sorry, I removed others by mistake
thanks a lot, Mario, for explaining. Appreciate it.
On Sun, May 1, 2016 at 11:51 PM, Mario Ds Briggs
wrote:
> Not sure if it was a mistake that you removed others and the group on this
> response
>
> >>
>
>the data duplication in-efficiency (replication to
Thanks, Shane!
On Monday, May 2, 2016, shane knapp wrote:
> workers -01 and -04 are back up, is is -06 (as i hit the wrong power
> button by accident). :)
>
> -01 and -04 got hung on shutdown, so i'll investigate them and see
> what exactly happened. regardless, we should be building happily!
workers -01 and -04 are back up, is is -06 (as i hit the wrong power
button by accident). :)
-01 and -04 got hung on shutdown, so i'll investigate them and see
what exactly happened. regardless, we should be building happily!
On Mon, May 2, 2016 at 8:44 AM, shane knapp wrote:
> hey everyone!
>
I plan to.
I am not that familiar with all the parts involved though :-)
On Mon, May 2, 2016 at 9:42 AM, Reynold Xin wrote:
> Definitely looks like a bug.
>
> Ted - are you looking at this?
>
>
> On Mon, May 2, 2016 at 7:15 AM, Koert Kuipers wrote:
>
>> Created issue:
>> https://issues.apache.
Definitely looks like a bug.
Ted - are you looking at this?
On Mon, May 2, 2016 at 7:15 AM, Koert Kuipers wrote:
> Created issue:
> https://issues.apache.org/jira/browse/SPARK-15062
>
> On Mon, May 2, 2016 at 6:48 AM, Ted Yu wrote:
>
>> I tried the same statement using Spark 1.6.1
>> There wa
There is a JIRA and PR around for supporting polynomial expansion with
degree 1. Offhand I can't recall if it's been merged
On Mon, 2 May 2016 at 17:45, Julio Antonio Soto de Vicente
wrote:
> Hi,
>
> Same goes for the PolynomialExpansion in org.apache.spark.ml.feature. It
> would be dice to cross
Hi,
Same goes for the PolynomialExpansion in org.apache.spark.ml.feature. It would
be dice to cross-validate with degree 1 polynomial expansion (this is, with no
expansion at all) vs other degree polynomial expansions. Unfortunately, degree
is forced to be >= 2.
--
Julio
> El 2 may 2016, a la
Hi Nitin,
Sorry for waking up this ancient thread. That's a fantastic set of JVM
flags! We just hit the same problem, but we haven't even discovered all
those flags for limiting memory growth. I wanted to ask if you ever
discovered anything further?
I see you also set -XX:NewRatio=3. This is a ver
hey everyone!
looks like two of the workers didn't survive a reboot, so i will need
to head to the colo and console in to see what's going on.
sadly, one of the workers that didn't come back is -01, which runs the
doc builds.
anyways, i will post another update within the hour with the status of
this is happening now.
On Fri, Apr 29, 2016 at 12:52 PM, shane knapp wrote:
> (copy-pasta of previous message)
>
> another project hosted on our jenkins (e-mission) needs anaconda scipy
> upgraded from 0.15.1 to 0.17.0. this will also upgrade a few other
> libs, which i've included at the end of
Hi,
Since the 2.0.0 branch has been created and is now nearing feature freeze,
can SPARK-11962 get some love please. If we can decide if this should go
into 2.0.0 or 2.1.0, that would be great. Personally, I feel it can totally
go into 2.0.0 as the code is pretty much ready (except for the one bug
Created issue:
https://issues.apache.org/jira/browse/SPARK-15062
On Mon, May 2, 2016 at 6:48 AM, Ted Yu wrote:
> I tried the same statement using Spark 1.6.1
> There was no error with default memory setting.
>
> Suggest logging a bug.
>
> On May 1, 2016, at 9:22 PM, Koert Kuipers wrote:
>
> Yea
https://issues.apache.org/jira/browse/SPARK-13745
is really a defect and a blocker unless it is the decision to drop support
for Big Endian platforms. The PR has been reviewed and tested and I
strongly believe this needs to be targeted for 2.0.
On Mon, May 2, 2016 at 12:00 AM Reynold Xin wrote:
I tried the same statement using Spark 1.6.1
There was no error with default memory setting.
Suggest logging a bug.
> On May 1, 2016, at 9:22 PM, Koert Kuipers wrote:
>
> Yeah I got that too, then I increased heap for tests to 8G to get error I
> showed earlier.
>
>> On May 2, 2016 12:09 AM
Hi,
In certain cases (mostly due to time constraints), we need some model to run
without cross validation. In such a case, since k-fold value for cross
validator cannot be one, we have to maintain two different code paths to
achieve both the scenarios (with and without cross validation).
Would it
15 matches
Mail list logo