Druid连接池是阿里巴巴开源的数据库连接池项目。Druid连接池为监控而生,内置强大的监控功能,监控特性不影响性能。功能强大,能防SQL注入,内置Loging能诊断Hack应用行为。
Druid连接池是阿里巴巴内部唯一使用的连接池,在内部数据库相关中间件TDDL/DRDS 都内置使用强依赖了Druid连接池,经过阿里内部数千上万的系统大规模验证,经过历年双十一超大规模并发验证。
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
<!-- 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>
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/*
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;
}
}
@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" ;
}
}
完成一次数据请求后,访问如下链接。
http://localhost:8007/druid
输入配置的用户名和密码:
root root
主要展示链接数据库的基础信息。
连接池配置的各项详细属性,可以参考这里查看,无需再从网上查找。
所有执行的SQL,都会在这里被监控到,且会有SQL执行的详细计划。
GitHub地址:知了一笑
https://github.com/cicadasmile
码云地址:知了一笑
https://gitee.com/cicadasmile
免责声明:本站发布的内容(图片、视频和文字)以原创、转载和分享为主,文章观点不代表本网站立场,如果涉及侵权请联系站长邮箱:is@yisu.com进行举报,并提供相关证据,一经查实,将立刻删除涉嫌侵权内容。