Abstract
The distributed file system landscape is scattered. Besides a plethora of research file systems, there is also a large number of production grade file systems with various strengths and weaknesses. The file system, as an abstraction of permanent storage, is appealing because it provides application portability and integration with legacy and third-party applications, including UNIX utilities. On the other hand, the general and simple file system interface makes it notoriously difficult for a distributed file system to perform well under a variety of different workloads. This contribution provides a taxonomy of commonly used distributed file systems and points out areas of research and development that are particularly important for high-energy physics.
Highlights
In high-energy physics, we store files in a variety of distributed file systems
XrootD is optimized for high-throughput access to high-energy physics data sets [1], the Hadoop File System (HDFS) is designed as a storage layer for the MapReduce framework [2, 3], the CernVM File System (CVMFS) is optimized to distribute software binaries [4], and Lustre is optimized as a scratch space for cooperating applications on supercomputers [5]
Distributed file systems are at the heart of our distributed computing
Summary
In high-energy physics, we store files in a variety of distributed file systems. The first and foremost advantage of using a file system is application portability. XrootD is optimized for high-throughput access to high-energy physics data sets [1], the Hadoop File System (HDFS) is designed as a storage layer for the MapReduce framework [2, 3], the CernVM File System (CVMFS) is optimized to distribute software binaries [4], and Lustre is optimized as a scratch space for cooperating applications on supercomputers [5]. These use cases differ both quantitatively and qualitatively. At the software level of storage space management, log-structured storage systems provide an interesting approach that can help to utilize the available bandwidth in an optimal way
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