Github user feynmanliang commented on the pull request:
https://github.com/apache/spark/pull/7166#issuecomment-118238218
I did some [perf
testing](https://gist.github.com/feynmanliang/70d79c23dffc828939ec) and it
shows that distributing the Gaussians does yield a significant improvement in
performance when the number of clusters and dimensionality of the data is
sufficiently large (>30 dimensions, >10 clusters).
In particular, the "typical" use case of 40 dimensions and 10k clusters
gains about 15 seconds in runtime when distributing the Gaussians.
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