hdfs词频统计idea
时间: 2023-11-17 18:04:20 浏览: 115
大型文件中词频的统计
以下是在IDEA中进行HDFS词频统计的步骤:
1.创建一个Maven项目,添加Hadoop依赖项。
2.在HDFS上创建一个输入目录,并将要处理的文本文件上传到该目录中。
3.创建一个Java类,用于实现MapReduce作业。在该类中,实现Mapper和Reducer类,并在main()方法中配置和运行MapReduce作业。
4.在Mapper类中,实现map()方法,将每个单词作为键,将其出现的次数作为值进行输出。
5.在Reducer类中,实现reduce()方法,将每个单词的出现次数进行累加,并将结果输出。
6.在main()方法中,配置和运行MapReduce作业。设置输入和输出路径,以及Mapper和Reducer类。
7.运行程序,等待作业完成后,在HDFS上查看输出结果。
8.如果需要在Map阶段进行词频统计,可以自定义实现Combine阶段的类InvertedIndexCombiner,对每个文档的单词进行词频统计。
代码示例:
```java
// Mapper类
public static class WordCountMapper extends 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, Context context) throws IOException, InterruptedException {
String line = value.toString();
StringTokenizer tokenizer = new StringTokenizer(line);
while (tokenizer.hasMoreTokens()) {
word.set(tokenizer.nextToken());
context.write(word, one);
}
}
}
// Reducer类
public static class WordCountReducer extends Reducer<Text, IntWritable, Text, IntWritable> {
private IntWritable result = new IntWritable();
public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
int sum = 0;
for (IntWritable val : values) {
sum += val.get();
}
result.set(sum);
context.write(key, result);
}
}
// main()方法
public static void main(String[] args) throws Exception {
Configuration conf = new Configuration();
Job job = Job.getInstance(conf, "word count");
job.setJarByClass(WordCount.class);
job.setMapperClass(WordCountMapper.class);
job.setCombinerClass(WordCountReducer.class);
job.setReducerClass(WordCountReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
FileInputFormat.addInputPath(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
System.exit(job.waitForCompletion(true) ? 0 : 1);
}
```
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