the "hitting the observation queue limit" problem

There are several tickets in this area:

• OAK-2587: threading with observation being too eagar causing observation queue to grow
• OAK-2669: avoiding diffing from mongo by using persistent cache instead.
• OAK-2349: which might be a duplicate or at least similar to 2669..
• OAK-2562: diffcache is inefficient

Yet I think it makes sense to create this summarizing ticket, about describing again what happens when the observation queue hits the limit - and eventually about how this can be improved

Consider the following scenario (also compare with OAK-2587 - but that one focused more on eagerness of threading):

• rate of incoming commits is large and starts to generate many changes into the observation queues, hence those queue become somewhat filled/loaded
• depending on the underlying nodestore used the calculation of diffs is more or less expensive - but at least for mongomk it is important that the diff can be served from the cache
  • in case of mongomk it can happen that diffs are no longer found in the cache and thus require a round-trip to mongo - which is magnitudes slower than via cache of course. this would result in the queue to start increasing even faster as dequeuing becomes slower now.
  • not sure about tarmk - I believe it should always be fast there
• so based on the above, there can be a situation where the queue grows and hits the configured limit
• if this limit is reached, the current mechanism is to collapse any subsequent change into one-big-marked-as-external-event change, lets call this a collapsed-change.
• this collapsed-change now becomes part of the normal queue and eventually would 'walk down the queue' and be processed normally - hence opening a high chance that yet a new collapsed-change is created should the queue just hit the limit again. and this game can now be played for a while, resulting in the queue to contain many/mostly such collapse-changes.
• there is now an additional assumption in that the diffing of such collapses is more expensive than normal diffing - plus it is almost guaranteed that the diff cannot for example be shared between observation listeners, since the exact 'collapse borders' depends on timing of each of the listeners' queues - ie the collapse diffs are unique thus not cachable..
• so as a result: once you have those collapse-diffs you can almost not get rid of them - they are heavy to process - hence dequeuing is very slow
• at the same time, there is always likely some commits happening in a typical system, eg with sling on top you have sling discovery which does heartbeats every now and then. So there's always new commits that add to the load.
• this will hence create a situation where quite a small additional commit rate can keep all the queues filled - due to the fact that the queue is full with 'heavy collapse diffs' that have to be calculated for each and every listener (of which you could have eg 150-200) individually.

So again, possible solutions for this:

• OAK-2669: tune diffing via persistent cache
• OAK-2587: have more threads to remain longer 'in the cache zone'
• tune your input speed explicitly to avoid filling the observation queues (this would be specific to your use-case of course, but can be seen as explicitly throttling on the input side)
• increase the relevant caches to the max
• but I think we will come up with yet a broader improvement of this observation queue limit problem by either
  • doing flow control - eg via the commit rate limiter (also see OAK-1659)
  • moving out handling of observation changes to a messaging subsystem - be it to handle local events only (since handling external events makes the system problematic wrt scalability if not done right) - also see corresponding suggestion on dev list