As I am no Spark expert - will it be used only as kind of 
messaging(streaming) middleware to sync write and read store or also to 
somehow change/merge/
filter the events it gets/pulls from the write store or is this all done 
via the plugin for PersistentViews?
(I guess it has to be like this, otherwise using only one backend store 
cannot be supported?)

thanks,

michael

On Tuesday, 19 August 2014 17:48:16 UTC+2, Martin Krasser wrote:
>
>  
> On 19.08.14 17:41, Ashley Aitken wrote:
>  
>
>
> On Tuesday, 19 August 2014 19:33:55 UTC+8, Martin Krasser wrote: 
>>
>>   If so, it sounds like a great solution but why would that require an 
>> extension to the Akka Persistence design/API?
>>  
>>
>> Because transformed/joined/... event streams in backend store on the read 
>> side must be consumable by PersistentViews (for creating read models). I 
>> still see this backend store to maintain changes (= transformed/joined/... 
>> events) instead of current state. 
>>  
>
>  I am sorry I still don't see this.
>
>  This suggests to me that spark is talking directly to the read model 
> datastore (e.g. graph database, MongoDB, SQL database).
>
>  So are you suggesting: 
>
>  1. journal -> spark -> Akka actors (like PersistentView) -> read model 
> data store 
>
>  or
>
>  2. journal -> spark -> read model data store (like graph database, 
> MongoDb, SQL database) -> Akka actors <- Queries
>  
>
> I was suggesting 2.
>
>  
>  I see PersistentView(for generalised topics) as the glue between the 
> Akka journal (write store) and read stores (1.).
>  
>  Thanks for your patience.
>
>  Cheers,
> Ashley.
>
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>  

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