Repository: spark Updated Branches: refs/heads/branch-2.2 4bbfad44e -> 4b7aa0b1d
[SPARK-20606][ML] ML 2.2 QA: Remove deprecated methods for ML ## What changes were proposed in this pull request? Remove ML methods we deprecated in 2.1. ## How was this patch tested? Existing tests. Author: Yanbo Liang <[email protected]> Closes #17867 from yanboliang/spark-20606. (cherry picked from commit b8733e0ad9f5a700f385e210450fd2c10137293e) Signed-off-by: Yanbo Liang <[email protected]> Project: http://git-wip-us.apache.org/repos/asf/spark/repo Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/4b7aa0b1 Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/4b7aa0b1 Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/4b7aa0b1 Branch: refs/heads/branch-2.2 Commit: 4b7aa0b1dbd85e2238acba45e8f94c097358fb72 Parents: 4bbfad4 Author: Yanbo Liang <[email protected]> Authored: Tue May 9 17:30:37 2017 +0800 Committer: Yanbo Liang <[email protected]> Committed: Tue May 9 17:30:50 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, 134 insertions(+), 219 deletions(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/spark/blob/4b7aa0b1/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 9f60f08..5fb105c 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") - override def setMaxDepth(value: Int): this.type = set(maxDepth, value) + def setMaxDepth(value: Int): this.type = set(maxDepth, value) /** @group setParam */ @Since("1.4.0") - override def setMaxBins(value: Int): this.type = set(maxBins, value) + def setMaxBins(value: Int): this.type = set(maxBins, value) /** @group setParam */ @Since("1.4.0") - override def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value) + def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value) /** @group setParam */ @Since("1.4.0") - override def setMinInfoGain(value: Double): this.type = set(minInfoGain, value) + def setMinInfoGain(value: Double): this.type = set(minInfoGain, value) /** @group expertSetParam */ @Since("1.4.0") - override def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value) + def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value) /** @group expertSetParam */ @Since("1.4.0") - override def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value) + 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") - override def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value) + def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value) /** @group setParam */ @Since("1.4.0") - override def setImpurity(value: String): this.type = set(impurity, value) + def setImpurity(value: String): this.type = set(impurity, value) /** @group setParam */ @Since("1.6.0") - override def setSeed(value: Long): this.type = set(seed, value) + 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/4b7aa0b1/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 ade0960..263ed10 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") - override def setMaxDepth(value: Int): this.type = set(maxDepth, value) + def setMaxDepth(value: Int): this.type = set(maxDepth, value) /** @group setParam */ @Since("1.4.0") - override def setMaxBins(value: Int): this.type = set(maxBins, value) + def setMaxBins(value: Int): this.type = set(maxBins, value) /** @group setParam */ @Since("1.4.0") - override def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value) + def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value) /** @group setParam */ @Since("1.4.0") - override def setMinInfoGain(value: Double): this.type = set(minInfoGain, value) + def setMinInfoGain(value: Double): this.type = set(minInfoGain, value) /** @group expertSetParam */ @Since("1.4.0") - override def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value) + def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value) /** @group expertSetParam */ @Since("1.4.0") - override def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value) + 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") - override def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value) + 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") - override def setImpurity(value: String): this.type = { + 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") - override def setSubsamplingRate(value: Double): this.type = set(subsamplingRate, value) + def setSubsamplingRate(value: Double): this.type = set(subsamplingRate, value) /** @group setParam */ @Since("1.4.0") - override def setSeed(value: Long): this.type = set(seed, value) + def setSeed(value: Long): this.type = set(seed, value) // Parameters from GBTParams: /** @group setParam */ @Since("1.4.0") - override def setMaxIter(value: Int): this.type = set(maxIter, value) + def setMaxIter(value: Int): this.type = set(maxIter, value) /** @group setParam */ @Since("1.4.0") - override def setStepSize(value: Double): this.type = set(stepSize, value) + def setStepSize(value: Double): this.type = set(stepSize, value) // Parameters from GBTClassifierParams: http://git-wip-us.apache.org/repos/asf/spark/blob/4b7aa0b1/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 ab4c235..441cfda 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") - override def setMaxDepth(value: Int): this.type = set(maxDepth, value) + def setMaxDepth(value: Int): this.type = set(maxDepth, value) /** @group setParam */ @Since("1.4.0") - override def setMaxBins(value: Int): this.type = set(maxBins, value) + def setMaxBins(value: Int): this.type = set(maxBins, value) /** @group setParam */ @Since("1.4.0") - override def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value) + def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value) /** @group setParam */ @Since("1.4.0") - override def setMinInfoGain(value: Double): this.type = set(minInfoGain, value) + def setMinInfoGain(value: Double): this.type = set(minInfoGain, value) /** @group expertSetParam */ @Since("1.4.0") - override def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value) + def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value) /** @group expertSetParam */ @Since("1.4.0") - override def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value) + 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") - override def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value) + def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value) /** @group setParam */ @Since("1.4.0") - override def setImpurity(value: String): this.type = set(impurity, value) + def setImpurity(value: String): this.type = set(impurity, value) // Parameters from TreeEnsembleParams: /** @group setParam */ @Since("1.4.0") - override def setSubsamplingRate(value: Double): this.type = set(subsamplingRate, value) + def setSubsamplingRate(value: Double): this.type = set(subsamplingRate, value) /** @group setParam */ @Since("1.4.0") - override def setSeed(value: Long): this.type = set(seed, value) + def setSeed(value: Long): this.type = set(seed, value) // Parameters from RandomForestParams: /** @group setParam */ @Since("1.4.0") - override def setNumTrees(value: Int): this.type = set(numTrees, value) + def setNumTrees(value: Int): this.type = set(numTrees, value) /** @group setParam */ @Since("1.4.0") - override def setFeatureSubsetStrategy(value: String): this.type = + 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/4b7aa0b1/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 01c5cc1..c2b0358 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") - override def setMaxDepth(value: Int): this.type = set(maxDepth, value) + def setMaxDepth(value: Int): this.type = set(maxDepth, value) /** @group setParam */ @Since("1.4.0") - override def setMaxBins(value: Int): this.type = set(maxBins, value) + def setMaxBins(value: Int): this.type = set(maxBins, value) /** @group setParam */ @Since("1.4.0") - override def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value) + def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value) /** @group setParam */ @Since("1.4.0") - override def setMinInfoGain(value: Double): this.type = set(minInfoGain, value) + def setMinInfoGain(value: Double): this.type = set(minInfoGain, value) /** @group expertSetParam */ @Since("1.4.0") - override def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value) + def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value) /** @group expertSetParam */ @Since("1.4.0") - override def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value) + 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") - override def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value) + def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value) /** @group setParam */ @Since("1.4.0") - override def setImpurity(value: String): this.type = set(impurity, value) + def setImpurity(value: String): this.type = set(impurity, value) /** @group setParam */ @Since("1.6.0") - override def setSeed(value: Long): this.type = set(seed, value) + 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/4b7aa0b1/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 08d175c..8d9b519 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") - override def setMaxDepth(value: Int): this.type = set(maxDepth, value) + def setMaxDepth(value: Int): this.type = set(maxDepth, value) /** @group setParam */ @Since("1.4.0") - override def setMaxBins(value: Int): this.type = set(maxBins, value) + def setMaxBins(value: Int): this.type = set(maxBins, value) /** @group setParam */ @Since("1.4.0") - override def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value) + def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value) /** @group setParam */ @Since("1.4.0") - override def setMinInfoGain(value: Double): this.type = set(minInfoGain, value) + def setMinInfoGain(value: Double): this.type = set(minInfoGain, value) /** @group expertSetParam */ @Since("1.4.0") - override def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value) + def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value) /** @group expertSetParam */ @Since("1.4.0") - override def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value) + 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") - override def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value) + 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") - override def setImpurity(value: String): this.type = { + 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") - override def setSubsamplingRate(value: Double): this.type = set(subsamplingRate, value) + def setSubsamplingRate(value: Double): this.type = set(subsamplingRate, value) /** @group setParam */ @Since("1.4.0") - override def setSeed(value: Long): this.type = set(seed, value) + def setSeed(value: Long): this.type = set(seed, value) // Parameters from GBTParams: /** @group setParam */ @Since("1.4.0") - override def setMaxIter(value: Int): this.type = set(maxIter, value) + def setMaxIter(value: Int): this.type = set(maxIter, value) /** @group setParam */ @Since("1.4.0") - override def setStepSize(value: Double): this.type = set(stepSize, value) + def setStepSize(value: Double): this.type = set(stepSize, value) // Parameters from GBTRegressorParams: http://git-wip-us.apache.org/repos/asf/spark/blob/4b7aa0b1/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 a58da50..7b9ddf6 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") - override def setMaxDepth(value: Int): this.type = set(maxDepth, value) + def setMaxDepth(value: Int): this.type = set(maxDepth, value) /** @group setParam */ @Since("1.4.0") - override def setMaxBins(value: Int): this.type = set(maxBins, value) + def setMaxBins(value: Int): this.type = set(maxBins, value) /** @group setParam */ @Since("1.4.0") - override def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value) + def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value) /** @group setParam */ @Since("1.4.0") - override def setMinInfoGain(value: Double): this.type = set(minInfoGain, value) + def setMinInfoGain(value: Double): this.type = set(minInfoGain, value) /** @group expertSetParam */ @Since("1.4.0") - override def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value) + def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value) /** @group expertSetParam */ @Since("1.4.0") - override def setCacheNodeIds(value: Boolean): this.type = set(cacheNodeIds, value) + 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") - override def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value) + def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value) /** @group setParam */ @Since("1.4.0") - override def setImpurity(value: String): this.type = set(impurity, value) + def setImpurity(value: String): this.type = set(impurity, value) // Parameters from TreeEnsembleParams: /** @group setParam */ @Since("1.4.0") - override def setSubsamplingRate(value: Double): this.type = set(subsamplingRate, value) + def setSubsamplingRate(value: Double): this.type = set(subsamplingRate, value) /** @group setParam */ @Since("1.4.0") - override def setSeed(value: Long): this.type = set(seed, value) + def setSeed(value: Long): this.type = set(seed, value) // Parameters from RandomForestParams: /** @group setParam */ @Since("1.4.0") - override def setNumTrees(value: Int): this.type = set(numTrees, value) + def setNumTrees(value: Int): this.type = set(numTrees, value) /** @group setParam */ @Since("1.4.0") - override def setFeatureSubsetStrategy(value: String): this.type = + 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/4b7aa0b1/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 cd1950b..5526d4d 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 @@ -109,80 +109,24 @@ 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], @@ -225,13 +169,6 @@ 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) @@ -276,13 +213,6 @@ 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) @@ -338,13 +268,6 @@ 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) @@ -382,13 +305,6 @@ 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) @@ -430,13 +346,6 @@ 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) } @@ -472,13 +381,6 @@ 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) @@ -491,13 +393,6 @@ 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/4b7aa0b1/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 a8b8003..f7e570f 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 @@ -43,16 +43,6 @@ 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") @@ -130,9 +120,6 @@ 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) } /** @@ -188,9 +175,6 @@ 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/4b7aa0b1/project/MimaExcludes.scala ---------------------------------------------------------------------- diff --git a/project/MimaExcludes.scala b/project/MimaExcludes.scala index feae76a..92e1bbe 100644 --- a/project/MimaExcludes.scala +++ b/project/MimaExcludes.scala @@ -999,6 +999,74 @@ 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/4b7aa0b1/python/pyspark/ml/util.py ---------------------------------------------------------------------- diff --git a/python/pyspark/ml/util.py b/python/pyspark/ml/util.py index 02016f1..688109a 100644 --- a/python/pyspark/ml/util.py +++ b/python/pyspark/ml/util.py @@ -76,13 +76,6 @@ 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)) @@ -110,15 +103,6 @@ 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) @@ -165,13 +149,6 @@ 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)) @@ -197,15 +174,6 @@ 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: [email protected] For additional commands, e-mail: [email protected]
