详解log4j2(下) - Async/MongoDB/Flume Appender 按日志级别区分文件输出

1. 按日志级别区分文件输出

有些人习惯按日志信息级别输出到不同名称的文件中，如info.log，error.log，warn.log等，在log4j2中可通过配置Filters来实现。

假定需求是把INFO及以下级别的信息输出到info.log，WARN和ERROR级别的信息输出到error.log，FATAL级别输出到fatal.log，配置文件如下：

<Configuration status="WARN" monitorInterval="300">
<properties>
<property name="LOG_HOME">D:/logs</property>
</properties>
<Appenders>
<Console name="Console" target="SYSTEM_OUT">
<PatternLayout pattern="%d{HH:mm:ss.SSS} [%t] %-5level %logger{36} - %msg%n" />
</Console>

<RollingRandomAccessFile name="InfoFile"
fileName="${LOG_HOME}/info.log"
filePattern="${LOG_HOME}/$${date:yyyy-MM}/info-%d{yyyy-MM-dd}-%i.log">
<Filters>
<ThresholdFilter level="warn" onMatch="DENY" onMismatch="NEUTRAL" />
<ThresholdFilter level="trace" onMatch="ACCEPT" onMismatch="DENY" />
</Filters>
<PatternLayout pattern="%date{yyyy-MM-dd HH:mm:ss.SSS} %level [%thread][%file:%line] - %msg%n" />
<Policies>
<TimeBasedTriggeringPolicy />
<SizeBasedTriggeringPolicy size="10 MB" />
</Policies>
<DefaultRolloverStrategy max="20" />
</RollingRandomAccessFile>

<RollingRandomAccessFile name="ErrorFile"
fileName="${LOG_HOME}/error.log"
filePattern="${LOG_HOME}/$${date:yyyy-MM}/error-%d{yyyy-MM-dd}-%i.log">
<Filters>
<ThresholdFilter level="fatal" onMatch="DENY" onMismatch="NEUTRAL" />
<ThresholdFilter level="warn" onMatch="ACCEPT" onMismatch="DENY" />
</Filters>
<PatternLayout pattern="%date{yyyy-MM-dd HH:mm:ss.SSS} %level [%thread][%file:%line] - %msg%n" />
<Policies>
<TimeBasedTriggeringPolicy />
<SizeBasedTriggeringPolicy size="10 MB" />
</Policies>
<DefaultRolloverStrategy max="20" />
</RollingRandomAccessFile>

<RollingRandomAccessFile name="FatalFile"
fileName="${LOG_HOME}/fatal.log"
filePattern="${LOG_HOME}/$${date:yyyy-MM}/fatal-%d{yyyy-MM-dd}-%i.log">
<Filters>
<ThresholdFilter level="fatal" onMatch="ACCEPT" onMismatch="DENY" />
</Filters>
<PatternLayout pattern="%date{yyyy-MM-dd HH:mm:ss.SSS} %level [%thread][%file:%line] - %msg%n" />
<Policies>
<TimeBasedTriggeringPolicy />
<SizeBasedTriggeringPolicy size="10 MB" />
</Policies>
<DefaultRolloverStrategy max="20" />
</RollingRandomAccessFile>
</Appenders>

<Loggers>
<Root level="trace">
<AppenderRef ref="Console" />
<AppenderRef ref="InfoFile" />
<AppenderRef ref="ErrorFile" />
<AppenderRef ref="FatalFile" />
</Root>
</Loggers>
</Configuration>

测试代码：

public static void main(String[] args) {
Logger logger = LogManager.getLogger(Client.class);
logger.trace("trace level");
logger.debug("debug level");
logger.info("info level");
logger.warn("warn level");
logger.error("error level");
logger.fatal("fatal level");
}

2 异步写日志

配置文件：

<Configuration status="WARN" monitorInterval="300">
<properties>
<property name="LOG_HOME">D:/logs</property>
<property name="FILE_NAME">mylog</property>
</properties>

<Appenders>
<Console name="Console" target="SYSTEM_OUT">
<PatternLayout pattern="%d{HH:mm:ss.SSS} [%t] %-5level %logger{36} - %msg%n" />
</Console>
<RollingRandomAccessFile name="MyFile"
fileName="${LOG_HOME}/${FILE_NAME}.log"
filePattern="${LOG_HOME}/$${date:yyyy-MM}/${FILE_NAME}-%d{yyyy-MM-dd HH-mm}-%i.log">
<PatternLayout
pattern="%date{yyyy-MM-dd HH:mm:ss.SSS} %level [%thread][%file:%line] - %msg%n" />
<Policies>
<TimeBasedTriggeringPolicy interval="1" />
<SizeBasedTriggeringPolicy size="10 MB" />
</Policies>
<DefaultRolloverStrategy max="20" />
</RollingRandomAccessFile>
<Async name="Async">
<AppenderRef ref="MyFile" />
</Async>
</Appenders>

<Loggers>
<Logger name="asynclog" level="trace" additivity="false" >
<AppenderRef ref="Async" />
</Logger>
<Root level="error">
<AppenderRef ref="Console" />
</Root>
</Loggers>
</Configuration>

测试代码：

public static void main(String[] args) {
Logger logger = LogManager.getLogger("asynclog");
logger.trace("trace level");
logger.debug("debug level");
logger.info("info level");
logger.warn("warn level");
logger.error("error level");
logger.fatal("fatal level");
}

3 输出到MongoDB

添加依赖：

<dependency>
<groupId>org.apache.logging.log4j</groupId>
<artifactId>log4j-nosql</artifactId>
<version>2.5</version>
</dependency>
<dependency>
<groupId>org.mongodb</groupId>
<artifactId>mongo-java-driver</artifactId>
<version>3.2.2</version>
</dependency>

配置文件：

<Configuration status="WARN" monitorInterval="300">
<Appenders>
<Console name="Console" target="SYSTEM_OUT">
<PatternLayout pattern="%d{HH:mm:ss.SSS} [%t] %-5level %logger{36} - %msg%n" />
</Console>

<NoSql name="databaseAppender">
<MongoDb databaseName="test" collectionName="errorlog"
server="localhost" port="27017" />
</NoSql>
</Appenders>

<Loggers>
<Logger name="mongolog" level="trace" additivity="false">
<AppenderRef ref="databaseAppender" />
</Logger>
<Root level="error">
<AppenderRef ref="Console" />
</Root>
</Loggers>
</Configuration>

4 输出到Flume

Flume配置(flume-conf.properties)

agent1.sources=source1
agent1.sinks=sink1
agent1.channels=channel1

agent1.sources.source1.type=avro
agent1.sources.source1.channels=channel1
agent1.sources.source1.bind=0.0.0.0
agent1.sources.source1.port=41414

agent1.sinks.sink1.type=file_roll
agent1.sinks.sink1.sink.directory=D:/log
agent1.sinks.sink1.channel=channel1
agent1.sinks.sink1.sink.rollInterval=86400
agent1.sinks.sink1.sink.batchSize=100
agent1.sinks.sink1.sink.serializer=text
agent1.sinks.sink1.sink.serializer.appendNewline = false

agent1.channels.channel1.type=file
agent1.channels.channel1.checkpointDir=D:/log/checkpoint
agent1.channels.channel1.dataDirs=D:/log/data

启动Flume（注：测试环境为windows）

flume-ng.cmd agent --conf ../conf/ --conf-file ../conf/flume-conf.properties -name agent1

添加依赖：

<dependency>
<groupId>org.apache.logging.log4j</groupId>
<artifactId>log4j-flume-ng</artifactId>
<version>2.5</version>
</dependency>

配置文件：

<Configuration status="WARN" monitorInterval="300">
<Appenders>
<Flume name="eventLogger" compress="false">
<Agent host="127.0.0.1" port="41414" />
<RFC5424Layout enterpriseNumber="18060" includeMDC="true" appName="MyApp" />
</Flume>
</Appenders>
<Loggers>
<Root level="trace">
<AppenderRef ref="eventLogger" />
</Root>
</Loggers>
</Configuration>