ITRI HBase 進階課程

HBase 範例

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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
• 請注意在將hbase 等函式庫放入hadoop 的lib 目錄後，必須重新啟動hbase 與 hadoop 再執行此範例程式才不會出現錯誤

$ bin/hadoop dfs -mkdir input
$ bin/hadoop dfs -put README.txt input
$ bin/hadoop jar ItriMenu.jar CountToHBaseReducer input

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

程式碼

package itri;


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;
import org.apache.hadoop.util.GenericOptionsParser;

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("word"), Bytes
          .toBytes(key.toString()));
      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 argv[]) throws Exception {
//    String[] argc = {"input"};  argv = argc ; // in hdfs
    
    Configuration conf = new Configuration();
    String[] otherArgs = new GenericOptionsParser(conf, argv)
        .getRemainingArgs();
    if (otherArgs.length < 1) {
      System.out.println("CountToHBaseReducer <inHdfsDir> ");
      return;
    }
    
    String input = otherArgs[0];
    
    String tablename = "wordcounthbase";


    // 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, "content");

    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);
  }
}

執行測試

$ /opt/hbase/bin/hbase shell
hbase(main):x:0> list
wordcount                                                                                                     
1 row(s) in 0.0240 seconds
hbase(main):x:0> scan 'wordcount'
.....
 zeller                      column=content:count, timestamp=1285674576293, value=1                           
 zero                        column=content:count, timestamp=1285674576293, value=8                           
 zero,                       column=content:count, timestamp=1285674576293, value=2                           
 zero-compressed             column=content:count, timestamp=1285674576293, value=1              
.....
hbase(main):x:0> exit