eclipse/intellij idea 远程调试hadoop 2.6.0

很多hadoop初学者估计都我一样,由于没有足够的机器资源,只能在虚拟机里弄一个linux安装hadoop的伪分布,然后在host机上win7里使用eclipse或Intellj idea来写代码测试,那么问题来了,win7下的eclipse或intellij idea如何远程提交map/reduce任务到远程hadoop,并断点调试?

一、准备工作

1.1 在win7中,找一个目录,解压hadoop-2.6.0,本文中是D:\yangjm\Code\study\hadoop\hadoop-2.6.0 (以下用$HADOOP_HOME表示)

1.2 在win7中添加几个环境变量

HADOOP_HOME=D:\yangjm\Code\study\hadoop\hadoop-2.6.0

HADOOP_BIN_PATH=%HADOOP_HOME%\bin

HADOOP_PREFIX=D:\yangjm\Code\study\hadoop\hadoop-2.6.0

另外,PATH变量在最后追加;%HADOOP_HOME%\bin

二、eclipse远程调试

1.1 下载hadoop-eclipse-plugin插件

hadoop-eclipse-plugin是一个专门用于eclipse的hadoop插件,可以直接在IDE环境中查看hdfs的目录和文件内容。其源代码托管于github上,官网地址是 https://github.com/winghc/hadoop2x-eclipse-plugin

有兴趣的可以自己下载源码编译,百度一下N多文章,但如果只是使用 https://github.com/winghc/hadoop2x-eclipse-plugin/tree/master/release%20 这里已经提供了各种编译好的版本,直接用就行,将下载后的hadoop-eclipse-plugin-2.6.0.jar复制到eclipse/plugins目录下,然后重启eclipse就完事了

1.2 下载windows64位平台的hadoop2.6插件包(hadoop.dll,winutils.exe)

在hadoop2.6.0源码的hadoop-common-project\hadoop-common\src\main\winutils下,有一个vs.net工程,编译这个工程可以得到这一堆文件,输出的文件中,

hadoop.dll、winutils.exe 这二个最有用,将winutils.exe复制到$HADOOP_HOME\bin目录,将hadoop.dll复制到%windir%\system32目录 (主要是防止插件报各种莫名错误,比如空对象引用啥的)

注:如果不想编译,可直接下载编译好的文件 hadoop2.6(x64)V0.2.zip

1.3 配置hadoop-eclipse-plugin插件

启动eclipse,windows->show view->other

window->preferences->hadoop map/reduce 指定win7上的hadoop根目录(即:$HADOOP_HOME)

点击查看原图

然后在Map/Reduce Locations 面板中,点击小象图标

点击查看原图

添加一个Location

这个界面灰常重要,解释一下几个参数:

Location name 这里就是起个名字,随便起

Map/Reduce(V2) Master Host 这里就是虚拟机里hadoop master对应的IP地址,下面的端口对应 hdfs-site.xml里dfs.datanode.ipc.address属性所指定的端口

DFS Master Port: 这里的端口,对应core-site.xml里fs.defaultFS所指定的端口

最后的user name要跟虚拟机里运行hadoop的用户名一致,我是用hadoop身份安装运行hadoop 2.6.0的,所以这里填写hadoop,如果你是用root安装的,相应的改成root

这些参数指定好以后,点击Finish,eclipse就知道如何去连接hadoop了,一切顺利的话,在Project Explorer面板中,就能看到hdfs里的目录和文件了

可以在文件上右击,选择删除试下,通常第一次是不成功的,会提示一堆东西,大意是权限不足之类,原因是当前的win7登录用户不是虚拟机里hadoop的运行用户,解决办法有很多,比如你可以在win7上新建一个hadoop的管理员用户,然后切换成hadoop登录win7,再使用eclipse开发,但是这样太烦,最简单的办法:

hdfs-site.xml里添加

1  <property>
2     <name>dfs.permissions</name>
3     <value>false</value>
4  </property>

然后在虚拟机里,运行hadoop dfsadmin -safemode leave

保险起见,再来一个 hadoop fs -chmod 777 /

总而言之,就是彻底把hadoop的安全检测关掉(学习阶段不需要这些,正式生产上时,不要这么干),最后重启hadoop,再到eclipse里,重复刚才的删除文件操作试下,应该可以了。

1.4 创建WoldCount示例项目

新建一个项目,选择Map/Reduce Project

后面的Next就行了,然后放一上WodCount.java,代码如下:

 1 package yjmyzz;
 2 
 3 import java.io.IOException;
 4 import java.util.StringTokenizer;
 5 
 6 import org.apache.hadoop.conf.Configuration;
 7 import org.apache.hadoop.fs.Path;
 8 import org.apache.hadoop.io.IntWritable;
 9 import org.apache.hadoop.io.Text;
10 import org.apache.hadoop.mapreduce.Job;
11 import org.apache.hadoop.mapreduce.Mapper;
12 import org.apache.hadoop.mapreduce.Reducer;
13 import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
14 import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
15 import org.apache.hadoop.util.GenericOptionsParser;
16 
17 public class WordCount {
18 
19     public static class TokenizerMapper
20             extends Mapper<Object, Text, Text, IntWritable> {
21 
22         private final static IntWritable one = new IntWritable(1);
23         private Text word = new Text();
24 
25         public void map(Object key, Text value, Context context) throws IOException, InterruptedException {
26             StringTokenizer itr = new StringTokenizer(value.toString());
27             while (itr.hasMoreTokens()) {
28                 word.set(itr.nextToken());
29                 context.write(word, one);
30             }
31         }
32     }
33 
34     public static class IntSumReducer extends Reducer<Text, IntWritable, Text, IntWritable> {
35         private IntWritable result = new IntWritable();
36 
37         public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
38             int sum = 0;
39             for (IntWritable val : values) {
40                 sum += val.get();
41             }
42             result.set(sum);
43             context.write(key, result);
44         }
45     }
46 
47     public static void main(String[] args) throws Exception {
48         Configuration conf = new Configuration();        
49         String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
50         if (otherArgs.length < 2) {
51             System.err.println("Usage: wordcount <in> [<in>...] <out>");
52             System.exit(2);
53         }
54         Job job = Job.getInstance(conf, "word count");
55         job.setJarByClass(WordCount.class);
56         job.setMapperClass(TokenizerMapper.class);
57         job.setCombinerClass(IntSumReducer.class);
58         job.setReducerClass(IntSumReducer.class);
59         job.setOutputKeyClass(Text.class);
60         job.setOutputValueClass(IntWritable.class);
61         for (int i = 0; i < otherArgs.length - 1; ++i) {
62             FileInputFormat.addInputPath(job, new Path(otherArgs[i]));
63         }
64         FileOutputFormat.setOutputPath(job,
65                 new Path(otherArgs[otherArgs.length - 1]));
66         System.exit(job.waitForCompletion(true) ? 0 : 1);
67     }
68 }
View Code

然后再放一个log4j.properties,内容如下:(为了方便运行起来后,查看各种输出)

 1 log4j.rootLogger=INFO, stdout
 2 
 3 #log4j.logger.org.springframework=INFO
 4 #log4j.logger.org.apache.activemq=INFO
 5 #log4j.logger.org.apache.activemq.spring=WARN
 6 #log4j.logger.org.apache.activemq.store.journal=INFO
 7 #log4j.logger.org.activeio.journal=INFO
 8 
 9 log4j.appender.stdout=org.apache.log4j.ConsoleAppender
10 log4j.appender.stdout.layout=org.apache.log4j.PatternLayout
11 log4j.appender.stdout.layout.ConversionPattern=%d{ABSOLUTE} | %-5.5p | %-16.16t | %-32.32c{1} | %-32.32C %4L | %m%n
View Code

最终的目录结构如下:

然后可以Run了,当然是不会成功的,因为没给WordCount输入参数,参考下图:

1.5 设置运行参数

点击查看原图

因为WordCount是输入一个文件用于统计单词字,然后输出到另一个文件夹下,所以给二个参数,参考上图,在Program arguments里,输入

hdfs://172.28.20.xxx:9000/jimmy/input/README.txt
hdfs://172.28.20.xxx:9000/jimmy/output/

大家参考这个改一下(主要是把IP换成自己虚拟机里的IP),注意的是,如果input/READM.txt文件没有,请先手动上传,然后/output/ 必须是不存在的,否则程序运行到最后,发现目标目录存在,也会报错,这个弄完后,可以在适当的位置打个断点,终于可以调试了:

点击查看原图

三、intellij idea 远程调试hadoop

3.1 创建一个maven的WordCount项目

pom文件如下:

 1 <?xml version="1.0" encoding="UTF-8"?>
 2 <project xmlns="http://maven.apache.org/POM/4.0.0"
 3          xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
 4          xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
 5     <modelVersion>4.0.0</modelVersion>
 6 
 7     <groupId>yjmyzz</groupId>
 8     <artifactId>mapreduce-helloworld</artifactId>
 9     <version>1.0-SNAPSHOT</version>
10 
11     <dependencies>
12         <dependency>
13             <groupId>org.apache.hadoop</groupId>
14             <artifactId>hadoop-common</artifactId>
15             <version>2.6.0</version>
16         </dependency>
17         <dependency>
18             <groupId>org.apache.hadoop</groupId>
19             <artifactId>hadoop-mapreduce-client-jobclient</artifactId>
20             <version>2.6.0</version>
21         </dependency>
22         <dependency>
23             <groupId>commons-cli</groupId>
24             <artifactId>commons-cli</artifactId>
25             <version>1.2</version>
26         </dependency>
27     </dependencies>
28 
29     <build>
30         <finalName>${project.artifactId}</finalName>
31     </build>
32 
33 </project>
View Code

项目结构如下:

项目上右击-》Open Module Settings 或按F12,打开模块属性

添加依赖的Libary引用

点击查看原图

然后把$HADOOP_HOME下的对应包全导进来

点击查看原图

导入的libary可以起个名称,比如hadoop2.6

点击查看原图

3.2 设置运行参数

点击查看原图

注意二个地方:

1是Program aguments,这里跟eclipes类似的做法,指定输入文件和输出文件夹

2是Working Directory,即工作目录,指定为$HADOOP_HOME所在目录

然后就可以调试了

点击查看原图

intellij下唯一不爽的,由于没有类似eclipse的hadoop插件,每次运行完wordcount,下次再要运行时,只能手动命令行删除output目录,再行调试。为了解决这个问题,可以将WordCount代码改进一下,在运行前先删除output目录,见下面的代码:

 1 package yjmyzz;
 2 
 3 import java.io.IOException;
 4 import java.util.StringTokenizer;
 5 
 6 import org.apache.hadoop.conf.Configuration;
 7 import org.apache.hadoop.fs.FileSystem;
 8 import org.apache.hadoop.fs.Path;
 9 import org.apache.hadoop.io.IntWritable;
10 import org.apache.hadoop.io.Text;
11 import org.apache.hadoop.mapreduce.Job;
12 import org.apache.hadoop.mapreduce.Mapper;
13 import org.apache.hadoop.mapreduce.Reducer;
14 import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
15 import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
16 import org.apache.hadoop.util.GenericOptionsParser;
17 
18 public class WordCount {
19 
20     public static class TokenizerMapper
21             extends Mapper<Object, Text, Text, IntWritable> {
22 
23         private final static IntWritable one = new IntWritable(1);
24         private Text word = new Text();
25 
26         public void map(Object key, Text value, Context context) throws IOException, InterruptedException {
27             StringTokenizer itr = new StringTokenizer(value.toString());
28             while (itr.hasMoreTokens()) {
29                 word.set(itr.nextToken());
30                 context.write(word, one);
31             }
32         }
33     }
34 
35     public static class IntSumReducer extends Reducer<Text, IntWritable, Text, IntWritable> {
36         private IntWritable result = new IntWritable();
37 
38         public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
39             int sum = 0;
40             for (IntWritable val : values) {
41                 sum += val.get();
42             }
43             result.set(sum);
44             context.write(key, result);
45         }
46     }
47 
48 
49     /**
50      * 删除指定目录
51      *
52      * @param conf
53      * @param dirPath
54      * @throws IOException
55      */
56     private static void deleteDir(Configuration conf, String dirPath) throws IOException {
57         FileSystem fs = FileSystem.get(conf);
58         Path targetPath = new Path(dirPath);
59         if (fs.exists(targetPath)) {
60             boolean delResult = fs.delete(targetPath, true);
61             if (delResult) {
62                 System.out.println(targetPath + " has been deleted sucessfullly.");
63             } else {
64                 System.out.println(targetPath + " deletion failed.");
65             }
66         }
67 
68     }
69 
70     public static void main(String[] args) throws Exception {
71         Configuration conf = new Configuration();
72         String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
73         if (otherArgs.length < 2) {
74             System.err.println("Usage: wordcount <in> [<in>...] <out>");
75             System.exit(2);
76         }
77 
78         //先删除output目录
79         deleteDir(conf, otherArgs[otherArgs.length - 1]);
80 
81         Job job = Job.getInstance(conf, "word count");
82         job.setJarByClass(WordCount.class);
83         job.setMapperClass(TokenizerMapper.class);
84         job.setCombinerClass(IntSumReducer.class);
85         job.setReducerClass(IntSumReducer.class);
86         job.setOutputKeyClass(Text.class);
87         job.setOutputValueClass(IntWritable.class);
88         for (int i = 0; i < otherArgs.length - 1; ++i) {
89             FileInputFormat.addInputPath(job, new Path(otherArgs[i]));
90         }
91         FileOutputFormat.setOutputPath(job,
92                 new Path(otherArgs[otherArgs.length - 1]));
93         System.exit(job.waitForCompletion(true) ? 0 : 1);
94     }
95 }
View Code

 但是光这样还不够,在IDE环境中运行时,IDE需要知道去连哪一个hdfs实例(就好象在db开发中,需要在配置xml中指定DataSource一样的道理),将$HADOOP_HOME\etc\hadoop下的core-site.xml,复制到resouces目录下,类似下面这样:

里面的内容如下:

<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration>
    <property>
        <name>fs.defaultFS</name>
        <value>hdfs://172.28.20.***:9000</value>
    </property>
</configuration>

上面的IP换成虚拟机里的IP即可

 

posted @ 2015-05-19 16:22  菩提树下的杨过  阅读(...)  评论(... 编辑 收藏