mirror of
https://gitlab.ub.uni-bielefeld.de/sfb1288inf/nopaque.git
synced 2024-12-24 02:24:20 +00:00
Don't use jaas as if offers not enough configuration possibilities.
This commit is contained in:
Patrick Jentsch
parent
7b185d929e
commit
cd79061579
162
app/swarm.py
162
app/swarm.py
@ -1,98 +1,88 @@
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import docker
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import subprocess
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import time
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class Swarm:
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def __init__(self):
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self.docker = docker.from_env()
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self.checkout()
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def checkout(self):
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cpus = 0
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memory = 0
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for node in self.docker.nodes.list(filters={'role': 'worker'}):
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if node.attrs.get('Status').get('State') == 'ready':
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cpus += 0 or node.attrs \
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.get('Description') \
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.get('Resources') \
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.get('NanoCPUs')
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memory += 0 or node.attrs \
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.get('Description') \
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.get('Resources') \
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.get('MemoryBytes')
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'''
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' For whatever reason the Python Docker SDK provides a CPU count in
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' nano (10^-6), whilst this is not that handy, it gets converted.
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'''
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cpus *= 10 ** -9
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'''
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' For a more natural handling the memory information
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' gets converted from bytes to megabytes.
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'''
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memory *= 10 ** -6
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self.cpus = int(cpus)
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self.memory = int(memory)
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self.available_cpus = self.cpus
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self.available_memory = self.memory
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'''
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' Swarm mode is intendet to run containers which serve a non terminating
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' service like a webserver. For processing an occuring job it is necessary
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' to use a one-shot container, which stops after the wrapped job process is
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' completly executed. In order to run these one-shot containers in Swarm
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' mode, the following run method is implemented analog to the presented
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' implementation in Alex Ellis' blog post "One-shot containers on Docker
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' Swarm"¹.
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'
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' ¹ https://blog.alexellis.io/containers-on-swarm/
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'''
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def run(self, job):
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if self.available_cpus < job['requested_cpus'] or \
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self.available_memory < job['requested_memory']:
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print('Not enough ressources available.')
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'''
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' TODO: At this point the scheduler thinks that the job gets
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' processed, which apparently is not the case. So the job
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' needs to get rescheduled and gain a new chance to get
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' processed (next).
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'
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' Note: Maybe it is a good idea to create a method that checks if
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' enough ressources are available before the run method gets
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' executed. This would replace the need of the TODO mentioned
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' above.
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'''
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return
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job['status'] = 'running'
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# TODO: Push job changes to the database
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self.available_cpus -= job['requested_cpus']
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self.available_memory -= job['requested_memory']
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container_command = 'ocr' \
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+ ' -i /input/{}'.format(job['id']) \
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+ ' -l {}'.format(job['service_args']['lang']) \
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+ ' -o /output' \
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+ ' --keep-intermediates' \
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+ ' --nCores {}'.format(job['requested_cpus'])
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container_image = 'gitlab.ub.uni-bielefeld.de:4567/sfb1288inf/ocr'
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container_mount = '/media/sf_files/=/input/'
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'''
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' Swarm mode is intendet to run containers which are meant to serve a
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' non terminating service like a webserver. In order to process the
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' occuring jobs it is necessary to use one-shot (terminating)
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' containers. These one-shot containers are spawned with a programm
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' called JaaS¹ (Jobs as a Service), which is described in Alex Ellis'
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' short article "One-shot containers on Docker Swarm"².
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'
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' ¹ https://github.com/alexellis/jaas
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' ² https://blog.alexellis.io/containers-on-swarm/
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'''
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cmd = ['jaas', 'run'] \
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+ ['--command', container_command] \
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+ ['--image', container_image] \
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+ ['--mount', container_mount] \
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+ ['--timeout', '86400s']
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completed_process = subprocess.run(
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cmd,
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stderr=subprocess.DEVNULL,
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stdout=subprocess.DEVNULL
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# Prepare argument values needed for the service creation.
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_command = 'ocr' \
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+ ' -i /input/{}'.format(job['id']) \
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+ ' -l {}'.format(job['service_args']['lang']) \
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+ ' -o /output' \
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+ ' --keep-intermediates' \
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+ ' --nCores {}'.format(job['requested_cpus'])
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_constraints = ['node.role==worker']
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_image = 'gitlab.ub.uni-bielefeld.de:4567/sfb1288inf/{}:{}'.format(
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job['service'],
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job['service_args']['version']
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)
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self.available_cpus += job['requested_cpus']
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self.available_memory += job['requested_memory']
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if (completed_process.returncode == 0):
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job['status'] = 'finished'
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else:
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job['status'] = 'failed'
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# TODO: Push job changes to the database
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_labels = {'service': 'ocr'}
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_mounts = ['/media/sf_files:/input:rw']
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_name = job['id']
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'''
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' The Docker SDK for Python expects the cpu_reservation value to be
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' scaled to nanos (10^9). Because the job object contains unscaled
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' (10^0) values, it must be conveted.
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'
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' While the cpu_reservation value has to be in nanos, the
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' mem_reservation value must be presented in bytes (intuitive right?).
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' Bacause the job object provides the memory value in megabytes, it is
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' also necessary to convert the value.
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'''
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_resources = docker.types.Resources(
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cpu_reservation=job['requested_cpus'] * (10 ** 9),
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mem_reservation=job['requested_memory'] * (10 ** 6)
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)
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_restart_policy = docker.types.RestartPolicy(condition='none')
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'''
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' Create the service with the prepared values.
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'
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' Note: A service reserves hardware ressources. In case no worker node
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' has the required ressources available (not reserved), the
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' service gets queued by the Docker engine until a node is able
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' to meet the requirements.
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'
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' TODO: The name argument should be used with the prepared value
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' (name=_name). Because there is no id generator for now, it is
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' not set, so that the Docker engine assigns a random name.
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'''
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service = self.docker.services.create(
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_image,
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command=_command,
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constraints=_constraints,
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labels=_labels,
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mounts=_mounts,
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resources=_resources,
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restart_policy=_restart_policy
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)
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'''
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' Poll the service until the job is completly executed.
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'
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' Note: Because it takes some time until all data in the service object
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' is initialized (especcially the task list returned by the tasks
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' method) the poll loop also checks if the task list is empy (The
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' not service.tasks() condition implements this).
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'''
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while not service.tasks() or \
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service.tasks()[0].get('Status').get('State') != 'complete':
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time.sleep(1)
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service.reload()
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# Remove the service from the swarm.
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service.remove()
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return
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