马士兵hadoop2.7.3_mapreduce笔记

  • 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
posted @ 2017-03-31 09:58  Mr.xiaobai丶  阅读(1439)  评论(0)    收藏  举报