转载请写明来源地址：http://blog.csdn.net/lastsweetop/article/details/9773233
所有源码在github上，https://github.com/lastsweetop/styhadoop
使用avro在很多情况下是对原有系统的改造，框架格式都已经定义好了，我们只能直接用avro对原有数据进行整合。（如果是新建系统，最好还是用avro的datafile，下一章讲datafile）
准备工作
将一下schema保存成文件StringPair.avsc,放在src/test/resources目录下
{
"type":"record",
"name":"StringPair",
"doc":"A pair of strings",
"fields":[
{"name":"left","type":"string"},
{"name":"right","type":"string"}
]
}
引入最新版本的avro时要主要，最新的avro包为1.7.4，依赖org.codehaus.jackson:jackson-core-asl:1.8.8包，但是maven库中已经没有该版本
所以要换成其他版本
<dependency>
<groupId>org.codehaus.jackson</groupId>
<artifactId>jackson-core-asl</artifactId>
<version>1.9.9</version>
</dependency>
如果你用的时1.0.4版本的hadoop（或者其他版本），依赖于jackson-mapper-asl，如果与jackson-core-asl版本不一致就会产生找不到方法等异常你需要入引入相同版本
<dependency>
<groupId>org.codehaus.jackson</groupId>
<artifactId>jackson-mapper-asl</artifactId>
<version>1.9.9</version>
</dependency>
generic方式
这一节我们用代码讲解
package com.sweetop.styhadoop;
import junit.framework.Assert;
import org.apache.avro.Schema;
import org.apache.avro.generic.GenericData;
import org.apache.avro.generic.GenericDatumReader;
import org.apache.avro.generic.GenericDatumWriter;
import org.apache.avro.generic.GenericRecord;
import org.apache.avro.io.*;
import org.junit.Test;
import java.io.ByteArrayOutputStream;
import java.io.File;
import java.io.IOException;
/**
* Created with IntelliJ IDEA.
* User: lastsweetop
* Date: 13-8-5
* Time: 下午7:59
* To change this template use File | Settings | File Templates.
*/
public class TestGenericMapping {
@Test
public void test() throws IOException {
//将schema从StringPair.avsc文件中加载
Schema.Parser parser = new Schema.Parser();
Schema schema = parser.parse(getClass().getResourceAsStream("/StringPair.avsc"));
//根据schema创建一个record示例
GenericRecord datum = new GenericData.Record(schema);
datum.put("left", "L");
datum.put("right", "R");
ByteArrayOutputStream out = new ByteArrayOutputStream();
//DatumWriter可以将GenericRecord变成edncoder可以理解的类型
DatumWriter<GenericRecord> writer = new GenericDatumWriter<GenericRecord>(schema);
//encoder可以将数据写入流中，binaryEncoder第二个参数是重用的encoder，这里不重用，所用传空
Encoder encoder = EncoderFactory.get().binaryEncoder(out, null);
writer.write(datum,encoder);
encoder.flush();
out.close();
DatumReader<GenericRecord> reader=new GenericDatumReader<GenericRecord>(schema);
Decoder decoder=DecoderFactory.get().binaryDecoder(out.toByteArray(),null);
GenericRecord result=reader.read(null,decoder);
Assert.assertEquals("L",result.get("left").toString());
Assert.assertEquals("R",result.get("right").toString());
}
}
result.get返回的是utf-8格式，需要调用toString方法，才能和字符串一致。
specific方式
首先使用avro-maven-plugin生成代码，pom的配置
<plugin>
<groupId>org.apache.avro</groupId>
<artifactId>avro-maven-plugin</artifactId>
<version>1.7.0</version>
<executions>
<execution>
<id>schemas</id>
<phase>generate-sources</phase>
<goals>
<goal>schema</goal>
</goals>
<configuration>
<includes>
<include>StringPair.avsc</include>
</includes>
<sourceDirectory>src/test/resources</sourceDirectory>
<outputDirectory>${project.build.directory}/generated-sources/java</outputDirectory>
</configuration>
</execution>
</executions>
</plugin>
avro-maven-plugin插件绑定在generate-sources阶段，调用mvn generate-sources即可生成源代码，我们来看下生成的源代码
package com.sweetop.styhadoop;
/**
* Autogenerated by Avro
* <p/>
* DO NOT EDIT DIRECTLY
*/
@SuppressWarnings("all")
/** A pair of strings */
public class StringPair extends org.apache.avro.specific.SpecificRecordBase implements org.apache.avro.specific.SpecificRecord {
public static final org.apache.avro.Schema SCHEMA$ = new org.apache.avro.Schema.Parser().parse("{"type":"record","name":"StringPair","doc":"A pair of strings","fields":[{"name":"left","type":"string","avro.java.string":"String"},{"name":"right","type":"string"}]}");
@Deprecated
public java.lang.CharSequence left;
@Deprecated
public java.lang.CharSequence right;
public org.apache.avro.Schema getSchema() {
return SCHEMA$;
}
// Used by DatumWriter. Applications should not call.
public java.lang.Object get(int field$) {
switch (field$) {
case 0:
return left;
case 1:
return right;
default:
throw new org.apache.avro.AvroRuntimeException("Bad index");
}
}
// Used by DatumReader. Applications should not call.
@SuppressWarnings(value = "unchecked")
public void put(int field$, java.lang.Object value$) {
switch (field$) {
case 0:
left = (java.lang.CharSequence) value$;
break;
case 1:
right = (java.lang.CharSequence) value$;
break;
default:
throw new org.apache.avro.AvroRuntimeException("Bad index");
}
}
/**
* Gets the value of the 'left' field.
*/
public java.lang.CharSequence getLeft() {
return left;
}
/**
* Sets the value of the 'left' field.
*
* @param value the value to set.
*/
public void setLeft(java.lang.CharSequence value) {
this.left = value;
}
/**
* Gets the value of the 'right' field.
*/
public java.lang.CharSequence getRight() {
return right;
}
/**
* Sets the value of the 'right' field.
*
* @param value the value to set.
*/
public void setRight(java.lang.CharSequence value) {
this.right = value;
}
}
为了兼容之前的版本生成了一组get，put方法，1.6.0后生成添加了getter/setter方法，还有一个与Builder的类，没什么用已经被我删掉
另外上一篇文章有点没讲到就是schama里的name里可以使用命名空间，如com.sweetop.styhadoop.StringPair，这样生成的源代码才会是带package的
那我们来看如果使用这个生成的类，和generic方式有什么不同：
package com.sweetop.styhadoop;
import junit.framework.Assert;
import org.apache.avro.Schema;
import org.apache.avro.io.*;
import org.apache.avro.specific.SpecificDatumReader;
import org.apache.avro.specific.SpecificDatumWriter;
import org.junit.Test;
import java.io.ByteArrayOutputStream;
import java.io.IOException;
/**
* Created with IntelliJ IDEA.
* User: lastsweetop
* Date: 13-8-6
* Time: 下午2:19
* To change this template use File | Settings | File Templates.
*/
public class TestSprecificMapping {
@Test
public void test() throws IOException {
//因为已经生成StringPair的源代码，所以不再使用schema了，直接调用setter和getter即可
StringPair datum=new StringPair();
datum.setLeft("L");
datum.setRight("R");
ByteArrayOutputStream out=new ByteArrayOutputStream();
//不再需要传schema了，直接用StringPair作为范型和参数，
DatumWriter<StringPair> writer=new SpecificDatumWriter<StringPair>(StringPair.class);
Encoder encoder= EncoderFactory.get().binaryEncoder(out,null);
writer.write(datum, encoder);
encoder.flush();
out.close();
DatumReader<StringPair> reader=new SpecificDatumReader<StringPair>(StringPair.class);
Decoder decoder= DecoderFactory.get().binaryDecoder(out.toByteArray(),null);
StringPair result=reader.read(null,decoder);
Assert.assertEquals("L",result.getLeft().toString());
Assert.assertEquals("R",result.getRight().toString());
}
}
不同点总结一下， schema->StringPair.class, GenericRecord->StringPair