For your use case one might indeed be able to work simply with incremental 
graph updates. However they are not straight forward in Spark. You can union 
the new Data with the existing dataframes that represent your graph and create 
from that a new graph frame.

However I am not sure if this will fully fulfill your requirement for 
incremental graph updates.

> On 14. Jul 2018, at 15:59, kant kodali <kanth...@gmail.com> wrote:
> 
> "You want to update incrementally an existing graph and run incrementally a 
> graph algorithm suitable for this - you have to implement yourself as far as 
> I am aware"
> 
> I want to update the graph incrementally and want to run some graph queries 
> similar to Cypher like give me all the vertices that are connected by a 
> specific set of edges and so on. Don't really intend to run graph algorithms 
> like ConnectedComponents or anything else at this point but of course, it's 
> great to have.
> 
> If we were to do this myself should I extend the GraphFrame? any suggestions?
> 
> 
>> On Sun, Apr 29, 2018 at 3:24 AM, Jörn Franke <jornfra...@gmail.com> wrote:
>> What is the use case you are trying to solve?
>> You want to load graph data from a streaming window in separate graphs - 
>> possible but requires probably a lot of memory. 
>> You want to update an existing graph with new streaming data and then fully 
>> rerun an algorithms -> look at Janusgraph
>> You want to update incrementally an existing graph and run incrementally a 
>> graph algorithm suitable for this - you have to implement yourself as far as 
>> I am aware
>> 
>> > On 29. Apr 2018, at 11:43, kant kodali <kanth...@gmail.com> wrote:
>> > 
>> > Do GraphFrames support streaming?
> 

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