Repository: spark Updated Branches: refs/heads/master fc4b792d2 -> d9cf9c21f
[SPARK-11912][ML] ml.feature.PCA minor refactor Like [SPARK-11852](https://issues.apache.org/jira/browse/SPARK-11852), ```k``` is params and we should save it under ```metadata/``` rather than both under ```data/``` and ```metadata/```. Refactor the constructor of ```ml.feature.PCAModel``` to take only ```pc``` but construct ```mllib.feature.PCAModel``` inside ```transform```. Author: Yanbo Liang <yblia...@gmail.com> Closes #9897 from yanboliang/spark-11912. Project: http://git-wip-us.apache.org/repos/asf/spark/repo Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/d9cf9c21 Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/d9cf9c21 Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/d9cf9c21 Branch: refs/heads/master Commit: d9cf9c21fc6b1aa22e68d66760afd42c4e1c18b8 Parents: fc4b792 Author: Yanbo Liang <yblia...@gmail.com> Authored: Sun Nov 22 21:56:07 2015 -0800 Committer: Xiangrui Meng <m...@databricks.com> Committed: Sun Nov 22 21:56:07 2015 -0800 ---------------------------------------------------------------------- .../scala/org/apache/spark/ml/feature/PCA.scala | 23 +++++++-------- .../org/apache/spark/ml/feature/PCASuite.scala | 31 ++++++++------------ 2 files changed, 24 insertions(+), 30 deletions(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/spark/blob/d9cf9c21/mllib/src/main/scala/org/apache/spark/ml/feature/PCA.scala ---------------------------------------------------------------------- diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/PCA.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/PCA.scala index 32d7afe..aa88cb0 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/feature/PCA.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/feature/PCA.scala @@ -73,7 +73,7 @@ class PCA (override val uid: String) extends Estimator[PCAModel] with PCAParams val input = dataset.select($(inputCol)).map { case Row(v: Vector) => v} val pca = new feature.PCA(k = $(k)) val pcaModel = pca.fit(input) - copyValues(new PCAModel(uid, pcaModel).setParent(this)) + copyValues(new PCAModel(uid, pcaModel.pc).setParent(this)) } override def transformSchema(schema: StructType): StructType = { @@ -99,18 +99,17 @@ object PCA extends DefaultParamsReadable[PCA] { /** * :: Experimental :: * Model fitted by [[PCA]]. + * + * @param pc A principal components Matrix. Each column is one principal component. */ @Experimental class PCAModel private[ml] ( override val uid: String, - pcaModel: feature.PCAModel) + val pc: DenseMatrix) extends Model[PCAModel] with PCAParams with MLWritable { import PCAModel._ - /** a principal components Matrix. Each column is one principal component. */ - val pc: DenseMatrix = pcaModel.pc - /** @group setParam */ def setInputCol(value: String): this.type = set(inputCol, value) @@ -124,6 +123,7 @@ class PCAModel private[ml] ( */ override def transform(dataset: DataFrame): DataFrame = { transformSchema(dataset.schema, logging = true) + val pcaModel = new feature.PCAModel($(k), pc) val pcaOp = udf { pcaModel.transform _ } dataset.withColumn($(outputCol), pcaOp(col($(inputCol)))) } @@ -139,7 +139,7 @@ class PCAModel private[ml] ( } override def copy(extra: ParamMap): PCAModel = { - val copied = new PCAModel(uid, pcaModel) + val copied = new PCAModel(uid, pc) copyValues(copied, extra).setParent(parent) } @@ -152,11 +152,11 @@ object PCAModel extends MLReadable[PCAModel] { private[PCAModel] class PCAModelWriter(instance: PCAModel) extends MLWriter { - private case class Data(k: Int, pc: DenseMatrix) + private case class Data(pc: DenseMatrix) override protected def saveImpl(path: String): Unit = { DefaultParamsWriter.saveMetadata(instance, path, sc) - val data = Data(instance.getK, instance.pc) + val data = Data(instance.pc) val dataPath = new Path(path, "data").toString sqlContext.createDataFrame(Seq(data)).repartition(1).write.parquet(dataPath) } @@ -169,11 +169,10 @@ object PCAModel extends MLReadable[PCAModel] { override def load(path: String): PCAModel = { val metadata = DefaultParamsReader.loadMetadata(path, sc, className) val dataPath = new Path(path, "data").toString - val Row(k: Int, pc: DenseMatrix) = sqlContext.read.parquet(dataPath) - .select("k", "pc") + val Row(pc: DenseMatrix) = sqlContext.read.parquet(dataPath) + .select("pc") .head() - val oldModel = new feature.PCAModel(k, pc) - val model = new PCAModel(metadata.uid, oldModel) + val model = new PCAModel(metadata.uid, pc) DefaultParamsReader.getAndSetParams(model, metadata) model } http://git-wip-us.apache.org/repos/asf/spark/blob/d9cf9c21/mllib/src/test/scala/org/apache/spark/ml/feature/PCASuite.scala ---------------------------------------------------------------------- diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/PCASuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/PCASuite.scala index 5a21cd2..edab21e 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/PCASuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/PCASuite.scala @@ -32,7 +32,7 @@ class PCASuite extends SparkFunSuite with MLlibTestSparkContext with DefaultRead test("params") { ParamsSuite.checkParams(new PCA) val mat = Matrices.dense(2, 2, Array(0.0, 1.0, 2.0, 3.0)).asInstanceOf[DenseMatrix] - val model = new PCAModel("pca", new OldPCAModel(2, mat)) + val model = new PCAModel("pca", mat) ParamsSuite.checkParams(model) } @@ -66,23 +66,18 @@ class PCASuite extends SparkFunSuite with MLlibTestSparkContext with DefaultRead } } - test("read/write") { + test("PCA read/write") { + val t = new PCA() + .setInputCol("myInputCol") + .setOutputCol("myOutputCol") + .setK(3) + testDefaultReadWrite(t) + } - def checkModelData(model1: PCAModel, model2: PCAModel): Unit = { - assert(model1.pc === model2.pc) - } - val allParams: Map[String, Any] = Map( - "k" -> 3, - "inputCol" -> "features", - "outputCol" -> "pca_features" - ) - val data = Seq( - (0.0, Vectors.sparse(5, Seq((1, 1.0), (3, 7.0)))), - (1.0, Vectors.dense(2.0, 0.0, 3.0, 4.0, 5.0)), - (2.0, Vectors.dense(4.0, 0.0, 0.0, 6.0, 7.0)) - ) - val df = sqlContext.createDataFrame(data).toDF("id", "features") - val pca = new PCA().setK(3) - testEstimatorAndModelReadWrite(pca, df, allParams, checkModelData) + test("PCAModel read/write") { + val instance = new PCAModel("myPCAModel", + Matrices.dense(2, 2, Array(0.0, 1.0, 2.0, 3.0)).asInstanceOf[DenseMatrix]) + val newInstance = testDefaultReadWrite(instance) + assert(newInstance.pc === instance.pc) } } --------------------------------------------------------------------- To unsubscribe, e-mail: commits-unsubscr...@spark.apache.org For additional commands, e-mail: commits-h...@spark.apache.org
