{"id":52513,"date":"2019-11-10T00:00:00","date_gmt":"2019-11-09T21:00:00","guid":{"rendered":"https:\/\/prohoster.info\/blog\/blog_prohoster\/obnovlenie-klasternoj-fajlovoj-sistemy-lizardfs-3-13-0-rc2"},"modified":"2020-02-18T14:00:15","modified_gmt":"2020-02-18T11:00:15","slug":"obnovlenie-klasternoj-fajlovoj-sistemy-lizardfs-3-13-0-rc2","status":"publish","type":"post","link":"https:\/\/prohoster.info\/en\/blog\/news\/obnovlenie-klasternoj-fajlovoj-sistemy-lizardfs-3-13-0-rc2","title":{"rendered":"LizardFS 3.13.0-rc2 Cluster File System Update","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

After a year-long lull in development work has resumed<\/a><\/noindex> on the new branch of the fault-tolerant distributed file system LizardF 3.13<\/a><\/noindex> and has been published<\/a><\/noindex> as the second candidate for releases. Recently, occurred<\/a><\/noindex> with the change of ownership of the company developing LizardFS, new management has been adopted, and the developers have changed. Over the past two years, the project has distanced itself from the community and hasn't given it due attention, but the new team intends to revive the previous relationships with the community and establish close collaboration with it. The project's code is written in C and C++ and is distributed<\/a><\/noindex> is under the GPLv3 license. <\/p>\n

LizardFS is<\/a><\/noindex> is a distributed clustered file system that allows data to be spread across different servers while presenting access to them as a single large partition, which can be used similarly to traditional disk partitions. The mounted partition with LizardFS supports POSIX file attributes, ACL, locks, sockets, pipes, device files, symbolic and hard links. The system has no single point of failure, and all components are backed up. It supports parallel data operations (multiple clients can access files simultaneously).<\/p>\n

To ensure redundancy, data is split into replicas that are distributed across different nodes with redundancy (multiple copies are placed on different nodes). In the event of node or drive failure, the system continues operation without data loss and automatically redistributes data considering the remaining nodes. To expand storage, new nodes can be added without service interruption (the system replicates part of the data to new servers and balances the storage according to the new servers). Similarly, to reduce the cluster size, outdated equipment can simply be removed from the setup.<\/p>\n

Data and metadata are stored separately. For optimal operation, it is recommended to install two metadata servers operating in a master-slave mode, as well as at least two data storage servers (chunkservers). Additionally, log servers can be used for backup of metadata, storing information about metadata changes and allowing recovery in case all existing metadata servers are damaged. Each file is broken down into chunks of up to 64 MB. The chunks are distributed across storage servers according to the selected replication mode: standard (explicitly defining the number of copies to place on different nodes, including binding to specific directories\u2014more copies for important data can be created, while fewer can be for non-essential data), XOR (RAID5), and EC (RAID6).<\/p>\n

The storage can scale to petabyte sizes. Use cases include archiving, storing virtual machine images, multimedia data, backups, serving as a DRC (Disaster Recovery Center), and as storage in high-performance computing clusters. LizardFS provides very high read speeds for files of any size and shows good performance when writing large and medium-sized files entirely, especially when there is no constant modification, intensive operations with open files, and one-off operations involving many small files.<\/p>\n

\"LizardFS<\/a><\/noindex><\/center><\/p>\n

Among the features of the FS, there is also support for snapshots that reflect the state of files at specific times, and a built-in implementation of a 'trash can' (files are not deleted immediately and are available for recovery for some time). Access to the section can be restricted by IP address or password (similar to NFS). There are quota mechanisms and quality of service management to limit size and throughput for certain user categories. The creation of geographically distributed storage systems is possible, with segments located in different data centers. <\/p>\n

The LizardFS project was founded in 2013 as a fork of MooseFS<\/a><\/noindex>, and differs mainly in having a replication mode based on Reed-Solomon error correction codes (analogous to raidzN), enhanced ACL support, a client for the Windows platform, additional optimizations (for instance, when combining the client and storage server, blocks are preferably delivered from the current node, while metadata is cached in memory), a more flexible configuration system, support for preemptive data reading, quotas on directories, and internal refinements.<\/p>\n

The release of LizardFS 3.13.0 is planned for the end of December. The main innovation of LizardFS 3.13 is the use of a consensus algorithm for ensuring fault tolerance (switching master servers in case of failure). Raft<\/a><\/noindex> (a custom implementation of uRaft is used, which was previously used in commercial products). The use of uRaft simplifies configuration and reduces recovery delays after a failure but requires at least three operational nodes, one of which is used for quorum. <\/p>\n

Other changes include: a new client based on the FUSE3 subsystem, solutions for error correction issues, and the nfs-ganesha plugin has been rewritten in C. The update 3.13.0-rc2 fixes several critical bugs that rendered previous test releases of the 3.13 branch nearly unusable (fixes for the 3.12 branch have not yet been published, and upgrading from 3.12 to 3.13 still results in complete data loss).<\/p>\n

In 2020, the focus will be on the development
\nAgama<\/a><\/noindex>, a completely rewritten core of LizardFS, which, according to the developers, will provide a threefold increase in performance compared to the 3.12 branch. In Agama, there will be a transition to an event-driven architecture, asynchronous I\/O based on asio<\/a><\/noindex>, and predominantly operation in user space (to reduce dependency on kernel caching mechanisms). Additionally, a new debugging subsystem and a network activity analyzer with performance auto-tuning support will be offered. <\/p>\n

The LizardFS client will receive full support for versioning write operations, which will enhance fault recovery reliability, address issues that arise when different clients access the same data, and significantly improve performance. The client will be transitioned to its own network subsystem operating in user space. The first working prototype of LizardFS based on Agama is planned for the second quarter of 2020. At the same time, integration tools for LizardFS with the Kubernetes platform are promised to be implemented.<\/p>\n

<\/a><\/noindex><\/p>\n

Source: opennet.ru<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

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