下载链接：https://github.com/alibaba/druid/wiki

官网：https://druid.apache.org/ 其实没必要去看

我们直接 SpringBoot 整合

        <!-- Druid数据库连接池 -->
        <dependency>
            <groupId>com.alibaba</groupId>
            <artifactId>druid-spring-boot-starter</artifactId>
            <version>1.2.8</version>
            <!-- 不同版本可能会报错，Springboot2.5.5使用Druid版本 -->
        </dependency>

设置 数据源类型

# 线上+
spring.datasource.url=jdbc:mysql://127.0.0.1:3306/XXDB?useUnicode=true&useJDBCCompliantTimezoneShift=true&useLegacyDatetimeCode=false&serverTimezone=UTC&useSSL=false&characterEncoding=utf8
spring.datasource.driver-class-name=com.mysql.cj.jdbc.Driver
spring.datasource.username=root
spring.datasource.password=root

#Druid详细配置
spring.datasource.druid.initial-size=5
spring.datasource.druid.max-active=20
spring.datasource.druid.min-idle=5
#spring.datasource.druid.max-wait=60000
spring.datasource.druid.max-wait=10000
spring.datasource.druid.pool-prepared-statements=true
spring.datasource.druid.max-pool-prepared-statement-per-connection-size=20
# spring.datasource.druid.max-open-prepared-statements= #和上面的等价
spring.datasource.druid.validation-query=
spring.datasource.druid.validation-query-timeout=
spring.datasource.druid.test-on-borrow=
spring.datasource.druid.test-on-return=
spring.datasource.druid.test-while-idle=
spring.datasource.druid.time-between-eviction-runs-millis=
spring.datasource.druid.min-evictable-idle-time-millis=
spring.datasource.druid.max-evictable-idle-time-millis=
spring.datasource.druid.filters=stat
# Druid 慢日志 可以用sql： SELECT SLEEP(10)即可获得10秒的慢sql
spring.datasource.druid.filter.stat.log-slow-sql=true
spring.datasource.druid.filter.stat.slow-sql-millis=5000

YML比较老了，忽略吧，我留着的作用仅做对照使用。

spring:
  #配置数据库连接信息
  datasource:
    url: jdbc:mysql://192.168.3.110:3306/govbuy?useUnicode=true&useJDBCCompliantTimezoneShift=true&useLegacyDatetimeCode=false&serverTimezone=UTC&useSSL=false&characterEncoding=utf8

    username: ****

    password: ****
    driver-class-name: com.mysql.jdbc.Driver
    # 这样就不会使用Springboot默认的连接池Hikari
    type: com.alibaba.druid.pool.DruidDataSource
    druid:
      initial-size: 5
      min-idle: 5
      max-active: 20
      test-while-idle: true
      test-on-borrow: false
      test-on-return: false
      pool-prepared-statements: true
      max-pool-prepared-statement-per-connection-size: 20
      max-wait: 60000
      time-between-eviction-runs-millis: 60000
      min-evictable-idle-time-millis: 30000
      filters: stat
      async-init: true
      # 通过connectProperties属性来打开mergeSql功能；慢SQL记录
      connection-properties: druid.stat.mergeSql=true;druid.stat.SlowSqlMills=5000
      # 监控后台的配置，如登录账号和密码等
      monitor:
        #下面内容被配置文件覆盖了 下面不生效
        allow: 127.0.0.1
        loginUsername: ok
        loginPassword: ok

添加配置DruidConfig类

import com.alibaba.druid.pool.DruidDataSource;
import com.alibaba.druid.support.http.StatViewServlet;
import com.alibaba.druid.support.http.WebStatFilter;
import org.springframework.boot.context.properties.ConfigurationProperties;
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 javax.sql.DataSource;
import java.util.Arrays;
import java.util.HashMap;
import java.util.Map;

/**
 * @author : zanglikun
 * @date : 2021/9/25 17:11
 * @Version: 1.0
 * @Desc : Druid 配置文件
 */
@Configuration
public class DruidConfig {

    // 以下druid()方法配置会使在application.yml中后半部分的配置生效
    @ConfigurationProperties(prefix = "spring.datasource")
    @Bean
    public DataSource druidDataSource() {
        return new DruidDataSource();
    }

    // 配置Druid的监控。配置一个管理后台的Servlet
    @Bean
    public ServletRegistrationBean statViewServlet() {
        ServletRegistrationBean bean = new ServletRegistrationBean(new StatViewServlet(), "/druid/*");
        Map<String, String> initParams = new HashMap<>();
        initParams.put("loginUsername", "admin");
        initParams.put("loginPassword", "123456");
        initParams.put("allow", "");//默认就是允许所有访问
        bean.setInitParameters(initParams);
        return bean;
    }

    // 2、配置一个web监控的filter
    @Bean
    public FilterRegistrationBean webStatFilter() {
        FilterRegistrationBean bean = new FilterRegistrationBean();
        bean.setFilter(new WebStatFilter());
        Map<String, String> initParams = new HashMap<>();
        initParams.put("exclusions", "*.js,*.gif,*.jpg,*.png,*.css,*.ico,/druid/*");
        bean.setInitParameters(initParams);
        bean.setUrlPatterns(Arrays.asList("/*"));
        return bean;
    }

}

启动项目

初始化成功！！！

访问我们项目后缀加上 /druid 即可 如：127.0.0.1:8080/druid

如果数据源有这个

解决无效！！！不管他！

Druid中使用log4j2进行日志输出

点击标题 跳到Github 的原文

步骤 简述：pom文件去除原有依赖，添加 log4j2.xml ,配置 application.yml 文件

1、pom.xml 坐标配置

<!--Spring-boot中去掉logback的依赖-->
<dependency>
	<groupId>org.springframework.boot</groupId>
	<artifactId>spring-boot-starter-web</artifactId>
	<exclusions>
		<exclusion>
			<groupId>org.springframework.boot</groupId>
			<artifactId>spring-boot-starter-logging</artifactId>
		</exclusion>
	</exclusions>
</dependency>

<!--日志-->
<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-log4j2</artifactId>
</dependency>
        <dependency>
            <groupId>org.springframework</groupId>
            <artifactId>spring-jdbc</artifactId>
        </dependency>

<!--数据库连接池-->
<dependency>
	<groupId>com.alibaba</groupId>
	<artifactId>druid-spring-boot-starter</artifactId>
	<version>1.1.6</version>
</dependency>

2、配置application.properties

# 配置日志输出
spring.datasource.druid.filter.slf4j.enabled=true
spring.datasource.druid.filter.slf4j.statement-create-after-log-enabled=false
spring.datasource.druid.filter.slf4j.statement-close-after-log-enabled=false
spring.datasource.druid.filter.slf4j.result-set-open-after-log-enabled=false
spring.datasource.druid.filter.slf4j.result-set-close-after-log-enabled=false
      filter:
        slf4j:
          enabled: true
          statement-create-after-log-enabled: false
          statement-close-after-log-enabled: false
          result-set-open-after-log-enabled: false
          result-set-close-after-log-enabled: false

3、添加log4j2.xml文件中的日志配置(完整，可直接拷贝使用)

<?xml version="1.0" encoding="UTF-8"?>
<configuration status="OFF">
    <appenders>

        <Console name="Console" target="SYSTEM_OUT">
            <!--只接受程序中DEBUG级别的日志进行处理-->
            <ThresholdFilter level="DEBUG" onMatch="ACCEPT" onMismatch="DENY"/>
            <PatternLayout pattern="[%d{HH:mm:ss.SSS}] %-5level %class{36} %L %M - %msg%xEx%n"/>
        </Console>

        <!--处理DEBUG级别的日志，并把该日志放到logs/debug.log文件中-->
        <!--打印出DEBUG级别日志，每次大小超过size，则这size大小的日志会自动存入按年份-月份建立的文件夹下面并进行压缩，作为存档-->
        <RollingFile name="RollingFileDebug" fileName="./logs/debug.log"
                     filePattern="logs/$${date:yyyy-MM}/debug-%d{yyyy-MM-dd}-%i.log.gz">
            <Filters>
                <ThresholdFilter level="DEBUG"/>
                <ThresholdFilter level="INFO" onMatch="DENY" onMismatch="NEUTRAL"/>
            </Filters>
            <PatternLayout
                    pattern="[%d{yyyy-MM-dd HH:mm:ss}] %-5level %class{36} %L %M - %msg%xEx%n"/>
            <Policies>
                <SizeBasedTriggeringPolicy size="500 MB"/>
                <TimeBasedTriggeringPolicy/>
            </Policies>
        </RollingFile>

        <!--处理INFO级别的日志，并把该日志放到logs/info.log文件中-->
        <RollingFile name="RollingFileInfo" fileName="./logs/info.log"
                     filePattern="logs/$${date:yyyy-MM}/info-%d{yyyy-MM-dd}-%i.log.gz">
            <Filters>
                <!--只接受INFO级别的日志，其余的全部拒绝处理-->
                <ThresholdFilter level="INFO"/>
                <ThresholdFilter level="WARN" onMatch="DENY" onMismatch="NEUTRAL"/>
            </Filters>
            <PatternLayout
                    pattern="[%d{yyyy-MM-dd HH:mm:ss}] %-5level %class{36} %L %M - %msg%xEx%n"/>
            <Policies>
                <SizeBasedTriggeringPolicy size="500 MB"/>
                <TimeBasedTriggeringPolicy/>
            </Policies>
        </RollingFile>

        <!--处理WARN级别的日志，并把该日志放到logs/warn.log文件中-->
        <RollingFile name="RollingFileWarn" fileName="./logs/warn.log"
                     filePattern="logs/$${date:yyyy-MM}/warn-%d{yyyy-MM-dd}-%i.log.gz">
            <Filters>
                <ThresholdFilter level="WARN"/>
                <ThresholdFilter level="ERROR" onMatch="DENY" onMismatch="NEUTRAL"/>
            </Filters>
            <PatternLayout
                    pattern="[%d{yyyy-MM-dd HH:mm:ss}] %-5level %class{36} %L %M - %msg%xEx%n"/>
            <Policies>
                <SizeBasedTriggeringPolicy size="500 MB"/>
                <TimeBasedTriggeringPolicy/>
            </Policies>
        </RollingFile>

        <!--处理error级别的日志，并把该日志放到logs/error.log文件中-->
        <RollingFile name="RollingFileError" fileName="./logs/error.log"
                     filePattern="logs/$${date:yyyy-MM}/error-%d{yyyy-MM-dd}-%i.log.gz">
            <ThresholdFilter level="ERROR"/>
            <PatternLayout
                    pattern="[%d{yyyy-MM-dd HH:mm:ss}] %-5level %class{36} %L %M - %msg%xEx%n"/>
            <Policies>
                <SizeBasedTriggeringPolicy size="500 MB"/>
                <TimeBasedTriggeringPolicy/>
            </Policies>
        </RollingFile>

        <!--druid的日志记录追加器-->
        <RollingFile name="druidSqlRollingFile" fileName="./logs/druid-sql.log"
                     filePattern="logs/$${date:yyyy-MM}/api-%d{yyyy-MM-dd}-%i.log.gz">
            <PatternLayout pattern="[%d{yyyy-MM-dd HH:mm:ss}] %-5level %L %M - %msg%xEx%n"/>
            <Policies>
                <SizeBasedTriggeringPolicy size="500 MB"/>
                <TimeBasedTriggeringPolicy/>
            </Policies>
        </RollingFile>
    </appenders>

    <loggers>
        <root level="DEBUG">
            <appender-ref ref="Console"/>
            <appender-ref ref="RollingFileInfo"/>
            <appender-ref ref="RollingFileWarn"/>
            <appender-ref ref="RollingFileError"/>
            <appender-ref ref="RollingFileDebug"/>
        </root>

        <!--记录druid-sql的记录-->
        <logger name="druid.sql.Statement" level="debug" additivity="false">
            <appender-ref ref="druidSqlRollingFile"/>
        </logger>
        <logger name="druid.sql.Statement" level="debug" additivity="false">
            <appender-ref ref="druidSqlRollingFile"/>
        </logger>

        <!--log4j2 自带过滤日志-->
        <Logger name="org.apache.catalina.startup.DigesterFactory" level="error" />
        <Logger name="org.apache.catalina.util.LifecycleBase" level="error" />
        <Logger name="org.apache.coyote.http11.Http11NioProtocol" level="warn" />
        <logger name="org.apache.sshd.common.util.SecurityUtils" level="warn"/>
        <Logger name="org.apache.tomcat.util.net.NioSelectorPool" level="warn" />
        <Logger name="org.crsh.plugin" level="warn" />
        <logger name="org.crsh.ssh" level="warn"/>
        <Logger name="org.eclipse.jetty.util.component.AbstractLifeCycle" level="error" />
        <Logger name="org.hibernate.validator.internal.util.Version" level="warn" />
        <logger name="org.springframework.boot.actuate.autoconfigure.CrshAutoConfiguration" level="warn"/>
        <logger name="org.springframework.boot.actuate.endpoint.jmx" level="warn"/>
        <logger name="org.thymeleaf" level="warn"/>
    </loggers>
</configuration>

自己随便测试：

[2018-02-07 14:15:50] DEBUG 134 statementLog - {conn-10001, pstmt-20000} created. INSERT INTO city  ( id,name,state ) VALUES( ?,?,? )
[2018-02-07 14:15:50] DEBUG 134 statementLog - {conn-10001, pstmt-20000} Parameters : [null, b2ffa7bd-6b53-4392-aa39-fdf8e172ddf9, a9eb5f01-f6e6-414a-bde3-865f72097550]
[2018-02-07 14:15:50] DEBUG 134 statementLog - {conn-10001, pstmt-20000} Types : [OTHER, VARCHAR, VARCHAR]
[2018-02-07 14:15:50] DEBUG 134 statementLog - {conn-10001, pstmt-20000} executed. 5.113815 millis. INSERT INTO city  ( id,name,state ) VALUES( ?,?,? )
[2018-02-07 14:15:50] DEBUG 134 statementLog - {conn-10001, stmt-20001} executed. 0.874903 millis. SELECT LAST_INSERT_ID()
[2018-02-07 14:15:52] DEBUG 134 statementLog - {conn-10001, stmt-20002, rs-50001} query executed. 0.622665 millis.

完成 去测试看看

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