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[SPARK-22885][ML][TEST] ML test for StructuredStreaming: spark.ml.tuning #20261

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[SPARK-22885][ML][TEST] ML test for StructuredStreaming: spark.ml.tuning #20261

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15 changes: 11 additions & 4 deletions mllib/src/test/scala/org/apache/spark/ml/tuning/CrossValidatorSuite.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -25,17 +25,17 @@ import org.apache.spark.ml.classification.{LogisticRegression, LogisticRegressio
import org.apache.spark.ml.classification.LogisticRegressionSuite.generateLogisticInput
import org.apache.spark.ml.evaluation.{BinaryClassificationEvaluator, Evaluator, MulticlassClassificationEvaluator, RegressionEvaluator}
import org.apache.spark.ml.feature.HashingTF
import org.apache.spark.ml.linalg.Vectors
import org.apache.spark.ml.linalg.{Vector, Vectors}
import org.apache.spark.ml.param.ParamMap
import org.apache.spark.ml.param.shared.HasInputCol
import org.apache.spark.ml.regression.LinearRegression
import org.apache.spark.ml.util.{DefaultReadWriteTest, Identifiable, MLTestingUtils}
import org.apache.spark.mllib.util.{LinearDataGenerator, MLlibTestSparkContext}
import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTest, MLTestingUtils}
import org.apache.spark.mllib.util.LinearDataGenerator
import org.apache.spark.sql.Dataset
import org.apache.spark.sql.types.StructType

class CrossValidatorSuite
extends SparkFunSuite with MLlibTestSparkContext with DefaultReadWriteTest {
extends MLTest with DefaultReadWriteTest {

import testImplicits._

Expand Down Expand Up @@ -66,6 +66,13 @@ class CrossValidatorSuite
assert(parent.getRegParam === 0.001)
assert(parent.getMaxIter === 10)
assert(cvModel.avgMetrics.length === lrParamMaps.length)

val result = cvModel.transform(dataset).select("prediction").as[Double].collect()
testTransformerByGlobalCheckFunc[(Double, Vector)](dataset.toDF(), cvModel, "prediction") {
rows =>
val result2 = rows.map(_.getDouble(0))
assert(result === result2)
}
}

test("cross validation with linear regression") {
Expand Down
15 changes: 11 additions & 4 deletions mllib/src/test/scala/org/apache/spark/ml/tuning/TrainValidationSplitSuite.scala
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Expand Up @@ -24,17 +24,17 @@ import org.apache.spark.ml.{Estimator, Model}
import org.apache.spark.ml.classification.{LogisticRegression, LogisticRegressionModel, OneVsRest}
import org.apache.spark.ml.classification.LogisticRegressionSuite.generateLogisticInput
import org.apache.spark.ml.evaluation.{BinaryClassificationEvaluator, Evaluator, RegressionEvaluator}
import org.apache.spark.ml.linalg.Vectors
import org.apache.spark.ml.linalg.{Vector, Vectors}
import org.apache.spark.ml.param.ParamMap
import org.apache.spark.ml.param.shared.HasInputCol
import org.apache.spark.ml.regression.LinearRegression
import org.apache.spark.ml.util.{DefaultReadWriteTest, Identifiable, MLTestingUtils}
import org.apache.spark.mllib.util.{LinearDataGenerator, MLlibTestSparkContext}
import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTest, MLTestingUtils}
import org.apache.spark.mllib.util.LinearDataGenerator
import org.apache.spark.sql.Dataset
import org.apache.spark.sql.types.StructType

class TrainValidationSplitSuite
extends SparkFunSuite with MLlibTestSparkContext with DefaultReadWriteTest {
extends MLTest with DefaultReadWriteTest {

import testImplicits._

Expand Down Expand Up @@ -64,6 +64,13 @@ class TrainValidationSplitSuite
assert(parent.getRegParam === 0.001)
assert(parent.getMaxIter === 10)
assert(tvsModel.validationMetrics.length === lrParamMaps.length)

val result = tvsModel.transform(dataset).select("prediction").as[Double].collect()
testTransformerByGlobalCheckFunc[(Double, Vector)](dataset.toDF(), tvsModel, "prediction") {
rows =>
val result2 = rows.map(_.getDouble(0))
assert(result === result2)
}
}

test("train validation with linear regression") {
Expand Down