HBase 之HFileOutputFormat

 hadoop mr 输出需要导入hbase的话最好先输出成HFile格式， 再导入到HBase,因为HFile是HBase的内部存储格式， 所以导入效率很高,下面是一个示例
1. 创建HBase表t1

hbase(main):157:0* create 't1','f1'
0 row(s) in 1.3280 seconds

hbase(main):158:0> scan 't1'
ROW                   COLUMN+CELL
0 row(s) in 1.2770 seconds

 

2.写MR作业
HBaseHFileMapper.java

 

package com.test.hfile;
import java.io.IOException;
import org.apache.hadoop.hbase.io.ImmutableBytesWritable;
import org.apache.hadoop.hbase.util.Bytes;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;

public class HBaseHFileMapper extends Mapper<LongWritable, Text, ImmutableBytesWritable, Text> {
    private ImmutableBytesWritable immutableBytesWritable = new ImmutableBytesWritable();
    @Override
    protected void map(LongWritable key, Text value,
            org.apache.hadoop.mapreduce.Mapper.Context context)
            throws IOException, InterruptedException {
        immutableBytesWritable.set(Bytes.toBytes(key.get()));
        context.write(immutableBytesWritable, value);
    }
}

 

HBaseHFileReducer.java

 

package com.test.hfile;
import java.io.IOException;
import org.apache.hadoop.hbase.KeyValue;
import org.apache.hadoop.hbase.io.ImmutableBytesWritable;
import org.apache.hadoop.hbase.util.Bytes;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;

public class HBaseHFileReducer extends Reducer<ImmutableBytesWritable, Text, ImmutableBytesWritable, KeyValue> {
    protected void reduce(ImmutableBytesWritable key, Iterable<Text> values,
            Context context)
            throws IOException, InterruptedException {
        String value="";
        while(values.iterator().hasNext())
        {
            value = values.iterator().next().toString();
            if(value != null && !"".equals(value))
            {
                KeyValue kv = createKeyValue(value.toString());
                if(kv!=null)
                    context.write(key, kv);
            }
        }
    }     // str格式为row:family:qualifier:value 简单模拟下
    private KeyValue createKeyValue(String str)
    {
        String[] strstrs = str.split(":");
        if(strs.length<4)
            return null;
        String row=strs[0];
        String family=strs[1];
        String qualifier=strs[2];
        String value=strs[3];
        return new KeyValue(Bytes.toBytes(row),Bytes.toBytes(family),Bytes.toBytes(qualifier),System.currentTimeMillis(), Bytes.toBytes(value));
    }
}

 

HbaseHFileDriver.java

 

package com.test.hfile;
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.HTable;
import org.apache.hadoop.hbase.io.ImmutableBytesWritable;
import org.apache.hadoop.hbase.mapreduce.HFileOutputFormat;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.GenericOptionsParser;

public class HbaseHFileDriver {
    public static void main(String[] args) throws IOException,
            InterruptedException, ClassNotFoundException {

        Configuration conf = new Configuration();
        String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();

        Job job = new Job(conf, "testhbasehfile");
        job.setJarByClass(HbaseHFileDriver.class);

        job.setMapperClass(com.test.hfile.HBaseHFileMapper.class);
        job.setReducerClass(com.test.hfile.HBaseHFileReducer.class);

        job.setMapOutputKeyClass(ImmutableBytesWritable.class);
        job.setMapOutputValueClass(Text.class);
        // 偷懒， 直接写死在程序里了，实际应用中不能这样, 应从命令行获取
        FileInputFormat.addInputPath(job, new Path("/home/yinjie/input"));
        FileOutputFormat.setOutputPath(job, new Path("/home/yinjie/output"));

        Configuration HBASE_CONFIG = new Configuration();
        HBASE_CONFIG.set("hbase.zookeeper.quorum", "localhost");
        HBASE_CONFIG.set("hbase.zookeeper.property.clientPort", "2181");
        HBaseConfiguration cfg = new HBaseConfiguration(HBASE_CONFIG);
        String tableName = "t1";
        HTable htable = new HTable(cfg, tableName);
        HFileOutputFormat.configureIncrementalLoad(job, htable);

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

 

/home/yinjie/input目录下有一个hbasedata.txt文件,内容为

 

[root@localhost input]# cat hbasedata.txt
r1:f1:c1:value1
r2:f1:c2:value2
r3:f1:c3:value3

 

将作业打包，我的到处路径为/home/yinjie/job/hbasetest.jar
提交作业到hadoop运行:

 

[root@localhost job]# hadoop jar /home/yinjie/job/hbasetest.jar com.test.hfile.HbaseHFileDriver -libjars /home/yinjie/hbase-0.90.3/hbase-0.90.3.jar

 

作业运行完毕后查看下输出目录:

 

[root@localhost input]# hadoop fs -ls /home/yinjie/output
Found 2 items
drwxr-xr-x   - root supergroup          0 2011-08-28 21:02 /home/yinjie/output/_logs
drwxr-xr-x   - root supergroup          0 2011-08-28 21:03 /home/yinjie/output/f1

 

OK, 已经生成以列族f1命名的文件夹了。
接下去使用Bulk Load将数据导入到HBbase

 

[root@localhost job]# hadoop jar /home/yinjie/hbase-0.90.3/hbase-0.90.3.jar completebulkload /home/yinjie/output t1

 

导入完毕，查询hbase表t1进行验证

 

hbase(main):166:0> scan 't1'
ROW                              COLUMN+CELL
 r1                              column=f1:c1, timestamp=1314591150788, value=value1
 r2                              column=f1:c2, timestamp=1314591150814, value=value2
 r3                              column=f1:c3, timestamp=1314591150815, value=value3
3 row(s) in 0.0210 seconds

数据已经导入!

 

出自：http://yaoyinjie.blog.51cto.com/3189782/652244