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new 25bcf59 [SPARK-25838][ML] Remove formatVersion from Saveable
25bcf59 is described below
commit 25bcf59b3b566b77bfc8a40a4f4253b81f340aa4
Author: Marco Gaido <marcogaid...@gmail.com>
AuthorDate: Sat Mar 9 09:44:20 2019 -0600
[SPARK-25838][ML] Remove formatVersion from Saveable
## What changes were proposed in this pull request?
`Saveable` interface introduces `formatVersion` which is protected and it
is used nowhere. So the PR proposes to remove it.
## How was this patch tested?
existing tests
Closes #22830 from mgaido91/SPARK-25838.
Authored-by: Marco Gaido <marcogaid...@gmail.com>
Signed-off-by: Sean Owen <sean.o...@databricks.com>
---
.../mllib/classification/LogisticRegression.scala | 2 --
.../spark/mllib/classification/NaiveBayes.scala | 2 --
.../org/apache/spark/mllib/classification/SVM.scala | 2 --
.../mllib/clustering/BisectingKMeansModel.scala | 2 --
.../mllib/clustering/GaussianMixtureModel.scala | 2 --
.../apache/spark/mllib/clustering/KMeansModel.scala | 2 --
.../apache/spark/mllib/clustering/LDAModel.scala | 4 ----
.../mllib/clustering/PowerIterationClustering.scala | 2 --
.../apache/spark/mllib/feature/ChiSqSelector.scala | 2 --
.../org/apache/spark/mllib/feature/Word2Vec.scala | 2 --
.../scala/org/apache/spark/mllib/fpm/FPGrowth.scala | 2 --
.../org/apache/spark/mllib/fpm/PrefixSpan.scala | 2 --
.../recommendation/MatrixFactorizationModel.scala | 2 --
.../spark/mllib/regression/IsotonicRegression.scala | 2 --
.../org/apache/spark/mllib/regression/Lasso.scala | 2 --
.../spark/mllib/regression/LinearRegression.scala | 2 --
.../spark/mllib/regression/RidgeRegression.scala | 2 --
.../spark/mllib/tree/model/DecisionTreeModel.scala | 4 ----
.../spark/mllib/tree/model/treeEnsembleModels.scala | 8 --------
.../org/apache/spark/mllib/util/modelSaveLoad.scala | 3 ---
project/MimaExcludes.scala | 21 +++++++++++++++++++++
21 files changed, 21 insertions(+), 51 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
index 4b65000..d86aa01 100644
---
a/mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala
+++
b/mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala
@@ -163,8 +163,6 @@ class LogisticRegressionModel @Since("1.3.0") (
numFeatures, numClasses, weights, intercept, threshold)
}
- override protected def formatVersion: String = "1.0"
-
override def toString: String = {
s"${super.toString}, numClasses = ${numClasses}, threshold =
${threshold.getOrElse("None")}"
}
diff --git
a/mllib/src/main/scala/org/apache/spark/mllib/classification/NaiveBayes.scala
b/mllib/src/main/scala/org/apache/spark/mllib/classification/NaiveBayes.scala
index 16ba6ca..79bb4ad 100644
---
a/mllib/src/main/scala/org/apache/spark/mllib/classification/NaiveBayes.scala
+++
b/mllib/src/main/scala/org/apache/spark/mllib/classification/NaiveBayes.scala
@@ -170,8 +170,6 @@ class NaiveBayesModel private[spark] (
val data = NaiveBayesModel.SaveLoadV2_0.Data(labels, pi, theta, modelType)
NaiveBayesModel.SaveLoadV2_0.save(sc, path, data)
}
-
- override protected def formatVersion: String = "2.0"
}
@Since("1.3.0")
diff --git
a/mllib/src/main/scala/org/apache/spark/mllib/classification/SVM.scala
b/mllib/src/main/scala/org/apache/spark/mllib/classification/SVM.scala
index 5fb04ed..087c2c2 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/classification/SVM.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/classification/SVM.scala
@@ -85,8 +85,6 @@ class SVMModel @Since("1.1.0") (
numFeatures = weights.size, numClasses = 2, weights, intercept,
threshold)
}
- override protected def formatVersion: String = "1.0"
-
override def toString: String = {
s"${super.toString}, numClasses = 2, threshold =
${threshold.getOrElse("None")}"
}
diff --git
a/mllib/src/main/scala/org/apache/spark/mllib/clustering/BisectingKMeansModel.scala
b/mllib/src/main/scala/org/apache/spark/mllib/clustering/BisectingKMeansModel.scala
index b54b891..c397911 100644
---
a/mllib/src/main/scala/org/apache/spark/mllib/clustering/BisectingKMeansModel.scala
+++
b/mllib/src/main/scala/org/apache/spark/mllib/clustering/BisectingKMeansModel.scala
@@ -112,8 +112,6 @@ class BisectingKMeansModel private[clustering] (
override def save(sc: SparkContext, path: String): Unit = {
BisectingKMeansModel.SaveLoadV3_0.save(sc, this, path)
}
-
- override protected def formatVersion: String = "3.0"
}
@Since("2.0.0")
diff --git
a/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureModel.scala
b/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureModel.scala
index 1933d54..5d2ecf3 100644
---
a/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureModel.scala
+++
b/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureModel.scala
@@ -48,8 +48,6 @@ class GaussianMixtureModel @Since("1.3.0") (
require(weights.length == gaussians.length, "Length of weight and Gaussian
arrays must match")
- override protected def formatVersion = "1.0"
-
@Since("1.4.0")
override def save(sc: SparkContext, path: String): Unit = {
GaussianMixtureModel.SaveLoadV1_0.save(sc, path, weights, gaussians)
diff --git
a/mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeansModel.scala
b/mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeansModel.scala
index 32a0bff..09c38f7 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeansModel.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeansModel.scala
@@ -112,8 +112,6 @@ class KMeansModel (@Since("1.0.0") val clusterCenters:
Array[Vector],
override def save(sc: SparkContext, path: String): Unit = {
KMeansModel.SaveLoadV2_0.save(sc, this, path)
}
-
- override protected def formatVersion: String = "2.0"
}
@Since("1.4.0")
diff --git
a/mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAModel.scala
b/mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAModel.scala
index fc0469c..91bc01c 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAModel.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAModel.scala
@@ -216,8 +216,6 @@ class LocalLDAModel private[spark] (
}.toArray
}
- override protected def formatVersion = "1.0"
-
/**
* Random seed for cluster initialization.
*/
@@ -835,8 +833,6 @@ class DistributedLDAModel private[clustering] (
// TODO:
// override def topicDistributions(documents: RDD[(Long, Vector)]):
RDD[(Long, Vector)] = ???
- override protected def formatVersion = "1.0"
-
@Since("1.5.0")
override def save(sc: SparkContext, path: String): Unit = {
// Note: This intentionally does not save checkpointFiles.
diff --git
a/mllib/src/main/scala/org/apache/spark/mllib/clustering/PowerIterationClustering.scala
b/mllib/src/main/scala/org/apache/spark/mllib/clustering/PowerIterationClustering.scala
index 765f272..48172f0 100644
---
a/mllib/src/main/scala/org/apache/spark/mllib/clustering/PowerIterationClustering.scala
+++
b/mllib/src/main/scala/org/apache/spark/mllib/clustering/PowerIterationClustering.scala
@@ -48,8 +48,6 @@ class PowerIterationClusteringModel @Since("1.3.0") (
override def save(sc: SparkContext, path: String): Unit = {
PowerIterationClusteringModel.SaveLoadV1_0.save(sc, this, path)
}
-
- override protected def formatVersion: String = "1.0"
}
@Since("1.4.0")
diff --git
a/mllib/src/main/scala/org/apache/spark/mllib/feature/ChiSqSelector.scala
b/mllib/src/main/scala/org/apache/spark/mllib/feature/ChiSqSelector.scala
index aa78e91..fc0a45c 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/feature/ChiSqSelector.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/feature/ChiSqSelector.scala
@@ -113,8 +113,6 @@ class ChiSqSelectorModel @Since("1.3.0") (
override def save(sc: SparkContext, path: String): Unit = {
ChiSqSelectorModel.SaveLoadV1_0.save(sc, this, path)
}
-
- override protected def formatVersion: String = "1.0"
}
object ChiSqSelectorModel extends Loader[ChiSqSelectorModel] {
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/feature/Word2Vec.scala
b/mllib/src/main/scala/org/apache/spark/mllib/feature/Word2Vec.scala
index 9cdade1..94c4fcc 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/feature/Word2Vec.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/feature/Word2Vec.scala
@@ -511,8 +511,6 @@ class Word2VecModel private[spark] (
this(Word2VecModel.buildWordIndex(model),
Word2VecModel.buildWordVectors(model))
}
- override protected def formatVersion = "1.0"
-
@Since("1.4.0")
def save(sc: SparkContext, path: String): Unit = {
Word2VecModel.SaveLoadV1_0.save(sc, path, getVectors)
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/fpm/FPGrowth.scala
b/mllib/src/main/scala/org/apache/spark/mllib/fpm/FPGrowth.scala
index 519c1ea..3531822 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/fpm/FPGrowth.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/fpm/FPGrowth.scala
@@ -84,8 +84,6 @@ class FPGrowthModel[Item: ClassTag] @Since("2.4.0") (
override def save(sc: SparkContext, path: String): Unit = {
FPGrowthModel.SaveLoadV1_0.save(this, path)
}
-
- override protected val formatVersion: String = "1.0"
}
@Since("2.0.0")
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/fpm/PrefixSpan.scala
b/mllib/src/main/scala/org/apache/spark/mllib/fpm/PrefixSpan.scala
index 55c2dc7..69e4b76 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/fpm/PrefixSpan.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/fpm/PrefixSpan.scala
@@ -628,8 +628,6 @@ class PrefixSpanModel[Item] @Since("1.5.0") (
override def save(sc: SparkContext, path: String): Unit = {
PrefixSpanModel.SaveLoadV1_0.save(this, path)
}
-
- override protected val formatVersion: String = "1.0"
}
@Since("2.0.0")
diff --git
a/mllib/src/main/scala/org/apache/spark/mllib/recommendation/MatrixFactorizationModel.scala
b/mllib/src/main/scala/org/apache/spark/mllib/recommendation/MatrixFactorizationModel.scala
index 7b49d4d..e5e82d1 100644
---
a/mllib/src/main/scala/org/apache/spark/mllib/recommendation/MatrixFactorizationModel.scala
+++
b/mllib/src/main/scala/org/apache/spark/mllib/recommendation/MatrixFactorizationModel.scala
@@ -196,8 +196,6 @@ class MatrixFactorizationModel @Since("0.8.0") (
.map(t => Rating(t._1, product, t._2))
}
- protected override val formatVersion: String = "1.0"
-
/**
* Save this model to the given path.
*
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 8347cca..649f981 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
@@ -160,8 +160,6 @@ class IsotonicRegressionModel @Since("1.3.0") (
override def save(sc: SparkContext, path: String): Unit = {
IsotonicRegressionModel.SaveLoadV1_0.save(sc, path, boundaries,
predictions, isotonic)
}
-
- override protected def formatVersion: String = "1.0"
}
@Since("1.4.0")
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/regression/Lasso.scala
b/mllib/src/main/scala/org/apache/spark/mllib/regression/Lasso.scala
index cef1b4f..ead9f5b 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/regression/Lasso.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/regression/Lasso.scala
@@ -51,8 +51,6 @@ class LassoModel @Since("1.1.0") (
override def save(sc: SparkContext, path: String): Unit = {
GLMRegressionModel.SaveLoadV1_0.save(sc, path, this.getClass.getName,
weights, intercept)
}
-
- override protected def formatVersion: String = "1.0"
}
@Since("1.3.0")
diff --git
a/mllib/src/main/scala/org/apache/spark/mllib/regression/LinearRegression.scala
b/mllib/src/main/scala/org/apache/spark/mllib/regression/LinearRegression.scala
index 60262fd..cb08216 100644
---
a/mllib/src/main/scala/org/apache/spark/mllib/regression/LinearRegression.scala
+++
b/mllib/src/main/scala/org/apache/spark/mllib/regression/LinearRegression.scala
@@ -51,8 +51,6 @@ class LinearRegressionModel @Since("1.1.0") (
override def save(sc: SparkContext, path: String): Unit = {
GLMRegressionModel.SaveLoadV1_0.save(sc, path, this.getClass.getName,
weights, intercept)
}
-
- override protected def formatVersion: String = "1.0"
}
@Since("1.3.0")
diff --git
a/mllib/src/main/scala/org/apache/spark/mllib/regression/RidgeRegression.scala
b/mllib/src/main/scala/org/apache/spark/mllib/regression/RidgeRegression.scala
index 52977ac..43c3154 100644
---
a/mllib/src/main/scala/org/apache/spark/mllib/regression/RidgeRegression.scala
+++
b/mllib/src/main/scala/org/apache/spark/mllib/regression/RidgeRegression.scala
@@ -52,8 +52,6 @@ class RidgeRegressionModel @Since("1.1.0") (
override def save(sc: SparkContext, path: String): Unit = {
GLMRegressionModel.SaveLoadV1_0.save(sc, path, this.getClass.getName,
weights, intercept)
}
-
- override protected def formatVersion: String = "1.0"
}
@Since("1.3.0")
diff --git
a/mllib/src/main/scala/org/apache/spark/mllib/tree/model/DecisionTreeModel.scala
b/mllib/src/main/scala/org/apache/spark/mllib/tree/model/DecisionTreeModel.scala
index 27618e1..9983ca7 100644
---
a/mllib/src/main/scala/org/apache/spark/mllib/tree/model/DecisionTreeModel.scala
+++
b/mllib/src/main/scala/org/apache/spark/mllib/tree/model/DecisionTreeModel.scala
@@ -126,15 +126,11 @@ class DecisionTreeModel @Since("1.0.0") (
override def save(sc: SparkContext, path: String): Unit = {
DecisionTreeModel.SaveLoadV1_0.save(sc, path, this)
}
-
- override protected def formatVersion: String =
DecisionTreeModel.formatVersion
}
@Since("1.3.0")
object DecisionTreeModel extends Loader[DecisionTreeModel] with Logging {
- private[spark] def formatVersion: String = "1.0"
-
private[tree] object SaveLoadV1_0 {
def thisFormatVersion: String = "1.0"
diff --git
a/mllib/src/main/scala/org/apache/spark/mllib/tree/model/treeEnsembleModels.scala
b/mllib/src/main/scala/org/apache/spark/mllib/tree/model/treeEnsembleModels.scala
index fc1d412..810f528 100644
---
a/mllib/src/main/scala/org/apache/spark/mllib/tree/model/treeEnsembleModels.scala
+++
b/mllib/src/main/scala/org/apache/spark/mllib/tree/model/treeEnsembleModels.scala
@@ -66,15 +66,11 @@ class RandomForestModel @Since("1.2.0") (
TreeEnsembleModel.SaveLoadV1_0.save(sc, path, this,
RandomForestModel.SaveLoadV1_0.thisClassName)
}
-
- override protected def formatVersion: String =
RandomForestModel.formatVersion
}
@Since("1.3.0")
object RandomForestModel extends Loader[RandomForestModel] {
- private[mllib] def formatVersion: String =
TreeEnsembleModel.SaveLoadV1_0.thisFormatVersion
-
/**
*
* @param sc Spark context used for loading model files.
@@ -170,8 +166,6 @@ class GradientBoostedTreesModel @Since("1.2.0") (
broadcastTrees.destroy()
evaluation.toArray
}
-
- override protected def formatVersion: String =
GradientBoostedTreesModel.formatVersion
}
/**
@@ -235,8 +229,6 @@ object GradientBoostedTreesModel extends
Loader[GradientBoostedTreesModel] {
newPredError
}
- private[mllib] def formatVersion: String =
TreeEnsembleModel.SaveLoadV1_0.thisFormatVersion
-
/**
* @param sc Spark context used for loading model files.
* @param path Path specifying the directory to which the model was saved.
diff --git
a/mllib/src/main/scala/org/apache/spark/mllib/util/modelSaveLoad.scala
b/mllib/src/main/scala/org/apache/spark/mllib/util/modelSaveLoad.scala
index da0eb04..e8889bf 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/util/modelSaveLoad.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/util/modelSaveLoad.scala
@@ -54,9 +54,6 @@ trait Saveable {
@Since("1.3.0")
def save(sc: SparkContext, path: String): Unit
- /** Current version of model save/load format. */
- protected def formatVersion: String
-
}
/**
diff --git a/project/MimaExcludes.scala b/project/MimaExcludes.scala
index 5d5d01f..fdc5cf1 100644
--- a/project/MimaExcludes.scala
+++ b/project/MimaExcludes.scala
@@ -36,6 +36,27 @@ object MimaExcludes {
// Exclude rules for 3.0.x
lazy val v30excludes = v24excludes ++ Seq(
+ // [SPARK-25838] Remove formatVersion from Saveable
+
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.mllib.clustering.DistributedLDAModel.formatVersion"),
+
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.mllib.clustering.LocalLDAModel.formatVersion"),
+
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.mllib.clustering.BisectingKMeansModel.formatVersion"),
+
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.mllib.clustering.KMeansModel.formatVersion"),
+
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.mllib.clustering.PowerIterationClusteringModel.formatVersion"),
+
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.mllib.clustering.GaussianMixtureModel.formatVersion"),
+
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.mllib.recommendation.MatrixFactorizationModel.formatVersion"),
+
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.mllib.feature.ChiSqSelectorModel.formatVersion"),
+
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.mllib.feature.Word2VecModel.formatVersion"),
+
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.mllib.classification.SVMModel.formatVersion"),
+
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.mllib.classification.LogisticRegressionModel.formatVersion"),
+
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.mllib.classification.NaiveBayesModel.formatVersion"),
+
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.mllib.util.Saveable.formatVersion"),
+
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.mllib.fpm.FPGrowthModel.formatVersion"),
+
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.mllib.fpm.PrefixSpanModel.formatVersion"),
+
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.mllib.regression.IsotonicRegressionModel.formatVersion"),
+
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.mllib.regression.RidgeRegressionModel.formatVersion"),
+
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.mllib.regression.LassoModel.formatVersion"),
+
ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.mllib.regression.LinearRegressionModel.formatVersion"),
+
// [SPARK-26254][CORE] Extract Hive + Kafka dependencies from Core.
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.deploy.security.HiveDelegationTokenProvider"),
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