[ML-3844] Add GBTRegression benchmark (#156)

* add GBTRegression benchmark

* add GBTRegression benchmark

src/main/resources/com/databricks/spark/sql/perf/mllib/config/mllib-large.yaml

@@ -111,6 +111,11 @@ benchmarks:
   - name: regression.DecisionTreeRegression
     params:
       depth: [5, 10]
+  - name: regression.GBTRegression
+    params:
+      numFeatures: 2000
+      depth: 5
+      maxIter: 5
   - name: regression.GLMRegression
     params:
       numExamples: 500000

src/main/resources/com/databricks/spark/sql/perf/mllib/config/mllib-small.yaml

@@ -142,6 +142,12 @@ benchmarks:
       depth: 3
       numClasses: 4
       numFeatures: 5
+  - name: regression.GBTRegression
+    params:
+      numExamples: 100
+      numTestExamples: 10
+      depth: 3
+      maxIter: 3
   - name: regression.GLMRegression
     params:
       numExamples: 100

src/main/scala/com/databricks/spark/sql/perf/mllib/regression/GBTRegression.scala

@@ -0,0 +1,18 @@
+package com.databricks.spark.sql.perf.mllib.regression
+
+import org.apache.spark.ml.PipelineStage
+import org.apache.spark.ml.regression.GBTRegressor
+
+import com.databricks.spark.sql.perf.mllib.OptionImplicits._
+import com.databricks.spark.sql.perf.mllib.{BenchmarkAlgorithm, MLBenchContext,
+  TreeOrForestRegressor}
+
+object GBTRegression extends BenchmarkAlgorithm with TreeOrForestRegressor {
+  override def getPipelineStage(ctx: MLBenchContext): PipelineStage = {
+    import ctx.params._
+    new GBTRegressor()
+      .setMaxDepth(depth)
+      .setMaxIter(maxIter)
+      .setSeed(ctx.seed())
+  }
+}