001/** 002 * Licensed to the Apache Software Foundation (ASF) under one 003 * or more contributor license agreements. See the NOTICE file 004 * distributed with this work for additional information 005 * regarding copyright ownership. The ASF licenses this file 006 * to you under the Apache License, Version 2.0 (the 007 * "License"); you may not use this file except in compliance 008 * with the License. You may obtain a copy of the License at 009 * 010 * http://www.apache.org/licenses/LICENSE-2.0 011 * 012 * Unless required by applicable law or agreed to in writing, software 013 * distributed under the License is distributed on an "AS IS" BASIS, 014 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 015 * See the License for the specific language governing permissions and 016 * limitations under the License. 017 */ 018package org.apache.hadoop.hbase.metrics.impl; 019 020import static org.junit.Assert.assertEquals; 021 022import java.util.Arrays; 023import java.util.Random; 024import org.apache.hadoop.hbase.HBaseClassTestRule; 025import org.apache.hadoop.hbase.testclassification.MiscTests; 026import org.apache.hadoop.hbase.testclassification.SmallTests; 027import org.junit.Assert; 028import org.junit.ClassRule; 029import org.junit.Test; 030import org.junit.experimental.categories.Category; 031 032/** 033 * Testcases for FastLongHistogram. 034 */ 035@Category({MiscTests.class, SmallTests.class}) 036public class TestFastLongHistogram { 037 038 @ClassRule 039 public static final HBaseClassTestRule CLASS_RULE = 040 HBaseClassTestRule.forClass(TestFastLongHistogram.class); 041 042 private static void doTestUniform(FastLongHistogram hist) { 043 long[] VALUES = { 0, 10, 20, 30, 40, 50 }; 044 double[] qs = new double[VALUES.length]; 045 for (int i = 0; i < qs.length; i++) { 046 qs[i] = (double) VALUES[i] / VALUES[VALUES.length - 1]; 047 } 048 049 for (int i = 0; i < 10; i++) { 050 for (long v : VALUES) { 051 hist.add(v, 1); 052 } 053 long[] vals = hist.getQuantiles(qs); 054 System.out.println(Arrays.toString(vals)); 055 for (int j = 0; j < qs.length; j++) { 056 Assert.assertTrue(j + "-th element org: " + VALUES[j] + ", act: " + vals[j], 057 Math.abs(vals[j] - VALUES[j]) <= 10); 058 } 059 hist.snapshotAndReset(); 060 } 061 } 062 063 @Test 064 public void testUniform() { 065 FastLongHistogram hist = new FastLongHistogram(100, 0, 50); 066 doTestUniform(hist); 067 } 068 069 @Test 070 public void testAdaptionOfChange() { 071 // assumes the uniform distribution 072 FastLongHistogram hist = new FastLongHistogram(100, 0, 100); 073 074 Random rand = new Random(); 075 076 for (int n = 0; n < 10; n++) { 077 for (int i = 0; i < 900; i++) { 078 hist.add(rand.nextInt(100), 1); 079 } 080 081 // add 10% outliers, this breaks the assumption, hope bin10xMax works 082 for (int i = 0; i < 100; i++) { 083 hist.add(1000 + rand.nextInt(100), 1); 084 } 085 086 long[] vals = hist.getQuantiles(new double[] { 0.25, 0.75, 0.95 }); 087 System.out.println(Arrays.toString(vals)); 088 if (n == 0) { 089 Assert.assertTrue("Out of possible value", vals[0] >= 0 && vals[0] <= 50); 090 Assert.assertTrue("Out of possible value", vals[1] >= 50 && vals[1] <= 100); 091 Assert.assertTrue("Out of possible value", vals[2] >= 900 && vals[2] <= 1100); 092 } 093 094 hist.snapshotAndReset(); 095 } 096 } 097 098 099 @Test 100 public void testGetNumAtOrBelow() { 101 long[] VALUES = { 1, 10, 20, 30, 40, 50 }; 102 103 FastLongHistogram h = new FastLongHistogram(); 104 for (long v : VALUES) { 105 for (int i = 0; i < 100; i++) { 106 h.add(v, 1); 107 } 108 } 109 110 h.add(Integer.MAX_VALUE, 1); 111 112 h.snapshotAndReset(); 113 114 for (long v : VALUES) { 115 for (int i = 0; i < 100; i++) { 116 h.add(v, 1); 117 } 118 } 119 // Add something way out there to make sure it doesn't throw off the counts. 120 h.add(Integer.MAX_VALUE, 1); 121 122 assertEquals(100, h.getNumAtOrBelow(1)); 123 assertEquals(200, h.getNumAtOrBelow(11)); 124 assertEquals(601, h.getNumAtOrBelow(Long.MAX_VALUE)); 125 } 126 127 128 @Test 129 public void testSameValues() { 130 FastLongHistogram hist = new FastLongHistogram(100); 131 132 hist.add(50, 100); 133 134 hist.snapshotAndReset(); 135 doTestUniform(hist); 136 } 137}