Java tutorial
/* * 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.kylin.measure.percentile; import static org.junit.Assert.assertEquals; import java.io.ByteArrayInputStream; import java.io.ByteArrayOutputStream; import java.io.IOException; import java.io.InputStream; import java.io.ObjectInputStream; import java.io.ObjectOutputStream; import java.util.Collections; import java.util.List; import java.util.Random; import org.apache.commons.io.IOUtils; import org.apache.kylin.common.util.MathUtil; import org.junit.Assert; import org.junit.Test; import com.google.common.collect.Lists; import com.tdunning.math.stats.TDigest; public class PercentileCounterTest { @Test public void testBasic() { int times = 1; int compression = 100; for (int t = 0; t < times; t++) { PercentileCounter counter = new PercentileCounter(compression, 0.5); Random random = new Random(); int dataSize = 10000; List<Double> dataset = Lists.newArrayListWithCapacity(dataSize); for (int i = 0; i < dataSize; i++) { double d = random.nextDouble(); counter.add(d); dataset.add(d); } Collections.sort(dataset); double actualResult = counter.getResultEstimate(); double expectedResult = MathUtil.findMedianInSortedList(dataset); assertEquals(expectedResult, actualResult, 0.001); } } @Test public void testTDigest() { double compression = 100; double quantile = 0.5; PercentileCounter counter = new PercentileCounter(compression, quantile); TDigest tDigest = TDigest.createAvlTreeDigest(compression); Random random = new Random(); int dataSize = 10000; List<Double> dataset = Lists.newArrayListWithCapacity(dataSize); for (int i = 0; i < dataSize; i++) { double d = random.nextDouble(); counter.add(d); tDigest.add(d); } double actualResult = counter.getResultEstimate(); Collections.sort(dataset); double expectedResult = tDigest.quantile(quantile); assertEquals(expectedResult, actualResult, 0); } @Test public void testSerialization() { double compression = 100; double quantile = 0.5; ByteArrayOutputStream os = new ByteArrayOutputStream(1024); ObjectOutputStream out = null; PercentileCounter origin_counter = null; try { out = new ObjectOutputStream(os); origin_counter = new PercentileCounter(compression, quantile); out.writeObject(origin_counter); } catch (IOException e) { e.printStackTrace(); } finally { IOUtils.closeQuietly(out); } InputStream is = new ByteArrayInputStream(os.toByteArray()); PercentileCounter serialized_counter = null; ObjectInputStream in = null; try { in = new ObjectInputStream(is); serialized_counter = (PercentileCounter) in.readObject(); Assert.assertNotNull(serialized_counter); Assert.assertNotNull(serialized_counter.registers); } catch (IOException e) { e.printStackTrace(); } catch (ClassNotFoundException e) { e.printStackTrace(); } finally { IOUtils.closeQuietly(os); IOUtils.closeQuietly(is); } } }