Making logical copies, or clones, of files and directories is critical to many real-world applications and workflows, including backups, virtual machines, and containers. An ideal clone implementation meets the following performance goals: (1) Creating the clone has low latency. (2) Reads are fast in all versions (i.e., spatial locality is always maintained, even after modifications). (3) Writes are fast in all versions. (4) The overall system is space efficient. Implementing a clone operation that realizes all four properties, which we call a nimble clone, is a long-standing, open problem.

This paper describes nimble clones in BetrFS, an open source, full-path-indexed, write-optimized file system. The key observation behind our work is that standard copy-on-write heuristics can be too coarse to be space efficient, or too fine-grained to preserve locality. On the other hand, a write-optimized key-value store, as used in BetrFS or an LSM-tree, can decouple the logical application of updates from the granularity that data is physically copied. In our write-optimized clone implementation, data sharing among clones is only broken when a clone has changed enough to warrant making a copy, a policy we call copy-on-abundant-write.

We demonstrate that the algorithmic work needed to batch and amortize the cost of BetrFS clone operations does not erode the performance advantages of baseline BetrFS; BetrFS performance even improves in a few cases. BetrFS cloning is efficient; for example, when using the clone operation for container creation, BetrFS outperforms a simple recursive copy by up to two orders-of-magnitude and outperforms file systems that have specialized LXC backends by 3–4x.


February, 2020


  • Yang Zhan
  • Alex Conway
  • Yizheng Jiao
  • Nirjhar Mukherjee
  • Ian Groombridge
  • Michael A. Bender
  • Martin Farach-Colton
  • William Jannen
  • Rob Johnson
  • Donald E. Porter
  • Jun Yuan

Related projects

Research Areas

  • External-Memory Data Structures
  • File systems
  • Write-Optimized Data Structures