通过mapreduce把mysql的数据读取到hdfs

时间：2021-03-03 08:04:02

前面讲过了怎么通过mapreduce把mysql的一张表的数据放到另外一张表中，这次讲的是把mysql的数据读取到hdfs里面去

具体怎么搭建环境我这里就不多说了。参考

通过mapreduce把mysql的一张表的数据导到另外一张表中

也在eclipse里面创建一个mapreduce工程

通过mapreduce把mysql的数据读取到hdfs

具体的实现代码

package com.gong.mrmysql;

import java.io.DataInput;

import java.io.DataOutput;

import java.io.IOException;

import java.sql.PreparedStatement;

import java.sql.ResultSet;

import java.sql.SQLException;

import java.util.Iterator;

import org.apache.hadoop.filecache.DistributedCache;

import org.apache.hadoop.fs.FileSystem;

import org.apache.hadoop.fs.Path;

import org.apache.hadoop.io.LongWritable;

import org.apache.hadoop.io.Text;

import org.apache.hadoop.io.Writable;

import org.apache.hadoop.mapred.FileOutputFormat;

import org.apache.hadoop.mapred.JobClient;

import org.apache.hadoop.mapred.JobConf;

import org.apache.hadoop.mapred.MapReduceBase;

import org.apache.hadoop.mapred.Mapper;

import org.apache.hadoop.mapred.OutputCollector;

import org.apache.hadoop.mapred.Reducer;

import org.apache.hadoop.mapred.Reporter;

import org.apache.hadoop.mapred.lib.IdentityReducer;

import org.apache.hadoop.mapred.lib.db.DBConfiguration;

import org.apache.hadoop.mapred.lib.db.DBInputFormat;

import org.apache.hadoop.mapred.lib.db.DBOutputFormat;

import org.apache.hadoop.mapred.lib.db.DBWritable;

/**

* Function: 测试 mr 与 mysql 的数据交互，此测试用例将一个表中的数据复制到另一张表中

*                          实际当中，可能只需要从 mysql 读，或者写到 mysql 中。

* date: 2013-7-29 上午2:34:04 <br/>

* @author june

*/

public class Mysql2Mr {

        // DROP TABLE IF EXISTS `hadoop`.`studentinfo`;

        // CREATE TABLE studentinfo (

        // id INTEGER NOT NULL PRIMARY KEY,

        // name VARCHAR(32) NOT NULL);

        public static class StudentinfoRecord implements Writable, DBWritable {

                int id;

                String name;

                //构造方法

                public StudentinfoRecord() { }

                //Writable接口是对数据流进行操作的，所以输入是DataInput类对象

                public void readFields(DataInput in) throws IOException {

                        this.id = in.readInt(); //输入流中的读取下一个整数，并返回

                        this.name = Text.readString(in);

                }

                public String toString() {

                        return new String(this.id + " " + this.name);

                }

                //DBWritable负责对数据库进行操作，所以输出格式是PreparedStatement

                //PreparedStatement接口继承并扩展了Statement接口，用来执行动态的SQL语句，即包含参数的SQL语句

                @Override

                public void write(PreparedStatement stmt) throws SQLException {

                        stmt.setInt(, this.id);

                        stmt.setString(, this.name);

                }

              //DBWritable负责对数据库进行操作，输入格式是ResultSet

                // ResultSet接口类似于一张数据表，用来暂时存放从数据库查询操作所获得的结果集

                @Override

                public void readFields(ResultSet result) throws SQLException {

                        this.id = result.getInt();

                        this.name = result.getString();

                }

              //Writable接口是对数据流进行操作的，所以输出是DataOutput类对象

                @Override

                public void write(DataOutput out) throws IOException {

                        out.writeInt(this.id);

                        Text.writeString(out, this.name);

                }

        }

        // 记住此处是静态内部类，要不然你自己实现无参构造器，或者等着抛异常：

        // Caused by: java.lang.NoSuchMethodException: DBInputMapper.<init>()

        // http://*.com/questions/7154125/custom-mapreduce-input-format-cant-find-constructor

        // 网上脑残式的转帖，没见到一个写对的。。。

        public static class DBInputMapper extends MapReduceBase implements

                        Mapper<LongWritable, StudentinfoRecord, LongWritable, Text> {

                public void map(LongWritable key, StudentinfoRecord value,

                                OutputCollector<LongWritable, Text> collector, Reporter reporter) throws IOException {

                        collector.collect(new LongWritable(value.id), new Text(value.toString()));

                }

        }

        public static class MyReducer extends MapReduceBase implements

                        Reducer<LongWritable, Text, StudentinfoRecord, Text> {

                @Override

                public void reduce(LongWritable key, Iterator<Text> values,

                                OutputCollector<StudentinfoRecord, Text> output, Reporter reporter) throws IOException {

                        String[] splits = values.next().toString().split(" ");

                        StudentinfoRecord r = new StudentinfoRecord();

                        r.id = Integer.parseInt(splits[]);

                        r.name = splits[];

                        output.collect(r, new Text(r.name));

                }

        }

        public static void main(String[] args) throws IOException {

                JobConf conf = new JobConf(Mysql2Mr.class);

                DistributedCache.addFileToClassPath(new Path("hdfs://192.168.241.13:9000/mysqlconnector/mysql-connector-java-5.1.38-bin.jar"), conf);

                conf.setMapOutputKeyClass(LongWritable.class);

                conf.setMapOutputValueClass(Text.class);

                conf.setOutputKeyClass(LongWritable.class);

                conf.setOutputValueClass(Text.class);

              //  conf.setOutputFormat(DBOutputFormat.class);

                conf.setInputFormat(DBInputFormat.class);

                 // mysql to hdfs

                conf.set("fs.defaultFS", "hdfs://192.168.241.13:9000");//在配置文件conf中指定所用的文件系统---HDFS

                 conf.setReducerClass(IdentityReducer.class);

                 Path outPath = new Path("hdfs://192.168.241.13:9000/student/out1");

                 FileSystem.get(conf).delete(outPath, true);

                 FileOutputFormat.setOutputPath(conf, outPath);

                DBConfiguration.configureDB(conf, "com.mysql.jdbc.Driver", "jdbc:mysql://192.168.241.13:3306/mrtest",

                                "root", "");

                String[] fields = { "id", "name" };

                // 从 t 表读数据

                DBInputFormat.setInput(conf, StudentinfoRecord.class, "t", null, "id", fields);

                // mapreduce 将数据输出到 t2 表

                //DBOutputFormat.setOutput(conf, "t2", "id", "name");

               // FileOutputFormat.setOutputPath(conf, new Path("hdfs://192.168.241.13:9000/student/out1"));

                 conf.setMapperClass(org.apache.hadoop.mapred.lib.IdentityMapper.class);

                conf.setMapperClass(DBInputMapper.class);

               // conf.setReducerClass(MyReducer.class);

                JobClient.runJob(conf);

        }

}

特别要主要的是在主函数里面添加这么一句话

通过mapreduce把mysql的数据读取到hdfs

如果不添加这句话的话就不能识别你的hdfs路径了，除了这个方法之外还，不想添加这句话的话还可以把集群的core-site.xml文件直接拷贝一份放到工程的src目录下

通过mapreduce把mysql的数据读取到hdfs

这样也是可以的

运行程序

通过mapreduce把mysql的数据读取到hdfs

可以看到hdfs的文件上面已经有mysql数据库表的内容了

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