HeartSaVioR commented on a change in pull request #27398: [SPARK-30481][DOCS][FOLLOWUP] Document event log compaction into new section of monitoring.md URL: https://github.com/apache/spark/pull/27398#discussion_r379874260
########## File path: docs/monitoring.md ########## @@ -95,6 +95,44 @@ The history server can be configured as follows: </tr> </table> +### Applying compaction of old event log files + +A long-running streaming application can bring a huge single event log file which may cost a lot to maintain and +also requires a bunch of resource to replay per each update in Spark History Server. + +Enabling <code>spark.eventLog.rolling.enabled</code> and <code>spark.eventLog.rolling.maxFileSize</code> would +let you have multiple event log files instead of single huge event log file which may help some scenarios on its own, +but it still doesn't help you reducing the overall size of logs. + +Spark History Server can apply 'compaction' on the rolling event log files to reduce the overall size of +logs, via setting the configuration <code>spark.history.fs.eventLog.rolling.maxFilesToRetain</code> on the +Spark History Server. + +When the compaction happens, History Server lists all the available event log files, and considers the event log files older than Review comment: I chose "older" because the target event log files are created "before" than the event log files which will be retained - so that's semantically date based. It might be better to explain it with "index" which is clearer, but requires another explanation on "index". ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
