What kind of partitioning are you exploring?  GraphX actually has some built in 
partitioning algorithms but if you are interested in spectral or hierarchical 
methods you might want to look at Metis/Zoltan?   There was some interest in 
integrating Metis style algorithms in Spark (GraphX or GraphFrames) so you may 
consider porting those algorithms.  As far as dynamic graphs go, there is an 
ongoing effort at Berkeley to study dynamic graphs in Spark. I have cc’ed one 
of the key graduate students in that effort.  I hope that helps.

Good Luck!
Joey




> On Oct 24, 2016, at 7:48 AM, Jörn Franke <[email protected]> wrote:
> 
> Maybe titandb ?! It uses Hbase to store graphs and solr (on HDFS) to index 
> graphs. I am not 100% sure it supports it, but probably.
> It can also integrate Spark, but analytics on a given graph only.
> Otherwise you need to go for dedicated graph system.
> 
>> On 24 Oct 2016, at 16:41, Marco <[email protected]> wrote:
>> 
>> Hi,
>> 
>> I'm a student in Computer Science and I'm working for my master thesis=20
>> on Graph Partitioning problem, focusing on dynamic graph.
>> 
>> I'm searching for a framework to manage Dynamic Graph, with possible=20
>> disappearing of edges/nodes. Now the problem is: GraphX alone cannot=20
>> provide solution to manages this kind of graph, and searching throw=20
>> internet I didn't found nothing of relevant. There is a framework or a=20
>> way to handle dynamic graphs?
>> 
>> Thanks in advance
>> 
>> Marco Rocchi
>> 
>> 
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