Hadoop无法处理中文问题解决方案
由于Hadoop默认编码为UTF－8，并且将UTF－8进行了硬编码，所以我们在处理中文时需要重写OutputFormat类。方法为：
1、新建类GBKFileOutputFormat，代码如下：
import java.io.DataOutputStream;
import java.io.IOException;
import java.io.UnsupportedEncodingException;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.fs.FSDataOutputStream;
import org.apache.hadoop.mapreduce.lib.*;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.compress.CompressionCodec;
import org.apache.hadoop.io.compress.GzipCodec;
import org.apache.hadoop.mapreduce.OutputFormat;
import org.apache.hadoop.mapreduce.RecordWriter;
import org.apache.hadoop.mapreduce.TaskAttemptContext;
import org.apache.hadoop.util.*;
/** An {@link OutputFormat} that writes plain text files. */
public class GBKFileOutputFormat<K, V> extends FileOutputFormat<K, V> {//TextInputFormat是默认的输出文件格式
protected static class LineRecordWriter<K, V>//默认
extends RecordWriter<K, V> {
private static final String utf8 = "GBK"; //硬编码，将“UTF－8”改为“GBK”
private static final byte[] newline;//行结束符？
static {
try {
newline = "\n".getBytes(utf8);
} catch (UnsupportedEncodingException uee) {
throw new IllegalArgumentException("can't find " + utf8 + " encoding");
}
}
protected DataOutputStream out;
private final byte[] keyValueSeparator;//key和value的分隔符，默认的好像是Tab
public LineRecordWriter(DataOutputStream out, String keyValueSeparator) {//构造函数，初始化输出流及分隔符
this.out = out;
try {
this.keyValueSeparator = keyValueSeparator.getBytes(utf8);
} catch (UnsupportedEncodingException uee) {
throw new IllegalArgumentException("can't find " + utf8 + " encoding");
}
}
public LineRecordWriter(DataOutputStream out) {//默认的分隔符
this(out, "\t");
}
/**
* Write the object to the byte stream, handling Text as a special输出流是byte格式的
* case.
* @param o the object to print是要输出的对象
* @throws IOException if the write throws, we pass it on
*/
private void writeObject(Object o) throws IOException {//应该是一行一行的写 key keyValueSeparator value \n
if (o instanceof Text) {//如果o是Text的实例
Text to = (Text) o;
out.write(to.getBytes(), 0, to.getLength());//写出
} else {
out.write(o.toString().getBytes(utf8));
}
}
public synchronized void write(K key, V value)//给写线程加锁，写是互斥行为
throws IOException {
//下面是为了判断key和value是否为空值
boolean nullKey = key == null || key instanceof NullWritable;//这语句太牛了
boolean nullValue = value == null || value instanceof NullWritable;
if (nullKey && nullValue) {//
return;
}
if (!nullKey) {
writeObject(key);
}
if (!(nullKey || nullValue)) {
out.write(keyValueSeparator);
}
if (!nullValue) {
writeObject(value);
}
out.write(newline);
}
public synchronized
void close(TaskAttemptContext context) throws IOException {
out.close();
}
}
public RecordWriter<K, V> getRecordWriter(TaskAttemptContext job//获得writer实例
) throws IOException, InterruptedException {
Configuration conf = job.getConfiguration();
boolean isCompressed = getCompressOutput(job);//
String keyValueSeparator= conf.get("mapred.textoutputformat.separator",
"\t");
CompressionCodec codec = null;//压缩格式 还是？
String extension = "";
if (isCompressed) {
Class<? extends CompressionCodec> codecClass =
getOutputCompressorClass(job, GzipCodec.class);
codec = (CompressionCodec) ReflectionUtils.newInstance(codecClass, conf);
extension = codec.getDefaultExtension();
}
Path file = getDefaultWorkFile(job, extension);//这个是获取缺省的文件路径及名称，在FileOutput中有对其的实现
FileSystem fs = file.getFileSystem(conf);
if (!isCompressed) {
FSDataOutputStream fileOut = fs.create(file, false);
return new LineRecordWriter<K, V>(fileOut, keyValueSeparator);
} else {
FSDataOutputStream fileOut = fs.create(file, false);
return new LineRecordWriter<K, V>(new DataOutputStream
(codec.createOutputStream(fileOut)),
keyValueSeparator);
}
}
}
该类是在源代码中TextOutputFormat类基础上进行修改的，在这需要注意的一点是继承的父类FileOutputFormat是位于org.apache.hadoop.mapreduce.lib.output包中的
2、在主类中添加job.setOutputFormatClass(GBKFileOutputFormat.class);