jHipster - 集成druid

step 1. 增加druid依赖

修改 pom.xml
在 标签内部追加以下配置

    4.0.0
 
 ...

    
        ... 
        
            fr.ippon.spark.metrics
            metrics-spark-reporter
            ${metrics-spark-reporter.version}
        
        
        
            com.alibaba
            druid
            1.0.25
        
    
   ...

step 2. 修改application-dev.yml / application-prod.xml配置

加完依赖的jar之后，我们还希望对druid进行一些配置，可以根据实际情况选择修改的文件，在这我们选择 src\main\resources\config\application-dev.yml

# ===================================================================
# Spring Boot configuration.
#
# This configuration will be overriden by the Spring profile you use,
# for example application-dev.yml if you use the "dev" profile.
# ===================================================================

# ===================================================================
# Standard Spring Boot properties.
# Full reference is available at:
# http://docs.spring.io/spring-boot/docs/current/reference/html/common-application-properties.html
# ===================================================================

management:
    context-path: /management
    health:
        mail:
            enabled: false # When using the MailService, configure an SMTP server and set this to true
spring:
    application:
        name: cms
    .......
    datasource:
        # type: com.zaxxer.hikari.HikariDataSource
        type: com.alibaba.druid.pool.DruidDataSource
        url: jdbc:mysql://localhost:3306/cms?useUnicode=true&characterEncoding=utf8&useSSL=false
        username: dev
        password: 123456
        hikari:
            data-source-properties:
                cachePrepStmts: true
                prepStmtCacheSize: 250
                prepStmtCacheSqlLimit: 2048
                useServerPrepStmts: true
        driverClassName: com.mysql.jdbc.Driver
        druid:
            initialSize: 5
            minIdle: 5
            maxActive: 20
            maxWait: 60000
            timeBetweenEvictionRunsMillis: 60000
            minEvictableIdleTimeMillis: 300000
            validationQuery: SELECT NOW()
            testWhileIdle: true
            testOnBorrow: false
            testOnReturn: false
            poolPreparedStatements: true
            maxPoolPreparedStatementPerConnectionSize: 20
            filters: stat,wall,log4j
            connectionProperties: druid.stat.mergeSql=true;druid.stat.slowSqlMillis=5000
.....

step 3. 添加druid配置类

创建一个新的java类

package cn.ctodb.cms.config;

import com.alibaba.druid.pool.DruidDataSource;
import com.alibaba.druid.support.http.StatViewServlet;
import com.alibaba.druid.support.http.WebStatFilter;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.beans.factory.annotation.Value;
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;
import org.springframework.context.annotation.Primary;

import javax.sql.DataSource;
import java.sql.SQLException;

@Configuration
public class DruidDBConfig {
    private Logger logger = LoggerFactory.getLogger(DruidDBConfig.class);

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

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

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

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

    @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     //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) {
            logger.error("druid configuration initialization filter", e);
        }
        datasource.setConnectionProperties(connectionProperties);

        return datasource;
    }

    // 注册druid后端监控的servlet
    @Bean
    public ServletRegistrationBean indexServletRegistration() {
        ServletRegistrationBean registration = new ServletRegistrationBean(new StatViewServlet());
        registration.addUrlMappings("/druid/*");
        registration.addInitParameter("allow", "127.0.0.1,192.168.1.105");// IP白名单(没有配置或者为空，则允许所有访问)
        registration.addInitParameter("deny", "");// IP黑名单 (存在共同时，deny优先于allow)
        registration.addInitParameter("loginUsername", "admin");// 用户名
        registration.addInitParameter("loginPassword", "123456");// 密码
        registration.addInitParameter("resetEnable", "false");// 禁用HTML页面上的“Reset All”功能
        return registration;
    }

    // 注册druid过滤器
    @Bean
    public FilterRegistrationBean indexFilterRegistration() {
        FilterRegistrationBean registration = new FilterRegistrationBean(new WebStatFilter());
        registration.addUrlPatterns("/*");
        registration.addInitParameter("exclusions", "*.js,*.gif,*.jpg,*.bmp,*.png,*.css,*.ico,/druid/*");
        return registration;
    }

}

传送门CTO智库 - JHipster用户指南