From Sanjay Ghemawat, Howard Gobioff, & Shun-Tak Leung’s “The Google File System“:
We have designed and implemented the Google File Sys- tem, 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. …
The file system has successfully met our storage needs. It is widely deployed within Google as the storage platform for the generation and processing of data used by our ser- vice as well as research and development efforts that require large data sets. The largest cluster to date provides hun- dreds of terabytes of storage across thousands of disks on over a thousand machines, and it is concurrently accessed by hundreds of clients. …
We have seen problems caused by application bugs, operating system bugs, human errors, and the failures of disks, memory, connectors, networking, and power sup- plies. Therefore, constant monitoring, error detection, fault tolerance, and automatic recovery must be integral to the system.
Second, files are huge by traditional standards. Multi-GB files are common. Each file typically contains many applica- tion objects such as web documents. When we are regularly working with fast growing data sets of many TBs comprising billions of objects, it is unwieldy to manage billions of ap- proximately KB-sized files even when the file system could support it. As a result, design assumptions and parameters such as I/O operation and blocksizes have to be revisited.
Third, most files are mutated by appending new data rather than overwriting existing data. Random writes within a file are practically non-existent. Once written, the files are only read, and often only sequentially. …
Multiple GFS clusters are currently deployed for different purposes. The largest ones have over 1000 storage nodes, over 300 TB of diskstorage, and are heavily accessed by hundreds of clients on distinct machines on a continuous basis. …
Despite occasional problems, the availability of Linux code has helped us time and again to explore and understand system behavior. When appropriate, we improve the kernel and share the changes with the open source community.