blob: 5c5f0368c04cfec7e36ed16094c13ab411835aa3 [file] [log] [blame]
/**
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you 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 org.apache.hadoop.metrics2.util;
import static org.junit.Assert.*;
import java.io.IOException;
import java.util.Arrays;
import java.util.Collections;
import java.util.Map;
import java.util.Random;
import org.junit.Before;
import org.junit.Test;
public class TestSampleQuantiles {
static final Quantile[] quantiles = { new Quantile(0.50, 0.050),
new Quantile(0.75, 0.025), new Quantile(0.90, 0.010),
new Quantile(0.95, 0.005), new Quantile(0.99, 0.001) };
SampleQuantiles estimator;
@Before
public void init() {
estimator = new SampleQuantiles(quantiles);
}
/**
* Check that the counts of the number of items in the window and sample are
* incremented correctly as items are added.
*/
@Test
public void testCount() throws IOException {
// Counts start off zero
assertEquals(estimator.getCount(), 0);
assertEquals(estimator.getSampleCount(), 0);
// Snapshot should be null if there are no entries.
assertNull(estimator.snapshot());
// Count increment correctly by 1
estimator.insert(1337);
assertEquals(estimator.getCount(), 1);
estimator.snapshot();
assertEquals(estimator.getSampleCount(), 1);
assertEquals(
"50.00 %ile +/- 5.00%: 1337\n" +
"75.00 %ile +/- 2.50%: 1337\n" +
"90.00 %ile +/- 1.00%: 1337\n" +
"95.00 %ile +/- 0.50%: 1337\n" +
"99.00 %ile +/- 0.10%: 1337", estimator.toString());
}
/**
* Check that counts and quantile estimates are correctly reset after a call
* to {@link SampleQuantiles#clear()}.
*/
@Test
public void testClear() throws IOException {
for (int i = 0; i < 1000; i++) {
estimator.insert(i);
}
estimator.clear();
assertEquals(estimator.getCount(), 0);
assertEquals(estimator.getSampleCount(), 0);
assertNull(estimator.snapshot());
}
/**
* Correctness test that checks that absolute error of the estimate is within
* specified error bounds for some randomly permuted streams of items.
*/
@Test
public void testQuantileError() throws IOException {
final int count = 100000;
Random r = new Random(0xDEADDEAD);
Long[] values = new Long[count];
for (int i = 0; i < count; i++) {
values[i] = (long) (i + 1);
}
// Do 10 shuffle/insert/check cycles
for (int i = 0; i < 10; i++) {
System.out.println("Starting run " + i);
Collections.shuffle(Arrays.asList(values), r);
estimator.clear();
for (int j = 0; j < count; j++) {
estimator.insert(values[j]);
}
Map<Quantile, Long> snapshot;
snapshot = estimator.snapshot();
for (Quantile q : quantiles) {
long actual = (long) (q.quantile * count);
long error = (long) (q.error * count);
long estimate = snapshot.get(q);
System.out
.println(String.format("Expected %d with error %d, estimated %d",
actual, error, estimate));
assertTrue(estimate <= actual + error);
assertTrue(estimate >= actual - error);
}
}
}
}