Hey Ilya,
If you'd like to generate some real-time conversation about your proposal
this might be a good thing to talk about during tomorrow's developer sync
at 10:00 am Pacific time. If you're interested please feel free to put it
on the agenda
<https://docs.google.com/document/d/153CUCj5LOJCFAVpdDZC7COJDwKh9RDjxaTA0S7lzwDA/edit?usp=sharing>
!
All the best!
Judith

On Fri, Jul 6, 2018 at 2:35 PM Benjamin Mahler <[email protected]> wrote:

> I was chatting with Ilya on slack and I'll re-post here:
>
> * Like Jie, I was hoping for a toggle (maybe it should start default off
> until we have production experience? sounds like Ilya has already
> experience with it running in test clusters so far)
>
> * I was asking whether this would be considered a flaw in leveldb's
> compaction algorithm. Ilya didn't see any changes in recent leveldb
> releases that would affect this. So, we probably should file an issue to
> see if they think it's a flaw and whether our workaround makes sense to
> them. We can reference this in the code for posterity.
>
> On Fri, Jul 6, 2018 at 2:24 PM, Jie Yu <[email protected]> wrote:
>
> > Sounds good to me.
> >
> > My only ask is to have a way to turn this feature off (flag, env var,
> etc)
> >
> > - Jie
> >
> > On Fri, Jul 6, 2018 at 1:39 PM, Vinod Kone <[email protected]> wrote:
> >
> >> I don't know about the replicated log, but the proposal seems find to
> me.
> >>
> >> Jie/BenM, do you guys have an opinion?
> >>
> >> On Mon, Jul 2, 2018 at 10:57 PM Santhosh Kumar Shanmugham <
> >> [email protected]> wrote:
> >>
> >>> +1. Aurora will hugely benefit from this change.
> >>>
> >>> On Mon, Jul 2, 2018 at 4:49 PM Ilya Pronin <[email protected]>
> >>> wrote:
> >>>
> >>> > Hi everyone,
> >>> >
> >>> > I'd like to propose adding "manual" LevelDB compaction to the
> >>> > replicated log truncation process.
> >>> >
> >>> > Motivation
> >>> >
> >>> > Mesos Master and Aurora Scheduler use the replicated log to persist
> >>> > information about the cluster. This log is periodically truncated to
> >>> > prune outdated log entries. However the replicated log storage is not
> >>> > compacted and grows without bounds. This leads to problems like
> >>> > synchronous failover of all master/scheduler replicas happening
> >>> > because all of them ran out of disk space.
> >>> >
> >>> > The only time when log storage compaction happens is during recovery.
> >>> > Because of that periodic failovers are required to control the
> >>> > replicated log storage growth. But this solution is suboptimal.
> >>> > Failovers are not instant: e.g. Aurora Scheduler needs to recover the
> >>> > storage which depending on the cluster can take several minutes.
> >>> > During the downtime tasks cannot be (re-)scheduled and users cannot
> >>> > interact with the service.
> >>> >
> >>> > Proposal
> >>> >
> >>> > In MESOS-184 John Sirois pointed out that our usage pattern doesn’t
> >>> > work well with LevelDB background compaction algorithm. Fortunately,
> >>> > LevelDB provides a way to force compaction with DB::CompactRange()
> >>> > method. Replicated log storage can trigger it after persisting
> learned
> >>> > TRUNCATE action and deleting truncated log positions. The compacted
> >>> > range will be from previous first position of the log to the new
> first
> >>> > position (the one the log was truncated up to).
> >>> >
> >>> > Performance impact
> >>> >
> >>> > Mesos Master and Aurora Scheduler have 2 different replicated log
> >>> > usage profiles. For Mesos Master every registry update (agent
> >>> > (re-)registration/marking, maintenance schedule update, etc.) induces
> >>> > writing a complete snapshot which depending on the cluster size can
> >>> > get pretty big (in a scale test fake cluster with 55k agents it is
> >>> > ~15MB). Every snapshot is followed by a truncation of all previous
> >>> > entries, which doesn't block the registrar and happens kind of in the
> >>> > background. In the scale test cluster with 55k agents compactions
> >>> > after such truncations take ~680ms.
> >>> >
> >>> > To reduce the performance impact for the Master compaction can be
> >>> > triggered only after more than some configurable number of keys were
> >>> > deleted.
> >>> >
> >>> > Aurora Scheduler writes incremental changes of its storage to the
> >>> > replicated log. Every hour a storage snapshot is created and
> persisted
> >>> > to the log, followed by a truncation of all entries preceding the
> >>> > snapshot. Therefore, storage compactions will be infrequent but will
> >>> > deal with potentially large number of keys. In the scale test cluster
> >>> > such compactions took ~425ms each.
> >>> >
> >>> > Please let me know what you think about it.
> >>> >
> >>> > Thanks!
> >>> >
> >>> > --
> >>> > Ilya Pronin
> >>> >
> >>>
> >>
> >
>


-- 
Judith Malnick
Community Manager
310-709-1517

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