Disk performance analysis method based on high-density storage

Abstract

The present application provides a disk performance analysis method based on high-density storage, which relates to the technical field of disk performance analysis, including: reading the initial disk performance; obtaining the real-time storage data volume, combining the predetermined target capacity to obtain the real-time storage ratio, and using it as a disk performance analysis constraint; calling the predetermined disk performance analysis strategy to perform performance detection and analysis on the target storage to obtain real-time disk performance; generating a disk loss function based on the mapping relationship between the disk performance loss index and the real-time storage ratio obtained by comparing the real-time disk performance with the initial disk performance; and performing disk performance loss analysis on the target storage based on the disk loss function. The present application can solve the technical problem in the prior art that the disk performance decreases as the amount of stored data increases due to the failure to fully consider the decrease in disk performance, and achieve the technical goal of dynamically optimizing disk performance to cope with the performance decrease caused by the increase in the amount of stored data, thereby achieving the technical effect of improving the overall operating efficiency of the system.

Description

Technical Field

[0001] The present application relates to the technical field of disk performance analysis, and in particular to a disk performance analysis method based on a high-density memory. Background Art

[0002] As modern storage needs continue to grow, disk performance has become an important factor affecting the overall efficiency of the system. Traditional disk storage devices usually perform well in the design and initial use stages and can meet daily data storage and access needs. However, as the amount of stored data gradually increases, disk performance will show a clear downward trend.

[0003] At present, in traditional storage management technology, although the disk can provide a higher data transfer rate and a shorter data access time in the early stage, this gradually weakens as the amount of data stored on the disk increases. As the amount of data accumulates, the processing time and resource consumption required for the disk to transfer and access data also increases, resulting in a gradual decrease in the transfer rate and a corresponding increase in the data access time. Among them, when processing a large number of data access requests, the disk often requires multiple seek operations, especially when the data is stored in a dispersed manner. This increase in seek time directly leads to an increase in data access time. Although some solutions try to alleviate this performance degradation problem by increasing cache or optimizing data access algorithms, the effect is usually limited, and often does not fully consider the combined impact of the initial data transfer rate and initial data access time as the amount of stored data increases. Therefore, they perform poorly in the face of large-scale data storage and high-frequency data access scenarios, and it is difficult to meet the requirements of modern information systems for high performance and low latency.

[0004] To sum up, there is a technical problem in the prior art that, due to the failure to fully consider the combined impact of the initial data transmission rate and the initial data access time as the amount of stored data increases, the disk performance decreases significantly as the amount of stored data increases, further affecting the overall operating efficiency and performance stability of the system. Summary of the invention

[0005] The purpose of this application is to provide a disk performance analysis method based on high-density storage, so as to solve the technical problem in the prior art that the disk performance decreases significantly with the increase of stored data volume due to the failure to fully consider the combined impact of the initial data transmission rate and the initial data access time as the stored data volume increases, further affecting the overall operating efficiency and performance stability of the system.

[0006] In view of the above problems, the present application provides a disk performance analysis method based on high-density memory.

[0007] The present application provides a disk performance analysis method based on a high-density memory, comprising: reading initial disk performance, wherein the initial disk performance refers to the qualified disk performance of the target memory when it leaves the factory, wherein the target memory has an identifier of a predetermined target capacity; obtaining a real-time storage data volume, combining the predetermined target capacity to obtain a real-time storage ratio, and using the real-time storage ratio as a disk performance analysis constraint; under the disk performance analysis constraint, calling a predetermined disk performance analysis strategy to perform performance detection and analysis on the target memory to obtain real-time disk performance; generating a disk loss function based on a mapping relationship between a disk performance loss index obtained by comparing the real-time disk performance with the initial disk performance and the real-time storage ratio; and performing a disk performance loss analysis on the target memory based on the disk loss function.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0009] By reading the initial disk performance, the initial disk performance refers to the qualified disk performance of the target storage when it leaves the factory, wherein the target storage has an identifier of a predetermined target capacity; obtaining the real-time storage data volume, combining the predetermined target capacity to obtain the real-time storage ratio, and using the real-time storage ratio as a disk performance analysis constraint; under the disk performance analysis constraint, calling the predetermined disk performance analysis strategy to perform performance detection and analysis on the target storage to obtain real-time disk performance; generating a disk loss function based on the mapping relationship between the disk performance loss index obtained by comparing the real-time disk performance with the initial disk performance and the real-time storage ratio; performing a disk performance loss analysis on the target storage based on the disk loss function, achieving the technical goal of dynamically optimizing disk performance to cope with the performance degradation caused by the increase in the amount of stored data, and achieving the technical effect of maintaining a higher data transmission rate and a shorter data access time in large-scale data storage and high-frequency data access scenarios, thereby improving the overall operation efficiency and performance stability of the system.

[0010] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented according to the contents of the specification, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are specifically cited below. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0012] Figure 1 This is a flow chart of a disk performance analysis method based on high-density storage in this application;

[0013] Figure 2 This is a schematic diagram of the process of obtaining real-time disk performance in the disk performance analysis method based on high-density storage in this application. DETAILED DESCRIPTION

[0014] This application provides a disk performance analysis method based on high-density storage, which solves the technical problem in the prior art that the disk performance significantly decreases with the increase of the amount of stored data, further affecting the overall operation efficiency and performance stability of the system, due to the failure to fully consider the combined impact of the initial data transmission rate and the initial data access time as the amount of stored data increases. The technical goal of dynamically optimizing disk performance to cope with the performance degradation caused by the increase in the amount of stored data is achieved, and the technical effect of maintaining a higher data transmission rate and a shorter data access time in large-scale data storage and high-frequency data access scenarios is achieved, thereby improving the overall operation efficiency and performance stability of the system.

[0015] Below, the technical solutions in the present application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments of the present application. It should be understood that the present application is not limited to the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application. It should also be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, rather than all of them.

[0016] Please see attached Figure 1 The present application provides a disk performance analysis method based on high-density storage, which specifically includes the following steps:

[0017] Step 1: Reading the initial disk performance, wherein the initial disk performance refers to the disk performance of the target storage device when it is qualified before leaving the factory, wherein the target storage device has an identifier of a predetermined target capacity.

[0018] Specifically, by reading the initial disk performance, the disk performance of the target storage when it leaves the factory is obtained, wherein the disk performance includes the key indicators of the target storage. Then, by correlating the initial performance, the target storage can be further analyzed to evaluate its current status and operating efficiency. Moreover, the target storage has a specific identification of the predetermined target capacity, which helps to accurately locate the storage and ensure the accuracy of the performance analysis. By comparing the initial performance with the current performance, potential performance degradation or abnormality can be effectively identified, thereby providing a reference for further optimization and maintenance.

[0019] Step 2: Obtain the real-time storage data volume, combine it with the predetermined target capacity to obtain the real-time storage ratio, and use the real-time storage ratio as a disk performance analysis constraint.

[0020] Specifically, the current usage of the target storage is understood by obtaining the real-time storage data volume, and the real-time storage ratio is calculated in combination with the predetermined target capacity. Then, the real-time storage ratio is used as a key constraint condition for disk performance analysis, so that the actual load and usage status of the storage can be more accurately reflected during the analysis process, and the performance of the disk can be more accurately evaluated, thus providing a reliable basis for performance optimization and fault prediction.

[0021] Step three: Under the disk performance analysis constraint, call a predetermined disk performance analysis strategy to perform performance detection and analysis on the target storage to obtain real-time disk performance.

[0022] Specifically, under the constraints of disk performance analysis, according to predetermined disk performance analysis strategies, such as predetermined transmission rate analysis strategies or predetermined access time analysis strategies, the actual performance of the storage is systematically detected, and finally a real-time disk performance result can be generated, which accurately reflects the actual operating status of the target storage under current conditions and provides data support for further performance optimization.

[0023] Step 4: Generate a disk loss function according to a mapping relationship between a disk performance loss index obtained by comparing the real-time disk performance with the initial disk performance and the real-time storage ratio.

[0024] Specifically, the disk performance loss index is obtained by comparing the real-time disk performance with the initial disk performance, that is, by comparing the current performance with the performance at the factory, the degree of disk performance degradation or loss is identified. Then, the loss index is mapped to the real-time storage ratio, and the relationship between the two is established, which can reflect how the performance loss fluctuates with the change of memory usage, and then a disk loss function is generated, which associates the disk performance loss index with the real-time storage ratio, providing a mathematical model to measure the overall health status of the disk, thereby providing a strong theoretical basis for further performance evaluation and optimization.

[0025] Step 5: Perform disk performance loss analysis on the target storage based on the disk loss function.

[0026] Specifically, the target storage is analyzed for disk performance loss based on the disk loss function, and the performance degradation of the target storage during use is quantified. By substituting real-time data into the disk loss function, the performance loss value of the current real-time disk performance is calculated, thereby clarifying the actual operating status of the storage, which not only reveals the performance degradation trend of the storage, but also helps predict future performance changes and guides corresponding maintenance and optimization measures, providing a scientific basis for ensuring the continuous stability of disk performance.

[0027] The disk performance analysis method based on high-density memory analyzes disk performance according to data transmission rate and data access time, and realizes the technical goal of dynamically optimizing disk performance to cope with the performance degradation caused by the increase in the amount of stored data. It achieves the technical effect of maintaining a higher data transmission rate and a shorter data access time in large-scale data storage and high-frequency data access scenarios, thereby improving the overall operating efficiency and performance stability of the system.

[0028] Further, if Figure 2 As shown, this application also includes:

[0029] The predetermined disk performance analysis strategy includes a predetermined transmission rate analysis strategy and a predetermined access time analysis strategy; under the constraints of the disk performance analysis, a performance test is performed on the target buffer of the target storage according to the predetermined transmission rate analysis strategy to obtain buffer test data; the preset transmission characteristics are traversed in the buffer test data to obtain target transmission characteristic parameters; under the constraints of the disk performance analysis, a performance test is performed on the target storage area of ​​the target storage according to the predetermined access time analysis strategy to obtain storage area test data, and the storage area test data includes data access time parameters; a disk performance evaluation function is introduced to evaluate and analyze the target transmission characteristic parameters and the data access time parameters to obtain the real-time disk performance.

[0030] Specifically, the scheduled disk performance analysis strategy includes the scheduled transfer rate analysis strategy and the scheduled access time analysis strategy, which means that during the disk performance analysis process, the scheduled transfer rate analysis strategy and the scheduled access time analysis strategy will be relied upon to evaluate the disk's performance. The scheduled transfer rate analysis strategy focuses on the speed at which data is transferred between disks, while the scheduled access time analysis strategy focuses on the time it takes to read and write data. Therefore, the two strategies can comprehensively evaluate the disk's performance under different operations, so as to facilitate more detailed performance analysis.

[0031] Based on the disk performance analysis constraints, the target buffer of the target storage is performance tested according to the predetermined transmission rate analysis strategy, so that the actual data transmission capacity of the target buffer can be obtained, thereby generating buffer detection data, which reflects the performance of the target buffer under current conditions, especially in terms of data transmission rate, and helps identify potential bottlenecks or performance improvement space, thereby ensuring that the disk performs at its best during data transmission.

[0032] The preset transmission characteristics refer to the specific parameters defined in the buffer detection data, which represent the transmission characteristics of the buffer. By traversing the preset transmission characteristics in the buffer detection data, the target transmission characteristic parameters can be extracted, and then the complex detection data can be simplified into key transmission parameters for further analysis. The target transmission characteristic parameters can be used to measure whether the disk has achieved the expected performance during the data transmission process, thereby providing a basis for performance optimization.

[0033] Under the constraints of disk performance analysis, performance detection is performed on the target storage area of ​​the target storage according to the predetermined access time analysis strategy, aiming to evaluate the performance of the storage area during data access, thereby obtaining the actual data access time of the storage area and generating storage area detection data, which reflects the reading or writing speed of data in the storage area, and further reveals the efficiency of the storage area when processing different types of data, thereby helping to identify factors affecting disk performance.

[0034] Finally, by introducing the disk performance evaluation function, the target transmission characteristic parameters and data access duration parameters are comprehensively evaluated, that is, the data transmission rate and data access duration are comprehensively evaluated to obtain the real-time disk performance. The disk performance evaluation function is to analyze different types of performance parameters in a unified manner to generate an overall performance index, which can then serve as an accurate reflection of the current state of the disk, help identify potential problems and make necessary optimizations.

[0035] Through the predetermined analysis strategy and constraints, the disk buffer and storage area are subjected to detailed performance detection and parameter extraction, and the real-time disk performance is obtained through comprehensive evaluation, thus providing strong support for the comprehensive analysis and optimization of disk performance.

[0036] Furthermore, the present application also includes:

[0037] The preset transmission characteristics include read and write transmission rate, data persistence, concurrent operation capability and error resilience.

[0038] Specifically, the preset transmission characteristics include read and write transmission rate, data persistence, concurrent operation capability, and error resilience, which means that the preset transmission characteristics are used as the measurement standard when analyzing disk performance. Among them, the read and write transmission rate measures the speed of reading and writing data on the disk, while data persistence evaluates the reliability of long-term storage of data on the disk. Concurrent operation capability reflects the ability of the disk to handle multiple operation requests, and error resilience examines the recovery efficiency of the disk when errors occur.

[0039] By presetting the transmission characteristics, the performance of the disk in various operating scenarios can be comprehensively evaluated, thus providing specific direction and basis for performance optimization.

[0040] Furthermore, the present application also includes:

[0041] The expression of the disk performance evaluation function is as follows: ;in, refers to the target memory The real-time disk performance, refers to the target memory Real-time transmission performance, It refers to the target transmission characteristic parameter parameters, refers to the The coefficient of variation of the parameters, and the target transmission characteristic parameters include parameters, , refers to the target memory The data access duration parameter, and They refer to the transmission performance coefficient and the access performance coefficient respectively, and .

[0042] Specifically, the expression of the disk performance evaluation function is used to calculate the real-time disk performance of the target storage. First, Indicates the real-time disk performance of the target storage, which combines multiple factors to reflect the overall performance status of the current disk. Then, Indicates the real-time transfer performance of the target storage, which is related to the data transfer speed and efficiency. Next, Indicates the target transmission characteristic parameter parameters, each of which represents a specific transfer characteristic, such as read / write rate or data persistence. Indicates The coefficient of variation of a parameter is used to measure the stability or volatility of the parameter, which helps to understand whether the transmission characteristic is consistent under different conditions. parameters, , indicating that the evaluation involves The transmission characteristics of the dimensions are analyzed. Indicates the target memory The data access time parameter directly reflects the time efficiency of the disk in processing data access requests. In addition, and They are the transmission performance coefficient and the access performance coefficient, which are used to weigh the relative importance of transmission performance and access performance in the overall performance evaluation. and The coefficient ranges from 0 to 1, ensuring the rationality and stability of the evaluation results.

[0043] By combining real-time transmission performance, transmission characteristic parameters and their coefficient of variation, and data access time parameters, the overall performance of the target storage is comprehensively evaluated, providing a scientific basis for performance optimization and fault warning.

[0044] Furthermore, the present application also includes:

[0045] Extract a first mode from a predetermined disk mode; perform a garbage cleaning performance test on the target buffer in the first mode to obtain first cleaning test data, wherein the first cleaning test data includes multiple groups of cleaning records; obtain first read-write information corresponding to a first cleaning record in the multiple groups of cleaning records, and collect first information features of the first read-write information; perform a cleaning feature analysis on the first cleaning record in combination with the first information features to obtain a target cleaning index; and calibrate the real-time disk performance using the target cleaning index as a coefficient.

[0046] Specifically, the predetermined disk mode refers to different buffer cleaning mechanisms corresponding to different disk modes. Extracting the first mode in the predetermined disk mode refers to selecting a specific operation mode that matches the application from multiple possible disk modes. The first mode can represent a specific operation scenario or configuration scheme. For example, when a large amount of data is read and written, the greedy garbage cleaning strategy is started to stabilize the buffer performance. When a small amount of data is read and written, the lazy garbage cleaning strategy is started. Set a foundation for the next operation to ensure that subsequent detection and analysis are performed in this clear mode, so as to obtain consistent and comparable results. Among them, the greedy garbage cleaning strategy will immediately clean up all useless data at every possible opportunity, without waiting until the system is idle or resources are insufficient, thereby maximizing the cleanliness of the system and reducing potential performance problems. Lazy garbage cleaning is an on-demand cleaning strategy that is usually performed when the system is idle or when resources are insufficient, so as to avoid affecting the normal operation of the system. The lazy cleaning mechanism is more efficient when the system load is light.

[0047] In the first mode, the garbage cleaning performance test of the target buffer is performed to evaluate the efficiency of the buffer in cleaning redundant data or useless data, thereby generating the first cleaning test data. The first cleaning test data includes multiple groups of cleaning records, each of which describes in detail the specific operations and effects during the cleaning process, providing a basis for further analyzing the buffer cleaning capability. For example, multiple groups of cleaning records are data with different cleaning times.

[0048] Obtaining the first read / write information corresponding to the first cleaning record in the multiple sets of cleaning records and collecting the first information features of the first read / write information refers to extracting key information related to the disk read / write operation from the cleaning record and performing feature processing on the first read / write information, thereby understanding the specific behavior and pattern exhibited by the disk during the cleaning process, laying the foundation for subsequent cleaning feature analysis. For example, the first information features include the data volume and the data types of audio data, image data, text data, etc.

[0049] The first cleaning record is analyzed for cleaning characteristics in combination with the first information characteristics, and the extracted read-write information is compared and analyzed with the actual cleaning record to identify specific characteristics or rules in the cleaning operation, obtain a target cleaning index, quantify the cleaning performance of the buffer under a specific operation mode, and reflect the efficiency and effect of the cleaning process. Among them, the cleaning characteristic analysis includes the analysis of cleaning efficiency, cleaning effect, impact on normal operation, stability of the cleaning operation, resource consumption and automation. Cleaning speed analysis refers to measuring the time required for the cleaning operation to complete, usually measured by the amount of data that can be cleaned per second (MB / s or GB / s). The IOPS of the cleaning operation refers to the evaluation of the number of cleaning operations that can be completed in a unit of time. Cleaning effect analysis refers to the analysis of data recovery rate and space recovery rate. The data recovery rate refers to the ratio of the amount of valid data that can be recovered to the total amount of data during the cleaning process. The space recovery rate refers to the ratio of the space released after cleaning to the total space. The impact analysis on normal operation refers to the analysis of performance impact and concurrent performance. The performance impact refers to the evaluation of the impact of garbage cleaning on the normal read and write performance of the buffer, including the decrease in data transmission rate and response time. Concurrency performance refers to the ability of the buffer to handle normal read and write requests while performing garbage cleaning. Stability analysis of the cleaning operation refers to the analysis of continuous running time and error rate. Continuous running time refers to the time that the garbage cleaning operation can run continuously to evaluate its stability. Error rate refers to the probability of errors or failures during the cleaning process. Resource consumption analysis refers to the analysis of CPU and memory usage and energy consumption. CPU and memory usage refers to the use of CPU and memory resources during the garbage cleaning process. Energy consumption refers to the impact of garbage cleaning operations on energy consumption. Automation analysis refers to the analysis of intelligent cleaning. Intelligent cleaning refers to the evaluation of the intelligence of the garbage cleaning strategy, such as whether the cleaning frequency and strategy can be automatically adjusted according to data access patterns and storage usage.

[0050] Finally, the real-time disk performance is calibrated using the target cleaning index as a coefficient. This means using the target cleaning index to adjust and correct the evaluation results of the real-time disk performance. The real-time disk performance can more accurately reflect the performance in the actual operating environment, especially the impact of the cleaning operation on the overall performance.

[0051] By extracting specific operating modes, performing cleaning performance testing and data analysis, and then calibrating the disk performance based on the cleaning index, we can achieve performance optimization and accurate evaluation of the disk under specific conditions, ensuring the stability and efficiency of the disk performance in actual applications.

[0052] Furthermore, the present application also includes:

[0053] Perform information feature clustering analysis on the first read-write information to obtain a first information clustering result; obtain a first information type number based on the first information clustering result, and establish the first information feature in combination with a first information capacity value of the first read-write information.

[0054] Specifically, performing information feature clustering analysis on the first read-write information refers to classifying the read-write operation data of the disk through a clustering algorithm, grouping the read-write information with similar features, and then identifying different patterns or types existing in the data operation process, thereby simplifying the complex read-write information into several key categories for subsequent analysis and processing.

[0055] The first information type number obtained according to the first information clustering result indicates that the number of different categories existing in the read and write information is determined through cluster analysis. Each first information clustering result represents a specific read and write behavior or mode, and combined with the first information type number, the performance of the disk under different operating conditions can be more clearly understood.

[0056] Combining the first information capacity value of the first read-write information to form the first information feature means combining the first information type number obtained by cluster analysis with the first information capacity value of the read-write information to form a comprehensive feature description, thereby constructing a more comprehensive and accurate information feature, thereby providing a stronger basis for disk performance analysis.

[0057] Through cluster analysis, disk read and write information is classified, different information types are identified, and a detailed information feature description is constructed in combination with the information capacity, which provides a basis for in-depth analysis and optimization of disk performance and helps the system to more accurately reflect the actual operating status of the disk.

[0058] Furthermore, the present application also includes:

[0059] The predetermined cleaning feature is traversed in the first cleaning record to obtain a first cleaning feature parameter; the first cleaning feature parameter is normalized and weighted calculated using the inverse of the first information feature as a weighting coefficient to obtain a first cleaning index under the first mode; the predetermined mode ratio is read, and the target cleaning index is calculated based on the predetermined mode ratio and the first cleaning index.

[0060] Specifically, the predetermined cleaning features are accessed in sequence in the first cleaning record to obtain the first cleaning feature parameters, that is, by accessing the preset cleaning features in the first cleaning record in sequence, the parameter values ​​corresponding to the predetermined cleaning features are extracted, and then the specific cleaning behavior pattern is identified from the first cleaning record, and quantified into specific parameters to provide data support for subsequent analysis.

[0061] The first cleaning feature parameters are normalized and weighted, taking the reciprocal of the first information feature as the weighting coefficient, that is, the extracted first cleaning feature parameters are weighted, where the weight coefficient is the reciprocal of the information feature. Normalized weighted calculation can balance the influence of different parameters, making the cleaning feature parameters comparable under different conditions, thereby obtaining a more objective and accurate first cleaning index.

[0062] The predetermined mode ratio refers to a ratio set by the user, or a ratio obtained by weighted calculation based on the historical usage of the disk. Among them, the commonly used modes have a large weight, and the uncommon modes have a small weight. For example, the weight corresponding to frequently reading and writing large file data is large, and the weight corresponding to occasionally transmitting small video data is small. Then, the predetermined mode ratio is read, and the target cleaning index is calculated based on the predetermined mode ratio and the first cleaning index, for example, by combining methods such as weighted calculation. The target cleaning index comprehensively considers the impact of different modes, so that the target cleaning index can more comprehensively reflect the cleaning efficiency and effect of the disk in the actual operating environment.

[0063] By traversing the cleaning records to extract key parameters, combining information features for weighted calculation, and calculating the final target cleaning index based on a predetermined pattern ratio, accurate evaluation of the cleaning operation is ensured and a reliable basis is provided for optimizing disk performance.

[0064] Furthermore, the present application also includes:

[0065] The first cleanup index is adjusted according to a first write amplification in the first cleanup record.

[0066] Specifically, the first cleaning index is adjusted according to the first write amplification in the first cleaning record, that is, the write amplification effect is considered when calculating the disk cleaning efficiency. Write amplification means that in actual operation, in order to complete a data write, the disk may need to perform multiple write operations, resulting in additional write burden. Specifically, if the write amplification effect is large during the cleaning process, it means that the actual amount of data written far exceeds the original amount of data, which will lead to a potential decrease in disk performance. Therefore, the adjustment process will reflect the negative impact by reducing the value of the cleaning index and reduce the initial cleaning index, so as to more accurately evaluate the actual efficiency and impact of the disk in the cleaning operation. Conversely, if the write amplification effect is small, the impact of the adjustment on the cleaning index will also be small, so that the cleaning index can more objectively reflect the actual cleaning effect. By adjusting the first cleaning index, the performance loss caused by write amplification during the cleaning process of the disk can be more accurately reflected.

[0067] By combining the adjusted cleaning index, the actual cleaning efficiency of the disk can be evaluated more objectively, and more targeted guidance can be provided for optimizing disk performance.

[0068] In summary, the disk performance analysis method based on high-density storage provided by the present application has the following technical effects:

[0069] By reading the initial disk performance, the initial disk performance refers to the qualified disk performance of the target storage when it leaves the factory, wherein the target storage has an identifier of a predetermined target capacity; obtaining the real-time storage data volume, combining the predetermined target capacity to obtain the real-time storage ratio, and using the real-time storage ratio as a disk performance analysis constraint; under the disk performance analysis constraint, calling the predetermined disk performance analysis strategy to perform performance detection and analysis on the target storage to obtain real-time disk performance; generating a disk loss function based on the mapping relationship between the disk performance loss index obtained by comparing the real-time disk performance with the initial disk performance and the real-time storage ratio; performing a disk performance loss analysis on the target storage based on the disk loss function, achieving the technical goal of dynamically optimizing disk performance to cope with the performance degradation caused by the increase in the amount of stored data, and achieving the technical effect of maintaining a higher data transmission rate and a shorter data access time in large-scale data storage and high-frequency data access scenarios, thereby improving the overall operation efficiency and performance stability of the system.

[0070] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0071] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application belong to the scope of the present application and its equivalent technology, the present application is also intended to include these modifications and variations.

Claims

1. A disk performance analysis method based on high-density storage, characterized in that: include: Reading initial disk performance, where the initial disk performance refers to the disk performance of the target storage device when it is qualified before leaving the factory, wherein the target storage device has an identifier of a predetermined target capacity; Acquire the real-time storage data volume, combine it with the predetermined target capacity to obtain the real-time storage ratio, and use the real-time storage ratio as a disk performance analysis constraint; Under the disk performance analysis constraint, a predetermined disk performance analysis strategy is called to perform performance detection and analysis on the target storage to obtain real-time disk performance. The predetermined disk performance analysis strategy includes a predetermined transmission rate analysis strategy and a predetermined access time analysis strategy, which means that the predetermined transmission rate analysis strategy and the predetermined access time analysis strategy will be relied upon to evaluate the working performance of the disk during the disk performance analysis process. Among them, the predetermined transmission rate analysis strategy focuses on the speed of data transmission between disks, while the predetermined access time analysis strategy focuses on the time spent on data reading and writing. Generate a disk loss function according to a mapping relationship between a disk performance loss index obtained by comparing the real-time disk performance with the initial disk performance and the real-time storage ratio; Performing a disk performance loss analysis on the target storage based on the disk loss function; The method further comprises: Under the disk performance analysis constraint, performing performance detection on the target buffer of the target storage according to the predetermined transmission rate analysis strategy to obtain buffer detection data; Traversing the preset transmission characteristics in the buffer detection data to obtain target transmission characteristic parameters; Under the disk performance analysis constraint, a performance test is performed on the target storage area of ​​the target storage according to the predetermined access duration analysis strategy to obtain storage area test data, wherein the storage area test data includes a data access duration parameter; Introducing a disk performance evaluation function to evaluate and analyze the target transmission characteristic parameter and the data access duration parameter to obtain the real-time disk performance; extracting a first mode of the predetermined disk modes; Performing a garbage cleaning performance test on the target buffer in the first mode to obtain first cleaning test data, wherein the first cleaning test data includes a plurality of groups of cleaning records; Acquire first read-write information corresponding to a first cleaning record in the plurality of groups of cleaning records, and collect first information features of the first read-write information; performing cleaning feature analysis on the first cleaning record in combination with the first information feature to obtain a target cleaning index; Calibrate the real-time disk performance using the target cleaning index as a coefficient; Performing information feature clustering analysis on the first read / write information to obtain a first information clustering result; The first information type number is obtained according to the first information clustering result, and the first information feature is constructed in combination with the first information capacity value of the first read-write information.

2. The disk performance analysis method based on high-density storage according to claim 1, characterized in that: The preset transmission characteristics include read and write transmission rate, data persistence, concurrent operation capability and error resilience.

3. The disk performance analysis method based on high-density storage according to claim 2 is characterized in that: The expression of the disk performance evaluation function is as follows: ； in, refers to the target memory The real-time disk performance, refers to the target memory Real-time transmission performance, It refers to the target transmission characteristic parameter parameters, refers to the The coefficient of variation of the parameters, and the target transmission characteristic parameters include parameters, , refers to the target memory The data access duration parameter, and They refer to the transmission performance coefficient and the access performance coefficient respectively, and .

4. The disk performance analysis method based on high-density storage according to claim 1 is characterized in that: include: Traversing the predetermined cleaning feature in the first cleaning record to obtain a first cleaning feature parameter; Taking the reciprocal of the first information feature as a weighting coefficient, performing normalized weighted calculation on the first cleaning feature parameter to obtain a first cleaning index under the first mode; The predetermined mode ratio is read, and the target cleaning index is calculated based on the predetermined mode ratio and the first cleaning index.

5. The disk performance analysis method based on high-density storage according to claim 4 is characterized in that: It also includes adjusting the first cleanup index according to a first write amplification in the first cleanup record.

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