From 0698e6c88ca11fdfd6e5498cab784cf6dbcdfacb Mon Sep 17 00:00:00 2001
From: Yanbo Liang <ybliang8@gmail.com>
Date: Thu, 11 May 2017 14:48:13 +0800
Subject: [PATCH] [SPARK-20606][ML] Revert "[] ML 2.2 QA: Remove deprecated
methods for ML"
This reverts commit b8733e0ad9f5a700f385e210450fd2c10137293e.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes #17944 from yanboliang/spark-20606-revert.
---
.../DecisionTreeClassifier.scala | 18 +--
.../ml/classification/GBTClassifier.scala | 24 ++--
.../RandomForestClassifier.scala | 24 ++--
.../ml/regression/DecisionTreeRegressor.scala | 18 +--
.../spark/ml/regression/GBTRegressor.scala | 24 ++--
.../ml/regression/RandomForestRegressor.scala | 24 ++--
.../org/apache/spark/ml/tree/treeParams.scala | 105 ++++++++++++++++++
.../org/apache/spark/ml/util/ReadWrite.scala | 16 +++
project/MimaExcludes.scala | 68 ------------
python/pyspark/ml/util.py | 32 ++++++
10 files changed, 219 insertions(+), 134 deletions(-)
diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/DecisionTreeClassifier.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/DecisionTreeClassifier.scala
index 5fb105c6af..9f60f0896e 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/classification/DecisionTreeClassifier.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/classification/DecisionTreeClassifier.scala
@@ -54,27 +54,27 @@ class DecisionTreeClassifier @Since("1.4.0") (
/** @group setParam */
@Since("1.4.0")
- def setMaxDepth(value: Int): this.type = set(maxDepth, value)
+ override def setMaxDepth(value: Int): this.type = set(maxDepth, value)
/** @group setParam */
@Since("1.4.0")
- def setMaxBins(value: Int): this.type = set(maxBins, value)
+ override def setMaxBins(value: Int): this.type = set(maxBins, value)
/** @group setParam */
@Since("1.4.0")
- def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value)
+ override def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value)
/** @group setParam */
@Since("1.4.0")
- def setMinInfoGain(value: Double): this.type = set(minInfoGain, value)
+ override def setMinInfoGain(value: Double): this.type = set(minInfoGain, value)
/** @group expertSetParam */
@Since("1.4.0")
- def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value)
+ override def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value)
/** @group expertSetParam */
@Since("1.4.0")
- def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value)
+ override def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value)
/**
* Specifies how often to checkpoint the cached node IDs.
@@ -86,15 +86,15 @@ class DecisionTreeClassifier @Since("1.4.0") (
* @group setParam
*/
@Since("1.4.0")
- def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value)
+ override def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value)
/** @group setParam */
@Since("1.4.0")
- def setImpurity(value: String): this.type = set(impurity, value)
+ override def setImpurity(value: String): this.type = set(impurity, value)
/** @group setParam */
@Since("1.6.0")
- def setSeed(value: Long): this.type = set(seed, value)
+ override def setSeed(value: Long): this.type = set(seed, value)
override protected def train(dataset: Dataset[_]): DecisionTreeClassificationModel = {
val categoricalFeatures: Map[Int, Int] =
diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/GBTClassifier.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/GBTClassifier.scala
index 263ed10f19..ade0960f87 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/classification/GBTClassifier.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/classification/GBTClassifier.scala
@@ -70,27 +70,27 @@ class GBTClassifier @Since("1.4.0") (
/** @group setParam */
@Since("1.4.0")
- def setMaxDepth(value: Int): this.type = set(maxDepth, value)
+ override def setMaxDepth(value: Int): this.type = set(maxDepth, value)
/** @group setParam */
@Since("1.4.0")
- def setMaxBins(value: Int): this.type = set(maxBins, value)
+ override def setMaxBins(value: Int): this.type = set(maxBins, value)
/** @group setParam */
@Since("1.4.0")
- def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value)
+ override def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value)
/** @group setParam */
@Since("1.4.0")
- def setMinInfoGain(value: Double): this.type = set(minInfoGain, value)
+ override def setMinInfoGain(value: Double): this.type = set(minInfoGain, value)
/** @group expertSetParam */
@Since("1.4.0")
- def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value)
+ override def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value)
/** @group expertSetParam */
@Since("1.4.0")
- def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value)
+ override def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value)
/**
* Specifies how often to checkpoint the cached node IDs.
@@ -102,7 +102,7 @@ class GBTClassifier @Since("1.4.0") (
* @group setParam
*/
@Since("1.4.0")
- def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value)
+ override def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value)
/**
* The impurity setting is ignored for GBT models.
@@ -111,7 +111,7 @@ class GBTClassifier @Since("1.4.0") (
* @group setParam
*/
@Since("1.4.0")
- def setImpurity(value: String): this.type = {
+ override def setImpurity(value: String): this.type = {
logWarning("GBTClassifier.setImpurity should NOT be used")
this
}
@@ -120,21 +120,21 @@ class GBTClassifier @Since("1.4.0") (
/** @group setParam */
@Since("1.4.0")
- def setSubsamplingRate(value: Double): this.type = set(subsamplingRate, value)
+ override def setSubsamplingRate(value: Double): this.type = set(subsamplingRate, value)
/** @group setParam */
@Since("1.4.0")
- def setSeed(value: Long): this.type = set(seed, value)
+ override def setSeed(value: Long): this.type = set(seed, value)
// Parameters from GBTParams:
/** @group setParam */
@Since("1.4.0")
- def setMaxIter(value: Int): this.type = set(maxIter, value)
+ override def setMaxIter(value: Int): this.type = set(maxIter, value)
/** @group setParam */
@Since("1.4.0")
- def setStepSize(value: Double): this.type = set(stepSize, value)
+ override def setStepSize(value: Double): this.type = set(stepSize, value)
// Parameters from GBTClassifierParams:
diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/RandomForestClassifier.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/RandomForestClassifier.scala
index 441cfda899..ab4c235209 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/classification/RandomForestClassifier.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/classification/RandomForestClassifier.scala
@@ -56,27 +56,27 @@ class RandomForestClassifier @Since("1.4.0") (
/** @group setParam */
@Since("1.4.0")
- def setMaxDepth(value: Int): this.type = set(maxDepth, value)
+ override def setMaxDepth(value: Int): this.type = set(maxDepth, value)
/** @group setParam */
@Since("1.4.0")
- def setMaxBins(value: Int): this.type = set(maxBins, value)
+ override def setMaxBins(value: Int): this.type = set(maxBins, value)
/** @group setParam */
@Since("1.4.0")
- def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value)
+ override def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value)
/** @group setParam */
@Since("1.4.0")
- def setMinInfoGain(value: Double): this.type = set(minInfoGain, value)
+ override def setMinInfoGain(value: Double): this.type = set(minInfoGain, value)
/** @group expertSetParam */
@Since("1.4.0")
- def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value)
+ override def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value)
/** @group expertSetParam */
@Since("1.4.0")
- def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value)
+ override def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value)
/**
* Specifies how often to checkpoint the cached node IDs.
@@ -88,31 +88,31 @@ class RandomForestClassifier @Since("1.4.0") (
* @group setParam
*/
@Since("1.4.0")
- def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value)
+ override def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value)
/** @group setParam */
@Since("1.4.0")
- def setImpurity(value: String): this.type = set(impurity, value)
+ override def setImpurity(value: String): this.type = set(impurity, value)
// Parameters from TreeEnsembleParams:
/** @group setParam */
@Since("1.4.0")
- def setSubsamplingRate(value: Double): this.type = set(subsamplingRate, value)
+ override def setSubsamplingRate(value: Double): this.type = set(subsamplingRate, value)
/** @group setParam */
@Since("1.4.0")
- def setSeed(value: Long): this.type = set(seed, value)
+ override def setSeed(value: Long): this.type = set(seed, value)
// Parameters from RandomForestParams:
/** @group setParam */
@Since("1.4.0")
- def setNumTrees(value: Int): this.type = set(numTrees, value)
+ override def setNumTrees(value: Int): this.type = set(numTrees, value)
/** @group setParam */
@Since("1.4.0")
- def setFeatureSubsetStrategy(value: String): this.type =
+ override def setFeatureSubsetStrategy(value: String): this.type =
set(featureSubsetStrategy, value)
override protected def train(dataset: Dataset[_]): RandomForestClassificationModel = {
diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/DecisionTreeRegressor.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/DecisionTreeRegressor.scala
index c2b0358e84..01c5cc1c7e 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/regression/DecisionTreeRegressor.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/regression/DecisionTreeRegressor.scala
@@ -53,27 +53,27 @@ class DecisionTreeRegressor @Since("1.4.0") (@Since("1.4.0") override val uid: S
// Override parameter setters from parent trait for Java API compatibility.
/** @group setParam */
@Since("1.4.0")
- def setMaxDepth(value: Int): this.type = set(maxDepth, value)
+ override def setMaxDepth(value: Int): this.type = set(maxDepth, value)
/** @group setParam */
@Since("1.4.0")
- def setMaxBins(value: Int): this.type = set(maxBins, value)
+ override def setMaxBins(value: Int): this.type = set(maxBins, value)
/** @group setParam */
@Since("1.4.0")
- def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value)
+ override def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value)
/** @group setParam */
@Since("1.4.0")
- def setMinInfoGain(value: Double): this.type = set(minInfoGain, value)
+ override def setMinInfoGain(value: Double): this.type = set(minInfoGain, value)
/** @group expertSetParam */
@Since("1.4.0")
- def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value)
+ override def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value)
/** @group expertSetParam */
@Since("1.4.0")
- def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value)
+ override def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value)
/**
* Specifies how often to checkpoint the cached node IDs.
@@ -85,15 +85,15 @@ class DecisionTreeRegressor @Since("1.4.0") (@Since("1.4.0") override val uid: S
* @group setParam
*/
@Since("1.4.0")
- def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value)
+ override def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value)
/** @group setParam */
@Since("1.4.0")
- def setImpurity(value: String): this.type = set(impurity, value)
+ override def setImpurity(value: String): this.type = set(impurity, value)
/** @group setParam */
@Since("1.6.0")
- def setSeed(value: Long): this.type = set(seed, value)
+ override def setSeed(value: Long): this.type = set(seed, value)
/** @group setParam */
@Since("2.0.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/GBTRegressor.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/GBTRegressor.scala
index 8d9b519efb..08d175cb94 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/regression/GBTRegressor.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/regression/GBTRegressor.scala
@@ -68,27 +68,27 @@ class GBTRegressor @Since("1.4.0") (@Since("1.4.0") override val uid: String)
/** @group setParam */
@Since("1.4.0")
- def setMaxDepth(value: Int): this.type = set(maxDepth, value)
+ override def setMaxDepth(value: Int): this.type = set(maxDepth, value)
/** @group setParam */
@Since("1.4.0")
- def setMaxBins(value: Int): this.type = set(maxBins, value)
+ override def setMaxBins(value: Int): this.type = set(maxBins, value)
/** @group setParam */
@Since("1.4.0")
- def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value)
+ override def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value)
/** @group setParam */
@Since("1.4.0")
- def setMinInfoGain(value: Double): this.type = set(minInfoGain, value)
+ override def setMinInfoGain(value: Double): this.type = set(minInfoGain, value)
/** @group expertSetParam */
@Since("1.4.0")
- def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value)
+ override def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value)
/** @group expertSetParam */
@Since("1.4.0")
- def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value)
+ override def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value)
/**
* Specifies how often to checkpoint the cached node IDs.
@@ -100,7 +100,7 @@ class GBTRegressor @Since("1.4.0") (@Since("1.4.0") override val uid: String)
* @group setParam
*/
@Since("1.4.0")
- def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value)
+ override def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value)
/**
* The impurity setting is ignored for GBT models.
@@ -109,7 +109,7 @@ class GBTRegressor @Since("1.4.0") (@Since("1.4.0") override val uid: String)
* @group setParam
*/
@Since("1.4.0")
- def setImpurity(value: String): this.type = {
+ override def setImpurity(value: String): this.type = {
logWarning("GBTRegressor.setImpurity should NOT be used")
this
}
@@ -118,21 +118,21 @@ class GBTRegressor @Since("1.4.0") (@Since("1.4.0") override val uid: String)
/** @group setParam */
@Since("1.4.0")
- def setSubsamplingRate(value: Double): this.type = set(subsamplingRate, value)
+ override def setSubsamplingRate(value: Double): this.type = set(subsamplingRate, value)
/** @group setParam */
@Since("1.4.0")
- def setSeed(value: Long): this.type = set(seed, value)
+ override def setSeed(value: Long): this.type = set(seed, value)
// Parameters from GBTParams:
/** @group setParam */
@Since("1.4.0")
- def setMaxIter(value: Int): this.type = set(maxIter, value)
+ override def setMaxIter(value: Int): this.type = set(maxIter, value)
/** @group setParam */
@Since("1.4.0")
- def setStepSize(value: Double): this.type = set(stepSize, value)
+ override def setStepSize(value: Double): this.type = set(stepSize, value)
// Parameters from GBTRegressorParams:
diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/RandomForestRegressor.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/RandomForestRegressor.scala
index 7b9ddf6e95..a58da50fad 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/regression/RandomForestRegressor.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/regression/RandomForestRegressor.scala
@@ -55,27 +55,27 @@ class RandomForestRegressor @Since("1.4.0") (@Since("1.4.0") override val uid: S
/** @group setParam */
@Since("1.4.0")
- def setMaxDepth(value: Int): this.type = set(maxDepth, value)
+ override def setMaxDepth(value: Int): this.type = set(maxDepth, value)
/** @group setParam */
@Since("1.4.0")
- def setMaxBins(value: Int): this.type = set(maxBins, value)
+ override def setMaxBins(value: Int): this.type = set(maxBins, value)
/** @group setParam */
@Since("1.4.0")
- def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value)
+ override def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value)
/** @group setParam */
@Since("1.4.0")
- def setMinInfoGain(value: Double): this.type = set(minInfoGain, value)
+ override def setMinInfoGain(value: Double): this.type = set(minInfoGain, value)
/** @group expertSetParam */
@Since("1.4.0")
- def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value)
+ override def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value)
/** @group expertSetParam */
@Since("1.4.0")
- def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value)
+ override def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value)
/**
* Specifies how often to checkpoint the cached node IDs.
@@ -87,31 +87,31 @@ class RandomForestRegressor @Since("1.4.0") (@Since("1.4.0") override val uid: S
* @group setParam
*/
@Since("1.4.0")
- def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value)
+ override def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value)
/** @group setParam */
@Since("1.4.0")
- def setImpurity(value: String): this.type = set(impurity, value)
+ override def setImpurity(value: String): this.type = set(impurity, value)
// Parameters from TreeEnsembleParams:
/** @group setParam */
@Since("1.4.0")
- def setSubsamplingRate(value: Double): this.type = set(subsamplingRate, value)
+ override def setSubsamplingRate(value: Double): this.type = set(subsamplingRate, value)
/** @group setParam */
@Since("1.4.0")
- def setSeed(value: Long): this.type = set(seed, value)
+ override def setSeed(value: Long): this.type = set(seed, value)
// Parameters from RandomForestParams:
/** @group setParam */
@Since("1.4.0")
- def setNumTrees(value: Int): this.type = set(numTrees, value)
+ override def setNumTrees(value: Int): this.type = set(numTrees, value)
/** @group setParam */
@Since("1.4.0")
- def setFeatureSubsetStrategy(value: String): this.type =
+ override def setFeatureSubsetStrategy(value: String): this.type =
set(featureSubsetStrategy, value)
override protected def train(dataset: Dataset[_]): RandomForestRegressionModel = {
diff --git a/mllib/src/main/scala/org/apache/spark/ml/tree/treeParams.scala b/mllib/src/main/scala/org/apache/spark/ml/tree/treeParams.scala
index 5526d4d75b..cd1950bd76 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/tree/treeParams.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/tree/treeParams.scala
@@ -109,24 +109,80 @@ private[ml] trait DecisionTreeParams extends PredictorParams
setDefault(maxDepth -> 5, maxBins -> 32, minInstancesPerNode -> 1, minInfoGain -> 0.0,
maxMemoryInMB -> 256, cacheNodeIds -> false, checkpointInterval -> 10)
+ /**
+ * @deprecated This method is deprecated and will be removed in 2.2.0.
+ * @group setParam
+ */
+ @deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
+ def setMaxDepth(value: Int): this.type = set(maxDepth, value)
+
/** @group getParam */
final def getMaxDepth: Int = $(maxDepth)
+ /**
+ * @deprecated This method is deprecated and will be removed in 2.2.0.
+ * @group setParam
+ */
+ @deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
+ def setMaxBins(value: Int): this.type = set(maxBins, value)
+
/** @group getParam */
final def getMaxBins: Int = $(maxBins)
+ /**
+ * @deprecated This method is deprecated and will be removed in 2.2.0.
+ * @group setParam
+ */
+ @deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
+ def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value)
+
/** @group getParam */
final def getMinInstancesPerNode: Int = $(minInstancesPerNode)
+ /**
+ * @deprecated This method is deprecated and will be removed in 2.2.0.
+ * @group setParam
+ */
+ @deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
+ def setMinInfoGain(value: Double): this.type = set(minInfoGain, value)
+
/** @group getParam */
final def getMinInfoGain: Double = $(minInfoGain)
+ /**
+ * @deprecated This method is deprecated and will be removed in 2.2.0.
+ * @group setParam
+ */
+ @deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
+ def setSeed(value: Long): this.type = set(seed, value)
+
+ /**
+ * @deprecated This method is deprecated and will be removed in 2.2.0.
+ * @group expertSetParam
+ */
+ @deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
+ def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value)
+
/** @group expertGetParam */
final def getMaxMemoryInMB: Int = $(maxMemoryInMB)
+ /**
+ * @deprecated This method is deprecated and will be removed in 2.2.0.
+ * @group expertSetParam
+ */
+ @deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
+ def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value)
+
/** @group expertGetParam */
final def getCacheNodeIds: Boolean = $(cacheNodeIds)
+ /**
+ * @deprecated This method is deprecated and will be removed in 2.2.0.
+ * @group setParam
+ */
+ @deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
+ def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value)
+
/** (private[ml]) Create a Strategy instance to use with the old API. */
private[ml] def getOldStrategy(
categoricalFeatures: Map[Int, Int],
@@ -169,6 +225,13 @@ private[ml] trait TreeClassifierParams extends Params {
setDefault(impurity -> "gini")
+ /**
+ * @deprecated This method is deprecated and will be removed in 2.2.0.
+ * @group setParam
+ */
+ @deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
+ def setImpurity(value: String): this.type = set(impurity, value)
+
/** @group getParam */
final def getImpurity: String = $(impurity).toLowerCase(Locale.ROOT)
@@ -213,6 +276,13 @@ private[ml] trait TreeRegressorParams extends Params {
setDefault(impurity -> "variance")
+ /**
+ * @deprecated This method is deprecated and will be removed in 2.2.0.
+ * @group setParam
+ */
+ @deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
+ def setImpurity(value: String): this.type = set(impurity, value)
+
/** @group getParam */
final def getImpurity: String = $(impurity).toLowerCase(Locale.ROOT)
@@ -268,6 +338,13 @@ private[ml] trait TreeEnsembleParams extends DecisionTreeParams {
setDefault(subsamplingRate -> 1.0)
+ /**
+ * @deprecated This method is deprecated and will be removed in 2.2.0.
+ * @group setParam
+ */
+ @deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
+ def setSubsamplingRate(value: Double): this.type = set(subsamplingRate, value)
+
/** @group getParam */
final def getSubsamplingRate: Double = $(subsamplingRate)
@@ -305,6 +382,13 @@ private[ml] trait RandomForestParams extends TreeEnsembleParams {
setDefault(numTrees -> 20)
+ /**
+ * @deprecated This method is deprecated and will be removed in 2.2.0.
+ * @group setParam
+ */
+ @deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
+ def setNumTrees(value: Int): this.type = set(numTrees, value)
+
/** @group getParam */
final def getNumTrees: Int = $(numTrees)
@@ -346,6 +430,13 @@ private[ml] trait RandomForestParams extends TreeEnsembleParams {
setDefault(featureSubsetStrategy -> "auto")
+ /**
+ * @deprecated This method is deprecated and will be removed in 2.2.0.
+ * @group setParam
+ */
+ @deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
+ def setFeatureSubsetStrategy(value: String): this.type = set(featureSubsetStrategy, value)
+
/** @group getParam */
final def getFeatureSubsetStrategy: String = $(featureSubsetStrategy).toLowerCase(Locale.ROOT)
}
@@ -380,6 +471,13 @@ private[ml] trait GBTParams extends TreeEnsembleParams with HasMaxIter {
// final val validationTol: DoubleParam = new DoubleParam(this, "validationTol", "")
// validationTol -> 1e-5
+ /**
+ * @deprecated This method is deprecated and will be removed in 2.2.0.
+ * @group setParam
+ */
+ @deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
+ def setMaxIter(value: Int): this.type = set(maxIter, value)
+
/**
* Param for Step size (a.k.a. learning rate) in interval (0, 1] for shrinking
* the contribution of each estimator.
@@ -393,6 +491,13 @@ private[ml] trait GBTParams extends TreeEnsembleParams with HasMaxIter {
/** @group getParam */
final def getStepSize: Double = $(stepSize)
+ /**
+ * @deprecated This method is deprecated and will be removed in 2.2.0.
+ * @group setParam
+ */
+ @deprecated("This method is deprecated and will be removed in 2.2.0.", "2.1.0")
+ def setStepSize(value: Double): this.type = set(stepSize, value)
+
setDefault(maxIter -> 20, stepSize -> 0.1)
/** (private[ml]) Create a BoostingStrategy instance to use with the old API. */
diff --git a/mllib/src/main/scala/org/apache/spark/ml/util/ReadWrite.scala b/mllib/src/main/scala/org/apache/spark/ml/util/ReadWrite.scala
index f7e570fd5c..a8b80031fa 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/util/ReadWrite.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/util/ReadWrite.scala
@@ -42,6 +42,16 @@ import org.apache.spark.util.Utils
private[util] sealed trait BaseReadWrite {
private var optionSparkSession: Option[SparkSession] = None
+ /**
+ * Sets the Spark SQLContext to use for saving/loading.
+ */
+ @Since("1.6.0")
+ @deprecated("Use session instead, This method will be removed in 2.2.0.", "2.0.0")
+ def context(sqlContext: SQLContext): this.type = {
+ optionSparkSession = Option(sqlContext.sparkSession)
+ this
+ }
+
/**
* Sets the Spark Session to use for saving/loading.
*/
@@ -120,6 +130,9 @@ abstract class MLWriter extends BaseReadWrite with Logging {
// override for Java compatibility
override def session(sparkSession: SparkSession): this.type = super.session(sparkSession)
+
+ // override for Java compatibility
+ override def context(sqlContext: SQLContext): this.type = super.session(sqlContext.sparkSession)
}
/**
@@ -175,6 +188,9 @@ abstract class MLReader[T] extends BaseReadWrite {
// override for Java compatibility
override def session(sparkSession: SparkSession): this.type = super.session(sparkSession)
+
+ // override for Java compatibility
+ override def context(sqlContext: SQLContext): this.type = super.session(sqlContext.sparkSession)
}
/**
diff --git a/project/MimaExcludes.scala b/project/MimaExcludes.scala
index 2dff154967..3cc089dced 100644
--- a/project/MimaExcludes.scala
+++ b/project/MimaExcludes.scala
@@ -1008,74 +1008,6 @@ object MimaExcludes {
ProblemFilters.exclude[IncompatibleResultTypeProblem]("org.apache.spark.ml.classification.RandomForestClassificationModel.setFeatureSubsetStrategy"),
ProblemFilters.exclude[IncompatibleResultTypeProblem]("org.apache.spark.ml.regression.RandomForestRegressionModel.numTrees"),
ProblemFilters.exclude[IncompatibleResultTypeProblem]("org.apache.spark.ml.regression.RandomForestRegressionModel.setFeatureSubsetStrategy")
- ) ++ Seq(
- // [SPARK-20606] ML 2.2 QA: Remove deprecated methods for ML
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.DecisionTreeClassificationModel.setSeed"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.DecisionTreeClassificationModel.setMinInfoGain"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.DecisionTreeClassificationModel.setCacheNodeIds"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.DecisionTreeClassificationModel.setCheckpointInterval"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.DecisionTreeClassificationModel.setMaxDepth"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.DecisionTreeClassificationModel.setImpurity"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.DecisionTreeClassificationModel.setMaxMemoryInMB"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.DecisionTreeClassificationModel.setMaxBins"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.DecisionTreeClassificationModel.setMinInstancesPerNode"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.GBTClassificationModel.setSeed"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.GBTClassificationModel.setMinInfoGain"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.GBTClassificationModel.setSubsamplingRate"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.GBTClassificationModel.setMaxIter"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.GBTClassificationModel.setCacheNodeIds"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.GBTClassificationModel.setCheckpointInterval"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.GBTClassificationModel.setMaxDepth"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.GBTClassificationModel.setImpurity"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.GBTClassificationModel.setMaxMemoryInMB"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.GBTClassificationModel.setStepSize"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.GBTClassificationModel.setMaxBins"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.GBTClassificationModel.setMinInstancesPerNode"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.RandomForestClassificationModel.setSeed"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.RandomForestClassificationModel.setMinInfoGain"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.RandomForestClassificationModel.setSubsamplingRate"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.RandomForestClassificationModel.setCacheNodeIds"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.RandomForestClassificationModel.setCheckpointInterval"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.RandomForestClassificationModel.setMaxDepth"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.RandomForestClassificationModel.setImpurity"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.RandomForestClassificationModel.setMaxMemoryInMB"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.RandomForestClassificationModel.setFeatureSubsetStrategy"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.RandomForestClassificationModel.setMaxBins"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.classification.RandomForestClassificationModel.setMinInstancesPerNode"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.DecisionTreeRegressionModel.setSeed"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.DecisionTreeRegressionModel.setMinInfoGain"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.DecisionTreeRegressionModel.setCacheNodeIds"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.DecisionTreeRegressionModel.setCheckpointInterval"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.DecisionTreeRegressionModel.setMaxDepth"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.DecisionTreeRegressionModel.setImpurity"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.DecisionTreeRegressionModel.setMaxMemoryInMB"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.DecisionTreeRegressionModel.setMaxBins"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.DecisionTreeRegressionModel.setMinInstancesPerNode"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.GBTRegressionModel.setSeed"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.GBTRegressionModel.setMinInfoGain"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.GBTRegressionModel.setSubsamplingRate"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.GBTRegressionModel.setMaxIter"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.GBTRegressionModel.setCacheNodeIds"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.GBTRegressionModel.setCheckpointInterval"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.GBTRegressionModel.setMaxDepth"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.GBTRegressionModel.setImpurity"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.GBTRegressionModel.setMaxMemoryInMB"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.GBTRegressionModel.setStepSize"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.GBTRegressionModel.setMaxBins"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.GBTRegressionModel.setMinInstancesPerNode"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.RandomForestRegressionModel.setSeed"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.RandomForestRegressionModel.setMinInfoGain"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.RandomForestRegressionModel.setSubsamplingRate"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.RandomForestRegressionModel.setCacheNodeIds"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.RandomForestRegressionModel.setCheckpointInterval"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.RandomForestRegressionModel.setMaxDepth"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.RandomForestRegressionModel.setImpurity"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.RandomForestRegressionModel.setMaxMemoryInMB"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.RandomForestRegressionModel.setFeatureSubsetStrategy"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.RandomForestRegressionModel.setMaxBins"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.regression.RandomForestRegressionModel.setMinInstancesPerNode"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.util.MLWriter.context"),
- ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.ml.util.MLReader.context")
)
}
diff --git a/python/pyspark/ml/util.py b/python/pyspark/ml/util.py
index 688109ab11..02016f172a 100644
--- a/python/pyspark/ml/util.py
+++ b/python/pyspark/ml/util.py
@@ -76,6 +76,13 @@ class MLWriter(object):
"""Overwrites if the output path already exists."""
raise NotImplementedError("MLWriter is not yet implemented for type: %s" % type(self))
+ def context(self, sqlContext):
+ """
+ Sets the SQL context to use for saving.
+ .. note:: Deprecated in 2.1 and will be removed in 2.2, use session instead.
+ """
+ raise NotImplementedError("MLWriter is not yet implemented for type: %s" % type(self))
+
def session(self, sparkSession):
"""Sets the Spark Session to use for saving."""
raise NotImplementedError("MLWriter is not yet implemented for type: %s" % type(self))
@@ -103,6 +110,15 @@ class JavaMLWriter(MLWriter):
self._jwrite.overwrite()
return self
+ def context(self, sqlContext):
+ """
+ Sets the SQL context to use for saving.
+ .. note:: Deprecated in 2.1 and will be removed in 2.2, use session instead.
+ """
+ warnings.warn("Deprecated in 2.1 and will be removed in 2.2, use session instead.")
+ self._jwrite.context(sqlContext._ssql_ctx)
+ return self
+
def session(self, sparkSession):
"""Sets the Spark Session to use for saving."""
self._jwrite.session(sparkSession._jsparkSession)
@@ -149,6 +165,13 @@ class MLReader(object):
"""Load the ML instance from the input path."""
raise NotImplementedError("MLReader is not yet implemented for type: %s" % type(self))
+ def context(self, sqlContext):
+ """
+ Sets the SQL context to use for loading.
+ .. note:: Deprecated in 2.1 and will be removed in 2.2, use session instead.
+ """
+ raise NotImplementedError("MLReader is not yet implemented for type: %s" % type(self))
+
def session(self, sparkSession):
"""Sets the Spark Session to use for loading."""
raise NotImplementedError("MLReader is not yet implemented for type: %s" % type(self))
@@ -174,6 +197,15 @@ class JavaMLReader(MLReader):
% self._clazz)
return self._clazz._from_java(java_obj)
+ def context(self, sqlContext):
+ """
+ Sets the SQL context to use for loading.
+ .. note:: Deprecated in 2.1 and will be removed in 2.2, use session instead.
+ """
+ warnings.warn("Deprecated in 2.1 and will be removed in 2.2, use session instead.")
+ self._jread.context(sqlContext._ssql_ctx)
+ return self
+
def session(self, sparkSession):
"""Sets the Spark Session to use for loading."""
self._jread.session(sparkSession._jsparkSession)
--
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