Thank you for the prompt feedbacks @Aljoscha. Yes you are absolutely correct - adding Hadoop dependency to cluster runtime component is definitely not what we are proposing. We were trying to see how the community thinks about the idea of adding log support into History server. - The reference to this JIRA ticket is more on the intention rather than the solution. - in fact the intention is slightly different, we were trying to put it in the history server while the original JIRA proposed to add it in the live runtime modules. - IMO, in order to support different cluster environments: the generic cluster component should only provide an interface, where each cluster impl module should extend from.
@Xiaogang, thank you for bringing up the idea of utilizing a trace system. The event tracing would definitely provide additional, in fact more valuable information for debugging purposes. In fact we were also internally experimenting with the idea similar to Spark's ListenerInterface [1] to capture some of the important messages sent via akka. But we are still in a very early preliminary stage, thus we haven't included them in this discussion. We would love to hear more regarding the trace system you proposed. could you share more information regarding this? Such as how would the live events being listened; how would the trace being collected/stored; etc. [1] https://spark.apache.org/docs/2.0.2/api/java/org/apache/spark/scheduler/SparkListener.html Thanks, Rong On Thu, Feb 13, 2020 at 7:33 AM Aljoscha Krettek <aljos...@apache.org> wrote: > Hi, > > what's the difference in approach to the mentioned related Jira Issue > ([1])? I commented there because I'm skeptical about adding > Hadoop-specific code to the generic cluster components. > > Best, > Aljoscha > > [1] https://issues.apache.org/jira/browse/FLINK-14317 > > On 13.02.20 03:47, SHI Xiaogang wrote: > > Hi Rong Rong, > > > > Thanks for the proposal. We are also suffering from some pains brought by > > history server. To address them, we propose a trace system, which is very > > similar to the metric system, for historical information. > > > > A trace is semi-structured information about events in Flink. Useful > traces > > include: > > * job traces: which contain the job graph of submitted jobs. > > * schedule traces: A schedule trace is typically composed of the > > information of task slots. They are generated when a job finishes, fails, > > or is canceled. As a job may restart mutliple times, a job typically has > > multiple schedule traces. > > * checkpoint traces: which are generated when a checkpoint completes or > > fails. > > * task manager traces: which are generated when a task manager > terminates. > > Users can access the link to aggregated logs intaskmanager traces. > > > > Users can use TraceReport to collect traces in Flink and export them to > > external storage (e.g., ElasticSearch). By retrieving traces when > > exceptions happen, we can improve user experience in altering. > > > > Regards, > > Xiaogang > > > > Rong Rong <walter...@gmail.com> 于2020年2月13日周四 上午9:41写道： > > > >> Hi All, > >> > >> Recently we have been experimenting using Flink’s history server as a > >> centralized debugging service for completed streaming jobs. > >> > >> Specifically, we dynamically generate links to access log files on the > YARN > >> host; in the meantime, we use the Flink history server to show job > graphs, > >> exceptions and other info of the completed jobs[2]. > >> > >> This causes some pain for our users, namely: It is inconvenient to go to > >> YARN host to access logs; then go to Flink history server for the other > >> information. > >> > >> Thus we would like to propose an improvement to the currently Flink > history > >> server: > >> > >> - > >> > >> To support dynamic links to residual log files from the host machine > >> within the retention period [3]; > >> - > >> > >> To support dynamic links to aggregated log files provided by the > >> cluster, if supported: such as Hadoop HistoryServer[1], or > Kubernetes > >> cluster level logging[4]? > >> - > >> > >> Similar integration with Hadoop HistoryServer was already > proposed > >> before[5] with slightly different approach. > >> > >> > >> Any feedback and suggestions are highly appreciated! > >> > >> -- > >> > >> Rong > >> > >> [1] > >> > >> > https://hadoop.apache.org/docs/r2.9.2/hadoop-mapreduce-client/hadoop-mapreduce-client-hs/HistoryServerRest.html > >> > >> [2] > >> > >> > https://ci.apache.org/projects/flink/flink-docs-release-1.9/monitoring/historyserver.html > >> > >> [3] > >> > >> > https://hadoop.apache.org/docs/r2.9.2/hadoop-yarn/hadoop-yarn-common/yarn-default.xml#yarn.nodemanager.log.retain-seconds > >> > >> [4] > >> > >> > https://kubernetes.io/docs/concepts/cluster-administration/logging/#cluster-level-logging-architectures > >> [5] https://issues.apache.org/jira/browse/FLINK-14317 > >> > > >
