6e73568e16
* Added small corrections to SLA schemas * Renamed test_ouliers.py to test_outliers.py Change-Id: I6b72a77d0c1d4f60a94c0687f470beed8b58bd97
129 lines
5.2 KiB
Python
129 lines
5.2 KiB
Python
# Copyright 2014: Mirantis 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 ddt
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from rally.plugins.common.sla import outliers
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from rally.task import sla
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from tests.unit import test
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@ddt.ddt
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class OutliersTestCase(test.TestCase):
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@ddt.data(({"max": 0, "min_iterations": 5, "sigmas": 2.5}, True),
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({"max": -1}, False),
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({"max": 0, "min_iterations": 2}, False),
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({"max": 0, "sigmas": 0}, False),
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({"foo": "bar"}, False))
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@ddt.unpack
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def test_validate(self, config, valid):
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results = sla.SLA.validate("outliers", None, None, config)
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if valid:
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self.assertEqual([], results)
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else:
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self.assertEqual(1, len(results))
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def test_result(self):
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sla1 = outliers.Outliers({"max": 1})
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sla2 = outliers.Outliers({"max": 2})
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iteration_durations = [3.1, 4.2, 3.6, 4.5, 2.8, 3.3, 4.1, 3.8, 4.3,
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2.9, 10.2, 11.2, 3.4] # outliers: 10.2, 11.2
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for sla_inst in [sla1, sla2]:
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for d in iteration_durations:
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sla_inst.add_iteration({"duration": d})
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self.assertFalse(sla1.result()["success"]) # 2 outliers > 1
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self.assertTrue(sla2.result()["success"]) # 2 outliers <= 2
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self.assertEqual("Failed", sla1.status())
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self.assertEqual("Passed", sla2.status())
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def test_result_large_sigmas(self):
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sla_inst = outliers.Outliers({"max": 1, "sigmas": 5})
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iteration_durations = [3.1, 4.2, 3.6, 4.5, 2.8, 3.3, 4.1, 3.8, 4.3,
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2.9, 10.2, 11.2, 3.4]
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for d in iteration_durations:
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sla_inst.add_iteration({"duration": d})
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# NOTE(msdubov): No outliers registered since sigmas = 5 (not 2)
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self.assertTrue(sla_inst.result()["success"])
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self.assertEqual("Passed", sla_inst.status())
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def test_result_no_iterations(self):
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sla_inst = outliers.Outliers({"max": 0})
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self.assertTrue(sla_inst.result()["success"])
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def test_result_few_iterations_large_min_iterations(self):
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sla_inst = outliers.Outliers({"max": 0, "min_iterations": 10})
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iteration_durations = [3.1, 4.2, 4.7, 3.6, 15.14, 2.8]
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for d in iteration_durations:
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sla_inst.add_iteration({"duration": d})
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# NOTE(msdubov): SLA doesn't fail because it hasn't iterations < 10
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self.assertTrue(sla_inst.result()["success"])
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def test_result_few_iterations_small_min_iterations(self):
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sla_inst = outliers.Outliers({"max": 0, "min_iterations": 5})
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iteration_durations = [3.1, 4.2, 4.7, 3.6, 15.14, 2.8]
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for d in iteration_durations:
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sla_inst.add_iteration({"duration": d})
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# NOTE(msdubov): Now this SLA can fail with >= 5 iterations
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self.assertFalse(sla_inst.result()["success"])
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def test_add_iteration(self):
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sla_inst = outliers.Outliers({"max": 1})
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# NOTE(msdubov): One outlier in the first 11 iterations
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first_iterations = [3.1, 4.2, 3.6, 4.5, 2.8, 3.3, 4.1, 3.8, 4.3,
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2.9, 10.2]
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for d in first_iterations:
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self.assertTrue(sla_inst.add_iteration({"duration": d}))
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# NOTE(msdubov): 12th iteration makes the SLA always failed
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self.assertFalse(sla_inst.add_iteration({"duration": 11.2}))
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self.assertFalse(sla_inst.add_iteration({"duration": 3.4}))
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@ddt.data([[3.1, 4.2, 3.6, 4.5, 2.8, 3.3, 4.1, 3.8, 4.3, 2.9, 10.2],
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[3.1, 4.2, 3.6, 4.5, 2.8, 3.3, 20.1, 3.8, 4.3, 2.9, 24.2],
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[3.1, 4.2, 3.6, 4.5, 2.8, 3.3, 4.1, 30.8, 4.3, 49.9, 69.2]])
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def test_merge(self, durations):
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single_sla = outliers.Outliers({"max": 1})
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for dd in durations:
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for d in dd:
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single_sla.add_iteration({"duration": d})
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slas = [outliers.Outliers({"max": 1})
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for _ in durations]
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for idx, sla_inst in enumerate(slas):
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for duration in durations[idx]:
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sla_inst.add_iteration({"duration": duration})
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merged_sla = slas[0]
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for sla_inst in slas[1:]:
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merged_sla.merge(sla_inst)
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self.assertEqual(single_sla.success, merged_sla.success)
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self.assertEqual(single_sla.iterations, merged_sla.iterations)
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# self.assertEqual(single_sla.threshold, merged_sla.threshold)
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# NOTE(ikhudoshyn): We are unable to implement
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# rally.plugins.common.sla.outliers.Outliers.merge(..) correctly
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# (see my comment for the method)
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# The assert above will fail with the majority of data
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# The line below passes with this particular data
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# but may fail as well on another data
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self.assertEqual(single_sla.outliers, merged_sla.outliers)
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