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Distributed File Systems

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(Photo: Princeton University, Office of Communications)

 

 

Computer File Systems

 

When computers first came out, the information and programs were stored in punch cards. These punch cards were stored in file cabinets, just like the physical file cabinets today. This is where the name, file system, comes from. The need to store information in files comes from a larger need to store information in the long-term. This way the information lives
after the computer program, or what we call process, that produced it terminates. If we don't have files, our access to such information would not be possible once a program using or producing it. Even during the process, we might need to store large amounts of information that we cannot store within the program components or computer memory. In addition, once the data is in a file, multiple processes can access the same information if needed. For all these reasons, we store information in files on a hard disk. There are many of these files, and they get managed by your operating system, like Windows or Linux. How the operating system manages files is called a file system. How this information is stored on disk drives has high impact on the efficiency and speed of access to data, especially in the big data case. 

 

Why Distributed File Systems Needed?

 

While the files have exact addresses for their locations in the drive, referring to the data units of sequence of these blocks, that's called the file structure, or hierarchy construction of index records, that's called the database. They also have human readable symbolic names, generally followed by an extension. Extensions tell what kind of file it is, in general. Programs and users can access files with their names. The contents of a file can be numeric, alphabetic, alphanumeric, or binary executables. Most computer users work on personal laptops or desktop computers with a single hard drive. In this model, the user is limited to the capacity of their hard drive. The capacity of different devices vary. For example, while your phone or tablet might have a storage capacity in the order of gigabytes, your laptop computer might have a terabyte of storage, but what if you have more data? Some of you probably had issues in the past with running out of space on your hard drive. A way to solve this is to have an external hard drive and store your files there or, you can buy a bigger disk. Both options are a bit of a hassle, to copy the data to a new disk, aren't they? They might not even be an option sometimes. 

Now imagine, you having two computers and storing some of your data in one and the rest of your data in another. How you organize and partition your data between these computers is up to you. You might want to store your work data in one computer and your personal data in another. Distributing data on multiple computers might be an option, but it raises new issues. In this situation, you need to know where to find the files you need, depending on what you’re doing. You can find it manageable if it’s just your data. But now imagine having thousands of computers to store your data with big volumes and variety. Wouldn't it be good to have a system that can handle the data access and do this for you? This is a case that can be handled by a distributed file system. 

 

Distributed File Systems

 

In computing, a distributed file system (DFS) is any file system that allows access to files from multiple hosts sharing via a computer network. This makes it possible for multiple users on multiple machines to share files and storage resources. Distributed file systems differ in their performance, mutability of content, handling of concurrent writes, handling of permanent or temporary loss of nodes or storage, and their policy of storing content. 

Typically, a distributed file system is divided into many smaller blocks, which are stored on different machines. Every file has a unique identifier, and every block within a file is also referenced uniquely. The distributed file system is oblivious to the local storage mechanisms used by the disk subsystem of the machines. The machine could employ various disk architectures like RAID, etc..

Distributed file systems (DFS) present the abstraction of a single unified storage to applications by abstracting away as many of the details of the individual storage machines as possible, the machines store the data on their local disks. Sun Microsystems' Network File System (NFS), Microsoft's Distributed File System, and IBM/Transarc's DFS are some examples of distributed file systems.

Network File System (NFS) is a distributed file system (DFS) developed by Sun Microsystems. This allows directory structures to be spread over the networked computing systems. A DFS is a file system whose clients, servers and storage devices are dis-persed among the machines of distributed system. A file system provides a set of file operations like read, write, open, close, delete etc. which forms the file services. The clients are provided with these file services. The basic features of DFS are multiplicity and autonomy of clients and servers. NFS follows the directory structure almost same as that in non-NFS system but there are some differences between them with respect to: Naming, Path Names, and Semantics.

Distributed Systems and Data Replication

 

Now, let's assume that there are racks of these computers, often even distributed across the local or wide area network, because such file systems, distributed file systems. Data sets, or parts of a data set, can be replicated across the nodes of a distributed file system. Since data is already on these nodes, then analysis of parts of the data is needed in a data parallel fashion, computation can be moved to these nodes. Additionally, distributed file systems replicate the data between the racks, and also computers distributed across geographical regions. Data replication makes the system more fault tolerant. That means, if some nodes or a rack goes down, there are other parts of the system, the same data can be found and analyzed. Data replication also helps with scaling the access to this data by many users. Often, if the data is popular, many reader processes will want access to it. In a highly parallelized replication, each reader can get their own node to access to and analyze data. This increases overall system performance. 

Note that a problem with having such a distributed replication is, that it is hard to make changes to data over time. However, in most big data systems, the data is written once and the updates to data is maintained as additional data sets over time. 

As a summary, a file system is responsible from the organization of the long term information storage in a computer. When many storage computers are connected through the network, we call it a distributed file system. Distributed file systems provide data scalability, fault tolerance, and high concurrency through partitioning and replication of data on many nodes.

 

 

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