1 | /** |
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2 | * Licensed to the Apache Software Foundation (ASF) under one |
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3 | * or more contributor license agreements. See the NOTICE file |
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4 | * distributed with this work for additional information |
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5 | * regarding copyright ownership. The ASF licenses this file |
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6 | * to you under the Apache License, Version 2.0 (the |
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7 | * "License"); you may not use this file except in compliance |
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8 | * with the License. You may obtain a copy of the License at |
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9 | * |
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10 | * http://www.apache.org/licenses/LICENSE-2.0 |
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11 | * |
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12 | * Unless required by applicable law or agreed to in writing, software |
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13 | * distributed under the License is distributed on an "AS IS" BASIS, |
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14 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
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15 | * See the License for the specific language governing permissions and |
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16 | * limitations under the License. |
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17 | */ |
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18 | |
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19 | package org.apache.hadoop.mapred; |
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20 | |
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21 | import java.io.File; |
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22 | import java.io.FileWriter; |
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23 | import java.io.Writer; |
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24 | import java.io.BufferedWriter; |
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25 | import java.io.IOException; |
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26 | |
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27 | import junit.framework.TestCase; |
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28 | |
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29 | import org.apache.hadoop.conf.Configuration; |
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30 | import org.apache.hadoop.fs.FileSystem; |
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31 | import org.apache.hadoop.fs.Path; |
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32 | import org.apache.hadoop.io.IntWritable; |
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33 | import org.apache.hadoop.io.Text; |
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34 | |
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35 | /** |
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36 | * This is an wordcount application that tests the count of records |
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37 | * got spilled to disk. It generates simple text input files. Then |
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38 | * runs the wordcount map/reduce application on (1) 3 i/p files(with 3 maps |
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39 | * and 1 reduce) and verifies the counters and (2) 4 i/p files(with 4 maps |
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40 | * and 1 reduce) and verifies counters. Wordcount application reads the |
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41 | * text input files, breaks each line into words and counts them. The output |
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42 | * is a locally sorted list of words and the count of how often they occurred. |
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43 | * |
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44 | */ |
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45 | public class TestSpilledRecordsCounter extends TestCase { |
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46 | |
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47 | private void validateCounters(Counters counter, long spillRecCnt) { |
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48 | // Check if the numer of Spilled Records is same as expected |
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49 | assertEquals(counter.findCounter(Task.Counter.SPILLED_RECORDS). |
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50 | getCounter(), spillRecCnt); |
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51 | } |
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52 | |
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53 | private void createWordsFile(File inpFile) throws Exception { |
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54 | Writer out = new BufferedWriter(new FileWriter(inpFile)); |
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55 | try { |
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56 | // 500*4 unique words --- repeated 5 times => 5*2K words |
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57 | int REPLICAS=5, NUMLINES=500, NUMWORDSPERLINE=4; |
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58 | |
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59 | for (int i = 0; i < REPLICAS; i++) { |
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60 | for (int j = 1; j <= NUMLINES*NUMWORDSPERLINE; j+=NUMWORDSPERLINE) { |
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61 | out.write("word" + j + " word" + (j+1) + " word" + (j+2) + " word" + (j+3) + '\n'); |
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62 | } |
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63 | } |
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64 | } finally { |
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65 | out.close(); |
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66 | } |
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67 | } |
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68 | |
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69 | |
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70 | /** |
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71 | * The main driver for word count map/reduce program. |
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72 | * Invoke this method to submit the map/reduce job. |
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73 | * @throws IOException When there is communication problems with the |
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74 | * job tracker. |
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75 | */ |
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76 | public void testSpillCounter() throws Exception { |
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77 | JobConf conf = new JobConf(TestSpilledRecordsCounter.class); |
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78 | conf.setJobName("wordcountSpilledRecordsCounter"); |
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79 | |
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80 | // the keys are words (strings) |
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81 | conf.setOutputKeyClass(Text.class); |
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82 | // the values are counts (ints) |
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83 | conf.setOutputValueClass(IntWritable.class); |
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84 | |
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85 | conf.setMapperClass(WordCount.MapClass.class); |
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86 | conf.setCombinerClass(WordCount.Reduce.class); |
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87 | conf.setReducerClass(WordCount.Reduce.class); |
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88 | |
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89 | conf.setNumMapTasks(3); |
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90 | conf.setNumReduceTasks(1); |
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91 | conf.setInt("io.sort.mb", 1); |
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92 | conf.setInt("io.sort.factor", 2); |
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93 | conf.set("io.sort.record.percent", "0.05"); |
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94 | conf.set("io.sort.spill.percent", "0.80"); |
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95 | |
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96 | |
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97 | String TEST_ROOT_DIR = new Path(System.getProperty("test.build.data", |
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98 | File.separator + "tmp")) |
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99 | .toString().replace(' ', '+'); |
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100 | conf.set("test.build.data", TEST_ROOT_DIR); |
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101 | String IN_DIR = TEST_ROOT_DIR + File.separator + |
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102 | "spilledRecords.countertest" + File.separator + |
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103 | "genins" + File.separator; |
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104 | String OUT_DIR = TEST_ROOT_DIR + File.separator + |
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105 | "spilledRecords.countertest" + File.separator; |
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106 | |
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107 | FileSystem fs = FileSystem.get(conf); |
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108 | Path testdir = new Path(TEST_ROOT_DIR, "spilledRecords.countertest"); |
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109 | try { |
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110 | if (fs.exists(testdir)) { |
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111 | fs.delete(testdir, true); |
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112 | } |
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113 | if (!fs.mkdirs(testdir)) { |
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114 | throw new IOException("Mkdirs failed to create " + testdir.toString()); |
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115 | } |
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116 | |
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117 | Path wordsIns = new Path(testdir, "genins"); |
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118 | if (!fs.mkdirs(wordsIns)) { |
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119 | throw new IOException("Mkdirs failed to create " + wordsIns.toString()); |
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120 | } |
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121 | |
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122 | //create 3 input files each with 5*2k words |
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123 | File inpFile = new File(IN_DIR + "input5_2k_1"); |
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124 | createWordsFile(inpFile); |
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125 | inpFile = new File(IN_DIR + "input5_2k_2"); |
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126 | createWordsFile(inpFile); |
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127 | inpFile = new File(IN_DIR + "input5_2k_3"); |
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128 | createWordsFile(inpFile); |
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129 | |
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130 | FileInputFormat.setInputPaths(conf, IN_DIR); |
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131 | Path outputPath1=new Path(OUT_DIR, "output5_2k_3"); |
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132 | FileOutputFormat.setOutputPath(conf, outputPath1); |
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133 | |
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134 | RunningJob myJob = JobClient.runJob(conf); |
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135 | Counters c1 = myJob.getCounters(); |
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136 | // 3maps & in each map, 4 first level spills --- So total 12. |
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137 | // spilled records count: |
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138 | // Each Map: 1st level:2k+2k+2k+2k=8k;2ndlevel=4k+4k=8k; |
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139 | // 3rd level=2k(4k from 1st level & 4k from 2nd level & combineAndSpill) |
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140 | // So total 8k+8k+2k=18k |
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141 | // For 3 Maps, total = 3*18=54k |
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142 | // Reduce: each of the 3 map o/p's(2k each) will be spilled in shuffleToDisk() |
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143 | // So 3*2k=6k in 1st level; 2nd level:4k(2k+2k); |
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144 | // 3rd level directly given to reduce(4k+2k --- combineAndSpill => 2k. |
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145 | // So 0 records spilled to disk in 3rd level) |
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146 | // So total of 6k+4k=10k |
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147 | // Total job counter will be 54k+10k = 64k |
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148 | validateCounters(c1, 64000); |
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149 | |
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150 | //create 4th input file each with 5*2k words and test with 4 maps |
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151 | inpFile = new File(IN_DIR + "input5_2k_4"); |
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152 | createWordsFile(inpFile); |
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153 | conf.setNumMapTasks(4); |
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154 | Path outputPath2=new Path(OUT_DIR, "output5_2k_4"); |
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155 | FileOutputFormat.setOutputPath(conf, outputPath2); |
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156 | |
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157 | myJob = JobClient.runJob(conf); |
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158 | c1 = myJob.getCounters(); |
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159 | // 4maps & in each map 4 first level spills --- So total 16. |
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160 | // spilled records count: |
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161 | // Each Map: 1st level:2k+2k+2k+2k=8k;2ndlevel=4k+4k=8k; |
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162 | // 3rd level=2k(4k from 1st level & 4k from 2nd level & combineAndSpill) |
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163 | // So total 8k+8k+2k=18k |
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164 | // For 3 Maps, total = 4*18=72k |
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165 | // Reduce: each of the 4 map o/p's(2k each) will be spilled in shuffleToDisk() |
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166 | // So 4*2k=8k in 1st level; 2nd level:4k+4k=8k; |
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167 | // 3rd level directly given to reduce(4k+4k --- combineAndSpill => 2k. |
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168 | // So 0 records spilled to disk in 3rd level) |
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169 | // So total of 8k+8k=16k |
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170 | // Total job counter will be 72k+16k = 88k |
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171 | validateCounters(c1, 88000); |
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172 | } finally { |
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173 | //clean up the input and output files |
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174 | if (fs.exists(testdir)) { |
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175 | fs.delete(testdir, true); |
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176 | } |
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177 | } |
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178 | } |
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179 | } |
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