188 lines
7.0 KiB
Python
188 lines
7.0 KiB
Python
# Copyright 2011 OpenStack Foundation
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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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Fakes For Scheduler tests.
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"""
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import datetime
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from oslo_utils.fixture import uuidsentinel
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from nova import objects
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from nova.scheduler import driver
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from nova.scheduler import host_manager
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NUMA_TOPOLOGY = objects.NUMATopology(cells=[
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objects.NUMACell(
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id=0, cpuset=set([1, 2]), memory=512,
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cpu_usage=0, memory_usage=0, mempages=[
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objects.NUMAPagesTopology(size_kb=16, total=387184, used=0),
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objects.NUMAPagesTopology(size_kb=2048, total=512, used=0)],
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pinned_cpus=set([]),
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siblings=[set([1]), set([2])]),
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objects.NUMACell(
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id=1, cpuset=set([3, 4]), memory=512,
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cpu_usage=0, memory_usage=0, mempages=[
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objects.NUMAPagesTopology(size_kb=4, total=1548736, used=0),
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objects.NUMAPagesTopology(size_kb=2048, total=512, used=0)],
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pinned_cpus=set([]),
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siblings=[set([3]), set([4])])])
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NUMA_TOPOLOGIES_W_HT = [
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objects.NUMATopology(cells=[
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objects.NUMACell(
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id=0, cpuset=set([1, 2, 5, 6]), memory=512,
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cpu_usage=0, memory_usage=0, mempages=[],
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siblings=[set([1, 5]), set([2, 6])], pinned_cpus=set([])),
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objects.NUMACell(
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id=1, cpuset=set([3, 4, 7, 8]), memory=512,
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cpu_usage=0, memory_usage=0, mempages=[],
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siblings=[set([3, 4]), set([7, 8])], pinned_cpus=set([]))
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]),
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objects.NUMATopology(cells=[
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objects.NUMACell(
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id=0, cpuset=set([]), memory=512,
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cpu_usage=0, memory_usage=0, mempages=[],
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siblings=[], pinned_cpus=set([])),
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objects.NUMACell(
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id=1, cpuset=set([1, 2, 5, 6]), memory=512,
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cpu_usage=0, memory_usage=0, mempages=[],
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siblings=[set([1, 5]), set([2, 6])], pinned_cpus=set([])),
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objects.NUMACell(
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id=2, cpuset=set([3, 4, 7, 8]), memory=512,
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cpu_usage=0, memory_usage=0, mempages=[],
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siblings=[set([3, 4]), set([7, 8])], pinned_cpus=set([])),
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]),
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]
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COMPUTE_NODES = [
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objects.ComputeNode(
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uuid=uuidsentinel.cn1,
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id=1, local_gb=1024, memory_mb=1024, vcpus=1,
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disk_available_least=None, free_ram_mb=512, vcpus_used=1,
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free_disk_gb=512, local_gb_used=0,
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updated_at=datetime.datetime(2015, 11, 11, 11, 0, 0),
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host='host1', hypervisor_hostname='node1', host_ip='127.0.0.1',
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hypervisor_version=0, numa_topology=None,
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hypervisor_type='foo', supported_hv_specs=[],
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pci_device_pools=None, cpu_info=None, stats=None, metrics=None,
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cpu_allocation_ratio=16.0, ram_allocation_ratio=1.5,
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disk_allocation_ratio=1.0),
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objects.ComputeNode(
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uuid=uuidsentinel.cn2,
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id=2, local_gb=2048, memory_mb=2048, vcpus=2,
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disk_available_least=1024, free_ram_mb=1024, vcpus_used=2,
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free_disk_gb=1024, local_gb_used=0,
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updated_at=datetime.datetime(2015, 11, 11, 11, 0, 0),
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host='host2', hypervisor_hostname='node2', host_ip='127.0.0.1',
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hypervisor_version=0, numa_topology=None,
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hypervisor_type='foo', supported_hv_specs=[],
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pci_device_pools=None, cpu_info=None, stats=None, metrics=None,
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cpu_allocation_ratio=16.0, ram_allocation_ratio=1.5,
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disk_allocation_ratio=1.0),
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objects.ComputeNode(
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uuid=uuidsentinel.cn3,
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id=3, local_gb=4096, memory_mb=4096, vcpus=4,
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disk_available_least=3333, free_ram_mb=3072, vcpus_used=1,
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free_disk_gb=3072, local_gb_used=0,
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updated_at=datetime.datetime(2015, 11, 11, 11, 0, 0),
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host='host3', hypervisor_hostname='node3', host_ip='127.0.0.1',
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hypervisor_version=0, numa_topology=NUMA_TOPOLOGY._to_json(),
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hypervisor_type='foo', supported_hv_specs=[],
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pci_device_pools=None, cpu_info=None, stats=None, metrics=None,
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cpu_allocation_ratio=16.0, ram_allocation_ratio=1.5,
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disk_allocation_ratio=1.0),
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objects.ComputeNode(
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uuid=uuidsentinel.cn4,
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id=4, local_gb=8192, memory_mb=8192, vcpus=8,
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disk_available_least=8192, free_ram_mb=8192, vcpus_used=0,
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free_disk_gb=8888, local_gb_used=0,
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updated_at=datetime.datetime(2015, 11, 11, 11, 0, 0),
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host='host4', hypervisor_hostname='node4', host_ip='127.0.0.1',
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hypervisor_version=0, numa_topology=None,
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hypervisor_type='foo', supported_hv_specs=[],
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pci_device_pools=None, cpu_info=None, stats=None, metrics=None,
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cpu_allocation_ratio=16.0, ram_allocation_ratio=1.5,
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disk_allocation_ratio=1.0),
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# Broken entry
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objects.ComputeNode(
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uuid=uuidsentinel.cn5,
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id=5, local_gb=1024, memory_mb=1024, vcpus=1,
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host='fake', hypervisor_hostname='fake-hyp'),
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]
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ALLOC_REQS = [
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{
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'allocations': {
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cn.uuid: {
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'resources': {
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'VCPU': 1,
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'MEMORY_MB': 512,
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'DISK_GB': 512,
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},
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}
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}
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} for cn in COMPUTE_NODES
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]
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RESOURCE_PROVIDERS = [
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dict(
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uuid=uuidsentinel.rp1,
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name='host1',
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generation=1),
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dict(
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uuid=uuidsentinel.rp2,
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name='host2',
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generation=1),
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dict(
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uuid=uuidsentinel.rp3,
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name='host3',
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generation=1),
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dict(
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uuid=uuidsentinel.rp4,
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name='host4',
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generation=1),
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]
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SERVICES = [
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objects.Service(host='host1', disabled=False),
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objects.Service(host='host2', disabled=True),
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objects.Service(host='host3', disabled=False),
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objects.Service(host='host4', disabled=False),
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]
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def get_service_by_host(host):
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services = [service for service in SERVICES if service.host == host]
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return services[0]
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class FakeHostState(host_manager.HostState):
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def __init__(self, host, node, attribute_dict, instances=None):
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super(FakeHostState, self).__init__(host, node, None)
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if instances:
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self.instances = {inst.uuid: inst for inst in instances}
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else:
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self.instances = {}
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for (key, val) in attribute_dict.items():
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setattr(self, key, val)
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class FakeScheduler(driver.Scheduler):
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def select_destinations(self, context, spec_obj, instance_uuids):
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return []
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