springboot+mybatis(mybatis-plus)+druid 多数据源
Druid介绍和使用
在使用Druid之前，先来简单的了解下Druid。
Druid是一个数据库连接池。Druid可以说是目前最好的数据库连接池！因其优秀的功能、性能和扩展性方面，深受开发人员的青睐。
Druid已经在阿里巴巴部署了超过600个应用，经过一年多生产环境大规模部署的严苛考验。Druid是阿里巴巴开发的号称为监控而生的数据库连接池！
同时Druid不仅仅是一个数据库连接池，Druid 核心主要包括三部分：
- 基于Filter－Chain模式的插件体系。
- DruidDataSource 高效可管理的数据库连接池。
- SQLParser
Druid的主要功能如下:
- 是一个高效、功能强大、可扩展性好的数据库连接池。
- 可以监控数据库访问性能。
- 数据库密码加密
- 获得SQL执行日志
- 扩展JDBC
介绍方面这块就不再多说，具体的可以看官方文档。
那么开始介绍Druid如何使用。
首先是Maven依赖，只需要添加druid这一个jar就行了。
com.alibaba
druid
1.1.8
配置方面，主要的只需要在application.properties或application.yml添加如下就可以了。
说明：因为这里我是用来两个数据源，所以稍微有些不同而已。Druid 配置的说明在下面中已经说的很详细了，这里我就不在说明了。
application.yml
server:
port: 8080
servlet:
context-path: /equaker
spring:
#主数据源
master:
datasource:
type: com.alibaba.druid.pool.DruidDataSource
name: master
url: jdbc:mysql://localhost:3306/wdz?useUnicode=true&characterEncoding=utf-8
username: root
password: 123456
driver-class-name: com.mysql.jdbc.Driver
#从数据源
cluster:
datasource:
type: com.alibaba.druid.pool.DruidDataSource
name: cluster
url: jdbc:mysql://localhost:3306/yufu?useUnicode=true&characterEncoding=utf-8
username: root
password: 123456
driver-class-name: com.mysql.jdbc.Driver
datasource:
druid:
# 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
initialSize: 5
minIdle: 5
maxActive: 20
# 配置获取连接等待超时的时间
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
timeBetweenEvictionRunsMillis: 60000
# 配置一个连接在池中最小生存的时间，单位是毫秒
minEvictableIdleTimeMillis: 30000
validationQuery: SELECT 1
validationQueryTimeout: 10000
testWhileIdle: true
testOnBorrow: false
testOnReturn: false
# 打开PSCache，并且指定每个连接上PSCache的大小
poolPreparedStatements: true
maxPoolPreparedStatementPerConnectionSize: 20
filters: stat,wall
# 通过connectProperties属性来打开mergeSql功能；慢SQL记录
connectionProperties: druid.stat.mergeSql=true;druid.stat.slowSqlMillis=5000
# 合并多个DruidDataSource的监控数据
useGlobalDataSourceStat: true
mybatis:
# 已经再 masterdatasource/clusterdatasource指定了mapper映射文件，所以不用配置
# mapper-locations: classpath:master/*Mapper.xml
type-aliases-package: com.equaker.model
configuration:
database-id: db1
#pagehelper
pagehelper:
helperDialect: mysql
reasonable: true
supportMethodsArguments: true
params: count=countSql
logging:
level:
com.equaker.mapper : debug成功添加了配置文件之后，我们再来编写Druid相关的类。
首先是MasterDataSourceConfig.java这个类，这个是默认的数据源配置类。
MasterDataSourceConfig.hava
package com.equaker.druid;
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;
import java.sql.SQLException;
/**
* 主数据源
*/
@Configuration
@MapperScan(basePackages = MasterDataSourceConfig.PACKAGE, sqlSessionFactoryRef = "masterSqlSessionFactory")
public class MasterDataSourceConfig {
static final String PACKAGE = "com.equaker.mapper.master";
static final String MAPPER_LOCATION = "classpath:mapper/master/*.xml";
@Value("${spring.master.datasource.url}")
private String url;
@Value("${spring.master.datasource.username}")
private String username;
@Value("${spring.master.datasource.password}")
private String password;
@Value("${spring.master.datasource.driver-class-name}")
private String driverClassName;
@Value("${spring.master.datasource.name}")
private String name;
@Value("${spring.datasource.druid.initialSize}")
private int initialSize;
@Value("${spring.datasource.druid.minIdle}")
private int minIdle;
@Value("${spring.datasource.druid.maxActive}")
private int maxActive;
@Value("${spring.datasource.druid.maxWait}")
private int maxWait;
@Value("${spring.datasource.druid.timeBetweenEvictionRunsMillis}")
private int timeBetweenEvictionRunsMillis;
@Value("${spring.datasource.druid.minEvictableIdleTimeMillis}")
private int minEvictableIdleTimeMillis;
@Value("${spring.datasource.druid.validationQuery}")
private String validationQuery;
@Value("${spring.datasource.druid.testWhileIdle}")
private boolean testWhileIdle;
@Value("${spring.datasource.druid.testOnBorrow}")
private boolean testOnBorrow;
@Value("${spring.datasource.druid.testOnReturn}")
private boolean testOnReturn;
@Value("${spring.datasource.druid.poolPreparedStatements}")
private boolean poolPreparedStatements;
@Value("${spring.datasource.druid.maxPoolPreparedStatementPerConnectionSize}")
private int maxPoolPreparedStatementPerConnectionSize;
@Value("${spring.datasource.druid.filters}")
private String filters;
@Value("{spring.datasource.druid.connectionProperties}")
private String connectionProperties;
@Bean(name = "masterDataSource")
@Primary
public DataSource masterDataSource() {
DruidDataSource dataSource = new DruidDataSource();
dataSource.setName(name);
dataSource.setUrl(url);
dataSource.setUsername(username);
dataSource.setPassword(password);
dataSource.setDriverClassName(driverClassName);
//具体配置
dataSource.setInitialSize(initialSize);
dataSource.setMinIdle(minIdle);
dataSource.setMaxActive(maxActive);
dataSource.setMaxWait(maxWait);
dataSource.setTimeBetweenEvictionRunsMillis(timeBetweenEvictionRunsMillis);
dataSource.setMinEvictableIdleTimeMillis(minEvictableIdleTimeMillis);
dataSource.setValidationQuery(validationQuery);
dataSource.setTestWhileIdle(testWhileIdle);
dataSource.setTestOnBorrow(testOnBorrow);
dataSource.setTestOnReturn(testOnReturn);
dataSource.setPoolPreparedStatements(poolPreparedStatements);
dataSource.setMaxPoolPreparedStatementPerConnectionSize(maxPoolPreparedStatementPerConnectionSize);
try {
dataSource.setFilters(filters);
} catch (SQLException e) {
e.printStackTrace();
}
dataSource.setConnectionProperties(connectionProperties);
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.javapackage com.equaker.druid;
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;
import java.sql.SQLException;
/**
* 副数据源
*/
@Configuration
@MapperScan(basePackages = ClusterDataSourceConfig.PACKAGE, sqlSessionFactoryRef = "clusterSqlSessionFactory")
public class ClusterDataSourceConfig {
static final String PACKAGE = "com.equaker.mapper.cluster";
static final String MAPPER_LOCATION = "classpath:mapper/cluster/*.xml";
@Value("${spring.cluster.datasource.url}")
private String url;
@Value("${spring.cluster.datasource.username}")
private String username;
@Value("${spring.cluster.datasource.password}")
private String password;
@Value("${spring.cluster.datasource.driver-class-name}")
private String driverClassName;
@Value("${spring.cluster.datasource.name}")
private String name;
@Value("${spring.datasource.druid.initialSize}")
private int initialSize;
@Value("${spring.datasource.druid.minIdle}")
private int minIdle;
@Value("${spring.datasource.druid.maxActive}")
private int maxActive;
@Value("${spring.datasource.druid.maxWait}")
private int maxWait;
@Value("${spring.datasource.druid.timeBetweenEvictionRunsMillis}")
private int timeBetweenEvictionRunsMillis;
@Value("${spring.datasource.druid.minEvictableIdleTimeMillis}")
private int minEvictableIdleTimeMillis;
@Value("${spring.datasource.druid.validationQuery}")
private String validationQuery;
@Value("${spring.datasource.druid.testWhileIdle}")
private boolean testWhileIdle;
@Value("${spring.datasource.druid.testOnBorrow}")
private boolean testOnBorrow;
@Value("${spring.datasource.druid.testOnReturn}")
private boolean testOnReturn;
@Value("${spring.datasource.druid.poolPreparedStatements}")
private boolean poolPreparedStatements;
@Value("${spring.datasource.druid.maxPoolPreparedStatementPerConnectionSize}")
private int maxPoolPreparedStatementPerConnectionSize;
@Value("${spring.datasource.druid.filters}")
private String filters;
@Value("{spring.datasource.druid.connectionProperties}")
private String connectionProperties;
@Bean(name = "clusterDataSource")
public DataSource masterDataSource() {
DruidDataSource dataSource = new DruidDataSource();
dataSource.setName(name);
dataSource.setUrl(url);
dataSource.setUsername(username);
dataSource.setPassword(password);
dataSource.setDriverClassName(driverClassName);
//具体配置
dataSource.setInitialSize(initialSize);
dataSource.setMinIdle(minIdle);
dataSource.setMaxActive(maxActive);
dataSource.setMaxWait(maxWait);
dataSource.setTimeBetweenEvictionRunsMillis(timeBetweenEvictionRunsMillis);
dataSource.setMinEvictableIdleTimeMillis(minEvictableIdleTimeMillis);
dataSource.setValidationQuery(validationQuery);
dataSource.setTestWhileIdle(testWhileIdle);
dataSource.setTestOnBorrow(testOnBorrow);
dataSource.setTestOnReturn(testOnReturn);
dataSource.setPoolPreparedStatements(poolPreparedStatements);
dataSource.setMaxPoolPreparedStatementPerConnectionSize(maxPoolPreparedStatementPerConnectionSize);
try {
dataSource.setFilters(filters);
} catch (SQLException e) {
e.printStackTrace();
}
dataSource.setConnectionProperties(connectionProperties);
return dataSource;
}
@Bean(name = "clusterTransactionManager")
public DataSourceTransactionManager masterTransactionManager() {
return new DataSourceTransactionManager(masterDataSource());
}
@Bean(name = "clusterSqlSessionFactory")
public SqlSessionFactory masterSqlSessionFactory(@Qualifier("clusterDataSource") DataSource masterDataSource)
throws Exception {
final SqlSessionFactoryBean sessionFactory = new SqlSessionFactoryBean();
sessionFactory.setDataSource(masterDataSource);
sessionFactory.setMapperLocations(new PathMatchingResourcePatternResolver()
.getResources(ClusterDataSourceConfig.MAPPER_LOCATION));
return sessionFactory.getObject();
}
}
其中这两个注解说明下:
-
@Primary ：标志这个 Bean 如果在多个同类 Bean 候选时，该 Bean
优先被考虑。多数据源配置的时候注意，必须要有一个主数据源，用 @Primary 标志该 Bean。 -
@MapperScan： 扫描 Mapper 接口并容器管理。
需要注意的是sqlSessionFactoryRef 表示定义一个唯一 SqlSessionFactory 实例。
上面的配置完之后，就可以将Druid作为连接池使用了。但是Druid并不简简单单的是个连接池，它也可以说是一个监控应用，它自带了web监控界面，可以很清晰的看到SQL相关信息。
在SpringBoot中运用Druid的监控作用，只需要编写StatViewServlet和WebStatFilter类，实现注册服务和过滤规则。这里我们可以将这两个写在一起，使用@Configuration和@Bean。
为了方便理解，相关的配置说明也写在代码中了，这里就不再过多赘述了。
代码如下:
DruidConfiguration.javapackage com.equaker.druid;
import com.alibaba.druid.support.http.StatViewServlet;
import com.alibaba.druid.support.http.WebStatFilter;
import org.springframework.boot.web.servlet.FilterRegistrationBean;
import org.springframework.boot.web.servlet.ServletRegistrationBean;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
/**
* druid数据源监控web应用
*/
@Configuration
public class DruidConfiguration {
@Bean
public ServletRegistrationBean druidStatViewServle() {
//注册服务
ServletRegistrationBean servletRegistrationBean = new ServletRegistrationBean(
new StatViewServlet(), "/druid/*");
// 白名单(为空表示,所有的都可以访问,多个IP的时候用逗号隔开)
servletRegistrationBean.addInitParameter("allow", "127.0.0.1");
// IP黑名单 (存在共同时，deny优先于allow)
servletRegistrationBean.addInitParameter("deny", "127.0.0.2");
// 设置登录的用户名和密码
servletRegistrationBean.addInitParameter("loginUsername", "equaker");
servletRegistrationBean.addInitParameter("loginPassword", "123456");
// 是否能够重置数据.
servletRegistrationBean.addInitParameter("resetEnable", "false");
return servletRegistrationBean;
}
@Bean
public FilterRegistrationBean druidStatFilter() {
FilterRegistrationBean filterRegistrationBean = new FilterRegistrationBean(
new WebStatFilter());
// 添加过滤规则
filterRegistrationBean.addUrlPatterns("/*");
// 添加不需要忽略的格式信息
filterRegistrationBean.addInitParameter("exclusions",
"*.js,*.gif,*.jpg,*.png,*.css,*.ico,/druid/*");
System.out.println("druid初始化成功!");
return filterRegistrationBean;
}
}
编写完之后，启动程序，在浏览器输入:http://127.0.0.1:8084/druid/index.html ，然后输入设置的用户名和密码，便可以访问Web界面了。
效果如图：
DemoController.java:
package com.equaker.controller;
import com.equaker.mapper.cluster.UserMapper;
import com.equaker.mapper.master.EQMapper;
import com.equaker.model.EQ;
import com.equaker.model.User;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Controller;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.ResponseBody;
import java.math.BigDecimal;
import java.util.Date;
import java.util.HashMap;
import java.util.Map;
@Controller
@RequestMapping("demo")
public class DemoController {
@Autowired
private EQMapper eqMapper;
@Autowired
private UserMapper userMapper;
@RequestMapping("/save")
@ResponseBody
public EQ save(){
EQ eq = new EQ();
eq.setcAmount(new BigDecimal(10));
eq.setcCardno("1");
eq.setcDatetime(new Date());
eq.setcGcode("1");
eq.setcGname("sdq");
eq.setcId("1");
eq.setcQtty(new BigDecimal(10));
eq.setcSname("ss");
eq.setcStoreId("1");
eqMapper.insert(eq);
return eq;
}
@RequestMapping("/saveUser")
@ResponseBody
public User saveUser(){
User user = new User();
user.setName("sdq");
user.setAge(23);
user.setCreateTime(new Date());
user.setUpdateTime(new Date());
userMapper.save(user);
return user;
}
}
启动类 ：
因为使用了自定义的数据源配置，所以在启动类里面一定要把springboot自己默认的配置去除
package com.equaker.fhcrm;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.boot.autoconfigure.jdbc.DataSourceAutoConfiguration;
import org.springframework.context.annotation.ComponentScan;
@SpringBootApplication(exclude = {DataSourceAutoConfiguration.class})
@ComponentScan(basePackages = {"com.equaker"})
//@MapperScan(basePackages = {"com.equaker.mapper"})
public class FhCrmApplication {
public static void main(String[] args) {
SpringApplication.run(FhCrmApplication.class, args);
}
}访问：http://localhost:8080/equaker/demo/save 初始化并使用master数据源 ok
访问：http://localhost:8080/equaker/demo/saveUser 初始化并使用cluster数据源 ok
注意！注意！注意！
1,由于在数据源中已经配置了mapper接口和mapper映射文件，所以再启动类main方法中不需要指定mapperscan 了，，在application.yml里面也不需要执行mapper映射文件了。否则会提示waring:
2018-12-17 11:06:14.294 WARN 36624 --- [ main] o.m.s.mapper.ClassPathMapperScanner : Skipping MapperFactoryBean with name 'userMapper' and 'com.equaker.mapper.cluster.UserMapper' mapperInterface. Bean already defined with the same name!
2018-12-17 11:06:14.294 WARN 36624 --- [ main] o.m.s.mapper.ClassPathMapperScanner : Skipping MapperFactoryBean with name 'EQMapper' and 'com.equaker.mapper.master.EQMapper' mapperInterface. Bean already defined with the same name!
2018-12-17 11:06:14.294 WARN 36624 --- [ main] o.m.s.mapper.ClassPathMapperScanner : No MyBatis mapper was found in '[com.equaker.mapper]' package. Please check your configuration.
2, 若是mybatis-plus 进行多数据源配置，只需要在构建会话工厂的时候把
final SqlSessionFactoryBean sessionFactory = new SqlSessionFactoryBean();
改成：
final MybatisSqlSessionFactoryBean sessionFactory = new MybatisSqlSessionFactoryBean();
即可。道理你懂的！！！