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Google File System (GFS or GoogleFS, not to be confused with the GFS Linux file system) is a proprietary distributed file system developed by Google to provide efficient, reliable access to data using large clusters of commodity hardware. Google file system was replaced by Colossus in 2010.
In computing, the Global File System 2 (GFS2) is a shared-disk file system for Linux computer clusters. GFS2 allows all members of a cluster to have direct concurrent access to the same shared block storage, in contrast to distributed file systems which distribute data throughout the cluster. GFS2 can also be used as a local file system on a ...
Google, one of the biggest internet companies, has created its own distributed file system, named Google File System (GFS), to meet the rapidly growing demands of Google's data processing needs, and it is used for all cloud services. GFS is a scalable distributed file system for data-intensive applications.
Clustered file systems can provide features like location-independent addressing and redundancy which improve reliability or reduce the complexity of the other parts of the cluster. Parallel file systems are a type of clustered file system that spread data across multiple storage nodes, usually for redundancy or performance.
A Google cluster has thousands of servers, and once the client has connected to the server additional load balancing is done to send the queries to the least loaded web server. This makes Google one of the largest and most complex content delivery networks. [94] Google has numerous data centers scattered around the world.
The implementation is intended to execute on clusters of commodity processors. Hadoop implements a distributed data processing scheduling and execution environment and framework for MapReduce jobs. Hadoop includes a distributed file system called HDFS which is analogous to GFS in the Google MapReduce implementation. The Hadoop execution ...
Some researchers have made a functional and experimental analysis of several distributed file systems including HDFS, Ceph, Gluster, Lustre and old (1.6.x) version of MooseFS, although this document is from 2013 and a lot of information are outdated (e.g. MooseFS had no HA for Metadata Server at that time).
Google's server logs are stored as large collections of records (Protocol Buffers) that are partitioned over many disks within GFS. In order to perform calculations involving the logs, engineers can write MapReduce programs in C++ or Java. MapReduce programs need to be compiled and may be more verbose than necessary, so writing a program to ...