需求

两张表,一张click表记录某广告某一天的点击量,另一张total_click表记录某广告的总点击量

建表

CREATE TABLE `click` (
`id` int(20) NOT NULL AUTO_INCREMENT,
`ad_id` int(20) DEFAULT NULL, -- 广告ID
`click_num` int(30) DEFAULT NULL, -- 某天的点击数量
`day` date,
PRIMARY KEY (`id`)
); CREATE TABLE `total_click` (
`id` int(20) NOT NULL AUTO_INCREMENT,
`ad_id` int(20) DEFAULT NULL, -- 广告ID
`total_click_num` int(50) DEFAULT NULL, -- 总点击数量
PRIMARY KEY (`id`)
)

pom依赖

<dependencies>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-client</artifactId>
<version>2.7.3</version>
</dependency> <dependency>
<groupId>junit</groupId>
<artifactId>junit</artifactId>
<version>4.11</version>
</dependency> <dependency>
<groupId>log4j</groupId>
<artifactId>log4j</artifactId>
<version>1.2.17</version>
</dependency> <dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
<version>5.1.45</version>
</dependency>
</dependencies>

代码

自定义类

Writable是为了与MapReduce进行对接,而DBWritable是为了与MySQL进行对接。

import org.apache.hadoop.io.Writable;
import org.apache.hadoop.mapreduce.lib.db.DBWritable; import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
import java.sql.PreparedStatement;
import java.sql.ResultSet;
import java.sql.SQLException; public class MyDBWritable implements DBWritable, Writable {
private String ad_id;
private int click_num;
private int total_click_num; public MyDBWritable(){ }
public MyDBWritable(String name, int age) {
this.ad_id = name;
this.click_num = age;
this.total_click_num = total_click_num;
} public void write(DataOutput out) throws IOException {
out.writeUTF(ad_id);
out.writeInt(click_num);
out.writeInt(total_click_num);
} //写数据的过程
public void write(PreparedStatement statement) throws SQLException {
//要和SQL_Run类的DBOutputFormat.setOutput(job,"total_click","ad_id","total_click_num")语句里字段的顺序保持一致
statement.setString(1,ad_id);
statement.setInt(2, total_click_num);
} //读数据的过程
public void readFields(ResultSet resultSet) throws SQLException {
ad_id =resultSet.getString(1);
click_num =resultSet.getInt(2);
} public void readFields(DataInput in) throws IOException {
ad_id =in.readUTF();
click_num =in.readInt();
total_click_num =in.readInt();
} public String getAd_id() {
return ad_id;
} public void setAd_id(String ad_id) {
this.ad_id = ad_id;
} public int getClick_num() {
return click_num;
} public void setClick_num(int click_num) {
this.click_num = click_num;
} public int getTotal_click_num() {
return total_click_num;
} public void setTotal_click_num(int total_click_num) {
this.total_click_num = total_click_num;
} }

Map

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper; import java.io.IOException; public class SQLMapper extends Mapper<LongWritable,MyDBWritable,Text,IntWritable> {
@Override
protected void map(LongWritable key, MyDBWritable value, Context context) throws IOException, InterruptedException {
context.write(new Text(value.getAd_id()),new IntWritable(value.getClick_num()));
} }

Reduce

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer; import java.io.IOException; public class SQLReducer extends Reducer<Text,IntWritable,MyDBWritable,NullWritable> {
@Override
protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
int total = 0;
for(IntWritable i :values) {
total+= i.get();
}
MyDBWritable myDBWritable = new MyDBWritable();
myDBWritable.setAd_id(key.toString());
myDBWritable.setTotal_click_num(total);
context.write(myDBWritable,NullWritable.get());
}
}

App

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.db.DBConfiguration;
import org.apache.hadoop.mapreduce.lib.db.DBInputFormat;
import org.apache.hadoop.mapreduce.lib.db.DBOutputFormat; public class SQL_Run {
public static void main(String[] args) throws Exception { Configuration conf=new Configuration(); //假如是本地测试,需要设置fs.defaultFS
conf.set("fs.defaultFS","file:///"); Job job = Job.getInstance(conf); FileSystem fs=FileSystem.get(conf); job.setJobName("SQL_TEST");
job.setJarByClass(SQL_Run.class);
job.setMapperClass(SQLMapper.class);
job.setReducerClass(SQLReducer.class); //配置数据库信息
String driveclass="com.mysql.jdbc.Driver";
String url="jdbc:mysql://192.168.0.8:3306/bigdata";
String username="root";
String password="123456";
DBConfiguration.configureDB(job.getConfiguration(),driveclass,url,username,password); //设置数据库输入
//需要通过总的记录数来计算切片
DBInputFormat.setInput(job,MyDBWritable.class,"select ad_id,click_num from click","select count(id) from click"); //设置数据库输出 //total_click是表名,后面参数是字段值(可以多个)
DBOutputFormat.setOutput(job,"total_click","ad_id","total_click_num"); job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(IntWritable.class); job.setOutputKeyClass(MyDBWritable.class);
job.setOutputValueClass(NullWritable.class); job.waitForCompletion(true);
}
}
05-28 12:41