使用hadoop读写mysql

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与mongodb相比，hadoop提供了内置的输入输出库DBInputFormat和DBOutputFormat,但是依然要使用JDBC驱动包com.mysql.jdbc.Driver。没有的可以去http://www.mysql.com/products/connector/ 下载。下下来后，只要把该包放在项目路径下即可，切莫在文件中import该包中内容，只要import java.sql.* 相关包内容即可。

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自定义类实现Writable和DBWritable接口

将驱动导入之后，还需要自己写一个MySQL与MapReduce之间交互的类，需要实现Writable和DBWritable接口，Writable是为了与MapReduce进行对接，而DBWritable是为了与MySQL进行对接。这两个功能要实现的函数是比较类似的，都要实现write和readFields函数。作用顾名思义，前者用于将一条数据写入数据流或者数据库中，而后者则从数据流/库中读取数据。值得注意的是，如果你选择自己写初始化函数，那么这个类必须要有一个空白的初始化函数，不然会报错。

如果我要输入的数据库如下面所示

那么我的相关自定义类应该这么写：

private static class MysqlRecord implements DBWritable,Writable {
    protected int size ;
    protected Date time ;
    protected int input_speed ;
    protected int output_speed ;

    @Override
    public void write(PreparedStatement preparedStatement) throws SQLException {
        preparedStatement.setInt(1,this.size);
        preparedStatement.setDate(2,this.time);
        preparedStatement.setInt(3,this.input_speed);
        preparedStatement.setInt(4,this.output_speed);
    }

    @Override
    public void readFields(ResultSet resultSet) throws SQLException {
        this.size = resultSet.getInt(1) ;
        this.time = resultSet.getDate(2) ;
        this.input_speed = resultSet.getInt(3) ;
        this.output_speed = resultSet.getInt(4) ;
    }

    @Override
    public void write(DataOutput dataOutput) throws IOException {
        dataOutput.writeInt(this.size);
        Text.writeString(dataOutput, this.time.toString()) ;
        dataOutput.writeInt(this.input_speed);
        dataOutput.writeInt(this.output_speed);
    }

    @Override
    public void readFields(DataInput dataInput) throws IOException {
        this.size = dataInput.readInt() ;
        this.time = Date.valueOf(Text.readString(dataInput)) ;
        this.input_speed = dataInput.readInt() ;
        this.output_speed = dataInput.readInt() ;
    }
}

如上面所示，我要读取的数据共有4个字段，Writable接口是对数据流进行操作的，所以输入输出是DataInput和DataOutput类对象； DBWritable负责对数据库进行操作，所以输入格式是ResultSet，输出格式是PreparedStatement; 这两个类的用法不再赘述，注意这两者的字段是从1开始计数的。

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实现Mapper和Reducer

在定义好了接口类以后，下面就开始写Mapper类和Reducer类了。我的目标是统计同一个日期中的output_speed之和，那么根据MapReduce的流程，我要在Mapper类中生成许多Text-IntWritable键值对，分别存放date和output_speed，然后hadoop会自动通过shuffle过程将所有同一date的键值队放入一个递归器Iterator里面，输入到Reducer类中。

过程比较简单，不细说了，注意这里用的是新版api, 是org.apache.hadoop.mapreduce下的用法，而不是org.apache.hadoop.mapred中的用法，两者略有不同。

private static class SQLMapper extends Mapper<LongWritable, MysqlRecord, Text, IntWritable> {
    @Override
    protected void map(LongWritable key, MysqlRecord value, Context context)
            throws IOException, InterruptedException {
        Date d = value.time ;
        int output = value.output_speed ;
        context.write(new Text(d.toString()),new IntWritable(output));
    }
}
private static class SQLReducer extends Reducer<Text, IntWritable, MySQLStatistic, NullWritable> {
    @Override
    protected void reduce(Text key, Iterable values, Context context)
            throws IOException, InterruptedException {
        int sum = 0 ;
        for (IntWritable v:values){
            sum += v.get() ;
        }
        MySQLStatistic res = new MySQLStatistic(key.toString(),sum) ;
        context.write(res, NullWritable.get());
    }
}

其中MySQLStatistic也是实现Writable/DBWritable的类，只有两个字段，负责输出到MySQL。
此外，如果是要输出数据到MySQL，Reducer类的KEYOUT必须是实现Writalbe和DBWritable的类，而VALUEOUT是NullWritable类。

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设置Job参数

这部分是main函数中的一些参数设置。
首先要用DBConfiguration.configureDB来设定连接MySQL所需要的一些认证信息。其函数的定义如下

public static void configureDB(Configuration conf, String driverClass, String dbUrl, String userName, String passwd)

这个没什么好说的，照着格式填就好了

DBConfiguration.configureDB(
    conf, "com.mysql.jdbc.Driver",
    "jdbc:mysql://localhost:3306/microblog_spider",
    "root","admin");

上面值得注意的是dbUrl部分，这个地址的格式一般为

jdbc:mysql//hostname[:port]/dbname[?param1=value1][¶m2=value2]

使用[ ]括起来的部分是可选项。还有一点要注意的是，在数据中有中文存在的情况下，可能还需要指定连接的编码。此时就应该在参数中加上useUnicode和characterEncoding这两个选项。例如指定使用utf8字符集。

jdbc:mysql://localhost:3306/microblog_spider?useUnicode=true&characterEncoding=utf8

在写完MySQL的认证信息以后，再设置输出输出类

job.setInputFormatClass(DBInputFormat.class) ;
job.setOutputFormatClass(DBOutputFormat.class);

然后，再设置表名，字段名等信息。

String[] fields = {"size","time","input_speed","output_speed"} ; 
DBInputFormat.setInput(
        job,                // job
        MysqlRecord.class,  // input class
        "proxy_table",      // table name
        null,               // condition
        "time",             // order by
        fields);            // fields
DBOutputFormat.setOutput(
        job,                // job
        "hadoop_out",       // output table name
        "date","nums"       // fields
);

下面是main函数的完整代码

public static void main(String[] args) throws Exception{
    Configuration conf = new Configuration() ;
    DBConfiguration.configureDB(
            conf, "com.mysql.jdbc.Driver",
            "jdbc:mysql://localhost:3306/microblog_spider",
            "root","admin");
    Job job = Job.getInstance(conf,"mysql test") ;
    job.setJarByClass(mysql_test.class);
    job.setMapperClass(SQLMapper.class);
    job.setReducerClass(SQLReducer.class);
    job.setMapOutputKeyClass(Text.class);
    job.setMapOutputValueClass(IntWritable.class);
    job.setOutputKeyClass(MySQLStatistic.class);
    job.setOutputValueClass(NullWritable.class);
    job.setInputFormatClass(DBInputFormat.class);
    job.setOutputFormatClass(DBOutputFormat.class);
    String[] fields = {"size","time","input_speed","output_speed"} ; 
    DBInputFormat.setInput(
            job,                // job
            MysqlRecord.class,  // input class
            "proxy_table",      // table name
            null,               // condition
            "time",             // order by
            fields);            // fields
    DBOutputFormat.setOutput(
            job,                // job
            "hadoop_out",       // output table name
            "date","nums"       // fields
    );
    job.waitForCompletion(true) ;
}

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所有代码

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.io.*;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.db.DBConfiguration;
import org.apache.hadoop.mapreduce.lib.db.DBInputFormat;
import org.apache.hadoop.mapreduce.lib.db.DBOutputFormat;
import org.apache.hadoop.mapreduce.lib.db.DBWritable;
import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
import java.sql.Date;
import java.sql.PreparedStatement;
import java.sql.ResultSet;
import java.sql.SQLException;

/**
 * Created by multiangle on 16-11-12.
 */

public class mysql_test_demo {
    private static class MysqlRecord implements DBWritable,Writable {
        protected int size ;
        protected Date time ;
        protected int input_speed ;
        protected int output_speed ;

        @Override
        public void write(PreparedStatement preparedStatement) throws SQLException {
            preparedStatement.setInt(1,this.size);
            preparedStatement.setDate(2,this.time);
            preparedStatement.setInt(3,this.input_speed);
            preparedStatement.setInt(4,this.output_speed);
        }

        @Override
        public void readFields(ResultSet resultSet) throws SQLException {
            this.size = resultSet.getInt(1) ;
            this.time = resultSet.getDate(2) ;
            this.input_speed = resultSet.getInt(3) ;
            this.output_speed = resultSet.getInt(4) ;
        }

        @Override
        public void write(DataOutput dataOutput) throws IOException {
            dataOutput.writeInt(this.size);
            Text.writeString(dataOutput, this.time.toString()) ;
            dataOutput.writeInt(this.input_speed);
            dataOutput.writeInt(this.output_speed);
        }

        @Override
        public void readFields(DataInput dataInput) throws IOException {
            this.size = dataInput.readInt() ;
            this.time = Date.valueOf(Text.readString(dataInput)) ;
            this.input_speed = dataInput.readInt() ;
            this.output_speed = dataInput.readInt() ;
        }

        @Override
        public String toString() {
            return String.format("%d\t%s\t%d\t%d",size,time.toString(),input_speed,output_speed);
        }
    }

    private static class MySQLStatistic implements DBWritable,Writable{
        private Date date ;
        private int nums ;

        MySQLStatistic(Date date, int nums){
            this.date = date ;
            this.nums = nums ;
        }
        MySQLStatistic(String date, int nums){
            this.date = Date.valueOf(date) ;
            this.nums = nums ;
        }

        @Override
        public void write(DataOutput dataOutput) throws IOException {
            Text.writeString(dataOutput,date.toString()) ;
            dataOutput.writeInt(nums);
        }

        @Override
        public void readFields(DataInput dataInput) throws IOException {
            date = Date.valueOf(Text.readString(dataInput)) ;
            nums = dataInput.readInt() ;
        }

        @Override
        public void write(PreparedStatement preparedStatement) throws SQLException {
            preparedStatement.setDate(1, date);
            preparedStatement.setInt(2, nums);
        }

        @Override
        public void readFields(ResultSet resultSet) throws SQLException {
            date = resultSet.getDate(1) ;
            nums = resultSet.getInt(2) ;
        }
    }

    private static class SQLMapper extends Mapper<LongWritable, MysqlRecord, Text, IntWritable> {
        @Override
        protected void map(LongWritable key, MysqlRecord value, Context context)
                throws IOException, InterruptedException {
            Date d = value.time ;
            int output = value.output_speed ;
            context.write(new Text(d.toString()),new IntWritable(output));
        }
    }

    private static class SQLReducer extends Reducer<Text, IntWritable, MySQLStatistic, NullWritable> {
        @Override
        protected void reduce(Text key, Iterable values, Context context)
                throws IOException, InterruptedException {
            int sum = 0 ;
            for (IntWritable v:values){
                sum += v.get() ;
            }
            MySQLStatistic res = new MySQLStatistic(key.toString(),sum) ;
            context.write(res, NullWritable.get());
        }
    }

    public static void main(String[] args) throws Exception{
        Configuration conf = new Configuration() ;
        DBConfiguration.configureDB(
                conf, "com.mysql.jdbc.Driver",
                "jdbc:mysql://localhost:3306/microblog_spider",
                "root","admin");


        Job job = Job.getInstance(conf,"mysql test") ;
        job.setJarByClass(mysql_test.class);
        job.setMapperClass(SQLMapper.class);
        job.setReducerClass(SQLReducer.class);

        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(IntWritable.class);
        job.setOutputKeyClass(MySQLStatistic.class);
        job.setOutputValueClass(NullWritable.class);
        job.setInputFormatClass(DBInputFormat.class);
        job.setOutputFormatClass(DBOutputFormat.class);

        String[] fields = {"size","time","input_speed","output_speed"} ; 
        DBInputFormat.setInput(
                job,                // job
                MysqlRecord.class,  // input class
                "proxy_table",      // table name
                null,               // condition
                "time",             // order by
                fields);            // fields

        DBOutputFormat.setOutput(
                job,                // job
                "hadoop_out",       // output table name
                "date","nums"       // fields
        );

        job.waitForCompletion(true) ;
    }

}