Hadoop中的Yarn的Tool接口案例、Yarn 案例实操(四)
文章目录
- 17. Yarn 案例实操
- 17.4 Yarn的Tool接口案例
- 17.4.1 回顾
- 17.4.2 需求
- 17.4.3 具体步骤
- 17.4.3.1 新建Maven项目YarnDemo,pom如下
- 17.4.3.2 新建com.summer.yarn包名
- 17.4.3.3 创建类WordCount并实现Tool接口
- 17.4.3.4 新建WordCountDriver
- 17.4.3.5 将包进行打包
- 17.4.3.6 将jar包上传到Linux里
- 17.4.4 在HDFS上准备输入文件,假设为/testinput目录,向集群提交该Jar包
17. Yarn 案例实操
17.4 Yarn的Tool接口案例
17.4.1 回顾
[summer@hadoop102 hadoop-3.1.3]$ hadoop jar wc.jar com.summer.mapreduce.wordcount2.WordCountDriver /testinput /testoutput/output1
期望可以动态传参,结果报错,误认为是第一个输入参数。
[summer@hadoop102 hadoop-3.1.3]$ hadoop jar wc.jar com.summer.mapreduce.wordcount1.WordCountDriver -Dmapreduce.job.queuename=root.test /testinput /testoutput/output1
17.4.2 需求
自己写的程序也可以动态修改参数。编写Yarn的Tool接口。
17.4.3 具体步骤
17.4.3.1 新建Maven项目YarnDemo,pom如下
<?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>com.summer</groupId>
<artifactId>YarnDemo</artifactId>
<version>1.0-SNAPSHOT</version>
<properties>
<maven.compiler.source>8</maven.compiler.source>
<maven.compiler.target>8</maven.compiler.target>
</properties>
<dependencies>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-client</artifactId>
<version>3.1.3</version>
</dependency>
</dependencies>
</project>
添加依赖后记得刷新一下
17.4.3.2 新建com.summer.yarn包名
17.4.3.3 创建类WordCount并实现Tool接口
package com.summer.yarn;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.Writable;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.yarn.webapp.hamlet2.Hamlet;
import java.io.IOException;
/**
* @author Redamancy
* @create 2022-10-15 15:00
*/
public class WordCount implements Tool {
private Configuration conf;
@Override
public int run(String[] args) throws Exception {
Job job = Job.getInstance(conf);
job.setJarByClass(WordCountDriver.class);
job.setMapperClass(WordCountMapper.class);
job.setReducerClass(WordCountReducer.class);
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(IntWritable.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
FileInputFormat.setInputPaths(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
return job.waitForCompletion(true) ? 0 : 1;
}
@Override
public void setConf(Configuration configuration) {
this.conf = configuration;
}
@Override
public Configuration getConf() {
return conf;
}
// maper
public static class WordCountMapper extends Mapper<LongWritable, Text, Text, IntWritable>{
private IntWritable outV = new IntWritable(1);
private Text outK = new Text();
@Override
protected void map(LongWritable key, Text value, Mapper<LongWritable, Text, Text, IntWritable>.Context context) throws IOException, InterruptedException {
String line = value.toString();
String[] words = line.split(" ");
for (String word : words) {
outK.set(word);
context.write(outK, outV);
}
}
}
//reducer
public static class WordCountReducer extends Reducer<Text, IntWritable,Text, IntWritable>{
private IntWritable outV = new IntWritable();
@Override
protected void reduce(Text key, Iterable<IntWritable> values, Reducer<Text, IntWritable, Text, IntWritable>.Context context) throws IOException, InterruptedException {
int sum = 0;
for (IntWritable value : values) {
sum += value.get();
}
outV.set(sum);
context.write(key, outV);
}
}
}
17.4.3.4 新建WordCountDriver
package com.summer.yarn;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;
import java.util.Arrays;
/**
* @author Redamancy
* @create 2022-10-15 15:25
*/
public class WordCountDriver {
private static Tool tool;
public static void main(String[] args) throws Exception {
//1 创建配置文件
Configuration conf = new Configuration();
//2 判断是否有Tool接口
switch (args[0]){
case "wordcount":
tool = new WordCount();
break;
default:
throw new RuntimeException("no such tool: " + args[0]);
}
//3 用Tool执行程序
//Arrays.copyOfRange将老数组的元素放到新元素数组里面
int run = ToolRunner.run(conf, tool, Arrays.copyOfRange(args, 1, args.length));
System.exit(run);
}
}
17.4.3.5 将包进行打包
点击reload from Disk进行刷新
17.4.3.6 将jar包上传到Linux里
将这个复制到桌面
改名为YarnDemo,然后进行上传到Linux上
将jar包拖拽到XShell里面
17.4.4 在HDFS上准备输入文件,假设为/testinput目录,向集群提交该Jar包
[summer@hadoop102 hadoop-3.1.3]$ yarn jar YarnDemo.jar com.summer.yarn.WordCountDriver wordcount /testinput /testoutputoutput1
注意此时提交的3个参数,第一个用于生成特定的Tool,第二个和第三个为输入输出目录。此时如果我们希望加入设置参数,可以在wordcount后面添加参数,例如:
[summer@hadoop102 hadoop-3.1.3]$ yarn jar YarnDemo.jar com.summer.yarn.WordCountDriver wordcount -Dmapreduce.job.queuename=root.test /testinput /testoutput/output1
注:以上操作全部做完过后,快照回去或者手动将配置文件修改成之前的状态,因为本身资源就不够,分成了这么多,不方便以后测试。