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Hikari常用连接参数说明
Hikari 为 SpringBoot2.0默认的连接池，Hikary常用连接参数说明
| 参数 | 说明 |
| maxLifeTime | 池中连接的最大生存期。使用中的连接永远不会停止使用，只有在关闭连接后才将其删除。默认30min，不能小于30s，若小于，将设置为默认值 |
| connectionTimeout | 等待来自池的连接的最大毫秒数。默认30min，不能小于250ms，若小于，将设置为默认值 |
| validationTimeout | 测试连接的活动性的最长时间。默认5min，不能小于250ms，若小于，将设置为默认值。此值必须小于connectionTimeout |
| maxPoolSize | 池达到的最大连接，包括空闲和使用中的连接。默认10。需按实际应用运行设置 |
| minIdle | 池中的最小空闲连接数。默认=maxPoolSize，若小于0或大于maxPoolSize，则设置为maxPoolSize。为了获得峰值需求响应，可不设置 |
| idleTimeout | 允许连接在池中保持空闲状态的最长时间。若idleTimeout>maxLifeTime，则设置为0，若idleTimeout<10s，则设置为10min，若minIdle == maxPoolSize并且idleTimeout<>10s，则设置不起作用 |
| auto-commit | 从池返回的连接的默认自动提交行为，默认true。 |
业务应用配置
连接池配置，以供参考。
hikari: pool-name: carpool minimum-idle: 3 maximum-pool-size: 10 idle-timeout: 30000 connection-timeout: 30000 max-lifetime: 60000如有以下警告信息
Failed to validate connection org.postgresql.jdbc.PgConnection@605c8e77 (This connection has been closed.). Possibly consider using a shorter maxLifetime value. 或抛出以下异常，则可将maxLifetime设的短一点。
2023-12-02 10:56:20.103 [32mERROR[0;39m --- [http-nio-8080-exec-2] [36mo.a.c.c.C.[.[localhost].[/].[dispatcherServlet][0;39m : Servlet.service() for servlet [dispatcherServlet] in context with path [] threw exception [Request processing failed; nested exception is org.springframework.transaction.CannotCreateTransactionException: Could not open JDBC Connection for transaction; nested exception is java.sql.SQLTransientConnectionException: carpool - Connection is not available, request timed out after 20056ms.] with root cause org.postgresql.util.PSQLException: This connection has been closed. at org.postgresql.jdbc.PgConnection.checkClosed(PgConnection.java:865) at org.postgresql.jdbc.PgConnection.setNetworkTimeout(PgConnection.java:1647) at com.zaxxer.hikari.pool.PoolBase.setNetworkTimeout(PoolBase.java:560) at com.zaxxer.hikari.pool.PoolBase.isConnectionAlive(PoolBase.java:173) at com.zaxxer.hikari.pool.HikariPool.getConnection(HikariPool.java:186) at com.zaxxer.hikari.pool.HikariPool.getConnection(HikariPool.java:162) at com.zaxxer.hikari.HikariDataSource.getConnection(HikariDataSource.java:128)HikariCP监控
若需要监控数据库连接池设置是否合理, 需要能监控到连接池对应的指标, 具体如何操作，可依据以下进行配置。.
1. 增加依赖
<dependency> <groupId>io.dropwizard.metrics</groupId> <artifactId>metrics-core</artifactId> <version>4.0.7</version> </dependency>2. 增加配置类
@Configuration public class DataSourceConfig { private final static Logger LOGGER = LoggerFactory.getLogger(DataSourceConfig.class); @Bean @ConfigurationProperties(prefix = "spring.datasource.hikari") public HikariDataSource dataSource(DataSourceProperties properties){ HikariDataSource dataSource = properties.initializeDataSourceBuilder() .type(HikariDataSource.class) .build(); dataSource.setMetricRegistry(initMetricRegistry("carpool")); return dataSource; } public MetricRegistry initMetricRegistry(String poolName) { MetricRegistry metricRegistry = new MetricRegistry(); Slf4jReporter reporter = Slf4jReporter.forRegistry(metricRegistry) .outputTo(LOGGER) .convertRatesTo(TimeUnit.SECONDS) .convertDurationsTo(TimeUnit.MILLISECONDS) .build(); reporter.start(30, TimeUnit.SECONDS);//30秒打印一次 return metricRegistry; } }3. 打印结果
name=carpool.pool.ActiveConnections, value=0 //活跃的连接数 name=carpool.pool.IdleConnections, value=5 //空闲连接数 name=carpool.pool.MaxConnections, value=50 //最大连接数 name=carpool.pool.MinConnections, value=5 //最小连接数 name=carpool.pool.PendingConnections, value=0 //正在等待连接的线程数量。若大于0，则可适当调整最大连接数，即maxPoolSize name=carpool.pool.TotalConnections, value=5 //总连接数，=ActiveConnections+IdleConnections //创建连接时间，单位(ms) name=carpool.pool.ConnectionCreation, count=64, min=20, max=42, mean=25.4595, stddev=4.7287, median=25.0, p75=27.0, p95=35.0, p98=41.0, p99=41.0, p999=41.0 //连接从池中取出到返回的时间，单位(ms) name=carpool.pool.Usage, count=12, min=1, max=161, mean=16.677, stddev=37.069, median=5.0, p75=7.0, p95=90.0, p98=161.0, p99=161.0, p999=161.0 //连接超时比率 name=carpool.pool.ConnectionTimeoutRate, count=0, mean_rate=0.0, m1=0.0, m5=0.0, m15=0.0, rate_unit=events/second //连接等待时间，单位(ms) name=carpool.pool.Wait, count=12, min=0.0216, max=3.9868, mean=2.80117, stddev=1.66339, median=1.9914, p75=3.8614, p95=3.9868, p98=3.9868, p99=3.9868, p999=3.9868, mean_rate=0.0, m1=6.3693E-6, m5=0.078474, m15=0.86262, rate_unit=events/second, duration_unit=milliseconds 免责声明：本站所有文章内容,图片，视频等均是来源于用户投稿和互联网及文摘转载整编而成，不代表本站观点，不承担相关法律责任。其著作权各归其原作者或其出版社所有。如发现本站有涉嫌抄袭侵权/违法违规的内容,侵犯到您的权益，请在线联系站长,一经查实,本站将立刻删除。 本文来自网络,若有侵权，请联系删除，如若转载，请注明出处：https://haidsoft.com/133330.html
