@@ -36,6 +36,44 @@ object MimaExcludes {
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// Exclude rules for 3.0.x
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lazy val v30excludes = v24excludes ++ Seq (
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+ // [SPARK-21708][BUILD] Migrate build to sbt 1.x
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+ // mima plugin update caused new incompatibilities to be detected
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+ // core module
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+ // TODO(lmartini): this group was originally on top of 3.1 but applied on 3.0 because we picked the above commit
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+ // on top of 3.0
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+ ProblemFilters .exclude[IncompatibleResultTypeProblem ](" org.apache.spark.shuffle.sort.io.LocalDiskShuffleMapOutputWriter.commitAllPartitions" ),
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+ ProblemFilters .exclude[IncompatibleResultTypeProblem ](" org.apache.spark.shuffle.api.ShuffleMapOutputWriter.commitAllPartitions" ),
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+ ProblemFilters .exclude[ReversedMissingMethodProblem ](" org.apache.spark.shuffle.api.ShuffleMapOutputWriter.commitAllPartitions" ),
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+ // mllib module
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+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionTrainingSummary.totalIterations" ),
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+ ProblemFilters .exclude[DirectMissingMethodProblem ](" org.apache.spark.ml.classification.LogisticRegressionTrainingSummary.$init$" ),
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+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.labels" ),
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+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.truePositiveRateByLabel" ),
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+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.falsePositiveRateByLabel" ),
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+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.precisionByLabel" ),
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+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.recallByLabel" ),
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+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.fMeasureByLabel" ),
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+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.fMeasureByLabel" ),
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+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.accuracy" ),
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+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.weightedTruePositiveRate" ),
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+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.weightedFalsePositiveRate" ),
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+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.weightedRecall" ),
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+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.weightedPrecision" ),
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+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.weightedFMeasure" ),
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+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.weightedFMeasure" ),
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+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.BinaryLogisticRegressionSummary.roc" ),
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+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.BinaryLogisticRegressionSummary.areaUnderROC" ),
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+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.BinaryLogisticRegressionSummary.pr" ),
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+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.BinaryLogisticRegressionSummary.fMeasureByThreshold" ),
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+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.BinaryLogisticRegressionSummary.precisionByThreshold" ),
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+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.BinaryLogisticRegressionSummary.recallByThreshold" ),
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+ ProblemFilters .exclude[IncompatibleResultTypeProblem ](" org.apache.spark.ml.classification.FMClassifier.trainImpl" ),
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+ ProblemFilters .exclude[IncompatibleResultTypeProblem ](" org.apache.spark.ml.regression.FMRegressor.trainImpl" ),
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+ // TODO(lmartini): Additional excludes not in upstream but unique to palantir fork
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+ ProblemFilters .exclude[DirectMissingMethodProblem ](" org.apache.spark.SparkContext.initializeForcefully" ),
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+ ProblemFilters .exclude[DirectMissingMethodProblem ](" org.apache.spark.SparkContext.initializeForcefully" ),
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+ ProblemFilters .exclude[DirectMissingMethodProblem ](" org.apache.spark.broadcast.Broadcast.initializeForcefully" ),
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+
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// [SPARK-23429][CORE] Add executor memory metrics to heartbeat and expose in executors REST API
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ProblemFilters .exclude[DirectMissingMethodProblem ](" org.apache.spark.scheduler.SparkListenerExecutorMetricsUpdate.apply" ),
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ProblemFilters .exclude[DirectMissingMethodProblem ](" org.apache.spark.scheduler.SparkListenerExecutorMetricsUpdate.copy" ),
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