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spark-instrumented-optimizer/project/MimaExcludes.scala
Shixiong Zhu 4f5a24d7e7 [SPARK-7995][SPARK-6280][CORE] Remove AkkaRpcEnv and remove systemName from setupEndpointRef 
### Remove AkkaRpcEnv

Keep `SparkEnv.actorSystem` because Streaming still uses it. Will remove it and AkkaUtils after refactoring Streaming actorStream API.

### Remove systemName
There are 2 places using `systemName`:
* `RpcEnvConfig.name`. Actually, although it's used as `systemName` in `AkkaRpcEnv`, `NettyRpcEnv` uses it as the service name to output the log `Successfully started service *** on port ***`. Since the service name in log is useful, I keep `RpcEnvConfig.name`.
* `def setupEndpointRef(systemName: String, address: RpcAddress, endpointName: String)`. Each `ActorSystem` has a `systemName`. Akka requires `systemName` in its URI and will refuse a connection if `systemName` is not matched. However, `NettyRpcEnv` doesn't use it. So we can remove `systemName` from `setupEndpointRef` since we are removing `AkkaRpcEnv`.

### Remove RpcEnv.uriOf

`uriOf` exists because Akka uses different URI formats for with and without authentication, e.g., `akka.ssl.tcp...` and `akka.tcp://...`. But `NettyRpcEnv` uses the same format. So it's not necessary after removing `AkkaRpcEnv`.

Author: Shixiong Zhu <shixiong@databricks.com>

Closes #10459 from zsxwing/remove-akka-rpc-env.
2015-12-31 00:15:55 -08:00

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/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
import com.typesafe.tools.mima.core._
import com.typesafe.tools.mima.core.ProblemFilters._
/**
* Additional excludes for checking of Spark's binary compatibility.
*
* The Mima build will automatically exclude @DeveloperApi and @Experimental classes. This acts
* as an official audit of cases where we excluded other classes. Please use the narrowest
* possible exclude here. MIMA will usually tell you what exclude to use, e.g.:
*
* ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.rdd.RDD.take")
*
* It is also possible to exclude Spark classes and packages. This should be used sparingly:
*
* MimaBuild.excludeSparkClass("graphx.util.collection.GraphXPrimitiveKeyOpenHashMap")
*/
object MimaExcludes {
def excludes(version: String) = version match {
case v if v.startsWith("2.0") =>
Seq(
// SPARK-7995 Remove AkkaRpcEnv
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.rpc.akka.AkkaFailure"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.rpc.akka.AkkaFailure$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.rpc.akka.AkkaRpcEndpointRef$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.rpc.akka.AkkaRpcEnvFactory"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.rpc.akka.AkkaRpcEnv"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.rpc.akka.AkkaMessage$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.rpc.akka.AkkaRpcEndpointRef"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.rpc.akka.ErrorMonitor"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.rpc.akka.AkkaMessage")
) ++ Seq(
ProblemFilters.exclude[IncompatibleResultTypeProblem]("org.apache.spark.SparkContext.emptyRDD"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.broadcast.HttpBroadcastFactory")
) ++
// When 1.6 is officially released, update this exclusion list.
Seq(
MimaBuild.excludeSparkPackage("deploy"),
MimaBuild.excludeSparkPackage("network"),
MimaBuild.excludeSparkPackage("unsafe"),
// These are needed if checking against the sbt build, since they are part of
// the maven-generated artifacts in 1.3.
excludePackage("org.spark-project.jetty"),
MimaBuild.excludeSparkPackage("unused"),
// SQL execution is considered private.
excludePackage("org.apache.spark.sql.execution"),
// SQL columnar is considered private.
excludePackage("org.apache.spark.sql.columnar"),
// The shuffle package is considered private.
excludePackage("org.apache.spark.shuffle"),
// The collections utlities are considered pricate.
excludePackage("org.apache.spark.util.collection")
) ++
MimaBuild.excludeSparkClass("streaming.flume.FlumeTestUtils") ++
MimaBuild.excludeSparkClass("streaming.flume.PollingFlumeTestUtils") ++
Seq(
// MiMa does not deal properly with sealed traits
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.ml.classification.LogisticRegressionSummary.featuresCol")
) ++ Seq(
// SPARK-11530
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.mllib.feature.PCAModel.this")
) ++ Seq(
// SPARK-10381 Fix types / units in private AskPermissionToCommitOutput RPC message.
// This class is marked as `private` but MiMa still seems to be confused by the change.
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.scheduler.AskPermissionToCommitOutput.task"),
ProblemFilters.exclude[IncompatibleResultTypeProblem](
"org.apache.spark.scheduler.AskPermissionToCommitOutput.copy$default$2"),
ProblemFilters.exclude[IncompatibleMethTypeProblem](
"org.apache.spark.scheduler.AskPermissionToCommitOutput.copy"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.scheduler.AskPermissionToCommitOutput.taskAttempt"),
ProblemFilters.exclude[IncompatibleResultTypeProblem](
"org.apache.spark.scheduler.AskPermissionToCommitOutput.copy$default$3"),
ProblemFilters.exclude[IncompatibleMethTypeProblem](
"org.apache.spark.scheduler.AskPermissionToCommitOutput.this"),
ProblemFilters.exclude[IncompatibleMethTypeProblem](
"org.apache.spark.scheduler.AskPermissionToCommitOutput.apply")
) ++ Seq(
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.shuffle.FileShuffleBlockResolver$ShuffleFileGroup")
) ++ Seq(
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.ml.regression.LeastSquaresAggregator.add"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.ml.regression.LeastSquaresCostFun.this"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.sql.SQLContext.clearLastInstantiatedContext"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.sql.SQLContext.setLastInstantiatedContext"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.sql.SQLContext$SQLSession"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.sql.SQLContext.detachSession"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.sql.SQLContext.tlSession"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.sql.SQLContext.defaultSession"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.sql.SQLContext.currentSession"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.sql.SQLContext.openSession"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.sql.SQLContext.setSession"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.sql.SQLContext.createSession")
) ++ Seq(
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.SparkContext.preferredNodeLocationData_="),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.rdd.MapPartitionsWithPreparationRDD"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.rdd.MapPartitionsWithPreparationRDD$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.SparkSQLParser")
) ++ Seq(
// SPARK-11485
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.DataFrameHolder.df"),
// SPARK-11541 mark various JDBC dialects as private
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.NoopDialect.productElement"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.NoopDialect.productArity"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.NoopDialect.canEqual"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.NoopDialect.productIterator"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.NoopDialect.productPrefix"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.NoopDialect.toString"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.NoopDialect.hashCode"),
ProblemFilters.exclude[MissingTypesProblem]("org.apache.spark.sql.jdbc.PostgresDialect$"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.PostgresDialect.productElement"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.PostgresDialect.productArity"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.PostgresDialect.canEqual"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.PostgresDialect.productIterator"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.PostgresDialect.productPrefix"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.PostgresDialect.toString"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.PostgresDialect.hashCode"),
ProblemFilters.exclude[MissingTypesProblem]("org.apache.spark.sql.jdbc.NoopDialect$")
) ++ Seq (
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.status.api.v1.ApplicationInfo.this"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.status.api.v1.StageData.this")
) ++ Seq(
// SPARK-11766 add toJson to Vector
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.linalg.Vector.toJson")
) ++ Seq(
// SPARK-9065 Support message handler in Kafka Python API
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.streaming.kafka.KafkaUtilsPythonHelper.createDirectStream"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.streaming.kafka.KafkaUtilsPythonHelper.createRDD")
) ++ Seq(
// SPARK-4557 Changed foreachRDD to use VoidFunction
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.streaming.api.java.JavaDStreamLike.foreachRDD")
) ++ Seq(
// SPARK-11996 Make the executor thread dump work again
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.executor.ExecutorEndpoint"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.executor.ExecutorEndpoint$"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.storage.BlockManagerMessages$GetRpcHostPortForExecutor"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.storage.BlockManagerMessages$GetRpcHostPortForExecutor$")
) ++ Seq(
// SPARK-3580 Add getNumPartitions method to JavaRDD
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.api.java.JavaRDDLike.getNumPartitions")
) ++
// SPARK-11314: YARN backend moved to yarn sub-module and MiMA complains even though it's a
// private class.
MimaBuild.excludeSparkClass("scheduler.cluster.YarnSchedulerBackend$YarnSchedulerEndpoint")
case v if v.startsWith("1.6") =>
Seq(
MimaBuild.excludeSparkPackage("deploy"),
MimaBuild.excludeSparkPackage("network"),
MimaBuild.excludeSparkPackage("unsafe"),
// These are needed if checking against the sbt build, since they are part of
// the maven-generated artifacts in 1.3.
excludePackage("org.spark-project.jetty"),
MimaBuild.excludeSparkPackage("unused"),
// SQL execution is considered private.
excludePackage("org.apache.spark.sql.execution"),
// SQL columnar is considered private.
excludePackage("org.apache.spark.sql.columnar"),
// The shuffle package is considered private.
excludePackage("org.apache.spark.shuffle"),
// The collections utlities are considered pricate.
excludePackage("org.apache.spark.util.collection")
) ++
MimaBuild.excludeSparkClass("streaming.flume.FlumeTestUtils") ++
MimaBuild.excludeSparkClass("streaming.flume.PollingFlumeTestUtils") ++
Seq(
// MiMa does not deal properly with sealed traits
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.ml.classification.LogisticRegressionSummary.featuresCol")
) ++ Seq(
// SPARK-11530
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.mllib.feature.PCAModel.this")
) ++ Seq(
// SPARK-10381 Fix types / units in private AskPermissionToCommitOutput RPC message.
// This class is marked as `private` but MiMa still seems to be confused by the change.
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.scheduler.AskPermissionToCommitOutput.task"),
ProblemFilters.exclude[IncompatibleResultTypeProblem](
"org.apache.spark.scheduler.AskPermissionToCommitOutput.copy$default$2"),
ProblemFilters.exclude[IncompatibleMethTypeProblem](
"org.apache.spark.scheduler.AskPermissionToCommitOutput.copy"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.scheduler.AskPermissionToCommitOutput.taskAttempt"),
ProblemFilters.exclude[IncompatibleResultTypeProblem](
"org.apache.spark.scheduler.AskPermissionToCommitOutput.copy$default$3"),
ProblemFilters.exclude[IncompatibleMethTypeProblem](
"org.apache.spark.scheduler.AskPermissionToCommitOutput.this"),
ProblemFilters.exclude[IncompatibleMethTypeProblem](
"org.apache.spark.scheduler.AskPermissionToCommitOutput.apply")
) ++ Seq(
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.shuffle.FileShuffleBlockResolver$ShuffleFileGroup")
) ++ Seq(
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.ml.regression.LeastSquaresAggregator.add"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.ml.regression.LeastSquaresCostFun.this"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.sql.SQLContext.clearLastInstantiatedContext"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.sql.SQLContext.setLastInstantiatedContext"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.sql.SQLContext$SQLSession"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.sql.SQLContext.detachSession"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.sql.SQLContext.tlSession"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.sql.SQLContext.defaultSession"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.sql.SQLContext.currentSession"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.sql.SQLContext.openSession"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.sql.SQLContext.setSession"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.sql.SQLContext.createSession")
) ++ Seq(
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.SparkContext.preferredNodeLocationData_="),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.rdd.MapPartitionsWithPreparationRDD"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.rdd.MapPartitionsWithPreparationRDD$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.SparkSQLParser")
) ++ Seq(
// SPARK-11485
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.DataFrameHolder.df"),
// SPARK-11541 mark various JDBC dialects as private
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.NoopDialect.productElement"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.NoopDialect.productArity"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.NoopDialect.canEqual"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.NoopDialect.productIterator"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.NoopDialect.productPrefix"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.NoopDialect.toString"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.NoopDialect.hashCode"),
ProblemFilters.exclude[MissingTypesProblem]("org.apache.spark.sql.jdbc.PostgresDialect$"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.PostgresDialect.productElement"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.PostgresDialect.productArity"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.PostgresDialect.canEqual"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.PostgresDialect.productIterator"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.PostgresDialect.productPrefix"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.PostgresDialect.toString"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.sql.jdbc.PostgresDialect.hashCode"),
ProblemFilters.exclude[MissingTypesProblem]("org.apache.spark.sql.jdbc.NoopDialect$")
) ++ Seq (
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.status.api.v1.ApplicationInfo.this"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.status.api.v1.StageData.this")
) ++ Seq(
// SPARK-11766 add toJson to Vector
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.linalg.Vector.toJson")
) ++ Seq(
// SPARK-9065 Support message handler in Kafka Python API
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.streaming.kafka.KafkaUtilsPythonHelper.createDirectStream"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.streaming.kafka.KafkaUtilsPythonHelper.createRDD")
) ++ Seq(
// SPARK-4557 Changed foreachRDD to use VoidFunction
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.streaming.api.java.JavaDStreamLike.foreachRDD")
) ++ Seq(
// SPARK-11996 Make the executor thread dump work again
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.executor.ExecutorEndpoint"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.executor.ExecutorEndpoint$"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.storage.BlockManagerMessages$GetRpcHostPortForExecutor"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.storage.BlockManagerMessages$GetRpcHostPortForExecutor$")
) ++ Seq(
// SPARK-3580 Add getNumPartitions method to JavaRDD
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.api.java.JavaRDDLike.getNumPartitions")
) ++
// SPARK-11314: YARN backend moved to yarn sub-module and MiMA complains even though it's a
// private class.
MimaBuild.excludeSparkClass("scheduler.cluster.YarnSchedulerBackend$YarnSchedulerEndpoint")
case v if v.startsWith("1.5") =>
Seq(
MimaBuild.excludeSparkPackage("network"),
MimaBuild.excludeSparkPackage("deploy"),
// These are needed if checking against the sbt build, since they are part of
// the maven-generated artifacts in 1.3.
excludePackage("org.spark-project.jetty"),
MimaBuild.excludeSparkPackage("unused"),
// JavaRDDLike is not meant to be extended by user programs
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.api.java.JavaRDDLike.partitioner"),
// Modification of private static method
ProblemFilters.exclude[IncompatibleMethTypeProblem](
"org.apache.spark.streaming.kafka.KafkaUtils.org$apache$spark$streaming$kafka$KafkaUtils$$leadersForRanges"),
// Mima false positive (was a private[spark] class)
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.util.collection.PairIterator"),
// Removing a testing method from a private class
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.streaming.kafka.KafkaTestUtils.waitUntilLeaderOffset"),
// While private MiMa is still not happy about the changes,
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.ml.regression.LeastSquaresAggregator.this"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.ml.regression.LeastSquaresCostFun.this"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.ml.classification.LogisticCostFun.this"),
// SQL execution is considered private.
excludePackage("org.apache.spark.sql.execution"),
// The old JSON RDD is removed in favor of streaming Jackson
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.json.JsonRDD$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.json.JsonRDD"),
// local function inside a method
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.sql.SQLContext.org$apache$spark$sql$SQLContext$$needsConversion$1"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.sql.UDFRegistration.org$apache$spark$sql$UDFRegistration$$builder$24")
) ++ Seq(
// SPARK-8479 Add numNonzeros and numActives to Matrix.
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.linalg.Matrix.numNonzeros"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.linalg.Matrix.numActives")
) ++ Seq(
// SPARK-8914 Remove RDDApi
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.RDDApi")
) ++ Seq(
// SPARK-7292 Provide operator to truncate lineage cheaply
ProblemFilters.exclude[AbstractClassProblem](
"org.apache.spark.rdd.RDDCheckpointData"),
ProblemFilters.exclude[AbstractClassProblem](
"org.apache.spark.rdd.CheckpointRDD")
) ++ Seq(
// SPARK-8701 Add input metadata in the batch page.
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.streaming.scheduler.InputInfo$"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.streaming.scheduler.InputInfo")
) ++ Seq(
// SPARK-6797 Support YARN modes for SparkR
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.api.r.PairwiseRRDD.this"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.api.r.RRDD.createRWorker"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.api.r.RRDD.this"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.api.r.StringRRDD.this"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.api.r.BaseRRDD.this")
) ++ Seq(
// SPARK-7422 add argmax for sparse vectors
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.linalg.Vector.argmax")
) ++ Seq(
// SPARK-8906 Move all internal data source classes into execution.datasources
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.ResolvedDataSource"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.PreInsertCastAndRename$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.CreateTableUsingAsSelect$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.InsertIntoDataSource$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.SqlNewHadoopPartition"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.PartitioningUtils$PartitionValues$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.DefaultWriterContainer"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.PartitioningUtils$PartitionValues"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.RefreshTable$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.CreateTempTableUsing$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.PartitionSpec"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.DynamicPartitionWriterContainer"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.CreateTableUsingAsSelect"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.SqlNewHadoopRDD$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.DescribeCommand$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.PartitioningUtils$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.SqlNewHadoopRDD"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.PreInsertCastAndRename"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.Partition$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.LogicalRelation$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.PartitioningUtils"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.LogicalRelation"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.Partition"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.BaseWriterContainer"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.PreWriteCheck"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.CreateTableUsing"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.RefreshTable"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.SqlNewHadoopRDD$NewHadoopMapPartitionsWithSplitRDD"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.DataSourceStrategy$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.CreateTempTableUsing"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.CreateTempTableUsingAsSelect$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.CreateTempTableUsingAsSelect"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.CreateTableUsing$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.ResolvedDataSource$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.PreWriteCheck$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.InsertIntoDataSource"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.InsertIntoHadoopFsRelation"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.DDLParser"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.CaseInsensitiveMap"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.InsertIntoHadoopFsRelation$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.DataSourceStrategy"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.SqlNewHadoopRDD$NewHadoopMapPartitionsWithSplitRDD$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.PartitionSpec$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.DescribeCommand"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.DDLException"),
// SPARK-9763 Minimize exposure of internal SQL classes
excludePackage("org.apache.spark.sql.parquet"),
excludePackage("org.apache.spark.sql.json"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.jdbc.JDBCRDD$DecimalConversion$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.jdbc.JDBCPartition"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.jdbc.JdbcUtils$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.jdbc.JDBCRDD$DecimalConversion"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.jdbc.JDBCPartitioningInfo$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.jdbc.JDBCPartition$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.jdbc.package"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.jdbc.JDBCRDD$JDBCConversion"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.jdbc.JDBCRDD$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.jdbc.package$DriverWrapper"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.jdbc.JDBCRDD"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.jdbc.JDBCPartitioningInfo"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.jdbc.JdbcUtils"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.jdbc.DefaultSource"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.jdbc.JDBCRelation$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.jdbc.package$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.jdbc.JDBCRelation")
) ++ Seq(
// SPARK-4751 Dynamic allocation for standalone mode
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.SparkContext.supportDynamicAllocation")
) ++ Seq(
// SPARK-9580: Remove SQL test singletons
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.sql.test.LocalSQLContext$SQLSession"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.sql.test.LocalSQLContext"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.sql.test.TestSQLContext"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.sql.test.TestSQLContext$")
) ++ Seq(
// SPARK-9704 Made ProbabilisticClassifier, Identifiable, VectorUDT public APIs
ProblemFilters.exclude[IncompatibleResultTypeProblem](
"org.apache.spark.mllib.linalg.VectorUDT.serialize")
) ++ Seq(
// SPARK-10381 Fix types / units in private AskPermissionToCommitOutput RPC message.
// This class is marked as `private` but MiMa still seems to be confused by the change.
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.scheduler.AskPermissionToCommitOutput.task"),
ProblemFilters.exclude[IncompatibleResultTypeProblem](
"org.apache.spark.scheduler.AskPermissionToCommitOutput.copy$default$2"),
ProblemFilters.exclude[IncompatibleMethTypeProblem](
"org.apache.spark.scheduler.AskPermissionToCommitOutput.copy"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.scheduler.AskPermissionToCommitOutput.taskAttempt"),
ProblemFilters.exclude[IncompatibleResultTypeProblem](
"org.apache.spark.scheduler.AskPermissionToCommitOutput.copy$default$3"),
ProblemFilters.exclude[IncompatibleMethTypeProblem](
"org.apache.spark.scheduler.AskPermissionToCommitOutput.this"),
ProblemFilters.exclude[IncompatibleMethTypeProblem](
"org.apache.spark.scheduler.AskPermissionToCommitOutput.apply")
)
case v if v.startsWith("1.4") =>
Seq(
MimaBuild.excludeSparkPackage("deploy"),
MimaBuild.excludeSparkPackage("ml"),
// SPARK-7910 Adding a method to get the partioner to JavaRDD,
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.api.java.JavaRDDLike.partitioner"),
// SPARK-5922 Adding a generalized diff(other: RDD[(VertexId, VD)]) to VertexRDD
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.graphx.VertexRDD.diff"),
// These are needed if checking against the sbt build, since they are part of
// the maven-generated artifacts in 1.3.
excludePackage("org.spark-project.jetty"),
MimaBuild.excludeSparkPackage("unused"),
ProblemFilters.exclude[MissingClassProblem]("com.google.common.base.Optional"),
ProblemFilters.exclude[IncompatibleResultTypeProblem](
"org.apache.spark.rdd.JdbcRDD.compute"),
ProblemFilters.exclude[IncompatibleResultTypeProblem](
"org.apache.spark.broadcast.HttpBroadcastFactory.newBroadcast"),
ProblemFilters.exclude[IncompatibleResultTypeProblem](
"org.apache.spark.broadcast.TorrentBroadcastFactory.newBroadcast"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.scheduler.OutputCommitCoordinator$OutputCommitCoordinatorEndpoint")
) ++ Seq(
// SPARK-4655 - Making Stage an Abstract class broke binary compatility even though
// the stage class is defined as private[spark]
ProblemFilters.exclude[AbstractClassProblem]("org.apache.spark.scheduler.Stage")
) ++ Seq(
// SPARK-6510 Add a Graph#minus method acting as Set#difference
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.graphx.VertexRDD.minus")
) ++ Seq(
// SPARK-6492 Fix deadlock in SparkContext.stop()
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.SparkContext.org$" +
"apache$spark$SparkContext$$SPARK_CONTEXT_CONSTRUCTOR_LOCK")
)++ Seq(
// SPARK-6693 add tostring with max lines and width for matrix
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.linalg.Matrix.toString")
)++ Seq(
// SPARK-6703 Add getOrCreate method to SparkContext
ProblemFilters.exclude[IncompatibleResultTypeProblem]
("org.apache.spark.SparkContext.org$apache$spark$SparkContext$$activeContext")
)++ Seq(
// SPARK-7090 Introduce LDAOptimizer to LDA to further improve extensibility
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.mllib.clustering.LDA$EMOptimizer")
) ++ Seq(
// SPARK-6756 add toSparse, toDense, numActives, numNonzeros, and compressed to Vector
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.linalg.Vector.compressed"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.linalg.Vector.toDense"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.linalg.Vector.numNonzeros"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.linalg.Vector.toSparse"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.linalg.Vector.numActives"),
// SPARK-7681 add SparseVector support for gemv
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.linalg.Matrix.multiply"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.linalg.DenseMatrix.multiply"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.linalg.SparseMatrix.multiply")
) ++ Seq(
// Execution should never be included as its always internal.
MimaBuild.excludeSparkPackage("sql.execution"),
// This `protected[sql]` method was removed in 1.3.1
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.sql.SQLContext.checkAnalysis"),
// These `private[sql]` class were removed in 1.4.0:
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.sql.execution.AddExchange"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.sql.execution.AddExchange$"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.sql.parquet.PartitionSpec"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.sql.parquet.PartitionSpec$"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.sql.parquet.Partition"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.sql.parquet.Partition$"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.sql.parquet.ParquetRelation2$PartitionValues"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.sql.parquet.ParquetRelation2$PartitionValues$"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.sql.parquet.ParquetRelation2"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.sql.parquet.ParquetRelation2$"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.sql.parquet.ParquetRelation2$MetadataCache"),
// These test support classes were moved out of src/main and into src/test:
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.sql.parquet.ParquetTestData"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.sql.parquet.ParquetTestData$"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.sql.parquet.TestGroupWriteSupport"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.CachedData"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.CachedData$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.CacheManager"),
// TODO: Remove the following rule once ParquetTest has been moved to src/test.
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.sql.parquet.ParquetTest")
) ++ Seq(
// SPARK-7530 Added StreamingContext.getState()
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.streaming.StreamingContext.state_=")
) ++ Seq(
// SPARK-7081 changed ShuffleWriter from a trait to an abstract class and removed some
// unnecessary type bounds in order to fix some compiler warnings that occurred when
// implementing this interface in Java. Note that ShuffleWriter is private[spark].
ProblemFilters.exclude[IncompatibleTemplateDefProblem](
"org.apache.spark.shuffle.ShuffleWriter")
) ++ Seq(
// SPARK-6888 make jdbc driver handling user definable
// This patch renames some classes to API friendly names.
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.jdbc.DriverQuirks$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.jdbc.DriverQuirks"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.jdbc.PostgresQuirks"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.jdbc.NoQuirks"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.jdbc.MySQLQuirks")
)
case v if v.startsWith("1.3") =>
Seq(
MimaBuild.excludeSparkPackage("deploy"),
MimaBuild.excludeSparkPackage("ml"),
// These are needed if checking against the sbt build, since they are part of
// the maven-generated artifacts in the 1.2 build.
MimaBuild.excludeSparkPackage("unused"),
ProblemFilters.exclude[MissingClassProblem]("com.google.common.base.Optional")
) ++ Seq(
// SPARK-2321
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.SparkStageInfoImpl.this"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.SparkStageInfo.submissionTime")
) ++ Seq(
// SPARK-4614
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.linalg.Matrices.randn"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.linalg.Matrices.rand")
) ++ Seq(
// SPARK-5321
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.linalg.SparseMatrix.transposeMultiply"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.linalg.Matrix.transpose"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.linalg.DenseMatrix.transposeMultiply"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.mllib.linalg.Matrix." +
"org$apache$spark$mllib$linalg$Matrix$_setter_$isTransposed_="),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.linalg.Matrix.isTransposed"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.linalg.Matrix.foreachActive")
) ++ Seq(
// SPARK-5540
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.recommendation.ALS.solveLeastSquares"),
// SPARK-5536
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.recommendation.ALS.org$apache$spark$mllib$recommendation$ALS$^dateFeatures"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.recommendation.ALS.org$apache$spark$mllib$recommendation$ALS$^dateBlock")
) ++ Seq(
// SPARK-3325
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.streaming.api.java.JavaDStreamLike.print"),
// SPARK-2757
ProblemFilters.exclude[IncompatibleResultTypeProblem](
"org.apache.spark.streaming.flume.sink.SparkAvroCallbackHandler." +
"removeAndGetProcessor")
) ++ Seq(
// SPARK-5123 (SparkSQL data type change) - alpha component only
ProblemFilters.exclude[IncompatibleResultTypeProblem](
"org.apache.spark.ml.feature.HashingTF.outputDataType"),
ProblemFilters.exclude[IncompatibleResultTypeProblem](
"org.apache.spark.ml.feature.Tokenizer.outputDataType"),
ProblemFilters.exclude[IncompatibleMethTypeProblem](
"org.apache.spark.ml.feature.Tokenizer.validateInputType"),
ProblemFilters.exclude[IncompatibleMethTypeProblem](
"org.apache.spark.ml.classification.LogisticRegressionModel.validateAndTransformSchema"),
ProblemFilters.exclude[IncompatibleMethTypeProblem](
"org.apache.spark.ml.classification.LogisticRegression.validateAndTransformSchema")
) ++ Seq(
// SPARK-4014
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.TaskContext.taskAttemptId"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.TaskContext.attemptNumber")
) ++ Seq(
// SPARK-5166 Spark SQL API stabilization
ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.ml.Transformer.transform"),
ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.ml.Estimator.fit"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.ml.Transformer.transform"),
ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.ml.Pipeline.fit"),
ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.ml.PipelineModel.transform"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.ml.Estimator.fit"),
ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.ml.Evaluator.evaluate"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.ml.Evaluator.evaluate"),
ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.ml.tuning.CrossValidator.fit"),
ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.ml.tuning.CrossValidatorModel.transform"),
ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.ml.feature.StandardScaler.fit"),
ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.ml.feature.StandardScalerModel.transform"),
ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.ml.classification.LogisticRegressionModel.transform"),
ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.ml.classification.LogisticRegression.fit"),
ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.ml.evaluation.BinaryClassificationEvaluator.evaluate")
) ++ Seq(
// SPARK-5270
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.api.java.JavaRDDLike.isEmpty")
) ++ Seq(
// SPARK-5430
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.api.java.JavaRDDLike.treeReduce"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.api.java.JavaRDDLike.treeAggregate")
) ++ Seq(
// SPARK-5297 Java FileStream do not work with custom key/values
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.streaming.api.java.JavaStreamingContext.fileStream")
) ++ Seq(
// SPARK-5315 Spark Streaming Java API returns Scala DStream
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.streaming.api.java.JavaDStreamLike.reduceByWindow")
) ++ Seq(
// SPARK-5461 Graph should have isCheckpointed, getCheckpointFiles methods
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.graphx.Graph.getCheckpointFiles"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.graphx.Graph.isCheckpointed")
) ++ Seq(
// SPARK-4789 Standardize ML Prediction APIs
ProblemFilters.exclude[MissingTypesProblem]("org.apache.spark.mllib.linalg.VectorUDT"),
ProblemFilters.exclude[IncompatibleResultTypeProblem]("org.apache.spark.mllib.linalg.VectorUDT.serialize"),
ProblemFilters.exclude[IncompatibleResultTypeProblem]("org.apache.spark.mllib.linalg.VectorUDT.sqlType")
) ++ Seq(
// SPARK-5814
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.recommendation.ALS.org$apache$spark$mllib$recommendation$ALS$$wrapDoubleArray"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.recommendation.ALS.org$apache$spark$mllib$recommendation$ALS$$fillFullMatrix"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.recommendation.ALS.org$apache$spark$mllib$recommendation$ALS$$iterations"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.recommendation.ALS.org$apache$spark$mllib$recommendation$ALS$$makeOutLinkBlock"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.recommendation.ALS.org$apache$spark$mllib$recommendation$ALS$$computeYtY"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.recommendation.ALS.org$apache$spark$mllib$recommendation$ALS$$makeLinkRDDs"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.recommendation.ALS.org$apache$spark$mllib$recommendation$ALS$$alpha"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.recommendation.ALS.org$apache$spark$mllib$recommendation$ALS$$randomFactor"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.recommendation.ALS.org$apache$spark$mllib$recommendation$ALS$$makeInLinkBlock"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.recommendation.ALS.org$apache$spark$mllib$recommendation$ALS$$dspr"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.recommendation.ALS.org$apache$spark$mllib$recommendation$ALS$$lambda"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.recommendation.ALS.org$apache$spark$mllib$recommendation$ALS$$implicitPrefs"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.recommendation.ALS.org$apache$spark$mllib$recommendation$ALS$$rank")
) ++ Seq(
// SPARK-4682
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.RealClock"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.Clock"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.TestClock")
) ++ Seq(
// SPARK-5922 Adding a generalized diff(other: RDD[(VertexId, VD)]) to VertexRDD
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.graphx.VertexRDD.diff")
)
case v if v.startsWith("1.2") =>
Seq(
MimaBuild.excludeSparkPackage("deploy"),
MimaBuild.excludeSparkPackage("graphx")
) ++
MimaBuild.excludeSparkClass("mllib.linalg.Matrix") ++
MimaBuild.excludeSparkClass("mllib.linalg.Vector") ++
Seq(
ProblemFilters.exclude[IncompatibleTemplateDefProblem](
"org.apache.spark.scheduler.TaskLocation"),
// Added normL1 and normL2 to trait MultivariateStatisticalSummary
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.stat.MultivariateStatisticalSummary.normL1"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.stat.MultivariateStatisticalSummary.normL2"),
// MapStatus should be private[spark]
ProblemFilters.exclude[IncompatibleTemplateDefProblem](
"org.apache.spark.scheduler.MapStatus"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.network.netty.PathResolver"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.network.netty.client.BlockClientListener"),
// TaskContext was promoted to Abstract class
ProblemFilters.exclude[AbstractClassProblem](
"org.apache.spark.TaskContext"),
ProblemFilters.exclude[IncompatibleTemplateDefProblem](
"org.apache.spark.util.collection.SortDataFormat")
) ++ Seq(
// Adding new methods to the JavaRDDLike trait:
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.api.java.JavaRDDLike.takeAsync"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.api.java.JavaRDDLike.foreachPartitionAsync"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.api.java.JavaRDDLike.countAsync"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.api.java.JavaRDDLike.foreachAsync"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.api.java.JavaRDDLike.collectAsync")
) ++ Seq(
// SPARK-3822
ProblemFilters.exclude[IncompatibleResultTypeProblem](
"org.apache.spark.SparkContext.org$apache$spark$SparkContext$$createTaskScheduler")
) ++ Seq(
// SPARK-1209
ProblemFilters.exclude[MissingClassProblem](
"org.apache.hadoop.mapreduce.SparkHadoopMapReduceUtil"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.hadoop.mapred.SparkHadoopMapRedUtil"),
ProblemFilters.exclude[MissingTypesProblem](
"org.apache.spark.rdd.PairRDDFunctions")
) ++ Seq(
// SPARK-4062
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.streaming.kafka.KafkaReceiver#MessageHandler.this")
)
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"),
// Should probably mark this as Experimental
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.api.java.JavaRDDLike.foreachAsync"),
// 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.DiskStore.getValues"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.storage.MemoryStore.Entry")
) ++
Seq(
// Serializer interface change. See SPARK-3045.
ProblemFilters.exclude[IncompatibleTemplateDefProblem](
"org.apache.spark.serializer.DeserializationStream"),
ProblemFilters.exclude[IncompatibleTemplateDefProblem](
"org.apache.spark.serializer.Serializer"),
ProblemFilters.exclude[IncompatibleTemplateDefProblem](
"org.apache.spark.serializer.SerializationStream"),
ProblemFilters.exclude[IncompatibleTemplateDefProblem](
"org.apache.spark.serializer.SerializerInstance")
)++
Seq(
// Renamed putValues -> putArray + putIterator
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.storage.MemoryStore.putValues"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.storage.DiskStore.putValues"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.storage.TachyonStore.putValues")
) ++
Seq(
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.streaming.flume.FlumeReceiver.this"),
ProblemFilters.exclude[IncompatibleMethTypeProblem](
"org.apache.spark.streaming.kafka.KafkaUtils.createStream"),
ProblemFilters.exclude[IncompatibleMethTypeProblem](
"org.apache.spark.streaming.kafka.KafkaReceiver.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$$<init>$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") ++
// Class was missing "@DeveloperApi" annotation in 1.0.
MimaBuild.excludeSparkClass("scheduler.SparkListenerApplicationStart") ++
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")
) ++
Seq( // Package-private classes removed in SPARK-2341
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.mllib.util.BinaryLabelParser"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.mllib.util.BinaryLabelParser$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.mllib.util.LabelParser"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.mllib.util.LabelParser$"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.mllib.util.MulticlassLabelParser"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.mllib.util.MulticlassLabelParser$")
) ++
Seq( // package-private classes removed in MLlib
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm.org$apache$spark$mllib$regression$GeneralizedLinearAlgorithm$$prependOne")
) ++
Seq( // new Vector methods in MLlib (binary compatible assuming users do not implement Vector)
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.mllib.linalg.Vector.copy")
) ++
Seq( // synthetic methods generated in LabeledPoint
ProblemFilters.exclude[MissingTypesProblem]("org.apache.spark.mllib.regression.LabeledPoint$"),
ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.mllib.regression.LabeledPoint.apply"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.mllib.regression.LabeledPoint.toString")
) ++
Seq ( // Scala 2.11 compatibility fix
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.streaming.StreamingContext.<init>$default$2")
)
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()
}
}
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