Hadoop学习笔记之---Hadoop I/O，

和通数据库htsjk.Com2019-12-21 22:08 来源:未知阅读:2477 评论 315 热度5

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Hadoop学习笔记之---Hadoop 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
DEFLATEa	DEFLATE	.deflate	no	no
gzip（zip）	DEFLATE	.gz(.zip)	no(yes)	no(yes)
bzip2	bzip2	.bz2	no	yes
LZO	LZO	.lzo	no	no

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 stub
String 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DataOutput
void 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 stub
String 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 stub
String 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。