Spark学习-事件日志EventLog

事件日志EventLog

  • 背景
  • 系统结构
  • Spark Event
    • 介绍
    • 事件类型
    • 事件内容
    • 事件日志
    • 事件分析

背景

    最近工作需要使用Flink对Spark的应用事件日志进行处理,帮助发现Spark应用中常见异常问题,为用户提供方便快捷的常见问题排查,在此作一下简单的记录和学习。

系统结构

Spark学习-事件日志EventLog_第1张图片

    Spark开启Thrift Server进行Spark SQL查询,Spark的Jobhistory服务对应用的事件进行记录和保存,利用FileBeat对历史事件日志传送到Kafka Topic中,最后使用Flink对Topic中的事件日志进行处理,并输出到ElasticSearch作结果展示。

Spark Event

介绍

    Spark Event是Spark为Spark App定义的运行事件,用于展示一个Spark App完整的生命周期,Spark History Server服务可将App的事件日志存储到Hdfs中(即Event Log,JSON文件格式),一般来说一个Spark Job对应一个事件日志,通过分析这些事件日志,我们可以发现一些应用中的错误和待提升的点,从而进一步去优化应用性能。

事件类型

    Spark事件类型可分为如下类型,具体可参考Spark源码SparkListener.class。
Spark学习-事件日志EventLog_第2张图片
    Spark的运行过程正是由上图中的多种不同事件组合而成,事件归纳一下主要分为Spark App运行事件、资源变更事件、环境变更事件和其他事件,图中相同颜色代表属于同一过程的不同状态的事件。

事件内容

事件名称 事件描述 事件内容
SparkListenerApplicationStart App开始事件 App Name:App名称
App ID:App的主键
Timestamp: 事件触发时间
User:提交App的用户
SparkListenerApplicationEnd App结束事件 Timestamp:事件触发时间
SparkListenerJobStart Job开始事件 Job ID:Job的主键
Submission Time:Job提交时间
Stage Infos: Job中所有stage的详细信息
Stage IDs:Job中所有stage的ID列表
Properties:Job的配置信息
SparkListenerJobEnd Job结束事件 Job ID:Job的主键
Completion Time:Job完成时间
Job Result: Job的执行结果信息
SparkListenerStageSubmitted Stage提交事件 Stage Info:当前提交Stage的详细信息
Properties:Stage的配置信息
SparkListenerStageCompleted Stage完成事件 Stage Info:当前完成Stage的详细信息
SparkListenerTaskStart Task启动事件 Stage ID:任务所在Stage的主键
Stage Attempt ID:上次尝试提交Stage的主键
Task Info:Task任务的详细信息
SparkListenerTaskGettingResult Task下载任务结果事件 Task Info:Task执行的详细信息
SparkListenerTaskEnd Task任务结束事件 Stage ID:任务所在Stage的主键
Stage Attempt ID:上次尝试提交Stage的主键
Task Type:Task的类型
Task End Reason:Task结束的原因
Task Info:Task任务的详细信息
Task Executor Metrics:执行Task的Executor的JVM指标信息
Task Metrics:Task运行的指标信息
SparkListenerEnvironmentUpdate 环境更新事件 JVM Information:Java和Scala的版本信息
Spark Properties:App的Spark参数配置信息
Hadoop Properties:App的Yarn参数配置信息
System Properties:提交App的系统环境配置信息
Classpath Entries:环境变量信息
SparkListenerBlockManagerAdded 块管理器添加事件 Block Manager ID:块管理器的主键信息
Maximum Memory:最大内存值
Timestamp:事件触发时间
Maximum Onheap Memory:最大堆内内存值
Maximum Offheap Memory:最大堆外内存值
SparkListenerBlockManagerRemoved 块管理器移除事件 Block Manager ID:块管理器的主键信息
Timestamp:事件触发时间
SparkListenerExecutorMetricsUpdate Task指标更新事件 Executor ID:Executor的主键
Metrics Updated:Task更新的指标值
SparkListenerExecutorAdded Executor注册事件 Executor ID:Executor的主键
Executor Info:Executor的详细信息
Timestamp:事件触发时间
SparkListenerExecutorRemoved Executor移除事件 Executor ID:Executor的主键
Timestamp:事件触发时间
Removed Reason:Executor移除原因
SparkListenerBlockUpdated block更新事件 Block Updated Info:Block更新的详细信息
SparkListenerUnpersistRDD 取消 RDD缓存事件 RDD ID:RDD的主键
SparkListenerExecutorBlacklisted Executor黑名单事件 time:事件触发时间
executorId:Executor的主键
taskFailures:task失败次数
SparkListenerExecutorBlacklistedForStage 针对Stage的Executor黑名单事件 time:事件触发时间
executorId:Executor的主键
taskFailures:task失败次数
stageId:Stage的主键
stageAttemptId:上次尝试提交Stage的主键
SparkListenerNodeBlacklisted Node黑名单事件 time:事件触发时间
hostId:节点的主键
executorFailures:executor的失败次数
SparkListenerNodeBlacklistedForStage 针对Stage的Node黑名单事件 time:事件触发时间
executorId:Executor的主键
executorFailures:executor的失败次数
stageId:Stage的主键
stageAttemptId:上次尝试提交Stage的主键
SparkListenerExecutorUnblacklisted Executor黑名单移除事件 time:事件触发时间
executorId:Executor的主键
SparkListenerNodeUnblacklisted Node黑名单移除事件 time:事件触发时间
hostId:节点的主键

    表格事件内容列中,红色字段是会在事件日志中输出的JSON字段,蓝色字段是不会在事件日志中输出的后台字段。

事件日志

Spark Pi运行的事件日志如下所示:

{"Event":"SparkListenerLogStart","Spark Version":"3.0.1"}
{"Event":"SparkListenerBlockManagerAdded","Block Manager ID":{"Executor ID":"driver","Host":"master","Port":43711},"Maximum Memory":97832140,"Timestamp":1603121632911,"Maximum Onheap Memory":97832140,"Maximum Offheap Memory":0}
{"Event":"SparkListenerEnvironmentUpdate","JVM Information":{"Java Home":"/home/java/jre","Java Version":"1.8.0_162 (Oracle Corporation)","Scala Version":"version 2.12.10"},"Spark Properties":{"spark.serializer":"org.apache.spark.serializer.KryoSerializer","spark.driver.host":"master","spark.eventLog.enabled":"true","spark.driver.port":"46515","spark.jars":"file:/home/spark-3.0.1/examples/jars/spark-examples_2.12-3.0.1.jar","spark.app.name":"Spark Pi","spark.scheduler.mode":"FIFO","spark.driver.memory":"512m","spark.submit.pyFiles":"","spark.executor.id":"driver","spark.submit.deployMode":"client","spark.master":"spark://master:7077","spark.executor.memory":"512m","spark.eventLog.dir":"hdfs://master:9000/spark_event","spark.executor.cores":"1","spark.app.id":"app-20201019233352-0002"},"Hadoop 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","fs.s3a.s3guard.ddb.background.sleep":"25ms","fs.s3a.retry.limit":"${fs.s3a.attempts.maximum}","mapreduce.jobhistory.loadedjobs.cache.size":"5","fs.s3a.s3guard.ddb.table.create":"false","yarn.nodemanager.amrmproxy.enabled":"false","yarn.timeline-service.entity-group-fs-store.with-user-dir":"false","mapreduce.input.fileinputformat.split.minsize":"0","yarn.resourcemanager.container.liveness-monitor.interval-ms":"600000","yarn.resourcemanager.client.thread-count":"50","io.seqfile.compress.blocksize":"1000000","yarn.sharedcache.checksum.algo.impl":"org.apache.hadoop.yarn.sharedcache.ChecksumSHA256Impl","yarn.nodemanager.amrmproxy.interceptor-class.pipeline":"org.apache.hadoop.yarn.server.nodemanager.amrmproxy.DefaultRequestInterceptor","dfs.datanode.data.dir":"/data/hadoop/hdfs/data","dfs.replication":"3","yarn.timeline-service.entity-group-fs-store.leveldb-cache-read-cache-size":"10485760","mapreduce.reduce.shuffle.fetch.retry.interval-ms":"1000","mapreduce.task.profile.maps":"0-2","yarn.scheduler.include-port-in-node-name":"false","yarn.nodemanager.admin-env":"MALLOC_ARENA_MAX=$MALLOC_ARENA_MAX","yarn.resourcemanager.node-removal-untracked.timeout-ms":"60000","mapreduce.am.max-attempts":"2","hadoop.security.kms.client.failover.sleep.base.millis":"100","mapreduce.jobhistory.webapp.https.address":"0.0.0.0:19890","yarn.node-labels.fs-store.impl.class":"org.apache.hadoop.yarn.nodelabels.FileSystemNodeLabelsStore","yarn.nodemanager.collector-service.address":"${yarn.nodemanager.hostname}:8048","fs.trash.checkpoint.interval":"0","mapreduce.job.map.output.collector.class":"org.apache.hadoop.mapred.MapTask$MapOutputBuffer","yarn.resourcemanager.node-ip-cache.expiry-interval-secs":"-1","hadoop.http.authentication.signature.secret.file":"*********(redacted)","hadoop.jetty.logs.serve.aliases":"true","yarn.resourcemanager.placement-constraints.handler":"disabled","yarn.timeline-service.handler-thread-count":"10","yarn.resourcemanager.max-completed-applications":"1000","yarn.resourcemanager.system-metrics-publisher.enabled":"false","yarn.resourcemanager.placement-constraints.algorithm.class":"org.apache.hadoop.yarn.server.resourcemanager.scheduler.constraint.algorithm.DefaultPlacementAlgorithm","yarn.sharedcache.webapp.address":"0.0.0.0:8788","yarn.resourcemanager.delegation.token.renew-interval":"*********(redacted)","yarn.sharedcache.nm.uploader.replication.factor":"10","hadoop.security.groups.negative-cache.secs":"30","yarn.app.mapreduce.task.container.log.backups":"0","mapreduce.reduce.skip.proc-count.auto-incr":"true","hadoop.security.group.mapping.ldap.posix.attr.gid.name":"gidNumber","rpc.engine.org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolPB":"org.apache.hadoop.ipc.ProtobufRpcEngine","ipc.client.fallback-to-simple-auth-allowed":"false","yarn.nodemanager.resource.memory.enforced":"true","hadoop.proxyuser.root.groups":"*","yarn.client.failover-proxy-provider":"org.apache.hadoop.yarn.client.ConfiguredRMFailoverProxyProvider","yarn.timeline-service.http-authentication.simple.anonymous.allowed":"true","ha.health-monitor.check-interval.ms":"1000","yarn.acl.reservation-enable":"false","yarn.resourcemanager.store.class":"org.apache.hadoop.yarn.server.resourcemanager.recovery.FileSystemRMStateStore","yarn.app.mapreduce.am.hard-kill-timeout-ms":"10000","fs.s3a.etag.checksum.enabled":"false","yarn.nodemanager.container-metrics.enable":"true","yarn.timeline-service.client.fd-clean-interval-secs":"60","yarn.resourcemanager.nodemanagers.heartbeat-interval-ms":"1000","hadoop.common.configuration.version":"3.0.0","fs.s3a.s3guard.ddb.table.capacity.read":"500","yarn.nodemanager.remote-app-log-dir-suffix":"logs","yarn.nodemanager.windows-container.cpu-limit.enabled":"false","yarn.nodemanager.runtime.linux.docker.privileged-containers.allowed":"false","file.blocksize":"67108864","hadoop.registry.zk.retry.ceiling.ms":"60000","yarn.scheduler.configuration.leveldb-store.path":"${hadoop.tmp.dir}/yarn/system/confstore","yarn.sharedcache.store.in-memory.initial-delay-mins":"10","mapreduce.jobhistory.principal":"jhs/[email protected]","mapreduce.map.skip.proc-count.auto-incr":"true","fs.s3a.committer.name":"file","mapreduce.task.profile.reduces":"0-2","hadoop.zk.num-retries":"1000","yarn.webapp.xfs-filter.enabled":"true","seq.io.sort.mb":"100","yarn.scheduler.configuration.max.version":"100","yarn.timeline-service.webapp.https.address":"${yarn.timeline-service.hostname}:8190","yarn.resourcemanager.scheduler.address":"${yarn.resourcemanager.hostname}:8030","yarn.node-labels.enabled":"false","yarn.resourcemanager.webapp.ui-actions.enabled":"true","mapreduce.task.timeout":"600000","yarn.sharedcache.client-server.thread-count":"50","hadoop.security.groups.shell.command.timeout":"0s","hadoop.security.crypto.cipher.suite":"AES/CTR/NoPadding","yarn.nodemanager.elastic-memory-control.oom-handler":"org.apache.hadoop.yarn.server.nodemanager.containermanager.linux.resources.DefaultOOMHandler","yarn.resourcemanager.connect.max-wait.ms":"9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","yarn.nodemanager.windows-container.memory-limit.enabled":"false","yarn.timeline-service.webapp.address":"${yarn.timeline-service.hostname}:8188","yarn.app.mapreduce.am.job.committer.commit-window":"10000","yarn.nodemanager.container-manager.thread-count":"20","yarn.minicluster.fixed.ports":"false","hadoop.tags.system":"YARN,HDFS,NAMENODE,DATANODE,REQUIRED,SECURITY,KERBEROS,PERFORMANCE,CLIENT\n      ,SERVER,DEBUG,DEPRECATED,COMMON,OPTIONAL","yarn.cluster.max-application-priority":"0","yarn.timeline-service.ttl-enable":"true","mapreduce.jobhistory.recovery.store.fs.uri":"${hadoop.tmp.dir}/mapred/history/recoverystore","hadoop.caller.context.signature.max.size":"40","yarn.client.load.resource-types.from-server":"false","ha.zookeeper.session-timeout.ms":"10000","tfile.io.chunk.size":"1048576","fs.s3a.s3guard.ddb.table.capacity.write":"100","mapreduce.job.speculative.slowtaskthreshold":"1.0","io.serializations":"org.apache.hadoop.io.serializer.WritableSerialization, 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{"Event":"SparkListenerApplicationStart","App Name":"Spark Pi","App ID":"app-20201019233352-0002","Timestamp":1603121631550,"User":"root"}
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{"Event":"SparkListenerStageSubmitted","Stage Info":{"Stage ID":0,"Stage Attempt ID":0,"Stage Name":"reduce at SparkPi.scala:38","Number of Tasks":2,"RDD Info":[{"RDD ID":1,"Name":"MapPartitionsRDD","Scope":"{\"id\":\"1\",\"name\":\"map\"}","Callsite":"map at SparkPi.scala:34","Parent IDs":[0],"Storage Level":{"Use Disk":false,"Use Memory":false,"Deserialized":false,"Replication":1},"Barrier":false,"Number of Partitions":2,"Number of Cached Partitions":0,"Memory Size":0,"Disk Size":0},{"RDD ID":0,"Name":"ParallelCollectionRDD","Scope":"{\"id\":\"0\",\"name\":\"parallelize\"}","Callsite":"parallelize at SparkPi.scala:34","Parent IDs":[],"Storage Level":{"Use Disk":false,"Use Memory":false,"Deserialized":false,"Replication":1},"Barrier":false,"Number of Partitions":2,"Number of Cached Partitions":0,"Memory Size":0,"Disk Size":0}],"Parent IDs":[],"Details":"org.apache.spark.rdd.RDD.reduce(RDD.scala:1076)\norg.apache.spark.examples.SparkPi$.main(SparkPi.scala:38)\norg.apache.spark.examples.SparkPi.main(SparkPi.scala)\nsun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)\nsun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)\nsun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)\njava.lang.reflect.Method.invoke(Method.java:498)\norg.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)\norg.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:928)\norg.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:180)\norg.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:203)\norg.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:90)\norg.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:1007)\norg.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:1016)\norg.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)","Submission Time":1603121636405,"Accumulables":[]},"Properties":{"spark.rdd.scope":"{\"id\":\"2\",\"name\":\"reduce\"}","spark.rdd.scope.noOverride":"true"}}
{"Event":"SparkListenerExecutorAdded","Timestamp":1603121637799,"Executor ID":"0","Executor Info":{"Host":"192.168.153.135","Total Cores":1,"Log Urls":{"stdout":"http://192.168.153.135:8081/logPage/?appId=app-20201019233352-0002&executorId=0&logType=stdout","stderr":"http://192.168.153.135:8081/logPage/?appId=app-20201019233352-0002&executorId=0&logType=stderr"},"Attributes":{},"Resources":{}}}
{"Event":"SparkListenerBlockManagerAdded","Block Manager ID":{"Executor ID":"0","Host":"192.168.153.135","Port":34409},"Maximum Memory":97832140,"Timestamp":1603121637949,"Maximum Onheap Memory":97832140,"Maximum Offheap Memory":0}
{"Event":"SparkListenerTaskStart","Stage ID":0,"Stage Attempt ID":0,"Task Info":{"Task ID":0,"Index":0,"Attempt":0,"Launch Time":1603121638008,"Executor ID":"0","Host":"192.168.153.135","Locality":"PROCESS_LOCAL","Speculative":false,"Getting Result Time":0,"Finish Time":0,"Failed":false,"Killed":false,"Accumulables":[]}}
{"Event":"SparkListenerExecutorAdded","Timestamp":1603121638131,"Executor ID":"2","Executor Info":{"Host":"192.168.153.137","Total Cores":1,"Log Urls":{"stdout":"http://192.168.153.137:8081/logPage/?appId=app-20201019233352-0002&executorId=2&logType=stdout","stderr":"http://192.168.153.137:8081/logPage/?appId=app-20201019233352-0002&executorId=2&logType=stderr"},"Attributes":{},"Resources":{}}}
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{"Event":"SparkListenerBlockManagerAdded","Block Manager ID":{"Executor ID":"2","Host":"192.168.153.137","Port":39783},"Maximum Memory":122644070,"Timestamp":1603121638354,"Maximum Onheap Memory":122644070,"Maximum Offheap Memory":0}
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{"Event":"SparkListenerTaskEnd","Stage ID":0,"Stage Attempt ID":0,"Task Type":"ResultTask","Task End Reason":{"Reason":"Success"},"Task Info":{"Task ID":1,"Index":1,"Attempt":0,"Launch Time":1603121638428,"Executor ID":"2","Host":"192.168.153.137","Locality":"PROCESS_LOCAL","Speculative":false,"Getting Result Time":0,"Finish Time":1603121640774,"Failed":false,"Killed":false,"Accumulables":[{"ID":5,"Name":"internal.metrics.jvmGCTime","Update":69,"Value":128,"Internal":true,"Count Failed Values":true},{"ID":4,"Name":"internal.metrics.resultSize","Update":842,"Value":1684,"Internal":true,"Count Failed Values":true},{"ID":3,"Name":"internal.metrics.executorCpuTime","Update":70763236,"Value":137334234,"Internal":true,"Count Failed Values":true},{"ID":2,"Name":"internal.metrics.executorRunTime","Update":160,"Value":230,"Internal":true,"Count Failed Values":true},{"ID":1,"Name":"internal.metrics.executorDeserializeCpuTime","Update":1007597102,"Value":2112153366,"Internal":true,"Count Failed Values":true},{"ID":0,"Name":"internal.metrics.executorDeserializeTime","Update":2121,"Value":3482,"Internal":true,"Count Failed Values":true}]},"Task Executor Metrics":{"JVMHeapMemory":0,"JVMOffHeapMemory":0,"OnHeapExecutionMemory":0,"OffHeapExecutionMemory":0,"OnHeapStorageMemory":0,"OffHeapStorageMemory":0,"OnHeapUnifiedMemory":0,"OffHeapUnifiedMemory":0,"DirectPoolMemory":0,"MappedPoolMemory":0,"ProcessTreeJVMVMemory":0,"ProcessTreeJVMRSSMemory":0,"ProcessTreePythonVMemory":0,"ProcessTreePythonRSSMemory":0,"ProcessTreeOtherVMemory":0,"ProcessTreeOtherRSSMemory":0,"MinorGCCount":0,"MinorGCTime":0,"MajorGCCount":0,"MajorGCTime":0},"Task Metrics":{"Executor Deserialize Time":2121,"Executor Deserialize CPU Time":1007597102,"Executor Run Time":160,"Executor CPU Time":70763236,"Peak Execution Memory":0,"Result Size":842,"JVM GC Time":69,"Result Serialization Time":0,"Memory Bytes Spilled":0,"Disk Bytes Spilled":0,"Shuffle Read Metrics":{"Remote Blocks Fetched":0,"Local Blocks Fetched":0,"Fetch Wait Time":0,"Remote Bytes Read":0,"Remote Bytes Read To Disk":0,"Local Bytes Read":0,"Total Records Read":0},"Shuffle Write Metrics":{"Shuffle Bytes Written":0,"Shuffle Write Time":0,"Shuffle Records Written":0},"Input Metrics":{"Bytes Read":0,"Records Read":0},"Output Metrics":{"Bytes Written":0,"Records Written":0},"Updated Blocks":[]}}
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{"Event":"SparkListenerJobEnd","Job ID":0,"Completion Time":1603121640792,"Job Result":{"Result":"JobSucceeded"}}
{"Event":"SparkListenerApplicationEnd","Timestamp":1603121640817}

    一个日志文件代表了一个Spark App,日志中每行为JSON格式的Spark App事件内容,文件由上而下顺序的输出了整个Spark App执行的事件过程。

事件分析

    利用事件日志提供的多个指标,我们可以发现一些Spark App中存在的程序错误和性能故障,大概有如下分析方法:

  1. 获取Task执行结果,对失败的Task进行异常总结,针对异常形成统一解决方案。
  2. 比较Task的平均执行时间和最大执行时间,以确定是否有某个Task拖慢整体任务进度。
  3. 观察Task的平均数据量大小和最大数据量大小,以确定是否存在数据倾斜。
  4. 分析Task的JVM GC时间,观察是否有GC时间过慢的情况,主要观察GC占用CPU时间的百分比,如果占用过多则需要对GC进行优化。

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