58359269b0
When a client disconnected while consuming an SLO or DLO GET response,
the proxy would leak a socket. This could be observed via strace as a
socket that had shutdown() called on it, but was never closed. It
could also be observed by counting entries in /proc/<pid>/fd, where
<pid> is the pid of a proxy server worker process.
This is due to a memory leak in SegmentedIterable. A SegmentedIterable
has an 'app_iter' attribute, which is a generator. That generator
references 'self' (the SegmentedIterable object). This creates a
cyclic reference: the generator refers to the SegmentedIterable, and
the SegmentedIterable refers to the generator.
Python can normally handle cyclic garbage; reference counting won't
reclaim it, but the garbage collector will. However, objects with
finalizers will stop the garbage collector from collecting them* and
the cycle of which they are part.
For most objects, "has finalizer" is synonymous with "has a __del__
method". However, a generator has a finalizer once it's started
running and before it finishes: basically, while it has stack frames
associated with it**.
When a client disconnects mid-stream, we get a memory leak. We have
our SegmentedIterable object (call it "si"), and its associated
generator. si.app_iter is the generator, and the generator closes over
si, so we have a cycle; and the generator has started but not yet
finished, so the generator needs finalization; hence, the garbage
collector won't ever clean it up.
The socket leak comes in because the generator *also* refers to the
request's WSGI environment, which contains wsgi.input, which
ultimately refers to a _socket object from the standard
library. Python's _socket objects only close their underlying file
descriptor when their reference counts fall to 0***.
This commit makes SegmentedIterable.close() call
self.app_iter.close(), thereby unwinding its generator's stack and
making it eligible for garbage collection.
* in Python < 3.4, at least. See PEP 442.
** see PyGen_NeedsFinalizing() in Objects/genobject.c and also
has_finalizer() in Modules/gcmodule.c in Python.
*** see sock_dealloc() in Modules/socketmodule.c in Python. See
sock_close() in the same file for the other half of the sad story.
This closes CVE-2016-0738.
Closes-Bug: 1493303
Co-Authored-By: Kota Tsuyuzaki <tsuyuzaki.kota@lab.ntt.co.jp>
Change-Id: Ib86c4c45641485ce1034212bf6f53bb84f02f612
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| bin | ||
| doc | ||
| etc | ||
| examples | ||
| swift | ||
| test | ||
| .alltests | ||
| .coveragerc | ||
| .functests | ||
| .gitignore | ||
| .gitreview | ||
| .mailmap | ||
| .probetests | ||
| .testr.conf | ||
| .unittests | ||
| AUTHORS | ||
| babel.cfg | ||
| bandit.yaml | ||
| CHANGELOG | ||
| CONTRIBUTING.md | ||
| LICENSE | ||
| MANIFEST.in | ||
| README.md | ||
| requirements.txt | ||
| setup.cfg | ||
| setup.py | ||
| test-requirements.txt | ||
| tox.ini | ||
Swift
A distributed object storage system designed to scale from a single machine to thousands of servers. Swift is optimized for multi-tenancy and high concurrency. Swift is ideal for backups, web and mobile content, and any other unstructured data that can grow without bound.
Swift provides a simple, REST-based API fully documented at http://docs.openstack.org/.
Swift was originally developed as the basis for Rackspace's Cloud Files and was open-sourced in 2010 as part of the OpenStack project. It has since grown to include contributions from many companies and has spawned a thriving ecosystem of 3rd party tools. Swift's contributors are listed in the AUTHORS file.
Docs
To build documentation install sphinx (pip install sphinx), run
python setup.py build_sphinx, and then browse to /doc/build/html/index.html.
These docs are auto-generated after every commit and available online at
http://docs.openstack.org/developer/swift/.
For Developers
The best place to get started is the "SAIO - Swift All In One". This document will walk you through setting up a development cluster of Swift in a VM. The SAIO environment is ideal for running small-scale tests against swift and trying out new features and bug fixes.
You can run unit tests with .unittests and functional tests with
.functests.
If you would like to start contributing, check out these notes to help you get started.
Code Organization
- bin/: Executable scripts that are the processes run by the deployer
- doc/: Documentation
- etc/: Sample config files
- swift/: Core code
- account/: account server
- common/: code shared by different modules
- middleware/: "standard", officially-supported middleware
- ring/: code implementing Swift's ring
- container/: container server
- obj/: object server
- proxy/: proxy server
- test/: Unit and functional tests
Data Flow
Swift is a WSGI application and uses eventlet's WSGI server. After the
processes are running, the entry point for new requests is the Application
class in swift/proxy/server.py. From there, a controller is chosen, and the
request is processed. The proxy may choose to forward the request to a back-
end server. For example, the entry point for requests to the object server is
the ObjectController class in swift/obj/server.py.
For Deployers
Deployer docs are also available at http://docs.openstack.org/developer/swift/. A good starting point is at http://docs.openstack.org/developer/swift/deployment_guide.html
You can run functional tests against a swift cluster with .functests. These
functional tests require /etc/swift/test.conf to run. A sample config file
can be found in this source tree in test/sample.conf.
For Client Apps
For client applications, official Python language bindings are provided at http://github.com/openstack/python-swiftclient.
Complete API documentation at http://docs.openstack.org/api/openstack-object-storage/1.0/content/
For more information come hang out in #openstack-swift on freenode.
Thanks,
The Swift Development Team