Right, but that's an intentionally duplicative environment.  In most Akka
systems, you want to have at *most* one Actor for any given entity.  In
particular, if you are using Cluster Sharding and Akka Persistence,
duplication is a recipe for database corruption.

One might well be able to build a more redundant system on top of Akka,
which would be partition-tolerant in the way you're describing.  (In
particular, I could imagine something CRDT-based that wouldn't care so
much.)  But that's higher-level than Akka itself generally focuses.

And even there, you want to have a well-defined concept of when a node has
left the cluster permanently.  (Remember that most Akka architectures are
designed to be tolerant of scaling the cluster up and down based on load,
relatively dynamically.)

On Fri, Mar 17, 2017 at 2:24 PM, kant kodali <[email protected]> wrote:

> Why does one needs to take an approach of Split brain resolver when there
> is something better? The problem of network partitions is well understood
> in most distributed nosql databases. For example Cassandra continues to
> operate with the nodes that are available/reachable/up&running during
> network partitions and when the network partition is resolved (typically by
> fixing the cable or hardware) The most up to date nodes will just stream
> data to the stale ones.
>
>
>
>
> On Thursday, March 16, 2017 at 4:08:07 AM UTC-7, Dai Yinhua wrote:
>>
>> Hi team,
>>
>> I am aware that akka cluster may be partitioned to 2 clusters with
>> auto-downing.
>> But I can't understand how does it happen?
>> If node A is performing a long GC? And then node A become unreachable,
>> after a while, node A is marked as down, why the cluster is partitioned in
>> this case?
>>
>> Can you help to explain more clearly on that?
>>
>> Thank you.
>>
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