Thank you guys for valuable inputs.

I have never used Jupyter myself but have used Zeppelin. Obviously it
sounds like if the Big Data deployed has Spark centric view of things (with
Spark being the penicillin of Big Data World :) together with Scala and
SQL, then Zeppelin is a goof fit. I have also noticed recently that
Hortonworks are actively promoting Zeppelin. However, I do appreciate that
there are fans of Python around.

May be a strategy would to offer both. Having said that there are hard core
users that would never give up on Tableau!

Regards


Dr Mich Talebzadeh



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On 28 November 2016 at 20:32, DuyHai Doan <doanduy...@gmail.com> wrote:

> "Granted, these two features are currently only fully supported by the
> spark interpreter group but work is currently underway to make the API
> extensible to other interpreters"
> --> Incorrect, the display system has also an API for front-end:
> https://zeppelin.apache.org/docs/0.7.0-SNAPSHOT/displaysystem/front-
> end-angular.html
>
> On Mon, Nov 28, 2016 at 9:23 PM, Goodman, Alexander (398K) <
> alexander.good...@jpl.nasa.gov> wrote:
>
>> Hi Mich,
>>
>> You might want to take a look at this:
>> https://www.linkedin.com/pulse/comprehensive-comparison-jupy
>> ter-vs-zeppelin-hoc-q-phan-mba-
>>
>> I use both Zeppelin and Jupyter myself, and I would say by and large the
>> conclusions of that article are still mostly correct. Jupyter is definitely
>> superior in terms of stability, language (kernel) support, ease of
>> installation and maintenance (thanks to conda) and performance. If you just
>> want something that works well straight out of the box, then Jupyter should
>> be your goto notebook solution. I would say this is especially true if your
>> workflow is largely in python since many of the Jupyter developers also
>> have close ties with the general python data analytics / scientific
>> computing community, which results in better integration with some
>> important packages (like matplotlib and bokeh, for example). This makes
>> sense given that the project was originally a part of ipython after all.
>>
>> However I definitely think Zeppelin still has an important place. The
>> vast majority of Zeppelin users also use spark (also an apache project),
>> and for that use case it should always be better than Jupyter given that
>> its backend code is written in Java (a JVM language). There are also
>> several advanced features that Zeppelin has that are somewhat unique,
>> including a simple API for sharing variables across interpreters (
>> https://zeppelin.apache.org/docs/0.7.0-SNAPSHOT/interpreter
>> /spark.html#object-exchange). There's also the angular display system
>> API (https://zeppelin.apache.org/docs/0.7.0-SNAPSHOT/displaysyst
>> em/back-end-angular.html). Granted, these two features are currently
>> only fully supported by the spark interpreter group but work is currently
>> underway to make the API extensible to other interpreters. Lastly, I think
>> the most powerful feature of Zeppelin is the overall concept of the
>> interpreter (in contrast to Jupyter's kernels) and the ability to use them
>> together in a single notebook. This is my main reason for using Zeppelin
>> since I regularly work with both spark/scala and python together.
>>
>> So tl;dr, if you are using spark and/or have workflows which use multiple
>> languages (namely scala/R/python/SQL), you should stick with Zeppelin.
>> Otherwise, I would suggest Jupyter.
>>
>> On Mon, Nov 28, 2016 at 5:06 AM, Mich Talebzadeh <
>> mich.talebza...@gmail.com> wrote:
>>
>>> H,
>>>
>>> I use Zeppelin in different form and shape and it is very promising.
>>> Some colleagues are mentioning that Jupiter can do all that Zeppelin
>>> handles.
>>>
>>> I have not used Jupiter myself. I have used Tableau but that is pretty
>>> limited to SQL.
>>>
>>> Anyone has used Jupiter and can share their experience of it vis-à-vis
>>> Zeppelin?
>>>
>>> Thanks
>>>
>>> Dr Mich Talebzadeh
>>>
>>>
>>>
>>> LinkedIn * 
>>> https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
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>>>
>>>
>>>
>>> http://talebzadehmich.wordpress.com
>>>
>>>
>>> *Disclaimer:* Use it at your own risk. Any and all responsibility for
>>> any loss, damage or destruction of data or any other property which may
>>> arise from relying on this email's technical content is explicitly
>>> disclaimed. The author will in no case be liable for any monetary damages
>>> arising from such loss, damage or destruction.
>>>
>>>
>>>
>>
>>
>>
>> --
>> Alex Goodman
>> Data Scientist I
>> Science Data Modeling and Computing (398K)
>> Jet Propulsion Laboratory
>> California Institute of Technology
>> Tel: +1-818-354-6012
>>
>
>

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