Asynchronous jobs and worker management¶
AtoM relies on Gearman in order to execute certain long-running tasks asynchronously to guarantee that web requests are handled promptly and work loads can be distributed across multiple machines.
For example, the ingest of Archivematica DIPs is processed asynchronously. See Upload DIP for more details.
You’ll need a good understanding of all the components involved to find out what the best configuration and arrangement of services will be for you. You could configure it so every service runs in the same machine, or scale up to many machines across the network. You can always start small in a single-node environment and add more hardware later.
Gearman Job Server¶
The first thing that you need to do is to install the job server (Gearman Job Server):
sudo apt-get install gearman-job-server
It’s up to you to install the job server in the same machine where you are
running AtoM or in another machine in the same network. If you are doing the
latter, make sure that you update /etc/default/gearman-job-server
accordingly:
PARAMS="--listen=* --port=4730"
Note
By default, Gearman’s job queues are stored in memory. However you are free to deploy the queue storage in a different machine or replace it with a durable solution like MySQL or SQLite3. For more configuration options available, visit: http://gearman.org/manual/job_server/.
Gearman Job Worker¶
In AtoM, a worker is just a CLI task that you can run in a terminal or supervise with specific tools like upstart, supervisord or circus. The worker will wait for jobs that are assigned by the job server.
The simplest way to run a worker is from your terminal:
php symfony jobs:worker
A better way to run a worker is to use a process supervisor like upstart (included in Ubuntu 14.04) or systemd (included in Ubuntu 16.04). Both options are documented below.
Upstart (Ubuntu 14.04)¶
An upstart service (/etc/init/atom-worker.conf
) could look like:
description "AtoM worker (gearmand) upstart service"
start on (started mysql)
stop on runlevel [016]
respawn
respawn limit 5 10
env LOCATION=/usr/share/nginx/atom
env LOGFILE=/usr/share/nginx/atom/log/atom-worker.log
setuid www-data
setgid www-data
script
php \
-d memory_limit=-1 \
-d error_reporting="E_ALL" \
${LOCATION}/symfony jobs:worker >> ${LOGFILE} 2>&1
end script
You can control the service execution status with the following commands:
sudo start atom-worker # Starts the worker
sudo stop atom-worker # Stops the worker
sudo restart atom-worker # Restarts the workers
sudo status atom-worker # Obtain current running status
initctl is the primary command used to interact with Upstart and its services. Check out its man page (man initctl) or the following link for more instructions: http://upstart.ubuntu.com/cookbook/#initctl.
systemd (Ubuntu 16.04)¶
Create the following service (/usr/lib/systemd/system/atom-worker.service
):
[Unit]
Description=AtoM worker
After=network.target
[Install]
WantedBy=multi-user.target
[Service]
Type=simple
User=www-data
Group=www-data
WorkingDirectory=/usr/share/nginx/atom
ExecStart=/usr/bin/php -d memory_limit=-1 -d error_reporting="E_ALL" symfony jobs:worker
ExecStop=/bin/kill -s TERM $MAINPID
Restart=no
Now reload systemd:
sudo systemctl daemon-reload
You can control the service execution status with the following commands:
sudo systemctl enable atom-worker # Enables the worker (on boot)
sudo systemctl start atom-worker # Starts the worker
sudo systemctl stop atom-worker # Stops the worker
sudo systemctl restart atom-worker # Restarts the workers
sudo systemctl status atom-worker # Obtains current status
You can have access to the journal of our new atom-worker
unit as follows:
sudo journalctl -f -u atom-worker
This is going to be useful in case you need to troubleshoot the worker.
Other considerations¶
An AtoM worker needs to know where the job server is running, which is defined
in an application setting called gearman_job_server under
config/gearman.yml
. Whenever you change that setting, make sure that the
Symfony cache is refreshed and the worker is restarted.
Note that the job server will perfectly handle multiple workers running simultaneously and the work load will be distributed across all available workers. If there are no workers available because they are busy completing other tasks, the job server will store the job in the queues and deliver them once a worker becomes available.