前言
Springboot让Java开发更加美好,更加简洁,更加简单。Spring Boot 2.x中使用HikariCP作为默认的数据连接池。 HikariCP使用Javassist字节码操作库来实现动态代理,优化并精简了字节码,同时内部使用 com.zaxxer.hikari.util.FastList
代替ArrayList、使用了更好的并发集合类 com.zaxxer.hikari.util.ConcurrentBag
,“号称”是目前最快的数据库连接池。
下面话不多说了,来一起看看详细的介绍吧
基本使用
在Spring Boot 2.x中使用HikariCP十分简单,只需引入依赖 implementation 'org.springframework.boot:spring-boot-starter-jdbc'
:
pluginManagement { repositories { gradlePluginPortal() }}rootProject.name = 'datasource-config'plugins { id 'org.springframework.boot' version '2.1.3.RELEASE' id 'java'}apply plugin: 'io.spring.dependency-management'group = 'spring-boot-guides'version = '0.0.1-SNAPSHOT'sourceCompatibility = '1.8'repositories { mavenCentral()}dependencies { implementation 'org.springframework.boot:spring-boot-starter-jdbc' runtimeOnly 'com.h2database:h2' testImplementation 'org.springframework.boot:spring-boot-starter-test'}
配置文件如下:
spring: datasource: url: jdbc:h2:mem:demodb username: sa password: hikari: # https://github.com/brettwooldridge/HikariCP (uses milliseconds for all time values) maximumPoolSize: 10 minimumIdle: 2 idleTimeout: 600000 connectionTimeout: 30000 maxLifetime: 1800000
关于连接池的具体配置参数详见 HikariCP 。
示例代码如下:
package springbootguides.datasourceconfig;import org.springframework.beans.factory.annotation.Autowired;import org.springframework.boot.CommandLineRunner;import org.springframework.boot.SpringApplication;import org.springframework.boot.autoconfigure.SpringBootApplication;import javax.sql.DataSource;import java.sql.Connection;@SpringBootApplicationpublic class DatasourceConfigApplication implements CommandLineRunner { @Autowired private DataSource datasource; @Override public void run(String... args) throws Exception { try(Connection conn = datasource.getConnection()) { System.out.println(conn); } } public static void main(String[] args) { SpringApplication.run(DatasourceConfigApplication.class, args); }}
实现原理
Spring Boot使用如下方式整合HikariCP:入口是 org.springframework.boot.autoconfigure.jdbc.DataSourceAutoConfiguration
,通过 org.springframework.boot.autoconfigure.jdbc.DataSourceConfiguration.Hikari
中的 @Bean 方式创建 com.zaxxer.hikari.HikariDataSource
:
/** * Hikari DataSource configuration. */ @ConditionalOnClass(HikariDataSource.class) @ConditionalOnMissingBean(DataSource.class) @ConditionalOnProperty(name = "spring.datasource.type", havingValue = "com.zaxxer.hikari.HikariDataSource", matchIfMissing = true) static class Hikari { @Bean @ConfigurationProperties(prefix = "spring.datasource.hikari") public HikariDataSource dataSource(DataSourceProperties properties) { HikariDataSource dataSource = createDataSource(properties, HikariDataSource.class); if (StringUtils.hasText(properties.getName())) { dataSource.setPoolName(properties.getName()); } return dataSource; } }
@ConfigurationProperties(prefix = "spring.datasource.hikari")
会自动把 spring.datasource.hikari.*
相关的连接池配置信息注入到创建的HikariDataSource实例中。
HikariCP的监控和遥测
因为在我们的微服务体系中使用的监控系统是Prometheus,这里以Prometheus为例。
注意spring boot 2.0对spring boot 1.x的metrics进行了重构,不再向后兼容,主要是在spring-boot-acutator中使用了micrometer,支持了更多的监控系统:Atlas、Datadog、Ganglia、Graphite、Influx、JMX、NewRelic、Prometheus、SignalFx、StatsD、Wavefront。Spring boot 2.0的metrics对比spring boot 1.x除了引入micrometer外,更大的体现是支持了tag,这也说明Prometheus、Influx等支持Tag的时序监控数据模型的监控系统已经成为主流。
在前面示例中的build.gradle中加入如下依赖:
implementation 'org.springframework.boot:spring-boot-starter-web'implementation 'org.springframework.boot:spring-boot-starter-actuator'implementation 'io.micrometer:micrometer-registry-prometheus'
配置文件applycation.yaml中加入对actuator的配置:
management: endpoints: web: exposure: include: "health,info,prometheus" server: port: 8079 servlet: context-path: /
注意这里引入了web和actuator依赖,通过配置 management.server.port 指定actuator的web端点为8089端口,通过 management.endpoints.include 对外开放 /actuator/prometheus ,在引入 io.micrometer:micrometer-registry-prometheus 依赖之后,端点 /actuator/prometheus 当即生效。
curl http://localhost:8079/actuator/prometheus | grep hikari# TYPE hikaricp_connections_acquire_seconds summaryhikaricp_connections_acquire_seconds_count{pool="HikariPool-1",} 3.0hikaricp_connections_acquire_seconds_sum{pool="HikariPool-1",} 0.001230082# HELP hikaricp_connections_acquire_seconds_max Connection acquire time# TYPE hikaricp_connections_acquire_seconds_max gaugehikaricp_connections_acquire_seconds_max{pool="HikariPool-1",} 0.0# HELP hikaricp_connections_min Min connections# TYPE hikaricp_connections_min gaugehikaricp_connections_min{pool="HikariPool-1",} 2.0# TYPE hikaricp_connections_timeout_total counterhikaricp_connections_timeout_total{pool="HikariPool-1",} 0.0# HELP hikaricp_connections_pending Pending threads# TYPE hikaricp_connections_pending gaugehikaricp_connections_pending{pool="HikariPool-1",} 0.0# HELP hikaricp_connections_usage_seconds Connection usage time# TYPE hikaricp_connections_usage_seconds summaryhikaricp_connections_usage_seconds_count{pool="HikariPool-1",} 3.0hikaricp_connections_usage_seconds_sum{pool="HikariPool-1",} 0.06# HELP hikaricp_connections_usage_seconds_max Connection usage time# TYPE hikaricp_connections_usage_seconds_max gaugehikaricp_connections_usage_seconds_max{pool="HikariPool-1",} 0.0# HELP hikaricp_connections_max Max connections# TYPE hikaricp_connections_max gaugehikaricp_connections_max{pool="HikariPool-1",} 10.0# HELP hikaricp_connections Total connections# TYPE hikaricp_connections gaugehikaricp_connections{pool="HikariPool-1",} 2.0# HELP hikaricp_connections_creation_seconds_max Connection creation time# TYPE hikaricp_connections_creation_seconds_max gaugehikaricp_connections_creation_seconds_max{pool="HikariPool-1",} 0.0# HELP hikaricp_connections_creation_seconds Connection creation time# TYPE hikaricp_connections_creation_seconds summaryhikaricp_connections_creation_seconds_count{pool="HikariPool-1",} 1.0hikaricp_connections_creation_seconds_sum{pool="HikariPool-1",} 0.001# HELP hikaricp_connections_idle Idle connections# TYPE hikaricp_connections_idle gaugehikaricp_connections_idle{pool="HikariPool-1",} 2.0# HELP hikaricp_connections_active Active connections# TYPE hikaricp_connections_active gaugehikaricp_connections_active{pool="HikariPool-1",} 0.0
参考
• HikariCP
总结
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