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MapReduce编程实战(2)-词频统计结果存入mysql数据库

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摘要

通过实现MapReduce计算结果保存到MySql数据库过程,掌握多种方式保存计算结果的技术,加深了对MapReduce的理解;

Api 文档地址:http://hadoop.apache.org/docs/current/api/index.html

maven资源库:https://mvnrepository.com/repos/central     ##用于配置pom.xml的时候查询资源

 

1.master主机安装mysql

参见文章:https://www.cnblogs.com/hemomo/p/11942661.html

创建maven项目,项目名称hdfs,这里不再说明。

2.修改pom.xml文件

红色部分为增加内容:

<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
  <modelVersion>4.0.0</modelVersion>

  <groupId>com.scitc</groupId>
  <artifactId>hdfs</artifactId>
  <version>0.0.1-SNAPSHOT</version>
  <packaging>jar</packaging>

  <name>hdfs</name>
  <url>http://maven.apache.org</url>

  <properties>
    <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    <hadoop.version>2.7.5</hadoop.version>
  </properties>

  <dependencies>
    <dependency>
      <groupId>junit</groupId>
      <artifactId>junit</artifactId>
      <version>3.8.1</version>
      <scope>test</scope>
    </dependency>
    
    <dependency>
      <groupId>org.apache.hadoop</groupId>
      <artifactId>hadoop-mapreduce-client-common</artifactId>
      <version>${hadoop.version}</version>
    </dependency>
    <dependency>
      <groupId>org.apache.hadoop</groupId>
      <artifactId>hadoop-mapreduce-client-jobclient</artifactId>
      <version>${hadoop.version}</version>
      <scope>provided</scope>
    </dependency>
    <dependency>
      <groupId>org.apache.hadoop</groupId>
      <artifactId>hadoop-client</artifactId>
      <version>${hadoop.version}</version>
    </dependency>
    
    <dependency>
      <groupId>org.apache.hadoop</groupId>
      <artifactId>hadoop-yarn-common</artifactId>
      <version>${hadoop.version}</version>
    </dependency>
     
    <dependency>
      <groupId>org.apache.hadoop</groupId>
      <artifactId>hadoop-mapreduce-client-core</artifactId>
      <version>${hadoop.version}</version>
    </dependency> 
    
    <dependency>
      <groupId>org.apache.hadoop</groupId>
      <artifactId>hadoop-hdfs</artifactId>
      <version>${hadoop.version}</version>
    </dependency>
    
    <dependency>
      <groupId>mysql</groupId>
      <artifactId>mysql-connector-java</artifactId>
      <version>5.1.27</version>
      <scope>compile</scope>
      <optional>true</optional>
    </dependency>
    
    <dependency>  
      <groupId>jdk.tools</groupId>  
      <artifactId>jdk.tools</artifactId>  
      <version>1.8</version>  
      <scope>system</scope>  
      <systemPath>${JAVA_HOME}/lib/tools.jar</systemPath>  
   </dependency>
   
  </dependencies>
  
  <build>
    <plugins>
        <plugin>
            <groupId>org.apache.maven.plugins</groupId>
            <artifactId>maven-compiler-plugin</artifactId>
            <configuration>
            <source>1.8</source>
            <target>1.8</target>
            </configuration>
    </plugin>
    
    <plugin>
             <artifactId>maven-assembly-plugin</artifactId>
             <configuration>
                 <descriptorRefs>
                     <descriptorRef>jar-with-dependencies</descriptorRef>
                 </descriptorRefs>
                 <archive>
                     <manifest>
                         <mainClass></mainClass>
                     </manifest>
                 </archive>
             </configuration>
             <executions>
                 <execution>
                     <id>make-assembly</id>
                     <phase>package</phase>
                     <goals>
                         <goal>single</goal>
                     </goals>
                 </execution>
             </executions>
         </plugin>
    
    </plugins>
</build>
  
</project>

2. 自定义数据类型(WordCountTb)

Hadoop给封装了许多输入输出的类型,如LongWritable、Text、 IntWritable、NullWritable等基础类型,这些类型和Java的基本数据类型一样,不能满足实际的业务需求;因此,我们可以通关过自定义输入输出类型来实现。

com.scitc.hdfs下新建WordCountTb.java类:

技术图片

 

 

 代码如下:

package com.scitc.hdfs;

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 org.apache.hadoop.io.Writable;
import org.apache.hadoop.mapreduce.lib.db.DBWritable;

public class WordCountTb implements Writable, DBWritable {  
    
//定义字段和构造函数
String name; int value; public WordCountTb(String name, int value) { this.name = name; this.value = value; }

//获取数据库表的字段值 @Override public void readFields(ResultSet resultSet) throws SQLException { // TODO Auto-generated method stub this.name = resultSet.getString(1); this.value = resultSet.getInt(2); } @Override public void write(PreparedStatement statement) throws SQLException { // TODO Auto-generated method stub statement.setString(1, this.name); statement.setInt(2, this.value); } @Override public void write(DataOutput out) throws IOException { // TODO Auto-generated method stub out.writeUTF(name); out.writeInt(value); } @Override public void readFields(DataInput in) throws IOException { // TODO Auto-generated method stub name = in.readUTF(); value = in.readInt(); } }

3.数据库属性类StaticConstant

普通类中定义常量://参考https://blog.csdn.net/rlnlo2pnefx9c/article/details/81277528 

com.scitc.hdfs下新建StaticConstant.java类

代码如下:

package com.scitc.hdfs;

public class StaticConstant {
    public static final String jdbcDriver = "com.mysql.jdbc.Driver";
    public static final String jdbcUrl = "jdbc:mysql://192.168.56.110:3306/test?useUnicode=true&characterEncoding=utf8";
    public static final String jdbcUser = "root";
    public static final String jdbcPassword = "bigData@123";
}

3.编写MapReduce类WordCountToDb

com.scitc.hdfs下新建WordCountToDb.java类

技术图片

 

 

 

4:本地运行程序

本地测试非常方便调试。省去排除错误的时候,来回打包在集群运行。

在WordCountToDb类的编辑界面上右击鼠标,在弹出的菜单中选中Run As -> Java Application开始运行该类。

eclipse的console输出如下:

技术图片

 

 

 

打开数据库wordcount表查看运行结果:

技术图片

5:打包、上传、在集群中运行

运行之前记得删除掉mysql中表wordcount里之前本地运行生成的数据

1.打包

项目名hdfs上右键>>Run As>>Maven clean

项目名hdfs上右键>>Run As>>Maven install

2.上传

项目根目录下的target文件夹中找到hdfs-0.0.1-SNAPSHOT.jar,改文件名为hdfs1.jar,上传到master的/opt/data/目录中

3.用hadoop jar 命令运行hdfs1.jar包

cd /opt/data

hadoop jar hdfs1.jar com.scitc.hdfs. WordCountToDb 

##命令语法:hadoop jar  jar包 类的全名称

 

查看结果:

在集群中运行,出现问题:Error: java.io.IOException: com.mysql.jdbc.Driver

 

解决方法1:

pom配置的插件maven-assembly-plugin

在mavne install之后有两个jar包

一个hdfs-0.0.1-SNAPSHOT-jar-with-dependencies.jar 包含所有依赖

因此在集群运行这个jar包,也会正常执行。  ##测试通过

但是这样jar包40多M,太大了。

 

解决方法2:(推荐)

把jar包传到集群上,命令如下

hadoop fs –mkdir –p /lib/mysql     ##创建目录

hadoop fs -put mysql-connector-java-5.1.27.jar /lib/mysql        ##上传驱动到hdfs的lib/mysql目录中

在WordCountToDb.java中提交任务代码前。添加如下代码:

job.addArchiveToClassPath(new Path("hdfs://master:9000/lib/mysql/mysql-connector-java-5.1.27.jar"));

//8:提交任务
boolean result = job.waitForCompletion(true);

查看结果:

查看集群执行结果:没问题,输出为0字节,因为我们是输出到mysql的。

技术图片

 查看mysql数据库:

技术图片

 

 

============================

问题集:

问题1:集群中运行jar包,报错:Error: java.io.IOException: com.mysql.jdbc.Driver

解决参考资料:https://www.cnblogs.com/codeOfLife/p/5464613.html

 

MapReduce编程实战(2)-词频统计结果存入mysql数据库

标签:bcp   VID   out   coding   conf   输出   cee   exception   eclipse   

原文地址:https://www.cnblogs.com/hemomo/p/12289303.html

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