google-nomulus/java/google/registry/monitoring/metrics/contrib/DistributionMetricSubject.java
jianglai 4a5b9fc288 Add a convenient method to DistributionMetricSubject
Currently to assert that a given Metric<Distribution> as a certain distribution for some labels, the caller needs to manually create an ImmutableDistribution and pass it to #hasValueForLabels method. With this change, an ImmutableSet of data points can be passed to #hasDataSetForLabels method.

Also switched to use expectThrow backport from JUnit 4.13.

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Created by MOE: https://github.com/google/moe
MOE_MIGRATED_REVID=173544521
2017-11-07 17:17:14 -05:00

125 lines
5.2 KiB
Java

// Copyright 2017 The Nomulus Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package google.registry.monitoring.metrics.contrib;
import static com.google.common.truth.Truth.assertAbout;
import com.google.common.base.Joiner;
import com.google.common.collect.BoundType;
import com.google.common.collect.ImmutableList;
import com.google.common.collect.ImmutableSet;
import com.google.common.collect.Range;
import com.google.common.truth.FailureMetadata;
import google.registry.monitoring.metrics.Distribution;
import google.registry.monitoring.metrics.ImmutableDistribution;
import google.registry.monitoring.metrics.Metric;
import google.registry.monitoring.metrics.MetricPoint;
import google.registry.monitoring.metrics.MutableDistribution;
import java.util.Map;
import javax.annotation.Nullable;
/**
* Truth subject for the {@link Metric<Distribution>} class.
*
* <p>For use with the Google <a href="https://google.github.io/truth/">Truth</a> framework. Usage:
*
* <pre> assertThat(myDistributionMetric)
* .hasAnyValueForLabels("label1", "label2", "label3")
* .and()
* .hasNoOtherValues();
* assertThat(myDistributionMetric)
* .doesNotHaveAnyValueForLabels("label1", "label2");
* assertThat(myDistributionMetric)
* .hasDataSetForLabels(ImmutableSet.of(data1, data2, data3), "label1", "label2");
* </pre>
*
* <p>The assertions treat an empty distribution as no value at all. This is not how the data is
* actually stored; event metrics do in fact have an empty distribution after they are reset. But
* it's difficult to write assertions about expected metric data when any number of empty
* distributions can also be present, so they are screened out for convenience.
*/
public final class DistributionMetricSubject
extends AbstractMetricSubject<Distribution, DistributionMetricSubject> {
/** {@link Subject.Factory} for assertions about {@link Metric<Distribution>} objects. */
/** Static assertThat({@link Metric<Distribution>}) shortcut method. */
public static DistributionMetricSubject assertThat(@Nullable Metric<Distribution> metric) {
return assertAbout(DistributionMetricSubject::new).that(metric);
}
private DistributionMetricSubject(FailureMetadata metadata, Metric<Distribution> actual) {
super(metadata, actual);
}
/**
* Returns an indication to {@link AbstractMetricSubject#hasNoOtherValues} on whether a {@link
* MetricPoint} has a non-empty distribution.
*/
@Override
protected boolean hasDefaultValue(MetricPoint<Distribution> metricPoint) {
return metricPoint.value().count() == 0;
}
/** Returns an appropriate string representation of a metric value for use in error messages. */
@Override
protected String getMessageRepresentation(Distribution distribution) {
StringBuilder sb = new StringBuilder("{");
boolean first = true;
for (Map.Entry<Range<Double>, Long> entry :
distribution.intervalCounts().asMapOfRanges().entrySet()) {
if (entry.getValue() != 0L) {
if (first) {
first = false;
} else {
sb.append(',');
}
if (entry.getKey().hasLowerBound()) {
sb.append((entry.getKey().lowerBoundType() == BoundType.CLOSED) ? '[' : '(');
sb.append(entry.getKey().lowerEndpoint());
}
sb.append("..");
if (entry.getKey().hasUpperBound()) {
sb.append(entry.getKey().upperEndpoint());
sb.append((entry.getKey().upperBoundType() == BoundType.CLOSED) ? ']' : ')');
}
sb.append('=');
sb.append(entry.getValue());
}
}
sb.append('}');
return sb.toString();
}
/**
* Asserts that the distribution for the given label can be constructed from the given data set.
*
* <p>Note that this only tests that the distribution has the same binned histogram as it would if
* it had recorded the specified data points. It could have in fact collected different data
* points that resulted in the same histogram, but that information is lost to us and cannot be
* tested.
*/
public And<DistributionMetricSubject> hasDataSetForLabels(
ImmutableSet<? extends Number> dataSet, String... labels) {
ImmutableList<MetricPoint<Distribution>> metricPoints = actual().getTimestampedValues();
if (metricPoints.isEmpty()) {
failWithBadResults(
"has a distribution for labels", Joiner.on(':').join(labels), "has", "no values");
}
MutableDistribution targetDistribution =
new MutableDistribution(metricPoints.get(0).value().distributionFitter());
dataSet.forEach(data -> targetDistribution.add(data.doubleValue()));
return hasValueForLabels(ImmutableDistribution.copyOf(targetDistribution), labels);
}
}