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author | Yanbo Liang <ybliang8@gmail.com> | 2015-04-21 00:14:16 -0700 |
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committer | Xiangrui Meng <meng@databricks.com> | 2015-04-21 00:14:16 -0700 |
commit | 1f2f723b0daacbb9e70ec42c19a84470af1d7765 (patch) | |
tree | 6befec666031eae7d9ad7012cb57ec499fd2888b /mllib/src | |
parent | ab9128fb7ec7ca479dc91e7cc7c775e8d071eafa (diff) | |
download | spark-1f2f723b0daacbb9e70ec42c19a84470af1d7765.tar.gz spark-1f2f723b0daacbb9e70ec42c19a84470af1d7765.tar.bz2 spark-1f2f723b0daacbb9e70ec42c19a84470af1d7765.zip |
[SPARK-5990] [MLLIB] Model import/export for IsotonicRegression
Model import/export for IsotonicRegression
Author: Yanbo Liang <ybliang8@gmail.com>
Closes #5270 from yanboliang/spark-5990 and squashes the following commits:
872028d [Yanbo Liang] fix code style
f80ec1b [Yanbo Liang] address comments
49600cc [Yanbo Liang] address comments
429ff7d [Yanbo Liang] store each interval as a record
2b2f5a1 [Yanbo Liang] Model import/export for IsotonicRegression
Diffstat (limited to 'mllib/src')
-rw-r--r-- | mllib/src/main/scala/org/apache/spark/mllib/regression/IsotonicRegression.scala | 78 | ||||
-rw-r--r-- | mllib/src/test/scala/org/apache/spark/mllib/regression/IsotonicRegressionSuite.scala | 21 |
2 files changed, 98 insertions, 1 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/regression/IsotonicRegression.scala b/mllib/src/main/scala/org/apache/spark/mllib/regression/IsotonicRegression.scala index cb70852e3c..1d7617046b 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/regression/IsotonicRegression.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/regression/IsotonicRegression.scala @@ -23,9 +23,16 @@ import java.util.Arrays.binarySearch import scala.collection.mutable.ArrayBuffer +import org.json4s._ +import org.json4s.JsonDSL._ +import org.json4s.jackson.JsonMethods._ + import org.apache.spark.annotation.Experimental import org.apache.spark.api.java.{JavaDoubleRDD, JavaRDD} +import org.apache.spark.mllib.util.{Loader, Saveable} import org.apache.spark.rdd.RDD +import org.apache.spark.SparkContext +import org.apache.spark.sql.{DataFrame, SQLContext} /** * :: Experimental :: @@ -42,7 +49,7 @@ import org.apache.spark.rdd.RDD class IsotonicRegressionModel ( val boundaries: Array[Double], val predictions: Array[Double], - val isotonic: Boolean) extends Serializable { + val isotonic: Boolean) extends Serializable with Saveable { private val predictionOrd = if (isotonic) Ordering[Double] else Ordering[Double].reverse @@ -124,6 +131,75 @@ class IsotonicRegressionModel ( predictions(foundIndex) } } + + override def save(sc: SparkContext, path: String): Unit = { + IsotonicRegressionModel.SaveLoadV1_0.save(sc, path, boundaries, predictions, isotonic) + } + + override protected def formatVersion: String = "1.0" +} + +object IsotonicRegressionModel extends Loader[IsotonicRegressionModel] { + + import org.apache.spark.mllib.util.Loader._ + + private object SaveLoadV1_0 { + + def thisFormatVersion: String = "1.0" + + /** Hard-code class name string in case it changes in the future */ + def thisClassName: String = "org.apache.spark.mllib.regression.IsotonicRegressionModel" + + /** Model data for model import/export */ + case class Data(boundary: Double, prediction: Double) + + def save( + sc: SparkContext, + path: String, + boundaries: Array[Double], + predictions: Array[Double], + isotonic: Boolean): Unit = { + val sqlContext = new SQLContext(sc) + + val metadata = compact(render( + ("class" -> thisClassName) ~ ("version" -> thisFormatVersion) ~ + ("isotonic" -> isotonic))) + sc.parallelize(Seq(metadata), 1).saveAsTextFile(metadataPath(path)) + + sqlContext.createDataFrame( + boundaries.toSeq.zip(predictions).map { case (b, p) => Data(b, p) } + ).saveAsParquetFile(dataPath(path)) + } + + def load(sc: SparkContext, path: String): (Array[Double], Array[Double]) = { + val sqlContext = new SQLContext(sc) + val dataRDD = sqlContext.parquetFile(dataPath(path)) + + checkSchema[Data](dataRDD.schema) + val dataArray = dataRDD.select("boundary", "prediction").collect() + val (boundaries, predictions) = dataArray.map { x => + (x.getDouble(0), x.getDouble(1)) + }.toList.sortBy(_._1).unzip + (boundaries.toArray, predictions.toArray) + } + } + + override def load(sc: SparkContext, path: String): IsotonicRegressionModel = { + implicit val formats = DefaultFormats + val (loadedClassName, version, metadata) = loadMetadata(sc, path) + val isotonic = (metadata \ "isotonic").extract[Boolean] + val classNameV1_0 = SaveLoadV1_0.thisClassName + (loadedClassName, version) match { + case (className, "1.0") if className == classNameV1_0 => + val (boundaries, predictions) = SaveLoadV1_0.load(sc, path) + new IsotonicRegressionModel(boundaries, predictions, isotonic) + case _ => throw new Exception( + s"IsotonicRegressionModel.load did not recognize model with (className, format version):" + + s"($loadedClassName, $version). Supported:\n" + + s" ($classNameV1_0, 1.0)" + ) + } + } } /** diff --git a/mllib/src/test/scala/org/apache/spark/mllib/regression/IsotonicRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/regression/IsotonicRegressionSuite.scala index 7ef4524828..8e12340bbd 100644 --- a/mllib/src/test/scala/org/apache/spark/mllib/regression/IsotonicRegressionSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/mllib/regression/IsotonicRegressionSuite.scala @@ -21,6 +21,7 @@ import org.scalatest.{Matchers, FunSuite} import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.mllib.util.TestingUtils._ +import org.apache.spark.util.Utils class IsotonicRegressionSuite extends FunSuite with MLlibTestSparkContext with Matchers { @@ -73,6 +74,26 @@ class IsotonicRegressionSuite extends FunSuite with MLlibTestSparkContext with M assert(model.isotonic) } + test("model save/load") { + val boundaries = Array(0.0, 1.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0) + val predictions = Array(1, 2, 2, 6, 16.5, 16.5, 17.0, 18.0) + val model = new IsotonicRegressionModel(boundaries, predictions, true) + + val tempDir = Utils.createTempDir() + val path = tempDir.toURI.toString + + // Save model, load it back, and compare. + try { + model.save(sc, path) + val sameModel = IsotonicRegressionModel.load(sc, path) + assert(model.boundaries === sameModel.boundaries) + assert(model.predictions === sameModel.predictions) + assert(model.isotonic === model.isotonic) + } finally { + Utils.deleteRecursively(tempDir) + } + } + test("isotonic regression with size 0") { val model = runIsotonicRegression(Seq(), true) |