GitHub user sethah opened a pull request:
https://github.com/apache/spark/pull/14109
[SPARK-16404][ML] LeastSquaresAggregators serializes unnecessary data
## What changes were proposed in this pull request?
Similar to `LogisticAggregator`, `LeastSquaresAggregator` used for linear
regression ends up serializing the coefficients and the features standard
deviations, which is not necessary and can cause performance issues for high
dimensional data. This patch removes this serialization.
In https://github.com/apache/spark/pull/13729 the approach was to pass
these values directly to the add method. The approach used here, initially, is
to mark these fields as transient instead which gives the benefit of keeping
the signature of the add method simple and interpretable. The downside is that
it requires the use of `@transient lazy val`s which are difficult to reason
about if one is not quite familiar with serialization in Scala/Spark.
## How was this patch tested?
**MLlib**
**ML without patch**
**ML with patch**
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/sethah/spark LIR_serialize
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/14109.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 #14109
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commit 6b85765fb37f32e0c7587cd463e387a13ed5abdd
Author: sethah <seth.hendrickso...@gmail.com>
Date: 2016-07-08T18:53:33Z
remove unnecessary serialization in linear regression
commit 53655486b8ab28aa27077910672d17f3f6b66dd4
Author: sethah <seth.hendrickso...@gmail.com>
Date: 2016-07-08T22:45:07Z
using transient
commit 53c9192f0a8c234a1d185e3066154861ef25b77f
Author: sethah <seth.hendrickso...@gmail.com>
Date: 2016-07-08T22:52:12Z
style
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