7.MapReduce操作Hbase

比眉伴天荒 2021-12-15 08:51 316阅读 0赞

## **7 HBase的MapReduce** ##

**![20160720191248566][]**

**　　HBase中Table和Region的关系，有些类似HDFS中File和Block的关系。由于HBase提供了配套的与MapReduce进行交互的API如**

**TableInputFormat和TableOutputFormat，可以将HBase的数据表直接作为Hadoop MapReduce的输入和输出，从而方便了MapReduce**

**应用程序的开发，基本不需要关注HBase系统自身的处理细节。**

### 8 **实现方法：** ###

**　　Hbase对MapReduce提供支持，它实现了TableMapper类和TableReducer类，我们只需要继承这两个类即可**

1、写个mapper继承TableMapper<Text, IntWritable>：参数：Text：mapper的输出key类型； IntWritable：mapper的输出value类型。
      其中的map方法如下：
        map(ImmutableBytesWritable key, Result value,Context context)：参数：key：rowKey；value： Result ，一行数据； context上下文
    2、写个reduce继承TableReducer<Text, IntWritable, ImmutableBytesWritable>：参数：Text:reducer的输入key； IntWritable：reduce的输入value
         ImmutableBytesWritable：reduce输出到hbase中的rowKey类型。
          其中的reduce方法如下：
        reduce(Text key, Iterable<IntWritable> values,Context context)
        参数： key：reduce的输入key；values：reduce的输入value；

**详细代码文件：　　**

import java.io.IOException;
    import java.util.ArrayList;
    import java.util.List;
    import org.apache.hadoop.conf.Configuration;
    import org.apache.hadoop.hbase.HBaseConfiguration;
    import org.apache.hadoop.hbase.HColumnDescriptor;
    import org.apache.hadoop.hbase.HTableDescriptor;
    import org.apache.hadoop.hbase.client.HBaseAdmin;
    import org.apache.hadoop.hbase.client.HTable;
    import org.apache.hadoop.hbase.client.Put;
    import org.apache.hadoop.hbase.client.Result;
    import org.apache.hadoop.hbase.client.Scan;
    import org.apache.hadoop.hbase.io.ImmutableBytesWritable;
    import org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil;
    import org.apache.hadoop.hbase.mapreduce.TableMapper;
    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.Text;
    import org.apache.hadoop.mapreduce.Job;
    /**
     * mapreduce操作hbase:创建word表，并插入数据，通过MapReduce将word表中的数据写入创建的hbase新表stat表
     */
    public class HBaseMr {
        /**
         * 创建hbase配置
         */
        static Configuration config = null;
        static {
            config = HBaseConfiguration.create();
            config.set("hbase.zookeeper.quorum", "shizhan3,shizhan5,shizhan6");
            config.set("hbase.zookeeper.property.clientPort", "2183");
        }
        /**
         * 表信息
         */
        public static final String tableName = "word";//表名1
        public static final String colf = "content";//列族
        public static final String col = "info";//列
        public static final String tableName2 = "stat";//表名2
        /**
         * 初始化表结构，及其数据
         */
        public static void initTB() {
            HTable table=null;
            HBaseAdmin admin=null;
            try {
                admin = new HBaseAdmin(config);//创建表管理
                /*删除表*/
                if (admin.tableExists(tableName)||admin.tableExists(tableName2)) {
                    System.out.println("table is already exists!");
                    admin.disableTable(tableName);
                    admin.deleteTable(tableName);
                    admin.disableTable(tableName2);
                    admin.deleteTable(tableName2);
                }
                /*创建表*/
                    HTableDescriptor desc = new HTableDescriptor(tableName);
                    HColumnDescriptor family = new HColumnDescriptor(colf);
                    desc.addFamily(family);
                    admin.createTable(desc);
                    HTableDescriptor desc2 = new HTableDescriptor(tableName2);
                    HColumnDescriptor family2 = new HColumnDescriptor(colf);
                    desc2.addFamily(family2);
                    admin.createTable(desc2);
                /*插入数据*/
                    table = new HTable(config,tableName);
                    table.setAutoFlush(false);
                    table.setWriteBufferSize(500);
                    List<Put> lp = new ArrayList<Put>();
                    Put p1 = new Put(Bytes.toBytes("1"));
                    p1.add(colf.getBytes(), col.getBytes(),    ("The Apache Hadoop software library is a framework").getBytes());
                    lp.add(p1);
                    Put p2 = new Put(Bytes.toBytes("2"));p2.add(colf.getBytes(),col.getBytes(),("The common utilities that support the other Hadoop modules").getBytes());
                    lp.add(p2);
                    Put p3 = new Put(Bytes.toBytes("3"));
                    p3.add(colf.getBytes(), col.getBytes(),("Hadoop by reading the documentation").getBytes());
                    lp.add(p3);
                    Put p4 = new Put(Bytes.toBytes("4"));
                    p4.add(colf.getBytes(), col.getBytes(),("Hadoop from the release page").getBytes());
                    lp.add(p4);
                    Put p5 = new Put(Bytes.toBytes("5"));
                    p5.add(colf.getBytes(), col.getBytes(),("Hadoop on the mailing list").getBytes());
                    lp.add(p5);
                    table.put(lp);
                    table.flushCommits();
                    lp.clear();
            } catch (Exception e) {
                e.printStackTrace();
            } finally {
                try {
                    if(table!=null){
                        table.close();
                    }
                } catch (IOException e) {
                    e.printStackTrace();
                }
            }
        }
        /**
         * MyMapper 继承 TableMapper
         * TableMapper<Text,IntWritable> 
         * Text:输出的key类型，
         * IntWritable：输出的value类型
         */
        public static class MyMapper extends TableMapper<Text, IntWritable> {
            private static IntWritable one = new IntWritable(1);
            private static Text word = new Text();
            @Override
            //输入的类型为：key：rowKey； value：一行数据的结果集Result
            protected void map(ImmutableBytesWritable key, Result value,Context context) throws IOException, InterruptedException {
                //获取一行数据中的colf：col
                String words = Bytes.toString(value.getValue(Bytes.toBytes(colf), Bytes.toBytes(col)));// 表里面只有一个列族，所以我就直接获取每一行的值
                //按空格分割
                String itr[] = words.toString().split(" ");
                //循环输出word和1
                for (int i = 0; i < itr.length; i++) {
                    word.set(itr[i]);
                    context.write(word, one);
                }
            }
        }
        /**
         * MyReducer 继承 TableReducer
         * TableReducer<Text,IntWritable> 
         * Text:输入的key类型，
         * IntWritable：输入的value类型，
         * ImmutableBytesWritable：输出类型，表示rowkey的类型
         */
        public static class MyReducer extends
                TableReducer<Text, IntWritable, ImmutableBytesWritable> {
            @Override
            protected void reduce(Text key, Iterable<IntWritable> values,
                    Context context) throws IOException, InterruptedException {
                //对mapper的数据求和
                int sum = 0;
                for (IntWritable val : values) {
        //叠加
                    sum += val.get();
                }
                // 创建put，设置rowkey为单词
                Put put = new Put(Bytes.toBytes(key.toString()));
                // 封装数据
                put.add(Bytes.toBytes(colf), Bytes.toBytes(col),Bytes.toBytes(String.valueOf(sum)));
                //写到hbase,需要指定rowkey、put
                context.write(new ImmutableBytesWritable(Bytes.toBytes(key.toString())),put);
            }
        }
        
        public static void main(String[] args) throws IOException,
                ClassNotFoundException, InterruptedException {
            //初始化表
            initTB();//初始化表
            //创建job
            Job job = new Job(config, "HBaseMr");//job
            job.setJarByClass(HBaseMr.class);//主类
            //创建scan
            Scan scan = new Scan();
            //可以指定查询某一列
            scan.addColumn(Bytes.toBytes(colf), Bytes.toBytes(col));
            //创建查询hbase的mapper，设置表名、scan、mapper类、mapper的输出key、mapper的输出value
            TableMapReduceUtil.initTableMapperJob(tableName, scan, MyMapper.class,Text.class, IntWritable.class, job);
            //创建写入hbase的reducer，指定表名、reducer类、job
            TableMapReduceUtil.initTableReducerJob(tableName2, MyReducer.class, job);
            System.exit(job.waitForCompletion(true) ? 0 : 1);
        }
    }

**运行截图：**

**![892002-20180725160332632-91295710.png][]**

**程序下载链接：[https://pan.baidu.com/s/1ofHWKNV9F-R8OcW54PGJ5g][https_pan.baidu.com_s_1ofHWKNV9F-R8OcW54PGJ5g]**

**总结：**

**　　通过Mr操作Hbase的‘word’表，对‘content：info’中的短文做词频统计，并将统计结果写入‘stat’表的‘content：info中’，**

**行键为单词**

转载于:https://www.cnblogs.com/yaboya/p/9364055.html

[20160720191248566]: /images/20211214/700aaf053caa45449deb7ca6feba7154.png
[892002-20180725160332632-91295710.png]: /images/20211214/bed76ff92c2841d49bb2337cd01267d6.png
[https_pan.baidu.com_s_1ofHWKNV9F-R8OcW54PGJ5g]: https://pan.baidu.com/s/1ofHWKNV9F-R8OcW54PGJ5g