077ba77ea6
This patch makes four significant changes to the handling of GET
requests for sharding or sharded containers:
- container server GET requests may now result in the entire list of
shard ranges being returned for the 'listing' state regardless of
any request parameter constraints.
- the proxy server may cache that list of shard ranges in memcache
and the requests environ infocache dict, and subsequently use the
cached shard ranges when handling GET requests for the same
container.
- the proxy now caches more container metadata so that it can
synthesize a complete set of container GET response headers from
cache.
- the proxy server now enforces more container GET request validity
checks that were previously only enforced by the backend server,
e.g. checks for valid request parameter values
With this change, when the proxy learns from container metadata
that the container is sharded then it will cache shard
ranges fetched from the backend during a container GET in memcache.
On subsequent container GETs the proxy will use the cached shard
ranges to gather object listings from shard containers, avoiding
further GET requests to the root container until the cached shard
ranges expire from cache.
Cached shard ranges are most useful if they cover the entire object
name space in the container. The proxy therefore uses a new
X-Backend-Override-Shard-Name-Filter header to instruct the container
server to ignore any request parameters that would constrain the
returned shard range listing i.e. 'marker', 'end_marker', 'includes'
and 'reverse' parameters. Having obtained the entire shard range
listing (either from the server or from cache) the proxy now applies
those request parameter constraints itself when constructing the
client response.
When using cached shard ranges the proxy will synthesize response
headers from the container metadata that is also in cache. To enable
the full set of container GET response headers to be synthezised in
this way, the set of metadata that the proxy caches when handling a
backend container GET response is expanded to include various
timestamps.
The X-Newest header may be used to disable looking up shard ranges
in cache.
Change-Id: I5fc696625d69d1ee9218ee2a508a1b9be6cf9685
OpenStack Swift
OpenStack Swift is 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 https://docs.openstack.org/swift/latest/.
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 run:
pip install -r requirements.txt -r doc/requirements.txt
sphinx-build -W -b html doc/source doc/build/htmland then browse to doc/build/html/index.html. These docs are auto-generated after every commit and available online at https://docs.openstack.org/swift/latest/.
For Developers
Getting Started
Swift is part of OpenStack and follows the code contribution, review, and testing processes common to all OpenStack projects.
If you would like to start contributing, check out these notes to help you get started.
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.
Tests
There are three types of tests included in Swift's source tree.
- Unit tests
- Functional tests
- Probe tests
Unit tests check that small sections of the code behave properly. For example, a unit test may test a single function to ensure that various input gives the expected output. This validates that the code is correct and regressions are not introduced.
Functional tests check that the client API is working as expected. These can be run against any endpoint claiming to support the Swift API (although some tests require multiple accounts with different privilege levels). These are "black box" tests that ensure that client apps written against Swift will continue to work.
Probe tests are "white box" tests that validate the internal workings of a Swift cluster. They are written to work against the "SAIO - Swift All In One" dev environment. For example, a probe test may create an object, delete one replica, and ensure that the background consistency processes find and correct the error.
You can run unit tests with .unittests, functional tests
with .functests, and probe tests with
.probetests. There is an additional .alltests
script that wraps the other three.
To fully run the tests, the target environment must use a filesystem
that supports large xattrs. XFS is strongly recommended. For unit tests
and in-process functional tests, either mount /tmp with XFS
or provide another XFS filesystem via the TMPDIR
environment variable. Without this setting, tests should still pass, but
a very large number will be skipped.
Code Organization
- bin/: Executable scripts that are the processes run by the deployer
- doc/: Documentation
- etc/: Sample config files
- examples/: Config snippets used in the docs
- swift/: Core code
- account/: account server
- cli/: code that backs some of the CLI tools in bin/
- common/: code shared by different modules
- middleware/: "standard", officially-supported middleware
- ring/: code implementing Swift's ring
- container/: container server
- locale/: internationalization (translation) data
- obj/: object server
- proxy/: proxy server
- test/: Unit, functional, and probe 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 https://docs.openstack.org/swift/latest/. A good starting point is at https://docs.openstack.org/swift/latest/deployment_guide.html There is an ops runbook that gives information about how to diagnose and troubleshoot common issues when running a Swift cluster.
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 https://github.com/openstack/python-swiftclient.
Complete API documentation at https://docs.openstack.org/api-ref/object-store/
There is a large ecosystem of applications and libraries that support and work with OpenStack Swift. Several are listed on the associated projects page.
For more information come hang out in #openstack-swift on freenode.
Thanks,
The Swift Development Team