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From Davies Liu <>
Subject Re: PySpark on PyPi
Date Thu, 06 Aug 2015 22:14:51 GMT
We could do that after 1.5 released, it will have same release cycle
as Spark in the future.

On Tue, Jul 28, 2015 at 5:52 AM, Olivier Girardot
<> wrote:
> +1 (once again :) )
> 2015-07-28 14:51 GMT+02:00 Justin Uang <>:
>> // ping
>> do we have any signoff from the pyspark devs to submit a PR to publish to
>> PyPI?
>> On Fri, Jul 24, 2015 at 10:50 PM Jeremy Freeman <>
>> wrote:
>>> Hey all, great discussion, just wanted to +1 that I see a lot of value in
>>> steps that make it easier to use PySpark as an ordinary python library.
>>> You might want to check out this (,
>>> started by Jupyter project devs, that offers one way to facilitate this
>>> stuff. I’ve also cced them here to join the conversation.
>>> Also, @Jey, I can also confirm that at least in some scenarios (I’ve done
>>> it in an EC2 cluster in standalone mode) it’s possible to run PySpark jobs
>>> just using `from pyspark import SparkContext; sc = SparkContext(master=“X”)`
>>> so long as the environmental variables (PYTHONPATH and PYSPARK_PYTHON) are
>>> set correctly on *both* workers and driver. That said, there’s definitely
>>> additional configuration / functionality that would require going through
>>> the proper submit scripts.
>>> On Jul 22, 2015, at 7:41 PM, Punyashloka Biswal <>
>>> wrote:
>>> I agree with everything Justin just said. An additional advantage of
>>> publishing PySpark's Python code in a standards-compliant way is the fact
>>> that we'll be able to declare transitive dependencies (Pandas, Py4J) in a
>>> way that pip can use. Contrast this with the current situation, where
>>> df.toPandas() exists in the Spark API but doesn't actually work until you
>>> install Pandas.
>>> Punya
>>> On Wed, Jul 22, 2015 at 12:49 PM Justin Uang <>
>>> wrote:
>>>> // + Davies for his comments
>>>> // + Punya for SA
>>>> For development and CI, like Olivier mentioned, I think it would be
>>>> hugely beneficial to publish pyspark (only code in the python/ dir) on PyPI.
>>>> If anyone wants to develop against PySpark APIs, they need to download the
>>>> distribution and do a lot of PYTHONPATH munging for all the tools (pylint,
>>>> pytest, IDE code completion). Right now that involves adding python/ and
>>>> python/lib/ In case pyspark ever wants to add more
>>>> dependencies, we would have to manually mirror all the PYTHONPATH munging
>>>> the ./pyspark script. With a proper pyspark which declares its
>>>> dependencies, and a published distribution, depending on pyspark will just
>>>> be adding pyspark to my dependencies.
>>>> Of course, if we actually want to run parts of pyspark that is backed by
>>>> Py4J calls, then we need the full spark distribution with either ./pyspark
>>>> or ./spark-submit, but for things like linting and development, the
>>>> PYTHONPATH munging is very annoying.
>>>> I don't think the version-mismatch issues are a compelling reason to not
>>>> go ahead with PyPI publishing. At runtime, we should definitely enforce that
>>>> the version has to be exact, which means there is no backcompat nightmare
>>>> suggested by Davies in
>>>> This would mean that even if the user got his pip installed pyspark to
>>>> somehow get loaded before the spark distribution provided pyspark, then the
>>>> user would be alerted immediately.
>>>> Davies, if you buy this, should me or someone on my team pick up
>>>> and
>>>> On Sat, Jun 6, 2015 at 12:48 AM Olivier Girardot
>>>> <> wrote:
>>>>> Ok, I get it. Now what can we do to improve the current situation,
>>>>> because right now if I want to set-up a CI env for PySpark, I have to
>>>>> 1- download a pre-built version of pyspark and unzip it somewhere on
>>>>> every agent
>>>>> 2- define the SPARK_HOME env
>>>>> 3- symlink this distribution pyspark dir inside the python install dir
>>>>> site-packages/ directory
>>>>> and if I rely on additional packages (like databricks' Spark-CSV
>>>>> project), I have to (except if I'm mistaken)
>>>>> 4- compile/assembly spark-csv, deploy the jar in a specific directory
>>>>> on every agent
>>>>> 5- add this jar-filled directory to the Spark distribution's additional
>>>>> classpath using the conf/spark-default file
>>>>> Then finally we can launch our unit/integration-tests.
>>>>> Some issues are related to spark-packages, some to the lack of
>>>>> python-based dependency, and some to the way SparkContext are launched
>>>>> using pyspark.
>>>>> I think step 1 and 2 are fair enough
>>>>> 4 and 5 may already have solutions, I didn't check and considering
>>>>> spark-shell is downloading such dependencies automatically, I think if
>>>>> nothing's done yet it will (I guess ?).
>>>>> For step 3, maybe just adding a to the distribution would be
>>>>> enough, I'm not exactly advocating to distribute a full 300Mb spark
>>>>> distribution in PyPi, maybe there's a better compromise ?
>>>>> Regards,
>>>>> Olivier.
>>>>> Le ven. 5 juin 2015 à 22:12, Jey Kottalam <>
a écrit
>>>>> :
>>>>>> Couldn't we have a pip installable "pyspark" package that just serves
>>>>>> as a shim to an existing Spark installation? Or it could even download
>>>>>> latest Spark binary if SPARK_HOME isn't set during installation.
Right now,
>>>>>> Spark doesn't play very well with the usual Python ecosystem. For
>>>>>> why do I need to use a strange incantation when booting up IPython
if I want
>>>>>> to use PySpark in a notebook with MASTER="local[4]"? It would be
much nicer
>>>>>> to just type `from pyspark import SparkContext; sc =
>>>>>> SparkContext("local[4]")` in my notebook.
>>>>>> I did a test and it seems like PySpark's basic unit-tests do pass
>>>>>> SPARK_HOME is set and Py4J is on the PYTHONPATH:
>>>>>> python $SPARK_HOME/python/pyspark/
>>>>>> -Jey
>>>>>> On Fri, Jun 5, 2015 at 10:57 AM, Josh Rosen <>
>>>>>> wrote:
>>>>>>> This has been proposed before:
>>>>>>> There's currently tighter coupling between the Python and Java
>>>>>>> of PySpark than just requiring SPARK_HOME to be set; if we did
this, I bet
>>>>>>> we'd run into tons of issues when users try to run a newer version
of the
>>>>>>> Python half of PySpark against an older set of Java components
>>>>>>> vice-versa.
>>>>>>> On Thu, Jun 4, 2015 at 10:45 PM, Olivier Girardot
>>>>>>> <> wrote:
>>>>>>>> Hi everyone,
>>>>>>>> Considering the python API as just a front needing the SPARK_HOME
>>>>>>>> defined anyway, I think it would be interesting to deploy
the Python part of
>>>>>>>> Spark on PyPi in order to handle the dependencies in a Python
>>>>>>>> needing PySpark via pip.
>>>>>>>> For now I just symlink the python/pyspark in my python install
>>>>>>>> site-packages/ in order for PyCharm or other lint tools to
work properly.
>>>>>>>> I can do the work or anything.
>>>>>>>> What do you think ?
>>>>>>>> Regards,
>>>>>>>> Olivier.

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