• 一个完整的MapReduce程序


    最近初学Hadoop,仿照参考书上编写了一个wordcount程序,本文主要解决运行过程中出现的一些问题,下边先看一下这个项目。

    项目结构



    WordMapper类

    package wordcount;
    
    import java.io.IOException;
    import java.util.StringTokenizer;
    import org.apache.hadoop.io.IntWritable;
    import org.apache.hadoop.io.Text;
    import org.apache.hadoop.mapreduce.Mapper;
    
    public class WordMapper extends Mapper<Object, Text, Text, IntWritable> {
    
        private final static IntWritable one = new IntWritable(1);
        private Text word = new Text();
    
        public void map(Object key, Text value, Context context)
                throws IOException, InterruptedException {
            StringTokenizer itr = new StringTokenizer(value.toString());
            while (itr.hasMoreTokens()) {
                word.set(itr.nextToken());
                context.write(word, one);
            }
        }
    
    }

    WordReducer类

    package wordcount;
    
    import java.io.IOException;
    
    import org.apache.hadoop.io.IntWritable;
    import org.apache.hadoop.io.Text;
    import org.apache.hadoop.mapreduce.Reducer;
    
    public class WordReducer extends Reducer<Text, IntWritable, Text, IntWritable> {
    
        private IntWritable result = new IntWritable();
    
        public void reduce(Text key, Iterable<IntWritable> values, Context context)
                throws IOException, InterruptedException {
            int sum = 0;
            for (IntWritable val : values) {
                sum += val.get();
            }
            result.set(sum);
            context.write(key, result);
        }
    }
    

    WordMain类

    package wordcount;
    
    import org.apache.hadoop.conf.Configuration;
    import org.apache.hadoop.fs.Path;
    import org.apache.hadoop.io.IntWritable;
    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;
    import org.apache.hadoop.util.GenericOptionsParser;
    
    public class WordMain {
        public static void main(String[] args) throws Exception {
            Configuration conf = new Configuration();
            String[] otherArgs = new GenericOptionsParser(conf, args)
                    .getRemainingArgs();
            if (otherArgs.length != 2) {
                System.out.println("Usage:wordcount<in> <out>");
                System.exit(2);
            }
            Job job = new Job(conf, "word count");
            job.setJarByClass(WordMain.class);
            job.setMapperClass(WordMapper.class);
            job.setCombinerClass(WordReducer.class);
            job.setReducerClass(WordReducer.class);
            job.setOutputKeyClass(Text.class);
            job.setOutputValueClass(IntWritable.class);
            FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
            FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
            System.exit(job.waitForCompletion(true) ? 0 : 1);
        }
    
    }
    

    统计单词存放文件

    file1.txt

    Hello, i love coding
    are you ok?
    Hello, i love hadoop
    are you ok?

    file2.txt

    Hello i love coding
    are you ok?
    Hello i love hadoop
    are you ok?

    将wordcount打包





    只选择src


    设置WordMain为启动类

    导入相关文件到虚拟机

    在linux的opt文件下新建一个file文件,将file1.txt和file2.txt复制进去,同时将wordcount.jar也复制到opt目录中






    运行程序

    进入hadoop的bin目录下,输入以下命令




    运行时会出现Input path does not exist错误



    这是因为没有设置路径造成的

    回到WordMain代码中



    改进后的WordMain代码:

    package wordcount;
    
    import org.apache.hadoop.conf.Configuration;
    import org.apache.hadoop.fs.Path;
    import org.apache.hadoop.io.IntWritable;
    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;
    import org.apache.hadoop.util.GenericOptionsParser;
    
    public class WordMain {
        public static void main(String[] args) throws Exception {
            Configuration conf = new Configuration();
    
            conf.set("mapred.job.tracker", "127.0.0.1:9001");
            String[] ars = new String[] { "input", "output" };
            String[] otherArgs = new GenericOptionsParser(conf, ars)
                    .getRemainingArgs();
            if (otherArgs.length != 2) {
                System.err.println("Usage: wordcount <in> <out>");
                System.exit(2);
            }
            Job job = new Job(conf, "word count");
            job.setJarByClass(WordMain.class);
            job.setMapperClass(WordMapper.class);
            job.setCombinerClass(WordReducer.class);
            job.setReducerClass(WordReducer.class);
            job.setOutputKeyClass(Text.class);
            job.setOutputValueClass(IntWritable.class);
            FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
            FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
            System.exit(job.waitForCompletion(true) ? 0 : 1);
        }
    
    }
    

    再次运行,没有错误









    Hadoop常用的几个配置文件

    core-site.xml

    <?xml version="1.0"?>
    <?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
    
    <!-- Put site-specific property overrides in this file. -->
    
    <configuration>
    <property>
      <name>hadoop.tmp.dir</name>
        <value>/hadoop</value>
        </property>
        <property>
          <name>fs.default.name</name>
            <value>hdfs://master:9000</value>
            </property>
            <property> 
              <name>dfs.name.dir</name>           
           <value>/hadoop/name</value> 
        </property>
    </configuration>

    mapred-site.xml

    <?xml version="1.0"?>
    <?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
    
    <!-- Put site-specific property overrides in this file. -->
    
    <configuration>
    <property>
        <name>mapred.job.tracker</name>  
        <value>master:9001</value>
    </property>
    <property>
        <name>mapred.system.dir</name>  
        <value>/hadoop/mapred_system</value>
    </property>
    <property>
        <name>mapred.local.dir</name>  
        <value>/hadoop/mapred_local</value>
    </property>
    </configuration>

    hdfs-site.xml

    <?xml version="1.0"?>
    <?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
    
    <!-- Put site-specific property overrides in this file. -->
    
    <configuration>
    <property>
        <name>dfs.replication</name>  
        <value>3</value>
    </property>
    <property>
        <name>dfs.data.dir</name>  
        <value>/hadoop/data</value>
    </property>
    </configuration>

    hadoop-env.sh

    这个文件中主要是配置Java路径,我的路径为/usr/java/jdk1.7.0_75

    # Set Hadoop-specific environment variables here.
    
    # The only required environment variable is JAVA_HOME.  All others are
    # optional.  When running a distributed configuration it is best to
    # set JAVA_HOME in this file, so that it is correctly defined on
    # remote nodes.
    
    # The java implementation to use.  Required.
    export JAVA_HOME=/usr/java/jdk1.7.0_75
    
    # Extra Java CLASSPATH elements.  Optional.
    # export HADOOP_CLASSPATH=
    
    # The maximum amount of heap to use, in MB. Default is 1000.
    # export HADOOP_HEAPSIZE=2000
    
    # Extra Java runtime options.  Empty by default.
    # export HADOOP_OPTS=-server
    
    # Command specific options appended to HADOOP_OPTS when specified
    export HADOOP_NAMENODE_OPTS="-Dcom.sun.management.jmxremote $HADOOP_NAMENODE_OPTS"
    export HADOOP_SECONDARYNAMENODE_OPTS="-Dcom.sun.management.jmxremote $HADOOP_SECONDARYNAMENODE_OPTS"
    export HADOOP_DATANODE_OPTS="-Dcom.sun.management.jmxremote $HADOOP_DATANODE_OPTS"
    export HADOOP_BALANCER_OPTS="-Dcom.sun.management.jmxremote $HADOOP_BALANCER_OPTS"
    export HADOOP_JOBTRACKER_OPTS="-Dcom.sun.management.jmxremote $HADOOP_JOBTRACKER_OPTS"
    
    # export HADOOP_TASKTRACKER_OPTS=
    # The following applies to multiple commands (fs, dfs, fsck, distcp etc)
    # export HADOOP_CLIENT_OPTS
    
    # Extra ssh options.  Empty by default.
    # export HADOOP_SSH_OPTS="-o ConnectTimeout=1 -o SendEnv=HADOOP_CONF_DIR"
    
    # Where log files are stored.  $HADOOP_HOME/logs by default.
    # export HADOOP_LOG_DIR=${HADOOP_HOME}/logs
    
    # File naming remote slave hosts.  $HADOOP_HOME/conf/slaves by default.
    # export HADOOP_SLAVES=${HADOOP_HOME}/conf/slaves
    
    # host:path where hadoop code should be rsync'd from.  Unset by default.
    # export HADOOP_MASTER=master:/home/$USER/src/hadoop
    
    # Seconds to sleep between slave commands.  Unset by default.  This
    # can be useful in large clusters, where, e.g., slave rsyncs can
    # otherwise arrive faster than the master can service them.
    # export HADOOP_SLAVE_SLEEP=0.1
    
    # The directory where pid files are stored. /tmp by default.
    # export HADOOP_PID_DIR=/var/hadoop/pids
    
    # A string representing this instance of hadoop. $USER by default.
    # export HADOOP_IDENT_STRING=$USER
    
    # The scheduling priority for daemon processes.  See 'man nice'.
    # export HADOOP_NICENESS=10

    /etc/hosts配置

    输入ifconfig,查看当前虚拟机IP,找到inet addr



    配置hosts,设置master为虚拟机的inet addr




    eclipse连接hdfs成功


    Eclipse运行Hadoop常见错误及解决办法

    Eclipse下搭建Hadoop开发环境

    Could not obtain block

    Too many fetch-failures

    unknown host: hadoop

    NameNode is in safe mode

    org.apache.hadoop.security.AccessControlException: Permission denied: user=d, access=WRITE, inode=”data”:zxg:supergroup:rwxr-xr-x

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  • 原文地址:https://www.cnblogs.com/ainima/p/6331805.html
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