The Google File System
📜 Abstract
We have designed and implemented the Google File System, a scalable distributed file system for large distributed data-intensive applications. It provides fault tolerance while running on inexpensive commodity hardware, and it delivers high aggregate performance to a large number of clients. While sharing many of the same goals as previous distributed file systems, our design has been driven by observations of our application workloads and technological environment, both current and anticipated, that reflect a marked departure from some earlier file system assumptions. This has led us to reexamine traditional choices and explore radically different design points. The file system has been in wide use at Google for more than two years now; it is the underlying storage system for many of our production services as well as research and engineering efforts. In this paper, we present the system's design, discuss many of the implementation issues, and trace the lessons we have learned.
✨ Summary
The Google File System (GFS), presented in this paper, is a distributed file system developed at Google to support its extensive applications and data requirements. It is designed to manage large volumes of data and provide fault tolerance by utilizing inexpensive, distributed storage solutions. Some of its key features include chunk replication, distributed metadata management, and performance optimizations tailored for Google’s needs. The system aims to enhance fault-tolerance and support high-throughput and reliability across a large number of client processes.
GFS has significantly influenced the design of subsequent distributed file systems and storage solutions. It inspired the development of Hadoop Distributed File System (HDFS), which has become a cornerstone of many big data technologies used worldwide (Shvachko et al., 2010). Additionally, the paper’s concepts have underpinned advancements in cloud storage systems and have been integral in shaping industry approaches to data-intensive computing environments.
For further citation, the paper has been referenced extensively and has over 10,000 citations according to Google Scholar, underscoring its impact in both academia and industry (Google Scholar citations).