Ability to work with many data source is one the reason we chose Apache
Zeppelin.
For branch-0.7 our ops-team wrote a lot of python functions for import and
export data from diffent source (Greenlum, Hive, Oracle) using Python DataFrame
as middleware.
Our users can upload flat files to Zeppelin via Samba, then upload to DBs and
run queries.
Availability of ResourcePool in 0.8 is big milestone.
I hope ResourcePool will allow to smoothly intergate all sources in company.
It would be great if not only spark and python interpreter could get data from
ResourcePool.
2b case is nice.
Now I see that the transmit of table data is sufficient.
Regards,
Maxim Belousov
________________________________________
От: Jeff Zhang <zjf...@gmail.com>
Отправлено: 13 июля 2018 г. 6:00
Кому: users@zeppelin.apache.org
Копия: dev
Тема: Re: [DISCUSS] Share Data in Zeppelin
Thanks Sanjay, I have fixed the example note.
*Folks, to be noticed,* the example note is just a fake note, it won't work
for now.
Jongyoul Lee <jongy...@gmail.com>于2018年7月13日周五 上午10:54写道：
> BTW, we need to consider the case where the result is large in a design
> time. In my experience, If we implement this feature, users could use it
> with large data.
>
> On Fri, Jul 13, 2018 at 11:51 AM, Sanjay Dasgupta <
> sanjay.dasgu...@gmail.com> wrote:
>
>> I prefer 2.b also. Could we use (save*Result*AsTable=people) instead?
>>
>> There are a few typos in the example note shared:
>>
>> 1) The line val peopleDF = spark.read.format("zeppelin").load() should
>> mention the table name (possibly as argument to load?)
>> 2) The python line val peopleDF = z.getTable("people").toPandas() should
>> not have the val
>>
>>
>> The z.getTable(<table-name>) method could be a very good tool to judge
>> which use-cases are important in the community. It is easy to implement for
>> the in-memory data case, and could be very useful for many situations where
>> a small amount of data is being transferred across interpreters (like the
>> jdbc -> matplotlib case mentioned).
>>
>> Thanks,
>> Sanjay
>>
>> On Fri, Jul 13, 2018 at 8:07 AM, Jongyoul Lee <jongy...@gmail.com> wrote:
>>
>>> Yes, it's similar to 2.b.
>>>
>>> Basically, my concern is to handle all kinds of data. But in your case,
>>> it looks like focusing on table data. It's also useful but it would be
>>> better to handle all of the data including table or plain text as well.
>>> WDYT?
>>>
>>> About storage, we could discuss it later.
>>>
>>> On Fri, Jul 13, 2018 at 11:25 AM, Jeff Zhang <zjf...@gmail.com> wrote:
>>>
>>>>
>>>> I think your use case is the same of 2.b. Personally I don't recommend
>>>> to use z.get(noteId, paragraphId) to get the shared data for 2 reasons
>>>> 1. noteId, paragraphId is meaningless, which is not readable
>>>> 2. The note will break if we clone it as the noteId is changed.
>>>> That's why I suggest to use paragraph property to save paragraph's
>>>> result
>>>>
>>>> Regarding the intermediate storage, I also though about it and agree
>>>> that in the long term we should provide such layer to support large data,
>>>> currently we put the shared data in memory which is not a scalable
>>>> solution. One candidate in my mind is alluxio [1], and regarding the data
>>>> format I think apache arrow [2] is another good option for zeppelin to
>>>> share table data across interpreter processes and different languages. But
>>>> these are all implementation details, I think we can talk about them in
>>>> another thread. In this thread, I think we should focus on the user facing
>>>> api.
>>>>
>>>>
>>>> [1] http://www.alluxio.org/
>>>> [2] https://arrow.apache.org/
>>>>
>>>>
>>>>
>>>> Jongyoul Lee <jongy...@gmail.com>于2018年7月13日周五 上午10:11写道：
>>>>
>>>>> I have a bit different idea to share data.
>>>>>
>>>>> In my case,
>>>>>
>>>>> It would be very useful to get a paragraph's result as an input of
>>>>> other paragraphs.
>>>>>
>>>>> e.g.
>>>>>
>>>>> -- Paragrph 1
>>>>> %jdbc
>>>>> select * from some_table;
>>>>>
>>>>> -- Paragraph 2
>>>>> %spark
>>>>> val rdd = z.get("noteId", "paragraphId").parse.makeRddByMyself
>>>>> spark.read(table).select....
>>>>>
>>>>> If paragraph 1's result is too big to show on FE, it would be saved in
>>>>> Zeppelin Server with proper way and pass to SparkInterpreter when
>>>>> Paragraph
>>>>> 2 is executed.
>>>>>
>>>>> Basically, I think we need to intermediate storage to store
>>>>> paragraph's results to share them. We can introduce another layer or
>>>>> extend
>>>>> NotebootRepo. In some cases, we might change notebook repos as well.
>>>>>
>>>>> JL
>>>>>
>>>>>
>>>>>
>>>>> On Fri, Jul 13, 2018 at 10:39 AM, Jeff Zhang <zjf...@gmail.com> wrote:
>>>>>
>>>>>> Hi Folks,
>>>>>>
>>>>>> Recently, there's several tickets [1][2][3] about sharing data in
>>>>>> zeppelin.
>>>>>> Zeppelin's goal is to be an unified data analyst platform which could
>>>>>> integrate most of the big data tools and help user to switch between
>>>>>> tools
>>>>>> and share data between tools easily. So sharing data is a very
>>>>>> critical and
>>>>>> killer feature of Zeppelin IMHO.
>>>>>>
>>>>>> I raise this ticket to discuss about the scenario of sharing data and
>>>>>> how
>>>>>> to do that. Although zeppelin already provides tools and api to share
>>>>>> data,
>>>>>> I don't think it is mature and stable enough. After seeing these
>>>>>> tickets, I
>>>>>> think it might be a good time to talk about it in community and
>>>>>> gather more
>>>>>> feedback, so that we could provide a more stable and mature approach
>>>>>> for
>>>>>> it.
>>>>>>
>>>>>> Currently, there're 3 approaches to share data between interpreters
>>>>>> and
>>>>>> interpreter processes.
>>>>>> 1. Sharing data across interpreter in the same interpreter process.
>>>>>> Like
>>>>>> sharing data via the same SparkContext in %spark, %spark.pyspark and
>>>>>> %spark.r.
>>>>>> 2. Sharing data between frontend and backend via angularObject
>>>>>> 3. Sharing data across interpreter processes via Zeppelin's
>>>>>> ResourcePool
>>>>>>
>>>>>> For this thread, I would like to talk about the approach 3 (Sharing
>>>>>> data
>>>>>> via Zeppelin's ResourcePool)
>>>>>>
>>>>>> Here's my current thinking of sharing data.
>>>>>> 1. What kind of data would be shared ?
>>>>>> IMHO, users would share 2 kinds of data: primitive data (string,
>>>>>> number)
>>>>>> and table data.
>>>>>>
>>>>>> 2. How to write shared data ?
>>>>>> User may want to share data via 2 approches
>>>>>> a. Use ZeppelinContext (e.g. z.put).
>>>>>> b. Share the paragraph result via paragraph properties. e.g. user
>>>>>> may
>>>>>> want to read data from oracle database via jdbc interpreter and then
>>>>>> do
>>>>>> plotting in python interpreter. In such scenario. he can save the jdbc
>>>>>> result in ResourcePool via paragraph property and then read it it via
>>>>>> z.get. Here's one simple example (Not implemented yet)
>>>>>>
>>>>>> %jdbc(saveAsTable=people)
>>>>>> select * from oracle_table
>>>>>>
>>>>>> %python
>>>>>> z.getTable("people).toPandas()
>>>>>>
>>>>>> 3. How to read shared data ?
>>>>>> User can also have 2 approaches to read the shared data.
>>>>>> a. Via ZeppelinContext. (e.g. z.get, z.getTable)
>>>>>> b. Via variable substitution [1]
>>>>>>
>>>>>> Here's one sample note which illustrate the scenario of sharing data.
>>>>>>
>>>>>> https://www.zepl.com/viewer/notebooks/bm90ZTovL3pqZmZkdS8zMzkxZjg3YmFhMjg0MDY3OGM1ZmYzODAwODAxMGJhNy9ub3RlLmpzb24
>>>>>>
>>>>>> This is just my current thinking of sharing data in zeppelin, it
>>>>>> definitely
>>>>>> doesn't cover all the scenarios, so I raise this thread to discuss
>>>>>> about in
>>>>>> community, welcome any feedback and comments.
>>>>>>
>>>>>>
>>>>>> [1]. https://issues.apache.org/jira/browse/ZEPPELIN-3377
>>>>>> [2]. https://issues.apache.org/jira/browse/ZEPPELIN-3596
>>>>>> [3]. https://issues.apache.org/jira/browse/ZEPPELIN-3617
>>>>>>
>>>>>
>>>>>
>>>>>
>>>>> --
>>>>> 이종열, Jongyoul Lee, 李宗烈
>>>>> http://madeng.net
>>>>>
>>>>
>>>
>>>
>>> --
>>> 이종열, Jongyoul Lee, 李宗烈
>>> http://madeng.net
>>>
>>
>>
>
>
> --
> 이종열, Jongyoul Lee, 李宗烈
> http://madeng.net
>
