词频示例
文件 wcFile
baozi hello
baozi hi
baozi chi
baozi roubaozi
代码
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
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 java.io.IOException;
public class WordCount {
/**
* Map
*/
public static class MapClass extends Mapper<LongWritable, Text, Text, LongWritable> {
LongWritable one = new LongWritable(1);
@Override
protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
// 切分
String[] worlds = value.toString().split(" ");
for (String world : worlds) {
// (world,1)
context.write(new Text(world), one);
}
}
}
/**
* Reduce
*/
public static class ReduceClass extends Reducer<Text, LongWritable, Text, LongWritable> {
@Override
protected void reduce(Text key, Iterable<LongWritable> values, Context context) throws IOException, InterruptedException {
// 累加 world,{1,1,1,1,1...}
long sum = 0;
for (LongWritable v : values) {
sum += v.get();
}
// (world,N)
context.write(key, new LongWritable(sum));
}
}
public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
Configuration conf = new Configuration();
// 输出文件路径已存在删除
Path inputPath = new Path(args[0]);
Path outputPath = new Path(args[1]);
FileSystem fileSystem = FileSystem.get(conf);
if (fileSystem.exists(outputPath)) {
fileSystem.delete(outputPath, true);
}
// Job处理类
Job job = Job.getInstance(conf,"wordCount");
job.setJarByClass(WordCount.class);
// 输入输出文件路径
FileInputFormat.addInputPath(job, inputPath);
FileOutputFormat.setOutputPath(job, outputPath);
// 设置map相关参数
job.setMapperClass(MapClass.class);
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(LongWritable.class);
// 设置reduce相关参数
job.setReducerClass(ReduceClass.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(LongWritable.class);
// 退出
System.exit(job.waitForCompletion(true) ? 0 : 1);
}
}
运行
$ mvn clean package -DskipTests
$ scp target/hadoop-spring-learning-1.0-SNAPSHOT.jar user000@host000:~/doc
$ hadoop jar ~/doc/hadoop-spring-learning-1.0-SNAPSHOT.jar \
WordCount \
hdfs://host000:8020/wcFile \
hdfs://host000:8020/output/
$ hdfs dfs -cat /output/part-r-00000
Partitioner
Partitioner：结果一样的统一输出到相同地方。
文件 salesFile
xiaomi 200
huawei 100
xiaomi 300
iphone7 200
huawei 200
xiaomi 300
others 100
代码
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Partitioner;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import java.io.IOException;
public class PartitionerApp {
public static class MapClass extends Mapper<LongWritable, Text, Text, LongWritable> {
@Override
protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
String[] words = value.toString().split(" ");
// {xiaomi,200}
context.write(
new Text(words[0]),
new LongWritable(Long.parseLong(words[1]))
);
}
}
public static class ReduceClass extends Reducer<Text, LongWritable, Text, LongWritable> {
@Override
protected void reduce(Text key, Iterable<LongWritable> values, Context context) throws IOException, InterruptedException {
// xiaomi,{200,300,400...}
long sum = 0;
for (LongWritable v : values) {
sum += v.get();
}
// (xiaomi, N)
context.write(key, new LongWritable(sum));
}
}
public static class PartitionerClass extends Partitioner<Text, LongWritable> {
@Override
public int getPartition(Text text, LongWritable longWritable, int numPartitions) {
if ("xiaomi".equals(text.toString())) {
return 0;
} else if ("huawei".equals(text.toString())) {
return 1;
} else if ("iphone7".equals(text.toString())) {
return 2;
}
return 3;
}
}
public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
Configuration conf = new Configuration();
// 输出文件路径已存在删除
Path inputPath = new Path(args[0]);
Path outputPath = new Path(args[1]);
FileSystem fileSystem = FileSystem.get(conf);
if (fileSystem.exists(outputPath)) {
fileSystem.delete(outputPath, true);
}
// Job处理类
Job job = Job.getInstance(conf,"wordCount");
job.setJarByClass(WordCount.class);
// 输入输出文件路径
FileInputFormat.addInputPath(job, inputPath);
FileOutputFormat.setOutputPath(job, outputPath);
// 设置map相关参数
job.setMapperClass(MapClass.class);
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(LongWritable.class);
// 设置reduce相关参数
job.setReducerClass(ReduceClass.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(LongWritable.class);
// 设置Partitioner
job.setPartitionerClass(PartitionerClass.class);
//设置4个reducer，每个分区一个,不加体现不出Partitioner
job.setNumReduceTasks(4);
// 退出
System.exit(job.waitForCompletion(true) ? 0 : 1);
}
}
Combiner
combiner在求和、次数的等汇总统计可以用。combiner设置了也未必会执行。
例如，求平均数，一边是2、7，一边是3、5。 左边使用了combiner，右边没有使用，得到的平均数与本应该得到的不符。
例如，求合汇总，一边是2、7，一边是3、5。 左边使用了combiner，右边没有使用，得到的和都不会改变。
job.setCombinerClass(Reducer.class); // combiner逻辑上和reduce一样
