@@ -36,6 +36,44 @@ object MimaExcludes {
3636
3737 // Exclude rules for 3.0.x
3838 lazy val v30excludes = v24excludes ++ Seq (
39+ // [SPARK-21708][BUILD] Migrate build to sbt 1.x
40+ // mima plugin update caused new incompatibilities to be detected
41+ // core module
42+ // TODO(lmartini): this group was originally on top of 3.1 but applied on 3.0 because we picked the above commit
43+ // on top of 3.0
44+ ProblemFilters .exclude[IncompatibleResultTypeProblem ](" org.apache.spark.shuffle.sort.io.LocalDiskShuffleMapOutputWriter.commitAllPartitions" ),
45+ ProblemFilters .exclude[IncompatibleResultTypeProblem ](" org.apache.spark.shuffle.api.ShuffleMapOutputWriter.commitAllPartitions" ),
46+ ProblemFilters .exclude[ReversedMissingMethodProblem ](" org.apache.spark.shuffle.api.ShuffleMapOutputWriter.commitAllPartitions" ),
47+ // mllib module
48+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionTrainingSummary.totalIterations" ),
49+ ProblemFilters .exclude[DirectMissingMethodProblem ](" org.apache.spark.ml.classification.LogisticRegressionTrainingSummary.$init$" ),
50+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.labels" ),
51+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.truePositiveRateByLabel" ),
52+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.falsePositiveRateByLabel" ),
53+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.precisionByLabel" ),
54+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.recallByLabel" ),
55+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.fMeasureByLabel" ),
56+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.fMeasureByLabel" ),
57+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.accuracy" ),
58+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.weightedTruePositiveRate" ),
59+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.weightedFalsePositiveRate" ),
60+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.weightedRecall" ),
61+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.weightedPrecision" ),
62+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.weightedFMeasure" ),
63+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.LogisticRegressionSummary.weightedFMeasure" ),
64+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.BinaryLogisticRegressionSummary.roc" ),
65+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.BinaryLogisticRegressionSummary.areaUnderROC" ),
66+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.BinaryLogisticRegressionSummary.pr" ),
67+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.BinaryLogisticRegressionSummary.fMeasureByThreshold" ),
68+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.BinaryLogisticRegressionSummary.precisionByThreshold" ),
69+ ProblemFilters .exclude[NewMixinForwarderProblem ](" org.apache.spark.ml.classification.BinaryLogisticRegressionSummary.recallByThreshold" ),
70+ ProblemFilters .exclude[IncompatibleResultTypeProblem ](" org.apache.spark.ml.classification.FMClassifier.trainImpl" ),
71+ ProblemFilters .exclude[IncompatibleResultTypeProblem ](" org.apache.spark.ml.regression.FMRegressor.trainImpl" ),
72+ // TODO(lmartini): Additional excludes not in upstream but unique to palantir fork
73+ ProblemFilters .exclude[DirectMissingMethodProblem ](" org.apache.spark.SparkContext.initializeForcefully" ),
74+ ProblemFilters .exclude[DirectMissingMethodProblem ](" org.apache.spark.SparkContext.initializeForcefully" ),
75+ ProblemFilters .exclude[DirectMissingMethodProblem ](" org.apache.spark.broadcast.Broadcast.initializeForcefully" ),
76+
3977 // [SPARK-23429][CORE] Add executor memory metrics to heartbeat and expose in executors REST API
4078 ProblemFilters .exclude[DirectMissingMethodProblem ](" org.apache.spark.scheduler.SparkListenerExecutorMetricsUpdate.apply" ),
4179 ProblemFilters .exclude[DirectMissingMethodProblem ](" org.apache.spark.scheduler.SparkListenerExecutorMetricsUpdate.copy" ),
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