hadoop的I/O

1. 数据完整性：任何语言对IO的操作都要保持其数据的完整性。hadoop当然希望数据在存储和处理中不会丢失或损坏。检查数据完整性的常用方法是校验和。

• HDFS的数据完整性：客户端在写或者读取HDFS的文件时，都会对其进行校验和验证，当然我们可以通过在Open（）方法读取之前，将false传给FileSystem中的setVerifyCheckSum()来禁用校验和。
• 本地文件系统，hadoop的本地文件系统执行客户端校验，这意味着，在写一个filename文件时，文件系统的客户端以透明方式创建了一个隐藏的文件.filename.crc,块的大小做为元数据存于此，所以读取文件时会进行校验和验证。
• ChecksumFileSystem：可以通过它对其数据验证。

2. 压缩：压缩后能够节省空间和减少网络中的传输。所以在hadoop中压缩是非常重要的。hadoop的压缩格式

压缩格式算法文件扩展名多文件可分割性DEFLATEaDEFLATE.deflatenonogzip（zip）DEFLATE.gz(.zip)no(yes)no(yes)bzip2bzip2.bz2noyesLZOLZO.lzonono

• 编码/解码

Compression format          Hadoop CompressionCodec

DEFLATE                            org.apache.hadoop.io.compress.DefaultCodec

gzip                                   org.apache.hadoop.io.compress.GzipCodec

bzip2                                 org.apache.hadoop.io.compress.BZip2Codec

LZO                                   com.hadoop.compression.lzo.LzopCodec

可以用ComressionCodec轻松的压缩和解压缩。我们可以用CompressionOutput创建一个CompressionOutputStream（未压缩的数据写到此）。相反，可以用compressionInputStream进行解压缩。

/** * @param args */public static void main(String[] args) throws Exception{// TODO Auto-generated method stubString codecClassname = args[0];Class<?> codecClass = Class.forName(codecClassname);Configuration configuration = new Configuration();CompressionCodec codec = (CompressionCodec)ReflectionUtils.newInstance(codecClass, configuration);CompressionOutputStream  outputStream = codec.createOutputStream(System.out);IOUtils.copyBytes(System.in, outputStream, 4096,false);outputStream.finish();}

• 压缩和分割：因为HDFS默认是以块的来存储数据的，所以在压缩时考虑是否支持分割时非常重要的。
• 在MapReduce使用压缩：例如要压缩MapReduce作业的输出，需要将配置文件中mapred.output.compress的属性设置为true

public static void main(String[] args) throws IOException {    if (args.length != 2) {      System.err.println("Usage: MaxTemperatureWithCompression <input path> " +      "<output path>");      System.exit(-1);    }        JobConf conf = new JobConf(MaxTemperatureWithCompression.class);    conf.setJobName("Max temperature with output compression");    FileInputFormat.addInputPath(conf, new Path(args[0]));    FileOutputFormat.setOutputPath(conf, new Path(args[1]));        conf.setOutputKeyClass(Text.class);    conf.setOutputValueClass(IntWritable.class);        /*[*/conf.setBoolean("mapred.output.compress", true);    conf.setClass("mapred.output.compression.codec", GzipCodec.class,        CompressionCodec.class);/*]*/    conf.setMapperClass(MaxTemperatureMapper.class);    conf.setCombinerClass(MaxTemperatureReducer.class);    conf.setReducerClass(MaxTemperatureReducer.class);    JobClient.runJob(conf);  }

3.序列化：将字节流和机构化对象的转化。hadoop是进程间通信（RPC调用），PRC序列号结构特点：紧凑，快速，可扩展，互操作，hadoop使用自己的序列化格式Writerable，

• Writerable接口： 
  

package org.apache.hadoop.io;import java.io.DataOutput;import java.io.DataInput;import java.io.IOException;public interface Writable {void write(DataOutput out) throws IOException;// 将序列化流写入DataOutputvoid readFields(DataInput in) throws IOException; //从DataInput流读取二进制}

package WritablePackage;import java.io.ByteArrayInputStream;import java.io.ByteArrayOutputStream;import java.io.DataInputStream;import java.io.DataOutputStream;import java.io.IOException;import org.apache.hadoop.io.Writable;import org.apache.hadoop.util.StringUtils;import org.hsqldb.lib.StringUtil;public class WritableTestBase{public static byte[] serialize(Writable writable) throws IOException{ByteArrayOutputStream outputStream  = new ByteArrayOutputStream();DataOutputStream dataOutputStream = new DataOutputStream(outputStream);writable.write(dataOutputStream);dataOutputStream.close();return outputStream.toByteArray();}public static byte[] deserialize(Writable writable,byte[] bytes) throws IOException{ByteArrayInputStream inputStream = new ByteArrayInputStream(bytes);DataInputStream dataInputStream = new DataInputStream(inputStream);writable.readFields(dataInputStream);dataInputStream.close();return bytes;}public static String serializeToString(Writable src) throws IOException{return StringUtils.byteToHexString(serialize(src));}public static String writeTo(Writable src, Writable des) throws IOException{byte[] data = deserialize(des, serialize(src));return StringUtils.byteToHexString(data);}}

 Writerable 类

Java primitive                  Writable implementation Serialized size (bytes)
boolean                           BooleanWritable 1
byte                                 ByteWritable 1
int                                    IntWritable 4
                                        VIntWritable 1–5
float                                FloatWritable 4
long                                LongWritable 8
                                       VLongWritable 1–9

4. 基于文件的数据结构

• SequenceFile类：是二进制键/值对提供一个持久化的数据结构。SequenceFile的读取和写入。

package WritablePackage;import java.io.IOException;import java.net.URI;import org.apache.hadoop.conf.Configuration;import org.apache.hadoop.fs.FileSystem;import org.apache.hadoop.fs.Path;import org.apache.hadoop.io.IOUtils;import org.apache.hadoop.io.IntWritable;import org.apache.hadoop.io.Text;import org.apache.hadoop.io.SequenceFile;public class SequenceFileWriteDemo{ private static final String[] DATA = {    "One, two, buckle my shoe",    "Three, four, shut the door",    "Five, six, pick up sticks",    "Seven, eight, lay them straight",    "Nine, ten, a big fat hen"  };/** * @param args * @throws IOException  */public static void main(String[] args) throws IOException{// TODO Auto-generated method stubString url = args[0];Configuration conf = new Configuration();FileSystem fs = FileSystem.get(URI.create(url),conf);Path path  = new Path(url);IntWritable key = new IntWritable();Text value = new Text();SequenceFile.Writer writer =null;try{writer = SequenceFile.createWriter(fs,conf,path,key.getClass(),value.getClass());for(int i = 0; i< 100; i++){key.set(100-i);value.set(DATA[i%DATA.length]);System.out.printf("[%s]\t%s\t%s\n", writer.getLength(), key, value);writer.append(key,value);}}catch (Exception e){// TODO: handle exception}finally{IOUtils.closeStream(writer);}}}

package WritablePackage;import java.io.IOException;import java.net.URI;import org.apache.hadoop.conf.Configuration;import org.apache.hadoop.fs.FileSystem;import org.apache.hadoop.fs.Path;import org.apache.hadoop.io.IOUtils;import org.apache.hadoop.io.SequenceFile;import org.apache.hadoop.io.Writable;import org.apache.hadoop.util.ReflectionUtils;public class SequenceFileReadDemo{/** * @param args * @throws IOException  */public static void main(String[] args) throws IOException{// TODO Auto-generated method stubString url = args[0];Configuration conf = new Configuration();FileSystem  fs = FileSystem.get(URI.create(url),conf);Path path = new Path(url);SequenceFile.Reader reader = null;try{reader = new SequenceFile.Reader(fs,path,conf);Writable key =(Writable)ReflectionUtils.newInstance(reader.getKeyClass(), conf);Writable value =(Writable) ReflectionUtils.newInstance(reader.getValueClass(), conf);long position = reader.getPosition();while(reader.next(key,value)){String syncSeen = reader.syncSeen()? "*":"";  System.out.printf("[%s%s]\t%s\t%s\n", position, syncSeen, key, value);        position = reader.getPosition(); // beginning of next record}}finally{IOUtils.closeStream(reader);}}}

• MapFile 是经过排序的带索引的sequenceFile，可以根据键值进行查找，MapFile可以被任务是java.util.map一种持久化形式。注意它必须按顺序添加条目。