DRUID配置多数据源项目

/**   
* @Title: DruidStatViewServlet.java 
* @Package org.spring.springboot.servlet 
* @Description: TODO(用一句话描述该文件做什么) 
* @author pengfei   
* @date 2017年7月15日 下午3:28:13 
* @version V1.0   
*/
package org.spring.springboot.servlet;

import javax.servlet.annotation.WebInitParam;
import javax.servlet.annotation.WebServlet;

import com.alibaba.druid.support.http.StatViewServlet;

/**
 * StatViewServlet
 *
 * @author 单红宇(365384722)
 * @myblog http://blog.csdn.net/catoop/
 * @create 2016年3月17日
 */
@SuppressWarnings("serial")
@WebServlet(urlPatterns = "/druid/*", 
    initParams={
            @WebInitParam(name="allow",value="192.168.16.110,127.0.0.1"),// IP白名单 (没有配置或者为空，则允许所有访问)
            @WebInitParam(name="deny",value="192.168.16.111"),// IP黑名单 (存在共同时，deny优先于allow)
            @WebInitParam(name="loginUsername",value="admin"),// 用户名
            @WebInitParam(name="loginPassword",value="123456"),// 密码
            @WebInitParam(name="resetEnable",value="false")// 禁用HTML页面上的“Reset All”功能
    })
public class DruidStatViewServlet extends StatViewServlet{
}

关于DRUID配置多数据源相信您在网上也找到不少文章，每个人方法各有不同，供大道同归，原理都是一样的;

介绍：

Druid是阿里巴巴开源平台上的一个项目，整个项目由数据库连接池、插件框架和SQL解析器组成。该项目主要是为了扩展JDBC的一些限制，可以让程序员实现一些特殊的需求，比如向密钥服务请求凭证、统计SQL信息、SQL性能收集、SQL注入检查、SQL翻译等，程序员可以通过定制来实现自己需要的功能。

个人理解：主要实现了数据源的优化，和对SQL的监控功能，对事务的管理还是解决JDBC 或 JTA那套来管理事务，我还是参照网上的JDBC事务。

我主要采用spring boot+druid配置数据源，包括事务的管理。
这是我对新技术采用的方法，应该可以放大图片来看：

图上链接我给大家发下，也有可能会失效，因为随网站内容变更啊

同类技术对比：https://github.com/alibaba/druid/wiki/%E5%90%84%E7%A7%8D%E8%BF%9E%E6%8E%A5%E6%B1%A0%E6%80%A7%E8%83%BD%E5%AF%B9%E6%AF%94%E6%B5%8B%E8%AF%95

官方示例：http://www.iteye.com/magazines/90#123 只是管理了链接池

文档：https://github.com/alibaba/druid/tree/master/druid-spring-boot-starter

看开源代码：https://github.com/AlibabaTech/druid

我直接写配置方法了：

application.properties

## master 数据源配置
master.datasource.url=jdbc:oracle:thin:@10.20.100.193:1521:mestest1
master.datasource.username=qnmest1
master.datasource.password=qnmest1
master.datasource.driverClassName=oracle.jdbc.driver.OracleDriver

## cluster 数据源配置
cluster.datasource.url=jdbc:mysql://localhost:3306/springbootdb_cluster?useUnicode=true&characterEncoding=utf8
cluster.datasource.username=root
cluster.datasource.password=root
cluster.datasource.driverClassName=com.mysql.jdbc.Driver


# 下面为连接池的补充设置，应用到上面所有数据源中
# 初始化大小，最小，最大
spring.datasource.initialSize=5
spring.datasource.minIdle=5
spring.datasource.maxActive=20
# 配置获取连接等待超时的时间
spring.datasource.maxWait=60000
# 配置间隔多久才进行一次检测，检测需要关闭的空闲连接，单位是毫秒 
spring.datasource.timeBetweenEvictionRunsMillis=60000
# 配置一个连接在池中最小生存的时间，单位是毫秒 
spring.datasource.minEvictableIdleTimeMillis=300000
spring.datasource.validationQuery=SELECT 1 FROM DUAL
spring.datasource.testWhileIdle=true
spring.datasource.testOnBorrow=false
spring.datasource.testOnReturn=false
spring.datasource.logImpl=STDOUT_LOGGING
# 打开PSCache，并且指定每个连接上PSCache的大小 
spring.datasource.poolPreparedStatements=true
spring.datasource.maxPoolPreparedStatementPerConnectionSize=20
# 配置监控统计拦截的filters，去掉后监控界面sql无法统计，'wall'用于防火墙 
spring.datasource.filters=stat,wall,log4j
# 通过connectProperties属性来打开mergeSql功能；慢SQL记录
spring.datasource.connectionProperties=druid.stat.mergeSql=true;druid.stat.slowSqlMillis=5000
# 合并多个DruidDataSource的监控数据
spring.datasource.useGlobalDataSourceStat=true


logback.access.config.path=./src/main/respirces/logback.xml

MasterDataSourceConfig

package org.spring.springboot.config.ds;

import com.alibaba.druid.pool.DruidDataSource;
import org.apache.ibatis.session.SqlSessionFactory;
import org.mybatis.spring.SqlSessionFactoryBean;
import org.mybatis.spring.annotation.MapperScan;
import org.springframework.beans.factory.annotation.Qualifier;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.context.annotation.Primary;
import org.springframework.core.io.support.PathMatchingResourcePatternResolver;
import org.springframework.jdbc.datasource.DataSourceTransactionManager;

import javax.sql.DataSource;

@Configuration
// 扫描 Mapper 接口并容器管理
@MapperScan(basePackages = MasterDataSourceConfig.PACKAGE, sqlSessionFactoryRef = "masterSqlSessionFactory")
public class MasterDataSourceConfig {

    // 精确到 master 目录，以便跟其他数据源隔离
    static final String PACKAGE = "org.spring.springboot.dao.master";
    static final String MAPPER_LOCATION = "classpath:mapper/master/*.xml";

    @Value("${master.datasource.url}")
    private String url;

    @Value("${master.datasource.username}")
    private String user;

    @Value("${master.datasource.password}")
    private String password;

    @Value("${master.datasource.driverClassName}")
    private String driverClass;

    @Bean(name = "masterDataSource")
    @Primary
    public DataSource masterDataSource() {
        DruidDataSource dataSource = new DruidDataSource();
        dataSource.setDriverClassName(driverClass);
        dataSource.setUrl(url);
        dataSource.setUsername(user);
        dataSource.setPassword(password);
  
        return dataSource;
    }

    @Bean(name = "masterTransactionManager")
    @Primary
    public DataSourceTransactionManager masterTransactionManager() {
        return new DataSourceTransactionManager(masterDataSource());
    }

    @Bean(name = "masterSqlSessionFactory")
    @Primary
    public SqlSessionFactory masterSqlSessionFactory(@Qualifier("masterDataSource") DataSource masterDataSource)
            throws Exception {
        final SqlSessionFactoryBean sessionFactory = new SqlSessionFactoryBean();
        sessionFactory.setDataSource(masterDataSource);
        sessionFactory.setMapperLocations(new PathMatchingResourcePatternResolver()
                .getResources(MasterDataSourceConfig.MAPPER_LOCATION));
        return sessionFactory.getObject();
    }
}

ClusterDataSourceConfig

package org.spring.springboot.config.ds;

import javax.sql.DataSource;

import org.apache.ibatis.session.SqlSessionFactory;
import org.mybatis.spring.SqlSessionFactoryBean;
import org.mybatis.spring.annotation.MapperScan;
import org.springframework.beans.factory.annotation.Qualifier;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.core.io.support.PathMatchingResourcePatternResolver;
import org.springframework.jdbc.datasource.DataSourceTransactionManager;

import com.alibaba.druid.pool.DruidDataSource;

@Configuration
// 扫描 Mapper 接口并容器管理
@MapperScan(basePackages = ClusterDataSourceConfig.PACKAGE, sqlSessionFactoryRef = "clusterSqlSessionFactory")
public class ClusterDataSourceConfig {
	// 精确到 cluster 目录，以便跟其他数据源隔离
	static final String PACKAGE = "org.spring.springboot.dao.cluster";
	static final String MAPPER_LOCATION = "classpath:mapper/cluster/*.xml";

	@Value("${cluster.datasource.url}")
	private String url;

	@Value("${cluster.datasource.username}")
	private String user;

	@Value("${cluster.datasource.password}")
	private String password;

	@Value("${cluster.datasource.driverClassName}")
	private String driverClass;

	@Bean(name = "clusterDataSource")
	public DataSource clusterDataSource() {
		DruidDataSource dataSource = new DruidDataSource();
		dataSource.setDriverClassName(driverClass);
		dataSource.setUrl(url);
		dataSource.setUsername(user);
		dataSource.setPassword(password);
		return dataSource;
	}

	@Bean(name = "clusterTransactionManager") //这里就是事务控制了
	public DataSourceTransactionManager clusterTransactionManager() {
		return new DataSourceTransactionManager(clusterDataSource());
	}

	@Bean(name = "clusterSqlSessionFactory")
	public SqlSessionFactory clusterSqlSessionFactory(@Qualifier("clusterDataSource") DataSource clusterDataSource)
			throws Exception {
		final SqlSessionFactoryBean sessionFactory = new SqlSessionFactoryBean();
		sessionFactory.setDataSource(clusterDataSource);
		sessionFactory.setMapperLocations(
				new PathMatchingResourcePatternResolver().getResources(ClusterDataSourceConfig.MAPPER_LOCATION));
		return sessionFactory.getObject();
	}
}

IntfCalculateZpfMapper

package org.spring.springboot.dao.master;

import java.math.BigDecimal;
import java.util.Date;
import java.util.List;

import org.spring.springboot.domain.IntfCalculateZpf;

public interface IntfCalculateZpfMapper {
    int deleteByPrimaryKey(Date sysid);

    int insert(IntfCalculateZpf record);

    int insertSelective(IntfCalculateZpf record);

    IntfCalculateZpf selectByPrimaryKey(Date sysid);
    List selectBySid(BigDecimal sid);

    int updateByPrimaryKeySelective(IntfCalculateZpf record);

    int updateByPrimaryKey(IntfCalculateZpf record);
    
    
}

IntfCalculateZpfMapper.xml

  
    
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
    
  
  
    SYSID, SID, APPLY_ID, CAR_NO, L4_MATNR, MAT_NAME, PRICE_UNIT, GROSS_WT, GROSS_DATE, 
    TARE_WT, TARE_DATE, WEIGHT, WT_UNIT, GROSS_BY, BUSINESS_ID, BUSINESS_TYPE, APPLY_ID_L2, 
    SUPPLY_NAME, GROSS_DATE_2, GROSS_DATE_1, GROSS_STATION_1, LADLE_SEQ, CELL_ID_LIST, 
    ASSIGNMENT, UNIT_CARRIED_NAME, REMARK, FLAG, LADLE_ID
  
  
    select 
    
    from INTF_CALCULATE_ZPF
    where SYSID = #{sysid,jdbcType=TIMESTAMP}
  
  
  
    select 
    
    from INTF_CALCULATE_ZPF
    where SID = #{sid,jdbcType=DECIMAL}
  
  
  
    delete from INTF_CALCULATE_ZPF
    where SYSID = #{sysid,jdbcType=TIMESTAMP}
  
  
    insert into INTF_CALCULATE_ZPF (SYSID, SID, APPLY_ID, 
      CAR_NO, L4_MATNR, MAT_NAME, 
      PRICE_UNIT, GROSS_WT, GROSS_DATE, 
      TARE_WT, TARE_DATE, WEIGHT, 
      WT_UNIT, GROSS_BY, BUSINESS_ID, 
      BUSINESS_TYPE, APPLY_ID_L2, SUPPLY_NAME, 
      GROSS_DATE_2, GROSS_DATE_1, GROSS_STATION_1, 
      LADLE_SEQ, CELL_ID_LIST, ASSIGNMENT, 
      UNIT_CARRIED_NAME, REMARK, FLAG, 
      LADLE_ID)
    values (#{sysid,jdbcType=TIMESTAMP}, #{sid,jdbcType=DECIMAL}, #{applyId,jdbcType=VARCHAR}, 
      #{carNo,jdbcType=VARCHAR}, #{l4Matnr,jdbcType=VARCHAR}, #{matName,jdbcType=VARCHAR}, 
      #{priceUnit,jdbcType=VARCHAR}, #{grossWt,jdbcType=DECIMAL}, #{grossDate,jdbcType=TIMESTAMP}, 
      #{tareWt,jdbcType=DECIMAL}, #{tareDate,jdbcType=TIMESTAMP}, #{weight,jdbcType=DECIMAL}, 
      #{wtUnit,jdbcType=VARCHAR}, #{grossBy,jdbcType=VARCHAR}, #{businessId,jdbcType=VARCHAR}, 
      #{businessType,jdbcType=VARCHAR}, #{applyIdL2,jdbcType=VARCHAR}, #{supplyName,jdbcType=VARCHAR}, 
      #{grossDate2,jdbcType=TIMESTAMP}, #{grossDate1,jdbcType=TIMESTAMP}, #{grossStation1,jdbcType=VARCHAR}, 
      #{ladleSeq,jdbcType=VARCHAR}, #{cellIdList,jdbcType=VARCHAR}, #{assignment,jdbcType=VARCHAR}, 
      #{unitCarriedName,jdbcType=VARCHAR}, #{remark,jdbcType=VARCHAR}, #{flag,jdbcType=VARCHAR}, 
      #{ladleId,jdbcType=VARCHAR})
  
  
    insert into INTF_CALCULATE_ZPF
    
      
        SYSID,
      
      
        SID,
      
      
        APPLY_ID,
      
      
        CAR_NO,
      
      
        L4_MATNR,
      
      
        MAT_NAME,
      
      
        PRICE_UNIT,
      
      
        GROSS_WT,
      
      
        GROSS_DATE,
      
      
        TARE_WT,
      
      
        TARE_DATE,
      
      
        WEIGHT,
      
      
        WT_UNIT,
      
      
        GROSS_BY,
      
      
        BUSINESS_ID,
      
      
        BUSINESS_TYPE,
      
      
        APPLY_ID_L2,
      
      
        SUPPLY_NAME,
      
      
        GROSS_DATE_2,
      
      
        GROSS_DATE_1,
      
      
        GROSS_STATION_1,
      
      
        LADLE_SEQ,
      
      
        CELL_ID_LIST,
      
      
        ASSIGNMENT,
      
      
        UNIT_CARRIED_NAME,
      
      
        REMARK,
      
      
        FLAG,
      
      
        LADLE_ID,
      
    
    
      
        #{sysid,jdbcType=TIMESTAMP},
      
      
        #{sid,jdbcType=DECIMAL},
      
      
        #{applyId,jdbcType=VARCHAR},
      
      
        #{carNo,jdbcType=VARCHAR},
      
      
        #{l4Matnr,jdbcType=VARCHAR},
      
      
        #{matName,jdbcType=VARCHAR},
      
      
        #{priceUnit,jdbcType=VARCHAR},
      
      
        #{grossWt,jdbcType=DECIMAL},
      
      
        #{grossDate,jdbcType=TIMESTAMP},
      
      
        #{tareWt,jdbcType=DECIMAL},
      
      
        #{tareDate,jdbcType=TIMESTAMP},
      
      
        #{weight,jdbcType=DECIMAL},
      
      
        #{wtUnit,jdbcType=VARCHAR},
      
      
        #{grossBy,jdbcType=VARCHAR},
      
      
        #{businessId,jdbcType=VARCHAR},
      
      
        #{businessType,jdbcType=VARCHAR},
      
      
        #{applyIdL2,jdbcType=VARCHAR},
      
      
        #{supplyName,jdbcType=VARCHAR},
      
      
        #{grossDate2,jdbcType=TIMESTAMP},
      
      
        #{grossDate1,jdbcType=TIMESTAMP},
      
      
        #{grossStation1,jdbcType=VARCHAR},
      
      
        #{ladleSeq,jdbcType=VARCHAR},
      
      
        #{cellIdList,jdbcType=VARCHAR},
      
      
        #{assignment,jdbcType=VARCHAR},
      
      
        #{unitCarriedName,jdbcType=VARCHAR},
      
      
        #{remark,jdbcType=VARCHAR},
      
      
        #{flag,jdbcType=VARCHAR},
      
      
        #{ladleId,jdbcType=VARCHAR},
      
    
  
  
    update INTF_CALCULATE_ZPF
    
      
        SID = #{sid,jdbcType=DECIMAL},
      
      
        APPLY_ID = #{applyId,jdbcType=VARCHAR},
      
      
        CAR_NO = #{carNo,jdbcType=VARCHAR},
      
      
        L4_MATNR = #{l4Matnr,jdbcType=VARCHAR},
      
      
        MAT_NAME = #{matName,jdbcType=VARCHAR},
      
      
        PRICE_UNIT = #{priceUnit,jdbcType=VARCHAR},
      
      
        GROSS_WT = #{grossWt,jdbcType=DECIMAL},
      
      
        GROSS_DATE = #{grossDate,jdbcType=TIMESTAMP},
      
      
        TARE_WT = #{tareWt,jdbcType=DECIMAL},
      
      
        TARE_DATE = #{tareDate,jdbcType=TIMESTAMP},
      
      
        WEIGHT = #{weight,jdbcType=DECIMAL},
      
      
        WT_UNIT = #{wtUnit,jdbcType=VARCHAR},
      
      
        GROSS_BY = #{grossBy,jdbcType=VARCHAR},
      
      
        BUSINESS_ID = #{businessId,jdbcType=VARCHAR},
      
      
        BUSINESS_TYPE = #{businessType,jdbcType=VARCHAR},
      
      
        APPLY_ID_L2 = #{applyIdL2,jdbcType=VARCHAR},
      
      
        SUPPLY_NAME = #{supplyName,jdbcType=VARCHAR},
      
      
        GROSS_DATE_2 = #{grossDate2,jdbcType=TIMESTAMP},
      
      
        GROSS_DATE_1 = #{grossDate1,jdbcType=TIMESTAMP},
      
      
        GROSS_STATION_1 = #{grossStation1,jdbcType=VARCHAR},
      
      
        LADLE_SEQ = #{ladleSeq,jdbcType=VARCHAR},
      
      
        CELL_ID_LIST = #{cellIdList,jdbcType=VARCHAR},
      
      
        ASSIGNMENT = #{assignment,jdbcType=VARCHAR},
      
      
        UNIT_CARRIED_NAME = #{unitCarriedName,jdbcType=VARCHAR},
      
      
        REMARK = #{remark,jdbcType=VARCHAR},
      
      
        FLAG = #{flag,jdbcType=VARCHAR},
      
      
        LADLE_ID = #{ladleId,jdbcType=VARCHAR},
      
    
    where SYSID = #{sysid,jdbcType=TIMESTAMP}
  
  
    update INTF_CALCULATE_ZPF
    set SID = #{sid,jdbcType=DECIMAL},
      APPLY_ID = #{applyId,jdbcType=VARCHAR},
      CAR_NO = #{carNo,jdbcType=VARCHAR},
      L4_MATNR = #{l4Matnr,jdbcType=VARCHAR},
      MAT_NAME = #{matName,jdbcType=VARCHAR},
      PRICE_UNIT = #{priceUnit,jdbcType=VARCHAR},
      GROSS_WT = #{grossWt,jdbcType=DECIMAL},
      GROSS_DATE = #{grossDate,jdbcType=TIMESTAMP},
      TARE_WT = #{tareWt,jdbcType=DECIMAL},
      TARE_DATE = #{tareDate,jdbcType=TIMESTAMP},
      WEIGHT = #{weight,jdbcType=DECIMAL},
      WT_UNIT = #{wtUnit,jdbcType=VARCHAR},
      GROSS_BY = #{grossBy,jdbcType=VARCHAR},
      BUSINESS_ID = #{businessId,jdbcType=VARCHAR},
      BUSINESS_TYPE = #{businessType,jdbcType=VARCHAR},
      APPLY_ID_L2 = #{applyIdL2,jdbcType=VARCHAR},
      SUPPLY_NAME = #{supplyName,jdbcType=VARCHAR},
      GROSS_DATE_2 = #{grossDate2,jdbcType=TIMESTAMP},
      GROSS_DATE_1 = #{grossDate1,jdbcType=TIMESTAMP},
      GROSS_STATION_1 = #{grossStation1,jdbcType=VARCHAR},
      LADLE_SEQ = #{ladleSeq,jdbcType=VARCHAR},
      CELL_ID_LIST = #{cellIdList,jdbcType=VARCHAR},
      ASSIGNMENT = #{assignment,jdbcType=VARCHAR},
      UNIT_CARRIED_NAME = #{unitCarriedName,jdbcType=VARCHAR},
      REMARK = #{remark,jdbcType=VARCHAR},
      FLAG = #{flag,jdbcType=VARCHAR},
      LADLE_ID = #{ladleId,jdbcType=VARCHAR}
    where SYSID = #{sysid,jdbcType=TIMESTAMP}
  

IntfCalculateZpfServiceImpl

/**   
* @Title: IntfCalculateZpfServiceImpl.java 
* @Package org.spring.springboot.service.impl 
* @Description: TODO(用一句话描述该文件做什么) 
* @author pengfei   
* @date 2017年7月15日 上午10:57:54 
* @version V1.0   
*/
package org.spring.springboot.service.impl;

import java.math.BigDecimal;
import java.util.Date;

import org.spring.springboot.dao.master.IntfCalculateZpfMapper;
import org.spring.springboot.domain.IntfCalculateZpf;
import org.spring.springboot.service.IntfCalculateZpfService;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Service;
import org.springframework.transaction.annotation.Transactional;

/** 
 * @author zhangPengFei QQ:635332940 
 * @version 创建时间：2017年7月15日 上午10:57:54 
 * 说明 :
 */
/**
 * @author pengfei
 *@version 创建时间：2017年7月15日 上午10:57:54 
 * @Description:TODO(这里用一句话描述这个类的作用) 
 * 
 */
@Service
public class IntfCalculateZpfServiceImpl implements IntfCalculateZpfService {

	
	 @Autowired
	    private IntfCalculateZpfMapper intfCalculateZpfDao; // 主数据源
	
	
	/* (非 Javadoc) 
	* 
Title: selectBySid
 
	* 
Description: 
 
	* @param sid
	* @return 
	* @see org.spring.springboot.service.IntfCalculateZpfService#selectBySid(java.lang.String) 
	*/
	
	@Transactional //这个就是事务控制
	public IntfCalculateZpf selectBySid(String sid) {
		IntfCalculateZpf inf=intfCalculateZpfDao.selectByPrimaryKey(null);
		IntfCalculateZpf record=new IntfCalculateZpf();
		
		BigDecimal sid1=new BigDecimal(12);
		record.setSid(sid1);
		record.setCarNo("FDSAFSFASF");
		record.setSysid(new Date());
		intfCalculateZpfDao.insert(record);
		int a=4/1;
		System.out.println(a);
		return inf;
	}

}

Application

package org.spring.springboot;

import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.boot.web.servlet.ServletComponentScan;

/**
 * Spring Boot 应用启动类
 *
 * Created by bysocket on 16/4/26.
 */
// Spring Boot 应用的标识
@SpringBootApplication
@ServletComponentScan

//@MapperScan 如果Mapper下面没有@mapper 这个就要加上去，官方说的，但我没有加也运行了，具体请各位指教
public class Application {

    public static void main(String[] args) {
        // 程序启动入口
        // 启动嵌入式的 Tomcat 并初始化 Spring 环境及其各 Spring 组件
        SpringApplication.run(Application.class,args);
    }
}

DruidStatFilter

/**   
* @Title: DruidStatFilter.java 
* @Package org.spring.springboot.servlet 
* @Description: TODO(用一句话描述该文件做什么) 
* @author pengfei   
* @date 2017年7月15日 下午3:28:56 
* @version V1.0   
*/
package org.spring.springboot.servlet;

import javax.servlet.annotation.WebFilter;
import javax.servlet.annotation.WebInitParam;

import com.alibaba.druid.support.http.WebStatFilter;

/**
 * Druid的StatFilter
 *
 * @author   单红宇(365384722)
 * @myblog  http://blog.csdn.net/catoop/
 * @create    2016年3月17日
 */
@WebFilter(filterName="druidWebStatFilter",urlPatterns="/*",
    initParams={
        @WebInitParam(name="exclusions",value="*.js,*.gif,*.jpg,*.bmp,*.png,*.css,*.ico,/druid/*")// 忽略资源
})
public class DruidStatFilter extends WebStatFilter {

}

DruidStatViewServlet

/**   
* @Title: DruidStatViewServlet.java 
* @Package org.spring.springboot.servlet 
* @Description: TODO(用一句话描述该文件做什么) 
* @author pengfei   
* @date 2017年7月15日 下午3:28:13 
* @version V1.0   
*/
package org.spring.springboot.servlet;

import javax.servlet.annotation.WebInitParam;
import javax.servlet.annotation.WebServlet;

import com.alibaba.druid.support.http.StatViewServlet;

/**
 * StatViewServlet
 *
 * @author 单红宇(365384722)
 * @myblog http://blog.csdn.net/catoop/
 * @create 2016年3月17日
 */
@SuppressWarnings("serial")
@WebServlet(urlPatterns = "/druid/*", 
    initParams={
            @WebInitParam(name="allow",value="192.168.16.110,127.0.0.1"),// IP白名单 (没有配置或者为空，则允许所有访问)
            @WebInitParam(name="deny",value="192.168.16.111"),// IP黑名单 (存在共同时，deny优先于allow)
            @WebInitParam(name="loginUsername",value="admin"),// 用户名
            @WebInitParam(name="loginPassword",value="123456"),// 密码
            @WebInitParam(name="resetEnable",value="false")// 禁用HTML页面上的“Reset All”功能
    })
public class DruidStatViewServlet extends StatViewServlet{
}

我的测试类：test

/**   
* @Title: test.java 
* @Package org.test 
* @Description: TODO(用一句话描述该文件做什么) 
* @author pengfei   
* @date 2017年7月15日 下午1:03:41 
* @version V1.0   
*/
package org.test;

import java.math.BigDecimal;
import java.util.List;

import org.junit.Test;
import org.junit.runner.RunWith;
import org.spring.springboot.Application;
import org.spring.springboot.dao.master.IntfCalculateZpfMapper;
import org.spring.springboot.domain.IntfCalculateZpf;
import org.spring.springboot.service.IntfCalculateZpfService;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.test.context.SpringBootTest;
import org.springframework.test.context.junit4.SpringJUnit4ClassRunner;
/** 
 * @author zhangPengFei QQ:635332940 
 * @version 创建时间：2017年7月15日 下午1:03:41 
 * 说明 :
 */
/**
 * @author pengfei
 *@version 创建时间：2017年7月15日 下午1:03:41 
 * @Description:TODO(这里用一句话描述这个类的作用) 
 * 
 */
@RunWith(SpringJUnit4ClassRunner.class)  
@SpringBootTest(classes=Application.class)
public class test {
	@Autowired
	private IntfCalculateZpfMapper intfCalculateZpfDao; // 主数据源
	@Autowired
	private IntfCalculateZpfService intfCalculateZpfService;
	@Test
	public void test(){
		
		BigDecimal sid=new BigDecimal(12);
		List list=intfCalculateZpfDao.selectBySid(sid);
		System.out.println(list.size());
	}
	@Test
	public void test2(){
		
		BigDecimal sid=new BigDecimal(12);
		IntfCalculateZpf list=intfCalculateZpfService.selectBySid("12");
		System.out.println(list);
	}
}

基本上就是这样了，有什么问题大家可以联系我QQ:635332940 张生

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