.Hbase批量导入数据应用

1.创建一个hadoop项目（导入hadoop相关包，hbase-0.90.5.jar，zookeeper-3.3.2.jar）

2.创建测试数据(2.txt 上传至hdfs://127.0.0.1:9000/tmp/2.txt)

1150,content,email,xx@gmail.com
1152,content,email,xx@cc.com

3.创建Hbase表(input_tb)

hbase shell>create 'input_tb','content' ---input_tb为表名 content为存储单位--族名

4.导入数据代码

SampleUploader.java

/**
* Copyright 2009 The Apache Software Foundation
*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
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.client.Put;
import org.apache.hadoop.hbase.io.ImmutableBytesWritable;
import org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil;
import org.apache.hadoop.hbase.util.Bytes;
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.SequenceFileInputFormat;
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
import org.apache.hadoop.util.GenericOptionsParser;

/**
* Sample Uploader MapReduce
* 
* This is EXAMPLE code. You will need to change it to work for your context.
* 
* Uses mailto:%7B@link TableReducer} to put the data into HBase. Change the InputFormat
* to suit your data. In this example, we are importing a CSV file.
* 
* <pre>row,family,qualifier,value</pre>
* 
* The table and columnfamily we're to insert into must preexist.
* 
* There is no reducer in this example as it is not necessary and adds
* significant overhead. If you need to do any massaging of data before
* inserting into HBase, you can do this in the map as well.
* Do the following to start the MR job:
* <pre>
* ./bin/hadoop org.apache.hadoop.hbase.mapreduce.SampleUploader /tmp/input.csv TABLE_NAME
* </pre>
* 
* This code was written against HBase 0.21 trunk.
*/
public class SampleUploader {

private static final String NAME = "SampleUploader";

static class Uploader
extends Mapper<LongWritable, Text, ImmutableBytesWritable, Put> {

    private long checkpoint = 100;
    private long count = 0;

    @Override
    public void map(LongWritable key, Text line, Context context)
    throws IOException {

      // Input is a CSV file
      // Each map() is a single line, where the key is the line number
      // Each line is comma-delimited; row,family,qualifier,value

      // Split CSV line
       java.util.Random r=new java.util.Random();

      String [] values = line.toString().split(",");
      System.out.println(r.nextInt());
   System.out.println(line.toString());

      if(values.length != 4) {
        return;
      }

      // Extract each value
      byte [] row = Bytes.toBytes(values[0]);
      byte [] family = Bytes.toBytes(values[1]);
      byte [] qualifier = Bytes.toBytes(values[2]);
      byte [] value = Bytes.toBytes(values[3]);

      // Create Put
      Put put = new Put(row);
      put.add(family, qualifier, value);

      // Uncomment below to disable WAL. This will improve performance but means
      // you will experience data loss in the case of a RegionServer crash.
      // put.setWriteToWAL(false);

      try {
        context.write(new ImmutableBytesWritable(row), put);
      } catch (InterruptedException e) {
        e.printStackTrace();
      }

      // Set status every checkpoint lines
      if(++count % checkpoint == 0) {
        context.setStatus("Emitting Put " + count);
      }
    }
}

/**
   * Job configuration.
   */
public static Job configureJob(Configuration conf, String [] args)
throws IOException {
    Path inputPath = new Path(args[0]);
    String tableName = args[1];
    Job job = new Job(conf, NAME + "_" + tableName);
    job.setJarByClass(Uploader.class);
    FileInputFormat.setInputPaths(job, inputPath);
    job.setInputFormatClass(TextInputFormat.class);
    job.setMapperClass(Uploader.class);
    // No reducers. Just write straight to table. Call initTableReducerJob
    // because it sets up the TableOutputFormat.
    TableMapReduceUtil.initTableReducerJob(tableName, null, job);
    job.setNumReduceTasks(0);
    return job;
}

/**
 * Main entry point.
 *
 * @param args The command line parameters.
 * @throws Exception When running the job fails.
 */
public static void main(String[] args) throws Exception {
 Configuration conf = HBaseConfiguration.create();
 String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
 if(otherArgs.length != 2) {
 System.err.println("Wrong number of arguments: " + otherArgs.length);
 System.err.println("Usage: " + NAME + " <input> <tablename>");
 System.exit(-1);
 }
 Job job = configureJob(conf, otherArgs);
 System.exit(job.waitForCompletion(true) ? 0 : 1);
}
}

5.hbase shell >scan 'input_tb'

即可看到所有导入的记录（2.txt）