此系列文章将会描述Java框架Spring Boot、服务治理框架Dubbo、应用容器引擎Docker,及使用Spring Boot集成Dubbo、Mybatis等开源框架,其中穿插着Spring Boot中日志切面等技术的实现,然后通过gitlab-CI以持续集成为Docker镜像。
本文为使用Spring Boot AOP 实现日志切面、分离INFO和ERROR级别日志
本系列文章中所使用的框架版本为Spring Boot 2.0.3-RELEASE,Spring 5.0.7-RELEASE,Dubbo 2.6.2。
通用日志组件
为了便于记录日志,实现了通用的日志组件,通过使用注解@Loggable
标记方法即可编制入日志切面中
日至切面及日志输出规则均已集成于Maven Archetype
通用日志组件通过以下配置引用
日志切面
根据定义日志切点(@Loggable
)环绕处理逻辑:
- 根据注解值获取相应的日志对象
- 记录日志信息
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@Aspect
@Component
public class LogAspect {
private static final Map<Class<?>, Logger> loggerHolder = new ConcurrentHashMap<Class<?>, Logger>();
@Pointcut(value = "@annotation(com.linghit.common.log.annotation.Loggable)")
public void log() {
}
/**
*
* around:根据日志注解类型为方法调用记录日志 <br/>
*/
@Around("log()")
public Object around(ProceedingJoinPoint joinPoint) throws Throwable {
AbstractLogBean logBean = null;
Method method = MethodSignature.class.cast(joinPoint.getSignature())
.getMethod();
Annotation[] annotations = method.getAnnotations();
for (Annotation annotation : annotations) {
if (annotation instanceof Loggable) {
Loggable loggable = Loggable.class.cast(annotation);
logBean = getLogBean(loggable.value(), joinPoint);
break;
}
}
Object retVal = null;
if (null == logBean) {
retVal = joinPoint.proceed(joinPoint.getArgs());
} else {
logBean.setEventName(StringUtils.isBlank(logBean.getEventName()) ? method
.getName() : logBean.getEventName() + "_"
+ method.getName());
logBean.setRequest(joinPoint.getArgs());
try {
retVal = joinPoint.proceed(joinPoint.getArgs());
} catch (Exception e) {
retVal = Resp.createError(RespCode.BUSINESS_INVALID,
"service.fail", "服务失败");
logBean.setE(e);
} finally {
logBean.setResponse(retVal);
Logger logger = getLogger(joinPoint.getTarget().getClass());
LogUtils.log(logger, logBean);
}
}
return retVal;
}
private AbstractLogBean getLogBean(DataAccessType type, JoinPoint joinPoint) {
AbstractLogBean logBean = null;
switch (type.getValue()) {
case "MySQL":
logBean = DataAccessLogBean.newDataAccessMysqlLogBean();
break;
case "Http":
logBean = DataAccessLogBean.newDataAccessHttpLogBean();
break;
case "Redis":
logBean = DataAccessLogBean.newDataAccessRedisLogBean();
break;
default:
logBean = new ServiceAccessLogBean(joinPoint.getTarget().getClass()
.getSimpleName(), DataAccessType.DUBBO.getValue(),
RpcContextUtils.getClientIp(),
RpcContextUtils.getLocalAddress());
}
return logBean;
}
private Logger getLogger(Class<?> clazz) {
if (!loggerHolder.containsKey(clazz)) {
loggerHolder.put(clazz, LoggerFactory.getLogger(clazz));
}
return loggerHolder.get(clazz);
}
}
日志注解
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@Target({ ElementType.METHOD })
@Retention(RetentionPolicy.RUNTIME)
@Inherited
@Documented
public @interface Loggable {
/**
* Name of the logType in which the logging takes place.
* <p>
* May be used to determine the target cache (or caches), matching the
* qualifier value (or the bean name(s)) of (a) specific bean definition.
*/
DataAccessType value() default DataAccessType.DUBBO;
}
切面扫描及使用
Spring Boot启动类扫描日志切面组件,及配置切面代理为true
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@EnableAspectJAutoProxy(proxyTargetClass = true)
@ComponentScan("com.linghit.ocs.zhanxing.service.handler.LogAspect")
使用时只需在相应方法处加入
@Loggable
注解
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@Loggable
public void test{}
相关依赖
Spring Boot AOP 起步依赖
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<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-aop</artifactId>
<version>${springboot.version}</version>
</dependency>
日志分离术
为了便于查看及采集错误日志,下述配置设置INFO
与ERROR
日志输出至不同文件
filePattern中需含有%i,每次rollover时,计数器将每次加1,若达到max的值,将删除旧的文件
log4j2.xml
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<?xml version="1.0" encoding="UTF-8"?>
<Configuration status="info" monitorInterval="30"
name="Log4j2Config">
<Properties>
<Property name="PATTERN">[%p] [%d{yyyy-MM-dd HH:mm:ss}][%c{10}]%m%n
</Property>
<Property name="filePatch">./log/${projectName}/</Property>
<Property name="fileName">${projectName}.log</Property>
<Property name="errorFileName">${projectName}-error.log</Property>
</Properties>
<Appenders>
<!-- 类型名为Console,名称为必须属性 -->
<Console name="STDOUT">
<PatternLayout charset="UTF-8" pattern="${PATTERN}" />
</Console>
<RollingFile name="DailyRollingFile" fileName="${filePatch}${fileName}"
filePattern="${filePatch}${fileName}.%d{yyyy-MM-dd}.%i">
<PatternLayout charset="UTF-8" pattern="${PATTERN}" />
<Filters>
<!--如果是error级别拒绝 -->
<ThresholdFilter level="error" onMatch="DENY"
onMismatch="NEUTRAL" />
<!--如果是debug\info\warn输出 -->
<ThresholdFilter level="debug" onMatch="ACCEPT"
onMismatch="DENY" />
</Filters>
<Policies>
<!-- 一般与 filePattern联用 以日志的命名精度来确定单位 这里用yyyy-MM-dd来记录 所以1 表示是以天为周期存储文件 -->
<TimeBasedTriggeringPolicy interval="1"
modulate="true" />
<!-- 日志文件大小 <SizeBasedTriggeringPolicy size="1 MB" /> -->
</Policies>
<!-- 最多保留文件数 -->
<DefaultRolloverStrategy max="7" />
</RollingFile>
<RollingFile name="ErrorDailyRollingFile" fileName="${filePatch}${errorFileName}"
filePattern="${filePatch}${errorFileName}.%d{yyyy-MM-dd}.%i">
<PatternLayout charset="UTF-8" pattern="${PATTERN}" />
<Filters>
<ThresholdFilter level="error" onMatch="ACCEPT"
onMismatch="DENY" />
</Filters>
<Policies>
<!-- 一般与 filePattern联用 以日志的命名精度来确定单位 这里用yyyy-MM-dd来记录 所以1 表示是以天为周期存储文件 -->
<TimeBasedTriggeringPolicy interval="1"
modulate="true" />
<!-- 日志文件大小 <SizeBasedTriggeringPolicy size="1 MB" /> -->
</Policies>
<!-- 最多保留文件数 -->
<DefaultRolloverStrategy max="7" />
</RollingFile>
<!-- Socket Apppender配置,通过TCP协议连接Logstash <Socket name="LOGSTASH" host="127.0.0.1"
port="9001" protocol="TCP"> <PatternLayout pattern="${PATTERN}" /> </Socket> -->
</Appenders>
<Loggers>
<!-- root loggerConfig设置 -->
<AsyncRoot level="info" additivity="false">
<AppenderRef ref="STDOUT" />
<AppenderRef ref="DailyRollingFile" />
<AppenderRef ref="ErrorDailyRollingFile" />
</AsyncRoot>
</Loggers>
</Configuration>
日志输出效果如下:
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log
project.name
service.log
service.log.2018-8-10
service-error.log
service-error.log.2018-8-10