| | 1 | = 將 wordcount2 改成 0.20 版 = |
| | 2 | |
| | 3 | == 前言 == |
| | 4 | 按照hadoop 0.20 官方網頁的 wordcount v2 . |
| | 5 | [[http://hadoop.apache.org/common/docs/r0.20.1/mapred_tutorial.html#Example%3A+WordCount+v1.0 ]] |
| | 6 | |
| | 7 | 最需要給的地方是 ''' " extends MapReduceBase implements Mapper" ''' 原因是在hadoop 0.20時,mapreducebase 此class已經被deprecated, |
| | 8 | |
| | 9 | 因此應改寫如 ''' " extends Mapper" ''' |
| | 10 | |
| | 11 | 然而最主要不能改變的原因是,程式中很重要的功能 [http://hadoop.apache.org/common/docs/r0.20.1/api/org/apache/hadoop/filecache/DistributedCache.html DistributedCache ] 以及 -Dwordcount.skip.patterns 等功能寫於 configure() 函數內。 此configure() 繼承自 MapReduceBase, |
| | 12 | |
| | 13 | 因此若整個程式改成hadoop 0.20 的 " extends Mapper" ''',則有些功能將不知是否能使用 |
| | 14 | |
| | 15 | |
| | 16 | == 原始程式碼 == |
| | 17 | |
| | 18 | {{{ |
| | 19 | #!java |
| | 20 | public class WordCountV2 extends Configured implements Tool { |
| | 21 | |
| | 22 | public static class Map extends MapReduceBase implements |
| | 23 | Mapper<LongWritable, Text, Text, IntWritable> { |
| | 24 | |
| | 25 | static enum Counters { |
| | 26 | INPUT_WORDS |
| | 27 | } |
| | 28 | |
| | 29 | private final static IntWritable one = new IntWritable(1); |
| | 30 | private Text word = new Text(); |
| | 31 | |
| | 32 | private boolean caseSensitive = true; |
| | 33 | private Set<String> patternsToSkip = new HashSet<String>(); |
| | 34 | |
| | 35 | private long numRecords = 0; |
| | 36 | private String inputFile; |
| | 37 | |
| | 38 | public void configure(JobConf job) { |
| | 39 | caseSensitive = job.getBoolean("wordcount.case.sensitive", true); |
| | 40 | inputFile = job.get("map.input.file"); |
| | 41 | |
| | 42 | if (job.getBoolean("wordcount.skip.patterns", false)) { |
| | 43 | Path[] patternsFiles = new Path[0]; |
| | 44 | try { |
| | 45 | patternsFiles = DistributedCache.getLocalCacheFiles(job); |
| | 46 | } catch (IOException ioe) { |
| | 47 | System.err |
| | 48 | .println("Caught exception while getting cached files: " |
| | 49 | + StringUtils.stringifyException(ioe)); |
| | 50 | } |
| | 51 | for (Path patternsFile : patternsFiles) { |
| | 52 | parseSkipFile(patternsFile); |
| | 53 | } |
| | 54 | } |
| | 55 | } |
| | 56 | |
| | 57 | private void parseSkipFile(Path patternsFile) { |
| | 58 | try { |
| | 59 | BufferedReader fis = new BufferedReader(new FileReader( |
| | 60 | patternsFile.toString())); |
| | 61 | String pattern = null; |
| | 62 | while ((pattern = fis.readLine()) != null) { |
| | 63 | patternsToSkip.add(pattern); |
| | 64 | } |
| | 65 | } catch (IOException ioe) { |
| | 66 | System.err |
| | 67 | .println("Caught exception while parsing the cached file '" |
| | 68 | + patternsFile |
| | 69 | + "' : " |
| | 70 | + StringUtils.stringifyException(ioe)); |
| | 71 | } |
| | 72 | } |
| | 73 | |
| | 74 | public void map(LongWritable key, Text value, |
| | 75 | OutputCollector<Text, IntWritable> output, Reporter reporter) |
| | 76 | throws IOException { |
| | 77 | String line = (caseSensitive) ? value.toString() : value.toString() |
| | 78 | .toLowerCase(); |
| | 79 | |
| | 80 | for (String pattern : patternsToSkip) { |
| | 81 | line = line.replaceAll(pattern, ""); |
| | 82 | } |
| | 83 | |
| | 84 | StringTokenizer tokenizer = new StringTokenizer(line); |
| | 85 | while (tokenizer.hasMoreTokens()) { |
| | 86 | word.set(tokenizer.nextToken()); |
| | 87 | output.collect(word, one); |
| | 88 | reporter.incrCounter(Counters.INPUT_WORDS, 1); |
| | 89 | } |
| | 90 | |
| | 91 | if ((++numRecords % 100) == 0) { |
| | 92 | reporter.setStatus("Finished processing " + numRecords |
| | 93 | + " records " + "from the input file: " + inputFile); |
| | 94 | } |
| | 95 | } |
| | 96 | } |
| | 97 | |
| | 98 | public static class Reduce extends MapReduceBase implements |
| | 99 | Reducer<Text, IntWritable, Text, IntWritable> { |
| | 100 | public void reduce(Text key, Iterator<IntWritable> values, |
| | 101 | OutputCollector<Text, IntWritable> output, Reporter reporter) |
| | 102 | throws IOException { |
| | 103 | int sum = 0; |
| | 104 | while (values.hasNext()) { |
| | 105 | sum += values.next().get(); |
| | 106 | } |
| | 107 | output.collect(key, new IntWritable(sum)); |
| | 108 | } |
| | 109 | } |
| | 110 | |
| | 111 | public int run(String[] args) throws Exception { |
| | 112 | |
| | 113 | |
| | 114 | JobConf conf = new JobConf(getConf(), WordCount.class); |
| | 115 | conf.setJobName("wordcount"); |
| | 116 | |
| | 117 | conf.setOutputKeyClass(Text.class); |
| | 118 | conf.setOutputValueClass(IntWritable.class); |
| | 119 | |
| | 120 | conf.setMapperClass(Map.class); |
| | 121 | conf.setCombinerClass(Reduce.class); |
| | 122 | conf.setReducerClass(Reduce.class); |
| | 123 | |
| | 124 | conf.setInputFormat(TextInputFormat.class); |
| | 125 | conf.setOutputFormat(TextOutputFormat.class); |
| | 126 | |
| | 127 | List<String> other_args = new ArrayList<String>(); |
| | 128 | for (int i = 0; i < args.length; ++i) { |
| | 129 | if ("-skip".equals(args[i])) { |
| | 130 | DistributedCache |
| | 131 | .addCacheFile(new Path(args[++i]).toUri(), conf); |
| | 132 | conf.setBoolean("wordcount.skip.patterns", true); |
| | 133 | } else { |
| | 134 | other_args.add(args[i]); |
| | 135 | } |
| | 136 | } |
| | 137 | |
| | 138 | FileInputFormat.setInputPaths(conf, new Path(other_args.get(0))); |
| | 139 | FileOutputFormat.setOutputPath(conf, new Path(other_args.get(1))); |
| | 140 | CheckAndDelete.checkAndDelete(other_args.get(1), conf); |
| | 141 | JobClient.runJob(conf); |
| | 142 | return 0; |
| | 143 | } |
| | 144 | |
| | 145 | public static void main(String[] args) throws Exception { |
| | 146 | String[] argv = { "-Dwordcount.case.sensitive=false", |
| | 147 | "/user/waue/input", "/user/waue/output-wc2", "-skip", |
| | 148 | "/user/waue/patterns/patterns.txt" }; |
| | 149 | args = argv; |
| | 150 | int res = ToolRunner.run(new Configuration(), new WordCountV2(), args); |
| | 151 | System.exit(res); |
| | 152 | } |
| | 153 | } |
| | 154 | }}} |
| | 155 | |
| | 156 | == 原始程式碼 == |