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Posted to issues@ozone.apache.org by GitBox <gi...@apache.org> on 2020/02/11 14:52:59 UTC

[GitHub] [hadoop-ozone] elek commented on issue #534: HDDS-2987. Add metrics to OM DoubleBuffer.

elek commented on issue #534: HDDS-2987. Add metrics to OM DoubleBuffer.
URL: https://github.com/apache/hadoop-ozone/pull/534#issuecomment-584673375
 
 
   > let me know your thoughts
   
   I misunderstood the average calculation previously therefore I used the wrong examples. This is a better one:
   
   Let's say you have 100 day uptime and at each of day you had 2_000_000 flush transactions with 1_000_000 flush operations. The avgFlushTransactionsInOneIteration is 2_000_000 * 100 / 1_000_000 * 100 = 2.0
   
   The 101st day is a very bad day as you have 2_000_000 transaction per day but with 1_500_000 operations. This is 50% bigger than before, but from the average it's very hard to notice: 2_000_000 * 100 + 2_000_000) / (1_000_000 * 100 + 1_500_000) = 1.99...
   
   I think a generic average (which is calculated based on **all the events from the start-up**) is not so effective. It is very expressive at the beginning but later it couldn't show real problems.
   
   With real moving averages (which can be easily calculated by prometheus or any other monitoring system) you can see the average of the **last day** or any period. 
   
   But this is not a blocking problem. I don't think that the average of this patch is a very useful metric for production but it might be useful for your performance tests (where you are interested only about the few hours after the startup). (But you can always use prometheus to calculate moving averages...)
   
   Long story short: I will merge it now... Thanks the patch...

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