HBase MapReduce实例分析

　　跟Hadoop的无缝集成使得使用MapReduce对HBase的数据进行分布式计算非常方便，本文将介绍HBase下 MapReduce开发要点。很好理解本文前提是你对Hadoop MapReduce有一定的了解，如果你是初次接触Hadoop MapReduce编程，可以参考 "第一个MapReduce应用" 这篇文章来建立基本概念。

一、Java代码

package hbase;
import java.io.IOException;
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.NullWritable;
import org.apache.hadoop.io.Text;
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;
public class WordCountHBase {public static class Map extendsMapper<LongWritable, Text, Text, IntWritable> {private IntWritable i = new IntWritable(1);public void map(LongWritable key, Text value, Context context)throws IOException, InterruptedException {String s[] = value.toString().trim().split(" ");// 将输入的每行以空格分开for (String m : s) {context.write(new Text(m), i);}}}public static class Reduce extendsTableReducer<Text, IntWritable, NullWritable> {public void reduce(Text key, Iterable<IntWritable> values,Context context) throws IOException, InterruptedException {int sum = 0;for (IntWritable i : values) {sum += i.get();}Put put = new Put(Bytes.toBytes(key.toString()));// Put实例化，每一个词存一行put.add(Bytes.toBytes("content"), Bytes.toBytes("count"),Bytes.toBytes(String.valueOf(sum)));// 列族为content，列为count，列值为数目context.write(NullWritable.get(), put);}}public static void createHBaseTable(String tableName) throws IOException {HTableDescriptor htd = new HTableDescriptor(tableName);HColumnDescriptor col = new HColumnDescriptor("content");htd.addFamily(col);Configuration conf = HBaseConfiguration.create();conf.set("hbase.zookeeper.quorum", "libin2");HBaseAdmin admin = new HBaseAdmin(conf);if (admin.tableExists(tableName)) {System.out.println("table exists, trying to recreate table......");admin.disableTable(tableName);admin.deleteTable(tableName);}System.out.println("create new table:" + tableName);admin.createTable(htd);}public static void main(String[] args) throws IOException,InterruptedException, ClassNotFoundException {String tableName = "WordCount";Configuration conf = new Configuration();conf.set(TableOutputFormat.OUTPUT_TABLE, tableName);createHBaseTable(tableName);String input = args[0];Job job = new Job(conf, "WordCount table with " + input);job.setJarByClass(WordCountHBase.class);job.setNumReduceTasks(3);job.setMapperClass(Map.class);job.setReducerClass(Reduce.class);job.setMapOutputKeyClass(Text.class);job.setMapOutputValueClass(IntWritable.class);job.setInputFormatClass(TextInputFormat.class);job.setOutputFormatClass(TableOutputFormat.class);FileInputFormat.addInputPath(job, new Path(input));System.exit(job.waitForCompletion(true) ? 0 : 1);}
}

二、把java代码打成jar包

如果同时用到了两个jar包，需要在两个jar包之间加一个":"分隔符。

三、运行程序

运行WordCountHBase.jar可能会报错：java.lang.NoClassDefFoundError: org/apache/hadoop/hbase/HTableDescriptor

解决方法（把hbase的核心jar包和hbase自带的Zookeeperjar包拷贝到hadoop的安装目录\lib下，然后重启服务）：

然后再次执行

四、查看HBase表中的数据

‍

如果表中有保存好的MapReduce处理后的数据，说明成功！本文通过实例分析演示了使用MapReduce分析HBase的数据，需要注意的这只是一种常规的方式（分析表中的数据存到另外的表中），实际上不局限于此，不过其他方式跟此类似。