Data migration method, device, equipment and medium

Abstract

The present application provides a data migration method, apparatus, device, and medium, relating to the field of storage system technology. The method, apparatus, and device can analyze the target association relationship between the change in multiple storage system resources associated with the data migration task and the change in the migration speed by increasing the migration speed of the data migration task multiple times during an observation phase prior to executing the data migration task. Based on the target association relationship and the resource requirements of multiple storage system resources associated with business I / O, the method determines the corresponding speed increments for each of the multiple storage system resources associated with the data migration task. Using the multiple speed increments, the method determines the target migration speed for executing the data migration task. This method achieves the target migration speed by dynamically adjusting the migration speed of the data migration task while ensuring the resource requirements of the business I / O, thereby maximizing the utilization of storage system resources and improving the execution efficiency of the data migration task.

Description

Technical Field

[0001] The present application relates to the technical field of storage systems, and in particular to a data migration method, apparatus, device, and medium. Background Art

[0002] The storage system's background data migration functions, including volume-level mirroring, disaster recovery-level cloning, backup, and remote replication, all require dual data backups and volume-level data migration across storage pools. Because data migration tasks consume storage system resources, including bandwidth, CPU resources, memory resources, and disk resources, overly rapid data migration can increase service I / O response latency, causing service interruptions.

[0003] Currently, most storage vendors offer data migration tasks that can be slowed down by adjusting the speed to prioritize business I / O. However, this speed adjustment only allows for a fixed migration speed and cannot dynamically adjust the migration speed based on the business I / O load. When the business I / O load is high, data migration tasks may occupy storage system resources that were previously allocated for business I / O, leading to increased business I / O latency. When the business I / O load is low, the migration speed cannot be increased, potentially leading to inefficient use of storage system resources. Summary of the Invention

[0004] In view of this, embodiments of the present application provide a data migration method, apparatus, device, and medium to overcome the above-mentioned problems or at least partially solve the above-mentioned problems.

[0005] A first aspect of an embodiment of the present application provides a data migration method, the method comprising:

[0006] After the data migration task is started, during an observation phase, the migration speed of the data migration task is increased multiple times according to preset unit speed increments, and a target association relationship is determined by analyzing the changes in multiple storage system resources associated with the data migration task. The target association relationship is used to represent the association between the changes in the multiple storage system resources associated with the data migration task and the changes in the migration speed of the data migration task.

[0007] Determining the speed increments that can be increased for each of the multiple storage system resources associated with the data migration task based on the target association relationship and the resource demands of the multiple storage system resources associated with the business IO;

[0008] A target migration speed of the data migration task is determined based on the plurality of scalable speed increments, and the data migration task is executed according to the target migration speed.

[0009] Optionally, the target association relationship is determined by the following steps:

[0010] For each observation period of the observation phase, increasing the migration speed according to the preset unit speed increment, and determining a change in a plurality of storage system resources associated with the data migration task during the observation period;

[0011] After the observation phase ends, statistics are collected on the changes in the plurality of storage system resources corresponding to each observation period to obtain statistical results;

[0012] Based on the statistical results, the target association relationship is determined.

[0013] Optionally, the multiple storage system resources include at least CPU resources, memory resources, and hard disk resources, and determining the target association relationship based on the statistical result includes:

[0014] Based on the statistical results, for each storage system resource associated with the data migration task, calculate an average change in the storage system resource after the migration speed of the data migration task is increased by a preset unit speed increment;

[0015] determining the target association relationship based on a correspondence between the preset unit speed increment and an average change in the plurality of storage system resources;

[0016] The determining, based on the target association relationship and the resource requirements of the multiple storage system resources associated with the business IO, the corresponding respective speed increments of the multiple storage system resources associated with the data migration task includes:

[0017] Calculating the speed increments corresponding to the plurality of storage system resources based on first resource margins currently available for the data migration task and the target association relationship;

[0018] The first resource margin is determined based on the total amount of the multiple storage system resources, the resource demand of the service IO for the multiple storage system resources, and the reserved resource amount of the multiple storage system resources.

[0019] Optionally, the method further includes:

[0020] Determining, based on a type of a hard disk corresponding to the hard disk resource associated with the data migration task, a statistical time interval corresponding to the hard disk;

[0021] Based on the statistical time interval, in a first statistical period before the start of the observation phase, the number of times the hard disk is in a busy state is counted, and a first hard disk resource occupancy rate of the hard disk resource before the start of the observation phase is calculated;

[0022] Based on the statistical time interval, within multiple observation cycles after the start of the observation phase, the number of times the hard disk is in a busy state is counted, and multiple second hard disk resource occupancy rates of the hard disk resource in the observation phase are calculated;

[0023] Calculating an average change in the hard disk resource based on the plurality of second hard disk resource occupancy rates and the first hard disk resource occupancy rate;

[0024] After obtaining the average change of the hard disk resource, the average change of the hard disk resource is updated based on the current change of the hard disk resource in the latest observation period, the average change of the hard disk resource, the preset unit speed increment, and the first weight of the average change of the hard disk resource and the second weight of the current change of the hard disk resource in the latest observation period.

[0025] Optionally, when the multiple storage system resources include bandwidth resources, determining the target association relationship based on the statistical result includes:

[0026] When the data migration task and the service IO share the same IO port, determining the bandwidth resources available for the data migration task based on the bandwidth resources occupied by the service IO;

[0027] Based on the bandwidth resources available for the data migration task, a speed increment corresponding to the bandwidth resources is determined.

[0028] Optionally, the method further includes:

[0029] In the first observation period of the observation phase, when the change in the storage system resources corresponding to the service IO is greater than a preset change or the storage system resources occupied by the service IO are greater than a first preset threshold, statistics are not collected on the change in the multiple storage system resources obtained in the first observation period;

[0030] In the second observation period of the observation phase, when the load corresponding to the business IO is greater than the second preset threshold and the data volume of the data migration task is less than the third preset threshold, the changes in the multiple storage system resources obtained in the second observation period are not counted.

[0031] Optionally, determining a target migration speed of the data migration task based on the plurality of speed-increase increments includes:

[0032] A target migration speed of the data migration task is calculated based on the smallest scalable speed increment among the multiple scalable speed increments and the current migration speed of the data migration task after the observation phase ends.

[0033] Optionally, the method further includes:

[0034] In the process of executing the data migration task according to the target migration speed, the target migration speed is adjusted based on changes in resource demands of the service IO on multiple storage system resources and the target association relationship.

[0035] A second aspect of an embodiment of the present application provides a data migration device, the device comprising:

[0036] An observation module is configured to, after a data migration task is initiated, increase the migration speed of the data migration task multiple times according to preset unit speed increments during an observation phase, and determine a target association relationship by analyzing changes in multiple storage system resources associated with the data migration task, wherein the target association relationship is used to represent an association between changes in the multiple storage system resources associated with the data migration task and changes in the migration speed of the data migration task;

[0037] a module for determining an increase in speed that can be increased, configured to determine an increase in speed that can be increased for each of the plurality of storage system resources associated with the data migration task based on the target association relationship and the resource demand of the plurality of storage system resources associated with the business IO;

[0038] The data migration task execution module is configured to determine a target migration speed of the data migration task based on the plurality of speed-increasing increments, and execute the data migration task according to the target migration speed.

[0039] A third aspect of an embodiment of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the data migration method as described in the first aspect.

[0040] A fourth aspect of an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the data migration method as described in the first aspect is implemented.

[0041] Beneficial effects of this application:

[0042] The embodiments of the present application provide a data migration method, apparatus, device and medium, which increases the migration speed of the data migration task multiple times according to a preset unit speed increment during the observation phase, and determines the target association relationship by analyzing the change amount of multiple storage system resources associated with the data migration task. The target association relationship is used to characterize the association relationship between the change amount of multiple storage system resources associated with the data migration task and the change amount of the migration speed of the data migration task. Then, based on the target association relationship and the resource demand amount of multiple storage system resources associated with the business IO, the speed increments that can be increased corresponding to each of the multiple storage system resources associated with the data migration task are determined. Finally, based on the multiple speed increments that can be increased, the target migration speed of the data migration task is determined, and the data migration task is executed according to the target migration speed.

[0043] In the early observation stage of executing the data migration task, the migration speed of the data migration task can be increased multiple times to analyze the target correlation relationship between the change amount of multiple storage system resources associated with the data migration task and the change amount of the migration speed. Then, according to the target correlation relationship and the resource requirements of multiple storage system resources associated with the business IO, the corresponding speed increments of the multiple storage system resources associated with the data migration task can be determined. Through the multiple speed increments, the target migration speed for executing the data migration task can be determined, so as to achieve the target migration speed by dynamically adjusting the migration speed of the data migration task under the premise of ensuring the resource requirements of the business IO. By executing the data migration task at the target migration speed, the storage system resources can be utilized to the greatest extent, thereby improving the execution efficiency of the data migration task. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The drawings that constitute a part of this application are used to provide further understanding of this application. The illustrative embodiments of this application and their descriptions are used to explain this application and do not constitute improper limitations on this application.

[0045] In order to more clearly illustrate the technical solution of the present application, the following is a brief introduction to the drawings required for the description of the present application. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0046] Figure 1 This is a flowchart of a data migration method provided by an embodiment of the present application;

[0047] Figure 2 This is a schematic diagram of a storage resource occupancy situation provided by an embodiment of the present application;

[0048] Figure 3This is an overall framework diagram of a data migration method provided by an embodiment of the present application;

[0049] Figure 4 This is a schematic diagram of a data migration device according to an embodiment of the present application. DETAILED DESCRIPTION

[0050] It should be noted that, unless there is any conflict, the embodiments and features in the embodiments of this application can be combined with each other.

[0051] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0052] The storage system's background data migration features, including volume-level mirroring, disaster recovery-level cloning, backup, and remote replication, all require dual data backups and volume-level cross-storage pool data migration. Because data migration also consumes storage resources, including transmission networks, CPUs, and back-end hard drives, overly fast data migration tasks can increase service I / O response latency, causing service interruptions.

[0053] Currently, most storage vendors offer data migration speed adjustments to prioritize business I / O. However, speed adjustment only sets a fixed migration speed and cannot automatically adjust the migration speed based on business load. High business loads can increase business I / O latency, while low business loads do not improve migration speed.

[0054] Figure 1 This is a flow chart of a data migration method provided by an embodiment of the present application. Figure 1 As shown, the method includes:

[0055] In step S101, after the data migration task is started, during an observation phase, the migration speed of the data migration task is increased multiple times according to preset unit speed increments, and a target association relationship is determined by analyzing the changes in multiple storage system resources associated with the data migration task. The target association relationship is used to represent the association between the changes in the multiple storage system resources associated with the data migration task and the changes in the migration speed of the data migration task.

[0056] In step S102, based on the target association relationship and the resource demand of the multiple storage system resources associated with the business IO, the speed increments that can be increased corresponding to the multiple storage system resources associated with the data migration task are determined;

[0057] In step S103 , a target migration speed of the data migration task is determined based on the plurality of scalable speed increments, and the data migration task is executed according to the target migration speed.

[0058] First, in step S101, when the data migration task is started, it immediately enters the observation phase, which is the early stage of the entire data migration task execution process. During the observation phase, the migration speed of the data migration task is increased multiple times according to the preset unit speed increment, that is, the migration speed is gradually increased.

[0059] After each migration speed increase, record the changes in multiple storage system resources associated with the data migration task, such as CPU resources, bandwidth resources, hard disk resources, and memory resources.

[0060] By analyzing the relationship between the change in multiple storage system resources associated with the data migration task and the change in the migration speed of the data migration task, a target correlation relationship is determined that characterizes the correlation relationship between the change in multiple storage system resources and the change in the migration speed, which can be a functional relationship or a model.

[0061] Furthermore, in step S102, a target correlation relationship between the change in the storage system resource corresponding to the data migration task and the change in the migration speed of the data migration task, as well as the resource requirements of the multiple storage system resources associated with the service I / O of the storage system, is determined through correlation analysis, regression analysis, a decision tree algorithm, a support vector machine algorithm, or an artificial neural network algorithm. Multiple scalable speed increments for the data migration task can be determined. The multiple scalable speed increments correspond one-to-one to the multiple storage system resources. Based on the target correlation relationship between the change in each storage system resource and the change in the migration speed of the data migration task, and in combination with the resource requirements of the multiple storage system resources associated with the service I / O, a scalable speed increment for the data migration task corresponding to each storage system resource can be determined. The scalable speed increment is a speed increment by which the current migration speed of the data migration task can be increased. The scalable speed increment for the data migration task corresponding to each storage system resource is a speed increment that ensures that the data migration task can maximize the utilization of the corresponding storage system resource while meeting the resource requirements of the service I / O.

[0062] For example, based on the target correlation between the change in CPU resource occupancy caused by a data migration task and the change in the migration speed of the data migration task, combined with the CPU resource demand of the storage system's business IO, the corresponding increase in CPU resource speed can be obtained.

[0063] Based on the target correlation between the change in memory resource usage caused by data migration tasks and the change in migration speed of data migration tasks, combined with the memory resource demand of the storage system's business I / O, the corresponding increase in memory resource speed can be obtained.

[0064] Based on the target correlation between the change in the utilization rate of the hard disk resources of the data migration task and the change in the migration speed of the data migration task, combined with the resource demand for hard disk resources by the business IO of the storage system, the corresponding speed increase of the hard disk resources can be obtained.

[0065] Based on the target correlation between the change in bandwidth resource occupancy due to data migration tasks and the change in migration speed, combined with the bandwidth resource demand of the storage system's business I / O, the corresponding increase in bandwidth resource speed can be obtained.

[0066] Finally, in step S103, after obtaining multiple scalable speed increments, one scalable speed increment is selected from the multiple scalable speed increments to determine a target migration speed for executing the data migration task, and the data migration task is executed according to the target migration speed.

[0067] Through the above embodiments, in the early observation stage of executing the data migration task, by increasing the migration speed of the data migration task multiple times, the target correlation relationship between the change amount of multiple storage system resources associated with the data migration task and the change amount of the migration speed can be analyzed, and then according to the target correlation relationship and the resource requirements of the multiple storage system resources associated with the business IO, the corresponding speed increments of the multiple storage system resources associated with the data migration task can be determined. Through the multiple speed increments, the target migration speed for executing the data migration task can be determined, so that under the premise of ensuring the resource requirements of the business IO, the migration speed of the data migration task is dynamically adjusted to obtain the target migration speed. By executing the data migration task at the target migration speed, the storage system resources can be utilized to the greatest extent, thereby improving the execution efficiency of the data migration task.

[0068] Optionally, the target association relationship is determined by the following steps:

[0069] In step S201, for each observation period of the observation phase, the migration speed is increased according to the preset unit speed increment, and changes in multiple storage system resources associated with the data migration task during the observation period are determined;

[0070] In step S202, after the observation phase ends, statistics are collected on the changes in the plurality of storage system resources corresponding to each observation period to obtain statistical results;

[0071] In step S203, the target association relationship is determined based on the statistical result.

[0072] Specifically, in one embodiment, in step S201, when a data migration task is received, the amount of data required for data migration contained in the data migration task can be obtained first, and the number of observation cycles contained in the observation phase corresponding to the data migration task can be determined based on the amount of data (the more data, the more observation cycles, and conversely, the less data, the fewer observation cycles), and the duration of the observation phase is less than the execution time of the entire data migration task.

[0073] After the storage system receives a signal to start a data migration task, the migration speed of the data migration task is the default initial migration speed (the initial migration speed is 0 or less than the preset speed threshold). At the same time, the storage system immediately enters the observation phase of the data migration task. The observation phase is the early stage of the data migration task execution process and includes multiple observation cycles. During the observation phase, at the beginning of each observation cycle, the migration speed of the data migration task is increased by a preset unit speed increment. The preset unit speed increment can be set based on the actual migration speed regulation requirements of the migration task.

[0074] For example, taking the initial migration speed as 5MB / s and the preset unit speed increment as 10MB / s, at the beginning of the first observation period, the migration speed of the data migration task is increased from 5MB / s by 10MB / s, so that the current migration speed is 15MB / s. The migration speed of the data migration task is increased from 15MB / s by 10MB / s, so that the current migration speed is 25MB / s. The speed adjustment process from the third observation period to the last observation period is similar until the end of the observation period.

[0075] During each observation cycle in the observation phase, changes in multiple storage system resources associated with the data migration task are collected. The change in each of the multiple storage system resources associated with the data migration task is the difference between the start and end times of the observation cycle. The multiple storage system resources include CPU resources, memory resources, hard disk resources, bandwidth resources, etc.

[0076] Furthermore, in step S202, after the observation phase ends, the change amount of each storage system resource associated with the data migration task in multiple observation cycles can be counted, that is, the statistical results can be obtained, wherein in the statistical results, each storage system resource will correspond to multiple change amounts, and the number of change amounts of each storage system resource is the number of observation cycles.

[0077] Finally, in step S203, the changes in the amount of change in the multiple storage system resources associated with the data migration task and the change in the migration speed in each observation period of the observation phase in the statistical results are analyzed to obtain a target correlation relationship for characterizing the correlation relationship between the change in the amount of change in the multiple storage system resources associated with the data migration task and the change in the migration speed of the data migration task.

[0078] The above process of analyzing the changes in the amount of storage system resources and the amount of migration speed changes in each observation period during the observation phase can be performed in the following ways:

[0079] 1. Calculate the correlation coefficients between the changes in the storage system resources and the migration speed during each observation period. These coefficients, such as the Pearson correlation coefficient and the Spearman rank correlation coefficient, measure the degree of correlation between the changes in the storage system resources and the migration speed during each observation period. Correlation coefficients closer to 1 or -1 indicate a higher degree of correlation. This correlation is used to determine the target correlation relationship.

[0080] For example, by calculating the correlation coefficient between the change in CPU resource utilization of a data migration task and the change in the migration speed of the data migration task, if the correlation coefficient is close to 1, it indicates that the change in CPU resource utilization of the data migration task and the change in the migration speed of the data migration task are positively correlated. In other words, the target correlation relationship is that higher the CPU resource utilization, higher the migration speed of the data migration task.

[0081] 2. Use regression models such as linear regression and multivariate linear regression, with the change in storage system resources as the independent variable and the change in the migration speed of the data migration task as the dependent variable. Establish a mathematical model to describe the correlation between the change in multiple storage system resources and the change in migration speed during each observation period of the observation phase. This model can then be used to determine the target correlation based on the correlation.

[0082] For example, a linear regression model can be used to describe the relationship between bandwidth resources used by data migration tasks and the migration speed of data migration tasks. By analyzing the coefficients and significance of the linear regression model, the degree of influence of bandwidth resources on the migration speed of data migration tasks can be determined, and the target correlation relationship can be determined based on the degree of influence.

[0083] 3. Use a decision tree algorithm, taking the change in storage system resources as a feature and the change in the migration speed of the data migration task as the target variable, to build a decision tree model. The branches of the decision tree represent the degree of influence of different changes in storage system resources on the change in migration speed, and the target association relationship is determined based on the degree of influence.

[0084] For example, a decision tree model can be constructed using the disk resource usage of a data migration task as a feature and the migration speed of the data migration task as a target variable. Through the branches of the decision tree, the degree to which different disk resource usage rates affect the migration speed of the data migration task can be determined, and the target association relationship can be determined based on the degree of impact.

[0085] Through the above-mentioned embodiments, in the observation phase after the data migration task is started, by increasing the migration speed of the data migration task multiple times and analyzing the changes in the storage system resources managed by the data migration task, the target correlation relationship between the changes in multiple storage system resources associated with the data migration task and the changes in the migration speed in each observation period of the observation phase can be accurately determined.

[0086] Optionally, the multiple storage system resources include at least CPU resources, memory resources, and hard disk resources, and step S203 includes:

[0087] In step S2031, based on the statistical result, for each storage system resource associated with the data migration task, an average change in the storage system resource after the migration speed of the data migration task is increased by a preset unit speed increment is calculated;

[0088] In step S2032, the target association relationship is determined based on the correspondence between the preset unit speed increment and the average change amount of the plurality of storage system resources;

[0089] The step S102 includes:

[0090] In step S1021, based on the first resource margins of the multiple storage system resources currently available for the data migration task and the target association relationship, the speed increments that can be increased corresponding to the multiple storage system resources are calculated;

[0091] The first resource margin is determined based on the total amount of the multiple storage system resources, the resource demand of the service IO for the multiple storage system resources, and the reserved resource amount of the multiple storage system resources.

[0092] Specifically, the speed increments corresponding to the CPU resources, memory resources, and hard disk resources in the plurality of storage system resources are determined by the following steps:

[0093] First, in step S2031, based on the statistical results of each storage system resource (i.e., CPU resources, memory resources, and hard disk resources) associated with the data migration task, the average change corresponding to each storage system resource is calculated after the migration speed is increased by multiple preset unit speed increments during multiple observation cycles of the data migration task in the observation phase, where the average change refers to the average value of the change of the storage system resources corresponding to multiple observation cycles.

[0094] The formula for calculating the average change is: A = (A1 + A2 + ... + An) / n, where A is the average change in storage system resources, A1 is the change in storage system resources in the first observation period, A2 is the change in storage system resources in the second observation period, An is the change in storage system resources in the third observation period, and n is the number of observation periods.

[0095] For example, taking an initial migration speed of 5 MB / s and a preset unit speed increment of 10 MB / s as an example, during the memory resource observation phase, when the data migration task is started, the migration speed of the data migration task is increased by 10 MB / s at the beginning of each observation cycle. At the end of the observation cycle, the change in memory resources is recorded. The change in memory resources can be represented by the increase in memory usage.

[0096] Observation period 1: Memory usage increased by 5%;

[0097] Observation period 2: Memory usage increased by 7%;

[0098] Observation period 3: Memory usage increased by 9%;

[0099] Observation period 4: Memory usage increased by 11%;

[0100] 5th observation period: memory usage increased by 13%;

[0101] It can be calculated that when the data migration speed is increased by 10 MB / s, the average change in memory resources is: A = (5% + 7% + 9% + 11% + 13%) / 5 = 9.8%.

[0102] The calculation methods for CPU resources and hard disk resources are similar and will not be repeated here.

[0103] Further, in step S2032, a target association relationship is determined based on the correspondence between the preset unit speed increment and the average change of multiple storage system resources, that is, the target association relationship is: the correspondence between the preset unit speed increment and the average change of multiple storage system resources.

[0104] For example, when the average change in CPU resources is 10%, the average change in memory resources is 9.8%, and the average change in hard disk resources is 12%, the target association relationship is: for each increase in the migration speed of the data migration task by one budgeted unit speed increment, the corresponding CPU resource utilization rate of the data migration task will increase by 10%, the memory resource utilization rate will increase by 9.8%, and the hard disk resource utilization rate will increase by 12%.

[0105] Further, in step S1021, based on the total amount of multiple storage system resources, the resource demand of business IO for multiple storage system resources, and the reserved resource amount of multiple storage system resources, the first resource margin of each storage system resource is determined. The first resource margin represents the resource amount of each storage system resource that can currently be allocated to the data migration task, that is, the first resource margin of each storage system resource is: the total amount of each storage system resource minus the demand of business IO for the storage system resource, and then minus the reserved resource amount of the storage system resource. The reserved resource amount is set according to the actual usage of each storage system resource, for example 20%. The reserved resource amount is used to ensure that there are sufficient storage system resources for a task during operation, thereby ensuring the normal operation of the task and avoiding slow operation or crash of the task.

[0106] Figure 2 This is a schematic diagram of a storage resource occupancy situation provided by an embodiment of the present application, such as Figure 2 As shown, each storage system resource is divided into three parts: reserved resources, the first resource margin of the data migration task, and the storage system resource demand of the business IO. The watermark between the first resource margin of the data migration task and the storage system resource demand of the business IO is dynamically adjusted according to the changes in the migration speed of the data migration task.

[0107] Then, based on the first resource margin and the target association relationship of each storage system resource, the scalable speed increment corresponding to each storage system resource is calculated. The scalable speed increment represents the migration speed that can be increased corresponding to each storage system resource.

[0108] The calculation formula for the increaseable speed increment of each storage system resource is: the first resource margin of each storage system resource / the average change of each storage system resource*the preset unit speed increment.

[0109] For example, the target association is: For every increase in the migration speed of a data migration task by a budgeted unit speed increment, the corresponding CPU resource utilization will increase by 10%, the memory resource utilization will increase by 9.8%, and the disk resource utilization will increase by 12%. If the first resource margin of the CPU resource is 50%, the first resource margin of the memory resource is 30%, and the first resource margin of the disk resource is 70%, then the corresponding CPU speed increment is: 50% / 10% * 10MB / s = 50MB / s, the corresponding memory speed increment is: 30% / 9.8% * 10MB / s = 30.6MB / s, and the corresponding disk speed increment is: 70% / 12% * 10MB / s = 58.3MB / s.

[0110] Through the above embodiment, the incremental speed increase for each storage system resource can be calculated based on the first resource margins and target associations of multiple storage system resources currently available for the data migration task. This incremental speed increase can be used to optimize the performance of the data migration task and further adjust the configuration of storage system resources to achieve better migration speed and performance.

[0111] Optionally, the method further includes:

[0112] The method further comprises:

[0113] In step S301, based on the type of the hard disk corresponding to the hard disk resource associated with the data migration task, a statistical time interval corresponding to the hard disk is determined;

[0114] In step S302, based on the statistical time interval, within a first statistical period before the start of the observation phase, the number of times the hard disk is in a busy state is counted, and a first hard disk resource occupancy rate of the hard disk resource before the start of the observation phase is calculated;

[0115] In step S303, based on the statistical time interval, the number of times the hard disk is in a busy state is counted in multiple observation cycles after the start of the observation phase, and multiple second hard disk resource occupancy rates of the hard disk resource in the observation phase are calculated;

[0116] In step S304, the average change amount of the hard disk resource is calculated according to the plurality of second hard disk resource occupancy rates and the first hard disk resource occupancy rate;

[0117] In step S305, after obtaining the average change of the hard disk resource, the average change of the hard disk resource is updated based on the current change of the hard disk resource in the latest observation period, the average change of the hard disk resource, the preset unit speed increment, and the first weight of the average change of the hard disk resource and the second weight of the current change of the hard disk resource in the latest observation period.

[0118] Specifically, in one embodiment, first, in step S301, according to the type of the hard disk corresponding to the hard disk resource associated with the data migration task, a statistical time interval corresponding to the hard disk is determined;

[0119] Different types of hard disks have different IO response delays. Therefore, when obtaining the current occupancy rate of the hard disk, it is necessary to set different statistical time intervals for different statistical cycles according to different types of hard disks. The statistical cycle is used to count the proportion of time the hard disk is in a busy state. The proportion of time in the busy state can be used to determine the occupancy rate of the hard disk resources. As a result, for hard disks of different media, the statistical time interval t of the statistical cycle can be set differently when the statistical cycle remains unchanged.

[0120] For example, for larger 7200 rpm disks, set the statistical interval t to 10 ms; for 10,000 rpm disks, set the statistical interval t to 5 ms; for SAS SSDs, set the statistical interval t to 2 ms; and for NVMe SSDs, set the statistical interval t to 1 ms. Set the statistical interval n to 5 seconds.

[0121] The calculation formula for the disk resource utilization is: B = (n*t) / T, where B is the disk resource utilization, n is the number of times the disk is busy during the statistical period, t is the statistical time interval of the statistical period, and T is the statistical period.

[0122] Further, in step S302, according to the statistical time interval of the hard disk type, the number of times the hard disk is in a busy state is counted within the first statistical period before the observation phase of the data migration task begins, and the first hard disk resource occupancy rate before the observation phase of the hard disk resource begins is calculated.

[0123] For example, for a 10,000 rpm disk, set the statistical interval t = 5ms, and the statistical period is 5s. During the statistical period, the number of IO queues is counted every 5ms. If the IO queue is empty, the hard disk is in an idle state within 5ms; if the number of IO queues is greater than 0, the hard disk is in a busy state within 5ms.

[0124] Further, in step S303, according to the statistical time interval, the number of times the hard disk is in a busy state is counted within multiple observation cycles after the observation phase of the data migration task begins, and multiple second hard disk resource occupancy rates of the hard disk resources in the observation phase are calculated, that is, for each observation cycle, according to the statistical time interval, the number of times the hard disk is in a busy state in each observation cycle is counted to obtain the second hard disk resource occupancy rate corresponding to each observation cycle.

[0125] Further, in step S304, based on the multiple second hard disk resource occupancy rates obtained in step S303 and the first hard disk resource occupancy rate, the changes in the multiple hard disk resource occupancy rates between the multiple second hard disk resource occupancy rates and the first hard disk resource occupancy rate are calculated, and the average of the changes in the multiple hard disk resource occupancy rates is calculated to obtain the average change in the hard disk resource.

[0126] Finally, in step S305, after obtaining the average change in the hard disk resources, since the weight of the hard disk resource occupancy rate corresponding to the data migration task is different at different times, for example, at the latest moment, the change in the hard disk resources can better reflect the current usage of the hard disk. Therefore, it is necessary to update the average change in the hard disk resources based on the average change in the hard disk resources during the observation phase and the current change in the hard disk in the latest observation period to ensure that the target correlation between the obtained average change in the hard disk resources and the preset unit speed increment is more accurate.

[0127] Specifically, a first weight can be set for the average change in the hard disk resources obtained during the observation phase, and a second weight can be set for the current change in the hard disk resources in the latest observation period. The update formula for the average change in the hard disk resources is: C = w2*C2+w1*C1, where C is the average change in the hard disk resources after update, C1 is the average change in the hard disk resources obtained during the observation phase, C2 is the current change in the hard disk resources in the latest observation period, w1 is the first weight, w2 is the second weight, and w1+w2=1. The first weight and the second weight can be set according to actual conditions.

[0128] Through the above embodiment, the average change of hard disk resources can be updated according to the average change of hard disk resources in the observation phase and the current change of hard disk in the latest observation period to obtain accurate target association relationship corresponding to hard disk resources.

[0129] Optionally, when the plurality of storage system resources include bandwidth resources, the method further includes:

[0130] In step S401, when the data migration task and the service IO share the same IO port, the bandwidth resources available for the data migration task are determined based on the bandwidth resources occupied by the service IO;

[0131] In step S402, based on the bandwidth resources available for the data migration task, the speed increment corresponding to the bandwidth resources is determined.

[0132] Specifically, in step S401, the server where the storage system is located has multiple IO ports. When processing data migration tasks and business IO at the same time, the data migration task and business IO may share the same IO port. In this case, there will be competition for bandwidth resources between the data migration task and business IO. Therefore, it is necessary to ensure that the bandwidth resources of business IO are not preempted by the data migration task. First, it is necessary to determine the bandwidth resources available for the data migration task based on the bandwidth resources occupied by business IO. The bandwidth resources occupied by business IO are the bandwidth resources required to ensure that business IO can perform IO operations normally. Therefore, the bandwidth resources available for the data migration task can be determined based on the difference between the total bandwidth resources and the bandwidth resources occupied by business IO. For example, the total bandwidth resources of the shared IO port are 1Gbps, and the business IO occupies 0.8Gbps of bandwidth resources per second. Therefore, the bandwidth resources available for the data migration task are 0.2Gbps.

[0133] Furthermore, in step S402, a calculation is performed based on the available bandwidth resources and the target association relationship for the data migration task, and the speed increment corresponding to the bandwidth resources can be determined. For example, after determining that the available bandwidth resources for the data migration task are 0.2 Gbps, it can be converted that the amount of data that can be transmitted per second at 0.2 Gbps is 25 MB. Therefore, it can be determined that the upper limit of the migration speed of the data migration task for the bandwidth resources is 25 MB / s. Therefore, based on the upper limit of the migration speed of the data migration task for the bandwidth resources and the current migration speed of the data migration task, the speed increment corresponding to the bandwidth resources can be determined.

[0134] It should be noted that the speed increment that can be increased can be greater than zero or less than or equal to 0. For example, when the current migration speed of the data migration task is 50 MB / s, the speed increment that can be increased corresponding to the bandwidth resource is -25 MB / s.

[0135] Through the above embodiment, the speed increment that can be increased can be determined based on bandwidth resources, thereby avoiding the occupation of bandwidth resources required for business IO during the speed adjustment process of the data migration task, so as to ensure that the IO operation of the business IO can be performed normally when the data migration task and the business IO share the IO port.

[0136] Optionally, the method further includes:

[0137] In step S501, in a first observation period of the observation phase, when the change in the storage system resources corresponding to the service IO is greater than a preset change or the storage system resources occupied by the service IO are greater than a first preset threshold, statistics are not collected on the change in the multiple storage system resources obtained in the first observation period;

[0138] In step S502, in the second observation period of the observation phase, when the load corresponding to the business IO is greater than the second preset threshold and the data volume of the data migration task is less than the third preset threshold, the changes in the multiple storage system resources obtained in the second observation period are not counted.

[0139] Specifically, in step S501, during the first observation period of the observation phase, the first observation period is an observation period in which the change in storage system resources corresponding to the business IO is greater than a preset change or the storage system resources occupied by the business IO is greater than a first preset threshold. In order to ensure that in the first observation period, due to the large fluctuation of the business IO or the business IO almost completely occupies the storage system resources, the obtained change in the storage system resources may be affected by the business IO, thereby interfering with subsequent statistical results. Therefore, the change in multiple storage system resources obtained in the first observation period will not be counted, so as to avoid large errors in the calculated average change in multiple storage system resources.

[0140] Furthermore, during the observation phase, when the data migration task causes the storage system resource usage to reach or approach a peak, the observation phase of the data migration task will be terminated directly to ensure normal operation of the storage system.

[0141] In step S502, in the second observation period of the observation phase, the second observation period is an observation period in which the load corresponding to the business IO is greater than the second preset threshold and the data volume of the data migration task is less than the third preset threshold. If the load of the business IO is high (the load of the business IO is greater than the second preset threshold, indicating that the load of the business IO is high) and the data volume of the data migration task is small (the data volume of the data migration task is less than the third preset threshold, indicating that the data volume of the data migration task is small), the changes in the multiple storage system resources obtained in the second observation period will not be counted, but statistics will be counted after the load of the business IO is reduced. This ensures the reliability and accuracy of the statistical results and avoids deviations in the statistical results.

[0142] Optionally, the step S103 includes:

[0143] In step S1031 , a target migration speed of the data migration task is calculated based on the smallest scalable speed increment among the multiple scalable speed increments and the current migration speed of the data migration task after the observation phase ends.

[0144] Specifically, in step S1031, the multiple speed increments corresponding to the multiple storage system resources may be of different sizes. Therefore, it is necessary to take into account the various storage system resources and select one of the multiple speed increments and the current migration speed of the data migration task after the end of the observation phase to determine the target migration speed of the data migration task.

[0145] For example, based on the above embodiment, assume that the available speed increments are 20 MB / s, 30 MB / s, and 40 MB / s, respectively. The current migration speed of the data migration task after the observation phase is 30 MB / s. In this case, based on the principle of "the smallest possible speed increment among the multiple possible speed increments," 20 MB / s can be selected to increase the migration speed of the data migration task, bringing the final target migration speed to 50 MB / s.

[0146] Through the above embodiment, it is possible to ensure that the data migration task can maximize the use of various storage system resources while taking into account the resource demand of business IO on various storage system resources and preventing them from being preempted by the data migration task.

[0147] Optionally, the method further includes:

[0148] In step S701, during the process of executing the data migration task according to the target migration speed, the target migration speed is adjusted based on the changes in the resource demands of the business IO on multiple storage system resources and the target association relationship.

[0149] Specifically, in step S701, after determining the target migration speed, the data migration task should be executed according to the target migration speed. In addition, in the process of executing the data migration task according to the target migration speed, it is also necessary to monitor in real time the changes in the resource demands of the business IO for the multiple storage system resources. When the change range of the monitored resource demands of the business IO for the multiple storage system resources is greater than the preset change range, it is also necessary to dynamically adjust the target migration speed based on the changes in the resource demands of the business IO for the multiple storage system resources and the target association relationship.

[0150] When the amount of change in the reduction (increase) in the resource demand of multiple storage system resources by business IO is greater than the preset change range, the target migration speed of the data migration task can be increased (decreased). The increase (decrease) process can dynamically adjust the target migration speed based on the amount of change in the resource demand of multiple storage system resources by business IO and the target association relationship. In addition, during the process of dynamically adjusting the target migration speed, it is necessary to ensure that the resource demand of business IO for each storage system resource is not preempted by the data migration task.

[0151] Figure 3 This is an overall framework diagram of a data migration method provided by an embodiment of the present application. Figure 3 As shown, after obtaining the target migration speed, the changes in the demand for storage system resources by business IO can be continuously monitored during the process of executing the data migration task according to the target migration speed. When the changes in the demand for storage system resources by business IO are increasing, the migration speed of the data migration task is reduced. When the changes in the demand for storage system resources by business IO are decreasing, the migration speed of the data migration task is increased, and monitoring is performed until the data migration task is completed.

[0152] Through the above embodiments, it is possible to ensure that during the execution of the data migration task at the target migration speed, the target migration speed is dynamically adjusted according to the changes in the resource demand of the business IO for multiple storage system resources, thereby realizing an adaptive speed control process for the data migration task.

[0153] Figure 4 This is a schematic diagram of a data migration device provided by an embodiment of the present application. Figure 4 As shown, the device includes:

[0154] An observation module 11 is configured to, after a data migration task is initiated, increase the migration speed of the data migration task multiple times according to preset unit speed increments during an observation phase, and determine a target association relationship by analyzing changes in multiple storage system resources associated with the data migration task, wherein the target association relationship is used to represent an association between changes in the multiple storage system resources associated with the data migration task and changes in the migration speed of the data migration task;

[0155] The speed increment determination module 12 is configured to determine the speed increments corresponding to the plurality of storage system resources associated with the data migration task according to the target association relationship and the resource requirements of the plurality of storage system resources associated with the business IO;

[0156] The data migration task execution module 13 is configured to determine a target migration speed of the data migration task based on the plurality of speed-increase increments, and execute the data migration task according to the target migration speed.

[0157] Optionally, the device further comprises:

[0158] a determination module configured to increase the migration speed according to the preset unit speed increment for each observation period of the observation phase, and determine a change in a plurality of storage system resources associated with the data migration task during the observation period;

[0159] A statistical result acquisition module is used to collect statistics on the changes in the plurality of storage system resources corresponding to each observation period after the observation phase ends to obtain statistical results;

[0160] The target association relationship determination module is used to determine the target association relationship based on the statistical result.

[0161] Optionally, the multiple storage system resources include at least CPU resources, memory resources, and hard disk resources, and the target association relationship determination module includes:

[0162] an average change amount determination module, configured to calculate, based on the statistical results, for each storage system resource associated with the data migration task, an average change amount of the storage system resource after the migration speed of the data migration task is increased by a preset unit speed increment;

[0163] a target association relationship determining unit, configured to determine the target association relationship based on a correspondence between the preset unit speed increment and an average change in the plurality of storage system resources;

[0164] The speed increment determination module 12 includes:

[0165] a speed increment determining unit configured to calculate a speed increment corresponding to each of the plurality of storage system resources based on first resource margins currently available for the data migration task and the target association relationship;

[0166] The first resource margin is determined based on the total amount of the multiple storage system resources, the resource demand of the service IO for the multiple storage system resources, and the reserved resource amount of the multiple storage system resources.

[0167] Optionally, the device further comprises:

[0168] a statistical time interval determining module, configured to determine a statistical time interval corresponding to a hard disk based on a type of the hard disk corresponding to the hard disk resource associated with the data migration task;

[0169] a first hard disk resource occupancy rate calculation module, configured to count the number of times the hard disk is in a busy state within a first statistical period before the start of the observation phase based on the statistical time interval, and calculate a first hard disk resource occupancy rate of the hard disk resource before the start of the observation phase;

[0170] a second hard disk resource occupancy rate calculation module, configured to count the number of times the hard disk is in a busy state within a plurality of observation periods after the start of the observation phase based on the statistical time interval, and calculate a plurality of second hard disk resource occupancy rates of the hard disk resource during the observation phase;

[0171] an average change amount calculation module for hard disk resources, configured to calculate the average change amount of the hard disk resources according to the plurality of second hard disk resource occupancy rates and the first hard disk resource occupancy rate;

[0172] The average change amount update module of the hard disk resource is used to update the average change amount of the hard disk resource based on the current change amount of the hard disk resource in the latest observation period, the average change amount of the hard disk resource, the preset unit speed increment, and the first weight of the average change amount of the hard disk resource and the second weight of the current change amount of the hard disk resource in the latest observation period after obtaining the average change amount of the hard disk resource.

[0173] Optionally, when the plurality of storage system resources include bandwidth resources, the target association relationship determining module includes:

[0174] an available bandwidth resource determination module, configured to determine, when the data migration task and the service IO share the same IO port, the bandwidth resources available for the data migration task based on the bandwidth resources occupied by the service IO;

[0175] The module for determining the increase in speed corresponding to the bandwidth resources is configured to determine the increase in speed corresponding to the bandwidth resources based on the bandwidth resources available for the data migration task.

[0176] Optionally, the device further comprises:

[0177] A first execution module is configured to, in a first observation period of an observation phase, not collect statistics on the changes in the multiple storage system resources obtained in the first observation period when the change in the storage system resources corresponding to the service IO is greater than a preset change or the storage system resources occupied by the service IO is greater than a first preset threshold;

[0178] The second execution module is used to not count the changes in multiple storage system resources obtained in the second observation period during the observation phase when the load corresponding to the business IO is greater than the second preset threshold and the data volume of the data migration task is less than the third preset threshold.

[0179] Optionally, the data migration task execution module 13 includes:

[0180] The data migration task execution unit is configured to calculate a target migration speed of the data migration task based on the smallest scalable speed increment among the multiple scalable speed increments and the current migration speed of the data migration task after the observation phase ends.

[0181] Optionally, the device further comprises:

[0182] The target migration speed adjustment module is used to adjust the target migration speed based on the changes in the resource demand of the business IO for multiple storage system resources and the target association relationship during the process of executing the data migration task according to the target migration speed.

[0183] Based on the same inventive concept, another embodiment of the present application further provides an electronic device, comprising a memory, a processor, and a computer program stored on the memory, wherein the processor executes the computer program to implement the data migration method as described in any of the above embodiments.

[0184] Based on the same inventive concept, another embodiment of the present application further provides a computer program product, including a computer program, which is executed by a processor to perform the data migration method described in any of the above embodiments.

[0185] Based on the same inventive concept, another embodiment of the present application further provides a computer-readable storage medium on which a computer program is stored, wherein when the program is executed by a processor, the data migration method as described in any of the above embodiments is implemented.

[0186] As for the device, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0187] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0188] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, devices, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0189] The embodiments of the present application are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0190] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0191] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0192] Although preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they become aware of the basic inventive concepts. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0193] Finally, it should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or terminal device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or terminal device that includes the element.

[0194] The above is a detailed introduction to the data migration method, device, equipment and medium provided by the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core ideas. At the same time, for general technical personnel in this field, based on the ideas of the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A data migration method, characterized in that: The method comprises: After the data migration task is started, during an observation phase, the migration speed of the data migration task is increased multiple times according to preset unit speed increments, and a target association relationship is determined by analyzing the changes in multiple storage system resources associated with the data migration task. The target association relationship is used to represent the association between the changes in the multiple storage system resources associated with the data migration task and the changes in the migration speed of the data migration task. Determining the speed increments that can be increased for each of the multiple storage system resources associated with the data migration task based on the target association relationship and the resource demands of the multiple storage system resources associated with the business IO; Based on the plurality of scalable speed increments, a target migration speed of the data migration task is determined, and the data migration task is executed according to the target migration speed.

2. The data migration method according to claim 1, characterized in that: The target association relationship is determined by the following steps: For each observation period of the observation phase, increasing the migration speed according to the preset unit speed increment, and determining a change in a plurality of storage system resources associated with the data migration task during the observation period; After the observation phase ends, statistics are collected on the changes in the plurality of storage system resources corresponding to each observation period to obtain statistical results; Based on the statistical results, the target association relationship is determined.

3. The data migration method according to claim 2, wherein: The multiple storage system resources include at least CPU resources, memory resources, and hard disk resources. The determining the target association relationship based on the statistical result includes: Based on the statistical results, for each storage system resource associated with the data migration task, calculate an average change in the storage system resource after the migration speed of the data migration task is increased by a preset unit speed increment; determining the target association relationship based on a correspondence between the preset unit speed increment and an average change in the plurality of storage system resources; The determining, based on the target association relationship and the resource requirements of the multiple storage system resources associated with the business IO, the corresponding respective speed increments of the multiple storage system resources associated with the data migration task includes: Calculating the speed increments corresponding to the plurality of storage system resources based on first resource margins currently available for the data migration task and the target association relationship; The first resource margin is determined based on the total amount of the multiple storage system resources, the resource demand of the service IO for the multiple storage system resources, and the reserved resource amount of the multiple storage system resources.

4. The data migration method according to claim 3, wherein: The method further comprises: Determining, based on a type of a hard disk corresponding to the hard disk resource associated with the data migration task, a statistical time interval corresponding to the hard disk; Based on the statistical time interval, in a first statistical period before the start of the observation phase, the number of times the hard disk is in a busy state is counted, and a first hard disk resource occupancy rate of the hard disk resource before the start of the observation phase is calculated; Based on the statistical time interval, within multiple observation cycles after the start of the observation phase, the number of times the hard disk is in a busy state is counted, and multiple second hard disk resource occupancy rates of the hard disk resource in the observation phase are calculated; Calculating an average change in the hard disk resource based on the plurality of second hard disk resource occupancy rates and the first hard disk resource occupancy rate; After obtaining the average change of the hard disk resource, the average change of the hard disk resource is updated based on the current change of the hard disk resource in the latest observation period, the average change of the hard disk resource, the preset unit speed increment, and the first weight of the average change of the hard disk resource and the second weight of the current change of the hard disk resource in the latest observation period.

5. The data migration method according to claim 2, wherein: In a case where the plurality of storage system resources include bandwidth resources, the method further includes: When the data migration task and the service IO share the same IO port, determining the bandwidth resources available for the data migration task based on the bandwidth resources occupied by the service IO; Based on the bandwidth resources available for the data migration task, a speed increment corresponding to the bandwidth resources is determined.

6. The data migration method according to claim 2, wherein: The method further comprises: In the first observation period of the observation phase, when the change in the storage system resources corresponding to the service IO is greater than a preset change or the storage system resources occupied by the service IO are greater than a first preset threshold, statistics are not collected on the change in the multiple storage system resources obtained in the first observation period; In the second observation period of the observation phase, when the load corresponding to the business IO is greater than the second preset threshold and the data volume of the data migration task is less than the third preset threshold, the changes in the multiple storage system resources obtained in the second observation period are not counted.

7. The data migration method according to claim 2, characterized in that: The step of determining a target migration speed of the data migration task based on the plurality of speed-increase increments includes: A target migration speed of the data migration task is calculated based on a minimum scalable speed increment among a plurality of scalable speed increments and a current migration speed of the data migration task after the observation phase ends.

8. The data migration method according to any one of claims 1 to 7, characterized in that: The method further comprises: In the process of executing the data migration task according to the target migration speed, the target migration speed is adjusted based on changes in resource demands of the service IO on multiple storage system resources and the target association relationship.

9. A data migration device, characterized in that: The device comprises: An observation module is configured to, after a data migration task is initiated, increase the migration speed of the data migration task multiple times according to preset unit speed increments during an observation phase, and determine a target association relationship by analyzing changes in multiple storage system resources associated with the data migration task, wherein the target association relationship is used to represent an association between changes in the multiple storage system resources associated with the data migration task and changes in the migration speed of the data migration task; a module for determining an increase in speed that can be increased, configured to determine an increase in speed that can be increased for each of the plurality of storage system resources associated with the data migration task based on the target association relationship and the resource demand of the plurality of storage system resources associated with the business IO; The data migration task execution module is configured to determine a target migration speed of the data migration task based on the plurality of speed-increasing increments, and execute the data migration task according to the target migration speed.

10. An electronic device, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the data migration method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that A computer program is stored thereon, wherein when the computer program is executed by a processor, the data migration method according to any one of claims 1 to 8 is implemented.

Images