Flink Log4j 2.x使用Filter过滤日志类型

Flink Log4j 2.x使用Filter过滤日志类型(区别INFO、ERROR)

文章目录

  • Flink Log4j 2.x使用Filter过滤日志类型(区别INFO、ERROR)
    • ThresholdFilter
    • LevelMatchFilter

日志级别:
ALL < TRACE < DEBUG < INFO < WARN < ERROR < FATAL < OFF

log4j官网:

https://logging.apache.org/log4j/2.x/index.html

ThresholdFilter

在官网中,有一个Filters的组件。Filters组件允许对日志事件进行评估,以确定是否或如何发布它们。Filter将在其过滤器方法之一上被调用,并将返回一个Result,这是一个Enum,具有3个值之一- ACCEPT, DENY或NEUTRAL。

如果LogEvent中的级别与配置的级别相同或更具体,则此过滤器返回onMatch结果,否则返回onMismatch值。例如,如果ThresholdFilter配置了ERROR级别,并且LogEvent包含DEBUG级别,那么onMismatch值将被返回,因为ERROR事件比DEBUG事件更高。

ThresholdFilter过滤器的原理是,如果LogEvent的日志级别被配置的高,则会执行onMatch,否则执行onMismatch。比如如果ThresholdFilter配置了INFO级别,而LogEvent是WARN、ERROR级别,那么onMatch值将会执行。而当LogEvent是DEBUG级别时,则onMismatch值将会执行。

这里有一个Threshold的过滤器,参数包含了:

  • Level:要匹配的有效日志级别。
  • onMatch: 当过滤器匹配时要采取的操作。可以是ACCEPT, DENY或NEUTRAL。缺省值为NEUTRAL。
  • onMismatch:当过滤器不匹配时采取的操作。可以是ACCEPT, DENY或NEUTRAL。缺省值为DENY。

借助于这个Threshold过滤器,可以初步实现过滤日志的功能:

显示info 级别的日志

appender.rolling.filter.threshold.type = ThresholdFilter
appender.rolling.filter.threshold.level = ERROR
appender.rolling.filter.threshold.onMatch = DENY
appender.rolling.filter.threshold.onMismatch = ACCEPT

由于log4j.properties的rootLogger.level = INFO,因此最小的日志级别就已经是INFO了,所以上面的配置可以保证当前appender的输出日志只包含INFO信息。相当于是对ERROR及以上级别的日志执行onMatch=>DENY,而对小于ERROR级别,也就是INFO级别,执行onMismatch => ACCEPT。

或者xml的配置方式:

<RollingFile name="RollingFileInfo" fileName="${logFilePath}/${logFileName}-info.log"
                     filePattern="${logFilePath}/$${date:yyyy-MM}/${logFileName}-%d{yyyy-MM-dd}_%i.log.gz">
            <Filters>
                
                
                
                
                <ThresholdFilter level="ERROR" onMatch="DENY" onMismatch="NEUTRAL"/>
                <ThresholdFilter level="INFO" onMatch="ACCEPT" onMismatch="DENY"/>
            Filters>
            <PatternLayout pattern="%d{yyyy.MM.dd HH:mm:ss z} %-5level %class{36} %L %M - %msg%xEx%n"/>
            <Policies>
                <TimeBasedTriggeringPolicy/>
                <SizeBasedTriggeringPolicy size="30MB"/>
            Policies>
        RollingFile>

这种方式看着总感觉有点别扭,那有没有其他的Filter组件能更好地支持呢?

LevelMatchFilter

查询资料发现,有一个LevelMatchFilter的过滤器组件,其执行原理是:

如果日志级别等于${指定的日志级别},则onMatch,否则onMismatch

刚好符合我们的需求,于是此时,log4j.properties的配置文件就可以变成:

################################################################################
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#  regarding copyright ownership.  The ASF licenses this file
#  to you under the Apache License, Version 2.0 (the
#  "License"); you may not use this file except in compliance
#  with the License.  You may obtain a copy of the License at
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#  distributed under the License is distributed on an "AS IS" BASIS,
#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
#  See the License for the specific language governing permissions and
# limitations under the License.
################################################################################

# Allows this configuration to be modified at runtime. The file will be checked every 30 seconds.
monitorInterval=30

# This affects logging for both user code and Flink

# This affects logging for both user code and Flink
rootLogger.level = INFO
rootLogger.appenderRef.rolling.ref = RollingFileAppender
rootLogger.appenderRef.errorLogFile.ref = errorLogFile

# Uncomment this if you want to _only_ change Flink's logging
#logger.flink.name = org.apache.flink
#logger.flink.level = INFO

# The following lines keep the log level of common libraries/connectors on
# log level INFO. The root logger does not override this. You have to manually
# change the log levels here.
logger.akka.name = akka
logger.akka.level = INFO
logger.kafka.name= org.apache.kafka
logger.kafka.level = INFO
logger.hadoop.name = org.apache.hadoop
logger.hadoop.level = INFO
logger.zookeeper.name = org.apache.zookeeper
logger.zookeeper.level = INFO

# Log all infos in the given rolling file
appender.rolling.name = RollingFileAppender
appender.rolling.type = RollingFile
appender.rolling.append = true
appender.rolling.fileName = ${sys:log.file}
appender.rolling.filePattern = ${sys:log.file}.%i
appender.rolling.layout.type = PatternLayout
appender.rolling.layout.pattern = %d{yyyy-MM-dd HH:mm:ss,SSS} %-5p %-60c %x - %m%n
appender.rolling.policies.type = Policies
appender.rolling.policies.size.type = SizeBasedTriggeringPolicy
appender.rolling.policies.size.size=100MB
appender.rolling.policies.startup.type = OnStartupTriggeringPolicy
appender.rolling.strategy.type = DefaultRolloverStrategy
appender.rolling.strategy.max = ${env:MAX_LOG_FILE_NUMBER:-10}
appender.rolling.filter.threshold.type = LevelMatchFilter
appender.rolling.filter.threshold.level = INFO
appender.rolling.filter.threshold.onMatch = ACCEPT
appender.rolling.filter.threshold.onMisMatch = DENY

appender.errorFile.name = errorLogFile
appender.errorFile.type = RollingFile
appender.errorFile.append = true
appender.errorFile.fileName = ${sys:log.file}.err
appender.errorFile.filePattern = ${sys:log.file}.err.%i
appender.errorFile.layout.type = PatternLayout
appender.errorFile.layout.pattern = %d{yyyy-MM-dd HH:mm:ss,SSS} %-5p %-60c %x - %m%n
appender.errorFile.policies.type = Policies
appender.errorFile.policies.size.type = SizeBasedTriggeringPolicy
appender.errorFile.policies.size.size = 100MB
appender.errorFile.policies.startup.type = OnStartupTriggeringPolicy
appender.errorFile.strategy.type = DefaultRolloverStrategy
appender.errorFile.strategy.max = ${env:MAX_LOG_FILE_NUMBER:-10}
appender.errorFile.filter.threshold.type = LevelMatchFilter
appender.errorFile.filter.threshold.level = ERROR
appender.errorFile.filter.threshold.onMatch = ACCEPT
appender.errorFile.filter.threshold.onMisMatch = DENY

# Suppress the irrelevant (wrong) warnings from the Netty channel handler
logger.netty.name = org.apache.flink.shaded.akka.org.jboss.netty.channel.DefaultChannelPipeline
logger.netty.level = OFF

大家如果在部署flink任务时有类似的需求,可以参考上面的配置进行修改,实际上主要添加的只有filter.threshold配置参数即可。

分享一些讲解比较好的相关文章:

log4j2使用filter过滤日志

Log4j2 将不同线程不同级别日志输出到不同的文件中

log4j2中LevelRangeFilter的注意点

Log4j2的Filters配置

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