I am developing a spark job using java1.8v.
Is it possible to write a spark app using spring-boot technology?
Did anyone tried it ? if so how it should be done?
Regards,
Shyam
Thank you, Hyukjin !
On Sun, Jun 16, 2019 at 4:12 PM Hyukjin Kwon wrote:
> Labels look good and useful.
>
> On Sat, 15 Jun 2019, 02:36 Dongjoon Hyun, wrote:
>
>> Now, you can see the exposed component labels (ordered by the number of
>> PRs) here and click the component to search.
>>
>> htt
There's a column which captures the corrupted record. However, the
exception isn't captured. If the exception is captured in another column
it'll be very useful.
On Mon, 17 Jun, 2019, 10:56 AM Gourav Sengupta,
wrote:
> Hi,
>
> it already does, I think, you just have to add the column in the sche
Hi Daniel,
not quite sure of this, but does Glue Data Catalogue support bucketing yet?
You might want to find that out first.
Regards,
Gourav
On Sat, Jun 15, 2019 at 1:30 PM Daniel Mateus Pires
wrote:
> Hi there!
>
> I am trying to optimize joins on data created by Spark, so I'd like to
> buc
Hi,
it already does, I think, you just have to add the column in the schema
that you are using to read.
Regards,
Gourav
On Sun, Jun 16, 2019 at 2:48 PM wrote:
> Hi Team,
>
>
>
> Can we have another column which gives the corrupted record reason in
> permissive mode while reading csv.
>
>
>
> T
Labels look good and useful.
On Sat, 15 Jun 2019, 02:36 Dongjoon Hyun, wrote:
> Now, you can see the exposed component labels (ordered by the number of
> PRs) here and click the component to search.
>
> https://github.com/apache/spark/labels?sort=count-desc
>
> Dongjoon.
>
>
> On Fri, Jun 14
Hi Team,
Can we have another column which gives the corrupted record reason in
permissive mode while reading csv.
Thanks,
Ajay
Thanks Jorn. I am interested in timeseries forecasting for now but in
general I was unable to find a good way to work with different time series
methods using spark..
On Fri, Jun 14, 2019 at 1:55 AM Jörn Franke wrote:
> Time series can mean a lot of different things and algorithms. Can you
> des