small cleanups

apache · Feb 3, 2015 · b1fc5ec · b1fc5ec
1 parent 418ba1b
commit b1fc5ec
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Showing 3 changed files with 13 additions and 21 deletions.
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala b/mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala
@@ -23,11 +23,11 @@ import org.apache.spark.mllib.linalg.BLAS.dot
 import org.apache.spark.mllib.linalg.{DenseVector, Vector}
 import org.apache.spark.mllib.optimization._
 import org.apache.spark.mllib.regression._
-import org.apache.spark.mllib.util.{DataValidators, MLUtils}
-import org.apache.spark.mllib.util.{Importable, DataValidators, Exportable}
+import org.apache.spark.mllib.util.{DataValidators, Exportable, Importable, MLUtils}
 import org.apache.spark.rdd.RDD
 import org.apache.spark.sql.{Row, SQLContext, SchemaRDD}
 
+
 /**
  * Classification model trained using Multinomial/Binary Logistic Regression.
  *
@@ -143,8 +143,8 @@ class LogisticRegressionModel (
     import sqlContext._
     // TODO: Do we need to use a SELECT statement to make the column ordering deterministic?
     // Create JSON metadata.
-    val metadata =
-      LogisticRegressionModel.Metadata(clazz = this.getClass.getName, version = Exportable.version)
+    val metadata = LogisticRegressionModel.Metadata(
+      clazz = this.getClass.getName, version = Exportable.latestVersion)
     val metadataRDD: SchemaRDD = sc.parallelize(Seq(metadata))
     metadataRDD.toJSON.saveAsTextFile(path + "/metadata")
     // Create Parquet data.
@@ -156,6 +156,10 @@ class LogisticRegressionModel (
 
 object LogisticRegressionModel extends Importable[LogisticRegressionModel] {
 
+  private case class Metadata(clazz: String, version: String)
+
+  private case class Data(weights: Vector, intercept: Double, threshold: Option[Double])
+
   override def load(sc: SparkContext, path: String): LogisticRegressionModel = {
     val sqlContext = new SQLContext(sc)
     import sqlContext._
@@ -169,7 +173,7 @@ object LogisticRegressionModel extends Importable[LogisticRegressionModel] {
       case Row(clazz: String, version: String) =>
         assert(clazz == classOf[LogisticRegressionModel].getName, s"LogisticRegressionModel.load" +
           s" was given model file with metadata specifying a different model class: $clazz")
-        assert(version == Importable.version, // only 1 version exists currently
+        assert(version == Exportable.latestVersion, // only 1 version exists currently
           s"LogisticRegressionModel.load did not recognize model format version: $version")
     }
 
@@ -192,10 +196,6 @@ object LogisticRegressionModel extends Importable[LogisticRegressionModel] {
     lr
   }
 
-  private case class Metadata(clazz: String, version: String)
-
-  private case class Data(weights: Vector, intercept: Double, threshold: Option[Double])
-
 }
 
 /**

diff --git a/mllib/src/main/scala/org/apache/spark/mllib/util/modelImportExport.scala b/mllib/src/main/scala/org/apache/spark/mllib/util/modelImportExport.scala
@@ -20,7 +20,6 @@ package org.apache.spark.mllib.util
 import org.apache.spark.SparkContext
 import org.apache.spark.annotation.DeveloperApi
 
-
 /**
  * :: DeveloperApi ::
  *
@@ -50,7 +49,7 @@ trait Exportable {
 object Exportable {
 
   /** Current version of model import/export format. */
-  val version: String = "1.0"
+  val latestVersion: String = "1.0"
 
 }
 
@@ -75,10 +74,3 @@ trait Importable[Model <: Exportable] {
   def load(sc: SparkContext, path: String): Model
 
 }
-
-object Importable {
-
-  /** Current version of model import/export format. */
-  val version: String = Exportable.version
-
-}
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala
@@ -30,6 +30,7 @@ import org.apache.spark.mllib.linalg.{Vector, Vectors}
 import org.apache.spark.mllib.regression._
 import org.apache.spark.mllib.util.{LocalClusterSparkContext, MLlibTestSparkContext}
 import org.apache.spark.mllib.util.TestingUtils._
+import org.apache.spark.util.Utils
 
 object LogisticRegressionSuite {
 
@@ -481,20 +482,19 @@ class LogisticRegressionSuite extends FunSuite with MLlibTestSparkContext with M
     val tempDir = Utils.createTempDir()
     val path = tempDir.toURI.toString
 
-    // Save model
+    // Save model, load it back, and compare.
     model.save(sc, path)
     val sameModel = LogisticRegressionModel.load(sc, path)
     assert(model.weights == sameModel.weights)
     assert(model.intercept == sameModel.intercept)
     assert(sameModel.getThreshold.isEmpty)
     Utils.deleteRecursively(tempDir)
 
-    // Save model with threshold
+    // Save model with threshold.
     model.setThreshold(0.7)
     model.save(sc, path)
     val sameModel2 = LogisticRegressionModel.load(sc, path)
     assert(model.getThreshold.get == sameModel2.getThreshold.get)
-
     Utils.deleteRecursively(tempDir)
   }