How big of a deal this use case is in a heterogeneous endianness
environment? If we do want to fix it, we should do it when right before
Spark shuffles data to minimize performance penalty, i.e. turn big-endian
encoded data into little-indian encoded data before it goes on the wire.
This is a
> Ok, sounds good. I think it would be great, if you could add installing the
> 'docker-engine' package and starting the 'docker' service in there too. I
> was planning to update the playbook if there were one in the apache/spark
> repo but I didn't see one, hence my question.
>
we currently have
(I don't know anything spark specific, so I'm going to treat it like a
Breeze question...)
As I understand it, Spark uses ARPACK via Breeze for SVD, and presumably
the same approach can be used for EVD. Basically, you make a function that
multiplies your "matrix" (which might be represented
I'd also like to get Wiki write access - at the least it allows a few of us
to amend the "Powered By" and similar pages when those requests come
through (Sean has been doing a lot of that recently :)
On Mon, Jan 11, 2016 at 11:01 PM, Sean Owen wrote:
> ... I forget who can
If you need it, just copy it over to your own package. That's probably the
safest option.
On Tue, Jan 12, 2016 at 12:50 PM, Ted Yu wrote:
> There is no annotation in TestingUtils class indicating whether it is
> suitable for consumption by external projects.
>
> You
Hi,
I'm putting together a Spark package (in the spark-packages.org sense)
and I'd like to make use of the class
org.apache.spark.mllib.util.TestingUtils which appears in
mllib/src/test. Can I declare a dependency in my build.sbt to pull in
a suitable jar? I have searched around but I have not
There is no annotation in TestingUtils class indicating whether it is
suitable for consumption by external projects.
You should assume the class is not public since its methods may change in
future Spark releases.
Cheers
On Tue, Jan 12, 2016 at 12:36 PM, Robert Dodier
Hi all,
I'd like to share news of the recent release of a new Spark package,
[ROSE](http://spark-packages.org/package/onetapbeyond/opencpu-spark-executor).
ROSE is a Scala library offering access to the full scientific computing power
of the R programming language to Apache Spark batch and
I logged SPARK-12778 where endian awareness in Platform.java should
help in mixed
endian set up.
There could be other parts of the code base which are related.
Cheers
On Tue, Jan 12, 2016 at 7:01 AM, Adam Roberts wrote:
> Hi all, I've been experimenting with DataFrame
Hi all, I've been experimenting with DataFrame operations in a mixed
endian environment - a big endian master with little endian workers. With
tungsten enabled I'm encountering data corruption issues.
For example, with this simple test code:
import org.apache.spark.SparkContext
import
Hi,
I wanted to know if there are any implementations yet within the Machine
Learning Library or generally that can efficiently solve eigenvalue problems?
Or if not do you have suggestions on how to approach a parallel execution maybe
with BLAS or Breeze?
Thanks in advance!
Lydia
Von meinem
David,
Thank you very much for announcing this! It looks like it could be very
useful. Would you mind providing a link to the github?
On Tue, Jan 12, 2016 at 10:03 AM, David
wrote:
> Hi all,
>
> I'd like to share news of the recent release of a new Spark
Hi Corey,
> Would you mind providing a link to the github?
Sure, here is the github link you're looking for:
https://github.com/onetapbeyond/opencpu-spark-executor
David
"All that is gold does not glitter, Not all those who wander are lost."
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