SpringBoot2.0 base case (07): Druid integrated connection pooling, configuration monitoring interface

A, Druid connection pool

1, druid Profile

Druid connection pool Alibaba open source database connection pool project. Druid connection pool and health monitoring, built-in powerful monitoring capabilities, monitoring features without compromising performance. Powerful, can prevent SQL injection, built Loging can diagnose Hack application behavior.
Druid connection pool connection pool is the only use of the internal Alibaba, in an internal database related middleware TDDL / DRDS are built using a strong dependence of the Druid connection pool, through the internal Ali thousands of thousands of large-scale verification system, double eleven years after ultra-large-scale concurrent validation.

2, druid Features

1）稳定性特性，阿里巴巴的业务验证
2）完备的监控信息，快速诊断系统的瓶颈
3）内置了WallFilter 提供防SQL注入功能

Second, the integration framework SpringBoot2.0

1, rely on Core

<!-- 数据库依赖 -->
<dependency>
    <groupId>mysql</groupId>
    <artifactId>mysql-connector-java</artifactId>
    <version>5.1.21</version>
</dependency>
<dependency>
    <groupId>com.alibaba</groupId>
    <artifactId>druid-spring-boot-starter</artifactId>
    <version>1.1.13</version>
</dependency>
<!-- JDBC 依赖 -->
<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-jdbc</artifactId>
</dependency>

2, the data source profile

spring:
  application:
    # 应用名称
    name: node07-boot-druid
  datasource:
    type: com.alibaba.druid.pool.DruidDataSource
    druid:
      driverClassName: com.mysql.jdbc.Driver
      url: jdbc:mysql://localhost:3306/data_one?useUnicode=true&characterEncoding=UTF8&zeroDateTimeBehavior=convertToNull&useSSL=false
      username: root
      password: 123
      initial-size: 10
      max-active: 100
      min-idle: 10
      max-wait: 60000
      pool-prepared-statements: true
      max-pool-prepared-statement-per-connection-size: 20
      time-between-eviction-runs-millis: 60000
      min-evictable-idle-time-millis: 300000
      max-evictable-idle-time-millis: 60000
      validation-query: SELECT 1 FROM DUAL
      # validation-query-timeout: 5000
      test-on-borrow: false
      test-on-return: false
      test-while-idle: true
      connectionProperties: druid.stat.mergeSql=true;druid.stat.slowSqlMillis=5000
      #filters: #配置多个英文逗号分隔(统计，sql注入，log4j过滤)
      filters: stat,wall
      stat-view-servlet:
        enabled: true
        url-pattern: /druid/*

3, the core configuration class

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.Autowired;
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.jdbc.core.JdbcTemplate;

/**
 * Druid数据库连接池配置文件
 */
@Configuration
public class DruidConfig {
    private static final Logger logger = LoggerFactory.getLogger(DruidConfig.class);
    @Value("${spring.datasource.druid.url}")
    private String dbUrl;
    @Value("${spring.datasource.druid.username}")
    private String username;
    @Value("${spring.datasource.druid.password}")
    private String password;
    @Value("${spring.datasource.druid.driverClassName}")
    private String driverClassName;
    @Value("${spring.datasource.druid.initial-size}")
    private int initialSize;
    @Value("${spring.datasource.druid.max-active}")
    private int maxActive;
    @Value("${spring.datasource.druid.min-idle}")
    private int minIdle;
    @Value("${spring.datasource.druid.max-wait}")
    private int maxWait;
    @Value("${spring.datasource.druid.pool-prepared-statements}")
    private boolean poolPreparedStatements;
    @Value("${spring.datasource.druid.max-pool-prepared-statement-per-connection-size}")
    private int maxPoolPreparedStatementPerConnectionSize;
    @Value("${spring.datasource.druid.time-between-eviction-runs-millis}")
    private int timeBetweenEvictionRunsMillis;
    @Value("${spring.datasource.druid.min-evictable-idle-time-millis}")
    private int minEvictableIdleTimeMillis;
    @Value("${spring.datasource.druid.max-evictable-idle-time-millis}")
    private int maxEvictableIdleTimeMillis;
    @Value("${spring.datasource.druid.validation-query}")
    private String validationQuery;
    @Value("${spring.datasource.druid.test-while-idle}")
    private boolean testWhileIdle;
    @Value("${spring.datasource.druid.test-on-borrow}")
    private boolean testOnBorrow;
    @Value("${spring.datasource.druid.test-on-return}")
    private boolean testOnReturn;
    @Value("${spring.datasource.druid.filters}")
    private String filters;
    @Value("{spring.datasource.druid.connection-properties}")
    private String connectionProperties;
    /**
     * Druid 连接池配置
     */
    @Bean     //声明其为Bean实例
    public DruidDataSource dataSource() {
        DruidDataSource datasource = new DruidDataSource();
        datasource.setUrl(dbUrl);
        datasource.setUsername(username);
        datasource.setPassword(password);
        datasource.setDriverClassName(driverClassName);
        datasource.setInitialSize(initialSize);
        datasource.setMinIdle(minIdle);
        datasource.setMaxActive(maxActive);
        datasource.setMaxWait(maxWait);
        datasource.setTimeBetweenEvictionRunsMillis(timeBetweenEvictionRunsMillis);
        datasource.setMinEvictableIdleTimeMillis(minEvictableIdleTimeMillis);
        datasource.setMaxEvictableIdleTimeMillis(minEvictableIdleTimeMillis);
        datasource.setValidationQuery(validationQuery);
        datasource.setTestWhileIdle(testWhileIdle);
        datasource.setTestOnBorrow(testOnBorrow);
        datasource.setTestOnReturn(testOnReturn);
        datasource.setPoolPreparedStatements(poolPreparedStatements);
        datasource.setMaxPoolPreparedStatementPerConnectionSize(maxPoolPreparedStatementPerConnectionSize);
        try {
            datasource.setFilters(filters);
        } catch (Exception e) {
            logger.error("druid configuration initialization filter", e);
        }
        datasource.setConnectionProperties(connectionProperties);
        return datasource;
    }
    /**
     * JDBC操作配置
     */
    @Bean(name = "dataOneTemplate")
    public JdbcTemplate jdbcTemplate (@Autowired DruidDataSource dataSource){
        return new JdbcTemplate(dataSource) ;
    }

    /**
     * 配置 Druid 监控界面
     */
    @Bean
    public ServletRegistrationBean statViewServlet(){
        ServletRegistrationBean srb =
                new ServletRegistrationBean(new StatViewServlet(),"/druid/*");
        //设置控制台管理用户
        srb.addInitParameter("loginUsername","root");
        srb.addInitParameter("loginPassword","root");
        //是否可以重置数据
        srb.addInitParameter("resetEnable","false");
        return srb;
    }
    @Bean
    public FilterRegistrationBean statFilter(){
        //创建过滤器
        FilterRegistrationBean frb =
                new FilterRegistrationBean(new WebStatFilter());
        //设置过滤器过滤路径
        frb.addUrlPatterns("/*");
        //忽略过滤的形式
        frb.addInitParameter("exclusions",
                "*.js,*.gif,*.jpg,*.png,*.css,*.ico,/druid/*");
        return frb;
    }
}

4, simple test class

@RestController
public class DruidController {
    private static final Logger LOG = LoggerFactory.getLogger(DruidController.class);
    @Resource
    private JdbcTemplate jdbcTemplate ;
    @RequestMapping("/druidData")
    public String druidData (){
        String sql = "SELECT COUNT(1) FROM d_phone" ;
        Integer countOne = jdbcTemplate.queryForObject(sql,Integer.class) ;
        // countOne==2
        LOG.info("countOne=="+countOne);
        return "success" ;
    }
}

Third, the test results

After completing a data request, visit the links below.

http://localhost:8007/druid
输入配置的用户名和密码：
root root

1, Druid monitor Home

The main display basic information link to the database.

2, Druid monitoring data source

The detailed properties of the connection pool configuration, you can refer here, no longer need to look for from the Internet.

3, Druid monitoring implementation of SQL

All executed SQL, will be here to be monitored, and there will be a detailed plan for the implementation of SQL.

Fourth, the source code

GitHub地址：知了一笑
https://github.com/cicadasmile
码云地址：知了一笑
https://gitee.com/cicadasmile