idea创建Maven工程，写好mapreduce程序，打成jar包，到hadoop下运行，就报错了
WARN net.NetUtils: Unable to wrap exception of type class org.apache.hadoop.ipc.RpcException: it has no (String) constructor
java.lang.NoSuchMethodException: org.apache.hadoop.ipc.RpcException.<init>(java.lang.String)
at java.lang.Class.getConstructor0(Class.java:3082)
at java.lang.Class.getConstructor(Class.java:1825)
at org.apache.hadoop.net.NetUtils.wrapWithMessage(NetUtils.java:830)
at org.apache.hadoop.net.NetUtils.wrapException(NetUtils.java:806)
at org.apache.hadoop.ipc.Client.getRpcResponse(Client.java:1549)
at org.apache.hadoop.ipc.Client.call(Client.java:1491)
at org.apache.hadoop.ipc.Client.call(Client.java:1388)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:233)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:118)
at com.sun.proxy.$Proxy9.getFileInfo(Unknown Source)
at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.getFileInfo(ClientNamenodeProtocolTranslatorPB.java:904)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:422)
at org.apache.hadoop.io.retry.RetryInvocationHandler$Call.invokeMethod(RetryInvocationHandler.java:165)
at org.apache.hadoop.io.retry.RetryInvocationHandler$Call.invoke(RetryInvocationHandler.java:157)
at org.apache.hadoop.io.retry.RetryInvocationHandler$Call.invokeOnce(RetryInvocationHandler.java:95)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:359)
at com.sun.proxy.$Proxy10.getFileInfo(Unknown Source)
at org.apache.hadoop.hdfs.DFSClient.getFileInfo(DFSClient.java:1661)
at org.apache.hadoop.hdfs.DistributedFileSystem$29.doCall(DistributedFileSystem.java:1577)
at org.apache.hadoop.hdfs.DistributedFileSystem$29.doCall(DistributedFileSystem.java:1574)
at org.apache.hadoop.fs.FileSystemLinkResolver.resolve(FileSystemLinkResolver.java:81)
at org.apache.hadoop.hdfs.DistributedFileSystem.getFileStatus(DistributedFileSystem.java:1589)
at org.apache.hadoop.fs.FileSystem.exists(FileSystem.java:1683)
at org.apache.hadoop.mapreduce.lib.output.FileOutputFormat.checkOutputSpecs(FileOutputFormat.java:163)
at org.apache.hadoop.mapreduce.JobSubmitter.checkSpecs(JobSubmitter.java:277)
at org.apache.hadoop.mapreduce.JobSubmitter.submitJobInternal(JobSubmitter.java:143)
at org.apache.hadoop.mapreduce.Job$11.run(Job.java:1570)
at org.apache.hadoop.mapreduce.Job$11.run(Job.java:1567)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1729)
at org.apache.hadoop.mapreduce.Job.submit(Job.java:1567)
at org.apache.hadoop.mapreduce.Job.waitForCompletion(Job.java:1588)
at cn.itcast.mapreduce.JobMain.run(JobMain.java:58)
at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:76)
at cn.itcast.mapreduce.JobMain.main(JobMain.java:65)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.util.RunJar.run(RunJar.java:318)
at org.apache.hadoop.util.RunJar.main(RunJar.java:232)
Exception in thread "main" java.io.IOException: Failed on local exception: org.apache.hadoop.ipc.RpcException: RPC response exceeds maximum data length; Host Details : local host is: "hadoop102/192.168.1.20"; destination host is: "hadoop102":9870;
at org.apache.hadoop.net.NetUtils.wrapException(NetUtils.java:816)
at org.apache.hadoop.ipc.Client.getRpcResponse(Client.java:1549)
at org.apache.hadoop.ipc.Client.call(Client.java:1491)
at org.apache.hadoop.ipc.Client.call(Client.java:1388)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:233)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:118)
at com.sun.proxy.$Proxy9.getFileInfo(Unknown Source)
at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.getFileInfo(ClientNamenodeProtocolTranslatorPB.java:904)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:422)
at org.apache.hadoop.io.retry.RetryInvocationHandler$Call.invokeMethod(RetryInvocationHandler.java:165)
at org.apache.hadoop.io.retry.RetryInvocationHandler$Call.invoke(RetryInvocationHandler.java:157)
at org.apache.hadoop.io.retry.RetryInvocationHandler$Call.invokeOnce(RetryInvocationHandler.java:95)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:359)
at com.sun.proxy.$Proxy10.getFileInfo(Unknown Source)
at org.apache.hadoop.hdfs.DFSClient.getFileInfo(DFSClient.java:1661)
at org.apache.hadoop.hdfs.DistributedFileSystem$29.doCall(DistributedFileSystem.java:1577)
at org.apache.hadoop.hdfs.DistributedFileSystem$29.doCall(DistributedFileSystem.java:1574)
at org.apache.hadoop.fs.FileSystemLinkResolver.resolve(FileSystemLinkResolver.java:81)
at org.apache.hadoop.hdfs.DistributedFileSystem.getFileStatus(DistributedFileSystem.java:1589)
at org.apache.hadoop.fs.FileSystem.exists(FileSystem.java:1683)
at org.apache.hadoop.mapreduce.lib.output.FileOutputFormat.checkOutputSpecs(FileOutputFormat.java:163)
at org.apache.hadoop.mapreduce.JobSubmitter.checkSpecs(JobSubmitter.java:277)
at org.apache.hadoop.mapreduce.JobSubmitter.submitJobInternal(JobSubmitter.java:143)
at org.apache.hadoop.mapreduce.Job$11.run(Job.java:1570)
at org.apache.hadoop.mapreduce.Job$11.run(Job.java:1567)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1729)
at org.apache.hadoop.mapreduce.Job.submit(Job.java:1567)
at org.apache.hadoop.mapreduce.Job.waitForCompletion(Job.java:1588)
at cn.itcast.mapreduce.JobMain.run(JobMain.java:58)
at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:76)
at cn.itcast.mapreduce.JobMain.main(JobMain.java:65)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.util.RunJar.run(RunJar.java:318)
at org.apache.hadoop.util.RunJar.main(RunJar.java:232)
Caused by: org.apache.hadoop.ipc.RpcException: RPC response exceeds maximum data length
at org.apache.hadoop.ipc.Client$IpcStreams.readResponse(Client.java:1864)
at org.apache.hadoop.ipc.Client$Connection.receiveRpcResponse(Client.java:1183)
at org.apache.hadoop.ipc.Client$Connection.run(Client.java:1079)
linux中执行的命令
hadoop jar original-day05_mapreduce-1.0-SNAPSHOT.jar cn.itcast.mapreduce.JobMain
尝试修改hdfs-site.xml中的配置
<property>
<name> ipc.maximum.data.length </ name>
<value> 134217728 </ value>
</ property>
如果已经足够确保fs.default.name的core-site.xml配置使用的是IP，而不是localhost。
<configuration>
....
<property>
<name>fs.default.name</name>
<value>hdfs://your ip:9000</value>
</property>
</configuration>
1.问题核心：
WARN net.NetUtils: Unable to wrap exception of type class org.apache.hadoop.ipc.RpcException: it has no (String) constructor
java.lang.NoSuchMethodException: org.apache.hadoop.ipc.RpcException.<init>(java.lang.String)
2.没有这样的构造函数，代码中使用到hadoop工具类的地方看一看？
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这个问题解了？我也遇到了，懵了，
你好，我也遇到了这个问题，请问你解决了吗？
这是maven pom.xml
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>cn.itcast</groupId>
<artifactId>day05_mapreduce</artifactId>
<version>1.0-SNAPSHOT</version>
<packaging>jar</packaging>
<dependencies>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-common</artifactId>
<version>3.1.3</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-client</artifactId>
<version>3.1.3</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-hdfs</artifactId>
<version>3.1.3</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-mapreduce-client-core</artifactId>
<version>3.1.3</version>
</dependency>
<dependency>
<groupId>junit</groupId>
<artifactId>junit</artifactId>
<version>RELEASE</version>
</dependency>
</dependencies>
<build>
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-compiler-plugin</artifactId>
<version>3.1</version>
<configuration>
<source>1.8</source>
<target>1.8</target>
<encoding>UTF-8</encoding>
</configuration>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-shade-plugin</artifactId>
<version>2.4.3</version>
<executions>
<execution>
<phase>package</phase>
<goals>
<goal>shade</goal>
</goals>
<configuration>
<minimizeJar>true</minimizeJar>
</configuration>
</execution>
</executions>
</plugin>
</plugins>
</build>
</project>
写了一个JobMain.java
package cn.itcast.mapreduce;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;
import java.net.URI;
public class JobMain extends Configured implements Tool {
//该方法用于指定一个job任务
@Override
public int run(String[] strings) throws Exception {
//1.创建一个job任务对象
Job job = Job.getInstance(super.getConf(), "wordcount");
//如果打包运行出错，则需要加该配置
job.setJarByClass(JobMain.class);
//2.配置job任务对象（八个步骤）
job.setInputFormatClass(TextInputFormat.class);
//第一步：指定文件的读取方式和读取路径
TextInputFormat.addInputPath
(job, new Path("hdfs://hadoop102:9870/spark/homework/homework4_mapreduce"));
//第二步：指定Map阶段的处理方式和数据类型
job.setMapperClass(WordCountMapper.class);
//设置Map阶段K2的类型
job.setMapOutputKeyClass(Text.class);
//设置Map阶段V2的类型
job.setMapOutputKeyClass(LongWritable.class);
//第三，四，五，六步：采用默认的方式
//第七步：指定Reduce阶段的处理方式和数据类型
job.setReducerClass(WordCountReducer.class);
//设置K3的类型
job.setOutputKeyClass(Text.class);
//设置V3的类型
job.setOutputValueClass(LongWritable.class);
//第八步：设置输出方式
job.setOutputFormatClass(TextOutputFormat.class);
//设置输出的路径
TextOutputFormat.setOutputPath
(job, new Path(
"hdfs://hadoop102:9870/spark/homework/homework4_mapreduce/output"
));
//获取FileSystem
FileSystem fileSystem = FileSystem.get(new URI("hdfs://hadoop102:9870"), new Configuration());
//判断目录是否存在
boolean bl2 = fileSystem.exists(new Path(
"hdfs://hadoop102:9870/spark/homework/homework4_mapreduce/output"));
if(bl2){
//删除目标目录
fileSystem.delete(new Path(
"hdfs://hadoop102:9870/spark/homework/homework4_mapreduce/output"), true);
}
//等待任务结束
boolean bl = job.waitForCompletion(true);
return bl ? 0:1;
}
public static void main(String[] args) throws Exception {
Configuration configuration = new Configuration();
//启动job任务
int run = ToolRunner.run(configuration, new JobMain(), args);
System.exit(run);
}
}
然后是WordCountMapper
package cn.itcast.mapreduce;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Counter;
import java.io.IOException;
public class WordCountMapper extends Mapper<LongWritable, Text, Text, LongWritable>{
//map方法就是将K1和V1 转为 K2和V2
/*
参数：
key ：K1 行偏移量
value ：V1 每一行的文本数据
context ：表示上下文对象
*/
/*
如何将K1和V1 转化为 K2和V2
K1 V1
0 hello,world,hadoop
15 hdfs,hive,hello
------------------------
K2 V2
hello 1
world 1
hadoop 1
hello 1
hdfs 1
*/
@Override
protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
Text text = new Text(); //创建Text对象放入K2中
LongWritable longWritable = new LongWritable(); //创建LongWritable对象放入V2中
//1.将一行的文本数据进行拆分
String[] split = value.toString().split(","); //将V1拆分
//2.遍历数组，组装K2和V2
for (String word : split){
//3.将K2和V2写入上下文中
text.set(word); //转换数据类型
longWritable.set(1); //装欢数据类型
context.write(text, longWritable);
}
}
}
WordCountReducer：
package cn.itcast.mapreduce;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;
import java.io.IOException;
/*
四个泛型解释：
KEYIN：K2类型
VALUEIN：V2类型
KEYOUT：K3类型
VALUEOUT：V3类型
*/
public class WordCountReducer extends Reducer<Text, LongWritable, Text, LongWritable>{
//reduce方法：将新的K2和V2转为K3和V3，将K3和V3写入上下文中
/*
参数：
key： 新K2
values： 集合新V2
context： 表示上下文对象
------------------------
如何将新的K2和V2转成 K3和V3
新 K2 V2
hello <1,1,1>
world <1,1>
hadoop <1>
K3 V3
hello 3
world 2
hadoop 1
*/
@Override
protected void reduce(Text key, Iterable<LongWritable> values, Context context) throws IOException, InterruptedException {
long count = 0;
//1.遍历集合，将集合中的数字相加，得到V3
for (LongWritable value: values){
count += value.get();
}
//2.将K3和V3写入上下文中的
context.write(key, new LongWritable(count));
}
}
是照着hm程序员的b站视频写的，但是人家导出jar包到hadoop中运行就没问题，我就出现问题了。。。。。
我出现这个报错是hdfs的active端口写错了，应该写core里配置的服务端口，我写错成了web访问端口，改回去就成功了。
你好，您这个问题解决了吗？我也遇到了。想请教一下