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组件版本Flink1.16.1kafka2.0.0Logstash6.5.4Elasticseach6.3.1Kibana6.3.1 针对按照⽇志⽂件⼤⼩滚动⽣成⽂件的⽅式#xff0c;可能因为某个错误的问题#xff0c;需要看好多个⽇志⽂件#xff0c;还有Flink on Yarn模式提交Flink任务#xff0c;在任务执…一、各组件版本
组件版本Flink1.16.1kafka2.0.0Logstash6.5.4Elasticseach6.3.1Kibana6.3.1 针对按照⽇志⽂件⼤⼩滚动⽣成⽂件的⽅式可能因为某个错误的问题需要看好多个⽇志⽂件还有Flink on Yarn模式提交Flink任务在任务执行完毕或者任务报错后container会被回收从而导致日志丢失为了方便排查问题可以把⽇志⽂件通过KafkaAppender写⼊到kafka中然后通过ELK等进⾏⽇志搜索甚⾄是分析告警。
二、Flink配置将日志写入Kafka
2.1 flink-conf.yaml增加下面两行配置信息
env.java.opts.taskmanager: -DyarnContainerId$CONTAINER_ID env.java.opts.jobmanager: -DyarnContainerId$CONTAINER_ID
2.2 log4j.properties配置案例如下
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# Allows this configuration to be modified at runtime. The file will be checked every 30 seconds.
monitorInterval30# This affects logging for both user code and Flink
#rootLogger.appenderRef.file.ref MainAppender
rootLogger.level INFO
rootLogger.appenderRef.kafka.ref Kafka
rootLogger.appenderRef.file.ref RollingFileAppender# Uncomment this if you want to _only_ change Flinks 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
logger.shaded_zookeeper.name org.apache.flink.shaded.zookeeper3
logger.shaded_zookeeper.level INFO# Log all infos in the given file
appender.rolling.name RollingFileAppender
appender.rolling.type RollingFile
appender.rolling.append false
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 500MB
appender.rolling.strategy.type DefaultRolloverStrategy
appender.rolling.strategy.max 10#appender.main.name MainAppender
#appender.main.type RollingFile
#appender.main.append true
#appender.main.fileName ${sys:log.file}
#appender.main.filePattern ${sys:log.file}.%i
#appender.main.layout.type PatternLayout
#appender.main.layout.pattern %d{yyyy-MM-dd HH:mm:ss,SSS} %-5p %-60c %x - %m%n
#appender.main.policies.type Policies
#appender.main.policies.size.type SizeBasedTriggeringPolicy
#appender.main.policies.size.size 100MB
#appender.main.policies.startup.type OnStartupTriggeringPolicy
#appender.main.strategy.type DefaultRolloverStrategy
#appender.main.strategy.max ${env:MAX_LOG_FILE_NUMBER:-10}# kafka
appender.kafka.type Kafka
appender.kafka.name Kafka
appender.kafka.syncSend true
appender.kafka.ignoreExceptions false
appender.kafka.topic flink_logs
appender.kafka.property.type Property
appender.kafka.property.name bootstrap.servers
appender.kafka.property.value xxx1:9092,xxx2:9092,xxx3:9092
appender.kafka.layout.type JSONLayout
apender.kafka.layout.value net.logstash.log4j.JSONEventLayoutV1
appender.kafka.layout.compact true
appender.kafka.layout.complete false# Suppress the irrelevant (wrong) warnings from the Netty channel handler
#logger.netty.name org.jboss.netty.channel.DefaultChannelPipeline
logger.netty.name org.apache.flink.shaded.akka.org.jboss.netty.channel.DefaultChannelPipeline
logger.netty.level OFF#通过 flink on yarn 模式还可以添加⾃定义字段
# 日志路径
appender.kafka.layout.additionalField1.type KeyValuePair
appender.kafka.layout.additionalField1.key logdir
appender.kafka.layout.additionalField1.value ${sys:log.file}
# flink-job-name
appender.kafka.layout.additionalField2.type KeyValuePair
appender.kafka.layout.additionalField2.key flinkJobName
appender.kafka.layout.additionalField2.value ${sys:flinkJobName}
# 提交到yarn的containerId
appender.kafka.layout.additionalField3.type KeyValuePair
appender.kafka.layout.additionalField3.key yarnContainerId
appender.kafka.layout.additionalField3.value ${sys:yarnContainerId}上⾯的 appender.kafka.layout.type 可以使⽤ JSONLayout 也可以⾃定义。 ⾃定义需要将上⾯的appender.kafka.layout.type 和 appender.kafka.layout.value 修改成如下
appender.kafka.layout.type PatternLayout
appender.kafka.layout.pattern {log_level:%p,log_timestamp:%d{ISO8601},log_thread:%t,log_file:%F,l
og_line:%L,log_message:%m,log_path:%X{log_path},job_name:${sys:flink
_job_name}}%n2.3 基于Flink on yarn模式提交任务前期准备
2.3.1 需要根据kafka的版本在flink/lib⽬录下放⼊kafka-clients的jar包 2.3.2 kafka处于启动状态
2.3.3 Flink Standalone集群
# 根据kafka的版本放⼊kafka-clients
kafka-clients-3.1.0.jar
# jackson对应的jar包
jackson-annotations-2.13.3.jar
jackson-core-2.13.3.jar
jackson-databind-2.13.3.jar2.4 Flink on yarn任务提交案例
/root/software/flink-1.16.1/bin/flink run-application \
-t yarn-application \
-D yarn.application.nameTopSpeedWindowing \
-D parallelism.default3 \
-D jobmanager.memory.process.size2g \
-D taskmanager.memory.process.size2g \
-D env.java.opts-DflinkJobNameTopSpeedWindowing \
/root/software/flink-1.16.1/examples/streaming/TopSpeedWindowing.jar【注意】启动脚本需要加入这个参数日志才能采集到任务名称(-D env.java.opts-DflinkJobNamexxx) 消费flink_logs案例
{instant: {epochSecond: 1698723428,nanoOfSecond: 544000000,},thread: flink-akka.actor.default-dispatcher-17,level: INFO,loggerName: org.apache.flink.runtime.rpc.akka.AkkaRpcService,message: Stopped Akka RPC service.,endOfBatch: false,loggerFqcn: org.apache.logging.slf4j.Log4jLogger,threadId: 68,threadPriority: 5,logdir: /yarn/container-logs/application_1697779774806_0046/container_1697779774806_0046_01_000002/taskmanager.log,flinkJobName: flink-log-collect-test,yarnContainerId: container_1697779774806_0046_01_000002,
}⽇志写⼊Kafka之后可以通过Logstash接⼊elasticsearch然后通过kibana进⾏查询或搜索
三、LogStash部署 部署过程略网上都有 需要注意Logstash内部kafka-clients和Kafka版本兼容问题,需要根据Kafka版本选择合适的Logstash版本 将以下内容写⼊config/logstash-sample.conf ⽂件中
input {kafka {bootstrap_servers [xxx1:9092,xxx2:9092,xxx3:9092] group_id logstash-grouptopics [flink_logs] consumer_threads 3 type flink-logs codec jsonauto_offset_reset latest}
}output {elasticsearch {hosts [192.168.1.249:9200] index flink-log-%{YYYY-MM-dd}}
}Logstash启动
logstash-6.5.4/bin/logstash -f logstash-6.5.4/config/logstash-sample.conf 21 logstash-6.5.4/logs/logstash.log 四、Elasticsearch部署 部署过程略网上都有 注意需要用root用户以外的用户启动Elasticsearch 启动脚本
Su elasticsearchlogtestelasticsearch-6.3.1/bin/elasticsearchWindows访问ES客户端推荐使用ElasticHD本地运行后可以直连ES
五、Kibana部署 部署过程略网上都有 启动脚本: kibana-6.3.1-linux-x86_64/bin/kibana
5.1 配置规则 5.2 日志分析
