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spark-instrumented-optimizer/project/MimaExcludes.scala

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Better explanation for how to use MIMA excludes. This patch does a few things: 1. We have a file MimaExcludes.scala exclusively for excludes. 2. The test runner tells users about that file if a test fails. 3. I've added back the excludes used from 0.9->1.0. We should keep these in the project as an official audit trail of times where we decided to make exceptions. Author: Patrick Wendell <pwendell@gmail.com> Closes #937 from pwendell/mima and squashes the following commits: 7ee0db2 [Patrick Wendell] Better explanation for how to use MIMA excludes.
2014-06-01 20:27:05 -04:00
/*
* 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._
[SPARK-6371] [build] Update version to 1.4.0-SNAPSHOT. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #5056 from vanzin/SPARK-6371 and squashes the following commits: 63220df [Marcelo Vanzin] Merge branch 'master' into SPARK-6371 6506f75 [Marcelo Vanzin] Use more fine-grained exclusion. 178ba71 [Marcelo Vanzin] Oops. 75b2375 [Marcelo Vanzin] Exclude VertexRDD in MiMA. a45a62c [Marcelo Vanzin] Work around MIMA warning. 1d8a670 [Marcelo Vanzin] Re-group jetty exclusion. 0e8e909 [Marcelo Vanzin] Ignore ml, don't ignore graphx. cef4603 [Marcelo Vanzin] Indentation. 296cf82 [Marcelo Vanzin] [SPARK-6371] [build] Update version to 1.4.0-SNAPSHOT.
2015-03-20 14:43:57 -04:00
import com.typesafe.tools.mima.core.ProblemFilters._
Better explanation for how to use MIMA excludes. This patch does a few things: 1. We have a file MimaExcludes.scala exclusively for excludes. 2. The test runner tells users about that file if a test fails. 3. I've added back the excludes used from 0.9->1.0. We should keep these in the project as an official audit trail of times where we decided to make exceptions. Author: Patrick Wendell <pwendell@gmail.com> Closes #937 from pwendell/mima and squashes the following commits: 7ee0db2 [Patrick Wendell] Better explanation for how to use MIMA excludes.
2014-06-01 20:27:05 -04:00
/**
* 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 {
[SPARK-2549] Functions defined inside of other functions trigger failures Author: Prashant Sharma <prashant.s@imaginea.com> 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
2014-07-23 20:12:28 -04:00
def excludes(version: String) =
version match {
[SPARK-6371] [build] Update version to 1.4.0-SNAPSHOT. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #5056 from vanzin/SPARK-6371 and squashes the following commits: 63220df [Marcelo Vanzin] Merge branch 'master' into SPARK-6371 6506f75 [Marcelo Vanzin] Use more fine-grained exclusion. 178ba71 [Marcelo Vanzin] Oops. 75b2375 [Marcelo Vanzin] Exclude VertexRDD in MiMA. a45a62c [Marcelo Vanzin] Work around MIMA warning. 1d8a670 [Marcelo Vanzin] Re-group jetty exclusion. 0e8e909 [Marcelo Vanzin] Ignore ml, don't ignore graphx. cef4603 [Marcelo Vanzin] Indentation. 296cf82 [Marcelo Vanzin] [SPARK-6371] [build] Update version to 1.4.0-SNAPSHOT.
2015-03-20 14:43:57 -04:00
case v if v.startsWith("1.4") =>
Seq(
MimaBuild.excludeSparkPackage("deploy"),
MimaBuild.excludeSparkPackage("ml"),
// 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"),
[SPARK-6428] Added explicit types for all public methods in core. Author: Reynold Xin <rxin@databricks.com> Closes #5125 from rxin/core-explicit-type and squashes the following commits: f471415 [Reynold Xin] Revert style checker changes. 81b66e4 [Reynold Xin] Code review feedback. a7533e3 [Reynold Xin] Mima excludes. 1d795f5 [Reynold Xin] [SPARK-6428] Added explicit types for all public methods in core.
2015-03-24 02:41:06 -04:00
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](
[SPARK-5124][Core] A standard RPC interface and an Akka implementation This PR added a standard internal RPC interface for Spark and an Akka implementation. See [the design document](https://issues.apache.org/jira/secure/attachment/12698710/Pluggable%20RPC%20-%20draft%202.pdf) for more details. I will split the whole work into multiple PRs to make it easier for code review. This is the first PR and avoid to touch too many files. Author: zsxwing <zsxwing@gmail.com> Closes #4588 from zsxwing/rpc-part1 and squashes the following commits: fe3df4c [zsxwing] Move registerEndpoint and use actorSystem.dispatcher in asyncSetupEndpointRefByURI f6f3287 [zsxwing] Remove RpcEndpointRef.toURI 8bd1097 [zsxwing] Fix docs and the code style f459380 [zsxwing] Add RpcAddress.fromURI and rename urls to uris b221398 [zsxwing] Move send methods above ask methods 15cfd7b [zsxwing] Merge branch 'master' into rpc-part1 9ffa997 [zsxwing] Fix MiMa tests 78a1733 [zsxwing] Merge remote-tracking branch 'origin/master' into rpc-part1 385b9c3 [zsxwing] Fix the code style and add docs 2cc3f78 [zsxwing] Add an asynchronous version of setupEndpointRefByUrl e8dfec3 [zsxwing] Remove 'sendWithReply(message: Any, sender: RpcEndpointRef): Unit' 08564ae [zsxwing] Add RpcEnvFactory to create RpcEnv e5df4ca [zsxwing] Handle AkkaFailure(e) in Actor ec7c5b0 [zsxwing] Fix docs 7fc95e1 [zsxwing] Implement askWithReply in RpcEndpointRef 9288406 [zsxwing] Document thread-safety for setupThreadSafeEndpoint 3007c09 [zsxwing] Move setupDriverEndpointRef to RpcUtils and rename to makeDriverRef c425022 [zsxwing] Fix the code style 5f87700 [zsxwing] Move the logical of processing message to a private function 3e56123 [zsxwing] Use lazy to eliminate CountDownLatch 07f128f [zsxwing] Remove ActionScheduler.scala 4d34191 [zsxwing] Remove scheduler from RpcEnv 7cdd95e [zsxwing] Add docs for RpcEnv 51e6667 [zsxwing] Add 'sender' to RpcCallContext and rename the parameter of receiveAndReply to 'context' ffc1280 [zsxwing] Rename 'fail' to 'sendFailure' and other minor code style changes 28e6d0f [zsxwing] Add onXXX for network events and remove the companion objects of network events 3751c97 [zsxwing] Rename RpcResponse to RpcCallContext fe7d1ff [zsxwing] Add explicit reply in rpc 7b9e0c9 [zsxwing] Fix the indentation 04a106e [zsxwing] Remove NopCancellable and add a const NOP in object SettableCancellable 2a579f4 [zsxwing] Remove RpcEnv.systemName 155b987 [zsxwing] Change newURI to uriOf and add some comments 45b2317 [zsxwing] A standard RPC interface and An Akka implementation
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"org.apache.spark.broadcast.TorrentBroadcastFactory.newBroadcast"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.scheduler.OutputCommitCoordinator$OutputCommitCoordinatorActor")
[SPARK-6510][GraphX]: Add Graph#minus method to act as Set#difference Adds a `Graph#minus` method which will return only unique `VertexId`'s from the calling `VertexRDD`. To demonstrate a basic example with pseudocode: ``` Set((0L,0),(1L,1)).minus(Set((1L,1),(2L,2))) > Set((0L,0)) ``` Author: Brennon York <brennon.york@capitalone.com> Closes #5175 from brennonyork/SPARK-6510 and squashes the following commits: 248d5c8 [Brennon York] added minus(VertexRDD[VD]) method to avoid createUsingIndex and updated the mask operations to simplify with andNot call 3fb7cce [Brennon York] updated graphx doc to reflect the addition of minus method 6575d92 [Brennon York] updated mima exclude aaa030b [Brennon York] completed graph#minus functionality 7227c0f [Brennon York] beginning work on minus functionality
2015-03-26 22:08:09 -04:00
) ++ Seq(
[SPARK-4655][Core] Split Stage into ShuffleMapStage and ResultStage subclasses Hi all - this patch changes the Stage class to an abstract class and introduces two new classes that extend it: ShuffleMapStage and ResultStage - with the goal of increasing readability of the DAGScheduler class. Their usage is updated within DAGScheduler. Author: Ilya Ganelin <ilya.ganelin@capitalone.com> Author: Ilya Ganelin <ilganeli@gmail.com> Closes #4708 from ilganeli/SPARK-4655 and squashes the following commits: c248924 [Ilya Ganelin] Merge branch 'SPARK-4655' of github.com:ilganeli/spark into SPARK-4655 d930385 [Ilya Ganelin] Fixed merge conflict from a9a765f [Ilya Ganelin] Update DAGScheduler.scala c03563c [Ilya Ganelin] Minor fixeS c39e971 [Ilya Ganelin] Added return typing for public methods 845bc87 [Ilya Ganelin] Merge branch 'SPARK-4655' of github.com:ilganeli/spark into SPARK-4655 e8031d8 [Ilya Ganelin] Minor string fixes 4ec53ac [Ilya Ganelin] Merge remote-tracking branch 'upstream/master' into SPARK-4655 c004f62 [Ilya Ganelin] Update DAGScheduler.scala a2cb03f [Ilya Ganelin] [SPARK-4655] Replaced usages of Nil and eliminated some code reuse 3d5cf20 [Ilya Ganelin] [SPARK-4655] Moved mima exclude to 1.4 6912c55 [Ilya Ganelin] Resolved merge conflict 4bff208 [Ilya Ganelin] Minor stylistic fixes c6fffbb [Ilya Ganelin] newline 41402ad [Ilya Ganelin] Style fixes 02c6981 [Ilya Ganelin] Merge branch 'SPARK-4655' of github.com:ilganeli/spark into SPARK-4655 c755a09 [Ilya Ganelin] Some more stylistic updates and minor refactoring b6257a0 [Ilya Ganelin] Update MimaExcludes.scala 0f0c624 [Ilya Ganelin] Fixed merge conflict 2eba262 [Ilya Ganelin] Merge remote-tracking branch 'upstream/master' into SPARK-4655 6b43d7b [Ilya Ganelin] Got rid of some spaces 6f1a5db [Ilya Ganelin] Revert "More minor formatting and refactoring" 1b3471b [Ilya Ganelin] Merge remote-tracking branch 'upstream/master' into SPARK-4655 c9288e2 [Ilya Ganelin] More minor formatting and refactoring d548caf [Ilya Ganelin] Formatting fix c3ae5c2 [Ilya Ganelin] Explicit typing 0dacaf3 [Ilya Ganelin] Got rid of stale import 6da3a71 [Ilya Ganelin] Trailing whitespace b85c5fe [Ilya Ganelin] Added minor fixes a57dfcd [Ilya Ganelin] Added MiMA exclusion to get around binary compatibility check 83ed849 [Ilya Ganelin] moved braces for consistency 96dd161 [Ilya Ganelin] Fixed minor style error cfd6f10 [Ilya Ganelin] Updated DAGScheduler to use new ResultStage and ShuffleMapStage classes 83494e9 [Ilya Ganelin] Added new Stage classes
2015-04-01 06:09:00 -04:00
// 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
[SPARK-6510][GraphX]: Add Graph#minus method to act as Set#difference Adds a `Graph#minus` method which will return only unique `VertexId`'s from the calling `VertexRDD`. To demonstrate a basic example with pseudocode: ``` Set((0L,0),(1L,1)).minus(Set((1L,1),(2L,2))) > Set((0L,0)) ``` Author: Brennon York <brennon.york@capitalone.com> Closes #5175 from brennonyork/SPARK-6510 and squashes the following commits: 248d5c8 [Brennon York] added minus(VertexRDD[VD]) method to avoid createUsingIndex and updated the mask operations to simplify with andNot call 3fb7cce [Brennon York] updated graphx doc to reflect the addition of minus method 6575d92 [Brennon York] updated mima exclude aaa030b [Brennon York] completed graph#minus functionality 7227c0f [Brennon York] beginning work on minus functionality
2015-03-26 22:08:09 -04:00
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.graphx.VertexRDD.minus")
[SPARK-6492][CORE] SparkContext.stop() can deadlock when DAGSchedulerEventProcessLoop dies I've added a timeout and retry loop around the SparkContext shutdown code that should fix this deadlock. If a SparkContext shutdown is in progress when another thread comes knocking, it will wait for 10 seconds for the lock, then fall through where the outer loop will re-submit the request. Author: Ilya Ganelin <ilya.ganelin@capitalone.com> Closes #5277 from ilganeli/SPARK-6492 and squashes the following commits: 8617a7e [Ilya Ganelin] Resolved merge conflict 2fbab66 [Ilya Ganelin] Added MIMA Exclude a0e2c70 [Ilya Ganelin] Deleted stale imports fa28ce7 [Ilya Ganelin] reverted to just having a single stopped 76fc825 [Ilya Ganelin] Updated to use atomic booleans instead of the synchronized vars 6e8a7f7 [Ilya Ganelin] Removing unecessary null check for now since i'm not fixing stop ordering yet cdf7073 [Ilya Ganelin] [SPARK-6492] Moved stopped=true back to the start of the shutdown sequence so this can be addressed in a seperate PR 7fb795b [Ilya Ganelin] Spacing b7a0c5c [Ilya Ganelin] Import ordering df8224f [Ilya Ganelin] Added comment for added lock 343cb94 [Ilya Ganelin] [SPARK-6492] Added timeout/retry logic to fix a deadlock in SparkContext shutdown
2015-04-03 14:23:11 -04:00
) ++ Seq(
// SPARK-6492 Fix deadlock in SparkContext.stop()
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.SparkContext.org$" +
"apache$spark$SparkContext$$SPARK_CONTEXT_CONSTRUCTOR_LOCK")
[Spark-6693][MLlib]add tostring with max lines and width for matrix jira: https://issues.apache.org/jira/browse/SPARK-6693 It's kind of annoying when debugging and found you cannot print out the matrix as you want. original toString of Matrix only print like following, 0.17810102596909183 0.5616906241468385 ... (10 total) 0.9692861997823815 0.015558159784155756 ... 0.8513015122819192 0.031523763918528847 ... 0.5396875653953941 0.3267864552779176 ... The def toString(maxLines : Int, maxWidth : Int) is useful when debuging, logging and saving matrix to files. Author: Yuhao Yang <hhbyyh@gmail.com> Closes #5344 from hhbyyh/addToString and squashes the following commits: 19a6836 [Yuhao Yang] remove extra line 6314b21 [Yuhao Yang] add exclude 736c324 [Yuhao Yang] add ut and exclude 420da39 [Yuhao Yang] Merge remote-tracking branch 'upstream/master' into addToString c22f352 [Yuhao Yang] style change 64a9e0f [Yuhao Yang] add specific to string to matrix
2015-04-09 18:37:45 -04:00
)++ Seq(
// SPARK-6693 add tostring with max lines and width for matrix
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.linalg.Matrix.toString")
[SPARK-6703][Core] Provide a way to discover existing SparkContext's I've added a static getOrCreate method to the static SparkContext object that allows one to either retrieve a previously created SparkContext or to instantiate a new one with the provided config. The method accepts an optional SparkConf to make usage intuitive. Still working on a test for this, basically want to create a new context from scratch, then ensure that subsequent calls don't overwrite that. Author: Ilya Ganelin <ilya.ganelin@capitalone.com> Closes #5501 from ilganeli/SPARK-6703 and squashes the following commits: db9a963 [Ilya Ganelin] Closing second spark context 1dc0444 [Ilya Ganelin] Added ref equality check 8c884fa [Ilya Ganelin] Made getOrCreate synchronized cb0c6b7 [Ilya Ganelin] Doc updates and code cleanup 270cfe3 [Ilya Ganelin] [SPARK-6703] Documentation fixes 15e8dea [Ilya Ganelin] Updated comments and added MiMa Exclude 0e1567c [Ilya Ganelin] Got rid of unecessary option for AtomicReference dfec4da [Ilya Ganelin] Changed activeContext to AtomicReference 733ec9f [Ilya Ganelin] Fixed some bugs in test code 8be2f83 [Ilya Ganelin] Replaced match with if e92caf7 [Ilya Ganelin] [SPARK-6703] Added test to ensure that getOrCreate both allows creation, retrieval, and a second context if desired a99032f [Ilya Ganelin] Spacing fix d7a06b8 [Ilya Ganelin] Updated SparkConf class to add getOrCreate method. Started test suite implementation
2015-04-17 21:28:42 -04:00
)++ Seq(
// SPARK-6703 Add getOrCreate method to SparkContext
ProblemFilters.exclude[IncompatibleResultTypeProblem]
("org.apache.spark.SparkContext.org$apache$spark$SparkContext$$activeContext")
[SPARK-7090] [MLLIB] Introduce LDAOptimizer to LDA to further improve extensibility jira: https://issues.apache.org/jira/browse/SPARK-7090 LDA was implemented with extensibility in mind. And with the development of OnlineLDA and Gibbs Sampling, we are collecting more detailed requirements from different algorithms. As Joseph Bradley jkbradley proposed in https://github.com/apache/spark/pull/4807 and with some further discussion, we'd like to adjust the code structure a little to present the common interface and extension point clearly. Basically class LDA would be a common entrance for LDA computing. And each LDA object will refer to a LDAOptimizer for the concrete algorithm implementation. Users can customize LDAOptimizer with specific parameters and assign it to LDA. Concrete changes: 1. Add a trait `LDAOptimizer`, which defines the common iterface for concrete implementations. Each subClass is a wrapper for a specific LDA algorithm. 2. Move EMOptimizer to file LDAOptimizer and inherits from LDAOptimizer, rename to EMLDAOptimizer. (in case a more generic EMOptimizer comes in the future) -adjust the constructor of EMOptimizer, since all the parameters should be passed in through initialState method. This can avoid unwanted confusion or overwrite. -move the code from LDA.initalState to initalState of EMLDAOptimizer 3. Add property ldaOptimizer to LDA and its getter/setter, and EMLDAOptimizer is the default Optimizer. 4. Change the return type of LDA.run from DistributedLDAModel to LDAModel. Further work: add OnlineLDAOptimizer and other possible Optimizers once ready. Author: Yuhao Yang <hhbyyh@gmail.com> Closes #5661 from hhbyyh/ldaRefactor and squashes the following commits: 0e2e006 [Yuhao Yang] respond to review comments 08a45da [Yuhao Yang] Merge remote-tracking branch 'upstream/master' into ldaRefactor e756ce4 [Yuhao Yang] solve mima exception d74fd8f [Yuhao Yang] Merge remote-tracking branch 'upstream/master' into ldaRefactor 0bb8400 [Yuhao Yang] refactor LDA with Optimizer ec2f857 [Yuhao Yang] protoptype for discussion
2015-04-27 22:02:51 -04:00
)++ Seq(
// SPARK-7090 Introduce LDAOptimizer to LDA to further improve extensibility
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.mllib.clustering.LDA$EMOptimizer")
[SPARK-6371] [build] Update version to 1.4.0-SNAPSHOT. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #5056 from vanzin/SPARK-6371 and squashes the following commits: 63220df [Marcelo Vanzin] Merge branch 'master' into SPARK-6371 6506f75 [Marcelo Vanzin] Use more fine-grained exclusion. 178ba71 [Marcelo Vanzin] Oops. 75b2375 [Marcelo Vanzin] Exclude VertexRDD in MiMA. a45a62c [Marcelo Vanzin] Work around MIMA warning. 1d8a670 [Marcelo Vanzin] Re-group jetty exclusion. 0e8e909 [Marcelo Vanzin] Ignore ml, don't ignore graphx. cef4603 [Marcelo Vanzin] Indentation. 296cf82 [Marcelo Vanzin] [SPARK-6371] [build] Update version to 1.4.0-SNAPSHOT.
2015-03-20 14:43:57 -04:00
)
Bumping version to 1.3.0-SNAPSHOT. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #3277 from vanzin/version-1.3 and squashes the following commits: 7c3c396 [Marcelo Vanzin] Added temp repo to sbt build. 5f404ff [Marcelo Vanzin] Add another exclusion. 19457e7 [Marcelo Vanzin] Update old version to 1.2, add temporary 1.2 repo. 3c8d705 [Marcelo Vanzin] Workaround for MIMA checks. e940810 [Marcelo Vanzin] Bumping version to 1.3.0-SNAPSHOT.
2014-11-19 00:24:18 -05:00
case v if v.startsWith("1.3") =>
Seq(
MimaBuild.excludeSparkPackage("deploy"),
[SPARK-4789] [SPARK-4942] [SPARK-5031] [mllib] Standardize ML Prediction APIs This is part (1a) of the updates from the design doc in [https://docs.google.com/document/d/1BH9el33kBX8JiDdgUJXdLW14CA2qhTCWIG46eXZVoJs] **UPDATE**: Most of the APIs are being kept private[spark] to allow further discussion. Here is a list of changes which are public: * new output columns: rawPrediction, probabilities * The “score” column is now called “rawPrediction” * Classifiers now provide numClasses * Params.get and .set are now protected instead of private[ml]. * ParamMap now has a size method. * new classes: LinearRegression, LinearRegressionModel * LogisticRegression now has an intercept. ### Sketch of APIs (most of which are private[spark] for now) Abstract classes for learning algorithms (+ corresponding Model abstractions): * Classifier (+ ClassificationModel) * ProbabilisticClassifier (+ ProbabilisticClassificationModel) * Regressor (+ RegressionModel) * Predictor (+ PredictionModel) * *For all of these*: * There is no strongly typed training-time API. * There is a strongly typed test-time (prediction) API which helps developers implement new algorithms. Concrete classes: learning algorithms * LinearRegression * LogisticRegression (updated to use new abstract classes) * Also, removed "score" in favor of "probability" output column. Changed BinaryClassificationEvaluator to match. (SPARK-5031) Other updates: * params.scala: Changed Params.set/get to be protected instead of private[ml] * This was needed for the example of defining a class from outside of the MLlib namespace. * VectorUDT: Will later change from private[spark] to public. * This is needed for outside users to write their own validateAndTransformSchema() methods using vectors. * Also, added equals() method.f * SPARK-4942 : ML Transformers should allow output cols to be turned on,off * Update validateAndTransformSchema * Update transform * (Updated examples, test suites according to other changes) New examples: * DeveloperApiExample.scala (example of defining algorithm from outside of the MLlib namespace) * Added Java version too Test Suites: * LinearRegressionSuite * LogisticRegressionSuite * + Java versions of above suites CC: mengxr etrain shivaram Author: Joseph K. Bradley <joseph@databricks.com> Closes #3637 from jkbradley/ml-api-part1 and squashes the following commits: 405bfb8 [Joseph K. Bradley] Last edits based on code review. Small cleanups fec348a [Joseph K. Bradley] Added JavaDeveloperApiExample.java and fixed other issues: Made developer API private[spark] for now. Added constructors Java can understand to specialized Param types. 8316d5e [Joseph K. Bradley] fixes after rebasing on master fc62406 [Joseph K. Bradley] fixed test suites after last commit bcb9549 [Joseph K. Bradley] Fixed issues after rebasing from master (after move from SchemaRDD to DataFrame) 9872424 [Joseph K. Bradley] fixed JavaLinearRegressionSuite.java Java sql api f542997 [Joseph K. Bradley] Added MIMA excludes for VectorUDT (now public), and added DeveloperApi annotation to it 216d199 [Joseph K. Bradley] fixed after sql datatypes PR got merged f549e34 [Joseph K. Bradley] Updates based on code review. Major ones are: * Created weakly typed Predictor.train() method which is called by fit() so that developers do not have to call schema validation or copy parameters. * Made Predictor.featuresDataType have a default value of VectorUDT. * NOTE: This could be dangerous since the FeaturesType type parameter cannot have a default value. 343e7bd [Joseph K. Bradley] added blanket mima exclude for ml package 82f340b [Joseph K. Bradley] Fixed bug in LogisticRegression (introduced in this PR). Fixed Java suites 0a16da9 [Joseph K. Bradley] Fixed Linear/Logistic RegressionSuites c3c8da5 [Joseph K. Bradley] small cleanup 934f97b [Joseph K. Bradley] Fixed bugs from previous commit. 1c61723 [Joseph K. Bradley] * Made ProbabilisticClassificationModel into a subclass of ClassificationModel. Also introduced ProbabilisticClassifier. * This was to support output column “probabilityCol” in transform(). 4e2f711 [Joseph K. Bradley] rat fix bc654e1 [Joseph K. Bradley] Added spark.ml LinearRegressionSuite 8d13233 [Joseph K. Bradley] Added methods: * Classifier: batch predictRaw() * Predictor: train() without paramMap ProbabilisticClassificationModel.predictProbabilities() * Java versions of all above batch methods + others 1680905 [Joseph K. Bradley] Added JavaLabeledPointSuite.java for spark.ml, and added constructor to LabeledPoint which defaults weight to 1.0 adbe50a [Joseph K. Bradley] * fixed LinearRegression train() to use embedded paramMap * added Predictor.predict(RDD[Vector]) method * updated Linear/LogisticRegressionSuites 58802e3 [Joseph K. Bradley] added train() to Predictor subclasses which does not take a ParamMap. 57d54ab [Joseph K. Bradley] * Changed semantics of Predictor.train() to merge the given paramMap with the embedded paramMap. * remove threshold_internal from logreg * Added Predictor.copy() * Extended LogisticRegressionSuite e433872 [Joseph K. Bradley] Updated docs. Added LabeledPointSuite to spark.ml 54b7b31 [Joseph K. Bradley] Fixed issue with logreg threshold being set correctly 0617d61 [Joseph K. Bradley] Fixed bug from last commit (sorting paramMap by parameter names in toString). Fixed bug in persisting logreg data. Added threshold_internal to logreg for faster test-time prediction (avoiding map lookup). 601e792 [Joseph K. Bradley] Modified ParamMap to sort parameters in toString. Cleaned up classes in class hierarchy, before implementing tests and examples. d705e87 [Joseph K. Bradley] Added LinearRegression and Regressor back from ml-api branch 52f4fde [Joseph K. Bradley] removing everything except for simple class hierarchy for classification d35bb5d [Joseph K. Bradley] fixed compilation issues, but have not added tests yet bfade12 [Joseph K. Bradley] Added lots of classes for new ML API:
2015-02-06 02:43:47 -05:00
MimaBuild.excludeSparkPackage("ml"),
Bumping version to 1.3.0-SNAPSHOT. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #3277 from vanzin/version-1.3 and squashes the following commits: 7c3c396 [Marcelo Vanzin] Added temp repo to sbt build. 5f404ff [Marcelo Vanzin] Add another exclusion. 19457e7 [Marcelo Vanzin] Update old version to 1.2, add temporary 1.2 repo. 3c8d705 [Marcelo Vanzin] Workaround for MIMA checks. e940810 [Marcelo Vanzin] Bumping version to 1.3.0-SNAPSHOT.
2014-11-19 00:24:18 -05:00
// 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")
[HOT FIX] MiMa tests are broken This is blocking #3353 and other patches. Author: Andrew Or <andrew@databricks.com> Closes #3371 from andrewor14/mima-hot-fix and squashes the following commits: 842d059 [Andrew Or] Move excludes to the right section c4d4f4e [Andrew Or] MIMA hot fix
2014-11-19 17:03:44 -05:00
) ++ Seq(
// SPARK-2321
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.SparkStageInfoImpl.this"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.SparkStageInfo.submissionTime")
[SPARK-4614][MLLIB] Slight API changes in Matrix and Matrices Before we have a full picture of the operators we want to add, it might be safer to hide `Matrix.transposeMultiply` in 1.2.0. Another update we want to change is `Matrix.randn` and `Matrix.rand`, both of which should take a `Random` implementation. Otherwise, it is very likely to produce inconsistent RDDs. I also added some unit tests for matrix factory methods. All APIs are new in 1.2, so there is no incompatible changes. brkyvz Author: Xiangrui Meng <meng@databricks.com> Closes #3468 from mengxr/SPARK-4614 and squashes the following commits: 3b0e4e2 [Xiangrui Meng] add mima excludes 6bfd8a4 [Xiangrui Meng] hide transposeMultiply; add rng to rand and randn; add unit tests
2014-11-26 11:22:50 -05:00
) ++ Seq(
// SPARK-4614
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.linalg.Matrices.randn"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.linalg.Matrices.rand")
[SPARK-5321] Support for transposing local matrices Support for transposing local matrices added. The `.transpose` function creates a new object re-using the backing array(s) but switches `numRows` and `numCols`. Operations check the flag `.isTransposed` to see whether the indexing in `values` should be modified. This PR will pave the way for transposing `BlockMatrix`. Author: Burak Yavuz <brkyvz@gmail.com> Closes #4109 from brkyvz/SPARK-5321 and squashes the following commits: 87ab83c [Burak Yavuz] fixed scalastyle caf4438 [Burak Yavuz] addressed code review v3 c524770 [Burak Yavuz] address code review comments 2 77481e8 [Burak Yavuz] fixed MiMa f1c1742 [Burak Yavuz] small refactoring ccccdec [Burak Yavuz] fixed failed test dd45c88 [Burak Yavuz] addressed code review a01bd5f [Burak Yavuz] [SPARK-5321] Fixed MiMa issues 2a63593 [Burak Yavuz] [SPARK-5321] fixed bug causing failed gemm test c55f29a [Burak Yavuz] [SPARK-5321] Support for transposing local matrices cleaned up c408c05 [Burak Yavuz] [SPARK-5321] Support for transposing local matrices added
2015-01-27 04:46:17 -05:00
) ++ 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")
[SPARK-5540] hide ALS.solveLeastSquares This method survived the code review and it has been there since v1.1.0. It exposes jblas types. Let's remove it from the public API. I think no one calls it directly. Author: Xiangrui Meng <meng@databricks.com> Closes #4318 from mengxr/SPARK-5540 and squashes the following commits: 586ade6 [Xiangrui Meng] hide ALS.solveLeastSquares
2015-02-02 20:10:01 -05:00
) ++ Seq(
// SPARK-5540
ProblemFilters.exclude[MissingMethodProblem](
[SPARK-5536] replace old ALS implementation by the new one The only issue is that `analyzeBlock` is removed, which was marked as a developer API. I didn't change other tests in the ALSSuite under `spark.mllib` to ensure that the implementation is correct. CC: srowen coderxiang Author: Xiangrui Meng <meng@databricks.com> Closes #4321 from mengxr/SPARK-5536 and squashes the following commits: 5a3cee8 [Xiangrui Meng] update python tests that are too strict e840acf [Xiangrui Meng] ignore scala style check for ALS.train e9a721c [Xiangrui Meng] update mima excludes 9ee6a36 [Xiangrui Meng] merge master 9a8aeac [Xiangrui Meng] update tests d8c3271 [Xiangrui Meng] remove analyzeBlocks d68eee7 [Xiangrui Meng] add checkpoint to new ALS 22a56f8 [Xiangrui Meng] wrap old ALS c387dff [Xiangrui Meng] support random seed 3bdf24b [Xiangrui Meng] make storage level configurable in the new ALS
2015-02-03 02:49:09 -05:00
"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")
SPARK-2757 [BUILD] [STREAMING] Add Mima test for Spark Sink after 1.10 is released Re-enable MiMa for Streaming Flume Sink module, now that 1.1.0 is released, per the JIRA TO-DO. That's pretty much all there is to this. Author: Sean Owen <sowen@cloudera.com> Closes #3842 from srowen/SPARK-2757 and squashes the following commits: 50ff80e [Sean Owen] Exclude apparent false positive turned up by re-enabling MiMa checks for Streaming Flume Sink 0e5ba5c [Sean Owen] Re-enable MiMa for Streaming Flume Sink module
2014-12-31 19:59:17 -05:00
) ++ Seq(
[SPARK-3325][Streaming] Add a parameter to the method print in class DStream This PR is a fixed version of the original PR #3237 by watermen and scwf. This adds the ability to specify how many elements to print in `DStream.print`. Author: Yadong Qi <qiyadong2010@gmail.com> Author: q00251598 <qiyadong@huawei.com> Author: Tathagata Das <tathagata.das1565@gmail.com> Author: wangfei <wangfei1@huawei.com> Closes #3865 from tdas/print-num and squashes the following commits: cd34e9e [Tathagata Das] Fix bug 7c09f16 [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into HEAD bb35d1a [Yadong Qi] Update MimaExcludes.scala f8098ca [Yadong Qi] Update MimaExcludes.scala f6ac3cb [Yadong Qi] Update MimaExcludes.scala e4ed897 [Yadong Qi] Update MimaExcludes.scala 3b9d5cf [wangfei] fix conflicts ec8a3af [q00251598] move to Spark 1.3 26a70c0 [q00251598] extend the Python DStream's print b589a4b [q00251598] add another print function
2015-01-02 18:09:41 -05:00
// SPARK-3325
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.streaming.api.java.JavaDStreamLike.print"),
SPARK-2757 [BUILD] [STREAMING] Add Mima test for Spark Sink after 1.10 is released Re-enable MiMa for Streaming Flume Sink module, now that 1.1.0 is released, per the JIRA TO-DO. That's pretty much all there is to this. Author: Sean Owen <sowen@cloudera.com> Closes #3842 from srowen/SPARK-2757 and squashes the following commits: 50ff80e [Sean Owen] Exclude apparent false positive turned up by re-enabling MiMa checks for Streaming Flume Sink 0e5ba5c [Sean Owen] Re-enable MiMa for Streaming Flume Sink module
2014-12-31 19:59:17 -05:00
// SPARK-2757
ProblemFilters.exclude[IncompatibleResultTypeProblem](
"org.apache.spark.streaming.flume.sink.SparkAvroCallbackHandler." +
"removeAndGetProcessor")
[SPARK-5123][SQL] Reconcile Java/Scala API for data types. Having two versions of the data type APIs (one for Java, one for Scala) requires downstream libraries to also have two versions of the APIs if the library wants to support both Java and Scala. I took a look at the Scala version of the data type APIs - it can actually work out pretty well for Java out of the box. As part of the PR, I created a sql.types package and moved all type definitions there. I then removed the Java specific data type API along with a lot of the conversion code. This subsumes https://github.com/apache/spark/pull/3925 Author: Reynold Xin <rxin@databricks.com> Closes #3958 from rxin/SPARK-5123-datatype-2 and squashes the following commits: 66505cc [Reynold Xin] [SPARK-5123] Expose only one version of the data type APIs (i.e. remove the Java-specific API).
2015-01-13 20:16:41 -05:00
) ++ 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")
[SPARK-4014] Add TaskContext.attemptNumber and deprecate TaskContext.attemptId `TaskContext.attemptId` is misleadingly-named, since it currently returns a taskId, which uniquely identifies a particular task attempt within a particular SparkContext, instead of an attempt number, which conveys how many times a task has been attempted. This patch deprecates `TaskContext.attemptId` and add `TaskContext.taskId` and `TaskContext.attemptNumber` fields. Prior to this change, it was impossible to determine whether a task was being re-attempted (or was a speculative copy), which made it difficult to write unit tests for tasks that fail on early attempts or speculative tasks that complete faster than original tasks. Earlier versions of the TaskContext docs suggest that `attemptId` behaves like `attemptNumber`, so there's an argument to be made in favor of changing this method's implementation. Since we've decided against making that change in maintenance branches, I think it's simpler to add better-named methods and retain the old behavior for `attemptId`; if `attemptId` behaved differently in different branches, then this would cause confusing build-breaks when backporting regression tests that rely on the new `attemptId` behavior. Most of this patch is fairly straightforward, but there is a bit of trickiness related to Mesos tasks: since there's no field in MesosTaskInfo to encode the attemptId, I packed it into the `data` field alongside the task binary. Author: Josh Rosen <joshrosen@databricks.com> Closes #3849 from JoshRosen/SPARK-4014 and squashes the following commits: 89d03e0 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-4014 5cfff05 [Josh Rosen] Introduce wrapper for serializing Mesos task launch data. 38574d4 [Josh Rosen] attemptId -> taskAttemptId in PairRDDFunctions a180b88 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-4014 1d43aa6 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-4014 eee6a45 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-4014 0b10526 [Josh Rosen] Use putInt instead of putLong (silly mistake) 8c387ce [Josh Rosen] Use local with maxRetries instead of local-cluster. cbe4d76 [Josh Rosen] Preserve attemptId behavior and deprecate it: b2dffa3 [Josh Rosen] Address some of Reynold's minor comments 9d8d4d1 [Josh Rosen] Doc typo 1e7a933 [Josh Rosen] [SPARK-4014] Change TaskContext.attemptId to return attempt number instead of task ID. fd515a5 [Josh Rosen] Add failing test for SPARK-4014
2015-01-14 14:45:40 -05:00
) ++ Seq(
// SPARK-4014
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.TaskContext.taskAttemptId"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.TaskContext.attemptNumber")
[SPARK-5193][SQL] Remove Spark SQL Java-specific API. After the following patches, the main (Scala) API is now usable for Java users directly. https://github.com/apache/spark/pull/4056 https://github.com/apache/spark/pull/4054 https://github.com/apache/spark/pull/4049 https://github.com/apache/spark/pull/4030 https://github.com/apache/spark/pull/3965 https://github.com/apache/spark/pull/3958 Author: Reynold Xin <rxin@databricks.com> Closes #4065 from rxin/sql-java-api and squashes the following commits: b1fd860 [Reynold Xin] Fix Mima 6d86578 [Reynold Xin] Ok one more attempt in fixing Python... e8f1455 [Reynold Xin] Fix Python again... 3e53f91 [Reynold Xin] Fixed Python. 83735da [Reynold Xin] Fix BigDecimal test. e9f1de3 [Reynold Xin] Use scala BigDecimal. 500d2c4 [Reynold Xin] Fix Decimal. ba3bfa2 [Reynold Xin] Updated javadoc for RowFactory. c4ae1c5 [Reynold Xin] [SPARK-5193][SQL] Remove Spark SQL Java-specific API.
2015-01-17 00:09:06 -05:00
) ++ Seq(
// SPARK-5166 Spark SQL API stabilization
ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.ml.Transformer.transform"),
[SPARK-5097][SQL] DataFrame This pull request redesigns the existing Spark SQL dsl, which already provides data frame like functionalities. TODOs: With the exception of Python support, other tasks can be done in separate, follow-up PRs. - [ ] Audit of the API - [ ] Documentation - [ ] More test cases to cover the new API - [x] Python support - [ ] Type alias SchemaRDD Author: Reynold Xin <rxin@databricks.com> Author: Davies Liu <davies@databricks.com> Closes #4173 from rxin/df1 and squashes the following commits: 0a1a73b [Reynold Xin] Merge branch 'df1' of github.com:rxin/spark into df1 23b4427 [Reynold Xin] Mima. 828f70d [Reynold Xin] Merge pull request #7 from davies/df 257b9e6 [Davies Liu] add repartition 6bf2b73 [Davies Liu] fix collect with UDT and tests e971078 [Reynold Xin] Missing quotes. b9306b4 [Reynold Xin] Remove removeColumn/updateColumn for now. a728bf2 [Reynold Xin] Example rename. e8aa3d3 [Reynold Xin] groupby -> groupBy. 9662c9e [Davies Liu] improve DataFrame Python API 4ae51ea [Davies Liu] python API for dataframe 1e5e454 [Reynold Xin] Fixed a bug with symbol conversion. 2ca74db [Reynold Xin] Couple minor fixes. ea98ea1 [Reynold Xin] Documentation & literal expressions. 2b22684 [Reynold Xin] Got rid of IntelliJ problems. 02bbfbc [Reynold Xin] Tightening imports. ffbce66 [Reynold Xin] Fixed compilation error. 59b6d8b [Reynold Xin] Style violation. b85edfb [Reynold Xin] ALS. 8c37f0a [Reynold Xin] Made MLlib and examples compile 6d53134 [Reynold Xin] Hive module. d35efd5 [Reynold Xin] Fixed compilation error. ce4a5d2 [Reynold Xin] Fixed test cases in SQL except ParquetIOSuite. 66d5ef1 [Reynold Xin] SQLContext minor patch. c9bcdc0 [Reynold Xin] Checkpoint: SQL module compiles!
2015-01-27 19:08:24 -05:00
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")
SPARK-5270 [CORE] Provide isEmpty() function in RDD API Pretty minor, but submitted for consideration -- this would at least help people make this check in the most efficient way I know. Author: Sean Owen <sowen@cloudera.com> Closes #4074 from srowen/SPARK-5270 and squashes the following commits: 66885b8 [Sean Owen] Add note that JavaRDDLike should not be implemented by user code 2e9b490 [Sean Owen] More tests, and Mima-exclude the new isEmpty method in JavaRDDLike 28395ff [Sean Owen] Add isEmpty to Java, Python 7dd04b7 [Sean Owen] Add efficient RDD.isEmpty()
2015-01-20 01:50:44 -05:00
) ++ Seq(
// SPARK-5270
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.api.java.JavaRDDLike.isEmpty")
[SPARK-5430] move treeReduce and treeAggregate from mllib to core We have seen many use cases of `treeAggregate`/`treeReduce` outside the ML domain. Maybe it is time to move them to Core. pwendell Author: Xiangrui Meng <meng@databricks.com> Closes #4228 from mengxr/SPARK-5430 and squashes the following commits: 20ad40d [Xiangrui Meng] exclude tree* from mima e89a43e [Xiangrui Meng] fix compile and update java doc 3ae1a4b [Xiangrui Meng] add treeReduce/treeAggregate to Python 6f948c5 [Xiangrui Meng] add treeReduce/treeAggregate to JavaRDDLike d600b6c [Xiangrui Meng] move treeReduce and treeAggregate to core
2015-01-28 20:26:03 -05:00
) ++ Seq(
// SPARK-5430
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.api.java.JavaRDDLike.treeReduce"),
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.api.java.JavaRDDLike.treeAggregate")
[SPARK-5297][Streaming] Fix Java file stream type erasure problem Current Java file stream doesn't support custom key/value type because of loss of type information, details can be seen in [SPARK-5297](https://issues.apache.org/jira/browse/SPARK-5297). Fix this problem by getting correct `ClassTag` from `Class[_]`. Author: jerryshao <saisai.shao@intel.com> Closes #4101 from jerryshao/SPARK-5297 and squashes the following commits: e022ca3 [jerryshao] Add Mima exclusion ecd61b8 [jerryshao] Fix Java fileInputStream type erasure problem
2015-01-21 02:37:47 -05:00
) ++ Seq(
// SPARK-5297 Java FileStream do not work with custom key/values
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.streaming.api.java.JavaStreamingContext.fileStream")
[SPARK-5315][Streaming] Fix reduceByWindow Java API not work bug `reduceByWindow` for Java API is actually not Java compatible, change to make it Java compatible. Current solution is to deprecate the old one and add a new API, but since old API actually is not correct, so is keeping the old one meaningful? just to keep the binary compatible? Also even adding new API still need to add to Mima exclusion, I'm not sure to change the API, or deprecate the old API and add a new one, which is the best solution? Author: jerryshao <saisai.shao@intel.com> Closes #4104 from jerryshao/SPARK-5315 and squashes the following commits: 5bc8987 [jerryshao] Address the comment c7aa1b4 [jerryshao] Deprecate the old one to keep binary compatible 8e9dc67 [jerryshao] Fix JavaDStream reduceByWindow signature error
2015-01-23 01:04:21 -05:00
) ++ Seq(
// SPARK-5315 Spark Streaming Java API returns Scala DStream
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.streaming.api.java.JavaDStreamLike.reduceByWindow")
[SPARK-5461] [graphx] Add isCheckpointed, getCheckpointedFiles methods to Graph Added the 2 methods to Graph and GraphImpl. Both make calls to the underlying vertex and edge RDDs. This is needed for another PR (for LDA): [https://github.com/apache/spark/pull/4047] Notes: * getCheckpointedFiles is plural and returns a Seq[String] instead of an Option[String]. * I attempted to test to make sure the methods returned the correct values after checkpointing. It did not work; I guess that checkpointing does not occur quickly enough? I noticed that there are not checkpointing tests for RDDs; is it just hard to test well? CC: rxin CC: mengxr (since related to LDA) Author: Joseph K. Bradley <joseph@databricks.com> Closes #4253 from jkbradley/graphx-checkpoint and squashes the following commits: b680148 [Joseph K. Bradley] added class tag to firstParent call in VertexRDDImpl.isCheckpointed, though not needed to compile 250810e [Joseph K. Bradley] In EdgeRDDImple, VertexRDDImpl, added transient back to partitionsRDD, and made isCheckpointed check firstParent instead of partitionsRDD 695b7a3 [Joseph K. Bradley] changed partitionsRDD in EdgeRDDImpl, VertexRDDImpl to be non-transient cc00767 [Joseph K. Bradley] added overrides for isCheckpointed, getCheckpointFile in EdgeRDDImpl, VertexRDDImpl. The corresponding Graph methods now work. 188665f [Joseph K. Bradley] improved documentation 235738c [Joseph K. Bradley] Added isCheckpointed and getCheckpointFiles to Graph, GraphImpl
2015-02-02 17:34:48 -05:00
) ++ 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")
[SPARK-4789] [SPARK-4942] [SPARK-5031] [mllib] Standardize ML Prediction APIs This is part (1a) of the updates from the design doc in [https://docs.google.com/document/d/1BH9el33kBX8JiDdgUJXdLW14CA2qhTCWIG46eXZVoJs] **UPDATE**: Most of the APIs are being kept private[spark] to allow further discussion. Here is a list of changes which are public: * new output columns: rawPrediction, probabilities * The “score” column is now called “rawPrediction” * Classifiers now provide numClasses * Params.get and .set are now protected instead of private[ml]. * ParamMap now has a size method. * new classes: LinearRegression, LinearRegressionModel * LogisticRegression now has an intercept. ### Sketch of APIs (most of which are private[spark] for now) Abstract classes for learning algorithms (+ corresponding Model abstractions): * Classifier (+ ClassificationModel) * ProbabilisticClassifier (+ ProbabilisticClassificationModel) * Regressor (+ RegressionModel) * Predictor (+ PredictionModel) * *For all of these*: * There is no strongly typed training-time API. * There is a strongly typed test-time (prediction) API which helps developers implement new algorithms. Concrete classes: learning algorithms * LinearRegression * LogisticRegression (updated to use new abstract classes) * Also, removed "score" in favor of "probability" output column. Changed BinaryClassificationEvaluator to match. (SPARK-5031) Other updates: * params.scala: Changed Params.set/get to be protected instead of private[ml] * This was needed for the example of defining a class from outside of the MLlib namespace. * VectorUDT: Will later change from private[spark] to public. * This is needed for outside users to write their own validateAndTransformSchema() methods using vectors. * Also, added equals() method.f * SPARK-4942 : ML Transformers should allow output cols to be turned on,off * Update validateAndTransformSchema * Update transform * (Updated examples, test suites according to other changes) New examples: * DeveloperApiExample.scala (example of defining algorithm from outside of the MLlib namespace) * Added Java version too Test Suites: * LinearRegressionSuite * LogisticRegressionSuite * + Java versions of above suites CC: mengxr etrain shivaram Author: Joseph K. Bradley <joseph@databricks.com> Closes #3637 from jkbradley/ml-api-part1 and squashes the following commits: 405bfb8 [Joseph K. Bradley] Last edits based on code review. Small cleanups fec348a [Joseph K. Bradley] Added JavaDeveloperApiExample.java and fixed other issues: Made developer API private[spark] for now. Added constructors Java can understand to specialized Param types. 8316d5e [Joseph K. Bradley] fixes after rebasing on master fc62406 [Joseph K. Bradley] fixed test suites after last commit bcb9549 [Joseph K. Bradley] Fixed issues after rebasing from master (after move from SchemaRDD to DataFrame) 9872424 [Joseph K. Bradley] fixed JavaLinearRegressionSuite.java Java sql api f542997 [Joseph K. Bradley] Added MIMA excludes for VectorUDT (now public), and added DeveloperApi annotation to it 216d199 [Joseph K. Bradley] fixed after sql datatypes PR got merged f549e34 [Joseph K. Bradley] Updates based on code review. Major ones are: * Created weakly typed Predictor.train() method which is called by fit() so that developers do not have to call schema validation or copy parameters. * Made Predictor.featuresDataType have a default value of VectorUDT. * NOTE: This could be dangerous since the FeaturesType type parameter cannot have a default value. 343e7bd [Joseph K. Bradley] added blanket mima exclude for ml package 82f340b [Joseph K. Bradley] Fixed bug in LogisticRegression (introduced in this PR). Fixed Java suites 0a16da9 [Joseph K. Bradley] Fixed Linear/Logistic RegressionSuites c3c8da5 [Joseph K. Bradley] small cleanup 934f97b [Joseph K. Bradley] Fixed bugs from previous commit. 1c61723 [Joseph K. Bradley] * Made ProbabilisticClassificationModel into a subclass of ClassificationModel. Also introduced ProbabilisticClassifier. * This was to support output column “probabilityCol” in transform(). 4e2f711 [Joseph K. Bradley] rat fix bc654e1 [Joseph K. Bradley] Added spark.ml LinearRegressionSuite 8d13233 [Joseph K. Bradley] Added methods: * Classifier: batch predictRaw() * Predictor: train() without paramMap ProbabilisticClassificationModel.predictProbabilities() * Java versions of all above batch methods + others 1680905 [Joseph K. Bradley] Added JavaLabeledPointSuite.java for spark.ml, and added constructor to LabeledPoint which defaults weight to 1.0 adbe50a [Joseph K. Bradley] * fixed LinearRegression train() to use embedded paramMap * added Predictor.predict(RDD[Vector]) method * updated Linear/LogisticRegressionSuites 58802e3 [Joseph K. Bradley] added train() to Predictor subclasses which does not take a ParamMap. 57d54ab [Joseph K. Bradley] * Changed semantics of Predictor.train() to merge the given paramMap with the embedded paramMap. * remove threshold_internal from logreg * Added Predictor.copy() * Extended LogisticRegressionSuite e433872 [Joseph K. Bradley] Updated docs. Added LabeledPointSuite to spark.ml 54b7b31 [Joseph K. Bradley] Fixed issue with logreg threshold being set correctly 0617d61 [Joseph K. Bradley] Fixed bug from last commit (sorting paramMap by parameter names in toString). Fixed bug in persisting logreg data. Added threshold_internal to logreg for faster test-time prediction (avoiding map lookup). 601e792 [Joseph K. Bradley] Modified ParamMap to sort parameters in toString. Cleaned up classes in class hierarchy, before implementing tests and examples. d705e87 [Joseph K. Bradley] Added LinearRegression and Regressor back from ml-api branch 52f4fde [Joseph K. Bradley] removing everything except for simple class hierarchy for classification d35bb5d [Joseph K. Bradley] fixed compilation issues, but have not added tests yet bfade12 [Joseph K. Bradley] Added lots of classes for new ML API:
2015-02-06 02:43:47 -05:00
) ++ 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")
[SPARK-5814][MLLIB][GRAPHX] Remove JBLAS from runtime The issue is discussed in https://issues.apache.org/jira/browse/SPARK-5669. Replacing all JBLAS usage by netlib-java gives us a simpler dependency tree and less license issues to worry about. I didn't touch the test scope in this PR. The user guide is not modified to avoid merge conflicts with branch-1.3. srowen ankurdave pwendell Author: Xiangrui Meng <meng@databricks.com> Closes #4699 from mengxr/SPARK-5814 and squashes the following commits: 48635c6 [Xiangrui Meng] move netlib-java version to parent pom ca21c74 [Xiangrui Meng] remove jblas from ml-guide 5f7767a [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-5814 c5c4183 [Xiangrui Meng] merge master 0f20cad [Xiangrui Meng] add mima excludes e53e9f4 [Xiangrui Meng] remove jblas from mllib runtime ceaa14d [Xiangrui Meng] replace jblas by netlib-java in graphx fa7c2ca [Xiangrui Meng] move jblas to test scope
2015-03-12 04:39:04 -04:00
) ++ 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")
SPARK-4682 [CORE] Consolidate various 'Clock' classes Another one from JoshRosen 's wish list. The first commit is much smaller and removes 2 of the 4 Clock classes. The second is much larger, necessary for consolidating the streaming one. I put together implementations in the way that seemed simplest. Almost all the change is standardizing class and method names. Author: Sean Owen <sowen@cloudera.com> Closes #4514 from srowen/SPARK-4682 and squashes the following commits: 5ed3a03 [Sean Owen] Javadoc Clock classes; make ManualClock private[spark] 169dd13 [Sean Owen] Add support for legacy org.apache.spark.streaming clock class names 277785a [Sean Owen] Reduce the net change in this patch by reversing some unnecessary syntax changes along the way b5e53df [Sean Owen] FakeClock -> ManualClock; getTime() -> getTimeMillis() 160863a [Sean Owen] Consolidate Streaming Clock class into common util Clock 7c956b2 [Sean Owen] Consolidate Clocks except for Streaming Clock
2015-02-19 18:35:23 -05:00
) ++ Seq(
// SPARK-4682
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.RealClock"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.Clock"),
ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.TestClock")
[SPARK-5922][GraphX]: Add diff(other: RDD[VertexId, VD]) in VertexRDD Changed method invocation of 'diff' to match that of 'innerJoin' and 'leftJoin' from VertexRDD[VD] to RDD[(VertexId, VD)]. This change maintains backwards compatibility and better unifies the VertexRDD methods to match each other. Author: Brennon York <brennon.york@capitalone.com> Closes #4733 from brennonyork/SPARK-5922 and squashes the following commits: e800f08 [Brennon York] fixed merge conflicts b9274af [Brennon York] fixed merge conflicts f86375c [Brennon York] fixed minor include line 398ddb4 [Brennon York] fixed merge conflicts aac1810 [Brennon York] updated to aggregateUsingIndex and added test to ensure that method works properly 2af0b88 [Brennon York] removed deprecation line 753c963 [Brennon York] fixed merge conflicts and set preference to use the diff(other: VertexRDD[VD]) method 2c678c6 [Brennon York] added mima exclude to exclude new public diff method from VertexRDD 93186f3 [Brennon York] added back the original diff method to sustain binary compatibility f18356e [Brennon York] changed method invocation of 'diff' to match that of 'innerJoin' and 'leftJoin' from VertexRDD[VD] to RDD[(VertexId, VD)]
2015-03-16 04:06:26 -04:00
) ++ Seq(
// SPARK-5922 Adding a generalized diff(other: RDD[(VertexId, VD)]) to VertexRDD
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.graphx.VertexRDD.diff")
Bumping version to 1.3.0-SNAPSHOT. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #3277 from vanzin/version-1.3 and squashes the following commits: 7c3c396 [Marcelo Vanzin] Added temp repo to sbt build. 5f404ff [Marcelo Vanzin] Add another exclusion. 19457e7 [Marcelo Vanzin] Update old version to 1.2, add temporary 1.2 repo. 3c8d705 [Marcelo Vanzin] Workaround for MIMA checks. e940810 [Marcelo Vanzin] Bumping version to 1.3.0-SNAPSHOT.
2014-11-19 00:24:18 -05:00
)
[HOTFIX] Fix broken Mima tests on the master branch By merging #2268, which bumped the Spark version to 1.2.0-SNAPSHOT, I inadvertently broke the Mima binary compatibility tests. The issue is that we were comparing 1.2.0-SNAPSHOT against Spark 1.0.0 without using any Mima excludes. The right long-term fix for this is probably to publish nightly snapshots on Maven central and change the master branch to test binary compatibility against the current release candidate branch's snapshots until that release is finalized. As a short-term fix until 1.1.0 is published on Maven central, I've configured the build to test the master branch for binary compatibility against the 1.1.0-RC4 jars. I'll loop back and remove the Apache staging repo as soon as 1.1.0 final is available. Author: Josh Rosen <joshrosen@apache.org> Closes #2315 from JoshRosen/mima-fix and squashes the following commits: 776bc2c [Josh Rosen] Add two excludes to workaround Mima annotation issues. ec90e21 [Josh Rosen] Add deploy and graphx to 1.2 MiMa excludes. 57569be [Josh Rosen] Fix MiMa tests in master branch; test against 1.1.0 RC.
2014-09-07 23:39:53 -04:00
case v if v.startsWith("1.2") =>
Seq(
MimaBuild.excludeSparkPackage("deploy"),
MimaBuild.excludeSparkPackage("graphx")
[SPARK-3418] Sparse Matrix support (CCS) and additional native BLAS operations added Local `SparseMatrix` support added in Compressed Column Storage (CCS) format in addition to Level-2 and Level-3 BLAS operations such as dgemv and dgemm respectively. BLAS doesn't support sparse matrix operations, therefore support for `SparseMatrix`-`DenseMatrix` multiplication and `SparseMatrix`-`DenseVector` implementations have been added. I will post performance comparisons in the comments momentarily. Author: Burak <brkyvz@gmail.com> Closes #2294 from brkyvz/SPARK-3418 and squashes the following commits: 88814ed [Burak] Hopefully fixed MiMa this time 47e49d5 [Burak] really fixed MiMa issue f0bae57 [Burak] [SPARK-3418] Fixed MiMa compatibility issues (excluded from check) 4b7dbec [Burak] 9/17 comments addressed 7af2f83 [Burak] sealed traits Vector and Matrix d3a8a16 [Burak] [SPARK-3418] Squashed missing alpha bug. 421045f [Burak] [SPARK-3418] New code review comments addressed f35a161 [Burak] [SPARK-3418] Code review comments addressed and multiplication further optimized 2508577 [Burak] [SPARK-3418] Fixed one more style issue d16e8a0 [Burak] [SPARK-3418] Fixed style issues and added documentation for methods 204a3f7 [Burak] [SPARK-3418] Fixed failing Matrix unit test 6025297 [Burak] [SPARK-3418] Fixed Scala-style errors dc7be71 [Burak] [SPARK-3418][MLlib] Matrix unit tests expanded with indexing and updating d2d5851 [Burak] [SPARK-3418][MLlib] Sparse Matrix support and additional native BLAS operations added
2014-09-19 01:18:51 -04:00
) ++
MimaBuild.excludeSparkClass("mllib.linalg.Matrix") ++
[MLlib] [SPARK-2885] DIMSUM: All-pairs similarity # All-pairs similarity via DIMSUM Compute all pairs of similar vectors using brute force approach, and also DIMSUM sampling approach. Laying down some notation: we are looking for all pairs of similar columns in an m x n RowMatrix whose entries are denoted a_ij, with the i’th row denoted r_i and the j’th column denoted c_j. There is an oversampling parameter labeled ɣ that should be set to 4 log(n)/s to get provably correct results (with high probability), where s is the similarity threshold. The algorithm is stated with a Map and Reduce, with proofs of correctness and efficiency in published papers [1] [2]. The reducer is simply the summation reducer. The mapper is more interesting, and is also the heart of the scheme. As an exercise, you should try to see why in expectation, the map-reduce below outputs cosine similarities. ![dimsumv2](https://cloud.githubusercontent.com/assets/3220351/3807272/d1d9514e-1c62-11e4-9f12-3cfdb1d78b3a.png) [1] Bosagh-Zadeh, Reza and Carlsson, Gunnar (2013), Dimension Independent Matrix Square using MapReduce, arXiv:1304.1467 http://arxiv.org/abs/1304.1467 [2] Bosagh-Zadeh, Reza and Goel, Ashish (2012), Dimension Independent Similarity Computation, arXiv:1206.2082 http://arxiv.org/abs/1206.2082 # Testing Tests for all invocations included. Added L1 and L2 norm computation to MultivariateStatisticalSummary since it was needed. Added tests for both of them. Author: Reza Zadeh <rizlar@gmail.com> Author: Xiangrui Meng <meng@databricks.com> Closes #1778 from rezazadeh/dimsumv2 and squashes the following commits: 404c64c [Reza Zadeh] Merge remote-tracking branch 'upstream/master' into dimsumv2 4eb71c6 [Reza Zadeh] Add excludes for normL1 and normL2 ee8bd65 [Reza Zadeh] Merge remote-tracking branch 'upstream/master' into dimsumv2 976ddd4 [Reza Zadeh] Broadcast colMags. Avoid div by zero. 3467cff [Reza Zadeh] Merge remote-tracking branch 'upstream/master' into dimsumv2 aea0247 [Reza Zadeh] Allow large thresholds to promote sparsity 9fe17c0 [Xiangrui Meng] organize imports 2196ba5 [Xiangrui Meng] Merge branch 'rezazadeh-dimsumv2' into dimsumv2 254ca08 [Reza Zadeh] Merge remote-tracking branch 'upstream/master' into dimsumv2 f2947e4 [Xiangrui Meng] some optimization 3c4cf41 [Xiangrui Meng] Merge branch 'master' into rezazadeh-dimsumv2 0e4eda4 [Reza Zadeh] Use partition index for RNG 251bb9c [Reza Zadeh] Documentation 25e9d0d [Reza Zadeh] Line length for style fb296f6 [Reza Zadeh] renamed to normL1 and normL2 3764983 [Reza Zadeh] Documentation e9c6791 [Reza Zadeh] New interface and documentation 613f261 [Reza Zadeh] Column magnitude summary 75a0b51 [Reza Zadeh] Use Ints instead of Longs in the shuffle 0f12ade [Reza Zadeh] Style changes eb1dc20 [Reza Zadeh] Use Double.PositiveInfinity instead of Double.Max f56a882 [Reza Zadeh] Remove changes to MultivariateOnlineSummarizer dbc55ba [Reza Zadeh] Make colMagnitudes a method in RowMatrix 41e8ece [Reza Zadeh] style changes 139c8e1 [Reza Zadeh] Syntax changes 029aa9c [Reza Zadeh] javadoc and new test 75edb25 [Reza Zadeh] All tests passing! 05e59b8 [Reza Zadeh] Add test 502ce52 [Reza Zadeh] new interface 654c4fb [Reza Zadeh] default methods 3726ca9 [Reza Zadeh] Remove MatrixAlgebra 6bebabb [Reza Zadeh] remove changes to MatrixSuite 5b8cd7d [Reza Zadeh] Initial files
2014-09-29 14:15:09 -04:00
MimaBuild.excludeSparkClass("mllib.linalg.Vector") ++
Seq(
SPARK-1767: Prefer HDFS-cached replicas when scheduling data-local tasks This change reorders the replicas returned by HadoopRDD#getPreferredLocations so that replicas cached by HDFS are at the start of the list. This requires Hadoop 2.5 or higher; previous versions of Hadoop do not expose the information needed to determine whether a replica is cached. Author: Colin Patrick Mccabe <cmccabe@cloudera.com> Closes #1486 from cmccabe/SPARK-1767 and squashes the following commits: 338d4f8 [Colin Patrick Mccabe] SPARK-1767: Prefer HDFS-cached replicas when scheduling data-local tasks
2014-10-02 03:29:31 -04:00
ProblemFilters.exclude[IncompatibleTemplateDefProblem](
"org.apache.spark.scheduler.TaskLocation"),
[MLlib] [SPARK-2885] DIMSUM: All-pairs similarity # All-pairs similarity via DIMSUM Compute all pairs of similar vectors using brute force approach, and also DIMSUM sampling approach. Laying down some notation: we are looking for all pairs of similar columns in an m x n RowMatrix whose entries are denoted a_ij, with the i’th row denoted r_i and the j’th column denoted c_j. There is an oversampling parameter labeled ɣ that should be set to 4 log(n)/s to get provably correct results (with high probability), where s is the similarity threshold. The algorithm is stated with a Map and Reduce, with proofs of correctness and efficiency in published papers [1] [2]. The reducer is simply the summation reducer. The mapper is more interesting, and is also the heart of the scheme. As an exercise, you should try to see why in expectation, the map-reduce below outputs cosine similarities. ![dimsumv2](https://cloud.githubusercontent.com/assets/3220351/3807272/d1d9514e-1c62-11e4-9f12-3cfdb1d78b3a.png) [1] Bosagh-Zadeh, Reza and Carlsson, Gunnar (2013), Dimension Independent Matrix Square using MapReduce, arXiv:1304.1467 http://arxiv.org/abs/1304.1467 [2] Bosagh-Zadeh, Reza and Goel, Ashish (2012), Dimension Independent Similarity Computation, arXiv:1206.2082 http://arxiv.org/abs/1206.2082 # Testing Tests for all invocations included. Added L1 and L2 norm computation to MultivariateStatisticalSummary since it was needed. Added tests for both of them. Author: Reza Zadeh <rizlar@gmail.com> Author: Xiangrui Meng <meng@databricks.com> Closes #1778 from rezazadeh/dimsumv2 and squashes the following commits: 404c64c [Reza Zadeh] Merge remote-tracking branch 'upstream/master' into dimsumv2 4eb71c6 [Reza Zadeh] Add excludes for normL1 and normL2 ee8bd65 [Reza Zadeh] Merge remote-tracking branch 'upstream/master' into dimsumv2 976ddd4 [Reza Zadeh] Broadcast colMags. Avoid div by zero. 3467cff [Reza Zadeh] Merge remote-tracking branch 'upstream/master' into dimsumv2 aea0247 [Reza Zadeh] Allow large thresholds to promote sparsity 9fe17c0 [Xiangrui Meng] organize imports 2196ba5 [Xiangrui Meng] Merge branch 'rezazadeh-dimsumv2' into dimsumv2 254ca08 [Reza Zadeh] Merge remote-tracking branch 'upstream/master' into dimsumv2 f2947e4 [Xiangrui Meng] some optimization 3c4cf41 [Xiangrui Meng] Merge branch 'master' into rezazadeh-dimsumv2 0e4eda4 [Reza Zadeh] Use partition index for RNG 251bb9c [Reza Zadeh] Documentation 25e9d0d [Reza Zadeh] Line length for style fb296f6 [Reza Zadeh] renamed to normL1 and normL2 3764983 [Reza Zadeh] Documentation e9c6791 [Reza Zadeh] New interface and documentation 613f261 [Reza Zadeh] Column magnitude summary 75a0b51 [Reza Zadeh] Use Ints instead of Longs in the shuffle 0f12ade [Reza Zadeh] Style changes eb1dc20 [Reza Zadeh] Use Double.PositiveInfinity instead of Double.Max f56a882 [Reza Zadeh] Remove changes to MultivariateOnlineSummarizer dbc55ba [Reza Zadeh] Make colMagnitudes a method in RowMatrix 41e8ece [Reza Zadeh] style changes 139c8e1 [Reza Zadeh] Syntax changes 029aa9c [Reza Zadeh] javadoc and new test 75edb25 [Reza Zadeh] All tests passing! 05e59b8 [Reza Zadeh] Add test 502ce52 [Reza Zadeh] new interface 654c4fb [Reza Zadeh] default methods 3726ca9 [Reza Zadeh] Remove MatrixAlgebra 6bebabb [Reza Zadeh] remove changes to MatrixSuite 5b8cd7d [Reza Zadeh] Initial files
2014-09-29 14:15:09 -04:00
// Added normL1 and normL2 to trait MultivariateStatisticalSummary
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.stat.MultivariateStatisticalSummary.normL1"),
ProblemFilters.exclude[MissingMethodProblem](
[SPARK-3613] Record only average block size in MapStatus for large stages This changes the way we send MapStatus from executors back to driver for large stages (>2000 tasks). For large stages, we no longer send one byte per block. Instead, we just send the average block size. This makes large jobs (tens of thousands of tasks) much more reliable since the driver no longer sends huge amount of data. Author: Reynold Xin <rxin@apache.org> Closes #2470 from rxin/mapstatus and squashes the following commits: 822ff54 [Reynold Xin] Code review feedback. 3b86f56 [Reynold Xin] Added MimaExclude. f89d182 [Reynold Xin] Fixed a bug in MapStatus 6a0401c [Reynold Xin] [SPARK-3613] Record only average block size in MapStatus for large stages.
2014-09-30 01:56:22 -04:00
"org.apache.spark.mllib.stat.MultivariateStatisticalSummary.normL2"),
// MapStatus should be private[spark]
ProblemFilters.exclude[IncompatibleTemplateDefProblem](
SPARK-3874: Provide stable TaskContext API This is a small number of clean-up changes on top of #2782. Closes #2782. Author: Prashant Sharma <prashant.s@imaginea.com> Author: Patrick Wendell <pwendell@gmail.com> Closes #2803 from pwendell/pr-2782 and squashes the following commits: 56d5b7a [Patrick Wendell] Minor clean-up 44089ec [Patrick Wendell] Clean-up the TaskContext API. ed551ce [Prashant Sharma] Fixed a typo df261d0 [Prashant Sharma] Josh's suggestion facf3b1 [Prashant Sharma] Fixed the mima issue. 7ecc2fe [Prashant Sharma] CR, Moved implementations to TaskContextImpl bbd9e05 [Prashant Sharma] adding missed out files to git. ef633f5 [Prashant Sharma] SPARK-3874, Provide stable TaskContext API
2014-10-16 21:38:45 -04:00
"org.apache.spark.scheduler.MapStatus"),
[SPARK-3453] Netty-based BlockTransferService, extracted from Spark core This PR encapsulates #2330, which is itself a continuation of #2240. The first goal of this PR is to provide an alternate, simpler implementation of the ConnectionManager which is based on Netty. In addition to this goal, however, we want to resolve [SPARK-3796](https://issues.apache.org/jira/browse/SPARK-3796), which calls for a standalone shuffle service which can be integrated into the YARN NodeManager, Standalone Worker, or on its own. This PR makes the first step in this direction by ensuring that the actual Netty service is as small as possible and extracted from Spark core. Given this, we should be able to construct this standalone jar which can be included in other JVMs without incurring significant dependency or runtime issues. The actual work to ensure that such a standalone shuffle service would work in Spark will be left for a future PR, however. In order to minimize dependencies and allow for the service to be long-running (possibly much longer-running than Spark, and possibly having to support multiple version of Spark simultaneously), the entire service has been ported to Java, where we have full control over the binary compatibility of the components and do not depend on the Scala runtime or version. These issues: have been addressed by folding in #2330: SPARK-3453: Refactor Netty module to use BlockTransferService interface SPARK-3018: Release all buffers upon task completion/failure SPARK-3002: Create a connection pool and reuse clients across different threads SPARK-3017: Integration tests and unit tests for connection failures SPARK-3049: Make sure client doesn't block when server/connection has error(s) SPARK-3502: SO_RCVBUF and SO_SNDBUF should be bootstrap childOption, not option SPARK-3503: Disable thread local cache in PooledByteBufAllocator TODO before mergeable: - [x] Implement uploadBlock() - [x] Unit tests for RPC side of code - [x] Performance testing (see comments [here](https://github.com/apache/spark/pull/2753#issuecomment-59475022)) - [x] Turn OFF by default (currently on for unit testing) Author: Reynold Xin <rxin@apache.org> Author: Aaron Davidson <aaron@databricks.com> Author: cocoatomo <cocoatomo77@gmail.com> Author: Patrick Wendell <pwendell@gmail.com> Author: Prashant Sharma <prashant.s@imaginea.com> Author: Davies Liu <davies.liu@gmail.com> Author: Anand Avati <avati@redhat.com> Closes #2753 from aarondav/netty and squashes the following commits: cadfd28 [Aaron Davidson] Turn netty off by default d7be11b [Aaron Davidson] Turn netty on by default 4a204b8 [Aaron Davidson] Fail block fetches if client connection fails 2b0d1c0 [Aaron Davidson] 100ch 0c5bca2 [Aaron Davidson] Merge branch 'master' of https://github.com/apache/spark into netty 14e37f7 [Aaron Davidson] Address Reynold's comments 8dfcceb [Aaron Davidson] Merge branch 'master' of https://github.com/apache/spark into netty 322dfc1 [Aaron Davidson] Address Reynold's comments, including major rename e5675a4 [Aaron Davidson] Fail outstanding RPCs as well ccd4959 [Aaron Davidson] Don't throw exception if client immediately fails 9da0bc1 [Aaron Davidson] Add RPC unit tests d236dfd [Aaron Davidson] Remove no-op serializer :) 7b7a26c [Aaron Davidson] Fix Nio compile issue dd420fd [Aaron Davidson] Merge branch 'master' of https://github.com/apache/spark into netty-test 939f276 [Aaron Davidson] Attempt to make comm. bidirectional aa58f67 [cocoatomo] [SPARK-3909][PySpark][Doc] A corrupted format in Sphinx documents and building warnings 8dc1ded [cocoatomo] [SPARK-3867][PySpark] ./python/run-tests failed when it run with Python 2.6 and unittest2 is not installed 5b5dbe6 [Prashant Sharma] [SPARK-2924] Required by scala 2.11, only one fun/ctor amongst overriden alternatives, can have default argument(s). 2c5d9dc [Patrick Wendell] HOTFIX: Fix build issue with Akka 2.3.4 upgrade. 020691e [Davies Liu] [SPARK-3886] [PySpark] use AutoBatchedSerializer by default ae4083a [Anand Avati] [SPARK-2805] Upgrade Akka to 2.3.4 29c6dcf [Aaron Davidson] [SPARK-3453] Netty-based BlockTransferService, extracted from Spark core f7e7568 [Reynold Xin] Fixed spark.shuffle.io.receiveBuffer setting. 5d98ce3 [Reynold Xin] Flip buffer. f6c220d [Reynold Xin] Merge with latest master. 407e59a [Reynold Xin] Fix style violation. a0518c7 [Reynold Xin] Implemented block uploads. 4b18db2 [Reynold Xin] Copy the buffer in fetchBlockSync. bec4ea2 [Reynold Xin] Removed OIO and added num threads settings. 1bdd7ee [Reynold Xin] Fixed tests. d68f328 [Reynold Xin] Logging close() in case close() fails. f63fb4c [Reynold Xin] Add more debug message. 6afc435 [Reynold Xin] Added logging. c066309 [Reynold Xin] Implement java.io.Closeable interface. 519d64d [Reynold Xin] Mark private package visibility and MimaExcludes. f0a16e9 [Reynold Xin] Fixed test hanging. 14323a5 [Reynold Xin] Removed BlockManager.getLocalShuffleFromDisk. b2f3281 [Reynold Xin] Added connection pooling. d23ed7b [Reynold Xin] Incorporated feedback from Norman: - use same pool for boss and worker - remove ioratio - disable caching of byte buf allocator - childoption sendbuf/receivebuf - fire exception through pipeline 9e0cb87 [Reynold Xin] Fixed BlockClientHandlerSuite 5cd33d7 [Reynold Xin] Fixed style violation. cb589ec [Reynold Xin] Added more test cases covering cleanup when fault happens in ShuffleBlockFetcherIteratorSuite 1be4e8e [Reynold Xin] Shorten NioManagedBuffer and NettyManagedBuffer class names. 108c9ed [Reynold Xin] Forgot to add TestSerializer to the commit list. b5c8d1f [Reynold Xin] Fixed ShuffleBlockFetcherIteratorSuite. 064747b [Reynold Xin] Reference count buffers and clean them up properly. 2b44cf1 [Reynold Xin] Added more documentation. 1760d32 [Reynold Xin] Use Epoll.isAvailable in BlockServer as well. 165eab1 [Reynold Xin] [SPARK-3453] Refactor Netty module to use BlockTransferService.
2014-10-29 14:27:07 -04:00
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.network.netty.PathResolver"),
ProblemFilters.exclude[MissingClassProblem](
"org.apache.spark.network.netty.client.BlockClientListener"),
SPARK-3874: Provide stable TaskContext API This is a small number of clean-up changes on top of #2782. Closes #2782. Author: Prashant Sharma <prashant.s@imaginea.com> Author: Patrick Wendell <pwendell@gmail.com> Closes #2803 from pwendell/pr-2782 and squashes the following commits: 56d5b7a [Patrick Wendell] Minor clean-up 44089ec [Patrick Wendell] Clean-up the TaskContext API. ed551ce [Prashant Sharma] Fixed a typo df261d0 [Prashant Sharma] Josh's suggestion facf3b1 [Prashant Sharma] Fixed the mima issue. 7ecc2fe [Prashant Sharma] CR, Moved implementations to TaskContextImpl bbd9e05 [Prashant Sharma] adding missed out files to git. ef633f5 [Prashant Sharma] SPARK-3874, Provide stable TaskContext API
2014-10-16 21:38:45 -04:00
// TaskContext was promoted to Abstract class
ProblemFilters.exclude[AbstractClassProblem](
[SPARK-4084] Reuse sort key in Sorter Sorter uses generic-typed key for sorting. When data is large, it creates lots of key objects, which is not efficient. We should reuse the key in Sorter for memory efficiency. This change is part of the petabyte sort implementation from rxin . The `Sorter` class was written in Java and marked package private. So it is only available to `org.apache.spark.util.collection`. I renamed it to `TimSort` and add a simple wrapper of it, still called `Sorter`, in Scala, which is `private[spark]`. The benchmark code is updated, which now resets the array before each run. Here is the result on sorting primitive Int arrays of size 25 million using Sorter: ~~~ [info] - Sorter benchmark for key-value pairs !!! IGNORED !!! Java Arrays.sort() on non-primitive int array: Took 13237 ms Java Arrays.sort() on non-primitive int array: Took 13320 ms Java Arrays.sort() on non-primitive int array: Took 15718 ms Java Arrays.sort() on non-primitive int array: Took 13283 ms Java Arrays.sort() on non-primitive int array: Took 13267 ms Java Arrays.sort() on non-primitive int array: Took 15122 ms Java Arrays.sort() on non-primitive int array: Took 15495 ms Java Arrays.sort() on non-primitive int array: Took 14877 ms Java Arrays.sort() on non-primitive int array: Took 16429 ms Java Arrays.sort() on non-primitive int array: Took 14250 ms Java Arrays.sort() on non-primitive int array: (13878 ms first try, 14499 ms average) Java Arrays.sort() on primitive int array: Took 2683 ms Java Arrays.sort() on primitive int array: Took 2683 ms Java Arrays.sort() on primitive int array: Took 2701 ms Java Arrays.sort() on primitive int array: Took 2746 ms Java Arrays.sort() on primitive int array: Took 2685 ms Java Arrays.sort() on primitive int array: Took 2735 ms Java Arrays.sort() on primitive int array: Took 2669 ms Java Arrays.sort() on primitive int array: Took 2693 ms Java Arrays.sort() on primitive int array: Took 2680 ms Java Arrays.sort() on primitive int array: Took 2642 ms Java Arrays.sort() on primitive int array: (2948 ms first try, 2691 ms average) Sorter without key reuse on primitive int array: Took 10732 ms Sorter without key reuse on primitive int array: Took 12482 ms Sorter without key reuse on primitive int array: Took 10718 ms Sorter without key reuse on primitive int array: Took 12650 ms Sorter without key reuse on primitive int array: Took 10747 ms Sorter without key reuse on primitive int array: Took 10783 ms Sorter without key reuse on primitive int array: Took 12721 ms Sorter without key reuse on primitive int array: Took 10604 ms Sorter without key reuse on primitive int array: Took 10622 ms Sorter without key reuse on primitive int array: Took 11843 ms Sorter without key reuse on primitive int array: (11089 ms first try, 11390 ms average) Sorter with key reuse on primitive int array: Took 5141 ms Sorter with key reuse on primitive int array: Took 5298 ms Sorter with key reuse on primitive int array: Took 5066 ms Sorter with key reuse on primitive int array: Took 5164 ms Sorter with key reuse on primitive int array: Took 5203 ms Sorter with key reuse on primitive int array: Took 5274 ms Sorter with key reuse on primitive int array: Took 5186 ms Sorter with key reuse on primitive int array: Took 5159 ms Sorter with key reuse on primitive int array: Took 5164 ms Sorter with key reuse on primitive int array: Took 5078 ms Sorter with key reuse on primitive int array: (5311 ms first try, 5173 ms average) ~~~ So with key reuse, it is faster and less likely to trigger GC. Author: Xiangrui Meng <meng@databricks.com> Author: Reynold Xin <rxin@apache.org> Closes #2937 from mengxr/SPARK-4084 and squashes the following commits: d73c3d0 [Xiangrui Meng] address comments 0b7b682 [Xiangrui Meng] fix mima a72f53c [Xiangrui Meng] update timeIt 38ba50c [Xiangrui Meng] update timeIt 720f731 [Xiangrui Meng] add doc about JIT specialization 78f2879 [Xiangrui Meng] update tests 7de2efd [Xiangrui Meng] update the Sorter benchmark code to be correct 8626356 [Xiangrui Meng] add prepare to timeIt and update testsin SorterSuite 5f0d530 [Xiangrui Meng] update method modifiers of SortDataFormat 6ffbe66 [Xiangrui Meng] rename Sorter to TimSort and add a Scala wrapper that is private[spark] b00db4d [Xiangrui Meng] doc and tests cf94e8a [Xiangrui Meng] renaming 464ddce [Reynold Xin] cherry-pick rxin's commit
2014-10-28 18:14:41 -04:00
"org.apache.spark.TaskContext"),
ProblemFilters.exclude[IncompatibleTemplateDefProblem](
"org.apache.spark.util.collection.SortDataFormat")
[SPARK-3902] [SPARK-3590] Stabilize AsynRDDActions and add Java API This PR adds a Java API for AsyncRDDActions and promotes the API from `Experimental` to stable. Author: Josh Rosen <joshrosen@apache.org> Author: Josh Rosen <joshrosen@databricks.com> Closes #2760 from JoshRosen/async-rdd-actions-in-java and squashes the following commits: 0d45fbc [Josh Rosen] Whitespace fix. ad3ae53 [Josh Rosen] Merge remote-tracking branch 'origin/master' into async-rdd-actions-in-java c0153a5 [Josh Rosen] Remove unused variable. e8e2867 [Josh Rosen] Updates based on Marcelo's review feedback 7a1417f [Josh Rosen] Removed unnecessary java.util import. 6f8f6ac [Josh Rosen] Fix import ordering. ff28e49 [Josh Rosen] Add MiMa excludes and fix a scalastyle error. 346e46e [Josh Rosen] [SPARK-3902] Stabilize AsyncRDDActions; add Java API.
2014-10-19 23:02:31 -04:00
) ++ 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")
[SPARK-3822] Executor scaling mechanism for Yarn This is part of a broader effort to enable dynamic scaling of executors ([SPARK-3174](https://issues.apache.org/jira/browse/SPARK-3174)). This is intended to work alongside SPARK-3795 (#2746), SPARK-3796 and SPARK-3797, but is functionally independently of these other issues. The logic is built on top of PraveenSeluka's changes at #2798. This is different from the changes there in a few major ways: (1) the mechanism is implemented within the existing scheduler backend framework rather than in new `Actor` classes. This also introduces a parent abstract class `YarnSchedulerBackend` to encapsulate common logic to communicate with the Yarn `ApplicationMaster`. (2) The interface of requesting executors exposed to the `SparkContext` is the same, but the communication between the scheduler backend and the AM uses total number executors desired instead of an incremental number. This is discussed in #2746 and explained in the comments in the code. I have tested this significantly on a stable Yarn cluster. ------------ A remaining task for this issue is to tone down the error messages emitted when an executor is removed. Currently, `SparkContext` and its components react as if the executor has failed, resulting in many scary error messages and eventual timeouts. While it's not strictly necessary to fix this as of the first-cut implementation of this mechanism, it would be good to add logic to distinguish this case. I prefer to address this in a separate PR. I have filed a separate JIRA for this task at SPARK-4134. Author: Andrew Or <andrew@databricks.com> Author: Andrew Or <andrewor14@gmail.com> Closes #2840 from andrewor14/yarn-scaling-mechanism and squashes the following commits: 485863e [Andrew Or] Minor log message changes 4920be8 [Andrew Or] Clarify that public API is only for Yarn mode for now 1c57804 [Andrew Or] Reword a few comments + other review comments 6321140 [Andrew Or] Merge branch 'master' of github.com:apache/spark into yarn-scaling-mechanism 02836c0 [Andrew Or] Limit scope of synchronization 4e2ed7f [Andrew Or] Fix bug: keep track of removed executors properly 73ade46 [Andrew Or] Wording changes (minor) 2a7a6da [Andrew Or] Add `sc.killExecutor` as a shorthand (minor) 665f229 [Andrew Or] Mima excludes 79aa2df [Andrew Or] Simplify the request interface by asking for a total 04f625b [Andrew Or] Fix race condition that causes over-allocation of executors f4783f8 [Andrew Or] Change the semantics of requesting executors 005a124 [Andrew Or] Fix tests 4628b16 [Andrew Or] Merge branch 'master' of github.com:apache/spark into yarn-scaling-mechanism db4a679 [Andrew Or] Merge branch 'master' of github.com:apache/spark into yarn-scaling-mechanism 572f5c5 [Andrew Or] Unused import (minor) f30261c [Andrew Or] Kill multiple executors rather than one at a time de260d9 [Andrew Or] Simplify by skipping useless null check 9c52542 [Andrew Or] Simplify by skipping the TaskSchedulerImpl 97dd1a8 [Andrew Or] Merge branch 'master' of github.com:apache/spark into yarn-scaling-mechanism d987b3e [Andrew Or] Move addWebUIFilters to Yarn scheduler backend 7b76d0a [Andrew Or] Expose mechanism in SparkContext as developer API 47466cd [Andrew Or] Refactor common Yarn scheduler backend logic c4dfaac [Andrew Or] Avoid thrashing when removing executors 53e8145 [Andrew Or] Start yarn actor early to listen for AM registration message bbee669 [Andrew Or] Add mechanism in yarn client mode
2014-10-29 17:01:00 -04:00
) ++ Seq(
// SPARK-3822
ProblemFilters.exclude[IncompatibleResultTypeProblem](
"org.apache.spark.SparkContext.org$apache$spark$SparkContext$$createTaskScheduler")
SPARK-1209 [CORE] (Take 2) SparkHadoop{MapRed,MapReduce}Util should not use package org.apache.hadoop andrewor14 Another try at SPARK-1209, to address https://github.com/apache/spark/pull/2814#issuecomment-61197619 I successfully tested with `mvn -Dhadoop.version=1.0.4 -DskipTests clean package; mvn -Dhadoop.version=1.0.4 test` I assume that is what failed Jenkins last time. I also tried `-Dhadoop.version1.2.1` and `-Phadoop-2.4 -Pyarn -Phive` for more coverage. So this is why the class was put in `org.apache.hadoop` to begin with, I assume. One option is to leave this as-is for now and move it only when Hadoop 1.0.x support goes away. This is the other option, which adds a call to force the constructor to be public at run-time. It's probably less surprising than putting Spark code in `org.apache.hadoop`, but, does involve reflection. A `SecurityManager` might forbid this, but it would forbid a lot of stuff Spark does. This would also only affect Hadoop 1.0.x it seems. Author: Sean Owen <sowen@cloudera.com> Closes #3048 from srowen/SPARK-1209 and squashes the following commits: 0d48f4b [Sean Owen] For Hadoop 1.0.x, make certain constructors public, which were public in later versions 466e179 [Sean Owen] Disable MIMA warnings resulting from moving the class -- this was also part of the PairRDDFunctions type hierarchy though? eb61820 [Sean Owen] Move SparkHadoopMapRedUtil / SparkHadoopMapReduceUtil from org.apache.hadoop to org.apache.spark
2014-11-10 01:11:20 -05:00
) ++ 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")
[SPARK-4062][Streaming]Add ReliableKafkaReceiver in Spark Streaming Kafka connector Add ReliableKafkaReceiver in Kafka connector to prevent data loss if WAL in Spark Streaming is enabled. Details and design doc can be seen in [SPARK-4062](https://issues.apache.org/jira/browse/SPARK-4062). Author: jerryshao <saisai.shao@intel.com> Author: Tathagata Das <tathagata.das1565@gmail.com> Author: Saisai Shao <saisai.shao@intel.com> Closes #2991 from jerryshao/kafka-refactor and squashes the following commits: 5461f1c [Saisai Shao] Merge pull request #8 from tdas/kafka-refactor3 eae4ad6 [Tathagata Das] Refectored KafkaStreamSuiteBased to eliminate KafkaTestUtils and made Java more robust. fab14c7 [Tathagata Das] minor update. 149948b [Tathagata Das] Fixed mistake 14630aa [Tathagata Das] Minor updates. d9a452c [Tathagata Das] Minor updates. ec2e95e [Tathagata Das] Removed the receiver's locks and essentially reverted to Saisai's original design. 2a20a01 [jerryshao] Address some comments 9f636b3 [Saisai Shao] Merge pull request #5 from tdas/kafka-refactor b2b2f84 [Tathagata Das] Refactored Kafka receiver logic and Kafka testsuites e501b3c [jerryshao] Add Mima excludes b798535 [jerryshao] Fix the missed issue e5e21c1 [jerryshao] Change to while loop ea873e4 [jerryshao] Further address the comments 98f3d07 [jerryshao] Fix comment style 4854ee9 [jerryshao] Address all the comments 96c7a1d [jerryshao] Update the ReliableKafkaReceiver unit test 8135d31 [jerryshao] Fix flaky test a949741 [jerryshao] Address the comments 16bfe78 [jerryshao] Change the ordering of imports 0894aef [jerryshao] Add some comments 77c3e50 [jerryshao] Code refactor and add some unit tests dd9aeeb [jerryshao] Initial commit for reliable Kafka receiver
2014-11-14 17:33:37 -05:00
) ++ Seq(
// SPARK-4062
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.streaming.kafka.KafkaReceiver#MessageHandler.this")
[MLlib] [SPARK-2885] DIMSUM: All-pairs similarity # All-pairs similarity via DIMSUM Compute all pairs of similar vectors using brute force approach, and also DIMSUM sampling approach. Laying down some notation: we are looking for all pairs of similar columns in an m x n RowMatrix whose entries are denoted a_ij, with the i’th row denoted r_i and the j’th column denoted c_j. There is an oversampling parameter labeled ɣ that should be set to 4 log(n)/s to get provably correct results (with high probability), where s is the similarity threshold. The algorithm is stated with a Map and Reduce, with proofs of correctness and efficiency in published papers [1] [2]. The reducer is simply the summation reducer. The mapper is more interesting, and is also the heart of the scheme. As an exercise, you should try to see why in expectation, the map-reduce below outputs cosine similarities. ![dimsumv2](https://cloud.githubusercontent.com/assets/3220351/3807272/d1d9514e-1c62-11e4-9f12-3cfdb1d78b3a.png) [1] Bosagh-Zadeh, Reza and Carlsson, Gunnar (2013), Dimension Independent Matrix Square using MapReduce, arXiv:1304.1467 http://arxiv.org/abs/1304.1467 [2] Bosagh-Zadeh, Reza and Goel, Ashish (2012), Dimension Independent Similarity Computation, arXiv:1206.2082 http://arxiv.org/abs/1206.2082 # Testing Tests for all invocations included. Added L1 and L2 norm computation to MultivariateStatisticalSummary since it was needed. Added tests for both of them. Author: Reza Zadeh <rizlar@gmail.com> Author: Xiangrui Meng <meng@databricks.com> Closes #1778 from rezazadeh/dimsumv2 and squashes the following commits: 404c64c [Reza Zadeh] Merge remote-tracking branch 'upstream/master' into dimsumv2 4eb71c6 [Reza Zadeh] Add excludes for normL1 and normL2 ee8bd65 [Reza Zadeh] Merge remote-tracking branch 'upstream/master' into dimsumv2 976ddd4 [Reza Zadeh] Broadcast colMags. Avoid div by zero. 3467cff [Reza Zadeh] Merge remote-tracking branch 'upstream/master' into dimsumv2 aea0247 [Reza Zadeh] Allow large thresholds to promote sparsity 9fe17c0 [Xiangrui Meng] organize imports 2196ba5 [Xiangrui Meng] Merge branch 'rezazadeh-dimsumv2' into dimsumv2 254ca08 [Reza Zadeh] Merge remote-tracking branch 'upstream/master' into dimsumv2 f2947e4 [Xiangrui Meng] some optimization 3c4cf41 [Xiangrui Meng] Merge branch 'master' into rezazadeh-dimsumv2 0e4eda4 [Reza Zadeh] Use partition index for RNG 251bb9c [Reza Zadeh] Documentation 25e9d0d [Reza Zadeh] Line length for style fb296f6 [Reza Zadeh] renamed to normL1 and normL2 3764983 [Reza Zadeh] Documentation e9c6791 [Reza Zadeh] New interface and documentation 613f261 [Reza Zadeh] Column magnitude summary 75a0b51 [Reza Zadeh] Use Ints instead of Longs in the shuffle 0f12ade [Reza Zadeh] Style changes eb1dc20 [Reza Zadeh] Use Double.PositiveInfinity instead of Double.Max f56a882 [Reza Zadeh] Remove changes to MultivariateOnlineSummarizer dbc55ba [Reza Zadeh] Make colMagnitudes a method in RowMatrix 41e8ece [Reza Zadeh] style changes 139c8e1 [Reza Zadeh] Syntax changes 029aa9c [Reza Zadeh] javadoc and new test 75edb25 [Reza Zadeh] All tests passing! 05e59b8 [Reza Zadeh] Add test 502ce52 [Reza Zadeh] new interface 654c4fb [Reza Zadeh] default methods 3726ca9 [Reza Zadeh] Remove MatrixAlgebra 6bebabb [Reza Zadeh] remove changes to MatrixSuite 5b8cd7d [Reza Zadeh] Initial files
2014-09-29 14:15:09 -04:00
)
[SPARK-3433][BUILD] Fix for Mima false-positives with @DeveloperAPI and @Experimental annotations. Actually false positive reported was due to mima generator not picking up the new jars in presence of old jars(theoretically this should not have happened.). So as a workaround, ran them both separately and just append them together. Author: Prashant Sharma <prashant@apache.org> Author: Prashant Sharma <prashant.s@imaginea.com> Closes #2285 from ScrapCodes/mima-fix and squashes the following commits: 093c76f [Prashant Sharma] Update mima 59012a8 [Prashant Sharma] Update mima 35b6c71 [Prashant Sharma] SPARK-3433 Fix for Mima false-positives with @DeveloperAPI and @Experimental annotations.
2014-09-16 00:14:00 -04:00
[SPARK-2549] Functions defined inside of other functions trigger failures Author: Prashant Sharma <prashant.s@imaginea.com> 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
2014-07-23 20:12:28 -04:00
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"),
SPARK-2636: Expose job ID in JobWaiter API This PR adds the async actions to the Java API. User can call these async actions to get the FutureAction and use JobWaiter (for SimpleFutureAction) to retrieve job Id. Author: lirui <rui.li@intel.com> Closes #2176 from lirui-intel/SPARK-2636 and squashes the following commits: ccaafb7 [lirui] SPARK-2636: fix java doc 5536d55 [lirui] SPARK-2636: mark the async API as experimental e2e01d5 [lirui] SPARK-2636: add mima exclude 0ca320d [lirui] SPARK-2636: fix method name & javadoc 3fa39f7 [lirui] SPARK-2636: refine the patch af4f5d9 [lirui] SPARK-2636: remove unused imports 843276c [lirui] SPARK-2636: only keep foreachAsync in the java API fbf5744 [lirui] SPARK-2636: add more async actions for java api 1b25abc [lirui] SPARK-2636: expose some fields in JobWaiter d09f732 [lirui] SPARK-2636: fix build eb1ee79 [lirui] SPARK-2636: change some parameters in SimpleFutureAction to member field 6e2b87b [lirui] SPARK-2636: add java API for async actions
2014-09-02 02:28:19 -04:00
// Should probably mark this as Experimental
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.api.java.JavaRDDLike.foreachAsync"),
[SPARK-2549] Functions defined inside of other functions trigger failures Author: Prashant Sharma <prashant.s@imaginea.com> 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
2014-07-23 20:12:28 -04:00
// 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"),
[SPARK-2288] Hide ShuffleBlockManager behind ShuffleManager By Hiding the shuffleblockmanager behind Shufflemanager, we decouple the shuffle data's block mapping management work from Diskblockmananger. This give a more clear interface and more easy for other shuffle manager to implement their own block management logic. the jira ticket have more details. Author: Raymond Liu <raymond.liu@intel.com> Closes #1241 from colorant/shuffle and squashes the following commits: 0e01ae3 [Raymond Liu] Move ShuffleBlockmanager behind shuffleManager
2014-08-30 02:05:18 -04:00
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.storage.DiskStore.getValues"),
[SPARK-2549] Functions defined inside of other functions trigger failures Author: Prashant Sharma <prashant.s@imaginea.com> 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
2014-07-23 20:12:28 -04:00
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.storage.MemoryStore.Entry")
) ++
[SPARK-3045] Make Serializer interface Java friendly Author: Reynold Xin <rxin@apache.org> Closes #1948 from rxin/kryo and squashes the following commits: a3a80d8 [Reynold Xin] [SPARK-3046] use executor's class loader as the default serializer classloader 3d13277 [Reynold Xin] Reverted that in TestJavaSerializerImpl too. 196f3dc [Reynold Xin] Ok one more commit to revert the classloader change. c49b50c [Reynold Xin] Removed JavaSerializer change. afbf37d [Reynold Xin] Moved the test case also. a2e693e [Reynold Xin] Removed the Kryo bug fix from this pull request. c81bd6c [Reynold Xin] Use defaultClassLoader when executing user specified custom registrator. 68f261e [Reynold Xin] Added license check excludes. 0c28179 [Reynold Xin] [SPARK-3045] Make Serializer interface Java friendly [SPARK-3046] Set executor's class loader as the default serializer class loader
2014-08-16 02:12:34 -04:00
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")
)++
[SPARK-2549] Functions defined inside of other functions trigger failures Author: Prashant Sharma <prashant.s@imaginea.com> 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
2014-07-23 20:12:28 -04:00
Seq(
[SPARK-1777] Prevent OOMs from single partitions **Problem.** When caching, we currently unroll the entire RDD partition before making sure we have enough free memory. This is a common cause for OOMs especially when (1) the BlockManager has little free space left in memory, and (2) the partition is large. **Solution.** We maintain a global memory pool of `M` bytes shared across all threads, similar to the way we currently manage memory for shuffle aggregation. Then, while we unroll each partition, periodically check if there is enough space to continue. If not, drop enough RDD blocks to ensure we have at least `M` bytes to work with, then try again. If we still don't have enough space to unroll the partition, give up and drop the block to disk directly if applicable. **New configurations.** - `spark.storage.bufferFraction` - the value of `M` as a fraction of the storage memory. (default: 0.2) - `spark.storage.safetyFraction` - a margin of safety in case size estimation is slightly off. This is the equivalent of the existing `spark.shuffle.safetyFraction`. (default 0.9) For more detail, see the [design document](https://issues.apache.org/jira/secure/attachment/12651793/spark-1777-design-doc.pdf). Tests pending for performance and memory usage patterns. Author: Andrew Or <andrewor14@gmail.com> Closes #1165 from andrewor14/them-rdd-memories and squashes the following commits: e77f451 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories c7c8832 [Andrew Or] Simplify logic + update a few comments 269d07b [Andrew Or] Very minor changes to tests 6645a8a [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories b7e165c [Andrew Or] Add new tests for unrolling blocks f12916d [Andrew Or] Slightly clean up tests 71672a7 [Andrew Or] Update unrollSafely tests 369ad07 [Andrew Or] Correct ensureFreeSpace and requestMemory behavior f4d035c [Andrew Or] Allow one thread to unroll multiple blocks a66fbd2 [Andrew Or] Rename a few things + update comments 68730b3 [Andrew Or] Fix weird scalatest behavior e40c60d [Andrew Or] Fix MIMA excludes ff77aa1 [Andrew Or] Fix tests 1a43c06 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories b9a6eee [Andrew Or] Simplify locking behavior on unrollMemoryMap ed6cda4 [Andrew Or] Formatting fix (super minor) f9ff82e [Andrew Or] putValues -> putIterator + putArray beb368f [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories 8448c9b [Andrew Or] Fix tests a49ba4d [Andrew Or] Do not expose unroll memory check period 69bc0a5 [Andrew Or] Always synchronize on putLock before unrollMemoryMap 3f5a083 [Andrew Or] Simplify signature of ensureFreeSpace dce55c8 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories 8288228 [Andrew Or] Synchronize put and unroll properly 4f18a3d [Andrew Or] bufferFraction -> unrollFraction 28edfa3 [Andrew Or] Update a few comments / log messages 728323b [Andrew Or] Do not synchronize every 1000 elements 5ab2329 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories 129c441 [Andrew Or] Fix bug: Use toArray rather than array 9a65245 [Andrew Or] Update a few comments + minor control flow changes 57f8d85 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories abeae4f [Andrew Or] Add comment clarifying the MEMORY_AND_DISK case 3dd96aa [Andrew Or] AppendOnlyBuffer -> Vector (+ a few small changes) f920531 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories 0871835 [Andrew Or] Add an effective storage level interface to BlockManager 64e7d4c [Andrew Or] Add/modify a few comments (minor) 8af2f35 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories 4f4834e [Andrew Or] Use original storage level for blocks dropped to disk ecc8c2d [Andrew Or] Fix binary incompatibility 24185ea [Andrew Or] Avoid dropping a block back to disk if reading from disk 2b7ee66 [Andrew Or] Fix bug in SizeTracking* 9b9a273 [Andrew Or] Fix tests 20eb3e5 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories 649bdb3 [Andrew Or] Document spark.storage.bufferFraction a10b0e7 [Andrew Or] Add initial memory request threshold + rename a few things e9c3cb0 [Andrew Or] cacheMemoryMap -> unrollMemoryMap 198e374 [Andrew Or] Unfold -> unroll 0d50155 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories d9d02a8 [Andrew Or] Remove unused param in unfoldSafely ec728d8 [Andrew Or] Add tests for safe unfolding of blocks 22b2209 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories 078eb83 [Andrew Or] Add check for hasNext in PrimitiveVector.iterator 0871535 [Andrew Or] Fix tests in BlockManagerSuite d68f31e [Andrew Or] Safely unfold blocks for all memory puts 5961f50 [Andrew Or] Fix tests 195abd7 [Andrew Or] Refactor: move unfold logic to MemoryStore 1e82d00 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories 3ce413e [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories d5dd3b4 [Andrew Or] Free buffer memory in finally ea02eec [Andrew Or] Fix tests b8e1d9c [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories a8704c1 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories e1b8b25 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories 87aa75c [Andrew Or] Fix mima excludes again (typo) 11eb921 [Andrew Or] Clarify comment (minor) 50cae44 [Andrew Or] Remove now duplicate mima exclude 7de5ef9 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories df47265 [Andrew Or] Fix binary incompatibility 6d05a81 [Andrew Or] Merge branch 'master' of github.com:apache/spark into them-rdd-memories f94f5af [Andrew Or] Update a few comments (minor) 776aec9 [Andrew Or] Prevent OOM if a single RDD partition is too large bbd3eea [Andrew Or] Fix CacheManagerSuite to use Array 97ea499 [Andrew Or] Change BlockManager interface to use Arrays c12f093 [Andrew Or] Add SizeTrackingAppendOnlyBuffer and tests
2014-07-27 19:08:16 -04:00
// 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(
[SPARK-2103][Streaming] Change to ClassTag for KafkaInputDStream and fix reflection issue This PR updates previous Manifest for KafkaInputDStream's Decoder to ClassTag, also fix the problem addressed in [SPARK-2103](https://issues.apache.org/jira/browse/SPARK-2103). Previous Java interface cannot actually get the type of Decoder, so when using this Manifest to reconstruct the decode object will meet reflection exception. Also for other two Java interfaces, ClassTag[String] is useless because calling Scala API will get the right implicit ClassTag. Current Kafka unit test cannot actually verify the interface. I've tested these interfaces in my local and distribute settings. Author: jerryshao <saisai.shao@intel.com> Closes #1508 from jerryshao/SPARK-2103 and squashes the following commits: e90c37b [jerryshao] Add Mima excludes 7529810 [jerryshao] Change Manifest to ClassTag for KafkaInputDStream's Decoder and fix Decoder construct issue when using Java API
2014-08-01 07:32:46 -04:00
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")
[SPARK-2549] Functions defined inside of other functions trigger failures Author: Prashant Sharma <prashant.s@imaginea.com> 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
2014-07-23 20:12:28 -04:00
) ++
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") ++
[SPARK-3388] Expose aplication ID in ApplicationStart event, use it in history server. This change exposes the application ID generated by the Spark Master, Mesos or Yarn via the SparkListenerApplicationStart event. It then uses that information to expose the application via its ID in the history server, instead of using the internal directory name generated by the event logger as an application id. This allows someone who knows the application ID to easily figure out the URL for the application's entry in the HS, aside from looking better. In Yarn mode, this is used to generate a direct link from the RM application list to the Spark history server entry (thus providing a fix for SPARK-2150). Note this sort of assumes that the different managers will generate app ids that are sufficiently different from each other that clashes will not occur. Author: Marcelo Vanzin <vanzin@cloudera.com> This patch had conflicts when merged, resolved by Committer: Andrew Or <andrewor14@gmail.com> Closes #1218 from vanzin/yarn-hs-link-2 and squashes the following commits: 2d19f3c [Marcelo Vanzin] Review feedback. 6706d3a [Marcelo Vanzin] Implement applicationId() in base classes. 56fe42e [Marcelo Vanzin] Fix cluster mode history address, plus a cleanup. 44112a8 [Marcelo Vanzin] Merge branch 'master' into yarn-hs-link-2 8278316 [Marcelo Vanzin] Merge branch 'master' into yarn-hs-link-2 a86bbcf [Marcelo Vanzin] Merge branch 'master' into yarn-hs-link-2 a0056e6 [Marcelo Vanzin] Unbreak test. 4b10cfd [Marcelo Vanzin] Merge branch 'master' into yarn-hs-link-2 cb0cab2 [Marcelo Vanzin] Merge branch 'master' into yarn-hs-link-2 25f2826 [Marcelo Vanzin] Add MIMA excludes. f0ba90f [Marcelo Vanzin] Use BufferedIterator. c90a08d [Marcelo Vanzin] Remove unused code. 3f8ec66 [Marcelo Vanzin] Review feedback. 21aa71b [Marcelo Vanzin] Fix JSON test. b022bae [Marcelo Vanzin] Undo SparkContext cleanup. c6d7478 [Marcelo Vanzin] Merge branch 'master' into yarn-hs-link-2 4e3483f [Marcelo Vanzin] Fix test. 57517b8 [Marcelo Vanzin] Review feedback. Mostly, more consistent use of Scala's Option. 311e49d [Marcelo Vanzin] Merge branch 'master' into yarn-hs-link-2 d35d86f [Marcelo Vanzin] Fix yarn backend after rebase. 36dc362 [Marcelo Vanzin] Don't use Iterator::takeWhile(). 0afd696 [Marcelo Vanzin] Wait until master responds before returning from start(). abc4697 [Marcelo Vanzin] Make FsHistoryProvider keep a map of applications by id. 26b266e [Marcelo Vanzin] Use Mesos framework ID as Spark application ID. b3f3664 [Marcelo Vanzin] [yarn] Make the RM link point to the app direcly in the HS. 2fb7de4 [Marcelo Vanzin] Expose the application ID in the ApplicationStart event. ed10348 [Marcelo Vanzin] Expose application id to spark context.
2014-09-03 17:57:38 -04:00
// Class was missing "@DeveloperApi" annotation in 1.0.
MimaBuild.excludeSparkClass("scheduler.SparkListenerApplicationStart") ++
[SPARK-2549] Functions defined inside of other functions trigger failures Author: Prashant Sharma <prashant.s@imaginea.com> 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
2014-07-23 20:12:28 -04:00
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")
SPARK-2341 [MLLIB] loadLibSVMFile doesn't handle regression datasets Per discussion at https://issues.apache.org/jira/browse/SPARK-2341 , this is a look at deprecating the multiclass parameter. Thoughts welcome of course. Author: Sean Owen <srowen@gmail.com> Closes #1663 from srowen/SPARK-2341 and squashes the following commits: 8a3abd7 [Sean Owen] Suppress MIMA error for removed package private classes 18a8c8e [Sean Owen] Updates from review 83d0092 [Sean Owen] Deprecated methods with multiclass, and instead always parse target as a double (ie. multiclass = true)
2014-07-30 20:34:32 -04:00
) ++
[SPARK-3388] Expose aplication ID in ApplicationStart event, use it in history server. This change exposes the application ID generated by the Spark Master, Mesos or Yarn via the SparkListenerApplicationStart event. It then uses that information to expose the application via its ID in the history server, instead of using the internal directory name generated by the event logger as an application id. This allows someone who knows the application ID to easily figure out the URL for the application's entry in the HS, aside from looking better. In Yarn mode, this is used to generate a direct link from the RM application list to the Spark history server entry (thus providing a fix for SPARK-2150). Note this sort of assumes that the different managers will generate app ids that are sufficiently different from each other that clashes will not occur. Author: Marcelo Vanzin <vanzin@cloudera.com> This patch had conflicts when merged, resolved by Committer: Andrew Or <andrewor14@gmail.com> Closes #1218 from vanzin/yarn-hs-link-2 and squashes the following commits: 2d19f3c [Marcelo Vanzin] Review feedback. 6706d3a [Marcelo Vanzin] Implement applicationId() in base classes. 56fe42e [Marcelo Vanzin] Fix cluster mode history address, plus a cleanup. 44112a8 [Marcelo Vanzin] Merge branch 'master' into yarn-hs-link-2 8278316 [Marcelo Vanzin] Merge branch 'master' into yarn-hs-link-2 a86bbcf [Marcelo Vanzin] Merge branch 'master' into yarn-hs-link-2 a0056e6 [Marcelo Vanzin] Unbreak test. 4b10cfd [Marcelo Vanzin] Merge branch 'master' into yarn-hs-link-2 cb0cab2 [Marcelo Vanzin] Merge branch 'master' into yarn-hs-link-2 25f2826 [Marcelo Vanzin] Add MIMA excludes. f0ba90f [Marcelo Vanzin] Use BufferedIterator. c90a08d [Marcelo Vanzin] Remove unused code. 3f8ec66 [Marcelo Vanzin] Review feedback. 21aa71b [Marcelo Vanzin] Fix JSON test. b022bae [Marcelo Vanzin] Undo SparkContext cleanup. c6d7478 [Marcelo Vanzin] Merge branch 'master' into yarn-hs-link-2 4e3483f [Marcelo Vanzin] Fix test. 57517b8 [Marcelo Vanzin] Review feedback. Mostly, more consistent use of Scala's Option. 311e49d [Marcelo Vanzin] Merge branch 'master' into yarn-hs-link-2 d35d86f [Marcelo Vanzin] Fix yarn backend after rebase. 36dc362 [Marcelo Vanzin] Don't use Iterator::takeWhile(). 0afd696 [Marcelo Vanzin] Wait until master responds before returning from start(). abc4697 [Marcelo Vanzin] Make FsHistoryProvider keep a map of applications by id. 26b266e [Marcelo Vanzin] Use Mesos framework ID as Spark application ID. b3f3664 [Marcelo Vanzin] [yarn] Make the RM link point to the app direcly in the HS. 2fb7de4 [Marcelo Vanzin] Expose the application ID in the ApplicationStart event. ed10348 [Marcelo Vanzin] Expose application id to spark context.
2014-09-03 17:57:38 -04:00
Seq( // Package-private classes removed in SPARK-2341
SPARK-2341 [MLLIB] loadLibSVMFile doesn't handle regression datasets Per discussion at https://issues.apache.org/jira/browse/SPARK-2341 , this is a look at deprecating the multiclass parameter. Thoughts welcome of course. Author: Sean Owen <srowen@gmail.com> Closes #1663 from srowen/SPARK-2341 and squashes the following commits: 8a3abd7 [Sean Owen] Suppress MIMA error for removed package private classes 18a8c8e [Sean Owen] Updates from review 83d0092 [Sean Owen] Deprecated methods with multiclass, and instead always parse target as a double (ie. multiclass = true)
2014-07-30 20:34:32 -04:00
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$")
[SPARK-3388] Expose aplication ID in ApplicationStart event, use it in history server. This change exposes the application ID generated by the Spark Master, Mesos or Yarn via the SparkListenerApplicationStart event. It then uses that information to expose the application via its ID in the history server, instead of using the internal directory name generated by the event logger as an application id. This allows someone who knows the application ID to easily figure out the URL for the application's entry in the HS, aside from looking better. In Yarn mode, this is used to generate a direct link from the RM application list to the Spark history server entry (thus providing a fix for SPARK-2150). Note this sort of assumes that the different managers will generate app ids that are sufficiently different from each other that clashes will not occur. Author: Marcelo Vanzin <vanzin@cloudera.com> This patch had conflicts when merged, resolved by Committer: Andrew Or <andrewor14@gmail.com> Closes #1218 from vanzin/yarn-hs-link-2 and squashes the following commits: 2d19f3c [Marcelo Vanzin] Review feedback. 6706d3a [Marcelo Vanzin] Implement applicationId() in base classes. 56fe42e [Marcelo Vanzin] Fix cluster mode history address, plus a cleanup. 44112a8 [Marcelo Vanzin] Merge branch 'master' into yarn-hs-link-2 8278316 [Marcelo Vanzin] Merge branch 'master' into yarn-hs-link-2 a86bbcf [Marcelo Vanzin] Merge branch 'master' into yarn-hs-link-2 a0056e6 [Marcelo Vanzin] Unbreak test. 4b10cfd [Marcelo Vanzin] Merge branch 'master' into yarn-hs-link-2 cb0cab2 [Marcelo Vanzin] Merge branch 'master' into yarn-hs-link-2 25f2826 [Marcelo Vanzin] Add MIMA excludes. f0ba90f [Marcelo Vanzin] Use BufferedIterator. c90a08d [Marcelo Vanzin] Remove unused code. 3f8ec66 [Marcelo Vanzin] Review feedback. 21aa71b [Marcelo Vanzin] Fix JSON test. b022bae [Marcelo Vanzin] Undo SparkContext cleanup. c6d7478 [Marcelo Vanzin] Merge branch 'master' into yarn-hs-link-2 4e3483f [Marcelo Vanzin] Fix test. 57517b8 [Marcelo Vanzin] Review feedback. Mostly, more consistent use of Scala's Option. 311e49d [Marcelo Vanzin] Merge branch 'master' into yarn-hs-link-2 d35d86f [Marcelo Vanzin] Fix yarn backend after rebase. 36dc362 [Marcelo Vanzin] Don't use Iterator::takeWhile(). 0afd696 [Marcelo Vanzin] Wait until master responds before returning from start(). abc4697 [Marcelo Vanzin] Make FsHistoryProvider keep a map of applications by id. 26b266e [Marcelo Vanzin] Use Mesos framework ID as Spark application ID. b3f3664 [Marcelo Vanzin] [yarn] Make the RM link point to the app direcly in the HS. 2fb7de4 [Marcelo Vanzin] Expose the application ID in the ApplicationStart event. ed10348 [Marcelo Vanzin] Expose application id to spark context.
2014-09-03 17:57:38 -04:00
) ++
[SPARK-2923][MLLIB] Implement some basic BLAS routines Having some basic BLAS operations implemented in MLlib can help simplify the current implementation and improve some performance. Tested on my local machine: ~~~ bin/spark-submit --class org.apache.spark.examples.mllib.BinaryClassification \ examples/target/scala-*/spark-examples-*.jar --algorithm LR --regType L2 \ --regParam 1.0 --numIterations 1000 ~/share/data/rcv1.binary/rcv1_train.binary ~~~ 1. before: ~1m 2. after: ~30s CC: jkbradley Author: Xiangrui Meng <meng@databricks.com> Closes #1849 from mengxr/ml-blas and squashes the following commits: ba583a2 [Xiangrui Meng] exclude Vector.copy a4d7d2f [Xiangrui Meng] Merge branch 'master' into ml-blas 6edeab9 [Xiangrui Meng] address comments 940bdeb [Xiangrui Meng] rename MLlibBLAS to BLAS c2a38bc [Xiangrui Meng] enhance dot tests 4cfaac4 [Xiangrui Meng] add apache header 48d01d2 [Xiangrui Meng] add tests for zeros and copy 3b882b1 [Xiangrui Meng] use blas.scal in gradient 735eb23 [Xiangrui Meng] remove d from BLAS routines d2d7d3c [Xiangrui Meng] update gradient and lbfgs 7f78186 [Xiangrui Meng] add zeros to Vectors; add dscal and dcopy to BLAS 14e6645 [Xiangrui Meng] add ddot cbb8273 [Xiangrui Meng] add daxpy test 07db0bb [Xiangrui Meng] Merge branch 'master' into ml-blas e8c326d [Xiangrui Meng] axpy
2014-08-12 01:33:45 -04:00
Seq( // package-private classes removed in MLlib
[SPARK-1997][MLLIB] update breeze to 0.9 0.9 dependences (this version doesn't depend on scalalogging and I excluded commons-math3 from its transitive dependencies): ~~~ +-org.scalanlp:breeze_2.10:0.9 [S] +-com.github.fommil.netlib:core:1.1.2 +-com.github.rwl:jtransforms:2.4.0 +-net.sf.opencsv:opencsv:2.3 +-net.sourceforge.f2j:arpack_combined_all:0.1 +-org.scalanlp:breeze-macros_2.10:0.3.1 [S] | +-org.scalamacros:quasiquotes_2.10:2.0.0 [S] | +-org.slf4j:slf4j-api:1.7.5 +-org.spire-math:spire_2.10:0.7.4 [S] +-org.scalamacros:quasiquotes_2.10:2.0.0 [S] | +-org.spire-math:spire-macros_2.10:0.7.4 [S] +-org.scalamacros:quasiquotes_2.10:2.0.0 [S] ~~~ Closes #1749 CC: witgo avati Author: Xiangrui Meng <meng@databricks.com> Closes #1857 from mengxr/breeze-0.9 and squashes the following commits: 7fc16b6 [Xiangrui Meng] don't know why but exclude a private method for mima dcc502e [Xiangrui Meng] update breeze to 0.9
2014-08-08 18:07:31 -04:00
ProblemFilters.exclude[MissingMethodProblem](
"org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm.org$apache$spark$mllib$regression$GeneralizedLinearAlgorithm$$prependOne")
[SPARK-2923][MLLIB] Implement some basic BLAS routines Having some basic BLAS operations implemented in MLlib can help simplify the current implementation and improve some performance. Tested on my local machine: ~~~ bin/spark-submit --class org.apache.spark.examples.mllib.BinaryClassification \ examples/target/scala-*/spark-examples-*.jar --algorithm LR --regType L2 \ --regParam 1.0 --numIterations 1000 ~/share/data/rcv1.binary/rcv1_train.binary ~~~ 1. before: ~1m 2. after: ~30s CC: jkbradley Author: Xiangrui Meng <meng@databricks.com> Closes #1849 from mengxr/ml-blas and squashes the following commits: ba583a2 [Xiangrui Meng] exclude Vector.copy a4d7d2f [Xiangrui Meng] Merge branch 'master' into ml-blas 6edeab9 [Xiangrui Meng] address comments 940bdeb [Xiangrui Meng] rename MLlibBLAS to BLAS c2a38bc [Xiangrui Meng] enhance dot tests 4cfaac4 [Xiangrui Meng] add apache header 48d01d2 [Xiangrui Meng] add tests for zeros and copy 3b882b1 [Xiangrui Meng] use blas.scal in gradient 735eb23 [Xiangrui Meng] remove d from BLAS routines d2d7d3c [Xiangrui Meng] update gradient and lbfgs 7f78186 [Xiangrui Meng] add zeros to Vectors; add dscal and dcopy to BLAS 14e6645 [Xiangrui Meng] add ddot cbb8273 [Xiangrui Meng] add daxpy test 07db0bb [Xiangrui Meng] Merge branch 'master' into ml-blas e8c326d [Xiangrui Meng] axpy
2014-08-12 01:33:45 -04:00
) ++
Seq( // new Vector methods in MLlib (binary compatible assuming users do not implement Vector)
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.mllib.linalg.Vector.copy")
[SPARK-2924] remove default args to overloaded methods Not supported in Scala 2.11. Split them into separate methods instead. Author: Anand Avati <avati@redhat.com> Closes #1704 from avati/SPARK-1812-default-args and squashes the following commits: 3e3924a [Anand Avati] SPARK-1812: Add Mima excludes for the broken ABI 901dfc7 [Anand Avati] SPARK-1812: core - Fix overloaded methods with default arguments 07f00af [Anand Avati] SPARK-1812: streaming - Fix overloaded methods with default arguments
2014-08-15 11:53:52 -04:00
) ++
[SPARK-3048][MLLIB] add LabeledPoint.parse and remove loadStreamingLabeledPoints Move `parse()` from `LabeledPointParser` to `LabeledPoint` and make it public. This breaks binary compatibility only when a user uses synthesized methods like `tupled` and `curried`, which is rare. `LabeledPoint.parse` is more consistent with `Vectors.parse`, which is why `LabeledPointParser` is not preferred. freeman-lab tdas Author: Xiangrui Meng <meng@databricks.com> Closes #1952 from mengxr/labelparser and squashes the following commits: c818fb2 [Xiangrui Meng] merge master ce20e6f [Xiangrui Meng] update mima excludes b386b8d [Xiangrui Meng] fix tests 2436b3d [Xiangrui Meng] add parse() to LabeledPoint
2014-08-16 18:13:34 -04:00
Seq( // synthetic methods generated in LabeledPoint
ProblemFilters.exclude[MissingTypesProblem]("org.apache.spark.mllib.regression.LabeledPoint$"),
ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.mllib.regression.LabeledPoint.apply"),
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.mllib.regression.LabeledPoint.toString")
) ++
[SPARK-2924] remove default args to overloaded methods Not supported in Scala 2.11. Split them into separate methods instead. Author: Anand Avati <avati@redhat.com> Closes #1704 from avati/SPARK-1812-default-args and squashes the following commits: 3e3924a [Anand Avati] SPARK-1812: Add Mima excludes for the broken ABI 901dfc7 [Anand Avati] SPARK-1812: core - Fix overloaded methods with default arguments 07f00af [Anand Avati] SPARK-1812: streaming - Fix overloaded methods with default arguments
2014-08-15 11:53:52 -04:00
Seq ( // Scala 2.11 compatibility fix
ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.streaming.StreamingContext.<init>$default$2")
Revert "[SPARK-1470][SPARK-1842] Use the scala-logging wrapper instead of the directly sfl4j api" This reverts commit adc8303294e26efb4ed15e5f5ba1062f7988625d.
2014-08-02 02:55:30 -04:00
)
[SPARK-2549] Functions defined inside of other functions trigger failures Author: Prashant Sharma <prashant.s@imaginea.com> 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
2014-07-23 20:12:28 -04:00
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()
}
Better explanation for how to use MIMA excludes. This patch does a few things: 1. We have a file MimaExcludes.scala exclusively for excludes. 2. The test runner tells users about that file if a test fails. 3. I've added back the excludes used from 0.9->1.0. We should keep these in the project as an official audit trail of times where we decided to make exceptions. Author: Patrick Wendell <pwendell@gmail.com> Closes #937 from pwendell/mima and squashes the following commits: 7ee0db2 [Patrick Wendell] Better explanation for how to use MIMA excludes.
2014-06-01 20:27:05 -04:00
}
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