SpringBoot集成Druid完成MySQL数据访问，以及配置Druid监控模块整合。

添加Druid依赖

<!--alibaba druid datasource-->
<dependency>
    <groupId>com.alibaba</groupId>
    <artifactId>druid</artifactId>
    <version>${alibaba-druid.version}</version>
</dependency>

添加配置

# DataSource settings
spring.datasource.type=com.alibaba.druid.pool.DruidDataSource
spring.datasource.url = jdbc:mysql://localhost:3306/test?useUnicode=true&characterEncoding=UTF8
spring.datasource.username = root
spring.datasource.password = root
spring.datasource.driverClassName = com.mysql.jdbc.Driver
#连接池的配置信息
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
# 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

启动项目

此时，SpringBoot已经把Druid当做dataSource加载到了项目中了

开启Druid监控功能

开启监控功能，可以在应用运行的过程中，通过监控提供的多维度数据来分析使用数据库的运行情况，从而可以调整程序设计，以便于优化数据库的访问性能。

@Configuration
public class DruidConfiguration {
    @Value("${spring.datasource.url}")
    private String dbUrl;
    @Value("${spring.datasource.username}")
    private String username;
    @Value("${spring.datasource.password}")
    private String password;
    @Value("${spring.datasource.driver-class-name}")
    private String driverClassName;
    @Value("${spring.datasource.initialSize}")
    private int initialSize;
    @Value("${spring.datasource.minIdle}")
    private int minIdle;
    @Value("${spring.datasource.maxActive}")
    private int maxActive;
    @Value("${spring.datasource.maxWait}")
    private int maxWait;
    @Value("${spring.datasource.timeBetweenEvictionRunsMillis}")
    private int timeBetweenEvictionRunsMillis;
    @Value("${spring.datasource.minEvictableIdleTimeMillis}")
    private int minEvictableIdleTimeMillis;
    @Value("${spring.datasource.validationQuery}")
    private String validationQuery;
    @Value("${spring.datasource.testWhileIdle}")
    private boolean testWhileIdle;
    @Value("${spring.datasource.testOnBorrow}")
    private boolean testOnBorrow;
    @Value("${spring.datasource.testOnReturn}")
    private boolean testOnReturn;
    @Value("${spring.datasource.poolPreparedStatements}")
    private boolean poolPreparedStatements;
    @Value("${spring.datasource.maxPoolPreparedStatementPerConnectionSize}")
    private int maxPoolPreparedStatementPerConnectionSize;
    @Value("${spring.datasource.filters}")
    private String filters;
    @Value("{spring.datasource.connectionProperties}")
    private String connectionProperties;

    @Bean     //声明其为Bean实例
    @Primary  //在同样的DataSource中，首先使用被标注的DataSource
    public DataSource dataSource() {
        DruidDataSource datasource = new DruidDataSource();
        datasource.setUrl(this.dbUrl);
        datasource.setUsername(username);
        datasource.setPassword(password);
        datasource.setDriverClassName(driverClassName);

        //configuration
        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) {
            System.err.println("druid configuration initialization filter: " + e);
        }
        datasource.setConnectionProperties(connectionProperties);
        return datasource;
    }

    @Bean
    public ServletRegistrationBean statViewServle() {
        ServletRegistrationBean servletRegistrationBean = new ServletRegistrationBean(new StatViewServlet(), "/druid/*");
        // IP白名单
        servletRegistrationBean.addInitParameter("allow", "127.0.0.1");
        // IP黑名单(共同存在时，deny优先于allow)
        servletRegistrationBean.addInitParameter("deny", "192.168.1.100");
        //控制台管理用户
        servletRegistrationBean.addInitParameter("loginUsername", "druid");
        servletRegistrationBean.addInitParameter("loginPassword", "druid");
        //是否能够重置数据
        servletRegistrationBean.addInitParameter("resetEnable", "false");
        return servletRegistrationBean;
    }

    @Bean
    public FilterRegistrationBean statFilter() {
        FilterRegistrationBean filterRegistrationBean = new FilterRegistrationBean(new WebStatFilter());
        //添加过滤规则
        filterRegistrationBean.addUrlPatterns("/*");
        //忽略过滤的格式
        filterRegistrationBean.addInitParameter("exclusions", "*.js,*.gif,*.jpg,*.png,*.css,*.ico,/druid/*");
        return filterRegistrationBean;
    }
}

重启项目

访问 : 项目链接+/druid/login.html

相关文档

https://github.com/alibaba/druid