Cluster File System

Kosmos File System (KFS) is a New High End Google File System Option

Todd Hoff

— 2 min read
There's a new clustered file system on the spindle: Kosmos File System (KFS). Thanks to Rich Skrenta for turning me on to KFS and I think his blog post says it all. KFS is an open source project written in C++ by search startup Kosmix. The team members have a good pedigree so there's a better than average chance this software will be worth considering.

After you stop trying to turn KFS into "Kentucky Fried File System" in your mind, take a look at KFS' intriguing feature set:


  • Incremental scalability: New chunkserver nodes can be added as storage needs increase; the system automatically adapts to the new nodes.
  • Availability: Replication is used to provide availability due to chunk server failures. Typically, files are replicated 3-way.
  • Per file degree of replication: The degree of replication is configurable on a per file basis, with a max. limit of 64.
  • Re-replication: Whenever the degree of replication for a file drops below the configured amount (such as, due to an extended chunkserver outage), the metaserver forces the block to be re-replicated on the remaining chunk servers. Re-replication is done in the background without overwhelming the system.
  • Re-balancing: Periodically, the meta-server may rebalance the chunks amongst chunkservers. This is done to help with balancing disk space utilization amongst nodes.
  • Data integrity: To handle disk corruptions to data blocks, data blocks are checksummed. Checksum verification is done on each read; whenever there is a checksum mismatch, re-replication is used to recover the corrupted chunk.
  • File writes: The system follows the standard model. When an application creates a file, the filename becomes part of the filesystem namespace. For performance, writes are cached at the KFS client library. Periodically, the cache is flushed and data is pushed out to the chunkservers. Also, applications can force data to be flushed to the chunkservers. In either case, once data is flushed to the server, it is available for reading.
  • Leases: KFS client library uses caching to improve performance. Leases are used to support cache consistency.
  • Chunk versioning: Versioning is used to detect stale chunks.
  • Client side fail-over: The client library is resilient to chunksever failures. During reads, if the client library determines that the chunkserver it is communicating with is unreachable, the client library will fail-over to another chunkserver and continue the read. This fail-over is transparent to the application.
  • Language support: KFS client library can be accessed from C++, Java, and Python.
  • FUSE support on Linux: By mounting KFS via FUSE, this support allows existing linux utilities (such as, ls) to interface with KFS.
  • Tools: A shell binary is included in the set of tools. This allows users to navigate the filesystem tree using utilities such as, cp, ls, mkdir, rmdir, rm, mv. Tools to also monitor the chunk/meta-servers are provided.
  • Deploy scripts: To simplify launching KFS servers, a set of scripts to (1) install KFS binaries on a set of nodes, (2) start/stop KFS servers on a set of nodes are also provided.

    This seems to compare very favorably to GFS and is targeted at:
  • Primarily write-once/read-many workloads
  • Few millions of large files, where each file is on the order of a few tens of MB to a few tens of GB in size
  • Mostly sequential access

    As Rich says everyone needs to solve the "storage problem" and this looks like an exciting option to add to your bag of tricks. What we are still missing though is a Bigtable like database on top of the file system for scaling structured data.

    If anyone is using KFS please consider sharing your experiences.

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