HeartSaVioR commented on a change in pull request #26416: [SPARK-29779][CORE]
Compact old event log files and cleanup
URL: https://github.com/apache/spark/pull/26416#discussion_r355822917
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File path: docs/configuration.md
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@@ -1023,6 +1023,24 @@ Apart from these, the following properties are also
available, and may be useful
The max size of event log file before it's rolled over.
</td>
</tr>
+<tr>
+ <td><code>spark.eventLog.rolling.maxFilesToRetain</code></td>
+ <td>Int.MaxValue</td>
+ <td>
+ The maximum number of event log files which will be retained as
non-compacted.
+ By default, all event log files will be retained. Please set the
configuration and
+ <code>spark.eventLog.rolling.maxFileSize</code> accordingly if you want to
control
+ the overall size of event log files. The event log files older than these
retained
+ files will be compacted into single file and deleted afterwards.<br/>
+ NOTE 1: Compaction will happen in Spark History Server, which means the
same value
+ will be applied across applications which are being loaded in Spark
History Server,
+ as well as compaction and cleanup would require running Spark History
Server.<br/>
+ NOTE 2: Spark History Server may not compact the old event log files if it
figures
+ out compaction on event log for such application won't reduce the size at
expected
+ rate threshold. For streaming query (including Structured Streaming) we
normally
+ expect compaction will run, but for batch query compaction won't run in
most cases.
Review comment:
No I don't expect compaction will run for batch query in most cases, as we
measure the acceptance rate and don't run compaction if the rate is low.
(That's a new change reflecting your suggestion.)
It might be possible if there're multiple "short" batch queries being run in
same driver process, but except jobserver-like one, I'm not sure it's the one
of major cases for batch query.
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