Hi,

> > Thus, I don’t think GremlinServer really needs to come into play.
> 
> Unless i'm missing something, I'm not sure we should say it quite that way - 
> that's a bit more jvm-centric sounding. So as not to be confused, non-jvm 
> GLVs would still require Gremlin Server, right?

I think it gets back to “anything that supports RemoteConnection” to accept the 
traversal (RemoteStrategy) and then "anything that implements GraphActors” to 
execute the traversal (ActorProgramStrategy).

Marko.



> 
> On Thu, Dec 15, 2016 at 11:47 AM, Marko Rodriguez <[email protected] 
> <mailto:[email protected]>> wrote:
> Hi,
> 
>> How will this get deployed? Each database instance (alternatively 
>> gremlin-server) shipping a version of akka-actor and akka-cluster?
> 
> This is a good question. As I’m seeing it lately, I think we treat it just 
> like spark-gremlin/. That is, lets assume a multi-machine graph database:
> 
>       1. User has a graph database across 3 nodes in a cluster.
>       2. User has Akka Cluster setup on those 3 nodes. (like they would have 
> SparkServer or Hadoop).
>       3. akka-gremlin/ “jobs” have a configuration with information about the 
> Akka cluster and the graph database partitions.
> 
> Thus, I don’t think GremlinServer really needs to come into play. However, I 
> sort of think that down the line, GremlinServer should support the spawning 
> of “services.” For instance, it would be great if GremlinServer, when 
> deployed, it could spawn a SparkServer cluster or an Akka Cluster… This 
> removes the headache for users having to install and configure stuff. It 
> would be great if GremlinServer was like a Docker or something.
> 
>       bin/gremlin-server.sh —i akka.gremlin.plugin —c akka.properties
> 
> Dunno. Stephen would have more to say.
> 
>> What does it mean for performance? Here's my understanding... thoughts?
>> 
>>      1. A sharded graph database: as long as the data is local it'll scale 
>> linearly, then it needs some synchronisation (i.e. hand off the traversal to 
>> the instance where the data is local again). I.e. there'll be a sweet spot 
>> of replication vs. shards for each use case. 
>>      2. A replicated graph database: should scale linearly for most 
>> traversals
>>      3. A single machine graph database: should scale linearly for most 
>> traversals
> 
> So there will be traverser migration when a traverser no longer references 
> data in its current partition. That is a message pass. You don’t want just 
> full replication because then you aren’t load balancing your traversals 
> across machines. Even if you have a replicated graph database, you will want 
> to create logical partitions so that traversers will be forced to move 
> between machines. When its worth doing that or when you should just use 
> standard iterator Gremlin execution is a fine line… how much data will your 
> traversal touch?
> 
> Marko.
> 
> 
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