Merge "Add vCPU cost to solver scheduler"
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# 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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"""
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VCPU Cost. Calculate instance placement costs by hosts' vCPU usage.
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The default is to spread instances across all hosts evenly. If you prefer
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stacking, you can set the 'vcpu_cost_multiplier' option to a negative
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number and the cost has the opposite effect of the default.
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"""
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from oslo_config import cfg
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from oslo_log import log as logging
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from nova.i18n import _LW
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from nova_solverscheduler.scheduler.solvers import costs as solver_costs
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from nova_solverscheduler.scheduler.solvers.costs import utils
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vcpu_cost_opts = [
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cfg.FloatOpt('vcpu_cost_multiplier',
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default=1.0,
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help='Multiplier used for vcpu costs. Negative '
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'numbers mean to stack vs spread.'),
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]
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CONF = cfg.CONF
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CONF.register_opts(vcpu_cost_opts, group='solver_scheduler')
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LOG = logging.getLogger(__name__)
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class VcpuCost(solver_costs.BaseLinearCost):
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def cost_multiplier(self):
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return CONF.solver_scheduler.vcpu_cost_multiplier
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def get_extended_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')
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instance_type = filter_properties.get('instance_type') or {}
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requested_vcpus = instance_type.get('vcpus', 0)
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if requested_vcpus <= 0:
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LOG.warn(_LW("Requested instances\' vCPU number is 0 or invalid, "
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"default value (0) is used."))
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remaining_vcpus_list = []
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for i in xrange(num_hosts):
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vcpus_total = hosts[i].vcpus_total
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vcpus_used = hosts[i].vcpus_used
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if not vcpus_total:
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LOG.warn(_LW("vCPUs of %(host)s not set; assuming CPU "
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"collection broken."), {'host': hosts[i]})
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vcpus_total = 0
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remaining_vcpus = vcpus_total - vcpus_used
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remaining_vcpus_list.append(remaining_vcpus)
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extended_cost_matrix = [[0 for j in xrange(num_instances + 1)]
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for i in xrange(num_hosts)]
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if requested_vcpus == 0:
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extended_cost_matrix = [
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[(-remaining_vcpus_list[i])
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for j in xrange(num_instances + 1)]
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for i in xrange(num_hosts)]
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else:
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# we use int approximation here to avoid scaling problems after
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# normalization, in the case that the free vcpus in all hosts are
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# of very small values
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extended_cost_matrix = [
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[-int(remaining_vcpus_list[i] / requested_vcpus) + j
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for j in xrange(num_instances + 1)]
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for i in xrange(num_hosts)]
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extended_cost_matrix = utils.normalize_cost_matrix(
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extended_cost_matrix)
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return extended_cost_matrix
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@ -0,0 +1,98 @@
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# 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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"""Test case for solver scheduler vCPU cost."""
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from nova import context
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from nova import test
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from nova_solverscheduler.scheduler.solvers import costs
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from nova_solverscheduler.scheduler.solvers.costs import vcpu_cost
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from nova_solverscheduler.tests.scheduler import solver_scheduler_fakes \
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as fakes
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class TestVcpuCost(test.NoDBTestCase):
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def setUp(self):
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super(TestVcpuCost, self).setUp()
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self.context = context.RequestContext('fake_usr', 'fake_proj')
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self.cost_handler = costs.CostHandler()
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self.cost_classes = self.cost_handler.get_matching_classes(
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['nova_solverscheduler.scheduler.solvers.costs.vcpu_cost.VcpuCost']
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)
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def _get_all_hosts(self):
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host1 = fakes.FakeSolverSchedulerHostState('host1', 'node1',
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{'vcpus_total': 32, 'vcpus_used': 12})
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host2 = fakes.FakeSolverSchedulerHostState('host2', 'node2',
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{'vcpus_total': 16, 'vcpus_used': 6})
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host3 = fakes.FakeSolverSchedulerHostState('host3', 'node3',
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{'vcpus_total': 8, 'vcpus_used': 3})
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host4 = fakes.FakeSolverSchedulerHostState('host4', 'node4',
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{'vcpus_total': 0, 'vcpus_used': 0})
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return [host1, host2, host3, host4]
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def test_vcpu_cost_multiplier_1(self):
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self.flags(vcpu_cost_multiplier=0.5, group='solver_scheduler')
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self.assertEqual(0.5, vcpu_cost.VcpuCost().cost_multiplier())
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def test_vcpu_cost_multiplier_2(self):
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self.flags(vcpu_cost_multiplier=(-2), group='solver_scheduler')
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self.assertEqual((-2), vcpu_cost.VcpuCost().cost_multiplier())
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def test_get_extended_cost_matrix(self):
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fake_hosts = self._get_all_hosts()
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fake_filter_properties = {
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'context': self.context,
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'num_instances': 3,
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'instance_type': {'vcpus': 5},
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'instance_uuids': ['fake_uuid_%s' % x for x in range(3)]}
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fake_cost = self.cost_classes[0]()
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expected_x_cost_mat = [
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[-1.0, -0.75, -0.5, -0.25],
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[-0.5, -0.25, 0.0, 0.25],
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[-0.25, 0.0, 0.25, 0.5],
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[0.0, 0.25, 0.5, 0.75]]
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x_cost_mat = fake_cost.get_extended_cost_matrix(fake_hosts,
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fake_filter_properties)
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expected_x_cost_mat = [[round(val, 4) for val in row]
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for row in expected_x_cost_mat]
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x_cost_mat = [[round(val, 4) for val in row] for row in x_cost_mat]
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self.assertEqual(expected_x_cost_mat, x_cost_mat)
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def test_get_extended_cost_matrix_bad_vcpu_req(self):
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fake_hosts = self._get_all_hosts()
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fake_filter_properties = {
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'context': self.context,
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'num_instances': 3,
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'instance_type': {'vcpus': 0},
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'instance_uuids': ['fake_uuid_%s' % x for x in range(3)]}
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fake_cost = self.cost_classes[0]()
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expected_x_cost_mat = [
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[-1.0, -1.0, -1.0, -1.0],
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[-0.5, -0.5, -0.5, -0.5],
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[-0.25, -0.25, -0.25, -0.25],
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[0.0, 0.0, 0.0, 0.0]]
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x_cost_mat = fake_cost.get_extended_cost_matrix(fake_hosts,
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fake_filter_properties)
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expected_x_cost_mat = [[round(val, 4) for val in row]
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for row in expected_x_cost_mat]
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x_cost_mat = [[round(val, 4) for val in row] for row in x_cost_mat]
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self.assertEqual(expected_x_cost_mat, x_cost_mat)
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