Hadoop序列化文件SequenceFile能够用于解决大量小文件（所谓小文件：泛指小于black大小的文件）问题，SequenceFile是Hadoop API提供的一种二进制文件支持。这样的二进制文件直接将<key,value>对序列化到文件里，一般对小文件能够使用这样的文件合并，即将文件名称作为key。文件内容作为value序列化到大文件里。
可是SequenceFile文件不能追加写入，适用于一次性写入大量小文件的操作。
SequenceFile的压缩基于CompressType，请看源代码：
/**
* The compression type used to compress key/value pairs in the
* {@link SequenceFile}.
* @see SequenceFile.Writer
*/
public static enum CompressionType {
/** Do not compress records. */
NONE, //不压缩
/** Compress values only, each separately. */
RECORD, //仅仅压缩values
/** Compress sequences of records together in blocks. */
BLOCK //压缩非常多记录的key/value组成块
}
SequenceFile读写演示样例：
import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IOUtils;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.SequenceFile;
import org.apache.hadoop.io.SequenceFile.CompressionType;
import org.apache.hadoop.io.SequenceFile.Reader;
import org.apache.hadoop.io.SequenceFile.Writer;
import org.apache.hadoop.io.Text;
/**
* @version 1.0
* @author Fish
*/
public class SequenceFileWriteDemo {
private static final String[] DATA = { "fish1", "fish2", "fish3", "fish4" };
public static void main(String[] args) throws IOException {
/**
* 写SequenceFile
*/
String uri = "/test/fish/seq.txt";
Configuration conf = new Configuration();
Path path = new Path(uri);
IntWritable key = new IntWritable();
Text value = new Text();
Writer writer = null;
try {
/**
* CompressionType.NONE 不压缩<br>
* CompressionType.RECORD 仅仅压缩value<br>
* CompressionType.BLOCK 压缩非常多记录的key/value组成块
*/
writer = SequenceFile.createWriter(conf, Writer.file(path), Writer.keyClass(key.getClass()),
Writer.valueClass(value.getClass()), Writer.compression(CompressionType.BLOCK));
for (int i = 0; i < 4; i++) {
value.set(DATA[i]);
key.set(i);
System.out.printf("[%s]\t%s\t%s\n", writer.getLength(), key, value);
writer.append(key, value);
}
} finally {
IOUtils.closeStream(writer);
}
/**
* 读SequenceFile
*/
SequenceFile.Reader reader = new SequenceFile.Reader(conf, Reader.file(path));
IntWritable key1 = new IntWritable();
Text value1 = new Text();
while (reader.next(key1, value1)) {
System.out.println(key1 + "----" + value1);
}
IOUtils.closeStream(reader);// 关闭read流
/**
* 用于排序
*/
// SequenceFile.Sorter sorter = new SequenceFile.Sorter(fs, comparator, IntWritable.class, Text.class, conf);
}
}
以上程序运行多次。并不会出现数据append的情况，每次都是又一次创建一个文件。且文件里只唯独四条数据。
究其原因。能够查看SequenceFile.Writer类的构造方法源代码：
out = fs.create(p, true, bufferSize, replication, blockSize, progress);
第二个參数为true，表示每次覆盖同名文件，假设为false会抛出异常。
这样设计的目的可能是和HDFS一次写入多次读取有关，不提倡追加现有文件，所以构造方法写死了true。
SequenceFile文件的数据组成形式：
一，Header
写入头部的源代码：
/** Write and flush the file header. */
private void writeFileHeader()
throws IOException {
out.write(VERSION);//版本
Text.writeString(out, keyClass.getName());//key的Class
Text.writeString(out, valClass.getName());//val的Class
out.writeBoolean(this.isCompressed());//是否压缩
out.writeBoolean(this.isBlockCompressed());//是否是CompressionType.BLOCK类型的压缩
if (this.isCompressed()) {
Text.writeString(out, (codec.getClass()).getName());//压缩类的名称
}
this.metadata.write(out);//写入metadata
out.write(sync); // write the sync bytes
out.flush(); // flush header
}
版本：
private static byte[] VERSION = new byte[] {
(byte)'S', (byte)'E', (byte)'Q', VERSION_WITH_METADATA
};同步标识符的生成方式：
byte[] sync; // 16 random bytes
{
try {
MessageDigest digester = MessageDigest.getInstance("MD5");
long time = Time.now();
digester.update((new UID()+"@"+time).getBytes());
sync = digester.digest();
} catch (Exception e) {
throw new RuntimeException(e);
}
}
二，Record
Writer有三个实现类，分别相应CompressType的NONE。RECOR，BLOCK。以下逐一介绍一下（结合上面的图看）：
1，NONE SequenceFile
Record直接存Record 的长度，KEY的长度，key值，Value的值
2, BlockCompressWriter
/** Append a key/value pair. */
@Override
@SuppressWarnings("unchecked")
public synchronized void append(Object key, Object val)
throws IOException {
if (key.getClass() != keyClass)
throw new IOException("wrong key class: "+key+" is not "+keyClass);
if (val.getClass() != valClass)
throw new IOException("wrong value class: "+val+" is not "+valClass);
// Save key/value into respective buffers
int oldKeyLength = keyBuffer.getLength();
keySerializer.serialize(key);
int keyLength = keyBuffer.getLength() - oldKeyLength;
if (keyLength < 0)
throw new IOException("negative length keys not allowed: " + key);
WritableUtils.writeVInt(keyLenBuffer, keyLength);//每调一次，都会累加keyLength
int oldValLength = valBuffer.getLength();
uncompressedValSerializer.serialize(val);
int valLength = valBuffer.getLength() - oldValLength;
WritableUtils.writeVInt(valLenBuffer, valLength);//每调一次，都会累加valLength
// Added another key/value pair
++noBufferedRecords;
// Compress and flush?
int currentBlockSize = keyBuffer.getLength() + valBuffer.getLength();
if (currentBlockSize >= compressionBlockSize) {
//compressionBlockSize = conf.getInt("io.seqfile.compress.blocksize", 1000000);
//超过1000000就会写一个Sync
sync();
}
超过compressionBlockSize的大小。就会调用sync()方法，以下看看sync的源代码（和上面的图对比）：
会写入和图中所画的各个数据项。
/** Compress and flush contents to dfs */
@Override
public synchronized void sync() throws IOException {
if (noBufferedRecords > 0) {
super.sync();
// No. of records
WritableUtils.writeVInt(out, noBufferedRecords);
// Write 'keys' and lengths
writeBuffer(keyLenBuffer);
writeBuffer(keyBuffer);
// Write 'values' and lengths
writeBuffer(valLenBuffer);
writeBuffer(valBuffer);
// Flush the file-stream
out.flush();
// Reset internal states
keyLenBuffer.reset();
keyBuffer.reset();
valLenBuffer.reset();
valBuffer.reset();
noBufferedRecords = 0;
}
}
2。RecordCompressWriter
/** Append a key/value pair. */
@Override
@SuppressWarnings("unchecked")
public synchronized void append(Object key, Object val)
throws IOException {
if (key.getClass() != keyClass)
throw new IOException("wrong key class: "+key.getClass().getName()
+" is not "+keyClass);
if (val.getClass() != valClass)
throw new IOException("wrong value class: "+val.getClass().getName()
+" is not "+valClass);
buffer.reset();
// Append the 'key'
keySerializer.serialize(key);
int keyLength = buffer.getLength();
if (keyLength < 0)
throw new IOException("negative length keys not allowed: " + key);
// Compress 'value' and append it
deflateFilter.resetState();
compressedValSerializer.serialize(val);
deflateOut.flush();
deflateFilter.finish();
// Write the record out
checkAndWriteSync(); // sync
out.writeInt(buffer.getLength()); // total record length record的长度
out.writeInt(keyLength); // key portion length key的长度
out.write(buffer.getData(), 0, buffer.getLength()); // data 数据
}
写入Sync：
synchronized void checkAndWriteSync() throws IOException {
if (sync != null &&
out.getPos() >= lastSyncPos+SYNC_INTERVAL) { // time to emit sync
sync();
}
}SYNC_INTERVAL的定义：
private static final int SYNC_ESCAPE = -1; // "length" of sync entries
private static final int SYNC_HASH_SIZE = 16; // number of bytes in hash
private static final int SYNC_SIZE = 4+SYNC_HASH_SIZE; // escape + hash
/** The number of bytes between sync points.*/
public static final int SYNC_INTERVAL = 100*SYNC_SIZE;
每2000个byte，就会写一个Sync。
总结：
Record：存储SequenceFile通用的KV数据格式，Key和Value都是二进制变长的数据。Record表示Key和Value的byte的总和。
Sync：主要是用来扫描和恢复数据的，以至于读取数据的Reader不会迷失。
Header：存储了例如以下信息：文件标识符SEQ，key和value的格式说明。以及压缩的相关信息，metadata等信息。
metadata：包括文件头所须要的数据：文件标识、Sync标识、数据格式说明(含压缩)、文件元数据(时间、owner、权限等)、检验信息等
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