WO2021057377A1 - Procédé de stockage de données et dispositif de stockage de données - Google Patents

Procédé de stockage de données et dispositif de stockage de données Download PDF

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WO2021057377A1
WO2021057377A1 PCT/CN2020/111903 CN2020111903W WO2021057377A1 WO 2021057377 A1 WO2021057377 A1 WO 2021057377A1 CN 2020111903 W CN2020111903 W CN 2020111903W WO 2021057377 A1 WO2021057377 A1 WO 2021057377A1
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data
storage
storage device
processing software
nodes
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PCT/CN2020/111903
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English (en)
Chinese (zh)
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杨艳伟
孙荣宗
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华为技术有限公司
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
    • G06F3/0601—Interfaces specially adapted for storage systems
    • G06F3/0602—Interfaces specially adapted for storage systems specifically adapted to achieve a particular effect
    • G06F3/0614—Improving the reliability of storage systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
    • G06F11/14—Error detection or correction of the data by redundancy in operation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
    • G06F11/14—Error detection or correction of the data by redundancy in operation
    • G06F11/1402—Saving, restoring, recovering or retrying
    • G06F11/1446—Point-in-time backing up or restoration of persistent data
    • G06F11/1448—Management of the data involved in backup or backup restore
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
    • G06F3/0601—Interfaces specially adapted for storage systems
    • G06F3/0628—Interfaces specially adapted for storage systems making use of a particular technique
    • G06F3/0638—Organizing or formatting or addressing of data
    • G06F3/0644—Management of space entities, e.g. partitions, extents, pools
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
    • G06F3/0601—Interfaces specially adapted for storage systems
    • G06F3/0628—Interfaces specially adapted for storage systems making use of a particular technique
    • G06F3/0662—Virtualisation aspects
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
    • G06F3/0601—Interfaces specially adapted for storage systems
    • G06F3/0668—Interfaces specially adapted for storage systems adopting a particular infrastructure
    • G06F3/067—Distributed or networked storage systems, e.g. storage area networks [SAN], network attached storage [NAS]

Definitions

  • This application relates to the field of computer networks, and in particular to a data storage method and data storage device.
  • the multi-copy storage method achieves data storage reliability through high redundancy. It should be noted that although this method has the advantage of easy data recovery, sometimes multiple backups are stored in the same data storage device during storage. When the data storage device that saves multiple backup data is out of power, downtime, etc., the number of copies that can be used is not the total number of copies minus one, but the total number of copies minus the current data storage device The number of copies stored, that is, the number of copies actually available is less than expected, which reduces the reliability of storage.
  • the embodiments of the present application provide a data storage method and a data storage device, which can improve the reliability of data storage.
  • an embodiment of the present application provides a data storage method, and the method includes the following steps:
  • the first control instruction instructs to install data processing software in N storage devices, create a storage resource pool and a virtual machine in any one of the N storage devices, any one of the The virtual machine uses the created storage resource pool in its corresponding storage device to store data, any one of the virtual machines is used as an optional data node of the data processing software, and the N is an integer greater than or equal to 2;
  • the configuration instruction includes: setting the number of copies M for data storage, and a storage awareness strategy;
  • the storage awareness strategy includes: determining M data nodes for storing data, and the M data nodes are located in M In different storage devices, the M is an integer less than or equal to the N;
  • the storage resource pools created in the N storage devices adopt erasure code EC encoding.
  • EC coding is used in the storage resource pool created by the storage device.
  • the lost data can be calculated to ensure that some data can still be used after loss.
  • the embodiment of the present application saves storage space and improves storage utilization.
  • the storage utilization rate of the hard disk when the EC encoding adopts 8 data blocks and 1 check block 8D1P mode, the storage utilization rate of the hard disk is 88.89%, and when the EC encoding adopts 4D1P mode, the storage utilization rate of the hard disk is 80%.
  • the storage utilization rate of the hard disk is 80%, and when the EC encoding adopts the 4D2P mode, the storage utilization rate of the hard disk is 66.67%.
  • an embodiment of the present application provides a data storage device, and the storage device includes:
  • the sending unit is configured to send a first control instruction that instructs to install data processing software in N storage devices, and create a storage resource pool and a virtual machine in any one of the N storage devices , Any one of the virtual machines uses the created storage resource pool in the corresponding storage device to store data, any one of the virtual machines is used as an optional data node of the data processing software, and the N is greater than or equal to 2 Integer.
  • the acquiring unit is configured to acquire a configuration instruction, the configuration instruction includes: setting the number of copies M for data storage, and a storage awareness strategy; the storage awareness strategy includes: determining M data nodes for storing data, the M Data nodes are located in M different storage devices, and the M is an integer less than or equal to the N.
  • the determining unit is configured to determine M data nodes for storing data to be stored according to the configuration instruction.
  • the processing unit is configured to store the data to be stored in the M data nodes.
  • the storage resource pools created in the N storage devices adopt erasure code EC encoding.
  • EC coding is used in the storage resource pool created by the storage device.
  • the lost data can be calculated to ensure that some data can still be used after loss.
  • the embodiment of the present application saves storage space and improves storage utilization.
  • the storage utilization rate of the hard disk when the EC encoding adopts 8 data blocks and 1 check block 8D1P mode, the storage utilization rate of the hard disk is 88.89%, and when the EC encoding adopts 4D1P mode, the storage utilization rate of the hard disk is 80%.
  • the storage utilization rate of the hard disk is 80%, and when the EC encoding adopts the 4D2P mode, the storage utilization rate of the hard disk is 66.67%.
  • the storage device includes: a distributed server or a magnetic array.
  • the data processing software includes: distributed processing software Hadoop.
  • the M 2.
  • an embodiment of the present application provides a data storage system, including N storage devices such as the data storage device described in the second aspect or any one of the possible implementation manners of the second aspect, where N is greater than or An integer equal to 2.
  • an electronic device including:
  • One or more processors are One or more processors;
  • Storage device for storing one or more programs
  • the one or more processors When the one or more programs are executed by the one or more processors, the one or more processors implement the method described in the first aspect or any one of the possible implementation manners of the first aspect.
  • the embodiments of the present application provide a computer-readable medium on which a computer program is stored.
  • the program is executed by a processor, the implementation is as in the first aspect or any one of the possible implementation manners of the first aspect The method described.
  • FIG. 1 is a schematic flowchart of a data storage method provided by an embodiment of the present application.
  • Fig. 2 is a schematic flowchart of a data storage method provided by another embodiment of the present application.
  • FIG. 3 is a schematic diagram of the interaction flow of a data storage method provided by an embodiment of the present application.
  • Fig. 4 is a schematic structural diagram of a data storage device provided by an embodiment of the present application.
  • FIG. 1 is a data processing method provided by an embodiment of the present application, which includes the following steps.
  • the first control instruction instructs to install data processing software in N storage devices, and create a storage resource pool and a virtual machine in any one of the N storage devices, any The virtual machine uses the created storage resource pool in the corresponding storage device to store data, any one of the virtual machines is used as an optional data node of the data processing software, and the N is an integer greater than or equal to 2.
  • the storage device may be a distributed server or a magnetic array.
  • the configuration instruction includes: setting the number of copies M for data storage and a storage awareness strategy; the storage awareness strategy includes: determining M data nodes for storing data, the M data nodes Located in M different storage devices, the M is an integer less than or equal to the N.
  • the first control instruction instructs to install data processing software in three storage devices, and create storage resource pools and virtual machines in any one of the three storage devices.
  • Any virtual machine uses the created storage resource pool in its corresponding storage device to create data, and the three created virtual machines can be used as optional data nodes of the data processing software.
  • the data processing software may be distributed processing software Hadoop.
  • the data to be stored is saved to a certain number of data nodes.
  • FIG. 2 is a schematic flowchart of a data processing method provided by another embodiment of the present application. Including the following steps:
  • the first control instruction instructs to install data processing software in N storage devices, create a storage resource pool and a virtual machine in any one of the N storage devices, any The virtual machine uses the created storage resource pool in its corresponding storage device to store data, any one of the virtual machines is used as an optional data node of the data processing software, and the N is an integer greater than or equal to 2, and the storage The resource pool is coded with erasure code EC.
  • the storage device may be a distributed server or a magnetic array.
  • the storage utilization rate of the hard disk is 88.89%.
  • the storage utilization rate of the hard disk is 80%.
  • the storage utilization rate of the hard disk is 80%, and when the EC encoding adopts the 4D2P mode, the storage utilization rate of the hard disk is 66.67%.
  • the configuration instruction includes: setting the number of copies M for data storage, and a storage-aware strategy; the storage-aware strategy includes: determining M data nodes for storing data, and the M data nodes Located in M different storage devices, the M is an integer less than or equal to the N.
  • the first control instruction instructs to install data processing software in three storage devices, and create storage resource pools and virtual machines in any one of the three storage devices.
  • Any virtual machine uses the created storage resource pool in its corresponding storage device to create data, and the three created virtual machines can be used as optional data nodes of the data processing software.
  • the data processing software may be distributed processing software Hadoop.
  • the data to be stored is saved to a certain number of data nodes.
  • EC coding is used in the storage resource pool created by the storage device.
  • the lost data can be calculated to ensure that some data can still be used after loss.
  • the embodiment of the present application saves storage space and improves storage utilization.
  • FIG. 3 is a schematic diagram of the interaction flow of the data storage method provided by an embodiment of the present application. As shown in FIG. 3, when data storage is performed in this embodiment, the following steps are included.
  • a storage resource pool 1 can be created by SDS, and the storage resource pool 1 adopts EC coding in the 8D1P mode.
  • the resource pool 2 is created by SDS, and the resource pool 2 adopts the EC code of the 8D1P mode.
  • SDS is a storage architecture that can separate storage software and hardware. Unlike traditional Network Attached Storage (NAS) or Storage Area Network (SAN) systems, SDS is generally executed on industry standard systems or x86 systems, thereby eliminating software dependence on proprietary hardware Sex. SDS usually uses a distributed architecture to improve reliability and scalability, so SDS is sometimes called distributed storage. In fact, the difference between the two is obvious. Distributed storage refers to the architecture, which emphasizes that the architecture is distributed; SDS refers to software-defined storage, which emphasizes the decoupling of software and hardware.
  • NAS Network Attached Storage
  • SAN Storage Area Network
  • SDS has the following advantages: (1) Software and hardware decoupling.
  • the storage hardware is a commercial off-the-shelf (COTS) COTS, which avoids vendor lock-in, and purchases software and hardware hierarchically to reduce equipment procurement costs.
  • COTS commercial off-the-shelf
  • SDS adopts a distributed architecture, and the storage specifications are theoretically unlimited, and the storage specifications increase linearly with the number of servers (horizontal expansion).
  • SAN is limited by the processing capacity of the controller, and the specifications of a single set of magnetic arrays are limited. After the storage specifications exceed the specifications of the magnetic array, a set of storage equipment must be added (vertical expansion). (3) High reliability.
  • the virtual machine disk on Rack1 uses storage resource pool 1
  • the virtual machine on Rack2 uses storage resource pool 2.
  • Hadoop is a distributed system infrastructure often used in the prior art.
  • the Hadoop Distributed File System (HDFS) divides nodes into two categories, Name Node and Data Node.
  • the NameNode manages the namespace of the file system. It maintains the file system tree and all files and directories in the entire tree. This information is permanently stored on the local disk in the form of two files: the namespace mirror file and the edit log file.
  • the NameNode records the data node information where each block in each file is located, but it does not permanently store the location information of the block. This information is reconstructed by the data node when the system is started.
  • the number of racks may not be limited to two, and the same strategy may be adopted for multiple racks.
  • EC coding is used in the storage resource pool created by the storage device.
  • the lost data can be calculated to ensure that some data can still be used after loss.
  • the embodiment of the present application saves storage space and improves storage utilization.
  • FIG. 4 is an embodiment of the present application provides a data storage device 400, the storage device 400 includes: a sending unit 401, configured to send a first control instruction, the first control instruction instructs N storage devices Install data processing software in the N storage devices, create a storage resource pool and a virtual machine in any one of the N storage devices, and any one of the virtual machines uses the created storage resource pool in the corresponding storage device to store data, Any one of the virtual machines is used as an optional data node of the data processing software, and the N is an integer greater than or equal to 2.
  • the obtaining unit 402 is configured to obtain a configuration instruction.
  • the configuration instruction includes: setting the number of copies M for data storage and a storage awareness strategy; the storage awareness strategy includes: determining M data nodes for storing data, the The M data nodes are located in M different storage devices, and the M is an integer less than or equal to the N.
  • the first control instruction instructs to install data processing software in three storage devices, and create storage resource pools and virtual machines in any one of the three storage devices.
  • Any virtual machine uses the created storage resource pool in its corresponding storage device to create data, and the three created virtual machines can be used as optional data nodes of the data processing software.
  • the data processing software may be distributed processing software Hadoop.
  • the determining unit 403 is configured to determine M data nodes for storing data to be stored according to the configuration instruction.
  • the processing unit 404 is configured to store the data to be stored in the M data nodes.
  • the data to be stored is saved to a certain number of data nodes.
  • the storage resource pools created in N storage devices are encoded with erasure code EC.
  • EC coding is used in the storage resource pool created by the storage device.
  • the lost data can be calculated to ensure that some data can still be used after loss.
  • the embodiment of the present application saves storage space and improves storage utilization.
  • the storage utilization rate of the hard disk when the EC encoding adopts 8 data blocks and 1 check block 8D1P mode, the storage utilization rate of the hard disk is 88.89%, and when the EC encoding adopts 4D1P mode, the storage utilization rate of the hard disk is 80%.
  • the storage utilization rate of the hard disk is 80%, and when the EC encoding adopts the 4D2P mode, the storage utilization rate of the hard disk is 66.67%.
  • An embodiment of the present application also provides a data storage system, including N storage devices and an embodiment corresponding to any of the foregoing data storage devices, where N is an integer greater than or equal to 2.
  • the data storage device is shown in FIG. 4, the storage device includes: a sending unit 401, configured to send a first control instruction, the first control instruction instructs to install data processing software in N storage devices, A storage resource pool and a virtual machine are created in any one of the storage devices, and any one of the virtual machines uses the created storage resource pool in the corresponding storage device to store data, and any one of the virtual machines is used as the data processing An optional data node of the software, where the N is an integer greater than or equal to 2.
  • the obtaining unit 402 is configured to obtain a configuration instruction.
  • the configuration instruction includes: setting the number of copies M for data storage and a storage awareness strategy; the storage awareness strategy includes: determining M data nodes for storing data, the The M data nodes are located in M different storage devices, and the M is an integer less than or equal to the N.
  • the first control instruction instructs to install data processing software in three storage devices, and create storage resource pools and virtual machines in any one of the three storage devices.
  • Any virtual machine uses the created storage resource pool in its corresponding storage device to create data, and the three created virtual machines can be used as optional data nodes of the data processing software.
  • the data processing software may be distributed processing software Hadoop.
  • the determining unit 403 is configured to determine M data nodes for storing data to be stored according to the configuration instruction.
  • the processing unit 404 is configured to store the data to be stored in the M data nodes.
  • the data to be stored is saved to a certain number of data nodes.
  • the storage resource pools created in N storage devices are coded with erasure code EC.
  • EC coding is used in the storage resource pool created by the storage device.
  • the lost data can be calculated to ensure that some data can still be used after loss.
  • the embodiment of the present application saves storage space and improves storage utilization.
  • the storage utilization rate of the hard disk is 88.89%
  • the storage utilization rate of the hard disk is 80%
  • the storage utilization rate of the hard disk is 80%
  • the storage utilization rate of the hard disk is 66.67%.
  • the embodiment of the present application also provides an electronic device, including: one or more processors; a storage device for storing one or more programs; when the one or more programs are used by the one or more processors Execution, so that the one or more processors implement the data storage method described in any of the foregoing method embodiments.
  • the method includes:
  • the first control instruction instructs to install data processing software in N storage devices, create a storage resource pool and a virtual machine in any one of the N storage devices, any one of the The virtual machine uses the created storage resource pool in its corresponding storage device to store data, any one of the virtual machines is used as an optional data node of the data processing software, and the N is an integer greater than or equal to 2;
  • the configuration instruction includes: setting the number of copies M for data storage, and a storage awareness strategy;
  • the storage awareness strategy includes: determining M data nodes for storing data, and the M data nodes are located in M In different storage devices, the M is an integer less than or equal to the N;
  • the storage resource pools created in the N storage devices adopt erasure code EC encoding.
  • the storage device includes a distributed server or a magnetic array.
  • the EC encoding includes 8 data blocks 1 check block 8D1P mode, 4D1P mode, 8D2P mode, or 4D2P mode.
  • the data processing software includes: distributed processing software Hadoop.
  • the M 2.
  • the embodiments of the present application when multiple copies are stored, different copies are located in different storage devices. In this way, when a storage device storing backup data fails, the number of copies actually reduced is one, which is relative to the current one. In some technologies, when a storage device that stores one copy has a problem, it may cause multiple copies to be unusable, which improves storage reliability. When the storage resource pools created in N storage devices are coded with erasure code EC, when data is lost or damaged, the lost data can be calculated to ensure that some data can still be used after loss. Compared with a traditional distributed system that can continue to provide services after 3 copies of data after hardware failures and other faults occur, the embodiment of the present application saves storage space and improves storage utilization.
  • the embodiment of the present application also provides a computer-readable medium on which a computer program is stored, and when the program is executed by a processor, the data storage method as described in any of the foregoing method embodiments is implemented.
  • the method includes:
  • the first control instruction instructs to install data processing software in N storage devices, create a storage resource pool and a virtual machine in any one of the N storage devices, any one of the The virtual machine uses the created storage resource pool in its corresponding storage device to store data, any one of the virtual machines is used as an optional data node of the data processing software, and the N is an integer greater than or equal to 2;
  • the configuration instruction includes: setting the number of copies M for data storage, and a storage awareness strategy;
  • the storage awareness strategy includes: determining M data nodes for storing data, and the M data nodes are located in M In different storage devices, the M is an integer less than or equal to the N;
  • the storage resource pools created in the N storage devices adopt erasure code EC encoding.
  • the storage device includes a distributed server or a magnetic array.
  • the EC encoding includes 8 data blocks 1 check block 8D1P mode, 4D1P mode, 8D2P mode, or 4D2P mode.
  • the data processing software includes: distributed processing software Hadoop.
  • the M 2.
  • the embodiments of the present application when multiple copies are stored, different copies are located in different storage devices. In this way, when a storage device storing backup data fails, the number of copies actually reduced is one, which is relative to the current one. In some technologies, when a storage device that stores one copy has a problem, it may cause multiple copies to be unusable, which improves storage reliability. When the storage resource pools created in N storage devices are coded with erasure code EC, when data is lost or damaged, the lost data can be calculated to ensure that some data can still be used after loss. Compared with a traditional distributed system that can continue to provide services after 3 copies of data after hardware failures and other faults occur, the embodiment of the present application saves storage space and improves storage utilization.

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Abstract

L'invention concerne un procédé de stockage de données, le procédé de stockage de données comprenant les étapes suivantes : envoi d'une première instruction de commande, la première instruction de commande ordonnant d'installer un logiciel de traitement de données dans N dispositifs de stockage et de créer des groupes de ressources de stockage et des machines virtuelles dans un dispositif de stockage quelconque parmi les N dispositifs de stockage, toute machine virtuelle utilisant un groupe de ressources de stockage créé dans un dispositif de stockage correspondant de celle-ci pour stocker des données, toute machine virtuelle servant de nœud de données sélectionnable pour le logiciel de traitement de données, et N étant un nombre entier supérieur ou égal à deux (101) ; acquisition d'une instruction de configuration, l'instruction de configuration comprenant la configuration d'un certain nombre de copies M pour le stockage de données, et d'une politique de conscience du stockage, la politique de conscience du stockage comprenant la détermination de M nœuds de données pour stocker des données, les M nœuds de données étant situés dans M dispositifs de stockage différents, M étant un nombre entier inférieur ou égal à N (102) ; selon l'instruction de configuration, détermination des M nœuds de données pour enregistrer des données à stocker (103) ; et stockage des données dans les M nœuds de données (104). La configuration d'une politique de conscience du stockage est avantageuse pour améliorer la fiabilité du stockage de données.
PCT/CN2020/111903 2019-09-27 2020-08-27 Procédé de stockage de données et dispositif de stockage de données WO2021057377A1 (fr)

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CN108287669A (zh) * 2018-01-26 2018-07-17 平安科技（深圳）有限公司 数据存储方法、装置及存储介质
CN108846009A (zh) * 2018-04-28 2018-11-20 北京奇艺世纪科技有限公司 一种ceph中副本数据存储方法及装置
CN110169008A (zh) * 2018-07-10 2019-08-23 深圳花儿数据技术有限公司 一种基于一致性哈希算法的分布式数据冗余存储方法
CN109408597A (zh) * 2018-11-29 2019-03-01 广东电网有限责任公司 一种电网计量大数据存储系统及其创建方法

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