40a8fef4e6
This is a modified version of this PR https://github.com/apache/spark/pull/1168 done by @tmalaska Adds MIMA binary check exclusions. Author: tmalaska <ted.malaska@cloudera.com> Author: Tathagata Das <tathagata.das1565@gmail.com> Closes #1347 from tdas/FLUME-1915 and squashes the following commits: 96065df [Tathagata Das] Added Mima exclusion for FlumeReceiver. 41d5338 [tmalaska] Address line 57 that was too long 12617e5 [tmalaska] SPARK-1478: Upgrade FlumeInputDStream's Flume...
106 lines
5.8 KiB
Scala
106 lines
5.8 KiB
Scala
/*
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* Licensed to the Apache Software Foundation (ASF) under one or more
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* contributor license agreements. See the NOTICE file distributed with
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* this work for additional information regarding copyright ownership.
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* The ASF licenses this file to You under the Apache License, Version 2.0
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* (the "License"); you may not use this file except in compliance with
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* the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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import com.typesafe.tools.mima.core._
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/**
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* Additional excludes for checking of Spark's binary compatibility.
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*
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* The Mima build will automatically exclude @DeveloperApi and @Experimental classes. This acts
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* as an official audit of cases where we excluded other classes. Please use the narrowest
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* possible exclude here. MIMA will usually tell you what exclude to use, e.g.:
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*
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* ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.rdd.RDD.take")
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*
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* It is also possible to exclude Spark classes and packages. This should be used sparingly:
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*
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* MimaBuild.excludeSparkClass("graphx.util.collection.GraphXPrimitiveKeyOpenHashMap")
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*/
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object MimaExcludes {
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def excludes(version: String) =
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version match {
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case v if v.startsWith("1.1") =>
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Seq(
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MimaBuild.excludeSparkPackage("deploy"),
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MimaBuild.excludeSparkPackage("graphx")
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) ++
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Seq(
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// Adding new method to JavaRDLike trait - we should probably mark this as a developer API.
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ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.api.java.JavaRDDLike.partitions"),
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// We made a mistake earlier (ed06500d3) in the Java API to use default parameter values
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// for countApproxDistinct* functions, which does not work in Java. We later removed
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// them, and use the following to tell Mima to not care about them.
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ProblemFilters.exclude[IncompatibleResultTypeProblem](
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"org.apache.spark.api.java.JavaPairRDD.countApproxDistinctByKey"),
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ProblemFilters.exclude[IncompatibleResultTypeProblem](
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"org.apache.spark.api.java.JavaPairRDD.countApproxDistinctByKey"),
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ProblemFilters.exclude[MissingMethodProblem](
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"org.apache.spark.api.java.JavaPairRDD.countApproxDistinct$default$1"),
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ProblemFilters.exclude[MissingMethodProblem](
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"org.apache.spark.api.java.JavaPairRDD.countApproxDistinctByKey$default$1"),
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ProblemFilters.exclude[MissingMethodProblem](
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"org.apache.spark.api.java.JavaRDD.countApproxDistinct$default$1"),
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ProblemFilters.exclude[MissingMethodProblem](
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"org.apache.spark.api.java.JavaRDDLike.countApproxDistinct$default$1"),
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ProblemFilters.exclude[MissingMethodProblem](
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"org.apache.spark.api.java.JavaDoubleRDD.countApproxDistinct$default$1"),
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ProblemFilters.exclude[MissingMethodProblem](
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"org.apache.spark.storage.MemoryStore.Entry"),
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ProblemFilters.exclude[MissingMethodProblem](
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"org.apache.spark.rdd.PairRDDFunctions.org$apache$spark$rdd$PairRDDFunctions$$"
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+ "createZero$1")
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) ++
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Seq(
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ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.streaming.flume.FlumeReceiver.this")
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) ++
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Seq( // Ignore some private methods in ALS.
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ProblemFilters.exclude[MissingMethodProblem](
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"org.apache.spark.mllib.recommendation.ALS.org$apache$spark$mllib$recommendation$ALS$^dateFeatures"),
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ProblemFilters.exclude[MissingMethodProblem]( // The only public constructor is the one without arguments.
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"org.apache.spark.mllib.recommendation.ALS.this"),
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ProblemFilters.exclude[MissingMethodProblem](
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"org.apache.spark.mllib.recommendation.ALS.org$apache$spark$mllib$recommendation$ALS$$<init>$default$7")
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) ++
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MimaBuild.excludeSparkClass("rdd.ZippedRDD") ++
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MimaBuild.excludeSparkClass("rdd.ZippedPartition") ++
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MimaBuild.excludeSparkClass("util.SerializableHyperLogLog") ++
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MimaBuild.excludeSparkClass("storage.Values") ++
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MimaBuild.excludeSparkClass("storage.Entry") ++
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MimaBuild.excludeSparkClass("storage.MemoryStore$Entry")
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case v if v.startsWith("1.0") =>
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Seq(
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MimaBuild.excludeSparkPackage("api.java"),
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MimaBuild.excludeSparkPackage("mllib"),
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MimaBuild.excludeSparkPackage("streaming")
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) ++
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MimaBuild.excludeSparkClass("rdd.ClassTags") ++
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MimaBuild.excludeSparkClass("util.XORShiftRandom") ++
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MimaBuild.excludeSparkClass("graphx.EdgeRDD") ++
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MimaBuild.excludeSparkClass("graphx.VertexRDD") ++
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MimaBuild.excludeSparkClass("graphx.impl.GraphImpl") ++
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MimaBuild.excludeSparkClass("graphx.impl.RoutingTable") ++
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MimaBuild.excludeSparkClass("graphx.util.collection.PrimitiveKeyOpenHashMap") ++
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MimaBuild.excludeSparkClass("graphx.util.collection.GraphXPrimitiveKeyOpenHashMap") ++
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MimaBuild.excludeSparkClass("mllib.recommendation.MFDataGenerator") ++
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MimaBuild.excludeSparkClass("mllib.optimization.SquaredGradient") ++
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MimaBuild.excludeSparkClass("mllib.regression.RidgeRegressionWithSGD") ++
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MimaBuild.excludeSparkClass("mllib.regression.LassoWithSGD") ++
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MimaBuild.excludeSparkClass("mllib.regression.LinearRegressionWithSGD")
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case _ => Seq()
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}
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}
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