Application best practices for distributed file systems¶
CephFS is POSIX compatible, and therefore should work with any existing applications that expect a POSIX file system. However, because it is a network file system (unlike e.g. XFS) and it is highly consistent (unlike e.g. NFS), there are some consequences that application authors may benefit from knowing about.
The following sections describe some areas where distributed file systems may have noticeably different performance behaviours compared with local file systems.
When you run “ls -l”, the
is first doing a directory listing, and then calling
stat on every
file in the directory.
This is usually far in excess of what an application really needs, and
it can be slow for large directories. If you don’t really need all
this metadata for each file, then use a plain
ls/stat on files being extended¶
If another client is currently extending files in the listed directory,
ls -l may take an exceptionally long time to complete, as
the lister must wait for the writer to flush data in order to do a valid
read of the every file’s size. So unless you really need to know the
exact size of every file in the directory, just don’t do it!
This would also apply to any application code that was directly
stat system calls on files being appended from
Very large directories¶
Do you really need that 10,000,000 file directory? While directory fragmentation enables CephFS to handle it, it is always going to be less efficient than splitting your files into more modest-sized directories.
Even standard userspace tools can become quite slow when operating on very
large directories. For example, the default behaviour of
is to give an alphabetically ordered result, but
calls do not give an ordered result (this is true in general, not just
with CephFS). So when you
ls on a million file directory, it is
loading a list of a million names into memory, sorting the list, then writing
it out to the display.
Working set size¶
The MDS acts as a cache for the metadata stored in RADOS. Metadata performance is very different for workloads whose metadata fits within that cache.
If your workload has more files than fit in your cache (configured using
mds_cache_memory_limit settings), then make sure you test it
appropriately: don’t test your system with a small number of files and then
expect equivalent performance when you move to a much larger number of files.