gcsfuse is a user-space file system for interacting with Google Cloud Storage.
Please treat gcsfuse as beta-quality software. Use it for whatever you like, but be aware that bugs may lurk, and that we reserve the right to make small backwards-incompatible changes.
The careful user should be sure to read semantics.md for information on how gcsfuse maps file system operations to GCS operations, and especially on surprising behaviors. The list of open issues may also be of interest.
See installing.md for full installation instructions for Linux and Mac OS X.
- Before invoking gcsfuse, you must have a GCS bucket that you want to mount. If your bucket doesn't yet exist, create one using the Google Developers Console.
- Make sure the Google Cloud Storage JSON API is enabled.
- GCS credentials are automatically loaded using Google application default
credentials, or a JSON key file can be specified
--key-file. If you haven't already done so, the easiest way to set up your credentials for testing is to run the gcloud tool:
gcloud auth login
See mounting.md for more information on credentials.
To mount a bucket using gcsfuse over an existing directory
invoke it like this:
gcsfuse my-bucket /path/to/mount
Important: You should run gcsfuse as the user who will be using the file
system, not as root. Do not use
The gcsfuse tool will exit successfully after mounting the file system. Unmount in the usual way for a fuse file system on your operating system:
umount /path/to/mount # OS X fusermount -u /path/to/mount # Linux
If you are mounting a bucket that was populated with objects by some other means
besides gcsfuse, you may be interested in the
--implicit-dirs flag. See the
notes in semantics.md for more information.
See mounting.md for more detail, including notes on running in the foreground and fstab compatiblity.
Latency and rsync
Writing files to and reading files from GCS has a much higher latency than using a local file system. If you are reading or writing one small file at a time, this may cause you to achieve a low throughput to or from GCS. If you want high throughput, you will need to either use larger files to smooth across latency hiccups or read/write multiple files at a time.
Note in particular that this heavily affects
rsync, which reads and writes
only one file at a time. You might try using
gsutil -m rsync
to transfer multiple files to or from your bucket in parallel instead of plain
rsync with gcsfuse.
If you would like to rate limit traffic to/from GCS in order to set limits on your GCS spending on behalf of gcsfuse, you can do so:
- The flag
--limit-ops-per-seccontrols the rate at which gcsfuse will send requests to GCS.
- The flag
--limit-bytes-per-seccontrols the egress bandwidth from gcsfuse to GCS.
All rate limiting is approximate, and is performed over an 8-hour window. By default, requests are limited to 5 per second. There is no limit applied to bandwidth by default.
GCS round trips
By default, gcsfuse uses two forms of caching to save round trips to GCS, at the
cost of consistency guarantees. These caching behaviors can be controlled with
semantics.md for more information.
If you are using FUSE for macOS, be aware that by
default it will give gcsfuse only 60 seconds to respond to each file system
operation. This means that if you write and then flush a large file and your
upstream bandwidth is insufficient to write it all to GCS within 60 seconds,
your gcsfuse file system may become unresponsive. This behavior can be tuned
daemon_timeout mount option. See issue #196 for
Downloading object contents
Behind the scenes, when a newly-opened file is first modified, gcsfuse downloads
the entire backing object's contents from GCS. The contents are stored in a
local temporary file whose location is controlled by the flag
Later, when the file is closed or fsync'd, gcsfuse writes the contents of the
local file back to GCS as a new object generation.
Files that have not been modified are read portion by portion on demand. gcsfuse uses a heuristic to detect when a file is being read sequentially, and will issue fewer, larger read requests to GCS in this case.
The consequence of this is that gcsfuse is relatively efficient when reading or writing entire large files, but will not be particularly fast for small numbers of random writes within larger files, and to a lesser extent the same is true of small random reads. Performance when copying large files into GCS is comparable to gsutil (see issue #22 for testing notes). There is some overhead due to the staging of data in a local temporary file, as discussed above.
Note that new and modified files are also fully staged in the local temporary directory until they are written out to GCS due to being closed or fsync'd. Therefore the user must ensure that there is enough free space available to handle staged content when writing large files.
Other performance issues
If you notice otherwise unreasonable performance, please file an issue.
gcsfuse is open source software, released under the Apache license. It is distributed as-is, without warranties or conditions of any kind.
For support, visit Server Fault. Tag your questions with
google-cloud-platform, and make sure to look at
previous questions and answers before asking a new one. For bugs and
feature requests, please file an issue.
gcsfuse version numbers are assigned according to Semantic
Versioning. Note that the current major version is
0, which means
that we reserve the right to make backwards-incompatible changes.