如何用Hadoop计算平均值
数据
data.txt
a 2
a 3
a 4
b 5
b 6
b 7
代码
import java.io.IOException; import java.util.StringTokenizer; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.fs.Path; import org.apache.hadoop.io.DoubleWritable; import org.apache.hadoop.io.IntWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.Job; import org.apache.hadoop.mapreduce.Mapper; import org.apache.hadoop.mapreduce.Reducer; import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; import org.apache.hadoop.util.GenericOptionsParser; public class Average { public static class TokenizerMapper extends Mapper<Object, Text, Text, Text> { private final static IntWritable one = new IntWritable(1); private Text word = new Text(); public void map(Object key, Text value, Context context) throws IOException, InterruptedException { StringTokenizer itr = new StringTokenizer(value.toString()); while (itr.hasMoreTokens()) { word.set(itr.nextToken()); if (itr.hasMoreTokens()) { context.write(word, new Text(itr.nextToken() + ",1")); } } } } static class AverageCombine extends Reducer<Text, Text, Text, Text> { public void reduce(Text key, Iterable<Text> values, Context context) throws IOException, InterruptedException { int sum = 0, cnt = 0; for (Text val : values) { String[] s1 = val.toString().split(","); sum += Integer.parseInt(s1[0]); cnt += Integer.parseInt(s1[1]); } String s; System.out.println("Combine" + (s = new String(sum + "," + cnt))); context.write(key, new Text(new String(sum + "," + cnt))); } } static class AverageReducer extends Reducer<Text, Text, Text, DoubleWritable> { public void reduce(Text key, Iterable<Text> values, Context context) throws IOException, InterruptedException { int sum = 0, cnt = 0; for (Text val : values) { String[] s = val.toString().split(","); sum += Integer.parseInt(s[0]); cnt += Integer.parseInt(s[1]); } String s; System.out.println("reduce" + (s = new String(key + "," + (sum * 1.0 / cnt)))); context.write(key, new DoubleWritable(sum * 1.0 / cnt)); } } public static void main(String[] args) throws Exception { Configuration conf = new Configuration(); String[] otherArgs = args; if (otherArgs.length != 2) { System.err.println("Usage:Data Average <in> <out>"); System.exit(2); } Job job = new Job(conf, "Data Average"); job.setJarByClass(Average.class); job.setMapperClass(TokenizerMapper.class); job.setCombinerClass(AverageCombine.class); job.setReducerClass(AverageReducer.class); job.setOutputKeyClass(Text.class); job.setOutputValueClass(Text.class); FileInputFormat.addInputPath(job, new Path(otherArgs[0])); FileOutputFormat.setOutputPath(job, new Path(otherArgs[1])); System.exit(job.waitForCompletion(true) ? 0 : 1); } }
执行
bin/hadoop jar Average.jar Average data.txt out
结果
a 3.0
b 6.0