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Add the Distribution data type for instrumentation
This is one of a series of CLs adding a new metric type, EventMetric, which is used for tracking numerical distributions. ------------- Created by MOE: https://github.com/google/moe MOE_MIGRATED_REVID=132103552
This commit is contained in:
shikhman
Ben McIlwain
parent
180240ae04
commit
dcb189943b
13 changed files with 961 additions and 0 deletions
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// Copyright 2016 The Domain Registry Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain 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,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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package google.registry.monitoring.metrics;
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import static com.google.common.truth.Truth.assertThat;
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import com.google.common.collect.ImmutableRangeMap;
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import com.google.common.collect.ImmutableSet;
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import com.google.common.collect.Range;
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import org.junit.Before;
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import org.junit.Rule;
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import org.junit.Test;
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import org.junit.rules.ExpectedException;
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import org.junit.runner.RunWith;
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import org.junit.runners.JUnit4;
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/** Tests for {@link MutableDistribution} */
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@RunWith(JUnit4.class)
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public class MutableDistributionTest {
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private MutableDistribution distribution;
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@Rule public final ExpectedException thrown = ExpectedException.none();
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@Before
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public void setUp() throws Exception {
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distribution = new MutableDistribution(CustomFitter.create(ImmutableSet.of(3.0, 5.0)));
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}
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@Test
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public void testAdd_oneValue() {
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distribution.add(5.0);
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assertThat(distribution.count()).isEqualTo(1);
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assertThat(distribution.mean()).isWithin(0.0).of(5.0);
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assertThat(distribution.sumOfSquaredDeviation()).isWithin(0.0).of(0);
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assertThat(distribution.intervalCounts())
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.isEqualTo(
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ImmutableRangeMap.<Double, Long>builder()
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.put(Range.lessThan(3.0), 0L)
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.put(Range.closedOpen(3.0, 5.0), 0L)
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.put(Range.atLeast(5.0), 1L)
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.build());
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}
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@Test
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public void testAdd_zero() {
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distribution.add(0.0);
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assertThat(distribution.count()).isEqualTo(1);
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assertThat(distribution.mean()).isWithin(0.0).of(0.0);
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assertThat(distribution.sumOfSquaredDeviation()).isWithin(0.0).of(0);
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assertThat(distribution.intervalCounts())
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.isEqualTo(
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ImmutableRangeMap.<Double, Long>builder()
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.put(Range.lessThan(3.0), 1L)
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.put(Range.closedOpen(3.0, 5.0), 0L)
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.put(Range.atLeast(5.0), 0L)
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.build());
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}
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@Test
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public void testAdd_multipleOfOneValue() {
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distribution.add(4.0, 2);
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assertThat(distribution.count()).isEqualTo(2);
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assertThat(distribution.mean()).isWithin(0.0).of(4.0);
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assertThat(distribution.sumOfSquaredDeviation()).isWithin(0.0).of(0);
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assertThat(distribution.intervalCounts())
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.isEqualTo(
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ImmutableRangeMap.<Double, Long>builder()
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.put(Range.lessThan(3.0), 0L)
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.put(Range.closedOpen(3.0, 5.0), 2L)
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.put(Range.atLeast(5.0), 0L)
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.build());
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}
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@Test
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public void testAdd_positiveThenNegativeValue() {
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distribution.add(2.0);
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distribution.add(-2.0);
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assertThat(distribution.count()).isEqualTo(2);
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assertThat(distribution.mean()).isWithin(0.0).of(0.0);
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assertThat(distribution.sumOfSquaredDeviation()).isWithin(0.0).of(8.0);
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assertThat(distribution.intervalCounts())
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.isEqualTo(
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ImmutableRangeMap.<Double, Long>builder()
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.put(Range.lessThan(3.0), 2L)
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.put(Range.closedOpen(3.0, 5.0), 0L)
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.put(Range.atLeast(5.0), 0L)
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.build());
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}
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@Test
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public void testAdd_wideRangeOfValues() {
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distribution.add(2.0);
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distribution.add(16.0);
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distribution.add(128.0, 5);
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assertThat(distribution.count()).isEqualTo(7);
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assertThat(distribution.mean()).isWithin(0.0).of(94.0);
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assertThat(distribution.sumOfSquaredDeviation()).isWithin(0.0).of(20328.0);
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assertThat(distribution.intervalCounts())
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.isEqualTo(
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ImmutableRangeMap.<Double, Long>builder()
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.put(Range.lessThan(3.0), 1L)
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.put(Range.closedOpen(3.0, 5.0), 0L)
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.put(Range.atLeast(5.0), 6L)
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.build());
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}
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@Test
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public void testAdd_negativeZero_throwsException() {
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thrown.expect(IllegalArgumentException.class);
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thrown.expectMessage("value must be finite, not NaN, and not -0.0");
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distribution.add(Double.longBitsToDouble(0x80000000));
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}
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@Test
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public void testAdd_NaN_throwsException() {
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thrown.expect(IllegalArgumentException.class);
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thrown.expectMessage("value must be finite, not NaN, and not -0.0");
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distribution.add(Double.NaN);
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}
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@Test
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public void testAdd_positiveInfinity_throwsException() {
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thrown.expect(IllegalArgumentException.class);
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thrown.expectMessage("value must be finite, not NaN, and not -0.0");
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distribution.add(Double.POSITIVE_INFINITY);
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}
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@Test
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public void testAdd_negativeInfinity_throwsException() {
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thrown.expect(IllegalArgumentException.class);
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thrown.expectMessage("value must be finite, not NaN, and not -0.0");
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distribution.add(Double.NEGATIVE_INFINITY);
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}
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@Test
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public void testAdd_iteratedFloatingPointValues_hasLowAccumulatedError() {
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for (int i = 0; i < 500; i++) {
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distribution.add(1 / 3.0);
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distribution.add(1 / 7.0);
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}
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// Test for nine significant figures of accuracy.
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assertThat(distribution.mean()).isWithin(0.000000001).of(5.0 / 21.0);
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assertThat(distribution.sumOfSquaredDeviation())
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.isWithin(0.000000001)
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.of(1000 * 4.0 / (21.0 * 21.0));
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}
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@Test
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public void testAdd_fitterWithNoFiniteIntervals_underflowValue_returnsUnderflowInterval()
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throws Exception {
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MutableDistribution distribution =
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new MutableDistribution(CustomFitter.create(ImmutableSet.of(5.0)));
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distribution.add(3.0);
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assertThat(distribution.intervalCounts())
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.isEqualTo(
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ImmutableRangeMap.<Double, Long>builder()
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.put(Range.lessThan(5.0), 1L)
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.put(Range.atLeast(5.0), 0L)
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.build());
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}
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@Test
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public void testAdd_noFiniteIntervals_overflowValue_returnsOverflowInterval() throws Exception {
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MutableDistribution distribution =
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new MutableDistribution(CustomFitter.create(ImmutableSet.of(5.0)));
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distribution.add(10.0);
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assertThat(distribution.intervalCounts())
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.isEqualTo(
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ImmutableRangeMap.<Double, Long>builder()
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.put(Range.lessThan(5.0), 0L)
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.put(Range.atLeast(5.0), 1L)
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.build());
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}
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@Test
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public void testAdd_noFiniteIntervals_edgeValue_returnsOverflowInterval() throws Exception {
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MutableDistribution distribution =
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new MutableDistribution(CustomFitter.create(ImmutableSet.of(2.0)));
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distribution.add(2.0);
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assertThat(distribution.intervalCounts())
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.isEqualTo(
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ImmutableRangeMap.<Double, Long>builder()
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.put(Range.lessThan(2.0), 0L)
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.put(Range.atLeast(2.0), 1L)
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.build());
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}
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@Test
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public void testAdd_oneFiniteInterval_underflowValue_returnsUnderflowInterval() throws Exception {
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MutableDistribution distribution =
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new MutableDistribution(CustomFitter.create(ImmutableSet.of(1.0, 5.0)));
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distribution.add(0.0);
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assertThat(distribution.intervalCounts())
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.isEqualTo(
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ImmutableRangeMap.<Double, Long>builder()
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.put(Range.lessThan(1.0), 1L)
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.put(Range.closedOpen(1.0, 5.0), 0L)
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.put(Range.atLeast(5.0), 0L)
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.build());
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}
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@Test
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public void testAdd_oneFiniteInterval_overflowValue_returnsOverflowInterval() throws Exception {
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MutableDistribution distribution =
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new MutableDistribution(CustomFitter.create(ImmutableSet.of(1.0, 5.0)));
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distribution.add(10.0);
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assertThat(distribution.intervalCounts())
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.isEqualTo(
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ImmutableRangeMap.<Double, Long>builder()
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.put(Range.lessThan(1.0), 0L)
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.put(Range.closedOpen(1.0, 5.0), 0L)
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.put(Range.atLeast(5.0), 1L)
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.build());
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}
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@Test
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public void testAdd_oneFiniteInterval_inBoundsValue_returnsInBoundsInterval() throws Exception {
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MutableDistribution distribution =
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new MutableDistribution(CustomFitter.create(ImmutableSet.of(1.0, 5.0)));
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distribution.add(3.0);
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assertThat(distribution.intervalCounts())
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.isEqualTo(
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ImmutableRangeMap.<Double, Long>builder()
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.put(Range.lessThan(1.0), 0L)
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.put(Range.closedOpen(1.0, 5.0), 1L)
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.put(Range.atLeast(5.0), 0L)
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.build());
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}
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@Test
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public void testAdd_oneFiniteInterval_firstEdgeValue_returnsFiniteInterval() throws Exception {
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MutableDistribution distribution =
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new MutableDistribution(CustomFitter.create(ImmutableSet.of(1.0, 5.0)));
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distribution.add(1.0);
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assertThat(distribution.intervalCounts())
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.isEqualTo(
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ImmutableRangeMap.<Double, Long>builder()
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.put(Range.lessThan(1.0), 0L)
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.put(Range.closedOpen(1.0, 5.0), 1L)
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.put(Range.atLeast(5.0), 0L)
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.build());
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}
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@Test
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public void testAdd_oneFiniteInterval_secondEdgeValue_returnsOverflowInterval() throws Exception {
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MutableDistribution distribution =
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new MutableDistribution(CustomFitter.create(ImmutableSet.of(1.0, 5.0)));
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distribution.add(5.0);
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assertThat(distribution.intervalCounts())
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.isEqualTo(
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ImmutableRangeMap.<Double, Long>builder()
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.put(Range.lessThan(1.0), 0L)
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.put(Range.closedOpen(1.0, 5.0), 0L)
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.put(Range.atLeast(5.0), 1L)
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.build());
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}
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}
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