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From Jiri Jetmar <juergen.jet...@gmail.com>
Subject Re: Apache Zest / Apache Cassandra
Date Sun, 21 Feb 2016 10:45:20 GMT
Hi Niclas,

thank you - I will take a look on the entity store cassandra
implementation.

Cheers,
Jiri

2016-02-21 1:52 GMT+01:00 Niclas Hedhman <niclas@hedhman.org>:

> About Cassandra...
>
> I think the only reason was that with CQL no one took the time to refactor
> the code, perhaps due to some conceptual changes were introduced.
> But it could have been that there were no true test suite, and failing the
> Release Criteria and fixing "run embedded during test" with the same client
> as in production code, may have been non-trivial (not sure). You have old
> code in the sandbox.
>
> Useful link;
>
> http://prettyprint.me/prettyprint.me/2010/02/14/running-cassandra-as-an-embedded-service/index.html
> But I am uncertain if it is still relevant.
>
> Sandbox;
>
> https://github.com/apache/zest-sandbox/tree/master/extensions/entitystore-cassandra
>
> Niclas
>
> On Sun, Feb 21, 2016 at 3:38 AM, Jiri Jetmar <juergen.jetmar@gmail.com>
> wrote:
>
> > Hi guys,
> >
> > what is the status of the Apache Cassandra Entity Store ? Somehow I can
> > remember that Cassandra was supported but can not
> > find it in the current development branch.
> >
> > The reason I;m asking is because Cassandra works well with the analytical
> > Apache Spark stack.
> >
> > Assume a scenario where you have e.g. the following Domain Models like :
> >
> > - Products
> > - Orders
> > - Users
> >
> > Each Domain has  its own Api, Usercases and States that is stored in the
> > DM. Now you have e.g. a Webshop UI on top of the
> > above Domains.
> >
> > Now you want to answer questions like : What kind of Users are buying
> > Product X. Or, find those Users that are most likely buying
> > Product X in the next Y days.
> >
> > To answer those questions is typically a challenge of "Data Analytics"
> > using algorithm like PCA, Random Forest, Regressions, XGBoost, etc.
> > All can be done surely in Java, but from my impression the Python
> community
> > built over the last years an amazing tool set and environments.
> >
> > Also a "Data Scientist"  has to try out different things, until a good
> and
> > robust prediction is done. So the workflow is interactive and here is
> where
> > Apache Spark is offering
> > great tools, including the usage of the IPython/Jupyter Notebooks.
> Another
> > benefit is that one does not need to kick-on any ETL Jobs to transfer the
> > transactional data from the Domain Models to the analytical world -
> > Cassandra does this already. So one can do all the analysis on a realtime
> > snapshot
> > without influencing the transactional processing.
> >
> > Thank you.
> >
> > Cheers,
> > Jiri
> >
>
>
>
> --
> Niclas Hedhman, Software Developer
> http://zest.apache.org - New Energy for Java
>

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