From 9b763329d968658d2dedee4485b7931646e6392e Mon Sep 17 00:00:00 2001 From: Prashant Sharma Date: Wed, 23 Jul 2014 17:12:28 -0700 Subject: [PATCH] [SPARK-2549] Functions defined inside of other functions trigger failures Author: Prashant Sharma Closes #1510 from ScrapCodes/SPARK-2549/fun-in-fun and squashes the following commits: 9458bc5 [Prashant Sharma] Tested by removing an inner function from excludes. bc03b1c [Prashant Sharma] SPARK-2549 Functions defined inside of other functions trigger failures --- project/MimaExcludes.scala | 183 ++++++++---------- .../spark/tools/GenerateMIMAIgnore.scala | 21 +- 2 files changed, 98 insertions(+), 106 deletions(-) diff --git a/project/MimaExcludes.scala b/project/MimaExcludes.scala index 5e5ddd227aab6..e9220db6b1f9a 100644 --- a/project/MimaExcludes.scala +++ b/project/MimaExcludes.scala @@ -32,108 +32,83 @@ import com.typesafe.tools.mima.core._ */ object MimaExcludes { - def excludes(version: String) = version match { - case v if v.startsWith("1.1") => - Seq( - MimaBuild.excludeSparkPackage("deploy"), - MimaBuild.excludeSparkPackage("graphx") - ) ++ - closures.map(method => ProblemFilters.exclude[MissingMethodProblem](method)) ++ - Seq( - // Adding new method to JavaRDLike trait - we should probably mark this as a developer API. - ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.api.java.JavaRDDLike.partitions"), - // We made a mistake earlier (ed06500d3) in the Java API to use default parameter values - // for countApproxDistinct* functions, which does not work in Java. We later removed - // them, and use the following to tell Mima to not care about them. - ProblemFilters.exclude[IncompatibleResultTypeProblem]( - "org.apache.spark.api.java.JavaPairRDD.countApproxDistinctByKey"), - ProblemFilters.exclude[IncompatibleResultTypeProblem]( - "org.apache.spark.api.java.JavaPairRDD.countApproxDistinctByKey"), - ProblemFilters.exclude[MissingMethodProblem]( - "org.apache.spark.api.java.JavaPairRDD.countApproxDistinct$default$1"), - ProblemFilters.exclude[MissingMethodProblem]( - "org.apache.spark.api.java.JavaPairRDD.countApproxDistinctByKey$default$1"), - ProblemFilters.exclude[MissingMethodProblem]( - "org.apache.spark.api.java.JavaRDD.countApproxDistinct$default$1"), - ProblemFilters.exclude[MissingMethodProblem]( - "org.apache.spark.api.java.JavaRDDLike.countApproxDistinct$default$1"), - ProblemFilters.exclude[MissingMethodProblem]( - "org.apache.spark.api.java.JavaDoubleRDD.countApproxDistinct$default$1"), - ProblemFilters.exclude[MissingMethodProblem]( - "org.apache.spark.storage.MemoryStore.Entry"), - ProblemFilters.exclude[MissingMethodProblem]( - "org.apache.spark.rdd.RDD.org$apache$spark$rdd$RDD$$debugChildren$1"), - ProblemFilters.exclude[MissingMethodProblem]( - "org.apache.spark.rdd.RDD.org$apache$spark$rdd$RDD$$firstDebugString$1"), - ProblemFilters.exclude[MissingMethodProblem]( - "org.apache.spark.rdd.RDD.org$apache$spark$rdd$RDD$$shuffleDebugString$1"), - ProblemFilters.exclude[MissingMethodProblem]( - "org.apache.spark.rdd.RDD.org$apache$spark$rdd$RDD$$debugString$1"), - ProblemFilters.exclude[MissingMethodProblem]( - "org.apache.spark.rdd.PairRDDFunctions.org$apache$spark$rdd$PairRDDFunctions$$" - + "createZero$1") - ) ++ - Seq( - ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.streaming.flume.FlumeReceiver.this") - ) ++ - Seq( // Ignore some private methods in ALS. - ProblemFilters.exclude[MissingMethodProblem]( - "org.apache.spark.mllib.recommendation.ALS.org$apache$spark$mllib$recommendation$ALS$^dateFeatures"), - ProblemFilters.exclude[MissingMethodProblem]( // The only public constructor is the one without arguments. - "org.apache.spark.mllib.recommendation.ALS.this"), - ProblemFilters.exclude[MissingMethodProblem]( - "org.apache.spark.mllib.recommendation.ALS.org$apache$spark$mllib$recommendation$ALS$$$default$7"), - ProblemFilters.exclude[IncompatibleMethTypeProblem]( - "org.apache.spark.mllib.recommendation.ALS.org$apache$spark$mllib$recommendation$ALS$^dateFeatures") - ) ++ - MimaBuild.excludeSparkClass("mllib.linalg.distributed.ColumnStatisticsAggregator") ++ - MimaBuild.excludeSparkClass("rdd.ZippedRDD") ++ - MimaBuild.excludeSparkClass("rdd.ZippedPartition") ++ - MimaBuild.excludeSparkClass("util.SerializableHyperLogLog") ++ - MimaBuild.excludeSparkClass("storage.Values") ++ - MimaBuild.excludeSparkClass("storage.Entry") ++ - MimaBuild.excludeSparkClass("storage.MemoryStore$Entry") ++ - Seq( - ProblemFilters.exclude[IncompatibleMethTypeProblem]( - "org.apache.spark.mllib.tree.impurity.Gini.calculate"), - ProblemFilters.exclude[IncompatibleMethTypeProblem]( - "org.apache.spark.mllib.tree.impurity.Entropy.calculate"), - ProblemFilters.exclude[IncompatibleMethTypeProblem]( - "org.apache.spark.mllib.tree.impurity.Variance.calculate") - ) - case v if v.startsWith("1.0") => - Seq( - MimaBuild.excludeSparkPackage("api.java"), - MimaBuild.excludeSparkPackage("mllib"), - MimaBuild.excludeSparkPackage("streaming") - ) ++ - MimaBuild.excludeSparkClass("rdd.ClassTags") ++ - MimaBuild.excludeSparkClass("util.XORShiftRandom") ++ - MimaBuild.excludeSparkClass("graphx.EdgeRDD") ++ - MimaBuild.excludeSparkClass("graphx.VertexRDD") ++ - MimaBuild.excludeSparkClass("graphx.impl.GraphImpl") ++ - MimaBuild.excludeSparkClass("graphx.impl.RoutingTable") ++ - MimaBuild.excludeSparkClass("graphx.util.collection.PrimitiveKeyOpenHashMap") ++ - MimaBuild.excludeSparkClass("graphx.util.collection.GraphXPrimitiveKeyOpenHashMap") ++ - MimaBuild.excludeSparkClass("mllib.recommendation.MFDataGenerator") ++ - MimaBuild.excludeSparkClass("mllib.optimization.SquaredGradient") ++ - MimaBuild.excludeSparkClass("mllib.regression.RidgeRegressionWithSGD") ++ - MimaBuild.excludeSparkClass("mllib.regression.LassoWithSGD") ++ - MimaBuild.excludeSparkClass("mllib.regression.LinearRegressionWithSGD") - case _ => Seq() - } - - private val closures = Seq( - "org.apache.spark.rdd.RDD.org$apache$spark$rdd$RDD$$mergeMaps$1", - "org.apache.spark.rdd.RDD.org$apache$spark$rdd$RDD$$countPartition$1", - "org.apache.spark.rdd.RDD.org$apache$spark$rdd$RDD$$distributePartition$1", - "org.apache.spark.rdd.PairRDDFunctions.org$apache$spark$rdd$PairRDDFunctions$$mergeValue$1", - "org.apache.spark.rdd.PairRDDFunctions.org$apache$spark$rdd$PairRDDFunctions$$writeToFile$1", - "org.apache.spark.rdd.PairRDDFunctions.org$apache$spark$rdd$PairRDDFunctions$$reducePartition$1", - "org.apache.spark.rdd.PairRDDFunctions.org$apache$spark$rdd$PairRDDFunctions$$writeShard$1", - "org.apache.spark.rdd.PairRDDFunctions.org$apache$spark$rdd$PairRDDFunctions$$mergeCombiners$1", - "org.apache.spark.rdd.PairRDDFunctions.org$apache$spark$rdd$PairRDDFunctions$$process$1", - "org.apache.spark.rdd.PairRDDFunctions.org$apache$spark$rdd$PairRDDFunctions$$createCombiner$1", - "org.apache.spark.rdd.PairRDDFunctions.org$apache$spark$rdd$PairRDDFunctions$$mergeMaps$1" - ) + def excludes(version: String) = + version match { + case v if v.startsWith("1.1") => + Seq( + MimaBuild.excludeSparkPackage("deploy"), + MimaBuild.excludeSparkPackage("graphx") + ) ++ + Seq( + // Adding new method to JavaRDLike trait - we should probably mark this as a developer API. + ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.api.java.JavaRDDLike.partitions"), + // We made a mistake earlier (ed06500d3) in the Java API to use default parameter values + // for countApproxDistinct* functions, which does not work in Java. We later removed + // them, and use the following to tell Mima to not care about them. + ProblemFilters.exclude[IncompatibleResultTypeProblem]( + "org.apache.spark.api.java.JavaPairRDD.countApproxDistinctByKey"), + ProblemFilters.exclude[IncompatibleResultTypeProblem]( + "org.apache.spark.api.java.JavaPairRDD.countApproxDistinctByKey"), + ProblemFilters.exclude[MissingMethodProblem]( + "org.apache.spark.api.java.JavaPairRDD.countApproxDistinct$default$1"), + ProblemFilters.exclude[MissingMethodProblem]( + "org.apache.spark.api.java.JavaPairRDD.countApproxDistinctByKey$default$1"), + ProblemFilters.exclude[MissingMethodProblem]( + "org.apache.spark.api.java.JavaRDD.countApproxDistinct$default$1"), + ProblemFilters.exclude[MissingMethodProblem]( + "org.apache.spark.api.java.JavaRDDLike.countApproxDistinct$default$1"), + ProblemFilters.exclude[MissingMethodProblem]( + "org.apache.spark.api.java.JavaDoubleRDD.countApproxDistinct$default$1"), + ProblemFilters.exclude[MissingMethodProblem]( + "org.apache.spark.storage.MemoryStore.Entry") + ) ++ + Seq( + ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.streaming.flume.FlumeReceiver.this") + ) ++ + Seq( // Ignore some private methods in ALS. + ProblemFilters.exclude[MissingMethodProblem]( + "org.apache.spark.mllib.recommendation.ALS.org$apache$spark$mllib$recommendation$ALS$^dateFeatures"), + ProblemFilters.exclude[MissingMethodProblem]( // The only public constructor is the one without arguments. + "org.apache.spark.mllib.recommendation.ALS.this"), + ProblemFilters.exclude[MissingMethodProblem]( + "org.apache.spark.mllib.recommendation.ALS.org$apache$spark$mllib$recommendation$ALS$$$default$7"), + ProblemFilters.exclude[IncompatibleMethTypeProblem]( + "org.apache.spark.mllib.recommendation.ALS.org$apache$spark$mllib$recommendation$ALS$^dateFeatures") + ) ++ + MimaBuild.excludeSparkClass("mllib.linalg.distributed.ColumnStatisticsAggregator") ++ + MimaBuild.excludeSparkClass("rdd.ZippedRDD") ++ + MimaBuild.excludeSparkClass("rdd.ZippedPartition") ++ + MimaBuild.excludeSparkClass("util.SerializableHyperLogLog") ++ + MimaBuild.excludeSparkClass("storage.Values") ++ + MimaBuild.excludeSparkClass("storage.Entry") ++ + MimaBuild.excludeSparkClass("storage.MemoryStore$Entry") ++ + Seq( + ProblemFilters.exclude[IncompatibleMethTypeProblem]( + "org.apache.spark.mllib.tree.impurity.Gini.calculate"), + ProblemFilters.exclude[IncompatibleMethTypeProblem]( + "org.apache.spark.mllib.tree.impurity.Entropy.calculate"), + ProblemFilters.exclude[IncompatibleMethTypeProblem]( + "org.apache.spark.mllib.tree.impurity.Variance.calculate") + ) + case v if v.startsWith("1.0") => + Seq( + MimaBuild.excludeSparkPackage("api.java"), + MimaBuild.excludeSparkPackage("mllib"), + MimaBuild.excludeSparkPackage("streaming") + ) ++ + MimaBuild.excludeSparkClass("rdd.ClassTags") ++ + MimaBuild.excludeSparkClass("util.XORShiftRandom") ++ + MimaBuild.excludeSparkClass("graphx.EdgeRDD") ++ + MimaBuild.excludeSparkClass("graphx.VertexRDD") ++ + MimaBuild.excludeSparkClass("graphx.impl.GraphImpl") ++ + MimaBuild.excludeSparkClass("graphx.impl.RoutingTable") ++ + MimaBuild.excludeSparkClass("graphx.util.collection.PrimitiveKeyOpenHashMap") ++ + MimaBuild.excludeSparkClass("graphx.util.collection.GraphXPrimitiveKeyOpenHashMap") ++ + MimaBuild.excludeSparkClass("mllib.recommendation.MFDataGenerator") ++ + MimaBuild.excludeSparkClass("mllib.optimization.SquaredGradient") ++ + MimaBuild.excludeSparkClass("mllib.regression.RidgeRegressionWithSGD") ++ + MimaBuild.excludeSparkClass("mllib.regression.LassoWithSGD") ++ + MimaBuild.excludeSparkClass("mllib.regression.LinearRegressionWithSGD") + case _ => Seq() + } } diff --git a/tools/src/main/scala/org/apache/spark/tools/GenerateMIMAIgnore.scala b/tools/src/main/scala/org/apache/spark/tools/GenerateMIMAIgnore.scala index 03a73f92b275e..566983675bff5 100644 --- a/tools/src/main/scala/org/apache/spark/tools/GenerateMIMAIgnore.scala +++ b/tools/src/main/scala/org/apache/spark/tools/GenerateMIMAIgnore.scala @@ -99,9 +99,25 @@ object GenerateMIMAIgnore { (ignoredClasses.flatMap(c => Seq(c, c.replace("$", "#"))).toSet, ignoredMembers.toSet) } + /** Scala reflection does not let us see inner function even if they are upgraded + * to public for some reason. So had to resort to java reflection to get all inner + * functions with $$ in there name. + */ + def getInnerFunctions(classSymbol: unv.ClassSymbol): Seq[String] = { + try { + Class.forName(classSymbol.fullName, false, classLoader).getMethods.map(_.getName) + .filter(_.contains("$$")).map(classSymbol.fullName + "." + _) + } catch { + case t: Throwable => + println("[WARN] Unable to detect inner functions for class:" + classSymbol.fullName) + Seq.empty[String] + } + } + private def getAnnotatedOrPackagePrivateMembers(classSymbol: unv.ClassSymbol) = { classSymbol.typeSignature.members - .filter(x => isPackagePrivate(x) || isDeveloperApi(x) || isExperimental(x)).map(_.fullName) + .filter(x => isPackagePrivate(x) || isDeveloperApi(x) || isExperimental(x)).map(_.fullName) ++ + getInnerFunctions(classSymbol) } def main(args: Array[String]) { @@ -121,7 +137,8 @@ object GenerateMIMAIgnore { name.endsWith("$class") || name.contains("$sp") || name.contains("hive") || - name.contains("Hive") + name.contains("Hive") || + name.contains("repl") } /**