通过hadoop实现单词的统计，并将统计结果保存到Hbase以及错误排解：org.apache.hadoop.io.compress.SnappyCodec not found

通过hadoop实现单词的统计，并将统计结果保存到Hbase以及错误排解：java.lang.ClassNotFoundException: org.apache.hadoop.io.compress.SnappyCodec

设计思想：通过MR框架来统计给定文件的单词数目，然后把统计结果保存到hbase中：

程序如下：

import java.io.IOException; 
import java.util.Iterator; 
import java.util.StringTokenizer; 
 
import org.apache.hadoop.conf.Configuration; 
import org.apache.hadoop.fs.Path; 
import org.apache.hadoop.hbase.HBaseConfiguration; 
import org.apache.hadoop.hbase.HColumnDescriptor; 
import org.apache.hadoop.hbase.HTableDescriptor; 
import org.apache.hadoop.hbase.client.HBaseAdmin; 
import org.apache.hadoop.hbase.client.Put; 
import org.apache.hadoop.hbase.mapreduce.TableOutputFormat; 
import org.apache.hadoop.hbase.mapreduce.TableReducer; 
import org.apache.hadoop.hbase.util.Bytes; 
import org.apache.hadoop.io.IntWritable; 
import org.apache.hadoop.io.LongWritable; 
import org.apache.hadoop.io.Text; 
import org.apache.hadoop.io.NullWritable; 
import org.apache.hadoop.mapreduce.Job; 
import org.apache.hadoop.mapreduce.Mapper; 
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; 
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat; 
//import org.apache.hadoop.io.compress.SnappyCodec;
 
 
public class WordCountHBase { 
 
  // 实现 Map 类 
  public static class Map extends 
      Mapper<LongWritable, Text, Text, IntWritable> { 
    private final static IntWritable one = new IntWritable(1); 
    private Text word = new Text(); 
 
    public void map(LongWritable 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); 
      } 
    } 
  } 
 
  // 实现 Reduce 类 
  public static class Reduce extends 
      TableReducer<Text, IntWritable, NullWritable> { 
 
    public void reduce(Text key, Iterable<IntWritable> values, 
        Context context) throws IOException, InterruptedException { 
 
      int sum = 0; 
 
      /* Iterator<IntWritable> iterator = values.iterator(); 
      while (iterator.hasNext()) { 
        sum += iterator.next().get(); 
      } 
      */
      for (IntWritable val : values) {
          sum += val.get();
        }
 
      // Put 实例化，每个词存一行 
      Put put = new Put(Bytes.toBytes(key.toString())); 
      // 列族为 content，列修饰符为 count，列值为数目 
      put.add(Bytes.toBytes("content"), Bytes.toBytes("count"), 
          Bytes.toBytes(String.valueOf(sum))); 
 
      context.write(NullWritable.get(), put); 
    } 
  } 
 
  // 创建 HBase 数据表 
  public static void createHBaseTable(String tableName)  
throws IOException { 
    // 创建表描述 
    HTableDescriptor htd = new HTableDescriptor(tableName); 
    // 创建列族描述 
    HColumnDescriptor col = new HColumnDescriptor("content"); 
    htd.addFamily(col); 
 
    // 配置 HBase 
    Configuration conf = HBaseConfiguration.create(); 
    //配置 从机
    conf.set("hbase.zookeeper.quorum", "172.16.2.34,172.16.2.54,172.16.2.57"); 
    conf.set("hbase.zookeeper.property.clientPort", "2181"); 

   //配置主机
    conf.set("hbase.master", "172.16.2.42:60000");
    HBaseAdmin hAdmin = new HBaseAdmin(conf); 
 
    if (hAdmin.tableExists(tableName)) { 
      System.out.println("该数据表已经存在，正在重新创建。"); 
      hAdmin.disableTable(tableName); 
      hAdmin.deleteTable(tableName); 
    } 
 
    System.out.println("创建表：" + tableName); 
    hAdmin.createTable(htd); 
  } 
 
  public static void main(String[] args) throws Exception { 
    String tableName = "wordcount"; 
    // one step：创建数据库表 
    WordCountHBase.createHBaseTable(tableName); 
 
    // two step：进行 MapReduce 处理 
    // 配置 hbase 
    Configuration conf = new Configuration(); 
    
    conf.set("hbase.zookeeper.quorum", "172.16.2.34,172.16.2.54,172.16.2.57"); 
    conf.set("hbase.zookeeper.property.clientPort", "2181"); 
    conf.set("hbase.master", "172.16.2.42:60000");

      //配置hadoop
       conf.set("fs.default.name", "hdfs://172.16.2.42:9000/");
        conf.set("hadoop.job.user", "hadoop");
conf.set("mapred.job.tracker", "172.16.2.42:9001");

        //eclipse提交到hadoop上  需要打包   理论上是不需要这样的，但是本人一直没弄出来
conf.set( "mapred.jar","WordCountHBase.jar"); 
    
    conf.set(TableOutputFormat.OUTPUT_TABLE, tableName); 
 
    Job job = new Job(conf, "New Word Count");