GitHub user SlavikBaranov opened a pull request:
https://github.com/apache/spark/pull/8395
[SPARK-10182] [MLlib] GeneralizedLinearModel doesn't unpersist cached data
`GeneralizedLinearModel` creates a cached RDD when building a model. It's
inconvenient, since these RDDs flood the memory when building several models in
a row, so useful data might get evicted from the cache.
The proposed solution is to always cache the dataset & remove the warning.
There's a caveat though: input dataset gets evaluated twice, in line 270 when
fitting `StandardScaler` for the first time, and when running optimizer for the
second time. So, it might worth to return removed warning.
Another possible solution is to disable caching entirely & return removed
warning. I don't really know what approach is better.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/SlavikBaranov/spark SPARK-10182
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/8395.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #8395
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commit 8a5a8e4111ca9ac0745af52e7a1c29d96711b5f4
Author: Vyacheslav Baranov <slavik.bara...@gmail.com>
Date: 2015-08-24T14:03:49Z
[SPARK-10182] [MLlib] GeneralizedLinearModel doesn't unpersist cached data
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