WO2022121387A1 - 数据存储方法、装置、服务器及介质 - Google Patents
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/10—File systems; File servers
- G06F16/18—File system types
- G06F16/182—Distributed file systems
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- H—ELECTRICITY
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- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/1097—Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
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- the present application relates to data processing technology, for example, to a data storage method, device, server and medium.
- the present application provides a data storage method, device, server and medium, so as to realize the separation of storage resource scheduling and data storage resources, and avoid the effect of hardware resource waste.
- a data storage method comprising:
- the data to be stored is sent to the storage server corresponding to the data information through the scheduling server for storage.
- a data storage device comprising:
- a data information acquisition module configured to acquire the data information of the data to be stored through the metadata gateway;
- the data saving module is configured to send the data to be stored to the storage server corresponding to the data information through the scheduling server according to the data information for saving.
- a server is also provided, wherein the server includes:
- processors one or more processors
- storage means arranged to store 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 data storage method provided by any embodiment of the present application.
- a computer-readable storage medium is also provided, storing a computer program, wherein, when the computer program is executed by a processor, the data storage method provided by any embodiment of the present application is implemented.
- Embodiment 1 is a flowchart of a data storage method in Embodiment 1 of the present application.
- FIG. 2 is a schematic diagram of a process flow diagram of stored data based on an erasure code algorithm in Embodiment 1 of the present application;
- FIG. 3 is a schematic diagram of storage processing according to a data name in Embodiment 1 of the present application.
- FIG. 5 is a structural diagram of a data storage device in Embodiment 3 of the present application.
- FIG. 6 is a schematic structural diagram of a server in Embodiment 4 of the present application.
- FIG. 1 is a flowchart of a data storage method according to Embodiment 1 of the present application. This embodiment is applicable to the case of storing data. The method can be executed by a data storage device, and includes the following steps.
- the data is calculated in real time and offline. During the calculation process or after the calculation is completed, the data is stored in different database components according to the data type. When saving the data, it is necessary to use the storage resource scheduling. Allocation, storage resource scheduling and storage resource binding, the above functions are implemented through a unified server, exemplarily, through Yet Another Resource Negotiator (Yet Another Resource Negotiator) in the Hadoop Distributed File System (HDFS) architecture , YARN) for storage resource scheduling.
- YARN is a general resource management system that can provide unified resource management and scheduling for upper-layer applications. Its introduction brings benefits to the cluster in terms of utilization, unified resource management, and data sharing.
- Storage resource scheduling is bound to storage resources, and storage resource scheduling capabilities often do not match storage resources. When one of them is insufficient and needs to be expanded, it can only be expanded at the same time, resulting in a waste of hardware resources. Therefore, it is necessary to separate storage resource scheduling from storage resources.
- Storage resource scheduling is completed by a separate resource scheduling server, and storage functions are completed by a separate storage server, thereby realizing the separation of storage resource scheduling and storage resources and avoiding the waste of hardware resources.
- the first step is to enable the HBase metadata gateway switch, log in to the storage management node, and execute commands through the executable command interface to open coexistence metadata. gateway.
- the second step is to configure a routing policy for forwarding the data to be stored to the remote server for storage.
- the third step is to modify the custom parameters of HDFS, and send the data to be stored that meets the custom parameters to the remote server for storage. After modifying the custom parameters, restart the server, so that all servers can obtain the configured routing policy and the modified self Define parameters.
- the fourth step is to configure a routing policy for forwarding the data to be stored to the local server.
- the storage capacity of the storage server needs to meet the storage capacity requirements of business processing. You can compare the effective storage space of the storage server with the effective storage space of the original storage server by calculating. In related solutions, there are often mismatches in storage resource scheduling capabilities and excessive redundancy in storage resources.
- the number of central processing unit (CPU) cores and storage capacity can be appropriately reduced according to business analysis or actual measurement, thereby reducing hardware costs. .
- the stored data is metadata, which is the data that describes the data attributes and information about the environment.
- the metadata gateway obtains data information such as the storage location, data name, data size, and data version of the data to be stored. After separation, the data information of the data to be stored is obtained through the metadata gateway, so as to save the data to be stored in a corresponding storage location.
- the metadata gateway provides a unified file system access entry for upper-layer big data computing applications, and identifies the storage server to be accessed by the metadata gateway.
- the data to be stored is sent to the storage server corresponding to the data information through the scheduling server for storage.
- the data information of the data to be stored is obtained through the metadata gateway, and the scheduling server allocates the storage server according to the data information of the data to be stored to save the data to be stored.
- the data information includes: data attribute information; the storage server includes: a big data storage server and a small data storage server; the data to be stored is sent to the data information through a scheduling server according to the data information
- the storing in the corresponding storage server includes: sending the data to be stored to the big data storage server or the small data storage server through the scheduling server according to the data attribute information for storage.
- the information of the data to be stored obtained through the metadata gateway includes the size of the data. If it is data with a large amount of data, the scheduling server schedules the big data storage server to store the data to be stored. If it is data with a small amount of data, the scheduling server schedules the small data storage. The server stores the data to be stored.
- the big data storage server can be the storage architecture of HDFS, which enables users to develop distributed programs without knowing the underlying details of the distribution, and make full use of the power of the cluster to perform high-speed computing and computing.
- HDFS provides storage for massive data.
- the HDFS storage architecture has the characteristics of high fault tolerance and improves the security of data storage.
- the small data storage server can use distributed storage or relational storage and other storage methods.
- the scheduling server includes: a first scheduling server and a second scheduling server; wherein the first scheduling server corresponds to the big data storage server; the second scheduling server corresponds to the small data storage server.
- the scheduling server is divided into a first scheduling server corresponding to the big data storage server and a second scheduling server corresponding to the small data storage server.
- the size information of the data to be stored is obtained through the metadata gateway, and when the data to be stored is big data, the storage resources are scheduled through the first scheduling server, and the data to be stored is stored in the big data storage server.
- the storage resource scheduling is performed by the second scheduling server, and the data to be stored is stored in the small data storage server.
- the data information includes: data name information; the big data storage server and the small data storage server include: a local storage server and a remote storage server; Sending the data to the storage server corresponding to the data information for storage includes: sending the data to be stored to the local storage server or the remote storage server through the scheduling server according to the data name information for storage.
- the data information obtained through the metadata gateway also includes data name information, the storage address includes the local server and the remote server, and the scheduling server sends the data to be stored to the local server or the remote server for storage according to the data name information.
- tables starting with test_+4 digits+01 are written to remote server storage, and tables with other names are written to local HDFS storage. As shown in Figure 3, test_202001 is written to the remote storage server, and test_202000 is written to the local HDFS.
- the files to be stored will be stored locally first, and the data stored remotely is read-only data.
- configure the gateway to transparently forward it to the remote for processing. Generally, it is used temporarily during the transformation process of the coexistence of the new and the old.
- the routing policy is modified to the actual required mode.
- the scheduling server will refer to the capacity of multiple storage servers, and schedule storage resources according to the absolute capacity value of the remaining capacity of multiple storage servers or the ratio of the remaining capacity to the total capacity, so that the storage resources of multiple storage servers can be maintained. balanced.
- the data information of the data to be stored is obtained through the metadata gateway; according to the data information, the data to be stored is sent to the corresponding storage server through the scheduling server for storage, which solves the problem of storage resource scheduling capability and storage.
- the resources are often mismatched. When one of them is insufficient and needs to be expanded, it can only be expanded at the same time, which leads to the problem of wasting hardware resources. It realizes the separation of storage resource scheduling and storage resources, and avoids the effect of wasting hardware resources.
- Embodiment 4 is a flowchart of a data storage method provided in Embodiment 2 of the present application.
- This embodiment is described on the basis of the previous embodiment, and the data information further includes: data type;
- the scheduling server sends the data to be stored to a storage server corresponding to the data information for storage, including: sending the data to be stored to a database corresponding to the data type in the storage server through the scheduling server save.
- the data to be stored is saved to the corresponding database according to the data type, which facilitates the management of the stored data.
- S220 Send the data to be stored to a database corresponding to the data type in the storage server through the scheduling server for storage.
- the data information of the data to be stored obtained through the metadata gateway further includes the data type.
- the database components include but are not limited to HBase, Druid, Greenplum, JanusGraph, and Solr, so as to satisfy the storage of data of different data types.
- sending the to-be-stored data to a database corresponding to the data type in the storage server for storage by the scheduling server includes: adjusting the storage server to divide the to-be-stored data into data blocks and check blocks.
- the proportion of the data to be stored is divided into a first preset number of data blocks and a second preset number of check blocks by the storage server according to the proportion; the data blocks and the second preset number of check blocks are divided according to the data type
- the check block is stored in a database corresponding to the data type.
- Replica is a data reliability protection technology under the distributed storage system. By storing the same data on different nodes, multiple copies of the same data content are supported in the case of a single point of failure, such as node or hard disk failure. , which can achieve uninterrupted external storage requests by reading redundant copies.
- Erasure coding is another mechanism to achieve data protection. It is a data protection method that divides data into fragments, expands, encodes redundant data blocks, and stores redundant data blocks in different locations, such as disks. , storage nodes, or other geographic locations. Compared with replicas, erasure codes have higher storage utilization and lower costs. When storing data, it is necessary to divide the data into data blocks and check blocks. When a data block is lost, the data can be recovered through other data blocks and check blocks to prevent data loss.
- the ratio of dividing the original data to be stored into data blocks and check blocks is adjusted, the data blocks are adjusted to a first preset number, and the check blocks are adjusted to a second preset number.
- the data to be stored is divided according to the newly adjusted ratio of the data block and the check block, so as to improve the utilization rate of the disk.
- adjusting the ratio of dividing the data to be stored into data blocks and check blocks by the storage server includes: increasing the number of data blocks that the storage server divides the data to be stored into, so as to increase the ratio of the data blocks.
- the utilization rate of the disk is 66.66%
- the utilization rate of the disk is 83%
- the ratio of data blocks to check blocks is adjusted to 22:2.
- the utilization rate of the disk is 91.67%.
- the number of parity blocks can be set to 1 or 2.
- the number of parity blocks must be less than the number of data blocks.
- the number of parity blocks can be determined according to the number of storage servers.
- the check block is the backup check block. When one check block is damaged or lost, another check block is enabled.
- the data information of the data to be stored is obtained through the metadata gateway; the data information further includes: data type; the scheduling server sends the to-be-stored data to the database corresponding to the data type in the storage server It solves the problem that the storage resource scheduling capability and storage resources often do not match. When one of them is insufficient and needs to be expanded, it can only be expanded at the same time, resulting in the waste of hardware resources. The separation of storage resource scheduling and storage resources is realized to avoid hardware waste of resources.
- FIG. 5 is a structural diagram of a data storage device according to Embodiment 3 of the present application.
- the data storage device includes: a data information acquisition module 310 and a data storage module 320 .
- the data information obtaining module 310 is configured to obtain the data information of the data to be stored through the metadata gateway; the data saving module 320 is configured to send the to-be-stored data to the corresponding data information through the scheduling server according to the data information storage server for saving.
- the data information includes: data attribute information;
- the storage server includes: a big data storage server and a small data storage server.
- the data saving module 320 is configured to send the data to be stored to the big data storage server or the small data storage server through the scheduling server according to the data attribute information. save.
- the scheduling server includes: a first scheduling server and a second scheduling server; wherein the first scheduling server corresponds to the big data storage server; the second scheduling server corresponds to the small data storage server.
- the data information includes: data name information;
- the big data storage server and the small data storage server include: a local storage server and a remote storage server;
- the data saving module 320 is further configured to send the data to be stored to the local storage server or the remote storage server through the scheduling server according to the data name information for saving.
- the data information further includes: data type;
- the data saving module 320 is further configured to send the to-be-stored data to a database corresponding to the data type in the storage server through the scheduling server for saving.
- the data saving module 320 includes:
- a proportion adjustment unit configured to adjust the proportion of the storage server dividing the data to be stored into data blocks and check blocks
- a storage data dividing unit configured to divide the to-be-stored data into a first preset number of data blocks and a second preset number of check blocks by the storage server according to the ratio;
- a data saving unit configured to save the data block and the check block in a database corresponding to the data type according to the data type.
- the proportional adjustment unit includes:
- the subunit for increasing the number of data blocks is configured to increase the number of data blocks that the storage server divides the data to be stored into, so as to increase the proportion of the data blocks.
- the data information of the data to be stored is obtained through the metadata gateway; according to the data information, the data to be stored is sent to the corresponding storage server through the scheduling server for storage, which solves the problem of storage resource scheduling capability and storage.
- the resources are often mismatched. When one of them is insufficient and needs to be expanded, it can only be expanded at the same time, which leads to the problem of wasting hardware resources. It realizes the separation of storage resource scheduling and storage resources, and avoids the effect of wasting hardware resources.
- the data storage device provided by the embodiment of the present application can execute the data storage method provided by any embodiment of the present application, and has functional modules and effects corresponding to the execution method.
- FIG. 6 is a schematic structural diagram of a server according to Embodiment 4 of the present application.
- the server includes a processor 410, a memory 420, an input device 430, and an output device 440; the number of processors 410 in the server may be One or more, one processor 410 is taken as an example in FIG. 6; the processor 410, the memory 420, the input device 430 and the output device 440 in the server can be connected through a bus or other means, and the connection through a bus is taken as an example in FIG. 6 .
- the memory 420 can be configured to store software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the data storage methods in the embodiments of the present application (for example, data in a data storage device). information acquisition module 310 and data storage module 320).
- the processor 410 executes various functional applications and data processing of the server by running the software programs, instructions and modules stored in the memory 420, that is, to implement the above-mentioned data storage method.
- the memory 420 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to use of the terminal, and the like. Additionally, memory 420 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, memory 420 may include memory located remotely from processor 410, which may be connected to a server through a network. Examples of such networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.
- the input device 430 may be configured to receive input numerical or character information, and to generate key signal input related to user settings and function control of the server.
- the output device 440 may include a display device such as a display screen.
- Embodiment 5 of the present application further provides a storage medium containing computer-executable instructions, where the computer-executable instructions are used to execute a data storage method when executed by a computer processor, and the method includes:
- the data to be stored is sent to the storage server corresponding to the data information through the scheduling server for storage.
- a storage medium containing computer-executable instructions provided by an embodiment of the present application the computer-executable instructions of which are not limited to the above method operations, and can also perform related operations in the data storage method provided by any embodiment of the present application .
- the present application can be implemented by means of software and general hardware, and can also be implemented by hardware.
- the present application can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a floppy disk of a computer, a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory) , RAM), flash memory (FLASH), hard disk or optical disk, etc., including several instructions to make a computer device (which may be a personal computer, server, or network device, etc.) execute the methods described in the various embodiments of the present application.
- a computer-readable storage medium such as a floppy disk of a computer, a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory) , RAM), flash memory (FLASH), hard disk or optical disk, etc.
- the multiple units and modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be realized;
- the names are only for the convenience of distinguishing from each other, and are not used to limit the protection scope of this application.
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Claims (10)
- 一种数据存储方法,包括:通过元数据网关获取待存储数据的数据信息;根据所述数据信息通过调度服务器将所述待存储数据发送至所述数据信息对应的存储服务器进行保存。
- 根据权利要求1所述的方法,其中,所述数据信息包括:数据属性信息;所述存储服务器包括:大数据存储服务器和小数据存储服务器;所述根据所述数据信息通过调度服务器将所述待存储数据发送至所述数据信息对应的存储服务器进行保存,包括:根据所述数据属性信息通过所述调度服务器将所述待存储数据发送至所述大数据存储服务器或所述小数据存储服务器中进行保存。
- 根据权利要求2所述的方法,其中,所述调度服务器包括:第一调度服务器和第二调度服务器;其中,所述第一调度服务器与所述大数据存储服务器对应;所述第二调度服务器与所述小数据存储服务器对应。
- 根据权利要求2所述的方法,其中,所述数据信息包括:数据名称信息;所述大数据存储服务器和所述小数据存储服务器包括:本地存储服务器和远程存储服务器;所述根据所述数据信息通过调度服务器将所述待存储数据发送至所述数据信息对应的存储服务器进行保存,包括:根据所述数据名称信息通过所述调度服务器将所述待存储数据发送至所述本地存储服务器或所述远程存储服务器中进行保存。
- 根据权利要求1所述的方法,其中,所述数据信息包括:数据类型;所述根据所述数据信息通过调度服务器将所述待存储数据发送至所述数据信息对应的存储服务器进行保存,包括:通过所述调度服务器将所述待存储数据发送至所述存储服务器中与所述数据类型对应的数据库中保存。
- 根据权利要求5所述的方法,其中,所述通过所述调度服务器将所述待存储数据发送至所述存储服务器中与所述数据类型对应的数据库中保存,包括:调整所述存储服务器将所述待存储数据划分为数据块和校验块的比例;根据所述比例通过所述存储服务器将所述待存储数据划分为第一预设数量的数据块和第二预设数量的校验块;根据所述数据类型将所述数据块和所述校验块保存至所述数据类型对应的数据库中。
- 根据权利要求6所述的方法,其中,所述调整所述存储服务器将所述待存储数据划分为数据块和校验块的比例,包括:提高所述存储服务器将所述待存储数据划分为所述数据块的数量,以提高所述数据块的比例。
- 一种数据存储装置,包括:数据信息获取模块,设置为通过元数据网关获取待存储数据的数据信息;数据保存模块,设置为根据所述数据信息通过调度服务器将所述待存储数据发送至所述数据信息对应的存储服务器进行保存。
- 一种服务器,包括:一个或多个处理器;存储装置,设置为存储一个或多个程序;当所述一个或多个程序被所述一个或多个处理器执行,使得所述一个或多个处理器实现如权利要求1-7中任一项所述的数据存储方法。
- 一种计算机可读存储介质,存储有计算机程序,其中,所述计算机程序被处理器执行时实现如权利要求1-7中任一项所述的数据存储方法。
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CN102045203A (zh) * | 2010-12-30 | 2011-05-04 | 华为技术有限公司 | 网络管理的方法、装置及网络管理*** |
WO2014071786A1 (zh) * | 2012-11-06 | 2014-05-15 | 腾讯科技(深圳)有限公司 | 一种文件传输的方法及*** |
CN105468451A (zh) * | 2014-08-19 | 2016-04-06 | 复旦大学 | 一种基于高通量测序数据的计算机集群的作业调度*** |
CN104469392A (zh) * | 2014-12-19 | 2015-03-25 | 北京奇艺世纪科技有限公司 | 一种视频文件存储方法及装置 |
CN107426288A (zh) * | 2017-05-26 | 2017-12-01 | 郑州云海信息技术有限公司 | 一种基于存储网络的资源共享调度方法和装置 |
CN112527760A (zh) * | 2020-12-11 | 2021-03-19 | 北京锐安科技有限公司 | 数据存储方法、装置、服务器及介质 |
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