imple enough, reading data from two S3 files, joining records
> on
> a shared field, filtering out some records and writing the result back to
> S3.
>
> Tried all kinds of stuff, but could not make it work. I did find similar
> questions, but had already tried the solutions that wo
he
>>> result back to
>>> S3.
>>>
>>> Tried all kinds of stuff, but could not make it work. I did
>>> find similar
>>> questions, but had already tried the solutions that worked
>>>
d the solutions that worked in those cases.
Would be really happy about any pointers.
Cheers,
Michael
--
View this message in context:
http://apache-spark-user-list.1001560.n3.nabble.com/Spark-job-uses-only-one-Worker-tp25909.html
Sent from the Apache Spark User List mailing list a
ng data from two S3
>>> files, joining records on
>>> a shared field, filtering out some records and writing
>>> the result back to
>>> S3.
>>>
>>> Tried all kinds of stuff, but could not make it wo
me records and writing the result back to
>>> S3.
>>>
>>> Tried all kinds of stuff, but could not make it work. I did find similar
>>> questions, but had already tried the solutions that worked in those
>>> cases.
>>&
s of stuff, but could not make it work. I did
>> find similar
>> questions, but had already tried the solutions that worked in
>> those cases.
>> Would be really happy about any pointers.
>>
>>
worked in those cases.
>> Would be really happy about any pointers.
>>
>> Cheers,
>> Michael
>>
>>
>>
>> --
>> View this message in context:
>> http://apache-spark-user-list.1001560.n3.nabble.com/Spark-job-uses-only-one-Worker-tp25909.ht
d the solutions that worked in
> those cases.
> Would be really happy about any pointers.
>
> Cheers,
> Michael
>
>
>
> --
> View this message in context:
>
> http://apache-spark-user-list.1001560.n3.nabble
uff, but could not make it work. I did find similar
> questions, but had already tried the solutions that worked in those cases.
> Would be really happy about any pointers.
>
> Cheers,
> Michael
>
>
>
> --
> View this message in context:
> http://apache-spark-user-list.1001
message in context:
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