Reynold's 3rd point is particularly strong in my opinion. Supporting
Scala 2.12 will require Java 8 anyway, and introducing such a change
is probably best done in a major release.
Consider what would happen if Spark 2.0 doesn't require Java 8 and
hence not support Scala 2.12. Will it be stuck on an older version
until 3.0 is out? Will it be introduced in a minor release?
I think 2.0 is the best time for such a change.

On Thu, Mar 24, 2016 at 11:46 AM, Stephen Boesch <java...@gmail.com> wrote:
> +1 for java8 only   +1 for 2.11+ only .    At this point scala libraries
> supporting only 2.10 are typically less active and/or poorly maintained.
> That trend will only continue when considering the lifespan of spark 2.X.
>
> 2016-03-24 11:32 GMT-07:00 Steve Loughran <ste...@hortonworks.com>:
>>
>>
>> On 24 Mar 2016, at 15:27, Koert Kuipers <ko...@tresata.com> wrote:
>>
>> i think the arguments are convincing, but it also makes me wonder if i
>> live in some kind of alternate universe... we deploy on customers clusters,
>> where the OS, python version, java version and hadoop distro are not chosen
>> by us. so think centos 6, cdh5 or hdp 2.3, java 7 and python 2.6. we simply
>> have access to a single proxy machine and launch through yarn. asking them
>> to upgrade java is pretty much out of the question or a 6+ month ordeal. of
>> the 10 client clusters i can think of on the top of my head all of them are
>> on java 7, none are on java 8. so by doing this you would make spark 2
>> basically unusable for us (unless most of them have plans of upgrading in
>> near term to java 8, i will ask around and report back...).
>>
>>
>>
>> It's not actually mandatory for the process executing in the Yarn cluster
>> to run with the same JVM as the rest of the Hadoop stack; all that is needed
>> is for the environment variables to set up the JAVA_HOME and PATH. Switching
>> JVMs not something which YARN makes it easy to do, but it may be possible,
>> especially if Spark itself provides some hooks, so you don't have to
>> manually lay with setting things up. That may be something which could
>> significantly ease adoption of Spark 2 in YARN clusters. Same for Python.
>>
>> This is something I could probably help others to address
>>
>

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