= 範例六：WordCountHBase = 

 == 說明：  ==
	此程式碼將輸入路徑的檔案內的字串取出做字數統計,再將結果塞回HTable內
 == 執行方法 ==

[raw-attachment:wiki:NCHCCloudCourse100204:tsmcHBase_100204.jar 測試用打包檔 tsmcHBase_100204.jar]

{{{
$ /opt/hadoop/bin/hadoop jar tsmcHBase_100204.jar CountToHBaseReducer
}}}


 == 結果： ==
{{{
$ hbase shell
	> scan 'wordcount'
 	ROW	COLUMN+CELL 
	am	column=content:count, timestamp=1264406245488, value=1
        chen	column=content:count, timestamp=1264406245488, value=1 
 	hi,	column=content:count, timestamp=1264406245488, value=2
  ......(略)
}}}
 == 注意： ==

1.	在hdfs 上來源檔案的路徑為 "/user/$YOUR_NAME/input"

	請注意必須先放資料到此hdfs上的資料夾內，且此資料夾內只能放檔案，不可再放資料夾

2.	運算完後，程式將執行結果放在hbase的wordcount資料表內

 == 參考： ==

1.程式碼改編於： http://blog.ring.idv.tw/comment.ser?i=337

2.hbase 運作 mapreduce 程式的方法參考於：http://wiki.apache.org/hadoop/Hbase/MapReduce

 == 程式碼 ==

{{{
#!java
package tsmc;

import java.io.IOException;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
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.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 CountToHBaseReducer {
	public static class HtMap extends
			Mapper<LongWritable, Text, Text, IntWritable> {
		private IntWritable one = new IntWritable(1);

		public void map(LongWritable key, Text value, Context context)
				throws IOException, InterruptedException {
			// 輸入的字串先轉換成小寫再用空白區隔
			String s[] = value.toString().toLowerCase().trim().split(" ");
			for (String m : s) {
				// 寫入到輸出串流
				context.write(new Text(m), one);
			}
		}
	}

	// TableReducer<KEYIN,VALUEIN,KEYOUT>
	// 原本為 TableReducer<Text, IntWritable, NullWritable >
	// 但在此改成 LongWritable 也可以
	// 因此證明在此的Class可以很多,org.apache.hadoop.io.* 內有write()的Writable class應該皆可
	public static class HtReduce extends
			TableReducer<Text, IntWritable, LongWritable> {

		public void reduce(Text key, Iterable<IntWritable> values,
				Context context) throws IOException, InterruptedException {
			int sum = 0;
			for (IntWritable i : values) {
				sum += i.get();
			}

			// org.apache.hadoop.hbase.client.Put
			// Used to perform Put operations for a single row.
			// new Put(byte[] row)
			Put put = new Put(Bytes.toBytes(key.toString()));

			// add(byte[] family, byte[] qualifier, byte[] value)
			// 在main設定output format class 為 TableOutputFormat
			// TableReducer 內有定義 output Key class 必須為 Put 或 Delete
			put.add(Bytes.toBytes("content"), Bytes.toBytes("count"), Bytes
					.toBytes(String.valueOf(sum)));

			// NullWritable.get(): Returns the single instance of this class.
			// NullWritable.write(): Serialize the fields of this object to out.
			context.write(new LongWritable(), put);
			// context.write(NullWritable.get(), put)
		}
	}

	public static void main(String args[]) throws Exception {
		// debug
		String[] argv = { "/user/waue/input" };
		args = argv;
		String input = args[0];

		String tablename = "wordcount";
		String family = "content";

		Configuration conf = new Configuration();
		// OUTPUT_TABLE = "hbase.mapred.outputtable"
		// conf.set 用於設定 如 core-site.xml 的 name 與 value
		// 告訴程式 hbase.mapred.outputtable --> wordcount
		conf.set(TableOutputFormat.OUTPUT_TABLE, tablename);
		// 建立hbase 的table 否則沒先建立會出錯
		CreateTable.createHBaseTable(tablename, family);

		Job job = new Job(conf, "WordCount table with " + input);

		job.setJarByClass(CountToHBaseReducer.class);

		job.setMapperClass(HtMap.class);
		job.setReducerClass(HtReduce.class);
		// 此範例的輸出為 <Text,IntWritable> 因此其實可以省略宣告
		// set{Map|Reduce}Output{Key|Value}Class()
		job.setMapOutputKeyClass(Text.class);
		job.setMapOutputValueClass(IntWritable.class);
		// InputFormat 只有一個子介面
		// FileInputFormat <-(SequenceFileInputFormat,TextInputFormat)
		// 其中TextInputFormat 最常用 ，預設輸入為 LongWritable,Text
		// 另外HBase 則設計了一個子類別 TableInputFormat
		job.setInputFormatClass(TextInputFormat.class);
		// TAbleOutputFormat
		// 宣告此行則可使 reduce 輸出為 HBase 的table
		job.setOutputFormatClass(TableOutputFormat.class);

		// 原本設定輸入檔案為 Config.setInputPath(Path) 卻改為
		// FileInputFormat.addInputPath(Job, Path()) 的設計，
		// 猜測應該是考慮某些檔案操作並不需要跑mapreduce的Job，因此提到外面
		FileInputFormat.addInputPath(job, new Path(input));

		System.exit(job.waitForCompletion(true) ? 0 : 1);
	}
}
}}}