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这篇文章给大家介绍SpringBoot2 中怎么使用Druid连接池,内容非常详细,感兴趣的小伙伴们可以参考借鉴,希望对大家能有所帮助。
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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。
稳定性特性,阿里巴巴的业务验证 完备的监控信息,快速诊断系统的瓶颈 内置了WallFilter 提供防SQL注入功能
MySQL mysql-connector-java 5.1.21 com.alibaba druid-spring-boot-starter 1.1.13 org.springframework.boot spring-boot-starter-jdbc
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。
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