Hi All,
I also had a scenario where at runtime, I needed to loop through a
dataframe to use withColumn many times.
For the safer side I used the reflection to access the withColumns to
prevent any java.lang.StackOverflowError.
val dataSetClass = Class.forName("org.apache.spark.sql.Dataset")
I recall that Bouncy Castle has some crypto export implications. If it's in
the distro then I think we'd have to update
https://www.apache.org/licenses/exports/ to reflect that Bouncy Castle is
again included in the product. But that's doable. Just have to recall how
one updates that.
On Thu, Apr
Hi Folks,
I've deployed a new version of K3s locally and I ran into an issue
with the key format not being supported out of the box. We delegate to
fabric8 which has bouncy castle EC as an optional dependency. Adding
it would add ~6mb to the Kube jars. What do folks think?
Cheers,
Holden
P.S.
I agree with Wenchen.
I can volunteer for Apache Spark 3.1.2 release manager at least.
Bests,
Dongjoon.
On Wed, Apr 28, 2021 at 10:15 AM Wenchen Fan wrote:
> Shall we make new releases for 3.0 and 3.1? So that people don't need to
> change the sbt resolver/pom files to work around Bintray
