Hi Luca!

Those were separate Yarn jobs I started later. When I got this error, I
found that the Yarn job corresponding to the SparkContext was marked as
"successful", but I still couldn't get SparkSession.builder.getOrCreate to
open a new one.

Any idea what might have caused that or how I could recover without
restarting the notebook, which could mean losing a lot of in-progress work?
I had already restarted that kernel so I don't know if I'll encounter this
problem again. If I do, I'll file a task.

On Wed, 5 Feb 2020 at 23:24, Luca Toscano <[email protected]> wrote:

> Hey Neil,
>
> there were two Yarn jobs running related to your notebooks, I just killed
> them, let's see if it solves the problem (you might need to restart again
> your notebook). If not, let's open a task and investigate :)
>
> Luca
>
> Il giorno gio 6 feb 2020 alle ore 02:08 Neil Shah-Quinn <
> [email protected]> ha scritto:
>
>> Whoa—I just got the same stopped SparkContext error on the query even
>> after restarting the notebook, without an intermediate Java heap space
>> error. That seems very strange to me.
>>
>> On Wed, 5 Feb 2020 at 16:09, Neil Shah-Quinn <[email protected]>
>> wrote:
>>
>>> Hey there!
>>>
>>> I was running SQL queries via PySpark (using the wmfdata package
>>> <https://github.com/neilpquinn/wmfdata/blob/master/wmfdata/hive.py>) on
>>> SWAP when one of my queries failed with "java.lang.OutofMemoryError: Java
>>> heap space".
>>>
>>> After that, when I tried to call the spark.sql function again (via
>>> wmfdata.hive.run), it failed with "java.lang.IllegalStateException: Cannot
>>> call methods on a stopped SparkContext."
>>>
>>> When I tried to create a new Spark context using
>>> SparkSession.builder.getOrCreate (whether using wmfdata.spark.get_session
>>> or directly), it returned a SparkContent object properly, but calling the
>>> object's sql function still gave the "stopped SparkContext error".
>>>
>>> Any idea what's going on? I assume restarting the notebook kernel would
>>> take care of the problem, but it seems like there has to be a better way to
>>> recover.
>>>
>>> Thank you!
>>>
>>>
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