Hi,

are you using Spark 2.0.*? Then it might be related to
https://issues.apache.org/jira/browse/SPARK-18281 .

Best

Eike

2016-12-18 6:21 GMT+01:00 Russell Jurney <russell.jur...@gmail.com>:

> Anyone? This is for a book, so I need to figure this out.
>
> On Fri, Dec 16, 2016 at 12:53 AM Russell Jurney <russell.jur...@gmail.com>
> wrote:
>
>> I have created a PySpark Streaming application that uses Spark ML to
>> classify flight delays into three categories: on-time, slightly late, very
>> late. After an hour or so something times out and the whole thing crashes.
>>
>> The code and error are on a gist here: https://gist.github.com/rjurney/
>> 17d471bc98fd1ec925c37d141017640d
>>
>> While I am interested in why I am getting an exception, I am more
>> interested in understanding what the correct deployment model is... because
>> long running processes will have new and varied errors and exceptions.
>> Right now with what I've built, Spark is a highly dependable distributed
>> system but in streaming mode the entire thing is dependent on one Python
>> PID going down. This can't be how apps are deployed in the wild because it
>> will never be very reliable, right? But I don't see anything about this in
>> the docs, so I am confused.
>>
>> Note that I use this to run the app, maybe that is the problem?
>>
>> ssc.start()
>> ssc.awaitTermination()
>>
>>
>> What is the actual deployment model for Spark Streaming? All I know to do
>> right now is to restart the PID. I'm new to Spark, and the docs don't
>> really explain this (that I can see).
>>
>> Thanks!
>> --
>> Russell Jurney twitter.com/rjurney russell.jur...@gmail.com relato.io
>>
>>
>>


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