some specific embodiments, when the processor 11 executes the computer subroutine stored in the memory 12, it may specifically implement the following steps:

[0105] Based on the timestamps of the performance data and the mapping relationship, a process performance heatmap that changes over time is generated.

[0106] In some specific embodiments, when the processor 11 executes the computer subroutine stored in the memory 12, it may specifically implement the following steps:

[0107] The cumulative performance heatmap of the process within the preset time period is generated.

[0108] In some specific embodiments, when the processor 11 executes the computer subroutine stored in the memory 12, it may specifically implement the following steps:

[0109] Determine whether the correlation between multiple performance data in the same disk partition in the performance heatmap of the same disk meets preset conditions;

[0110] If not, generate alarm information corresponding to the disk partition.

[0111] In some specific embodiments, when the processor 11 executes the computer subroutine stored in the memory 12, it may specifically implement the following steps:

[0112] Compare the performance heatmaps of multiple disks and generate a disk performance comparison report corresponding to the multiple disks.

[0113] Furthermore, the disk performance information processing device in this embodiment may further include:

[0114] Input interface 13 is used to acquire computer programs imported from external sources and save the acquired computer programs to the memory 12. It can also be used to acquire various instructions and parameters transmitted from external terminal devices and transmit them to the processor 11 so that the processor 11 can perform corresponding processing using the aforementioned instructions and parameters. In this embodiment, the input interface 13 may specifically include, but is not limited to, a USB interface, a serial interface, a voice input interface, a fingerprint input interface, a disk read interface, etc.

[0115] Output interface 14 is used to output various data generated by processor 11 to connected terminal devices, so that other terminal devices connected to output interface 14 can obtain various data generated by processor 11. In this embodiment, output interface 14 may specifically include, but is not limited to, USB interface, serial interface, etc.

[0116] The communication unit 15 is used to establish a remote communication connection between the disk performance information processing device and an external server, so that the disk performance information processing device can mount the image file to the external server. In this embodiment, the communication unit 15 may specifically include, but is not limited to, a remote communication unit based on wireless communication technology or wired communication technology.

[0117] Keyboard 16 is used to acquire various parameter data or commands input by the user through real-time keystrokes.

[0118] The display 17 is used to display relevant information about the disk performance information processing process in real time, so that users can understand the current disk performance information processing status in a timely manner.

[0119] Mouse 18 can be used to assist users in inputting data and simplify user operations.

[0120] Furthermore, this application also discloses a readable storage medium, which includes random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, disks, removable disks, CD-ROMs, or any other form of storage medium known in the art. The readable storage medium stores a computer program, typically used on a Linux platform running a disk, which is executed during disk operation. When executed by a processor, the computer program performs the following steps:

[0121] Monitor and obtain disk performance information;

[0122] Determine the mapping relationship between multiple performance data and multiple disk partitions in the performance information;

[0123] Based on the mapping relationship, a performance heatmap is generated, which displays the partition performance map with the corresponding performance data at the location of each disk partition;

[0124] A disk performance report is generated based on the performance heatmap.

[0125] This application embodiment generates a performance heatmap after determining the mapping relationship. The performance heatmap is in the form of a two-dimensional partition map, which intuitively and accurately reflects the performance status of each disk partition in the disk. Furthermore, a disk performance report is generated based on the performance heatmap, which can provide more accurate, effective and higher performance analysis.

[0126] In some specific embodiments, when the computer subroutine stored in the readable storage medium is executed by a processor, the following steps can be implemented:

[0127] Key strings are extracted from the performance information and sorted to determine multiple performance data.

[0128] In some specific embodiments, the performance data includes:

[0129] One or more of the following: IO time, bandwidth, IOPS, and queue depth.

[0130] In some specific embodiments, when the computer subroutine stored in the readable storage medium is executed by a processor, the following steps can be implemented:

[0131] Based on the timestamps of the performance data and the mapping relationship, a process performance heatmap that changes over time is generated.

[0132] In some specific embodiments, when the computer subroutine stored in the readable storage medium is executed by a processor, the following steps can be implemented:

[0133] The cumulative performance heatmap of the process within the preset time period is generated.

[0134] In some specific embodiments, when the computer subroutine stored in the readable storage medium is executed by a processor, the following steps can be implemented:

[0135] Determine whether the correlation between multiple performance data in the same disk partition in the performance heatmap of the same disk meets preset conditions;

[0136] If not, generate alarm information corresponding to the disk partition.

[0137] In some specific embodiments, when the computer subroutine stored in the readable storage medium is executed by a processor, the following steps can be implemented:

[0138] Compare the performance heatmaps of multiple disks and generate a disk performance comparison report corresponding to the multiple disks.

[0139] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0140] The present invention has provided a detailed description of a disk performance information processing method, system, apparatus, and readable storage medium. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, those skilled in the art will recognize that there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for processing disk performance information, characterized in that, include: Monitor and obtain disk performance information; Determine the mapping relationship between multiple performance data and multiple disk partitions in the performance information; Based on the mapping relationship, a performance heatmap is generated, which displays the partition performance map with the corresponding performance data at the location of each disk partition; Based on the performance heatmap, generate a disk performance report; The process of generating a performance heatmap based on the mapping relationship further includes: Based on the timestamps of the performance data and the mapping relationship, a process performance heatmap that changes over time is generated. After generating a process performance heatmap that changes over time based on the timestamps of the performance data and the mapping relationship, the method further includes: The cumulative performance heatmap of the process within the preset time period is generated.

2. The processing method according to claim 1, characterized in that, After monitoring and acquiring disk performance information, the process also includes: Key strings are extracted from the performance information and sorted to determine multiple performance data.

3. The processing method according to claim 1, characterized in that, The performance data includes: One or more of the following: IO time, bandwidth, IOPS, and queue depth.

4. The processing method according to any one of claims 1 to 3, characterized in that, The process of generating a disk performance report based on the performance heatmap includes: Determine whether the correlation between multiple performance data in the same disk partition in the performance heatmap of the same disk meets preset conditions; If not, generate alarm information corresponding to the disk partition.

5. The processing method according to any one of claims 1 to 3, characterized in that, The process of generating a disk performance report based on the performance heatmap includes: Compare the performance heatmaps of multiple disks and generate a disk performance comparison report corresponding to the multiple disks.

6. A disk performance information processing system, characterized in that, include: The information module is used to monitor and obtain disk performance information; A mapping module is used to determine the mapping relationship between multiple performance data and multiple disk partitions in the performance information; The heatmap module is used to generate a performance heatmap based on the mapping relationship. The performance heatmap displays a partition performance map with the corresponding performance data at the location of each disk partition. The reporting module is used to generate a disk performance report based on the performance heatmap; Specifically, the heatmap module is used to generate a process performance heatmap that changes over time based on the timestamps of the performance data and the mapping relationship. The processing system is also used to accumulate the process performance heatmap within a preset time period and generate a cumulative performance heatmap.

7. A disk performance information processing device, characterized in that, include: Memory, used to store computer programs; A processor, configured to implement the steps of the disk performance information processing method as described in any one of claims 1 to 5 when executing the computer program.

8. A readable storage medium, characterized in that, The readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the disk performance information processing method as described in any one of claims 1 to 5.

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