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Support missing value and add tests. (#11)
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119
...st4j-spark/src/test/scala/ml/dmlc/xgboost4j/scala/spark/CommunicatorRobustnessSuite.scala
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| /* | ||
| Copyright (c) 2014-2024 by Contributors | ||
| Licensed 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. | ||
| */ | ||
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| package ml.dmlc.xgboost4j.scala.spark | ||
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| import org.scalatest.funsuite.AnyFunSuite | ||
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| import ml.dmlc.xgboost4j.java.{Communicator, RabitTracker} | ||
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| class CommunicatorRobustnessSuite extends AnyFunSuite with PerTest { | ||
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| test("test Java RabitTracker wrapper's exception handling: it should not hang forever.") { | ||
| /* | ||
| Deliberately create new instances of SparkContext in each unit test to avoid reusing the | ||
| same thread pool spawned by the local mode of Spark. As these tests simulate worker crashes | ||
| by throwing exceptions, the crashed worker thread never calls Rabit.shutdown, and therefore | ||
| corrupts the internal state of the native Rabit C++ code. Calling Rabit.init() in subsequent | ||
| tests on a reentrant thread will crash the entire Spark application, an undesired side-effect | ||
| that should be avoided. | ||
| */ | ||
| val rdd = sc.parallelize(1 to numWorkers, numWorkers).cache() | ||
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| val tracker = new RabitTracker(numWorkers) | ||
| tracker.start() | ||
| val trackerEnvs = tracker.getWorkerArgs | ||
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| val workerCount: Int = numWorkers | ||
| /* | ||
| Simulate worker crash events by creating dummy Rabit workers, and throw exceptions in the | ||
| last created worker. A cascading event chain will be triggered once the RuntimeException is | ||
| thrown: the thread running the dummy spark job (sparkThread) catches the exception and | ||
| delegates it to the UnCaughtExceptionHandler, which is the Rabit tracker itself. | ||
| To prevent unit tests from crashing, deterministic delays were introduced to make sure that | ||
| the exception is thrown at last, ideally after all worker connections have been established. | ||
| */ | ||
| val dummyTasks = rdd.mapPartitions { iter => | ||
| Communicator.init(trackerEnvs) | ||
| val index = iter.next() | ||
| Thread.sleep(100 + index * 10) | ||
| if (index == workerCount) { | ||
| // kill the worker by throwing an exception | ||
| throw new RuntimeException("Worker exception.") | ||
| } | ||
| Communicator.shutdown() | ||
| Iterator(index) | ||
| }.cache() | ||
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| val sparkThread = new Thread() { | ||
| override def run(): Unit = { | ||
| // forces a Spark job. | ||
| dummyTasks.foreachPartition(() => _) | ||
| } | ||
| } | ||
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| sparkThread.setUncaughtExceptionHandler(tracker) | ||
| sparkThread.start() | ||
| } | ||
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| test("Communicator allreduce works.") { | ||
| val rdd = sc.parallelize(1 to numWorkers, numWorkers).cache() | ||
| val tracker = new RabitTracker(numWorkers) | ||
| tracker.start() | ||
| val trackerEnvs = tracker.getWorkerArgs | ||
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| val workerCount: Int = numWorkers | ||
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| rdd.mapPartitions { iter => | ||
| val index = iter.next() | ||
| Communicator.init(trackerEnvs) | ||
| val a = Array(1.0f, 2.0f, 3.0f) | ||
| System.out.println(a.mkString(", ")) | ||
| val b = Communicator.allReduce(a, Communicator.OpType.SUM) | ||
| for (i <- 0 to 2) { | ||
| assert(a(i) * workerCount == b(i)) | ||
| } | ||
| val c = Communicator.allReduce(a, Communicator.OpType.MIN); | ||
| for (i <- 0 to 2) { | ||
| assert(a(i) == c(i)) | ||
| } | ||
| Communicator.shutdown() | ||
| Iterator(index) | ||
| }.collect() | ||
| } | ||
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| test("should allow the dataframe containing communicator calls to be partially evaluated for" + | ||
| " multiple times (ISSUE-4406)") { | ||
| val paramMap = Map( | ||
| "eta" -> "1", | ||
| "max_depth" -> "6", | ||
| "silent" -> "1", | ||
| "objective" -> "binary:logistic") | ||
| val trainingDF = smallBinaryClassificationVector | ||
| val model = new XGBoostClassifier(paramMap) | ||
| .setNumWorkers(numWorkers) | ||
| .setNumRound(10) | ||
| .fit(trainingDF) | ||
| val prediction = model.transform(trainingDF) | ||
| // a partial evaluation of dataframe will cause rabit initialized but not shutdown in some | ||
| // threads | ||
| prediction.show() | ||
| // a full evaluation here will re-run init and shutdown all rabit proxy | ||
| // expecting no error | ||
| prediction.collect() | ||
| } | ||
| } |
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