[英]WordCount MapReduce is giving unexpected result
我正在mapreduce中尝试此Java代码进行wordcount操作,在reduce方法完成后,我想显示出现次数最多的唯一单词。
为此,我创建了一些名为myoutput,mykey和completeSum的类级别变量。
我正在用close方法写入此数据,但最后得到了意外结果。
public class WordCount {
public static class Map extends MapReduceBase implements
Mapper<LongWritable, Text, Text, IntWritable> {
private final static IntWritable one = new IntWritable(1);
private Text word = new Text();
public void map(LongWritable key, Text value,
OutputCollector<Text, IntWritable> output, Reporter reporter)
throws IOException {
String line = value.toString();
StringTokenizer tokenizer = new StringTokenizer(line);
while (tokenizer.hasMoreTokens()) {
word.set(tokenizer.nextToken());
output.collect(word, one);
}
}
}
static int completeSum = -1;
static OutputCollector<Text, IntWritable> myoutput;
static Text mykey = new Text();
public static class Reduce extends MapReduceBase implements
Reducer<Text, IntWritable, Text, IntWritable> {
public void reduce(Text key, Iterator<IntWritable> values,
OutputCollector<Text, IntWritable> output, Reporter reporter)
throws IOException {
int sum = 0;
while (values.hasNext()) {
sum += values.next().get();
}
if (completeSum < sum) {
completeSum = sum;
myoutput = output;
mykey = key;
}
}
@Override
public void close() throws IOException {
// TODO Auto-generated method stub
super.close();
myoutput.collect(mykey, new IntWritable(completeSum));
}
}
public static void main(String[] args) throws Exception {
JobConf conf = new JobConf(WordCount.class);
conf.setJobName("wordcount");
conf.setOutputKeyClass(Text.class);
conf.setOutputValueClass(IntWritable.class);
conf.setMapperClass(Map.class);
// conf.setCombinerClass(Reduce.class);
conf.setReducerClass(Reduce.class);
conf.setInputFormat(TextInputFormat.class);
conf.setOutputFormat(TextOutputFormat.class);
FileInputFormat.setInputPaths(conf, new Path(args[0]));
FileOutputFormat.setOutputPath(conf, new Path(args[1]));
JobClient.runJob(conf);
}
}
one
three three three
four four four four
six six six six six six six six six six six six six six six six six six
five five five five five
seven seven seven seven seven seven seven seven seven seven seven seven seven
six 18
three 18
通过结果,我可以看到总和是正确的,但关键不是。
您正在观察的问题是由于引用别名引起的。 key
引用的对象将与新内容一起重用于多次调用,从而更改了引用同一对象的mykey
。 它以最后一个减小的键结束。 可以通过复制对象来避免这种情况,如下所示:
mykey = new Text(key);
但是,您应该仅从输出文件中获得结果,因为static
变量不能由分布式集群中的其他节点共享。 它只能在独立模式下工作,无法达到map-reduce的目的。
最后,即使使用独立模式,使用全局变量(即使在独立模式下)也会在使用并行本地任务时导致竞赛(请参阅MAPREDUCE-1367和MAPREDUCE-434 )。
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