第六课 利用MapReduce将文件内容写入Hbase

    <!-- https://mvnrepository.com/artifact/org.apache.hadoop/hadoop-client -->
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-client</artifactId>
            <version>2.8.3</version>
        </dependency>
        <!-- https://mvnrepository.com/artifact/org.apache.hbase/hbase-client -->
        <dependency>
            <groupId>org.apache.hbase</groupId>
            <artifactId>hbase-client</artifactId>
            <version>1.3.1</version>
        </dependency>
        <!-- https://mvnrepository.com/artifact/org.apache.hbase/hbase-server -->
        <dependency>
            <groupId>org.apache.hbase</groupId>
            <artifactId>hbase-server</artifactId>
            <version>1.3.1</version>
        </dependency>

package com.neuedu;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.hbase.HBaseConfiguration;
import org.apache.hadoop.hbase.client.Mutation;
import org.apache.hadoop.hbase.client.Put;
import org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil;
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.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;

import java.io.IOException;

public class WordCountHbase {

    public static void main(String[] args) throws Exception {
        Configuration configuration = HBaseConfiguration.create();
        configuration.set("hbase.zookeeper.quorum","hadoop01,hadoop02,hadoop03");
        Job job = Job.getInstance(configuration);
        job.setJarByClass(WordCountHbase.class);

        job.setMapperClass(WordCountToBaseMap.class);
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(IntWritable.class);
        //这个wordcount是在Hbase中建好的表， create 'wordcount','i'
        TableMapReduceUtil.initTableReducerJob("wordcount", WordCountToBaseReduce.class, job);
        //这是上传到hdfs上的文档
        FileInputFormat.addInputPath(job, new Path("hdfs://hadoop01:8020/liushishi.love"));
        boolean completion = job.waitForCompletion(true);
        System.out.println(completion);
    }

    //定义reducer对接输出到hbase
    //reduce的输入类型KEYIN, VALUEIN
    //reduce输出的key的类型KEYOUT，写入hbase中reduce的输出key并不重要，重要的是value，value的数据会被写入hbase表，key的数据不重要
    //只需要保证reduce的输出value是put类型就可以了

    public static class WordCountToBaseMap extends Mapper<LongWritable, Text, Text, IntWritable> {
        public static IntWritable ONE = new IntWritable(1);
        public Text outputKey = new Text();
        public String[] info;

        @Override
        protected void map(LongWritable key, Text value, Mapper<LongWritable, Text, Text, IntWritable>.Context context)
                throws IOException, InterruptedException {
            String[] readline = value.toString().split("\\s+");
            for (String word : readline) {
                if (!word.equals("")) {
                    outputKey.set(word);
                    context.write(outputKey, ONE);
                }
            }
        }

    }

    public static class WordCountToBaseReduce extends TableReducer<Text, IntWritable, NullWritable> {
        public static NullWritable OUT_PUT_KEY = NullWritable.get();
        public Put outputValue;
        public int sum;

        @Override
        protected void reduce(Text key, Iterable<IntWritable> value,
                              Reducer<Text, IntWritable, NullWritable, Mutation>.Context context)
                throws IOException, InterruptedException {
            sum = 0;
            for (IntWritable intWritable : value) {
                sum += intWritable.get();
            }
            outputValue = new Put(Bytes.toBytes(key.toString()));
            outputValue.addColumn(Bytes.toBytes("i"), Bytes.toBytes("count"), Bytes.toBytes(String.valueOf(sum)));
            context.write(OUT_PUT_KEY, outputValue);
        }
    }

}