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### 简单了解 1.思考,为啥用druid? > Druid是一个高效的数据查询系统,主要解决的是对于大量的基于时序的数据进行聚合查询。数据可以实时摄入,进入到Druid后立即可查,同时数据是几乎是不可变。通常是基于时序的事实事件,事实发生后进入Druid,外部系统就可以对该事实进行查询。 Druid采用的架构: shared-nothing架构与lambda架构 Druid设计三个原则: 1.快速查询(Fast Query) : 部分数据聚合(Partial Aggregate) + 内存华(In-Memory) + 索引(Index) 2.水平拓展能力(Horizontal Scalability):分布式数据(Distributed data)+并行化查询(Parallelizable Query) 3.实时分析(Realtime Analytics):Immutable Past , Append-Only Future 2.Druid的技术特点 * 数据吞吐量大 * 支持流式数据摄入和实时 * 查询灵活且快速 **反正就是很厉害了,** ### 引入依赖 ~~~ <!--druid--> <dependency> <groupId>com.alibaba</groupId> <artifactId>druid</artifactId> <version>1.1.20</version> </dependency> <dependency> <groupId>com.alibaba</groupId> <artifactId>druid-spring-boot-starter</artifactId> <version>1.1.20</version> </dependency> ~~~ 数据库配置 ~~~ ## 数据库访问配置 spring.datasource.druid.db-type=com.alibaba.druid.pool.DruidDataSource spring.datasource.druid.driverClassName=com.mysql.jdbc.Driver spring.datasource.druid.url=jdbc:mysql://118.24.93.185:3306/blog?useUnicode=true&characterEncoding=utf8&serverTimezone=GMT%2B8&useSSL=false spring.datasource.druid.username=blog spring.datasource.druid.password=123456 # 下面为连接池的补充设置,应用到上面所有数据源中 # 初始化大小,最小,最大 spring.datasource.druid.initial-size=5 spring.datasource.druid.min-idle=5 spring.datasource.druid.max-active=20 # 配置获取连接等待超时的时间 spring.datasource.druid.max-wait=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.druid.time-between-eviction-runs-millis=60000 # 配置一个连接在池中最小生存的时间,单位是毫秒 spring.datasource.druid.min-evictable-idle-time-millis=300000 spring.datasource.druid.validation-query=SELECT 1 FROM DUAL spring.datasource.druid.test-while-idle=true spring.datasource.druid.test-on-borrow=false spring.datasource.druid.test-on-return=false # 打开PSCache,并且指定每个连接上PSCache的大小 spring.datasource.druid.pool-prepared-statements=true spring.datasource.druid.max-pool-prepared-statement-per-connection-size=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.druid.filter.commons-log.connection-logger-name=stat,wall,log4j spring.datasource.druid.filter.stat.log-slow-sql=true spring.datasource.druid.filter.stat.slow-sql-millis=2000 # 通过connectProperties属性来打开mergeSql功能;慢SQL记录 spring.datasource.druid.connect-properties.=druid.stat.mergeSql=true;druid.stat.slowSqlMillis=5000 # 合并多个DruidDataSource的监控数据 spring.datasource.druid.use-global-data-source-stat=true ~~~ ### 新建ruidConfig文件 ~~~ package com.blog.config; 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 cfun * @description * @date 2019-11-19 */ @Configuration public class DruidConfig { // 将所有前缀为spring.datasource下的配置项都加载到DataSource中 @ConfigurationProperties(prefix = "spring.datasource.druid") @Bean public DataSource druidDataSource() { return new DruidDataSource(); } @Bean public ServletRegistrationBean druidStatViewServlet() { ServletRegistrationBean servletRegistrationBean = new ServletRegistrationBean(new StatViewServlet(),"/druid/*"); Map<String, String> initParams = new HashMap<>(); // 可配的属性都在 StatViewServlet 和其父类下 initParams.put("loginUsername", "cfun"); initParams.put("loginPassword", "123456"); servletRegistrationBean.setInitParameters(initParams); return servletRegistrationBean; } @Bean public FilterRegistrationBean druidWebStatFilter() { FilterRegistrationBean filterRegistrationBean = new FilterRegistrationBean(new WebStatFilter()); Map<String, String> initParams = new HashMap<>(); initParams.put("exclusions", "*.js,*.css,/druid/*"); filterRegistrationBean.setInitParameters(initParams); filterRegistrationBean.setUrlPatterns(Arrays.asList("/*")); return filterRegistrationBean; } } ~~~ 访问地址 [http://localhost:8082/druid/index.html](http://localhost:8082/druid/index.html) ![](https://img.kancloud.cn/e6/17/e617de92a551922e710e10ef8159536d_2214x1072.png)