WO2023103519A1 - 集群数据迁移方法、装置、计算机设备及存储介质 - Google Patents

集群数据迁移方法、装置、计算机设备及存储介质 Download PDF

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Publication number
WO2023103519A1
WO2023103519A1 PCT/CN2022/120004 CN2022120004W WO2023103519A1 WO 2023103519 A1 WO2023103519 A1 WO 2023103519A1 CN 2022120004 W CN2022120004 W CN 2022120004W WO 2023103519 A1 WO2023103519 A1 WO 2023103519A1
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data
cluster
node
migration
access
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PCT/CN2022/120004
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English (en)
French (fr)
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董俊明
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苏州浪潮智能科技有限公司
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/21—Design, administration or maintenance of databases
    • G06F16/214—Database migration support
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
    • G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
    • G06F9/5038—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals considering the execution order of a plurality of tasks, e.g. taking priority or time dependency constraints into consideration
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2209/00—Indexing scheme relating to G06F9/00
    • G06F2209/50—Indexing scheme relating to G06F9/50
    • G06F2209/5021—Priority

Definitions

  • the present application relates to the field of data processing, and in particular to a cluster data migration method, device, computer equipment and storage medium.
  • the amount of data is large It takes a lot of time to migrate data, and users cannot use it normally during data migration, which seriously affects the daily business of users and reduces user experience.
  • the present application provides a cluster data migration method, including:
  • the data of each node in the first cluster is migrated to the second cluster based on the classification result.
  • the present application provides a cluster data migration device, including:
  • An acquisition module configured to acquire access information for the client to access each node in the first cluster
  • a classification module configured to perform priority classification for data migration of each node based on the access information, and obtain a classification result
  • the migration module is used to migrate the data of each node in the first cluster to the second cluster based on the classification result.
  • the present application provides a computer device, including a memory and one or more processors, where computer-readable instructions are stored in the memory, and when the computer-readable instructions are executed by the one or more processors, the above-mentioned one or a plurality of processors execute the steps of the above cluster data migration method.
  • the present application provides one or more non-volatile computer-readable storage media storing computer-readable instructions.
  • the above-mentioned computer-readable instructions are executed by one or more processors, the above-mentioned one or more processing
  • the server executes the steps of the above cluster data migration method.
  • FIG. 1 is a system architecture diagram of a cluster data migration method provided by the present application according to one or more embodiments
  • FIG. 2 is a schematic flowchart of a cluster data migration method provided by the present application according to one or more embodiments
  • FIG. 3 is a schematic flowchart of another cluster data migration method provided by the present application according to one or more embodiments
  • FIG. 4 is a schematic flow diagram of data access control during cluster data migration provided by the present application according to one or more embodiments
  • FIG. 5 is a schematic structural diagram of a cluster data migration device provided by the present application according to one or more embodiments.
  • Fig. 6 is a schematic structural diagram of a computer device provided by the present application according to one or more embodiments.
  • FIG. 1 is a system architecture diagram of a cluster data migration method provided by the present application. As shown in Figure 1, this method is preferably applicable to the data migration scenario of a distributed storage cluster.
  • the system architecture includes: the old cluster (hereinafter referred to as the first cluster), new cluster (hereinafter referred to as the second cluster), computer equipment including data access statistics, time-period traffic statistics, data analysis and evaluation, configuration center, control center, and data access/migration functions, which are used to complete this program
  • the cluster data migration method includes: the old cluster (hereinafter referred to as the first cluster), new cluster (hereinafter referred to as the second cluster), computer equipment including data access statistics, time-period traffic statistics, data analysis and evaluation, configuration center, control center, and data access/migration functions, which are used to complete this program The cluster data migration method.
  • the data access statistics collect and analyze the access information received by the first cluster within a certain period of time, and the access information includes access frequencies received by multiple nodes.
  • Periodic traffic statistics can collect statistics on the access traffic of the first cluster by hour, and collect statistics on the traffic value and system load status in each time period.
  • Data analysis and evaluation can analyze the access traffic of the first cluster on a daily basis, and evaluate the amount of migrated data within a time period.
  • the configuration center can configure the migration speed within the cluster time period and the data migration priority of each node in units of hours, and automatically adjust the cluster traffic load status according to the time period and period traffic statistics.
  • Migration speed within a time period monitor the CPU and bandwidth of the cluster at the same time, set the threshold, and when the amount of data migration occupies the CPU and bandwidth exceeds the threshold, the migration speed can be automatically reduced.
  • the control center provides an interface for starting and stopping data migration of the entire cluster, migration progress, and overview information about the currently migrated data.
  • the data access/migration function provides control over migrating files during data migration or access to prevent data inconsistencies between the first and second clusters.
  • FIG 2 is a schematic flow diagram of a cluster data migration method provided by the present application, as shown in Figure 2, the method specifically includes:
  • access information received by each node in the first cluster within a certain period of time is acquired, and the access information includes the amount of visits received by each node within a certain period of time.
  • the first cluster contains 10 nodes.
  • node 1 in the first cluster received 10,000 visits
  • node 2 received 12,000 visits
  • node 3 received 10,000 visits.
  • node 4 received 3,000 visits
  • node 5 received 2,000 visits
  • node 6 received 30,000 visits
  • node 7 received 35,000 visits
  • node 8 Received 3,000 visits
  • node 9 received 1,000 visits
  • node 10 received 50,000 visits.
  • each node can be classified according to the priority of data migration according to the amount of access. For example, 10,000 times and 30,000 times are the segment threshold Nodes with less than 10,000 visits can be classified as low-level categories, nodes with 10,000 to 30,000 visits can be divided into intermediate categories, and nodes with more than 30,000 visits can be divided into high-level categories.
  • nodes 4, 5, 8, and 9 can be divided into low-level categories; nodes 1, 2, 3, and 6 can be divided into intermediate categories; nodes 7 and 10 can be divided into high-level categories.
  • data migration can be performed on each node according to the priority category. If the data migration time is during the off-peak period of data access (for example, from 1 am to 5 am), the data of the nodes in each priority category can be migrated in the order of high-level category-middle-level category-low-level category, that is, first Migrate the data of each node in the high-level category, then migrate the data of each node in the middle-level category, and finally migrate the data of each node in the lower-level category.
  • the data migration time is the peak period of data access (for example, from 9:00 am to 5:00 pm)
  • the data of nodes in each priority category can be migrated in the order of low-level category-intermediate category-advanced category Migration means first migrating the data of each node in the low-level category, then migrating the data of each node in the middle-level category, and finally migrating the data of each node in the high-level category.
  • the cluster data migration method obtaineds the access information of each node in the first cluster accessed by the client; performs data migration priority classification on each node based on the access information, and obtains the classification result; based on the classification result, the first The data of each node in the cluster is migrated to the second cluster.
  • it is first necessary to stop the business of the old cluster and then migrate the data to the new cluster.
  • the amount of data is large During data migration, it takes a lot of time for data migration.
  • users cannot use it normally, which seriously affects the user's daily business.
  • This method can realize data migration without stopping the old cluster business, avoiding data
  • the problem that users cannot use normally caused by stopping the old cluster business during migration improves user experience.
  • FIG 3 is a schematic flow chart of another cluster data migration method provided by the present application, as shown in Figure 3, the method specifically includes:
  • a time period (for example, 9 am to 7 pm) may be preset, and the access frequency corresponding to each node in the first cluster accessed by the client within the preset time period is obtained.
  • the first cluster contains 5 nodes. From 9:00 a.m. to 7:00 p.m., node 1 receives a total of 80,000 visits at a frequency of 8,000 visits per hour, and node 2 receives a total of 30,000 visits , the visit frequency is 3,000 times per hour, node 3 receives a total of 120,000 visits, the visit frequency is 12,000 visits per hour, node 4 receives a total of 3,000 visits, and the visit frequency is 300 visits per hour, Node 5 receives a total of 10,000 visits, and the visit frequency is 1,000 visits per hour.
  • the nodes can be sorted according to the descending order of access frequency to obtain a node sequence: node 3, node 1, node 2, node 5, node 4.
  • a priority classification ratio of data migration (for example, 1:2:2) can be preset, and each node in the node sequence is assigned a priority classification for data migration according to the ratio, and the priority classification can be classified as advanced , middle-level, and low-level categories, then, according to the classification ratio, node 3 can be assigned to the high-level category, nodes 1 and 2 can be assigned to the middle-level category, and nodes 5 and 4 can be assigned to the low-level category.
  • data migration can be performed on each node according to the priority category, and the data can be migrated to the second cluster. If the data migration time is during the off-peak period of data access (for example, from 1 am to 5 am), the data of the nodes in each priority category can be migrated in the order of high-level category-middle-level category-low-level category, that is, first Migrate the data of each node in the high-level category, then migrate the data of each node in the middle-level category, and finally migrate the data of each node in the lower-level category.
  • the data migration time is the peak period of data access (for example, from 9:00 am to 5:00 pm)
  • the data of nodes in each priority category can be migrated in the order of low-level category-intermediate category-advanced category Migration means first migrating the data of each node in the low-level category, then migrating the data of each node in the middle-level category, and finally migrating the data of each node in the high-level category.
  • data migration of each node in a different priority category may also be controlled. For example, if the peak data access time of node 1 is from 8:00 am to 9:00 am, you can avoid this time period and perform data migration on node 1 in other time periods; At 9 o'clock in the evening, this time period can also be avoided, and the data migration of node 2 can be performed in other time periods.
  • the cluster data migration method obtaineds the access information of each node in the first cluster accessed by the client; performs data migration priority classification on each node based on the access information, and obtains the classification result; based on the classification result, the first The data of each node in the cluster is migrated to the second cluster.
  • it is first necessary to stop the business of the old cluster and then migrate the data to the new cluster.
  • the amount of data is large During data migration, it takes a lot of time for data migration.
  • users cannot use it normally, which seriously affects the user's daily business.
  • This method can realize data migration without stopping the old cluster business, avoiding data
  • the problem that users cannot use normally caused by stopping the old cluster business during migration improves user experience.
  • Fig. 4 is a schematic flow diagram of data access control in the cluster data migration process provided by the present application. As shown in Fig. 4, the method specifically includes:
  • the data being migrated can be locked. When the data is completely migrated, the lock is released. During the data migration process, only read operations are allowed, and update operations are not allowed to prevent data from being blocked during the data migration process. Modified, causing data inconsistency between the first and second clusters.
  • the target data can be queried and fed back based on the target data identifier carried in the data access request.
  • the data status of the target data is queried based on the target data identifier carried in the data access request.
  • the data status includes: migration status, not migrated, and migration completed.
  • a corresponding access prohibition prompt will be returned, that is, the target data is in the migration state and cannot be accessed.
  • the update operation of the data access request is allowed to update the data.
  • the target data in the first cluster and the second cluster are updated.
  • the update operation is a data addition operation
  • the data is first inserted into the first cluster, and then data migration is performed after completion.
  • the cluster data migration method controls access to the target data based on the type of the data access request by obtaining the type of the data access request. This method can realize the control of the data access operation during the data migration process. Avoid the data inconsistency between the first cluster and the second cluster due to access operations during data migration, and improve the cluster service effect.
  • Fig. 5 is a schematic structural diagram of a cluster data migration device provided in the embodiment of the present application, specifically including:
  • An acquisition module 501 configured to acquire access information for the client to access each node in the first cluster
  • a classification module 502 configured to perform priority classification for data migration of each node based on the access information, and obtain a classification result
  • the migration module 503 is configured to migrate the data of each node in the first cluster to the second cluster based on the classification result.
  • the obtaining module 501 is specifically configured to obtain the access frequency corresponding to each node in the first cluster accessed by the client within a preset time period.
  • the acquisition module 501 is further configured to acquire the type of the data access request, wherein the data access request carries the target data identifier; based on the type of the data access request, access control is performed on the target data .
  • the classification module 502 is specifically configured to sort the nodes according to the order of access frequency from large to small to obtain a node sequence; Priority classification of migration to obtain classification results.
  • the migration module 503 is specifically configured to migrate the data of each node in the first cluster to the second cluster according to the priority category based on the classification result.
  • the migration module 503 is further configured to perform migration control on the data of each node in different priority categories based on the access information and the current time.
  • the cluster data migration device further includes an access control module, specifically configured to feed back target data based on the data access request if the type of the data access request is read-only; if the type of the data access request is To update, the data status of the target data is determined based on the target data identifier; if the data status is in the migration status, a prompt is given that the target data is in the migration status and cannot be accessed; if the data status is not migrated, the update operation of the data access request is allowed; If the data status is migration completed, the target data in the first cluster and the second cluster are updated.
  • an access control module specifically configured to feed back target data based on the data access request if the type of the data access request is read-only; if the type of the data access request is To update, the data status of the target data is determined based on the target data identifier; if the data status is in the migration status, a prompt is given that the target data is in the migration status and cannot be accessed; if the data status is not migrated, the
  • the cluster data migration device provided in this embodiment can be the cluster data migration device as shown in Figure 5, which can perform all the steps of the cluster data migration method in Figure 2-4, and then realize the cluster data migration shown in Figure 2-4
  • Figure 5 For the technical effect of the method, please refer to the relevant descriptions in FIGS. 2-4 for details, and for the sake of brevity, details are not repeated here.
  • FIG. 6 is a schematic structural diagram of a computer device provided by an embodiment of the present application.
  • the computer device 600 shown in FIG. 6 includes: at least one processor 601 , memory 602 , at least one network interface 604 and other user interfaces 603 .
  • Various components in computer device 600 are coupled together by bus system 605 . It can be understood that the bus system 605 is used to realize connection and communication among these components.
  • the bus system 605 also includes a power bus, a control bus and a status signal bus.
  • the various buses are labeled as bus system 605 in FIG. 6 for clarity of illustration.
  • the user interface 603 may include a display, a keyboard or a pointing device (for example, a mouse, a trackball (trackball), a touch panel or a touch screen, and the like.
  • a keyboard or a pointing device for example, a mouse, a trackball (trackball), a touch panel or a touch screen, and the like.
  • the memory 602 in the embodiment of the present application may be a volatile memory or a nonvolatile memory, or may include both volatile and nonvolatile memories.
  • the non-volatile memory can be read-only memory (Read-Only Memory, ROM), programmable read-only memory (Programmable ROM, PROM), erasable programmable read-only memory (Erasable PROM, EPROM), electronically programmable Erase Programmable Read-Only Memory (Electrically EPROM, EEPROM) or Flash.
  • the volatile memory can be Random Access Memory (RAM), which acts as external cache memory.
  • RAM Static Random Access Memory
  • SRAM Static Random Access Memory
  • DRAM Dynamic Random Access Memory
  • Synchronous Dynamic Random Access Memory Synchronous Dynamic Random Access Memory
  • SDRAM double data rate synchronous dynamic random access memory
  • Double Data Rate SDRAM DDRSDRAM
  • enhanced SDRAM ESDRAM
  • Synch link DRAM SLDRAM
  • Direct Memory Bus Random Access Memory Direct Rambus RAM, DRRAM
  • the memory 602 described herein is intended to include, but is not limited to, these and any other suitable types of memory.
  • the memory 602 stores the following elements, executable units or data structures, or their subsets, or their extended sets: an operating system 6021 and an application program 6022 .
  • the operating system 6021 includes various system programs, such as framework layer, core library layer, driver layer, etc., for realizing various basic services and processing hardware-based tasks.
  • the application program 6022 includes various application programs, such as a media player (Media Player), a browser (Browser), etc., and is used to realize various application services.
  • the program for implementing the method of the embodiment of the present application may be included in the application program 6022 .
  • the processor 601 by calling the program or instruction stored in the memory 602, specifically, the program or instruction stored in the application program 6022, the processor 601 is used to execute the method steps provided by each method embodiment, for example including :
  • the access information of each node in the first cluster is acquired by the client; the priority classification of data migration is performed on each node based on the access information to obtain a classification result; and the data of each node in the first cluster is migrated to the second cluster based on the classification result.
  • the access frequency corresponding to the client's access to each node in the first cluster within a preset time period is acquired.
  • the nodes are sorted according to the order of access frequency from large to small to obtain the node sequence; according to the preset ratio, the priority classification of data migration is performed on each node in the node sequence to obtain classification results.
  • the data of each node in the first cluster is migrated to the second cluster according to the priority category.
  • the type of the data access request is acquired, wherein the data access request carries a target data identifier; based on the type of the data access request, access control is performed on the target data.
  • the target data is fed back based on the data access request; if the type of the data access request is update, then the data status of the target data is determined based on the target data identifier .
  • a prompt is given that the target data is in the migration state and cannot be accessed; if the data state is not migrated, the update operation of the data access request is allowed; if the data state If the migration is completed, the target data in the first cluster and the second cluster are updated.
  • migration control is performed on the data of each node in different priority categories.
  • the methods disclosed in the foregoing embodiments of the present application may be applied to the processor 601 or implemented by the processor 601 .
  • the processor 601 may be an integrated circuit chip and has signal processing capabilities. In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in the processor 601 or an instruction in the form of software.
  • the above-mentioned processor 601 may be a general-purpose processor, a digital signal processor (Digital Signal Processor, DSP), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), a ready-made programmable gate array (Field Programmable Gate Array, FPGA) or other Programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.
  • a general-purpose processor may be a microprocessor, or the processor may be any conventional processor, or the like.
  • the steps of the methods disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software units in the decoding processor.
  • the software unit may be located in a mature storage medium in the field such as random access memory, flash memory, read-only memory, programmable read-only memory or electrically erasable programmable memory, register.
  • the storage medium is located in the memory 602, and the processor 601 reads the information in the memory 602, and completes the steps of the above method in combination with its hardware.
  • the processing unit can be implemented in one or more application specific integrated circuits (Application Specific Integrated Circuits, ASIC), digital signal processor (Digital Signal Processing, DSP), digital signal processing device (DSPDevice, DSPD), programmable logic Equipment (Programmable Logic Device, PLD), Field-Programmable Gate Array (Field-Programmable Gate Array, FPGA), general-purpose processor, controller, microcontroller, microprocessor, other electronic units for performing the functions of this application or in its combination.
  • ASIC Application Specific Integrated Circuits
  • DSP Digital Signal Processing
  • DSPDevice digital signal processing device
  • PLD programmable logic Equipment
  • Field-Programmable Gate Array Field-Programmable Gate Array
  • FPGA Field-Programmable Gate Array
  • the techniques herein may be implemented by units that perform the functions herein.
  • Software codes can be stored in memory and executed by a processor.
  • Memory can be implemented within the processor or external to the processor.
  • the computer device provided in this embodiment may be the computer device shown in Figure 6, which can execute all the steps of the cluster data migration method shown in Figure 2-4, and then realize the technical effect of the cluster data migration method shown in Figure 2-4 , please refer to the related descriptions in FIG. 2-4 for details, which are not described here for brevity.
  • the present application also provides a storage medium (computer-readable storage medium).
  • the storage medium here stores one or more programs.
  • the storage medium may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a read-only memory, a flash memory, a hard disk or a solid-state disk; the memory may also include the above-mentioned types of memory combination.
  • the processor is used to execute the cluster data migration program stored in the memory, so as to realize the following steps of the cluster data migration method performed on the computer device side:
  • the access information of each node in the first cluster is acquired by the client; the priority classification of data migration is performed on each node based on the access information to obtain a classification result; and the data of each node in the first cluster is migrated to the second cluster based on the classification result.
  • the access frequency corresponding to the client's access to each node in the first cluster within a preset time period is acquired.
  • the nodes are sorted according to the order of access frequency from large to small to obtain the node sequence; according to the preset ratio, the priority classification of data migration is performed on each node in the node sequence to obtain classification results.
  • the data of each node in the first cluster is migrated to the second cluster according to the priority category.
  • the type of the data access request is acquired, wherein the data access request carries a target data identifier; based on the type of the data access request, access control is performed on the target data.
  • the target data is fed back based on the data access request; if the type of the data access request is update, then the data status of the target data is determined based on the target data identifier .
  • a prompt is given that the target data is in the migration state and cannot be accessed; if the data state is not migrated, the update operation of the data access request is allowed; if the data state If the migration is completed, the target data in the first cluster and the second cluster are updated.
  • migration control is performed on the data of each node in different priority categories.
  • Nonvolatile memory can include read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory.
  • Volatile memory can include random access memory (RAM) or external cache memory.
  • RAM random access memory
  • RAM is available in many forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Chain Synchlink DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

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Abstract

本申请涉及一种集群数据迁移方法、装置、计算机设备及存储介质，方法包括：获取用户端访问第一集群中各节点的访问信息；基于访问信息对各节点进行数据迁移的优先级分类，得到分类结果；基于分类结果将第一集群中各节点的数据迁移至第二集群。

Description

集群数据迁移方法、装置、计算机设备及存储介质
相关申请的交叉引用
本申请要求于2021年12月10日提交中国专利局，申请号为202111514759.8，申请名称为“集群数据迁移方法、装置、计算机设备及存储介质”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及数据处理领域，尤其涉及一种集群数据迁移方法、装置、计算机设备及存储介质。
背景技术
在当前的分布式存储集群环境中，可能需要对存储产品的版本、技术框架以及存储硬件进行更新换代，为了提升用户的使用体验，降低经营成本，需提高存储集群的性能，在对存储产品的版本、技术框架以及存储硬件进行更新换代的过程中，往往需要将老旧集群进行替换。
发明人意识到，目前，老旧集群替换的过程中，首先将旧集群业务停止，然后将数据迁移到新的集群中，以此保证新老集群的数据一致性，但是，当数据量较大时，需要花费大量的时间进行数据迁移，在数据迁移期间用户无法正常使用，严重影响用户的日常业务进行，降低用户的使用体验。
发明内容
第一方面，本申请提供一种集群数据迁移方法，包括：
获取用户端访问第一集群中各节点的访问信息；
基于访问信息对各节点进行数据迁移的优先级分类，得到分类结果；和
基于分类结果将第一集群中各节点的数据迁移至第二集群。
第二方面，本申请提供一种集群数据迁移装置，包括：
获取模块，用于获取用户端访问第一集群中各节点的访问信息；
分类模块，用于基于访问信息对各节点进行数据迁移的优先级分类，得到分类结果；和
迁移模块，用于基于分类结果将第一集群中各节点的数据迁移至第二集群。
第三方面，本申请提供一种计算机设备，包括存储器及一个或多个处理器，存储器中储存有计算机可读指令，上述计算机可读指令被上述一个或多个处理器执行时，使得上述一个或多个处理器执行上述集群数据迁移方法的步骤。
第四方面，本申请提供一个或多个存储有计算机可读指令的非易失性计算机可读存储介质，上述计算机可读指令被一个或多个处理器执行时，使得上述一个或多个处理器执行上述集群数据迁移方法的步骤。
本申请的一个或多个实施例的细节在下面的附图和描述中提出。本申请的其它特征和优点将从说明书、附图以及权利要求书变得明显。
附图说明
为了更清楚地说明本申请实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请的实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据提供的附图获得其他的附图。
图1为本申请根据一个或多个实施例提供的一种集群数据迁移方法的系统架构图；
图2为本申请根据一个或多个实施例提供的一种集群数据迁移方法的流程示意图；
图3为本申请根据一个或多个实施例提供的另一种集群数据迁移方法的流程示意图；
图4为本申请根据一个或多个实施例提供的一种集群数据迁移过程中对数据访问控制的流程示意图；
图5为本申请根据一个或多个实施例提供的一种集群数据迁移装置的结构示意图；
图6为本申请根据一个或多个实施例提供的一种计算机设备的结构示意图。
具体实施方式
为使本申请实施例的目的、技术方案和优点更加清楚，下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域 普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
为便于对本申请实施例的理解，下面将结合附图以具体实施例做进一步的解释说明，实施例并不构成对本申请实施例的限定。
图1为本申请提供的一种集群数据迁移方法的系统架构图，如图1所示，本方法优先适用于分布式存储集群的数据迁移场景，系统架构包括：旧集群(以下称为第一集群)、新集群(以下称为第二集群)、包含数据访问统计，时段流量统计，数据分析评估，配置中心，控制中心，数据访问/迁移功能的计算机设备，该计算机设备用于完成本方案的集群数据迁移方法。
其中，数据访问统计对第一集群在一定时段内接收到的访问信息进行采集分析，访问信息包括多个节点接收到的访问频次。
时段流量统计可以对第一集群的访问流量按小时进行统计，对各个时间段内的流量值、系统负载状况进行统计。
数据分析评估可以对第一集群的访问流量按天进行分析，对时段内迁移数据量进行评估。
配置中心根据数据访问统计提供的数据，可以以小时为单位，配置集群时间段内的迁移速度以及各个节点的数据迁移优先级，同时根据和时段流量统计的时段内的集群流量负载状况自动化调整该时间段内迁移速度，同时对集群的CPU以及带宽进行监控，设置阈值，当数据迁移量占用CPU以及带宽超过阈值时，可以自动降低迁移速度。
控制中心提供整个集群数据迁移的启停接口、迁移进度以及当前迁移数据的概览信息。
数据访问/迁移功能提供在数据迁移或呗访问时对迁移文件的控制，防止出现第一和第二集群数据不一致。
图2为本申请提供的一种集群数据迁移方法的流程示意图，如图2所示，该方法具体包括：
S21、获取用户端访问第一集群中各节点的访问信息。
在本申请实施例中，获取第一集群中各个节点在一定时段内接收到的访问信息，访问信息包括每个节点在一定时段内接收到的访问量。
例如，第一集群中包含10个节点，在早9点至早10点这一个小时内，第一集群中节点1接收到访问量一万次，节点2接收到访问量1.2万次，节点3接收到访问量1.5 万次，节点4接收到访问量3千次，节点5接收到访问量2千次，节点6接收到访问量3万次，节点7接收到访问量3.5万次，节点8接收到访问量3千次，节点9接收到访问量1千次，节点10接收到访问量5万次。
S22、基于访问信息对各节点进行数据迁移的优先级分类，得到分类结果。
基于S21中获取到的各节点的访问信息即一定时段内接收到的访问量，可以按照访问量对各个节点进行数据迁移的优先级分类，例如，以1万次和3万次为分段临界值，低于1万次访问量的节点可以划分到低级类别，1万次至3万次访问量的节点可以划分到中级类别，高于3万次访问量的节点可以划分到高级类别。
由上述可以划分节点4、节点5、节点8、节点9为低级类别；划分节点1、节点2、节点3、节点6为中级类别；划分节点7、节点10为高级类别。
S23、基于分类结果将第一集群中各节点的数据迁移至第二集群。
基于S22中对各个节点的数据迁移的优先级分类结果，可以按照优先级类别对各个节点进行数据迁移。数据迁移的时间如果是数据访问低峰时段(例如，凌晨1点至5点)，可以按照高级类别-中级类别-低级类别的顺序将每个优先级类别中的节点的数据进行迁移，即首先迁移高级类别中的各节点的数据，然后迁移中级类别中各节点的数据，最后迁移低级类别中各节点的数据。
可选的，数据迁移的时间如果是数据访问高峰时段(例如，上午9点至下午5点)，可以按照低级类别-中级类别-高级类别的顺序将每个优先级类别中的节点的数据进行迁移，即首先迁移低级类别中的各节点的数据，然后迁移中级类别中各节点的数据，最后迁移高级类别中各节点的数据。
本申请实施例提供的集群数据迁移方法，通过获取用户端访问第一集群中各节点的访问信息；基于访问信息对各节点进行数据迁移的优先级分类，得到分类结果；基于分类结果将第一集群中各节点的数据迁移至第二集群，相比于现有技术中老旧集群替换的过程中，首先需要将旧集群业务停止，然后将数据迁移到新的集群中，当数据量较大时，需要花费大量的时间进行数据迁移，在数据迁移期间用户无法正常使用，严重影响用户的日常业务进行的问题，由本方法，可以实现在不停止旧集群业务的情况下进行数据迁移，避免数据迁移时停止旧集群业务带来的用户无法正常使用的问题，提升用户体验。
图3为本申请提供的另一种集群数据迁移方法的流程示意图，如图3所示，该方法具体包括：
S31、获取预设时间段内用户端访问第一集群中各节点对应的访问频率。
本申请实施例中，可以预设一时间段(例如，早9点至晚7点)，获取该预设时间段内的用户端访问第一集群中各个节点所对应的访问频率。
例如，第一集群中包含5个节点，在早9点至晚7点，节点1接收到访问量总计8万次，访问频率为8千次每小时，节点2接收到访问量总计3万次，访问频率为3千次每小时，节点3接收到访问量总计12万次，访问频率为1.2万次每小时，节点4接收到访问量总计3千次，访问频率为3百次每小时，节点5接收到访问量总计1万次，访问频率为1千次每小时。
S32、根据访问频率由大到小的顺序对各节点进行排序，得到节点序列。
可以根据访问频率由大到小的顺序对各个节点进行排序，得到节点序列：节点3、节点1、节点2、节点5、节点4。
S33、根据预设比例，对节点序列中各节点进行数据迁移的优先级分类，得到分类结果。
本申请实施例中，可以预设一数据迁移的优先级分类比例(例如，1:2:2)，根据该比例对节点序列中各个节点进行数据迁移的优先级分类，优先级分类可以分类高级、中级、低级三种类别，那么，按照分类比例，节点3可以被分配到高级类别，节点1和节点2可以被分配到中级类别，节点5和节点4可以被分配到低级类别。
S34、基于分类结果，按照优先级类别将第一集群中各节点的数据迁移至第二集群。
基于S33中对各个节点的数据迁移的优先级分类结果，可以按照优先级类别对各个节点进行数据迁移，将数据迁移至第二集群。数据迁移的时间如果是数据访问低峰时段(例如，凌晨1点至5点)，可以按照高级类别-中级类别-低级类别的顺序将每个优先级类别中的节点的数据进行迁移，即首先迁移高级类别中的各节点的数据，然后迁移中级类别中各节点的数据，最后迁移低级类别中各节点的数据。
可选的，数据迁移的时间如果是数据访问高峰时段(例如，上午9点至下午5点)，可以按照低级类别-中级类别-高级类别的顺序将每个优先级类别中的节点的数据进行迁移，即首先迁移低级类别中的各节点的数据，然后迁移中级类别中各节点的数据，最后迁移高级类别中各节点的数据。
在一个可能的实施方式中，还可以基于各个节点的访问信息以及当前时间，对不同优先级类别中的各节点的数据进行迁移控制。例如，节点1的数据访问高峰时段为早8点至早9点，则可以避开该时段，在其他时段进行节点1的数据迁移；又如，节点2的数据访问高峰时段为早10点至晚9点，也可以避开该时段，在其他时段进行节点2 的数据迁移。
本申请实施例提供的集群数据迁移方法，通过获取用户端访问第一集群中各节点的访问信息；基于访问信息对各节点进行数据迁移的优先级分类，得到分类结果；基于分类结果将第一集群中各节点的数据迁移至第二集群，相比于现有技术中老旧集群替换的过程中，首先需要将旧集群业务停止，然后将数据迁移到新的集群中，当数据量较大时，需要花费大量的时间进行数据迁移，在数据迁移期间用户无法正常使用，严重影响用户的日常业务进行的问题，由本方法，可以实现在不停止旧集群业务的情况下进行数据迁移，避免数据迁移时停止旧集群业务带来的用户无法正常使用的问题，提升用户体验。
图4为本申请提供的一种集群数据迁移过程中对数据访问控制的流程示意图，如图4所示，该方法具体包括：
S41、获取数据访问请求的类型，其中，数据访问请求中携带有目标数据标识。
本申请实施例中，在集群数据迁移过程中可能存在用户端对数据的访问请求，需要对访问请求进行限制。
获取用户端发送的数据访问请求，解析该数据访问请求的类型，包括但不限于：只读、更新，其中，更新还可以包括增加、删除、修改等。
S42、若数据访问请求的类型为只读，则基于数据访问请求反馈目标数据。
本申请实施例中，可以对正在迁移的数据进行加锁，当数据完全迁移完成后释放锁，数据在进行迁移的过程中只允许进行读操作，不允许进行更新操作，防止数据迁移过程中被修改，造成第一和第二集群数据不一致。
若数据访问请求的类型为只读，则可以基于数据访问请求中携带的目标数据标识查询并反馈目标数据。
S43、若数据访问请求的类型为更新，则基于目标数据标识确定目标数据的数据状态。
当第一集群接收到的数据访问请求的类型为更新时，则基于数据访问请求中携带的目标数据标识，查询目标数据的数据状态，数据状态包括：迁移状态、未被迁移、已完成迁移。
S44、若数据状态为迁移状态，则进行目标数据处于迁移状态无法访问的提示。
若目标数据的数据状态为迁移状态，表征目标数据正在迁移，则返回相应的禁止访问提示，即目标数据处于迁移状态无法访问。
S45、若数据状态为未被迁移，则允许数据访问请求的更新操作。
若目标数据的数据状态为未被迁移，则允许数据访问请求的更新操作，进行数据更新。
S46、若数据状态为已完成迁移，则将第一集群和第二集群中的目标数据进行更新。
若目标数据的数据状态为已完成迁移，则将第一集群和第二集群中的目标数据进行更新。
可选的，若更新操作为数据增加操作，则先将数据插入到第一集群中，完成后再进行数据迁移。
需要说明的事，进行增加、修改或者删除操作时将待操作的数据进行加锁，加锁的数据在编辑操作过程中不允许进行迁移，锁释放后才可以进行数据迁移，保证第一集群和第二集群的数据一致性。
本申请实施例提供的集群数据迁移方法，通过获取数据访问请求的类型，基于数据访问请求的类型，对目标数据进行访问控制，由本方法，可以实现对数据迁移过程中的数据访问操作的控制，避免数据迁移时由于访问操作造成第一集群和第二集群数据不一致的问题，提升集群服务效果。
图5为本申请实施例提供的一种集群数据迁移装置的结构示意图，具体包括：
获取模块501，用于获取用户端访问第一集群中各节点的访问信息；
分类模块502，用于基于访问信息对各节点进行数据迁移的优先级分类，得到分类结果；
迁移模块503，用于基于分类结果将第一集群中各节点的数据迁移至第二集群。
在一个或多个可能的实施方式中，获取模块501，具体用于获取预设时间段内用户端访问第一集群中各节点对应的访问频率。
在一个或多个可能的实施方式中，获取模块501，还用于获取数据访问请求的类型，其中，数据访问请求中携带有目标数据标识；基于数据访问请求的类型，对目标数据进行访问控制。
在一个或多个可能的实施方式中，分类模块502，具体用于根据访问频率由大到小的顺序对各节点进行排序，得到节点序列；根据预设比例，对节点序列中各节点进行数据迁移的优先级分类，得到分类结果。
在一个或多个可能的实施方式中，迁移模块503，具体用于基于分类结果，按照优先级类别将第一集群中各节点的数据迁移至第二集群。
在一个或多个可能的实施方式中，迁移模块503，还用于基于访问信息以及当前时 间，对不同优先级类别中的各节点的数据进行迁移控制。
在一个或多个可能的实施方式中，集群数据迁移装置还包括访问控制模块，具体用于若数据访问请求的类型为只读，则基于数据访问请求反馈目标数据；若数据访问请求的类型为更新，则基于目标数据标识确定目标数据的数据状态；若数据状态为迁移状态，则进行目标数据处于迁移状态无法访问的提示；若数据状态为未被迁移，则允许数据访问请求的更新操作；若数据状态为已完成迁移，则将第一集群和第二集群中的目标数据进行更新。
本实施例提供的集群数据迁移装置可以是如图5中所示的集群数据迁移装置，可执行如图2-4中集群数据迁移方法的所有步骤，进而实现图2-4所示集群数据迁移方法的技术效果，具体请参照图2-4相关描述，为简洁描述，在此不作赘述。
图6为本申请实施例提供的一种计算机设备的结构示意图，图6所示的计算机设备600包括：至少一个处理器601、存储器602、至少一个网络接口604和其他用户接口603。计算机设备600中的各个组件通过总线系统605耦合在一起。可理解，总线系统605用于实现这些组件之间的连接通信。总线系统605除包括数据总线之外，还包括电源总线、控制总线和状态信号总线。但是为了清楚说明起见，在图6中将各种总线都标为总线系统605。
其中，用户接口603可以包括显示器、键盘或者点击设备(例如，鼠标，轨迹球(trackball)、触感板或者触摸屏等。
可以理解，本申请实施例中的存储器602可以是易失性存储器或非易失性存储器，或可包括易失性和非易失性存储器两者。其中，非易失性存储器可以是只读存储器(Read-Only Memory，ROM)、可编程只读存储器(Programmable ROM，PROM)、可擦除可编程只读存储器(Erasable PROM，EPROM)、电可擦除可编程只读存储器(Electrically EPROM，EEPROM)或闪存。易失性存储器可以是随机存取存储器(Random Access Memory，RAM)，其用作外部高速缓存。通过示例性但不是限制性说明，许多形式的RAM可用，例如静态随机存取存储器(Static RAM，SRAM)、动态随机存取存储器(Dynamic RAM，DRAM)、同步动态随机存取存储器(Synchronous DRAM，SDRAM)、双倍数据速率同步动态随机存取存储器(Double Data Rate SDRAM，DDRSDRAM)、增强型同步动态随机存取存储器(Enhanced SDRAM，ESDRAM)、同步连接动态随机存取存储器(Synch link DRAM，SLDRAM)和直接内存总线随机存取存储器(Direct Rambus RAM，DRRAM)。本文描述的存储器602旨在包括但不限于这些和任意其它适合类型的存储器。
在一个或多个实施方式中，存储器602存储了如下的元素，可执行单元或者数据结构，或者他们的子集，或者他们的扩展集：操作系统6021和应用程序6022。
其中，操作系统6021，包含各种系统程序，例如框架层、核心库层、驱动层等，用于实现各种基础业务以及处理基于硬件的任务。应用程序6022，包含各种应用程序，例如媒体播放器(Media Player)、浏览器(Browser)等，用于实现各种应用业务。实现本申请实施例方法的程序可以包含在应用程序6022中。
在本申请实施例中，通过调用存储器602存储的程序或指令，具体的，可以是应用程序6022中存储的程序或指令，处理器601用于执行各方法实施例所提供的方法步骤，例如包括：
获取用户端访问第一集群中各节点的访问信息；基于访问信息对各节点进行数据迁移的优先级分类，得到分类结果；基于分类结果将第一集群中各节点的数据迁移至第二集群。
在一个或多个可能的实施方式中，获取预设时间段内用户端访问第一集群中各节点对应的访问频率。
在一个或多个可能的实施方式中，根据访问频率由大到小的顺序对各节点进行排序，得到节点序列；根据预设比例，对节点序列中各节点进行数据迁移的优先级分类，得到分类结果。
在一个或多个可能的实施方式中，基于分类结果，按照优先级类别将第一集群中各节点的数据迁移至第二集群。
在一个或多个可能的实施方式中，获取数据访问请求的类型，其中，数据访问请求中携带有目标数据标识；基于数据访问请求的类型，对目标数据进行访问控制。
在一个或多个可能的实施方式中，若数据访问请求的类型为只读，则基于数据访问请求反馈目标数据；若数据访问请求的类型为更新，则基于目标数据标识确定目标数据的数据状态。
在一个或多个可能的实施方式中，若数据状态为迁移状态，则进行目标数据处于迁移状态无法访问的提示；若数据状态为未被迁移，则允许数据访问请求的更新操作；若数据状态为已完成迁移，则将第一集群和第二集群中的目标数据进行更新。
在一个或多个可能的实施方式中，基于访问信息以及当前时间，对不同优先级类别中的各节点的数据进行迁移控制。
上述本申请实施例揭示的方法可以应用于处理器601中，或者由处理器601实现。处理器601可能是一种集成电路芯片，具有信号的处理能力。在实现过程中，上 述方法的各步骤可以通过处理器601中的硬件的集成逻辑电路或者软件形式的指令完成。上述的处理器601可以是通用处理器、数字信号处理器(Digital Signal Processor，DSP)、专用集成电路(Application Specific Integrated Circuit，ASIC)、现成可编程门阵列(Field Programmable Gate Array，FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件。可以实现或者执行本申请实施例中的公开的各方法、步骤及逻辑框图。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。结合本申请实施例所公开的方法的步骤可以直接体现为硬件译码处理器执行完成，或者用译码处理器中的硬件及软件单元组合执行完成。软件单元可以位于随机存储器，闪存、只读存储器，可编程只读存储器或者电可擦写可编程存储器、寄存器等本领域成熟的存储介质中。该存储介质位于存储器602，处理器601读取存储器602中的信息，结合其硬件完成上述方法的步骤。
可以理解的是，本文描述的这些实施例可以用硬件、软件、固件、中间件、微码或其组合来实现。对于硬件实现，处理单元可以实现在一个或多个专用集成电路(Application Specific Integrated Circuits，ASIC)、数字信号处理器(Digital Signal Processing，DSP)、数字信号处理设备(DSPDevice，DSPD)、可编程逻辑设备(Programmable Logic Device，PLD)、现场可编程门阵列(Field-Programmable Gate Array，FPGA)、通用处理器、控制器、微控制器、微处理器、用于执行本申请功能的其它电子单元或其组合中。
对于软件实现，可通过执行本文功能的单元来实现本文的技术。软件代码可存储在存储器中并通过处理器执行。存储器可以在处理器中或在处理器外部实现。
本实施例提供的计算机设备可以是如图6中所示的计算机设备，可执行如图2-4中集群数据迁移方法的所有步骤，进而实现图2-4所示集群数据迁移方法的技术效果，具体请参照图2-4相关描述，为简洁描述，在此不作赘述。
本申请还提供了一种存储介质(计算机可读存储介质)。这里的存储介质存储有一个或者多个程序。其中，存储介质可以包括易失性存储器，例如随机存取存储器；存储器也可以包括非易失性存储器，例如只读存储器、快闪存储器、硬盘或固态硬盘；存储器还可以包括上述种类的存储器的组合。
当存储介质中一个或者多个程序可被一个或者多个处理器执行，以实现上述在计算机设备侧执行的集群数据迁移方法。
处理器用于执行存储器中存储的集群数据迁移程序，以实现以下在计算机设备侧执行的集群数据迁移方法的步骤：
获取用户端访问第一集群中各节点的访问信息；基于访问信息对各节点进行数据迁移的优先级分类，得到分类结果；基于分类结果将第一集群中各节点的数据迁移至第二集群。
在一个或多个可能的实施方式中，获取预设时间段内用户端访问第一集群中各节点对应的访问频率。
在一个或多个可能的实施方式中，根据访问频率由大到小的顺序对各节点进行排序，得到节点序列；根据预设比例，对节点序列中各节点进行数据迁移的优先级分类，得到分类结果。
在一个或多个可能的实施方式中，基于分类结果，按照优先级类别将第一集群中各节点的数据迁移至第二集群。
在一个或多个可能的实施方式中，获取数据访问请求的类型，其中，数据访问请求中携带有目标数据标识；基于数据访问请求的类型，对目标数据进行访问控制。
在一个或多个可能的实施方式中，若数据访问请求的类型为只读，则基于数据访问请求反馈目标数据；若数据访问请求的类型为更新，则基于目标数据标识确定目标数据的数据状态。
在一个或多个可能的实施方式中，若数据状态为迁移状态，则进行目标数据处于迁移状态无法访问的提示；若数据状态为未被迁移，则允许数据访问请求的更新操作；若数据状态为已完成迁移，则将第一集群和第二集群中的目标数据进行更新。
在一个或多个可能的实施方式中，基于访问信息以及当前时间，对不同优先级类别中的各节点的数据进行迁移控制。
专业人员应该还可以进一步意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够以电子硬件、计算机软件或者二者的结合来实现，为了清楚地说明硬件和软件的可互换性，在上述说明中已经按照功能一般性地描述了各示例的组成及步骤。这些功能究竟以硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本申请的范围。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程，是可以通过计算机可读指令来指令相关的硬件来完成，上述的计算机可读指令可存储于一非易失性计算机可读取存储介质中，该计算机可读指令在执行时，可包括如上述各方法的实施例的流程。其中，本申请所提供的各实施例中所使用的对存储器、存储、数据库或其它介质的任何引用，均可包括非易失性和/或易失性存储器。非易失性存储器可包括只读存 储器(ROM)、可编程ROM(PROM)、电可编程ROM(EPROM)、电可擦除可编程ROM(EEPROM)或闪存。易失性存储器可包括随机存取存储器(RAM)或者外部高速缓冲存储器。作为说明而非局限，RAM以多种形式可得，诸如静态RAM(SRAM)、动态RAM(DRAM)、同步DRAM(SDRAM)、双数据率SDRAM(DDRSDRAM)、增强型SDRAM(ESDRAM)、同步链路(Synchlink)DRAM(SLDRAM)、存储器总线(Rambus)直接RAM(RDRAM)、直接存储器总线动态RAM(DRDRAM)、以及存储器总线动态RAM(RDRAM)等。
以上实施例的各技术特征可以进行任意的组合，为使描述简洁，未对上述实施例中的各个技术特征所有可能的组合都进行描述，然而，只要这些技术特征的组合不存在矛盾，都应当认为是本说明书记载的范围。
以上上述实施例仅表达了本申请的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对申请专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本申请构思的前提下，还可以做出若干变形和改进，这些都属于本申请的保护范围。因此，本申请专利的保护范围应以所附权利要求为准。

Claims (20)

  1. 一种集群数据迁移方法，其特征在于，包括：
    获取用户端访问第一集群中各节点的访问信息；
    基于所述访问信息对各节点进行数据迁移的优先级分类，得到分类结果；和
    基于所述分类结果将所述第一集群中各节点的数据迁移至第二集群。
  2. 根据权利要求1所述的方法，其特征在于，所述获取用户端访问第一集群中各节点的访问信息，包括：
    获取所述第一集群中各所述节点在预设时间段内接收到的访问量。
  3. 根据权利要求1所述的方法，其特征在于，所述获取用户端访问第一集群中各节点的访问信息，包括：
    获取预设时间段内用户端访问第一集群中各节点对应的访问频率。
  4. 根据权利要求3所述的方法，其特征在于，所述基于所述访问信息对各节点进行数据迁移的优先级分类，得到分类结果，包括：
    根据访问频率由大到小的顺序对所述各节点进行排序，得到节点序列；和
    根据预设比例，对所述节点序列中各节点进行数据迁移的优先级分类，得到分类结果。
  5. 根据权利要求4所述的方法，其特征在于，所述基于所述分类结果将所述第一集群中各节点的数据迁移至第二集群，包括：
    基于所述分类结果，按照优先级类别将所述第一集群中各节点的数据迁移至第二集群。
  6. 根据权利要求5所述的方法，其特征在于，所述方法还包括：
    获取数据访问请求的类型；和
    基于所述数据访问请求的类型，对目标数据进行访问控制。
  7. 根据权利要求6所述的方法，其特征在于，所述数据访问请求中携带有目标数据标识。
  8. 根据权利要求6所述的方法，其特征在于，所述基于所述数据访问请求的类型，对目标数据进行访问控制，包括：
    在所述数据访问请求的类型为只读时，基于所述数据访问请求反馈目标数据。
  9. 根据权利要求6所述的方法，其特征在于，所述基于所述数据访问请求的类型，对目标数据进行访问控制，包括：
    在所述数据访问请求的类型为更新时，基于所述目标数据标识确定目标数据的数据状态。
  10. 根据权利要求9所述的方法，其特征在于，所述更新包括增加、删除和修改。
  11. 根据权利要求10所述的方法，其特征在于，在所述更新为增加时，将数据插入到第一集群中，完成后再进行数据迁移。
  12. 根据权利要求9所述的方法，其特征在于，所述数据状态包括迁移状态、未被迁移和已完成迁移。
  13. 根据权利要求12所述的方法，其特征在于，所述方法还包括：
    在所述数据状态为迁移状态时，进行所述目标数据处于迁移状态无法访问的提示。
  14. 根据权利要求12所述的方法，其特征在于，所述方法还包括：
    在所述数据状态为未被迁移时，允许所述数据访问请求的更新操作；
  15. 根据权利要求12所述的方法，其特征在于，所述方法还包括：
    在所述数据状态为已完成迁移时，将所述第一集群和所述第二集群中的目标数据进行更新。
  16. 根据权利要求1所述的方法，其特征在于，所述方法还包括：
    基于所述访问信息以及当前时间，对不同优先级类别中的各节点的数据进行迁移控制。
  17. 一种集群数据迁移装置，其特征在于，包括：
    获取模块，用于获取用户端访问第一集群中各节点的访问信息；
    分类模块，用于基于所述访问信息对各节点进行数据迁移的优先级分类，得到分类结果；和
    迁移模块，用于基于所述分类结果将所述第一集群中各节点的数据迁移至第二集群。
  18. 根据权利要求17所述的装置，其特征在于，所述获取模块还用于获取预设时间段内用户端访问第一集群中各节点对应的访问频率。
  19. 一种计算机设备，其特征在于，包括存储器及一个或多个处理器，所述存储器中储存有计算机可读指令，所述计算机可读指令被所述一个或多个处理器执行时，使得所述一个或多个处理器执行如权利要求1-16中任一项所述的集群数据迁移方法。
  20. 一个或多个存储有计算机可读指令的非易失性计算机可读存储介质，其特征在 于，所述计算机可读指令被一个或多个处理器执行时，使得所述一个或多个处理器执行如权利要求1-16中任一项所述的集群数据迁移方法。
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CN110569233A (zh) * 2019-06-30 2019-12-13 华为技术有限公司 一种热点数据的管理方法、装置及系统
CN111880744A (zh) * 2020-07-29 2020-11-03 苏州浪潮智能科技有限公司 一种数据迁移方法、装置、电子设备和介质
CN112015347A (zh) * 2020-08-28 2020-12-01 北京浪潮数据技术有限公司 一种数据迁移方法、装置及相关设备
CN114490566A (zh) * 2021-12-10 2022-05-13 苏州浪潮智能科技有限公司 集群数据迁移方法、装置、计算机设备及存储介质

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