GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/11367
[SPARK-13490] [ML] ML LinearRegression should cache standardization param
value
## What changes were proposed in this pull request?
Like [SPARK-13132](https://issues.apache.org/jira/browse/SPARK-13132) for
LogisticRegression, when LinearRegression with L1 regularization, the inner
functor passed to the quasi-newton optimizer in
```org.apache.spark.ml.regression.LinearRegression#train``` makes repeated
calls to ```$(standardization)```. This ultimately involves repeated string
interpolation triggered by ```org.apache.spark.ml.param.Param#hashCode```. We
should cache the value of the ```standardization``` rather than re-fetching it
from the ParamMap for every iteration.
## How was this patch tested?
No extra tests are added. It should pass all existing tests.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/yanboliang/spark spark-13490
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/11367.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 #11367
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commit f9c79b136ac41bd91f482a4f948acb780f493516
Author: Yanbo Liang <[email protected]>
Date: 2016-02-25T09:35:57Z
ML LinearRegression should cache standardization param value
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