马士兵hadoop2.7.3_mapreduce笔记

标签：stdout   cli   pat   2.7   test   oss   inpu   int   服务器   

• java开发map_reduce程序
• 配置系统环境变量HADOOP_HOME，指向hadoop安装目录（如果你不想招惹不必要的麻烦，不要在目录中包含空格或者中文字符）
  把HADOOP_HOME/bin加到PATH环境变量（非必要，只是为了方便）
• 如果是在windows下开发，需要添加windows的库文件
  1. 把盘中共享的bin目录覆盖HADOOP_HOME/bin
  2. 如果还是不行，把其中的hadoop.dll复制到c:\windows\system32目录下，可能需要重启机器
• 建立新项目，引入hadoop需要的jar文件
• 代码WordMapper：     

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  import java.io.IOException; import org.apache.hadoop.io.IntWritable; import org.apache.hadoop.io.LongWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.Mapper;     public class WordMapper extends Mapper<LongWritable,Text, Text, IntWritable> {       @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) {             context.write(new Text(word), new IntWritable(1));         }     }       }

• 代码WordReducer：

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  import java.io.IOException; import org.apache.hadoop.io.IntWritable; import org.apache.hadoop.io.LongWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.Reducer;   public class WordReducer extends Reducer<Text, IntWritable, Text, LongWritable> {       @Override     protected void reduce(Text key, Iterable<IntWritable> values,             Reducer<Text, IntWritable, Text, LongWritable>.Context context) throws IOException, InterruptedException {         long count = 0;         for(IntWritable v : values) {             count += v.get();         }         context.write(key, new LongWritable(count));     }       }

• 代码Test：

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  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.mapreduce.Job; import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;     public class Test {     public static void main(String[] args) throws Exception {         Configuration conf = new Configuration();                                   Job job = Job.getInstance(conf);                   job.setMapperClass(WordMapper.class);         job.setReducerClass(WordReducer.class);         job.setMapOutputKeyClass(Text.class);         job.setMapOutputValueClass(IntWritable.class);         job.setOutputKeyClass(Text.class);         job.setOutputValueClass(LongWritable.class);                   FileInputFormat.setInputPaths(job, "c:/bigdata/hadoop/test/test.txt");         FileOutputFormat.setOutputPath(job, new Path("c:/bigdata/hadoop/test/out/"));                   job.waitForCompletion(true);     } }

• 把hdfs中的文件拉到本地来运行

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  FileInputFormat.setInputPaths(job, "hdfs://master:9000/wcinput/"); FileOutputFormat.setOutputPath(job, new Path("hdfs://master:9000/wcoutput2/"));

  注意这里是把hdfs文件拉到本地来运行，如果观察输出的话会观察到jobID带有local字样
  同时这样的运行方式是不需要yarn的(自己停掉yarn服务做实验)
• 在远程服务器执行

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  conf.set("fs.defaultFS", "hdfs://master:9000/");   conf.set("mapreduce.job.jar", "target/wc.jar"); conf.set("mapreduce.framework.name", "yarn"); conf.set("yarn.resourcemanager.hostname", "master"); conf.set("mapreduce.app-submission.cross-platform", "true");

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  FileInputFormat.setInputPaths(job, "/wcinput/"); FileOutputFormat.setOutputPath(job, new Path("/wcoutput3/"));

  如果遇到权限问题，配置执行时的虚拟机参数-DHADOOP_USER_NAME=root
• 也可以将hadoop的四个配置文件拿下来放到src根目录下，就不需要进行手工配置了，默认到classpath目录寻找
• 或者将配置文件放到别的地方，使用conf.addResource(.class.getClassLoader.getResourceAsStream)方式添加，不推荐使用绝对路径的方式
• 建立maven-hadoop项目：

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  <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>mashibing.com</groupid>   <artifactid>maven</artifactid>   <version>0.0.1-SNAPSHOT</version>   <name>wc</name>   <description>hello mp</description>           <properties>         <project.build.sourceencoding>UTF-8</project.build.sourceencoding>         <hadoop.version>2.7.3</hadoop.version>     </properties>     <dependencies>         <dependency>             <groupId>junit</groupId>             <artifactId>junit</artifactId>             <version>4.12</version>         </dependency>         <dependency>             <groupId>org.apache.hadoop</groupId>             <artifactId>hadoop-client</artifactId>             <version>${hadoop.version}</version>         </dependency>         <dependency>             <groupId>org.apache.hadoop</groupId>             <artifactId>hadoop-common</artifactId>             <version>${hadoop.version}</version>         </dependency>         <dependency>             <groupId>org.apache.hadoop</groupId>             <artifactId>hadoop-hdfs</artifactId>             <version>${hadoop.version}</version>         </dependency>     </dependencies>         </project>

• 配置log4j.properties，放到src/main/resources目录下

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  log4j.rootCategory=INFO, stdout   log4j.appender.stdout=org.apache.log4j.ConsoleAppender   log4j.appender.stdout.layout=org.apache.log4j.PatternLayout   log4j.appender.stdout.layout.ConversionPattern=[QC] %p [%t] %C.%M(%L) | %m%n

马士兵hadoop2.7.3_mapreduce笔记

标签：stdout   cli   pat   2.7   test   oss   inpu   int   服务器   

原文地址：http://www.cnblogs.com/Jxiaobai/p/6649827.html