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网上虽然有不少关于MultipleOutputs实现多文件输出的文章,但发现要不还是使用mapred.lib旧接口,要不就是说明不清楚。
Mapper
package com.yy.hiido.itemcf.hadoop.mapper;
import java.io.IOException;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
public class ReadFilesMapper extends
Mapper<LongWritable, Text, Text, Text> {
private final String SPLITTER="\\s+";
private Text outkey;
private Text values;
@Override
protected void setup(Context context)
throws IOException, InterruptedException {
super.setup(context);
outkey = new Text();
values = new Text();
}
@Override
protected void map(LongWritable key, Text value,Context context)
throws IOException, InterruptedException {
String line = value.toString();
//System.out.println("line : "+line);
String [] fields = line.split(this.SPLITTER);
outkey.set(fields[0]);
values.set(fields[1]);
System.out.println("key : "+fields[0]+" | values : "+fields[1]);
context.write(outkey,values);
}
}
Reducer
package com.yy.hiido.itemcf.hadoop.reducer;
import java.io.IOException;
import java.util.HashMap;
import java.util.Map;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.output.MultipleOutputs;
import org.apache.mahout.math.RandomAccessSparseVector;
import org.apache.mahout.math.Vector;
import org.apache.mahout.math.VectorWritable;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
public class ReadFilesReducer extends
Reducer<Text, Text, Text, Text> {
private MultipleOutputs<Text,Text> mos;
@Override
protected void setup(Context context)
throws IOException, InterruptedException {
mos = new MultipleOutputs<Text,Text>(context);
}
@Override
protected void reduce(Text key, Iterable<Text> values,Context context)
throws IOException, InterruptedException {
String temp="";
for(Text t : values)
temp+=t.toString()+" | ";
//mos.write(key.toString(), key, new Text(temp));//这样需要预定义named output
mos.write(key, new Text(temp), key.toString());//这样不需要与定义named output
}
@Override
protected void cleanup(Context context)
throws IOException, InterruptedException {
mos.close();;
}
}
main
package com.yy.hiido.itemcf.hadoop.job;
import java.io.IOException;
import java.net.URI;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.hbase.HBaseConfiguration;
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.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.LazyOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;
import com.yy.hiido.itemcf.hadoop.mapper.ReadFilesMapper;
import com.yy.hiido.itemcf.hadoop.reducer.ReadFilesReducer;
/**
* @author BlackWing 测试multioutput
* */
public class TestMultiOutputJob extends Configured implements Tool {
// 配置文件名
public final static String propertyFileName = "config.xml";
private static final Log LOG = LogFactory.getLog(TestMultiOutputJob.class);
private static Configuration conf = HBaseConfiguration.create();
public int myjob() {
// 读配置文件
conf.addResource(propertyFileName);
String input = conf.get("file.to.read");
String outputDir = conf.get("test.output");
System.out.println("input : "+input);
System.out.println("output : "+outputDir);
// 若输出目录存在,则删除
try {
FileSystem fs = FileSystem.get(URI.create(outputDir),
new Configuration());
fs.delete(new Path(outputDir), true);
fs.close();
} catch (Exception e) {
e.printStackTrace();
}
Job myjob = null;
try {
myjob = new Job(conf);
} catch (IOException e) {
e.printStackTrace();
}
myjob.setJarByClass(ReadFilesMapper.class);
try {
FileInputFormat.setInputPaths(myjob, input);
FileOutputFormat.setOutputPath(myjob, new Path(outputDir));
} catch (IOException e1) {
e1.printStackTrace();
}
myjob.setMapperClass(ReadFilesMapper.class);
myjob.setInputFormatClass(TextInputFormat.class);
// myjob.setOutputFormatClass(TextOutputFormat.class);
LazyOutputFormat.setOutputFormatClass(myjob, TextOutputFormat.class);
myjob.setReducerClass(ReadFilesReducer.class);
myjob.setOutputKeyClass(Text.class);
myjob.setOutputValueClass(Text.class);
//MultipleOutputs.addNamedOutput(myjob, "moshouzhengba", TextOutputFormat.class, Text.class, Text.class);
//MultipleOutputs.addNamedOutput(myjob, "maoxiandao", TextOutputFormat.class, Text.class, Text.class);
//MultipleOutputs.addNamedOutput(myjob, "yingxionglianmen", TextOutputFormat.class, Text.class, Text.class);
boolean succeeded = false;
try {
succeeded = myjob.waitForCompletion(true);
} catch (IOException e) {
e.printStackTrace();
} catch (InterruptedException e) {
e.printStackTrace();
} catch (ClassNotFoundException e) {
e.printStackTrace();
}
if (!succeeded)
return -1;
// status记录job运行状态
LOG.info("Job complete !");
return 1;
}
@Override
public int run(String[] as) throws Exception {
// 读配置文件
conf.addResource(propertyFileName);
myjob();
return 0;
}
/**
* @param args
*/
public static void main(String[] args) {
long start = System.currentTimeMillis();
try {
ToolRunner.run(new TestMultiOutputJob(), args);
} catch (Exception e) {
e.printStackTrace();
}
long end = System.currentTimeMillis();
System.out.println("run the program costs time:" + (end - start)
/ 60000 + "Minutes");
}
}
其中注意的是:
1.reducer中调用时,要调用MultipleOutputs以下接口:
write
public void write(KEYOUT key,
VALUEOUT value,
String baseOutputPath)
throws IOException,
InterruptedException
如果调用
write
public <K,V> void write(String namedOutput,
K key,
V value)
throws IOException,
InterruptedException
则需要在job中,预先声明named output(如下),不然会报错:named output xxx not defined:
MultipleOutputs.addNamedOutput(myjob, "moshouzhengba", TextOutputFormat.class, Text.class, Text.class);
MultipleOutputs.addNamedOutput(myjob, "maoxiandao", TextOutputFormat.class, Text.class, Text.class);
MultipleOutputs.addNamedOutput(myjob, "yingxionglianmen", TextOutputFormat.class, Text.class, Text.class);
2.默认情况下,输出目录会生成part-r-00000或者part-m-00000的空文件,需要如下设置后,才不会生成:
// myjob.setOutputFormatClass(TextOutputFormat.class);
LazyOutputFormat.setOutputFormatClass(myjob, TextOutputFormat.class);
就是去掉job设置outputFormatClass,改为通过LazyOutputFormat设置
这里只是以Text的输入输出格式说明。
官方的文档:
https://hadoop.apache.org/docs/current2/api/org/apache/hadoop/mapreduce/lib/output/MultipleOutputs.html#write(java.lang.String, K, V)
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