doc | ||
etc | ||
tests | ||
tools/config | ||
zaqar | ||
.coveragerc | ||
.gitignore | ||
.gitreview | ||
.testr.conf | ||
AUTHORS.rst | ||
babel.cfg | ||
bench-requirements.txt | ||
doc-test.conf | ||
HACKING.rst | ||
LICENSE | ||
MANIFEST.in | ||
openstack-common.conf | ||
README.rst | ||
requirements-py3.txt | ||
requirements.txt | ||
setup.cfg | ||
setup.py | ||
test-requirements-py3.txt | ||
test-requirements.txt | ||
tox.ini |
Zaqar
Message queuing service for OpenStack. To find more information read our wiki.
Running a local Zaqar server with MongoDB
Note: These instructions are for running a local instance of Zaqar and not all of these steps are required. It is assumed you have MongoDB installed and running.
From your home folder create the
~/.zaqar
folder and clone the repo:$ cd $ mkdir .zaqar $ git clone https://github.com/openstack/zaqar.git
Copy the Zaqar config files to the directory
~/.zaqar
:$ cp zaqar/etc/zaqar.conf.sample ~/.zaqar/zaqar.conf $ cp zaqar/etc/logging.conf.sample ~/.zaqar/logging.conf
Find
[drivers]
section in~/.zaqar/zaqar.conf
and specify to use mongodb storage:storage = mongodb
Then find the
[drivers:storage:mongodb]
section and modify the URI to point to your local mongod instance:uri = mongodb://$MONGODB_HOST:$MONGODB_PORT
By default, you will have:
uri = mongodb://127.0.0.1:27017
For logging, find the
[DEFAULT]
section in~/.zaqar/zaqar.conf
and modify as desired:log_file = server.log
Change directories back to your local copy of the repo:
$ cd zaqar
Run the following so you can see the results of any changes you make to the code without having to reinstall the package each time:
$ pip install -e .
Start the Zaqar server with logging level set to INFO so you can see the port on which the server is listening:
$ zaqar-server -v
Test out that Zaqar is working by creating a queue:
$ curl -i -X PUT http://127.0.0.1:8888/v1/queues/samplequeue -H "Content-type: application/json"
You should get an HTTP 201 along with some headers that will look similar to this:
HTTP/1.0 201 Created
Date: Fri, 25 Oct 2013 15:34:37 GMT
Server: WSGIServer/0.1 Python/2.7.3
Content-Length: 0
Location: /v1/queues/samplequeue
Running tests
First install additional requirements:
$ pip install tox
And then run tests:
$ tox -e py27
You can read more about running functional tests in separate TESTS_README.
Running the benchmarking tool
First install and run zaqar-server (see above).
Then install additional requirements:
$ pip install -r bench-requirements.txt
Copy the configuration file to ~/.zaqar
:
$ cp etc/zaqar-benchmark.conf.sample ~/.zaqar/zaqar-benchmark.conf
In the configuration file specify where zaqar-server can be found:
server_url = http://localhost:8888
The benchmarking tool needs a set of messages to work with. Specify
the path to the file with messages in the configuration file.
Alternatively, put it in the directory with the configuration file and
name it zaqar-benchmark- messages.json
. As a starting
point, you can use the sample file from the etc
directory:
$ cp etc/zaqar-benchmark-messages.json ~/.zaqar/
If the file is not found or no file is specified, a single hard-coded message is used for all requests.
Run the benchmarking tool using the following command:
$ zaqar-bench-pc
By default, the command will run a performance test for 3 seconds, using one consumer and one producer for each CPU on the system, with 2 greenlet workers per CPU per process. You can override these defaults in the config file or on the command line using a variety of options. For example, the following command runs a performance test for 10 seconds using 4 producer processes with 20 workers each, plus 1 consumer process with 4 workers:
$ zaqar-bench-pc -pp 4 -pw 20 -cp 1 -cw 4 -t 10
By default, the results are in JSON. For more human-readable output
add the --verbose
flag. Verbose output looks similar to the
following:
Starting Producer...
Starting Consumer...
Consumer
========
duration_sec: 10.2
ms_per_claim: 37.6
ms_per_delete: 11.8
reqs_per_sec: 82.0
successful_reqs: 833.0
total_reqs: 833.0
Producer
========
duration_sec: 10.2
ms_per_req: 3.8
reqs_per_sec: 1033.6
successful_reqs: 10523.0
total_reqs: 10523.0