spark-instrumented-optimizer/mllib
Timothy Hunter 1018a1c1eb [SPARK-14568][ML] Instrumentation framework for logistic regression
## What changes were proposed in this pull request?

This adds extra logging information about a `LogisticRegression` estimator when being fit on a dataset. With this PR, you see the following extra lines when running the example in the documentation:

```
16/04/13 07:19:00 INFO Instrumentation: Instrumentation(LogisticRegression-logreg_55dd3c09f164-1230977381-1): training: numPartitions=1 storageLevel=StorageLevel(disk=true, memory=true, offheap=false, deserialized=true, replication=1)
16/04/13 07:19:00 INFO Instrumentation: Instrumentation(LogisticRegression-logreg_55dd3c09f164-1230977381-1): {"regParam":0.3,"elasticNetParam":0.8,"maxIter":10}
...
16/04/12 11:48:07 INFO Instrumentation: Instrumentation(LogisticRegression-logreg_a89eb23cb386-358781145):numClasses=2
16/04/12 11:48:07 INFO Instrumentation: Instrumentation(LogisticRegression-logreg_a89eb23cb386-358781145):numFeatures=692
...
16/04/13 07:19:01 INFO Instrumentation: Instrumentation(LogisticRegression-logreg_55dd3c09f164-1230977381-1): training finished
```

## How was this patch tested?

This PR was manually tested.

Author: Timothy Hunter <timhunter@databricks.com>

Closes #12331 from thunterdb/1604-instrumentation.
2016-04-13 11:06:42 -07:00
..
src [SPARK-14568][ML] Instrumentation framework for logistic regression 2016-04-13 11:06:42 -07:00
pom.xml [SPARK-14462][ML][MLLIB] Add the mllib-local build to maven pom 2016-04-11 09:35:47 -07:00