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  • Committer: Justin Santa Barbara
  • Date: 2011-03-07 20:27:59 UTC
  • Revision ID: justin@fathomdb.com-20110307202759-6y4on13t5td4zuz8
Initial implementation of proximity scheduler constraint

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Lines of Context:
nova/scheduler/constraint.py
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    def datastore(self):
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        return self.scheduler().datastore()
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    def topology(self):
 
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        context = self.request_context()
 
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        return self.scheduler().topology(context)
 
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    def selectivity(self):
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        # We default to an intermediate value here
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        return 0.75
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                self.trace(_("skip %s: capacity") % host)
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class InstanceConstraintPlaceNearLocation(SchedulerConstraint):
 
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    def __init__(self, target_location):
 
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        super(InstanceConstraintPlaceNearLocation, self).__init__()
 
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        self.target_location = target_location
 
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    def score_item(self, candidate):
 
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        location = self.scheduler().get_service_location(candidate)
 
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        distance = self.topology().distance(self.target_location, location)
 
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        return 1 / (1 + distance) # Map to (0, 1]
 
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    def get_candidate_iterator(self):
 
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        """Returns an iterator over all items in best-to-least-good order"""
 
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        topo = self.topology()
 
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        for location in topo.find_by_distance_from(self.target_location):
 
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            services = self.datastore().get_services_by_location(
 
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                                                    self.request_context(), 
 
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                                                    'compute',
 
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                                                    location)
 
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            for host in services:
 
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                score = self.score_item(host)
 
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                yield constraint_lib.Candidate(host.id, score)
 
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    def selectivity(self):
 
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        # TODO(justinsb): We need to systematize this a bit better...
 
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        return 0.1 # We expect to be very selective
 
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class VolumeConstraintFavorLeastGigabytes(SchedulerConstraint):
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    def __init__(self):
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        super(VolumeConstraintFavorLeastGigabytes, self).__init__()