Storage space management method, device, electronic device, storage medium and product

Abstract

The present application discloses a storage space management method, device, electronic device, storage medium, and product, including: classifying multiple disks of the same storage cluster according to a preset strategy to obtain multiple logical pools, wherein a logical pool includes at least two disks; when the type of the storage volume to be created is the first type, creating a first storage volume of the first type in a target logical pool among the multiple logical pools, wherein the data contained in the first storage volume is distributed and stored in the multiple disks of the target logical pool, and the data of the first type storage volumes in different logical pools are isolated from each other. The impact range of the failure is limited to a logical pool, avoiding the spread of the failure and improving the reliability and stability of the distributed storage system.

Description

Technical Field

[0001] The present application relates to the field of computers, and more specifically, to a storage space management method, device, electronic device, computer-readable storage medium, and computer program product. Background Art

[0002] In the era of cloud computing and big data, with the continuous growth of data volume, distributed storage systems have emerged. Distributed storage systems provide high-availability and high-efficiency data services by distributing data across multiple nodes and utilizing redundant storage and parallel processing of data.

[0003] However, traditional distributed storage systems lack reliability and stability. Summary of the Invention

[0004] The present application provides a storage space management method, device, electronic device, computer-readable storage medium, and computer program product to at least solve the problem of insufficient reliability and stability of distributed storage systems in related technologies.

[0005] The present application provides a storage space management method, which is applied to a distributed storage system, wherein the distributed storage system includes a storage cluster, and the storage cluster includes multiple disks. The method includes: classifying multiple disks of the same storage cluster according to a preset policy to obtain multiple logical pools, wherein a logical pool includes at least two disks; when the type of the storage volume to be created is a first type, creating a first storage volume of the first type in a target logical pool among the multiple logical pools, wherein the data contained in the first storage volume is distributed and stored in the multiple disks of the target logical pool, and the data of the first type storage volumes in different logical pools are isolated from each other.

[0006] The present application also provides a storage space management device, including:

[0007] A disk classification module is used to classify multiple disks in the same storage cluster according to a preset policy to obtain multiple logical pools, wherein a logical pool includes at least two disks;

[0008] A storage volume creation module is used to create a first storage volume of the first type in a target logical pool among multiple logical pools when the type of the storage volume to be created is the first type, wherein the data contained in the first storage volume is distributed and stored in multiple disks of the target logical pool, and the data of the first type storage volumes in different logical pools are isolated from each other.

[0009] The present application also provides an electronic device, comprising: a memory for storing a computer program; and a processor for implementing the steps of any of the above-mentioned storage space management methods when executing the computer program.

[0010] The present application also provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above-mentioned storage space management methods are implemented.

[0011] The present application also provides a computer program product, including a computer program, which implements the steps of any of the above-mentioned storage space management methods when executed by a processor.

[0012] Through the storage space management method of the present application, multiple disks of the same storage cluster are classified according to a preset strategy and divided into multiple logical pools, thereby realizing refined management of disk resources. By forming logical pools through disk classification, the distributed storage system can more effectively manage and utilize its internal resources, avoiding waste of resources and the emergence of performance bottlenecks. Disks can be classified according to user needs, so that the characteristics or performance of disks in a logical pool are as consistent as possible, reducing performance fluctuations and improving the stability of the storage system. This classification strategy can ensure that storage volumes with different performance requirements are created on the most suitable disk collection, thereby improving data processing efficiency and the overall performance of the storage system. By distributing and storing data in multiple disks of the target logical pool, not only is the storage space of the disk fully utilized, but also, through data isolation logic, it is ensured that data in different logical pools will not interfere with each other. The data isolation strategy effectively prevents data from being mixed between volumes with different business or performance requirements, thereby enhancing data security and stability. Since the data of the first storage volume is only distributed and stored in the target logical pool, even if a fault occurs in the target logical pool, it will only affect the data of the first storage volume, and will not affect the data in other logical pools, thus avoiding the spread of the fault. The scope of influence of the fault is limited to one logical pool, which greatly reduces the impact of the fault on the storage system and improves the reliability of the storage system. Therefore, the technical problem of insufficient reliability and stability of the distributed storage system in the related technology can be solved, and the technical effect of improving the reliability and stability of the distributed storage system can be achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. 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.

[0014] Figure 1 This is a hardware structure block diagram of a server device according to a storage space management method according to an embodiment of the present application;

[0015] Figure 2is a flowchart of a storage space management method according to an embodiment of the present application;

[0016] Figure 3 is a schematic structural diagram of a logic pool according to an embodiment of the present application;

[0017] Figure 4 This is a second flowchart of a storage space management method according to an embodiment of the present application;

[0018] Figure 5 This is a second structural diagram of a logic pool according to an embodiment of the present application;

[0019] Figure 6 This is a third flowchart of a storage space management method according to an embodiment of the present application;

[0020] Figure 7 This is a fourth flowchart of a storage space management method according to an embodiment of the present application;

[0021] Figure 8 This is a fifth flowchart of a storage space management method according to an embodiment of the present application;

[0022] Figure 9 This is a sixth flowchart of a storage space management method according to an embodiment of the present application;

[0023] Figure 10 This is a seventh flowchart of a storage space management method according to an embodiment of the present application;

[0024] Figure 11 This is a third structural diagram of a logic pool according to an embodiment of the present application;

[0025] Figure 12 This is an eighth flowchart of a storage space management method according to an embodiment of the present application;

[0026] Figure 13 is a ninth flowchart of a storage space management method according to an embodiment of the present application;

[0027] Figure 14 is a tenth flowchart of a storage space management method according to an embodiment of the present application;

[0028] Figure 15 This is a flowchart of a storage space management method according to an embodiment of the present application;

[0029] Figure 16 is a twelfth flowchart of a storage space management method according to an embodiment of the present application;

[0030] Figure 17This is a fourth structural diagram of a logic pool according to an embodiment of the present application;

[0031] Figure 18 This is a fifth structural diagram of a logic pool according to an embodiment of the present application;

[0032] Figure 19 is a thirteenth flowchart of a storage space management method according to an embodiment of the present application;

[0033] Figure 20 is a fourteenth flowchart of a storage space management method according to an embodiment of the present application;

[0034] Figure 21 This is a sixth structural diagram of a logic pool according to an embodiment of the present application;

[0035] Figure 22 This is a structural block diagram of a storage space management device according to an embodiment of the present application. DETAILED DESCRIPTION

[0036] The following will be combined with the accompanying 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 only 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.

[0037] It should be noted that, in the description of this application, the terms "comprises," "includes," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device comprising 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 device. The terms "first," "second," etc., in this application are used to distinguish similar objects, and are not used to describe a particular order or sequence.

[0038] In order to enable those skilled in the art to better understand the present application, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0039] In conjunction with the specific application environment architecture or specific hardware architecture on which the execution of the storage space management method depends, the specific application environment architecture or specific hardware architecture is described herein.

[0040] The storage space management method embodiment provided in the embodiment of the present application can be executed in a server device or a similar computing device. Taking running on a server device as an example, Figure 1This is a hardware structure diagram of a server device for a storage space management method according to an embodiment of the present application. Figure 1 As shown, the server device may include one or more ( Figure 1 Only one is shown) a processor 102 (the processor 102 may include but is not limited to a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data. The server device may also include a transmission device 106 and an input / output device 108 for communication functions. It will be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above server device. Figure 1 More or fewer components than shown, or with Figure 1 Different configurations shown.

[0041] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the storage space management method in the embodiment of the present application. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, implementing the above method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include a memory remotely located relative to the processor 102, and these remote memories can be connected to the server device via a network. Examples of the above-mentioned network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0042] Transmission device 106 is used to receive or transmit data via a network. A specific example of the aforementioned network may include a wireless network provided by a communication provider of the server device. In one embodiment, transmission device 106 includes a network interface controller (NIC), which can be connected to other network devices via a base station to enable communication with the Internet. In another embodiment, transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0043] As described in the background technology, in existing distributed storage clusters, once a node fails, not only will data access on that node be affected, but due to the tight coupling of data distribution, the data stored on other nodes may also need to be redistributed, which will trigger a large amount of data migration and reconstruction activities, thereby affecting the read and write performance of the entire cluster. In response to the above technical problems, the fault isolation capability of the storage cluster of the distributed storage system is insufficient, that is, when a node fails, it may affect the performance of the entire storage cluster, resulting in insufficient reliability of the distributed storage system. In order to solve the above problems, improve the reliability of the distributed storage system, and reduce the impact of a single node failure on the entire cluster, the storage space management method of the present application is proposed.

[0044] The embodiment of the present application provides a storage space management method, which is applied to the above-mentioned server device. The server device can be a distributed storage system, which includes a storage cluster. The storage cluster includes multiple disks. The method is described in detail in conjunction with the execution process of the storage space management method. Figure 2 As shown, the method includes the following steps S200-210:

[0045] Step S200 , classifying multiple disks of the same storage cluster according to a preset policy to obtain multiple logical pools.

[0046] A logical pool includes at least two disks.

[0047] Specifically, disk resources within the storage cluster are categorized based on pre-set policies to form multiple logical pools. Each logical pool contains multiple disks that collectively serve specific data storage needs. This categorization provides customized storage environments for different storage volumes based on factors such as disk performance, type, or geographic location.

[0048] For example, pre-defined policies can be based on disk performance (such as input / output operations per second (IOPS) and throughput), disk type (SSD, HDD), redundancy requirements, or other business needs to guide disk classification. A logical pool is a storage area abstracted from disk resources, with independent storage policies and redundancy mechanisms, and can be considered a logical unit for resource management.

[0049] Step S210 : When the type of the storage volume to be created is the first type, a first storage volume of the first type is created in a target logical pool among the multiple logical pools.

[0050] The data contained in the first storage volume is distributed and stored in multiple disks of the target logical pool, and the data of the first type of storage volumes in different logical pools are isolated from each other.

[0051] Specifically, when a storage volume of a specific type (such as high performance, high redundancy, or low cost) is required, the system selects a target logical pool from multiple logical pools to create the volume based on the preset policy and storage volume type. This ensures that data is stored in an environment that meets its storage characteristics, improving data access efficiency and reliability. A first storage volume of the first type is designed to be distributed and stored only within a single logical pool. Data in first storage volumes of the first type within different logical pools is isolated from each other.

[0052] For example, Figure 3 As shown, a storage cluster may include multiple storage nodes (node A, node B, node C, node D, node E). A storage node may be a physical node or a logical node in the storage cluster. A storage node may be an entity consisting of a set of disks, networks, memories, and central processing units (CPUs). Each storage node includes a set of disks. By classifying multiple disks, we can obtain, for example, Figure 3 Logical pool 10 and logical pool 20 are shown.

[0053] In this embodiment, multiple disks within the same storage cluster are classified according to a preset strategy, resulting in multiple logical pools. This enables refined management of disk resources. By classifying disks into logical pools, the distributed storage system can more effectively manage and utilize its internal resources, avoiding resource waste and performance bottlenecks. Disks can be classified according to user needs, ensuring that the characteristics or performance of disks within a logical pool are as consistent as possible, reducing performance fluctuations and improving storage system stability. This classification strategy ensures that storage volumes with different performance requirements are created on the most suitable set of disks, thereby improving data processing efficiency and overall storage system performance. By distributing and storing data in multiple disks of the target logical pool, not only is the storage space of the disk fully utilized, but also, through data isolation logic, it is ensured that data in different logical pools will not interfere with each other. The data isolation strategy effectively prevents data from being mixed between volumes with different business or performance requirements, thereby enhancing data security and stability. Since the data of the first storage volume is only distributed and stored in the target logical pool, even if a fault occurs in the target logical pool, it will only affect the data of the first storage volume, and will not affect the data in other logical pools, thus avoiding the spread of the fault. The scope of influence of the fault is limited to one logical pool, which greatly reduces the impact of the fault on the storage system and improves the reliability of the storage system. Therefore, the technical problem of insufficient reliability and stability of the distributed storage system in the related technology can be solved, and the technical effect of improving the reliability and stability of the distributed storage system can be achieved.

[0054] In one embodiment, Figure 4 As shown, step S200, multiple disks of the same storage cluster are classified according to a preset strategy to obtain multiple logical pools. It includes: steps S400-S420:

[0055] Step S400: determining disk parameters of multiple disks in the same storage cluster.

[0056] Specifically, basic information and performance metrics of all disks in the storage cluster are collected to serve as the basis for subsequent classification. This includes disk type (SSD or HDD), read / write speed, latency, available capacity, and disk combination (Redundant Array of Independent Disks, RAID) level.

[0057] Step S410 : matching a corresponding disk classification strategy to the business demand in response to the business demand of the target object.

[0058] Specifically, based on the business needs of the target object (such as an application, database, or specific user data), the system will select or automatically generate the most appropriate disk classification policy. This ensures that different business needs are matched to the most appropriate disk resources, improving the targeted and efficient allocation of resources.

[0059] For example, a business needs analysis engine can be built, with inputs including business performance requirements (such as input / output (I / O) intensiveness or CPU intensiveness), data volume, redundancy requirements, and cost budget. The results of the business needs analysis engine are used to dynamically generate or select disk classification policies. For example, for applications requiring high I / O performance, the policy will tend to select logical pools with abundant SSD resources.

[0060] Step S420 : Classify the multiple disks according to the disk classification policy and the disk parameters of the multiple disks to obtain multiple logical pools.

[0061] Specifically, after clarifying the classification strategy that matches disk parameters with business needs, the system begins to allocate disks to different logical pools based on the strategy. Each logical pool will focus on serving a type of business need to achieve optimal resource configuration and management.

[0062] For example, disks can be automatically assigned to corresponding logical pools based on disk parameters and a matching disk classification policy. A logical pool structure is created, and disk identifications (IDs) are added to the corresponding pool list. Storage policies and redundancy mechanisms, such as the number of data replicas and erasure code (EC) encoding parameters, are defined for each logical pool to ensure that data distribution and fault tolerance within the logical pool meet business requirements.

[0063] For example, Figure 5 As shown, the storage cluster may include multiple storage nodes (node A, node B, node C), each storage node includes a group of disks, and by classifying multiple disks, we can get, for example Figure 5 Logical pool 30, logical pool 40, and logical pool 50 are shown.

[0064] In this embodiment, by accurately collecting disk parameters and intelligently matching them to business needs, the system can automatically generate or dynamically adjust disk classification strategies, enabling intelligent and personalized configuration of storage resources to maximize business needs and improve resource utilization. The classification strategy design takes into account the performance differences and cost factors of different disk types, ensuring that high-cost, high-performance disk resources serve applications with high I / O requirements, while low-cost disk resources are used for cost-sensitive data storage, thereby achieving an optimal balance between performance and cost. The creation of logical pools not only optimizes data distribution but also allows for independent redundancy policies to be set for each pool, improving data reliability and security. In the event of a single disk or node failure, data can still be recovered from resources in other pools, reducing the risk of data loss. Through the above steps, the distributed storage system can more intelligently and efficiently manage storage resources, not only improving data storage and access performance, but also demonstrating significant advantages in cost control, data security, and system management, providing strong support for building highly available, high-performance cloud storage solutions. By matching disk classification strategies to business needs, data can be stored on disks that best suit its characteristics, thereby improving data processing efficiency and reducing data access latency. This method is particularly suitable for distributed storage systems that need to handle diverse business needs, and can effectively solve problems such as unreasonable resource allocation and low data processing efficiency.

[0065] In one embodiment, Figure 6 As shown, step S420, classifying multiple disks according to the disk classification strategy and the disk parameters of the multiple disks to obtain multiple logical pools. It includes: steps S600-S630:

[0066] Step S600 : determining the read and write modes of the plurality of disks according to the disk parameters of the plurality of disks.

[0067] Specifically, based on disk parameters such as read and write speed, I / O latency, disk type, etc., the read and write mode of each disk, i.e., I / O intensive or CPU intensive, is determined, which helps to improve the accuracy of subsequent classification.

[0068] For example, data analysis tools can be used to regularly collect and analyze disk read and write operation statistics, such as average I / O latency, I / O operations per second (IOPS), and throughput. Based on the statistical results and threshold settings, disks can be labeled as I / O-intensive (high-speed read and write) or CPU-intensive (low-speed read and write), or the disk's read and write pattern can be determined by the disk type (SSD, HDD). For example, SSD disks with faster read and write speeds can be classified as the first type of disks to form a high-performance first logical pool; HDD disks with slower read and write speeds can be classified as the second type of disks to form a large-capacity second logical pool. This classification method ensures that data is stored on the disk that best suits its access pattern, thereby improving data read and write efficiency and reducing data access latency.

[0069] Step S610 : determining a first type of disk and a second type of disk among the plurality of disks according to the respective read and write modes of the plurality of disks.

[0070] The read and write modes of the first type of disk are different from those of the second type of disk, and the read and write speed of the first type of disk is greater than that of the second type of disk.

[0071] Specifically, after clarifying the read and write patterns of the disks, the system divides the disks into two categories. The read and write speeds of the first category of disks are significantly higher than those of the second category of disks. This classification lays the foundation for creating logical pools with different performance characteristics.

[0072] Step S620: Select a first preset number of first type disks from the plurality of disks as a common set to obtain at least one first logical pool. And,

[0073] Step S630 : Select a second preset number of first-type disks and a third preset number of second-type disks from the plurality of disks as a common set to obtain at least one second logical pool.

[0074] Specifically, after disk classification is complete, the system selects a certain number of disks from the first category to create the first logical pool, and selects a portion of disks from both the first and second categories to create the second logical pool, based on preset quantity parameters. Each logical pool will have independent data distribution and redundancy strategies to meet the needs of different business types.

[0075] For example, the system selects a fixed number of disks (a first preset number) from the disks marked as Class 1 (high-speed read / write) to form a high-speed logical pool. This is typically suitable for applications that require frequent reads and writes and high I / O performance. The system also selects a fixed number of disks (a second preset number and a third preset number) from both Class 1 and Class 2 to form a hybrid logical pool, balancing read / write speed and cost-efficiency. This type of logical pool is suitable for businesses with a relatively balanced read / write profile or cost-sensitive operations.

[0076] In this embodiment, by classifying disks according to their read and write modes and creating logical pools with different performance characteristics, this method significantly improves the resource management efficiency and data service flexibility of the distributed storage system. Specifically, the I / O-intensive first logical pool can provide excellent read and write performance, ensuring the smooth operation of high-performance applications; while the hybrid second logical pool takes into account cost control while providing reasonable read and write speeds, and is suitable for processing large amounts of data with medium performance requirements. In this way, the system can not only intelligently schedule storage resources according to business needs and improve data access speed and efficiency, but also enhance data reliability and security and reduce potential data loss risks by reasonably configuring redundancy strategies for different logical pools. At the same time, this mechanism simplifies storage management and allows the system to dynamically adjust resource allocation to cope with changing business and data scales, thereby improving the stability and scalability of the storage cluster and providing efficient, flexible and secure resource management solutions for various distributed storage environments.

[0077] In one embodiment, Figure 7 As shown, step S420, classifying multiple disks according to the disk classification strategy and the disk parameters of the multiple disks to obtain multiple logical pools. It includes: steps S700-S710:

[0078] Step S700 : determining the disk models and disk capacities of the multiple disks according to the disk parameters of the multiple disks.

[0079] Specifically, the specific hardware information of all disks in the storage cluster, namely the disk model and disk capacity, is systematically identified to provide a basis for subsequent disk classification and logical pool creation.

[0080] Step S710 , classifying disks with the same disk model and the same disk capacity among the plurality of disks into the same set according to the respective disk models and disk capacities of the plurality of disks, so as to obtain a plurality of logical pools.

[0081] Specifically, the system categorizes disks with consistent hardware characteristics into the same logical pool based on disk model and capacity, forming a collection of storage resources with homogeneous hardware. This process helps optimize data distribution and redundancy strategies, improves storage efficiency and data access speed, and simplifies storage management.

[0082] In this embodiment, through the above two steps, the distributed storage system realizes intelligent classification of disks based on hardware characteristics and fine construction of logical pools. First, the precise classification of disks enables the system to schedule resources according to the actual capabilities of the disks, avoiding performance losses and uneven resource allocation caused by hardware mismatch. Second, the creation of logical pools simplifies the process of data storage and access. A collection of disks with the same hardware characteristics can provide a more consistent storage environment for data, enhance the system's storage capacity and data access efficiency, and reduce system delays caused by disk performance fluctuations. In addition, the construction of logical pools based on hardware homogeneity also optimizes the implementation of data redundancy strategies, allowing data replication and recovery operations to be performed under similar hardware conditions, improving the speed and reliability of data recovery and reducing the risk of data loss. Finally, this classification and construction method greatly simplifies the management complexity of the storage system, facilitates the dynamic adjustment and expansion of the system, and ensures that the system can maintain efficient and stable operation when facing diverse storage needs. In summary, by implementing precise classification and logical pool construction strategies based on disk hardware parameters, the distributed storage system not only improves resource utilization efficiency and data service performance, but also enhances system reliability, maintainability, and scalability, providing technical support for building an efficient, stable, and flexible cloud storage environment. This refined management approach enables the system to more intelligently respond to dynamically changing business needs, ensuring data security and continuous system optimization.

[0083] In one embodiment, Figure 8 As shown, in step S210, when the type of the storage volume to be created is the first type, a first storage volume of the first type is created in a target logical pool among the multiple logical pools. The steps include: S800-S820:

[0084] Step S800: Determine the type of storage volume to be created according to the creation request of the target object.

[0085] Specifically, when a request to create a storage volume is received, the system's primary task is to identify the storage volume type specified in the request to determine subsequent creation parameters and policies.

[0086] Exemplarily, the creation request is parsed to extract information about the storage volume type, such as whether it is a high-performance volume, a low-cost volume, or a volume with specific redundancy requirements, and whether the storage volume is stored only within a single logical pool or can span multiple logical pools. Based on the parsed type information, the corresponding storage volume creation policy is invoked to prepare for the creation process.

[0087] Step S810: When it is determined that the type of the storage volume to be created is the first type, a target logical pool is determined from a plurality of logical pools according to the performance requirement of the storage volume carried in the creation request.

[0088] Specifically, the system further analyzes the performance requirements of the storage volume, such as I / O rate, latency level, and redundancy, and selects a specific logical pool from multiple logical pools that best suits the storage volume type.

[0089] For example, the system evaluates performance metrics in the request, such as read / write speed, data redundancy level, and storage cost budget. It searches the logical pool database, compares the hardware characteristics of each logical pool (such as disk type and average I / O performance) with the required storage volume performance, and selects the logical pool that best matches the requirements as the target logical pool. It ensures that the target logical pool has sufficient remaining capacity and the necessary hardware specifications to meet the requirements for creating a high-performance Type 1 storage volume.

[0090] For example, a request might create a high-performance storage volume or a large-capacity storage volume. Based on the performance requirements in the request, the system automatically selects the most appropriate logical pool to create the storage volume. For example, if the request requires a high-performance storage volume, the system selects disks from the high-performance logical pool to create the storage volume; if the request requires a large-capacity storage volume, the system selects disks from the large-capacity logical pool to create the storage volume.

[0091] Step S820: Create a first storage volume of a first type in the target logical pool, and distribute and store data in the first storage volume in multiple disks of the target logical pool according to a preset data distribution strategy.

[0092] The data isolation logic is set to isolate the data of the first type of storage volumes in different logical pools from each other.

[0093] Specifically, after selecting the target logical pool, the next task is to create a storage volume in the logical pool and store data on the disks in the logical pool using a preset data distribution strategy while ensuring data isolation of the first storage volume across the logical pools.

[0094] For example, executing a storage volume creation command generates a new storage volume instance within the target logical pool and marks it as type one. Pre-defined data distribution strategies (such as EC-encoded redundancy strategies and RAID levels) are applied to evenly distribute the data in the storage volume across the disks within the logical pool, ensuring high data availability and read / write performance. Data isolation logic is implemented, and through metadata management and access control mechanisms, first storage volumes in different logical pools are prohibited from directly accessing each other's data, ensuring data security and business independence.

[0095] In this embodiment, firstly, the precise storage volume type is determined based on the performance requirements of the target object, which ensures the rational allocation of resources and avoids performance bottlenecks and resource waste caused by type errors. Secondly, by creating storage volumes in a logical pool that matches the hardware characteristics, the system can maximize the use of disk performance and provide users with expected read and write speeds and data access experience. In addition, the use of data distribution strategies ensures the redundancy and high availability of data. Even if a single disk fails, the data can be quickly recovered from other disks in the logical pool, enhancing the fault tolerance of the system. Most importantly, the setting of data isolation logic significantly improves data security. The data between different logical pools is completely isolated. Even for storage volumes of the same type, illegal data access and potential data leakage risks can be avoided, thereby maintaining the overall data privacy and compliance of the system. In summary, this method not only optimizes resource allocation and data service performance, but also strengthens data management and security, providing technical guarantees for the efficient and stable operation of distributed storage systems and user data protection.

[0096] In one embodiment, Figure 9 As shown, in step S820, after creating a first storage volume of the first type in the target logical pool and distributing and storing data in the first storage volume on multiple disks of the target logical pool according to a preset data distribution strategy, the method further includes steps S900-S910:

[0097] Step S900: Create a first data copy of a first storage volume in a target logical pool.

[0098] The first data copy is stored in at least one first backup disk in the target logical pool.

[0099] Specifically, when the system creates a storage volume, it also creates data copies on multiple disks within the target logical pool based on a pre-set redundancy policy. These backup disks are used to store data copies, aiming to improve data durability and availability.

[0100] For example, when creating the first storage volume in the target logical pool, the number of copies and the distribution mode are determined according to the policy (such as simple copy, EC encoding, etc.). Backup disks in the logical pool that meet the policy requirements are selected, and data copies are written to these disks.

[0101] Step S910 : When it is determined that a faulty disk exists in the target logical pool, data on the faulty disk is recovered using a first data copy stored in at least one first backup disk.

[0102] Specifically, when a disk failure is detected in the target logical pool, the system automatically restores the data on the failed disk using data copies stored on other backup disks, maintaining storage volume integrity and service continuity. If a disk fails within the target logical pool, data can be quickly restored from the backup disk, reducing the risk of data loss and improving system availability. Furthermore, the failure of any disk only affects the data storage services within the pool, achieving fault domain isolation based on the logical pool. Data recovery can also be performed within the logical pool, accelerating recovery times.

[0103] For example, the operating status of the disks in the logical pool is continuously monitored. Once a disk failure is detected, the failure recovery process is immediately triggered. A complete data copy stored on the backup disk is searched for. Based on the data distribution and redundancy strategy, an appropriate copy is selected for data recovery. The data recovery operation is executed, migrating or copying the copy data on the backup disk to a replacement disk for the failed disk, restoring the data integrity of the storage volume.

[0104] In this embodiment, by implementing the above two steps, the method of the present invention effectively improves the data persistence and service quality of the distributed storage system. First, the creation of the first data copy builds a stable data redundancy mechanism within the target logical pool. Even in the face of a single point of failure, the data can maintain integrity and ensure the continuous operation of the business. Secondly, the fault recovery strategy can be implemented directly within the logical pool, greatly shortening the data recovery time and system interruption time, reducing the risk of data service delays and business interruptions caused by disk failures, and enhancing the system's fault tolerance and recovery efficiency. Furthermore, by performing copy storage and fault recovery within the logical pool, the system can avoid data migration operations across logical pools, reducing network transmission delays and processing overhead, and optimizing data access performance. At the same time, this strategy also simplifies the fault recovery management process, focusing on the logical pool, improving the accuracy and speed of system recovery operations, and reducing the risk of data consistency during the recovery process. In summary, by creating data copies within the target logical pool and implementing automatic fault recovery, the distributed storage system not only enhances data persistence and availability, but also optimizes the fault response mechanism, significantly shortens business interruption time, and ensures the efficient and stable data service and the security of user data. This data management method provides strong technical support for building a high-availability, high-performance cloud storage environment.

[0105] In one embodiment, Figure 10 As shown, after determining the type of the storage volume to be created according to the creation request of the target object in step S800, the method further includes steps S1000-S1020:

[0106] Step S1000: When the type of the storage volume to be created is the second type, at least two target logical pools are determined from multiple logical pools according to the performance requirements and redundancy requirements of the storage volume carried in the creation request.

[0107] Specifically, when the system receives a request to create a stretched storage volume (i.e., the second type of storage volume), it will select at least two suitable target logical pools from the existing multiple logical pools based on the performance indicators required by the storage volume (such as IOPS, throughput) and redundancy strategy (such as the number of replicas, EC encoding strategy).

[0108] For example, the creation request is analyzed to extract parameters related to performance and redundancy requirements. A pre-defined logical pool attribute matching algorithm is used to select logical pools that meet these requirements, ensuring they can support the data distribution and redundancy policies of the extended storage volume. Matching logical pools are then re-verified for health and resource allocation to avoid selecting logical pools with potential risks or insufficient resources.

[0109] Step S1010: Create a second storage volume of a second type in at least two target logical pools respectively.

[0110] The data contained in the second storage volume is distributed and stored in multiple disks of at least two target logical pools.

[0111] Specifically, in the selected logical pool, the system will create an extended second storage volume, and the data will be dispersedly stored on multiple disks in these logical pools according to a preset distribution strategy, such as balanced distribution or consistent hash ring.

[0112] Exemplarily, within each selected target logical pool, a storage volume initialization process is executed to generate a second type of storage volume instance. A data distribution algorithm is applied to evenly divide the data in the storage volume and store it across the disks within each logical pool, ensuring that each target logical pool contains a complete copy of the data to meet redundancy requirements. A metadata management system is updated to record the data distribution location and redundancy information across the logical pools to facilitate fault recovery and data access.

[0113] Step S1020: Establish a first association relationship between at least two target logical pools that have stored the same second storage volume.

[0114] Specifically, the system will ensure that a close first-order association relationship is established between multiple logical pools storing data of the same extended storage volume by defining and implementing association rules to support functions such as data synchronization, redundancy management, and fault recovery.

[0115] For example, association rules are created to define the frequency, priority, and conflict resolution mechanism for data synchronization between logical pools. Association rules are implemented to establish data consistency between target logical pools through data distribution and synchronization protocols. Storage volume metadata is updated to record the association status and data distribution details of the associated logical pools, facilitating subsequent management operations such as fault detection and data recovery.

[0116] For example, Figure 11 As shown, a storage cluster may include multiple storage nodes (node A, node B, node C, node D, node E). A storage node may be a physical node or a logical node in the storage cluster. By classifying multiple disks, we can obtain, for example, Figure 11 As shown, the logical pool 60 and the logical pool 70 establish a first association relationship between the logical pool 60 and the logical pool 70 .

[0117] In this embodiment, first, by creating and storing extended storage volumes in multiple logical pools, the system can dynamically adjust the data distribution strategy according to actual needs and optimize the utilization efficiency of storage resources. Secondly, the redundant storage of data across logical pools ensures that even in the event of a failure in a single logical pool or disk, the system can still quickly restore the data through complete data copies in other logical pools, maintaining high data availability and persistence. Establishing an association relationship between logical pools not only achieves efficient synchronization and consistent management of data, but also provides the system with a higher level of disaster recovery and fault recovery capabilities. This association mechanism simplifies the fault detection process of the storage system and accelerates the data recovery speed. At the same time, it also provides a strong guarantee for the continuity and consistency of data, ensuring the smooth operation of the business and the continuity of the user experience. In summary, by creating an extended second storage volume in at least two target logical pools and establishing an association relationship between them, the system's ability to handle large data sets and complex business scenarios is effectively improved, the flexibility and reliability of data distribution are achieved, and the fault recovery process is optimized, providing users with continuous, reliable, and high-performance data storage services.

[0118] In one embodiment, Figure 12 As shown, the method further includes: steps S1200-S1210:

[0119] Step S1200: Create at least one second data copy of the second storage volume in at least two target logical pools that have stored the same second storage volume.

[0120] The second data copy is stored in at least one second backup disk in at least two target logical pools respectively.

[0121] Specifically, to enhance the redundancy and continuous availability of storage volume data, the system creates and stores at least one data replica within each target logical pool storing the secondary storage volume data. These replicas are placed on backup disks within each logical pool, ensuring distributed redundancy and fast access to data.

[0122] Exemplarily, for each target logical pool, a data replica creation process is initiated, and the number of replicas and their storage locations are determined based on the data redundancy policy. An appropriate location is selected on each logical pool's backup disk to store the second data replica, which may depend on the disk's current utilization and health, as well as the data distribution algorithm. Metadata information is updated to record the exact location and redundancy status of each second data replica, facilitating subsequent fault detection and data recovery operations.

[0123] Step S1210 : When it is determined that a faulty disk exists in one of the at least two target logical pools, data on the faulty disk is recovered using a second data copy stored in at least one second backup disk in the at least two target logical pools.

[0124] Specifically, once a disk failure is detected in any target logical pool, the system immediately executes the fault recovery process and uses the second data copy in other target logical pools to rebuild the data on the failed disk, thereby quickly restoring data services and the continuity of system operation.

[0125] For example, the status of the disks in each logical pool is continuously monitored. Once a failed disk is detected, a data recovery mechanism is immediately triggered. Based on the metadata records, a valid second data copy is located. These copies may come from backup disks in the same or different target logical pools. A data recovery algorithm is executed to migrate the data in the second data copy to a replacement location on the failed disk, ensuring data integrity and continuous system operation.

[0126] In this embodiment, firstly, the creation of the second data copy ensures that even if a single logical pool or disk fails, the system can still quickly restore data services by relying on redundant data copies in other logical pools, thus avoiding business interruptions and enhancing the fault tolerance of the system. Secondly, the storage of data copies across logical pools not only improves the redundancy level of data, but also optimizes the data recovery process. Even if the data in one logical pool is completely unavailable, the system can recover data from other logical pools, ensuring the continuity and efficiency of data services. The above mechanism simplifies the operations of fault detection and data recovery, reduces the burden on system operation and maintenance personnel through metadata management and automated recovery processes, and improves the response speed and processing capabilities of the storage system in the face of complex fault scenarios. Overall, the creation of a copy of the second storage volume and the cross-logical pool fault recovery mechanism significantly improve the data security and business continuity of the distributed storage system, laying a solid foundation for building a highly reliable cloud storage environment.

[0127] In one embodiment, Figure 13 As shown, step S1210 uses the second data copy stored in at least one second backup disk in at least two target logical pools to recover the data of the failed disk. It includes: steps S1300-S1330:

[0128] Step S1300 : When it is determined that a faulty disk exists in the logical pool storing the second storage volume, it is determined whether data of the second storage volume stored in the faulty disk is lost.

[0129] Specifically, when the system detects a disk failure in a logical pool, the first task is to evaluate whether the failure has caused data loss in the secondary storage volume stored on the disk, so as to provide guidance for subsequent recovery operations.

[0130] For example, the system checks the data status on the failed disk, including its integrity, accessibility, and availability. If the data exists but is inaccessible, the system attempts to recover it using underlying disk repair techniques (such as bad sector repair and disk rereading). If the data is completely lost, the system initiates the data recovery process.

[0131] Step S1310 : When it is determined that the data of the second storage volume stored in the failed disk is lost, the data of the failed disk is restored using the second data copy stored in the second backup disk in the logical pool to which the failed disk belongs.

[0132] Specifically, once data loss is confirmed, the system will first use the second data copy in the same logical pool to perform a data recovery operation to restore data services as quickly as possible.

[0133] For example, based on the preset metadata and data distribution strategy, a second data copy on a second backup disk associated with the failed disk is located, and a data recovery algorithm is executed to migrate the data in the second data copy to a replacement disk for the failed disk, ensuring data integrity and service continuity.

[0134] Step S1320 : When data recovery of the failed disk fails using the second data copy stored in the second backup disk in the logical pool to which the failed disk belongs, a backup logical pool associated with the logical pool to which the failed disk belongs is determined according to the first association relationship.

[0135] Specifically, if the recovery attempt in step S1310 fails, the system will jump to a higher-level recovery mechanism and search for a data copy in an associated backup logical pool for recovery based on the first association relationship between logical pools.

[0136] For example, if the cause of the recovery failure in step S1310 is due to a failure of the secondary backup disk itself or corruption of the data copy, the system automatically switches to the backup logical pool based on the association rule. The system searches for metadata records to locate the valid secondary data copy in the backup logical pool and prepares for secondary data recovery.

[0137] Step S1330 : Recover the data on the failed disk using the second data copy stored in the second backup disk in the backup logical pool.

[0138] Specifically, the data copy of the backup logical pool is used to perform a data recovery operation, ensuring that even if the recovery in step S1310 fails, the data can be recovered promptly and effectively.

[0139] In this embodiment, by constructing a multi-level fault detection and data recovery process, the persistence and availability of the data in the second storage volume are significantly enhanced. First, the primary data recovery mechanism can quickly respond to disk failures by quickly utilizing data copies within the same logical pool, avoiding the situation where data is unavailable for a long time and reducing business interruption time. Secondly, the secondary data recovery process provides a higher level of disaster recovery protection by utilizing data copies across logical pools. Even if a single logical pool is completely unavailable, it can rely on the associated backup logical pool to quickly restore data, ensuring the continuity of data services. Through automated fault detection and recovery processes, the complexity and response time of system operation and maintenance are significantly reduced, and the system's self-repair capabilities and data recovery efficiency are enhanced. The multi-level data recovery strategy greatly improves the data security and business continuity of the distributed storage system, provides users with more reliable and efficient data storage and access services, and reduces business risks and economic losses caused by data loss.

[0140] In one embodiment, Figure 14 As shown, step S200, classifying multiple disks of the same storage cluster according to a preset strategy to obtain multiple logical pools. It includes: steps S1400-S1420:

[0141] Step S1400: Acquire physical parameters and disk resource information of multiple storage nodes.

[0142] The storage cluster includes multiple storage nodes, and the storage nodes include multiple disks.

[0143] Specifically, one of the core aspects of distributed storage cluster management is the effective classification of storage nodes to optimize resource allocation and data distribution strategies. This involves collecting comprehensive information about storage nodes, including physical parameters such as hardware configuration (CPU, memory), disk type (SSD, HDD), disk capacity, and network bandwidth, as well as resource information such as current disk usage and health status.

[0144] Step S1410 , classifying multiple storage nodes according to their physical parameters and disk resource information to obtain multiple storage node sets.

[0145] Specifically, based on the collected physical parameters and disk resource information, the system executes a storage node classification algorithm to classify storage nodes with similar physical characteristics, similar resource utilization, or located in the same geographical location into the same set, providing a classification basis for the subsequent construction of logical pools.

[0146] Step S1420: Classify multiple disks included in multiple storage nodes in the same storage node set into the same logical pool.

[0147] Specifically, after completing the storage node classification, the system regards the disk resources of the storage nodes in the same set as storage units with the same or similar characteristics, and then merges them into a logical pool to achieve refined storage management based on hardware characteristics and resource status.

[0148] For example, all disks under the same storage node set are considered candidate members of the same logical pool. A logical pool construction process is executed to select disks based on preset policies (such as performance optimization, redundancy policy, and cost control), and the disks belonging to the same storage node are grouped into the same logical pool.

[0149] This embodiment first classifies storage nodes based on physical parameters and disk resource information, ensuring that logical pool construction takes into account hardware compatibility, resource availability, and geographic location. This optimizes data distribution logic, improving data read and write speeds and storage efficiency. Disks are then classified based on the classified storage nodes, and disks belonging to the same storage node class are grouped into the same logical pool. This not only facilitates the implementation of a unified data redundancy and recovery strategy, but also simplifies storage system management and maintenance, enhancing the system's disaster recovery capabilities.

[0150] In one embodiment, Figure 15 As shown, the method further includes: steps S1500-S1520:

[0151] Step S1500: When the type of the storage volume to be created is the second type, at least two target logical pools are determined from the multiple logical pools.

[0152] The storage nodes included in at least two target logical pools are different.

[0153] Specifically, for the second type of storage volumes with specific performance and redundancy requirements, the system intelligently selects a logical pool combination containing different storage nodes as the target in a multi-logical pool environment to disperse storage risks and improve data redundancy.

[0154] For example, the special requirements of the second type of storage volume, such as high performance, high availability, or geographically dispersed storage, are analyzed, and at least two logical pools covering different storage nodes are selected from the multiple logical pools to ensure data distribution diversity and wide-area redundancy.

[0155] Step S1510: Create a second storage volume of a second type in at least two target logical pools respectively.

[0156] The data contained in the second storage volume is distributed and stored in multiple disks of at least two target logical pools.

[0157] Specifically, within the selected target logical pool, the system will create a second type of storage volume and follow the pre-set data distribution strategy to evenly distribute the storage volume data on disks in different logical pools to achieve optimal storage efficiency and data protection.

[0158] Step S1520: Establish a first association relationship between at least two target logical pools that have stored the same second storage volume.

[0159] Specifically, in order to achieve data synchronization and redundancy management across logical pools, the system will establish a clear association relationship between logical pools storing the same second-type storage volume to support efficient synchronization and consistent management of data.

[0160] In this embodiment, target selection and storage volume creation across logical pools ensure that data is stored in a dispersed manner among different nodes, effectively preventing single point failures and improving the overall robustness and disaster response capabilities of the storage system. Secondly, the wide-area distribution of data stored on multiple disks, combined with the requirements of high performance and high redundancy, not only ensures a rapid response to data access, but also enhances the persistence and security of data, significantly improving user experience and service quality. The established first association relationship between logical pools not only simplifies data synchronization and consistency management, but also provides a clear path for fault recovery and data migration, greatly reducing the complexity of data management and enhancing the maintainability and scalability of the system. In summary, this second-type storage volume creation and association method across logical pools provides a high-level data distribution and redundancy management capability for distributed storage systems, ensuring the efficiency, reliability and security of data storage.

[0161] In one embodiment, the method further includes: establishing a first data synchronization mechanism between the at least two logical pools that have established the first association relationship.

[0162] Specifically, the system builds a data synchronization framework between associated logical pools to ensure that data changes in the second storage volume in any logical pool can be promptly perceived and responded to by other related logical pools, achieving data consistency or quasi-consistency.

[0163] The first data synchronization mechanism includes:

[0164] When data in the second storage volume of any one of the at least two logical pools with the first association relationship established is updated, data in the second storage volumes of the other logical pools of the at least two logical pools with the first association relationship established are simultaneously updated.

[0165] Specifically, when data is updated in the second storage volume of any logical pool, the real-time data synchronization mechanism ensures that the data in the corresponding storage volumes of other logical pools can be updated immediately to maintain data consistency.

[0166] Alternatively, when data in the second storage volume of any one of the at least two logical pools with which the first association relationship has been established is updated, data in the second storage volumes of the other logical pools of the at least two logical pools with which the first association relationship has been established is updated after a preset time period.

[0167] Specifically, to address the network pressure and resource consumption issues that real-time synchronization can cause, the system also supports synchronizing changes to other related logical pools after a preset period of time after data updates, achieving a quasi-consistent state. A data synchronization delay window can be defined, allowing data to be briefly cached locally before synchronization.

[0168] In this embodiment, through the real-time or delayed data synchronization mechanism, the distributed storage system not only improves the consistency and stability of the data, but also optimizes the efficiency of resource utilization and enhances the overall performance of the system. The real-time data synchronization strategy ensures that the second storage volume data between the associated logical pools always remains consistent, which is crucial for application scenarios that require high data consistency. Secondly, the delayed data synchronization strategy introduced by the system balances the relationship between data consistency and network resource consumption, avoiding the network bottlenecks and increased latency caused by high-frequency data synchronization, and is particularly suitable for scenarios where data is frequently updated but the consistency requirements are slightly lower, such as logging or big data analysis. By establishing the first association relationship and data synchronization mechanism between logical pools, the flexibility and reliability of the storage system are enhanced.

[0169] In one embodiment, Figure 16 As shown, the method further includes: steps S1600-S1620:

[0170] Step S1600 : In response to a target object's active-active storage request, when the type of the storage volume to be created is a first type, determining at least one target logical pool in at least two storage clusters respectively.

[0171] The distributed storage system includes at least two storage clusters.

[0172] Specifically, when the system receives an active-active storage request from a target, it indicates that the requester wishes to implement active-active redundant data storage across two or more storage clusters. To achieve this, the system first selects at least one target logical pool in each of the two storage clusters based on the specific conditions of the request to create and store the first type of storage volume.

[0173] Step S1610: Create a first storage volume of a first type in at least one target logical pool determined in at least two storage clusters.

[0174] Step S1620: Establish a second association relationship between target logical pools storing the same first storage volume in at least two storage clusters.

[0175] Specifically, to achieve the goal of active-active storage—real-time or near-real-time data synchronization across all selected storage clusters—the system establishes a secondary association between the target logical pools. This association defines the rules and processes for data synchronization, including trigger conditions, synchronization direction, synchronization protocol, and conflict resolution mechanisms, ensuring data consistency and high availability. By implementing these association rules between the target logical pools, a data synchronization network is established, ensuring that data updates on any one are quickly detected and synchronized by the others, maintaining data consistency.

[0176] For example, Figure 17 As shown, the distributed storage system includes two storage clusters. The first storage cluster includes multiple storage nodes (node A, node B, node C), and the second storage cluster includes multiple storage nodes (node D, node E). The storage nodes can be physical nodes or logical nodes in the storage cluster. By classifying multiple disks, we can get, for example Figure 17 As shown, the logical pool 80 and the logical pool 90 have a second association relationship established between them.

[0177] For example, Figure 18 As shown, the distributed storage system includes three storage clusters. The first storage cluster includes multiple storage nodes (node A, node B, node C), the second storage cluster includes multiple storage nodes (node D, node E), and the third storage cluster includes multiple storage nodes (node F, node G). The storage nodes can be physical nodes or logical nodes in the storage cluster. By classifying multiple disks, we can get, for example Figure 18 As shown, the logical pool 100 , the logical pool 110 , and the logical pool 120 establish a second association relationship among the logical pool 100 , the logical pool 110 , and the logical pool 120 .

[0178] In this embodiment, by building a redundant storage architecture based on active-active storage requests, data storage reliability, access speed, and disaster recovery capabilities are significantly improved. The system establishes a secondary association between the target logical pools of the two storage clusters, ensuring data synchronization between the two clusters. Even if one cluster fails, the other cluster can immediately take over services, ensuring business continuity and data reliability.

[0179] In one embodiment, Figure 19 As shown, the method further includes: steps S1900-S1930:

[0180] Step S1900: One of the at least two storage clusters with which the second association relationship has been established is used as a primary storage site, and the other storage clusters of the at least two storage clusters with which the second association relationship has been established are used as backup storage sites.

[0181] Specifically, one cluster is established as the primary storage site, and the remaining clusters as backup storage sites, forming an active-active or multi-active storage environment. The primary storage site handles daily data read and write requests, while the backup storage site takes over services and also performs data recovery functions in the event of a failure at the primary storage site.

[0182] Step S1910: When the primary storage site is normal, the primary storage site is used to provide storage services for the target object.

[0183] Specifically, when the primary storage site operates normally, all storage service requests from target objects are processed by the primary storage site to achieve efficient data reading and writing.

[0184] Step S1920: When the primary storage site fails, the backup storage site is used to provide storage services for the target object, and

[0185] Step S1930 uses the data of the first storage volume stored in the backup storage site to restore the data at the primary storage site.

[0186] Specifically, when a primary storage site fails, the system automatically redirects service requests to the backup site, seamlessly continuing storage services. Simultaneously, the backup site uses its stored copy of the primary site's data to perform data recovery, ensuring the primary site can be rolled back to its pre-failure state after the failure is repaired. If the primary storage site is unable to provide services, the system automatically switches to the backup site to ensure business continuity.

[0187] In this embodiment, by distinguishing between the primary storage site and the backup storage site, a dynamic active-active storage environment is established, which enables the system to quickly continue to provide storage services through the backup storage site when a failure occurs at the primary storage site, thereby avoiding business interruptions and ensuring the continuity of data services. Through the data synchronization mechanism and the efficient use of the backup storage site, not only the redundancy and persistence of data are improved, but also the response speed of the storage service is optimized, the data access latency is reduced, and the user experience is improved. The failover and primary site data recovery mechanism ensures the integrity of the data. Even if the primary storage site suffers a serious failure, it can be quickly restored through the data copy at the backup storage site, effectively preventing data loss and improving the overall reliability and stability of the system.

[0188] In one embodiment, Figure 20 As shown, the method further includes: steps S2000-S2030:

[0189] Step S2000: When the type of the storage volume to be created is the second type, at least two target logical pools are determined from multiple logical pools of the first storage cluster.

[0190] Specifically, the second type of storage volume is a storage volume that needs to be stored across logical pools. At least two target logical pools are used in the first cluster to create the second type of storage volume.

[0191] Step S2010: Create a second storage volume of a second type in at least two target logical pools of the first storage cluster.

[0192] The data contained in the second storage volume is distributed and stored in multiple disks of at least two target logical pools.

[0193] Specifically, a second type of storage volume is created in at least two selected target logical pools to ensure that data is distributed and stored across multiple disks, thereby improving data persistence and access efficiency.

[0194] Step S2020: Establish a first association relationship between at least two target logical pools that have stored the same second storage volume.

[0195] Specifically, a relationship between target logical pools storing the same second type storage volume is established to provide a framework for data synchronization and fault isolation. The first association relationship is the relationship between at least two target logical pools storing the same second storage volume in the same storage cluster.

[0196] Step S2030: Establish a third association relationship between the second storage volume in the first storage cluster and the first storage volume in the second storage cluster.

[0197] Specifically, a connection is established between the first and second storage clusters, connecting the second-type storage volume to the first storage volume of the backup storage cluster. This creates a cross-cluster data redundancy and synchronization mechanism, enhancing the system's disaster recovery and business continuity capabilities. The third association is the relationship between the second-type second storage volume in the first storage cluster and the first-type first storage volume in the second storage cluster, enabling cross-cluster data synchronization and redundancy.

[0198] Exemplarily, the metadata management system tracks the mapping relationship and data status between the second type storage volume and the first storage volume of the backup cluster, providing a basis for data synchronization and fault recovery.

[0199] For example, Figure 21 As shown, the distributed storage system includes two storage clusters. The first storage cluster includes multiple storage nodes (node A, node B, node C, node D, node E), and the second storage cluster includes multiple storage nodes (node F, node G). The storage nodes can be physical nodes or logical nodes in the storage cluster. By classifying multiple disks, we can get, for example Figure 21As shown, logical pool 130, logical pool 140, and logical pool 150, a first association relationship is established between logical pool 130 and logical pool 140, and a third association relationship is established between the second storage volume (logical pool 130 and logical pool 140) in the first storage cluster and the first storage volume (logical pool 150) in the second storage cluster.

[0200] In this embodiment, the selection of the target logical pool and the creation of the storage volume ensure the balanced and persistent distribution of data within the first storage cluster, and enhance the ability to resist single point failures. Secondly, the establishment of the first association relationship between logical pools and the third association relationship between clusters forms a multi-level data redundancy and synchronization network. Even if a logical pool or cluster encounters a failure, the system can quickly restore the data through the copies in other logical pools or clusters to maintain business continuity. A first association relationship is established between two logical pools in the same cluster to achieve cross-logical pool redundant backup of data. A third association relationship is established between the second storage volume in the first storage cluster and the first storage volume in the second storage cluster to ensure data synchronization between clusters, thereby improving data reliability and system stability.

[0201] In one embodiment, the method further includes: establishing a first data synchronization mechanism between the at least two logical pools that have established the first association relationship, wherein the first data synchronization mechanism includes:

[0202] When data in the second storage volume of any one of the at least two logical pools with the first association relationship established is updated, data in the second storage volumes of the other logical pools of the at least two logical pools with the first association relationship established are simultaneously updated.

[0203] Specifically, a data synchronization mechanism is established between at least two logical pools that have established a first association relationship to ensure that when the data in the second storage volume in any logical pool is updated, the second storage volume data in other associated logical pools can be updated synchronously in real time to maintain data consistency and availability.

[0204] A second data synchronization mechanism is established between the second storage volume of the first storage cluster and the first storage volume of the second storage cluster, in which the third association relationship has been established. The second data synchronization mechanism includes:

[0205] When the data in any one of the second storage volume and the first storage volume with which the third association relationship has been established is updated, the data in the other storage volume is updated after a preset time period.

[0206] Specifically, a second data synchronization mechanism is implemented between the first storage cluster and the second storage cluster based on the established third association relationship, so that after the data in any storage volume is updated, the data in the other storage volume can be updated after a preset period of time, ensuring the consistency and high availability of data across clusters, while also taking into account the rational use of network resources and delay management.

[0207] For example, the method in this embodiment can be applied to a two-location, three-center scenario (that is, two geographically distinct regions with three data storage centers). A first association relationship is established between two data storage centers in the same region, using a first data synchronization mechanism. A third association relationship is established between data storage centers in different regions, using a second data synchronization mechanism. Specifically, the data security policy based on extended clustering is adopted in the same city, while the data security policy of active-active asynchronous data synchronization is adopted in different regions. This enables real-time synchronization of data in the same city and asynchronous disaster recovery of data in the two locations.

[0208] In this embodiment, the instantaneous data synchronization update mechanism (the first data synchronization mechanism) ensures immediate data consistency across multiple logical pools, reducing potential issues caused by data inconsistencies, such as read-write conflicts or service interruptions, and enhancing overall system stability and data security. Secondly, the cross-cluster data synchronization mechanism (the second data synchronization mechanism) not only ensures data consistency but also balances network resource consumption by introducing a delay mechanism, avoiding the network congestion and high latency that can result from real-time synchronization. This makes it particularly suitable for clusters with widespread geographical distribution, improving system performance and efficiency in large-scale deployments.

[0209] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus the necessary general hardware platform, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method.

[0210] The embodiment of the present application also provides a storage space management device, Figure 22 1 is a structural block diagram of a storage space management device according to an embodiment of the present application, the device comprising:

[0211] The disk classification module 2201 is configured to classify multiple disks in the same storage cluster according to a preset policy to obtain multiple logical pools, wherein one logical pool includes at least two disks.

[0212] The storage volume creation module 2202 is used to create a first storage volume of the first type in a target logical pool among multiple logical pools when the type of the storage volume to be created is the first type, wherein the data contained in the first storage volume is distributed and stored in multiple disks of the target logical pool, and the data of the first type of storage volumes in different logical pools are isolated from each other.

[0213] In an exemplary embodiment, the disk classification module 2201 is further configured to determine disk parameters for multiple disks in the same storage cluster. A disk classification policy is then matched to the business requirements of the target object. The multiple disks are classified based on the disk classification policy and the disk parameters of the multiple disks to generate multiple logical pools.

[0214] In an exemplary embodiment, the disk classification module 2201 is further configured to determine the read / write modes of each of the multiple disks based on disk parameters of the multiple disks. First-class disks and second-class disks are identified from the multiple disks based on the read / write modes of the multiple disks, where the read / write modes of the first-class disks and the second-class disks are different, and the read / write speed of the first-class disks is greater than the read / write speed of the second-class disks. A first preset number of first-class disks are selected from the multiple disks as a common set to obtain at least one first logical pool. Furthermore, a second preset number of first-class disks and a third preset number of second-class disks are selected from the multiple disks as a common set to obtain at least one second logical pool.

[0215] In an exemplary embodiment, the disk classification module 2201 is further configured to determine the disk models and disk capacities of the plurality of disks based on the disk parameters of the plurality of disks. Based on the disk models and disk capacities of the plurality of disks, disks with the same disk models and disk capacities in the plurality of disks are classified into the same set to obtain multiple logical pools.

[0216] In an exemplary embodiment, the storage volume creation module 2202 is further configured to determine the type of storage volume to be created based on a creation request for a target object. If the type of the storage volume to be created is determined to be the first type, a target logical pool is determined from among multiple logical pools based on the performance requirements of the storage volume carried in the creation request. A first storage volume of the first type is created within the target logical pool, and data in the first storage volume is distributed and stored across multiple disks in the target logical pool according to a preset data distribution strategy. Data isolation logic is configured to isolate data in the first type storage volumes within different logical pools from each other.

[0217] In an exemplary embodiment, the apparatus further comprises:

[0218] The first creation module is configured to create a first data copy of the first storage volume in the target logical pool, wherein the first data copy is stored in at least one first backup disk in the target logical pool.

[0219] The first backup module is configured to, when it is determined that a failed disk exists in the target logical pool, recover data on the failed disk by using a first data copy stored in at least one first backup disk.

[0220] In an exemplary embodiment, the apparatus further comprises:

[0221] The first logical pool determining module is configured to determine at least two target logical pools from the plurality of logical pools according to the performance requirements and redundancy requirements of the storage volume carried in the creation request when the type of the storage volume to be created is the second type.

[0222] The second creation module is configured to create second storage volumes of the second type in at least two target logical pools respectively, wherein data contained in the second storage volumes is distributed and stored in multiple disks of the at least two target logical pools.

[0223] The first relationship establishing module is configured to establish a first association relationship between at least two target logical pools that have stored the same second storage volume.

[0224] In an exemplary embodiment, the apparatus further comprises:

[0225] The third creation module is used to create at least one second data copy of the second storage volume in at least two target logical pools that have stored the same second storage volume, wherein the second data copy is stored in at least one second backup disk in the at least two target logical pools.

[0226] The second backup module is configured to, when determining that a faulty disk exists in one of the at least two target logical pools, recover data on the faulty disk using a second data copy stored in at least one second backup disk in the at least two target logical pools.

[0227] In an exemplary embodiment, the second backup module is further configured to, upon determining that a faulty disk exists within a logical pool storing the second storage volume, determine whether data of the second storage volume stored within the faulty disk is lost. If it is determined that data of the second storage volume stored within the faulty disk is lost, the data of the faulty disk is recovered using a second data copy stored on a second backup disk within the logical pool to which the faulty disk belongs. If recovery of the data of the faulty disk fails using the second data copy stored on the second backup disk within the logical pool to which the faulty disk belongs, a backup logical pool associated with the logical pool to which the faulty disk belongs is determined based on the first association relationship. The data of the faulty disk is recovered using the second data copy stored on the second backup disk within the backup logical pool.

[0228] In an exemplary embodiment, the disk classification module 2201 is further configured to obtain physical parameters and disk resource information of multiple storage nodes. The multiple storage nodes are classified based on the physical parameters and disk resource information of the multiple storage nodes to obtain multiple storage node sets. The multiple disks included in the multiple storage nodes in the same storage node set are classified into the same logical pool.

[0229] In an exemplary embodiment, the apparatus further comprises:

[0230] The second logical pool determining module is configured to determine at least two target logical pools from the plurality of logical pools when the type of the storage volume to be created is the second type, wherein the storage nodes included in the at least two target logical pools are different.

[0231] The fourth creation module is configured to create a second storage volume of the second type in the at least two target logical pools respectively, wherein data contained in the second storage volume is distributed and stored in multiple disks of the at least two target logical pools.

[0232] The second relationship establishing module is configured to establish a first association relationship between at least two target logical pools that have stored the same second storage volume.

[0233] In an exemplary embodiment, the apparatus further comprises:

[0234] A first data synchronization module is configured to establish a first data synchronization mechanism between at least two logical pools that have established a first association relationship, wherein the first data synchronization mechanism includes: when data in the second storage volume of any one of the at least two logical pools that have established a first association relationship is updated, data in the second storage volumes of other logical pools in the at least two logical pools that have established a first association relationship is simultaneously updated. Alternatively, when data in the second storage volume of any one of the at least two logical pools that have established a first association relationship is updated, data in the second storage volumes of other logical pools in the at least two logical pools that have established a first association relationship is updated after a preset period of time.

[0235] In an exemplary embodiment, the apparatus further comprises:

[0236] The third logical pool determination module is configured to, in response to the active-active storage request of the target object, determine at least one target logical pool in each of the at least two storage clusters when the type of the storage volume to be created is the first type.

[0237] The fifth creation module is configured to create a first storage volume of a first type in at least one target logical pool determined in each of the at least two storage clusters.

[0238] The third relationship establishing module is configured to establish a second association relationship between target logical pools storing the same first storage volume in at least two storage clusters.

[0239] In an exemplary embodiment, the apparatus further comprises:

[0240] The site determination module is configured to use one of the at least two storage clusters with which the second association relationship has been established as a primary storage site and use the other storage clusters of the at least two storage clusters with which the second association relationship has been established as backup storage sites.

[0241] The service module is used to use the primary storage site to provide storage services for the target object when the primary storage site is normal.

[0242] The backup module is used to use the backup storage site to provide storage services for the target object when the primary storage site fails, and to use the data of the first storage volume stored in the backup storage site to recover the data of the primary storage site.

[0243] In an exemplary embodiment, the apparatus further comprises:

[0244] The fourth logical pool determining module is configured to determine at least two target logical pools from the plurality of logical pools in the first storage cluster when the type of the storage volume to be created is the second type.

[0245] The sixth creation module is configured to create second storage volumes of the second type in at least two target logical pools of the first storage cluster, respectively, wherein data contained in the second storage volumes is distributed and stored in multiple disks of the at least two target logical pools.

[0246] The fourth relationship establishing module is configured to establish a first association relationship between at least two target logical pools that have stored the same second storage volume.

[0247] The fifth relationship establishing module is configured to establish a third association relationship between the second storage volume in the first storage cluster and the first storage volume in the second storage cluster.

[0248] In an exemplary embodiment, the apparatus further comprises:

[0249] The second data synchronization module is used to establish a first data synchronization mechanism between at least two logical pools that have established a first association relationship, wherein the first data synchronization mechanism includes: when the data in the second storage volume of any one of the at least two logical pools that have established a first association relationship is updated, the data in the second storage volumes of other logical pools in the at least two logical pools that have established a first association relationship are simultaneously updated.

[0250] The third data synchronization module is used to establish a second data synchronization mechanism between the second storage volume of the first storage cluster and the first storage volume of the second storage cluster, in which a third association relationship has been established. The second data synchronization mechanism includes: when the data in any one of the second storage volume and the first storage volume, in which a third association relationship has been established, is updated, the data in the other storage volume is updated after a preset time period.

[0251] For the description of the features in the embodiment corresponding to the storage space management device, please refer to the relevant description of the embodiment corresponding to the storage space management method, and no further details will be given here.

[0252] An embodiment of the present application further provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the steps in any of the above-mentioned storage space management method embodiments.

[0253] An embodiment of the present application further provides a computer-readable storage medium, in which a computer program is stored, wherein the computer program is configured to execute the steps of any of the above-mentioned storage space management method embodiments when running.

[0254] In an exemplary embodiment, the computer-readable storage medium may include, but is not limited to, various media that can store computer programs, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk, or an optical disk.

[0255] An embodiment of the present application further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements the steps of any of the above-mentioned storage space management method embodiments.

[0256] An embodiment of the present application also provides another computer program product, including a non-volatile computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the steps in any of the above-mentioned storage space management method embodiments.

[0257] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the components and steps of each example according to their functions. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0258] The above is a detailed introduction to a storage space management method, device, electronic device, computer-readable storage medium, and computer program product provided by the present application. Specific examples are used herein 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 idea. It should be pointed out that for ordinary technicians in this technical field, without departing from the principles of the present application, several improvements and modifications can be made to the present application, and these improvements and modifications also fall within the scope of protection of the claims of the present application.

Claims

1. A storage space management method, characterized in that: Applied to a distributed storage system, the distributed storage system includes a storage cluster, the storage cluster includes multiple disks, and the method includes: Classifying the multiple disks of the same storage cluster according to a preset strategy to obtain multiple logical pools, wherein one logical pool includes at least two disks; When the type of the storage volume to be created is a first type, creating a first storage volume of the first type in a target logical pool among the multiple logical pools, wherein data contained in the first storage volume is distributed and stored across multiple disks in the target logical pool, and data of the first type storage volumes in different logical pools is isolated from each other; In a case where the type of the storage volume to be created is the second type, determining at least two target logical pools from the multiple logical pools; Creating second storage volumes of the second type in the at least two target logical pools respectively, wherein data contained in the second storage volumes is distributed and stored in multiple disks of the at least two target logical pools; A first association relationship is established between the at least two target logical pools storing the same second storage volume.

2. The storage space management method according to claim 1, characterized in that: The classifying the multiple disks of the same storage cluster according to a preset strategy to obtain multiple logical pools includes: Determining disk parameters of each of the plurality of disks in the same storage cluster; In response to the business requirements of the target object, matching the business requirements with corresponding disk classification strategies; The multiple disks are classified according to the disk classification strategy and the disk parameters of the multiple disks to obtain multiple logical pools.

3. The storage space management method according to claim 2, characterized in that: The classifying the plurality of disks according to the disk classification strategy and the respective disk parameters of the plurality of disks to obtain a plurality of logical pools includes: determining the read and write modes of the plurality of disks according to the disk parameters of the plurality of disks; Determining a first type of disk and a second type of disk among the plurality of disks according to the respective read and write modes of the plurality of disks, wherein the read and write mode of the first type of disk is different from the read and write mode of the second type of disk and the read and write speed of the first type of disk is greater than the read and write speed of the second type of disk; Selecting a first preset number of first-type disks from the plurality of disks as a same set to obtain at least one first logical pool; and A second preset number of first-type disks and a third preset number of second-type disks are selected from the plurality of disks as a same set to obtain at least one second logical pool.

4. The storage space management method according to claim 2, characterized in that: The classifying the plurality of disks according to the disk classification strategy and the respective disk parameters of the plurality of disks to obtain a plurality of logical pools includes: Determining the disk models and disk capacities of the plurality of disks according to the disk parameters of the plurality of disks; According to the disk models and disk capacities of the plurality of disks, disks with the same disk model and the same disk capacity among the plurality of disks are classified into the same set to obtain a plurality of logical pools.

5. The storage space management method according to any one of claims 1 to 4, characterized in that: When the type of the storage volume to be created is a first type, creating a first storage volume of the first type in a target logical pool among the multiple logical pools includes: Determine the type of storage volume to be created according to the creation request of the target object; When it is determined that the type of the storage volume to be created is the first type, determining a target logical pool from the multiple logical pools according to the performance requirement of the storage volume carried in the creation request; A first storage volume of the first type is created in the target logical pool, and the data in the first storage volume is distributed and stored in multiple disks of the target logical pool according to a preset data distribution strategy, wherein data isolation logic is set to isolate the data of the first type storage volumes in different logical pools from each other.

6. The storage space management method according to claim 5, characterized in that: After creating a first storage volume of the first type in the target logical pool and distributing and storing data in the first storage volume across multiple disks in the target logical pool according to a preset data distribution strategy, the method further includes: Creating a first data copy of the first storage volume in the target logical pool, wherein the first data copy is stored in at least one first backup disk in the target logical pool; When it is determined that a faulty disk exists in the target logical pool, the data of the faulty disk is restored using the first data copy stored in the at least one first backup disk.

7. The storage space management method according to claim 5, characterized in that: After determining the type of the storage volume to be created according to the creation request of the target object, the method further includes: When the type of the storage volume to be created is the second type, at least two target logical pools are determined from the multiple logical pools according to the performance requirements and redundancy requirements of the storage volume carried in the creation request.

8. The storage space management method according to claim 7, characterized in that: The method further comprises: creating at least one second data copy of the second storage volume in the at least two target logical pools storing the same second storage volume, respectively, wherein the second data copy is stored in at least one second backup disk in the at least two target logical pools; When it is determined that a failed disk exists in one of the at least two target logical pools, data of the failed disk is recovered by using a second data copy stored in at least one second backup disk in the at least two target logical pools.

9. The storage space management method according to claim 8, characterized in that: The recovering the data of the failed disk by using the second data copy stored in at least one second backup disk in the at least two target logical pools includes: In a case where it is determined that a faulty disk exists in the logical pool storing the second storage volume, determining whether data of the second storage volume stored in the faulty disk is lost; When it is determined that the data of the second storage volume stored in the failed disk is lost, recovering the data of the failed disk by using the second data copy stored in the second backup disk in the logical pool to which the failed disk belongs; In a case where data recovery of the failed disk using the second data copy stored in the second backup disk in the logical pool to which the failed disk belongs fails, determining a backup logical pool associated with the logical pool to which the failed disk belongs according to the first association relationship; The data of the failed disk is restored using the second data copy stored in the second backup disk in the backup logical pool.

10. The storage space management method according to any one of claims 1 to 4, characterized in that: The storage cluster includes multiple storage nodes, each storage node includes multiple disks, and classifying the multiple disks of the same storage cluster according to a preset policy to obtain multiple logical pools further includes: Obtaining physical parameters and disk resource information of the multiple storage nodes; Classifying the plurality of storage nodes according to the physical parameters and disk resource information of the plurality of storage nodes to obtain a plurality of storage node sets; Multiple disks included in multiple storage nodes in the same storage node set are classified into the same logical pool.

11. The storage space management method according to claim 10, characterized in that: The method further comprises: In a case where the type of the storage volume to be created is the second type, determining at least two target logical pools from the multiple logical pools, wherein the at least two target logical pools include different storage nodes; Creating second storage volumes of the second type in the at least two target logical pools respectively, wherein data contained in the second storage volumes is distributed and stored in multiple disks of the at least two target logical pools; A first association relationship is established between the at least two target logical pools storing the same second storage volume.

12. The storage space management method according to claim 11, characterized in that: The method further comprises: A first data synchronization mechanism is established between the at least two logical pools that have established the first association relationship, wherein the first data synchronization mechanism includes: When data in the second storage volume of any one of the at least two logical pools with which the first association relationship has been established is updated, data in the second storage volumes of the other logical pools of the at least two logical pools with which the first association relationship has been established are simultaneously updated; Alternatively, when data in the second storage volume of any one of the at least two logical pools with which the first association relationship has been established is updated, data in the second storage volumes of other logical pools of the at least two logical pools with which the first association relationship has been established is updated after a preset time period.

13. The storage space management method according to any one of claims 1 to 4, characterized in that: The distributed storage system includes at least two storage clusters, and the method further includes: In response to a dual-active storage request of a target object, when the type of the storage volume to be created is a first type, determining at least one target logical pool in each of the at least two storage clusters; Creating a first storage volume of the first type in at least one target logical pool determined respectively in the at least two storage clusters; A second association relationship is established between the target logical pools storing the same first storage volume in the at least two storage clusters.

14. The storage space management method according to claim 13, characterized in that: The method further comprises: One of the at least two storage clusters with which the second association relationship has been established is used as a primary storage site, and the other storage clusters of the at least two storage clusters with which the second association relationship has been established are used as backup storage sites; When the primary storage site is normal, the primary storage site is used to provide storage services for the target object; In the event of a failure at the primary storage site, the backup storage site is used to provide storage services for the target object, and the data of the first storage volume stored in the backup storage site is used to restore the data at the primary storage site.

15. The storage space management method according to claim 13, characterized in that: The method further comprises: When the type of the storage volume to be created is the second type, determining at least two target logical pools from the multiple logical pools of the first storage cluster; creating second storage volumes of the second type in the at least two target logical pools of the first storage cluster, respectively, wherein data contained in the second storage volumes is distributed and stored in multiple disks of the at least two target logical pools; Establishing a first association relationship between the at least two target logical pools storing the same second storage volume; A third association relationship is established between the second storage volume in the first storage cluster and the first storage volume in the second storage cluster.

16. The storage space management method according to claim 15, characterized in that: The method further comprises: A first data synchronization mechanism is established between the at least two logical pools that have established the first association relationship, wherein the first data synchronization mechanism includes: When data in the second storage volume of any one of the at least two logical pools with which the first association relationship has been established is updated, data in the second storage volumes of the other logical pools of the at least two logical pools with which the first association relationship has been established are simultaneously updated; A second data synchronization mechanism is established between the second storage volume of the first storage cluster and the first storage volume of the second storage cluster, with which the third association relationship has been established, wherein the second data synchronization mechanism includes: When data in any one of the second storage volume and the first storage volume with which the third association relationship has been established is updated, data in the other storage volume is updated after a preset time period.

17. A storage space management device, characterized in that: include: A disk classification module, configured to classify multiple disks of the same storage cluster according to a preset policy to obtain multiple logical pools, wherein one of the logical pools includes at least two of the disks; A storage volume creation module is used to, when the type of the storage volume to be created is a first type, create a first storage volume of the first type in a target logical pool among the multiple logical pools, wherein the data contained in the first storage volume is distributed and stored in multiple disks of the target logical pool, and the data of the first type storage volumes in different logical pools are isolated from each other; when the type of the storage volume to be created is a second type, determine at least two target logical pools among the multiple logical pools; create a second storage volume of the second type in each of the at least two target logical pools, wherein the data contained in the second storage volume is distributed and stored in multiple disks of the at least two target logical pools; and establish a first association relationship between the at least two target logical pools that have stored the same second storage volume.

18. An electronic device, characterized in that: include: memory for storing computer programs; A processor, configured to implement the steps of the method according to any one of claims 1 to 16 when executing the computer program.

19. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 16 are implemented.

20. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 16 are implemented.

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