. This
error seems to be happening completely on the driver as I don't see any
error on the Spark web interface. I have tried changing the
spark.yarn.am.memory configuration value, but it doesn't help. Any
suggestion on how to debug this will be very helpful.
Thank you,
Sooraj
Here i
parameter.
On 8 July 2015 at 12:35, sooraj wrote:
> Hi,
>
> I am using MLlib collaborative filtering API on an implicit preference
> data set. From a pySpark notebook, I am iteratively creating the matrix
> factorization model with the aim of measuring the RMSE for each combination
a PC) to
a remote Spark cluster. Not sure if that is possible.
- Sooraj
On 8 July 2015 at 15:31, Ashish Dutt wrote:
> My apologies for double posting but I missed the web links that i followed
> which are 1
> <http://ramhiser.com/2015/02/01/configuring-ipython-notebook-support-for-py
Hi,
The issue is very likely to be in the data or the transformations you
apply, rather than anything to do with the Spark Kmeans API as such. I'd
start debugging by doing a bit of exploratory analysis of the TFIDF
vectors. That is, for instance, plot the distribution (histogram) of the
TFIDF valu
