glusterfs简介

 

GlusterFS is an open source, clustered file system capable of scaling to several petabytes and
handling thousands of clients. GlusterFS can be flexibly combined with commodity physical, virtual,
and cloud resources to deliver highly available and performant enterprise storage at a fraction of the
cost of traditional solutions.

 

GlusterFS是一个开源集群文件系统，能够扩展到PB级存储容量并处理数以千计的客户端请求。GlusterFS可与物理资源、虚拟资源和云资源商品灵活组合，以低于传统的解决方案的成本，提供高可用和高性能的企业存储。

 

Red Hat Storage was designed to achieve several major goals:
Elasticity
Elasticity is the notion that an enterprise should be able to flexibly adapt to the growth (or reduction) of data
and to add or remove resources to a storage pool as needed without disrupting the system. Red Hat Storage
was designed to allow enterprises to add or delete users, application data, volumes and storage nodes, etc.,
without disrupting any running functionality within the infrastructure.
Linear scaling
“Linear scaling” is a much-abused phrase within the storage industry. It should mean, for example, that
twice the amount of storage systems will deliver twice the realized performance—twice the throughput (as
measured in gigabytes per second) with the same average response time per external file system I/O event
(i.e., how long an NFS client will wait for the file server to return the information associated with each NFS
client request).

 

红帽存储解决方案(也就是Glusterfs)有如下设计目标：

 

     弹性存储

 

     弹性存储是指企业应该能够灵活地适应数据的增长（或减少），在不中断系统的情况下，根据需要添加或删除资源存储池。红帽存储解决方案可以在不破坏的基础设施内的任何正在运行的功能的情况下，让企业添加/删除 用户、应用程序数据、卷和存储节点。

 

     线性扩展

 

 

      “线性扩展”是存储行业内的滥用短语。它应当意味着，例如，两倍存储系统容量将提供两倍的性能—两倍吞吐量（GB/s）,

并保持相同的外部文件系统I / O事件平均响应时间（如发送请求后，NFS文件服务器客户端将等待多久才能收到文件服务器返回的相关信息）。

 

There are seven fundamental technical differentiators between Red Hat Storage and traditional storage
systems. These are discussed in brief below.

  

      红帽存储和传统存储之间有7个基本的技术差异。下面将简单讨论它们。

 

Software-only 只用软件实现
Open source  开源
Complete storage operating system stack 不仅是分布式文件系统，还提供了应该有的各种功能。
Our belief is that it’s important not only to deliver a distributed file system, but also to deliver a number of
other important functions in a distributed fashion. Red Hat Storage delivers distributed memory manage-
ment, I/O scheduling, software RAID, self-healing, local N-way synchronous replication as well as asynchro-
nous long-distance replication via Red Hat Geo-Replication. In essence, by taking a lesson from micro-kernel
architectures, we have designed Red Hat Storage to deliver a complete storage operating system stack in
user space.
User space  用户模式而不是内核模式，通过fuse实现。
Unlike traditional file systems, Red Hat Storage operates in user space. This makes installing and upgrading
Red Hat Storage significantly easier. And it means that users who choose to develop on top of Red Hat
Storage need only have general C programming skills, not specialized kernel expertise.
Modular, stackable architecture  模块化、可堆放的架构， 通过xlator动态链接库实现。
Red Hat Storage is designed using a modular and stackable architecture approach. To configure Red Hat
Storage for highly specialized environments (e.g., large number of large flies, huge numbers of very small
files, environments with cloud storage, various transport protocols, etc.), it is a simple matter of including or
excluding particular modules.
For the sake of stability, certain options should not be changed once the system is in use (for example, one
would not remove a function such as replication if high availability was a desired functionality).
Data stored in native formats   数据以本地文件系统的格式存储，通过完全兼容POSIX语义实现。
With Red Hat Storage, data is stored on disk using native formats (e.g. EXT3, EXT4, XFS). Red Hat Storage
has implemented various self-healing processes for data. As a result, the system is extremely resilient.
Furthermore, files are naturally readable without Red Hat Storage. If a customer chooses to migrate away
from Red Hat Storage, their data is still completely usable without any required modifications or data
migration.
No metadata with the elastic hash algorithm  没有原数据（即数据的数据信息），通过DHT实现。
In a scale-out system, one of the biggest challenges is keeping track of the logical and physical location of
data (location metadata). Most distributed systems solve this problem by creating a separate index with file
names and location metadata. Unfortunately, this creates both a central point of failure and a huge perfor-
mance bottleneck. As traditional systems add more files, more servers, or more disks, the central metadata
server becomes a performance chokepoint. This becomes an even bigger challenge if the workload consists
primarily of small files and the ratio of metadata to data increases.
Unlike other storage systems with a distributed file system, Red Hat Storage does not create, store, or use
a separate index of metadata in any way. Instead, Red Hat Storage places and locates files algorithmically.
All storage node servers in the cluster have the intelligence to locate any piece of data without looking it up
in an index or querying another server. All a storage node server needs to do to locate a file is to know the
pathname and filename and apply the algorithm. This fully parallelizes data access and ensures linear perfor-
mance scaling. The performance, availability, and stability advantages of not using metadata are significant
and, in some cases, dramatic.