139 lines
5.8 KiB
Python
139 lines
5.8 KiB
Python
# Copyright (c) 2015 Cisco Systems, Inc.
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# All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License"); you may
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# not use this file except in compliance with the License. You may obtain
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# a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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# License for the specific language governing permissions and limitations
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# under the License.
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import operator
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from nova_solverscheduler.scheduler import solvers as scheduler_solver
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class FastSolver(scheduler_solver.BaseHostSolver):
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def __init__(self):
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super(FastSolver, self).__init__()
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self.cost_classes = self._get_cost_classes()
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self.constraint_classes = self._get_constraint_classes()
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def _get_cost_matrix(self, hosts, filter_properties):
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num_hosts = len(hosts)
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num_instances = filter_properties.get('num_instances', 1)
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solver_cache = filter_properties['solver_cache']
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# initialize cost matrix
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cost_matrix = [[0 for j in xrange(num_instances)]
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for i in xrange(num_hosts)]
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solver_cache['cost_matrix'] = cost_matrix
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cost_objects = [cost() for cost in self.cost_classes]
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cost_objects.sort(key=lambda cost: cost.precedence)
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precedence_level = 0
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for cost_object in cost_objects:
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if cost_object.precedence > precedence_level:
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# update cost matrix in the solver cache
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solver_cache['cost_matrix'] = cost_matrix
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precedence_level = cost_object.precedence
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cost_multiplier = cost_object.cost_multiplier()
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this_cost_mat = cost_object.get_cost_matrix(hosts,
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filter_properties)
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if not this_cost_mat:
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continue
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cost_matrix = [[cost_matrix[i][j] +
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this_cost_mat[i][j] * cost_multiplier
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for j in xrange(num_instances)]
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for i in xrange(num_hosts)]
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# update cost matrix in the solver cache
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solver_cache['cost_matrix'] = cost_matrix
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return cost_matrix
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def _get_constraint_matrix(self, hosts, filter_properties):
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num_hosts = len(hosts)
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num_instances = filter_properties.get('num_instances', 1)
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solver_cache = filter_properties['solver_cache']
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# initialize constraint_matrix
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constraint_matrix = [[True for j in xrange(num_instances)]
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for i in xrange(num_hosts)]
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solver_cache['constraint_matrix'] = constraint_matrix
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constraint_objects = [cons() for cons in self.constraint_classes]
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constraint_objects.sort(key=lambda cons: cons.precedence)
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precedence_level = 0
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for constraint_object in constraint_objects:
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if constraint_object.precedence > precedence_level:
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# update constraint matrix in the solver cache
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solver_cache['constraint_matrix'] = constraint_matrix
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precedence_level = constraint_object.precedence
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this_cons_mat = constraint_object.get_constraint_matrix(hosts,
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filter_properties)
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if not this_cons_mat:
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continue
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constraint_matrix = [[constraint_matrix[i][j] &
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this_cons_mat[i][j] for j in xrange(num_instances)]
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for i in xrange(num_hosts)]
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# update constraint matrix in the solver cache
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solver_cache['constraint_matrix'] = constraint_matrix
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return constraint_matrix
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def solve(self, hosts, filter_properties):
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host_instance_combinations = []
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num_instances = filter_properties['num_instances']
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num_hosts = len(hosts)
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instance_uuids = filter_properties.get('instance_uuids') or [
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'(unknown_uuid)' + str(i) for i in xrange(num_instances)]
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filter_properties.setdefault('solver_cache', {})
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filter_properties['solver_cache'].update(
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{'cost_matrix': [],
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'constraint_matrix': []})
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cost_matrix = self._get_cost_matrix(hosts, filter_properties)
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constraint_matrix = self._get_constraint_matrix(hosts,
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filter_properties)
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placement_cost_tuples = []
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for i in xrange(num_hosts):
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for j in xrange(num_instances):
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if constraint_matrix[i][j]:
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host_idx = i
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inst_num = j + 1
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cost_val = cost_matrix[i][j]
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placement_cost_tuples.append(
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(host_idx, inst_num, cost_val))
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sorted_placement_costs = sorted(placement_cost_tuples,
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key=operator.itemgetter(2))
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host_inst_alloc = [0 for i in xrange(num_hosts)]
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allocated_inst_num = 0
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for (host_idx, inst_num, cost_val) in sorted_placement_costs:
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delta = inst_num - host_inst_alloc[host_idx]
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if (delta <= 0) or (allocated_inst_num + delta > num_instances):
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continue
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host_inst_alloc[host_idx] += delta
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allocated_inst_num += delta
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if allocated_inst_num == num_instances:
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break
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instances_iter = iter(instance_uuids)
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for i in xrange(len(host_inst_alloc)):
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num = host_inst_alloc[i]
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for n in xrange(num):
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host_instance_combinations.append(
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(hosts[i], instances_iter.next()))
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return host_instance_combinations
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