Github user tweise commented on a diff in the pull request:
https://github.com/apache/apex-malhar/pull/301#discussion_r67933939
--- Diff:
sketches/src/test/java/org/apache/apex/malhar/sketches/QuantilesEstimatorTest.java
---
@@ -0,0 +1,172 @@
+/**
+ * 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.apex.malhar.sketches;
+
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.List;
+import java.util.Random;
+
+import javax.validation.ConstraintViolationException;
+
+import org.junit.Assert;
+import org.junit.Test;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import org.apache.hadoop.conf.Configuration;
+
+import com.datatorrent.api.DAG;
+import com.datatorrent.api.DefaultOutputPort;
+import com.datatorrent.api.InputOperator;
+import com.datatorrent.api.LocalMode;
+import com.datatorrent.api.StreamingApplication;
+import com.datatorrent.common.util.BaseOperator;
+import com.datatorrent.lib.io.ConsoleOutputOperator;
+import com.datatorrent.lib.testbench.CollectorTestSink;
+import com.datatorrent.lib.util.TestUtils;
+
+public class QuantilesEstimatorTest
+{
+ private static Logger LOG =
LoggerFactory.getLogger(QuantilesEstimatorTest.class);
+
+ public static class NumberSource extends BaseOperator implements
InputOperator
+ {
+ public final DefaultOutputPort<Double> output = new
DefaultOutputPort<>();
+
+ private Random rand = new Random(1234L);
+
+ public NumberSource() {}
+
+ @Override
+ public void emitTuples()
+ {
+ output.emit(rand.nextGaussian());
+ }
+ }
+
+ @Test
+ public void testQuantiles()
+ {
+ QuantilesEstimator quantilesOp = new QuantilesEstimator(128,
(short)12345);
+
+ CollectorTestSink<double[]> sink = new CollectorTestSink<>();
+ TestUtils.setSink(quantilesOp.quantilesOutput, sink);
+
+ Random rand = new Random(1234L);
+ ArrayList<Double> randArray = new ArrayList<>();
+
+ quantilesOp.setup(null);
+ quantilesOp.beginWindow(0);
+
+ for (int i = 0; i < 101; i++) {
+ double r = rand.nextGaussian();
+ quantilesOp.data.process(r);
+ randArray.add(r);
+ }
+
+ quantilesOp.endWindow();
+
+ Collections.sort(randArray);
+
+ Assert.assertEquals("Captures all computed quantiles",
sink.collectedTuples.size(), 101);
+ Assert.assertTrue("Computes median correctly", randArray.get(50) ==
sink.collectedTuples.get(100)[2]);
+ }
+
+ @Test
+ public void testCDF()
+ {
+ QuantilesEstimator quantilesOp = new QuantilesEstimator(128,
(short)12345);
+
+ CollectorTestSink<Double> sink = new CollectorTestSink<>();
+ TestUtils.setSink(quantilesOp.cdfOutput, sink);
+
+ quantilesOp.setup(null);
+ quantilesOp.beginWindow(0);
+
+ for (int i = 0; i < 1001; i++) {
+ double r = 0.001 * i;
+ quantilesOp.data.process(r);
+ }
+ quantilesOp.endWindow();
+
+ List<Double> cdfValues = sink.collectedTuples;
+ Assert.assertTrue("Highest CDF value is approx 1.0",
cdfValues.get(cdfValues.size() - 1) >= 0.99 &&
+ cdfValues.get(cdfValues.size() - 1) <= 1.0);
+ Assert.assertTrue("Lowest CDF value is approx 0.0", cdfValues.get(0)
>= 0.0 &&
+ cdfValues.get(0) <= 0.01);
+ }
+
+ @Test
+ public void testPMF()
+ {
+ QuantilesEstimator quantilesOp = new QuantilesEstimator(128,
(short)12345);
+ double[] intervals = {0.0, 0.20, 0.40, 0.60, 0.80, 1.0};
+ quantilesOp.setPmfIntervals(intervals);
+
+ CollectorTestSink<double[]> sink = new CollectorTestSink<>();
+ TestUtils.setSink(quantilesOp.pmfOutput, sink);
+
+ quantilesOp.setup(null);
+ quantilesOp.beginWindow(0);
+ for (int i = 0; i < 1000; i++) {
+ quantilesOp.data.process(0.001 * i);
+ }
+ quantilesOp.endWindow();
+
+ double[] finalPmf =
sink.collectedTuples.get(sink.collectedTuples.size() - 1);
+ Assert.assertTrue("Probability Mass between 0.0 and 0.2 is approx
0.2", finalPmf[1] >= 0.19 && finalPmf[1] <= 0.21);
+ }
+
+ public static class Application implements StreamingApplication
+ {
+ public void populateDAG(DAG dag, Configuration conf)
+ {
+ NumberSource source = dag.addOperator("source", NumberSource.class);
+ QuantilesEstimator quantilesOp =
dag.addOperator("quantilesEstimator", QuantilesEstimator.class);
+ ConsoleOutputOperator cdfConsole = dag.addOperator("cdf output",
ConsoleOutputOperator.class);
+ ConsoleOutputOperator quantilesConsole = dag.addOperator("quantiles
output", ConsoleOutputOperator.class);
+ ConsoleOutputOperator pmfConsole = dag.addOperator("pmf output",
ConsoleOutputOperator.class);
+ cdfConsole.setSilent(true);
+ quantilesConsole.setSilent(true);
+ pmfConsole.setSilent(true);
+
+ dag.addStream("random number stream", source.output,
quantilesOp.data);
+ dag.addStream("cdf", quantilesOp.cdfOutput, cdfConsole.input);
+ dag.addStream("quantiles", quantilesOp.quantilesOutput,
quantilesConsole.input);
+ dag.addStream("pmf", quantilesOp.pmfOutput, pmfConsole.input);
+ }
+ }
+
+ @Test
+ public void testInDAG() throws Exception
+ {
+ try {
+ LocalMode lma = LocalMode.newInstance();
+ Configuration conf = new Configuration(false);
+ lma.prepareDAG(new Application(), conf);
+ LocalMode.Controller lc = lma.getController();
+
+ lc.run(2500); // runs for 2.5 seconds and quits
--- End diff --
Instead of this, it is better to wait for the expected result with a
timeout.
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