spark-commits mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From yli...@apache.org
Subject spark git commit: [SPARK-20606][ML] Revert "[] ML 2.2 QA: Remove deprecated methods for ML"
Date Thu, 11 May 2017 06:48:36 GMT
Repository: spark
Updated Branches:
  refs/heads/branch-2.2 3eb0ee06a -> 80a57fa90


[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.

(cherry picked from commit 0698e6c88ca11fdfd6e5498cab784cf6dbcdfacb)
Signed-off-by: Yanbo Liang <ybliang8@gmail.com>


Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/80a57fa9
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/80a57fa9
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/80a57fa9

Branch: refs/heads/branch-2.2
Commit: 80a57fa90be8dca4340345c09b4ea28fbf11a516
Parents: 3eb0ee0
Author: Yanbo Liang <ybliang8@gmail.com>
Authored: Thu May 11 14:48:13 2017 +0800
Committer: Yanbo Liang <ybliang8@gmail.com>
Committed: Thu May 11 14:48:26 2017 +0800

----------------------------------------------------------------------
 .../classification/DecisionTreeClassifier.scala |  18 ++--
 .../spark/ml/classification/GBTClassifier.scala |  24 ++---
 .../classification/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(-)
----------------------------------------------------------------------


http://git-wip-us.apache.org/repos/asf/spark/blob/80a57fa9/mllib/src/main/scala/org/apache/spark/ml/classification/DecisionTreeClassifier.scala
----------------------------------------------------------------------
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 5fb105c..9f60f08 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] =

http://git-wip-us.apache.org/repos/asf/spark/blob/80a57fa9/mllib/src/main/scala/org/apache/spark/ml/classification/GBTClassifier.scala
----------------------------------------------------------------------
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 263ed10..ade0960 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:
 

http://git-wip-us.apache.org/repos/asf/spark/blob/80a57fa9/mllib/src/main/scala/org/apache/spark/ml/classification/RandomForestClassifier.scala
----------------------------------------------------------------------
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 441cfda..ab4c235 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 = {

http://git-wip-us.apache.org/repos/asf/spark/blob/80a57fa9/mllib/src/main/scala/org/apache/spark/ml/regression/DecisionTreeRegressor.scala
----------------------------------------------------------------------
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 c2b0358..01c5cc1 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")

http://git-wip-us.apache.org/repos/asf/spark/blob/80a57fa9/mllib/src/main/scala/org/apache/spark/ml/regression/GBTRegressor.scala
----------------------------------------------------------------------
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 8d9b519..08d175c 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:
 

http://git-wip-us.apache.org/repos/asf/spark/blob/80a57fa9/mllib/src/main/scala/org/apache/spark/ml/regression/RandomForestRegressor.scala
----------------------------------------------------------------------
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 7b9ddf6..a58da50 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 = {

http://git-wip-us.apache.org/repos/asf/spark/blob/80a57fa9/mllib/src/main/scala/org/apache/spark/ml/tree/treeParams.scala
----------------------------------------------------------------------
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 5526d4d..cd1950b 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)
 }
@@ -381,6 +472,13 @@ private[ml] trait GBTParams extends TreeEnsembleParams with HasMaxIter
{
   // 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.
    * (default = 0.1)
@@ -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. */

http://git-wip-us.apache.org/repos/asf/spark/blob/80a57fa9/mllib/src/main/scala/org/apache/spark/ml/util/ReadWrite.scala
----------------------------------------------------------------------
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 f7e570f..a8b8003 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
@@ -43,6 +43,16 @@ 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.
    */
   @Since("2.0.0")
@@ -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)
 }
 
 /**

http://git-wip-us.apache.org/repos/asf/spark/blob/80a57fa9/project/MimaExcludes.scala
----------------------------------------------------------------------
diff --git a/project/MimaExcludes.scala b/project/MimaExcludes.scala
index 92e1bbe..feae76a 100644
--- a/project/MimaExcludes.scala
+++ b/project/MimaExcludes.scala
@@ -999,74 +999,6 @@ 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")
     )
   }
 

http://git-wip-us.apache.org/repos/asf/spark/blob/80a57fa9/python/pyspark/ml/util.py
----------------------------------------------------------------------
diff --git a/python/pyspark/ml/util.py b/python/pyspark/ml/util.py
index 688109a..02016f1 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)


---------------------------------------------------------------------
To unsubscribe, e-mail: commits-unsubscribe@spark.apache.org
For additional commands, e-mail: commits-help@spark.apache.org


Mime
View raw message