OutputFormat是MapReduce输出的基类,所有实现MapReduce输出都实现了OutputFormat接口。下面我们介绍几种常见的OutputFormat实现类。
1、文本输出TextOutputFormat
默认的输出格式是TextOutputFormat,它把每条记录写为文本行。它的键和值可以是任意类型,疑问TextOutputFormat调用toString()方法把他们转换为字符串。
2、SequenceFileOutputFormat
将SequenceFileOutputFormat输出作为后续MapReduce任务的输入,这便是一种好的输出格式,因为它的格式紧凑,很容易被压缩。
3、自定义OutputFormat
根据用户需求,自定义实现输出。
1、使用场景
为了实现控制最终文件的输出路径和输出格式,可以自定义OutputFormat。
例如:要在一个MapReduce程序中根据数据的不同输出两类结果到不同的目录,这类灵活的输出需求可以通过自定义OutputFormat来实现。
2、自定义OUtputFormat步骤
(1)自定义一个类继承FileOutputFormat。
(2)改写RecordWriter,具体改写输出数据的方法write()。
1、需求
过滤输入的log日志,包含atguigu的网站输出到e:/atguigu.log,不包含atguigu的网站输出到e:/other.log。
(1)输入数据
http://www.baidu.com
http://www.google.com
http://cn.bing.com
http://www.atguigu.com
http://www.sohu.com
http://www.sina.com
http://www.sin2a.com
http://www.sin2desa.com
http://www.sindsafa.com
(2)期望输出数据
http://www.atguigu.com
http://cn.bing.com
http://www.baidu.com
http://www.google.com
http://www.sin2a.com
http://www.sin2desa.com
http://www.sina.com
http://www.sindsafa.com
http://www.sohu.com
2、需求分析
3、案例实操
(1)编写FilterMapper类
package com.cuiyf41.output;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
import java.io.IOException;
public class FilterMapper extends Mapper<LongWritable, Text, Text, NullWritable> {
@Override
protected void map(LongWritable key, Text value, Mapper<LongWritable, Text, Text, NullWritable>.Context context) throws IOException, InterruptedException {
// 写出
context.write(value, NullWritable.get());
}
}
(2)编写FilterReducer类
package com.cuiyf41.output;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;
import java.io.IOException;
public class FilterReducer extends Reducer<Text, NullWritable, Text, NullWritable> {
Text k = new Text();
@Override
protected void reduce(Text key, Iterable<NullWritable> values, Reducer<Text, NullWritable, Text, NullWritable>.Context context) throws IOException, InterruptedException {
// 1 获取一行
String line = key.toString();
// 2 拼接
line = line + "\r\n";
// 3 设置key
k.set(line);
// 4 输出
context.write(k, NullWritable.get());
}
}
(3)自定义一个OutputFormat类
package com.atguigu.mapreduce.outputformat;
import java.io.IOException;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.RecordWriter;
import org.apache.hadoop.mapreduce.TaskAttemptContext;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
public class FilterOutputFormat extends FileOutputFormat<Text, NullWritable>{
@Override
public RecordWriter<Text, NullWritable> getRecordWriter(TaskAttemptContext job) throws IOException, InterruptedException {
// 创建一个RecordWriter
return new FilterRecordWriter(job);
}
}
(4)编写RecordWriter类
package com.cuiyf41.output;
import org.apache.hadoop.fs.FSDataOutputStream;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IOUtils;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.RecordWriter;
import org.apache.hadoop.mapreduce.TaskAttemptContext;
import java.io.IOException;
public class FilterRecordWriter extends RecordWriter<Text, NullWritable> {
FSDataOutputStream atguiguOut = null;
FSDataOutputStream otherOut = null;
public FilterRecordWriter(TaskAttemptContext job) {
// 1 获取文件系统
FileSystem fs;
try {
fs = FileSystem.get(job.getConfiguration());
// 2 创建输出文件路径
Path atguiguPath = new Path("e:/atguigu.log");
Path otherPath = new Path("e:/other.log");
// 3 创建输出流
atguiguOut = fs.create(atguiguPath);
otherOut = fs.create(otherPath);
} catch (IOException e) {
e.printStackTrace();
}
}
@Override
public void write(Text key, NullWritable value) throws IOException, InterruptedException {
// 判断是否包含“atguigu”输出到不同文件
if (key.toString().contains("atguigu")) {
atguiguOut.write(key.toString().getBytes());
} else {
otherOut.write(key.toString().getBytes());
}
}
@Override
public void close(TaskAttemptContext context) throws IOException, InterruptedException {
// 关闭资源
IOUtils.closeStream(atguiguOut);
IOUtils.closeStream(otherOut);
}
}
(5)编写FilterDriver类
package com.cuiyf41.output;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import java.io.IOException;
public class FilterDriver {
public static void main(String[] args) throws IOException, InterruptedException, ClassNotFoundException {
// 输入输出路径需要根据自己电脑上实际的输入输出路径设置
args = new String[] { "e:/input/log.txt", "e:/output2" };
Configuration conf = new Configuration();
Job job = Job.getInstance(conf);
job.setJarByClass(FilterDriver.class);
job.setMapperClass(FilterMapper.class);
job.setReducerClass(FilterReducer.class);
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(NullWritable.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(NullWritable.class);
// 要将自定义的输出格式组件设置到job中
job.setOutputFormatClass(FilterOutputFormat.class);
Path input = new Path(args[0]);
Path output = new Path(args[1]);
// 如果输出路径存在,则进行删除
FileSystem fs = FileSystem.get(conf);
if (fs.exists(output)) {
fs.delete(output,true);
}
FileInputFormat.setInputPaths(job, input);
// 虽然我们自定义了outputformat,但是因为我们的outputformat继承自fileoutputformat
// 而fileoutputformat要输出一个_SUCCESS文件,所以,在这还得指定一个输出目录
FileOutputFormat.setOutputPath(job, output);
boolean result = job.waitForCompletion(true);
System.exit(result ? 0 : 1);
}
}