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[Breaking] Switch from rabit to the collective communicator (#8257)

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* Switch from rabit to the collective communicator

* fix size_t specialization

* really fix size_t

* try again

* add include

* more include

* fix lint errors

* remove rabit includes

* fix pylint error

* return dict from communicator context

* fix communicator shutdown

* fix dask test

* reset communicator mocklist

* fix distributed tests

* do not save device communicator

* fix jvm gpu tests

* add python test for federated communicator

* Update gputreeshap submodule

Co-authored-by: Hyunsu Philip Cho <chohyu01@cs.washington.edu>
This commit is contained in:
Rong Ou
2022-10-05 15:39:01 -07:00
committed by GitHub
parent e47b3a3da3
commit 668b8a0ea4
79 changed files with 805 additions and 2212 deletions
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6
jvm-packages/xgboost4j-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/PreXGBoost.scala
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@@ -22,7 +22,7 @@ import java.util.ServiceLoader
import scala.collection.JavaConverters._
import scala.collection.{AbstractIterator, Iterator, mutable}
import ml.dmlc.xgboost4j.java.Rabit
import ml.dmlc.xgboost4j.java.Communicator
import ml.dmlc.xgboost4j.scala.{Booster, DMatrix}
import ml.dmlc.xgboost4j.scala.spark.util.DataUtils.PackedParams
import ml.dmlc.xgboost4j.scala.spark.params.XGBoostEstimatorCommon
@@ -266,7 +266,7 @@ object PreXGBoost extends PreXGBoostProvider {
if (batchCnt == 0) {
val rabitEnv = Array(
"DMLC_TASK_ID" -> TaskContext.getPartitionId().toString).toMap
Rabit.init(rabitEnv.asJava)
Communicator.init(rabitEnv.asJava)
}
val features = batchRow.iterator.map(row => row.getAs[Vector](featuresCol))
@@ -298,7 +298,7 @@ object PreXGBoost extends PreXGBoostProvider {
override def next(): Row = {
val ret = batchIterImpl.next()
if (!batchIterImpl.hasNext) {
Rabit.shutdown()
Communicator.shutdown()
}
ret
}

6
jvm-packages/xgboost4j-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/XGBoost.scala
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@@ -22,7 +22,7 @@ import scala.collection.mutable
import scala.util.Random
import scala.collection.JavaConverters._
import ml.dmlc.xgboost4j.java.{IRabitTracker, Rabit, XGBoostError, RabitTracker => PyRabitTracker}
import ml.dmlc.xgboost4j.java.{Communicator, IRabitTracker, XGBoostError, RabitTracker => PyRabitTracker}
import ml.dmlc.xgboost4j.scala.rabit.RabitTracker
import ml.dmlc.xgboost4j.scala.spark.params.LearningTaskParams
import ml.dmlc.xgboost4j.scala.ExternalCheckpointManager
@@ -303,7 +303,7 @@ object XGBoost extends Serializable {
val makeCheckpoint = xgbExecutionParam.checkpointParam.isDefined && taskId.toInt == 0
try {
Rabit.init(rabitEnv)
Communicator.init(rabitEnv)
watches = buildWatchesAndCheck(buildWatches)
@@ -342,7 +342,7 @@ object XGBoost extends Serializable {
logger.error(s"XGBooster worker $taskId has failed $attempt times due to ", xgbException)
throw xgbException
} finally {
Rabit.shutdown()
Communicator.shutdown()
if (watches != null) watches.delete()
}
}

277
jvm-packages/xgboost4j-spark/src/test/scala/ml/dmlc/xgboost4j/scala/spark/RabitRobustnessSuite.scala
View File

@@ -1,277 +0,0 @@
/*
Copyright (c) 2014-2022 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.
*/
package ml.dmlc.xgboost4j.scala.spark
import java.util.concurrent.LinkedBlockingDeque
import scala.util.Random
import ml.dmlc.xgboost4j.java.{Rabit, RabitTracker => PyRabitTracker}
import ml.dmlc.xgboost4j.scala.rabit.{RabitTracker => ScalaRabitTracker}
import ml.dmlc.xgboost4j.java.IRabitTracker.TrackerStatus
import ml.dmlc.xgboost4j.scala.DMatrix
import org.scalatest.{FunSuite}
class RabitRobustnessSuite extends FunSuite with PerTest {
private def getXGBoostExecutionParams(paramMap: Map[String, Any]): XGBoostExecutionParams = {
val classifier = new XGBoostClassifier(paramMap)
val xgbParamsFactory = new XGBoostExecutionParamsFactory(classifier.MLlib2XGBoostParams, sc)
xgbParamsFactory.buildXGBRuntimeParams
}
test("Customize host ip and python exec for Rabit tracker") {
val hostIp = "192.168.22.111"
val pythonExec = "/usr/bin/python3"
val paramMap = Map(
"num_workers" -> numWorkers,
"tracker_conf" -> TrackerConf(0L, "python", hostIp))
val xgbExecParams = getXGBoostExecutionParams(paramMap)
val tracker = XGBoost.getTracker(xgbExecParams.numWorkers, xgbExecParams.trackerConf)
tracker match {
case pyTracker: PyRabitTracker =>
val cmd = pyTracker.getRabitTrackerCommand
assert(cmd.contains(hostIp))
assert(cmd.startsWith("python"))
case _ => assert(false, "expected python tracker implementation")
}
val paramMap1 = Map(
"num_workers" -> numWorkers,
"tracker_conf" -> TrackerConf(0L, "python", "", pythonExec))
val xgbExecParams1 = getXGBoostExecutionParams(paramMap1)
val tracker1 = XGBoost.getTracker(xgbExecParams1.numWorkers, xgbExecParams1.trackerConf)
tracker1 match {
case pyTracker: PyRabitTracker =>
val cmd = pyTracker.getRabitTrackerCommand
assert(cmd.startsWith(pythonExec))
assert(!cmd.contains(hostIp))
case _ => assert(false, "expected python tracker implementation")
}
val paramMap2 = Map(
"num_workers" -> numWorkers,
"tracker_conf" -> TrackerConf(0L, "python", hostIp, pythonExec))
val xgbExecParams2 = getXGBoostExecutionParams(paramMap2)
val tracker2 = XGBoost.getTracker(xgbExecParams2.numWorkers, xgbExecParams2.trackerConf)
tracker2 match {
case pyTracker: PyRabitTracker =>
val cmd = pyTracker.getRabitTrackerCommand
assert(cmd.startsWith(pythonExec))
assert(cmd.contains(s" --host-ip=${hostIp}"))
case _ => assert(false, "expected python tracker implementation")
}
}
test("training with Scala-implemented Rabit tracker") {
val eval = new EvalError()
val training = buildDataFrame(Classification.train)
val testDM = new DMatrix(Classification.test.iterator)
val paramMap = Map("eta" -> "1", "max_depth" -> "6",
"objective" -> "binary:logistic", "num_round" -> 5, "num_workers" -> numWorkers,
"tracker_conf" -> TrackerConf(60 * 60 * 1000, "scala"))
val model = new XGBoostClassifier(paramMap).fit(training)
assert(eval.eval(model._booster.predict(testDM, outPutMargin = true), testDM) < 0.1)
}
test("test Rabit allreduce to validate Scala-implemented Rabit tracker") {
val vectorLength = 100
val rdd = sc.parallelize(
(1 to numWorkers * vectorLength).toArray.map { _ => Random.nextFloat() }, numWorkers).cache()
val tracker = new ScalaRabitTracker(numWorkers)
tracker.start(0)
val trackerEnvs = tracker.getWorkerEnvs
val collectedAllReduceResults = new LinkedBlockingDeque[Array[Float]]()
val rawData = rdd.mapPartitions { iter =>
Iterator(iter.toArray)
}.collect()
val maxVec = (0 until vectorLength).toArray.map { j =>
(0 until numWorkers).toArray.map { i => rawData(i)(j) }.max
}
val allReduceResults = rdd.mapPartitions { iter =>
Rabit.init(trackerEnvs)
val arr = iter.toArray
val results = Rabit.allReduce(arr, Rabit.OpType.MAX)
Rabit.shutdown()
Iterator(results)
}.cache()
val sparkThread = new Thread() {
override def run(): Unit = {
allReduceResults.foreachPartition(() => _)
val byPartitionResults = allReduceResults.collect()
assert(byPartitionResults(0).length == vectorLength)
collectedAllReduceResults.put(byPartitionResults(0))
}
}
sparkThread.start()
assert(tracker.waitFor(0L) == 0)
sparkThread.join()
assert(collectedAllReduceResults.poll().sameElements(maxVec))
}
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()
val tracker = new PyRabitTracker(numWorkers)
tracker.start(0)
val trackerEnvs = tracker.getWorkerEnvs
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.
The Java RabitTracker class reacts to exceptions by killing the spawned process running
the Python tracker. If at least one Rabit worker has yet connected to the tracker before
it is killed, the resulted connection failure will trigger the Rabit worker to call
"exit(-1);" in the native C++ code, effectively ending the dummy Spark task.
In cluster (standalone or YARN) mode of Spark, tasks are run in containers and thus are
isolated from each other. That is, one task calling "exit(-1);" has no effect on other tasks
running in separate containers. However, as unit tests are run in Spark local mode, in which
tasks are executed by threads belonging to the same process, one thread calling "exit(-1);"
ultimately kills the entire process, which also happens to host the Spark driver, causing
the entire Spark application to crash.
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.
For the same reason, the Java RabitTracker class delays the killing of the Python tracker
process to ensure that pending worker connections are handled.
*/
val dummyTasks = rdd.mapPartitions { iter =>
Rabit.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.")
}
Rabit.shutdown()
Iterator(index)
}.cache()
val sparkThread = new Thread() {
override def run(): Unit = {
// forces a Spark job.
dummyTasks.foreachPartition(() => _)
}
}
sparkThread.setUncaughtExceptionHandler(tracker)
sparkThread.start()
assert(tracker.waitFor(0) != 0)
}
test("test Scala RabitTracker's exception handling: it should not hang forever.") {
val rdd = sc.parallelize(1 to numWorkers, numWorkers).cache()
val tracker = new ScalaRabitTracker(numWorkers)
tracker.start(0)
val trackerEnvs = tracker.getWorkerEnvs
val workerCount: Int = numWorkers
val dummyTasks = rdd.mapPartitions { iter =>
Rabit.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.")
}
Rabit.shutdown()
Iterator(index)
}.cache()
val sparkThread = new Thread() {
override def run(): Unit = {
// forces a Spark job.
dummyTasks.foreachPartition(() => _)
}
}
sparkThread.setUncaughtExceptionHandler(tracker)
sparkThread.start()
assert(tracker.waitFor(0L) == TrackerStatus.FAILURE.getStatusCode)
}
test("test Scala RabitTracker's workerConnectionTimeout") {
val rdd = sc.parallelize(1 to numWorkers, numWorkers).cache()
val tracker = new ScalaRabitTracker(numWorkers)
tracker.start(500)
val trackerEnvs = tracker.getWorkerEnvs
val dummyTasks = rdd.mapPartitions { iter =>
val index = iter.next()
// simulate that the first worker cannot connect to tracker due to network issues.
if (index != 1) {
Rabit.init(trackerEnvs)
Thread.sleep(1000)
Rabit.shutdown()
}
Iterator(index)
}.cache()
val sparkThread = new Thread() {
override def run(): Unit = {
// forces a Spark job.
dummyTasks.foreachPartition(() => _)
}
}
sparkThread.setUncaughtExceptionHandler(tracker)
sparkThread.start()
// should fail due to connection timeout
assert(tracker.waitFor(0L) == TrackerStatus.FAILURE.getStatusCode)
}
test("should allow the dataframe containing rabit 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 = buildDataFrame(Classification.train)
val model = new XGBoostClassifier(paramMap ++ Array("num_round" -> 10,
"num_workers" -> numWorkers)).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()
}
}

16
jvm-packages/xgboost4j-spark/src/test/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostRabitRegressionSuite.scala → jvm-packages/xgboost4j-spark/src/test/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostCommunicatorRegressionSuite.scala
View File

@@ -16,7 +16,7 @@
package ml.dmlc.xgboost4j.scala.spark
import ml.dmlc.xgboost4j.java.Rabit
import ml.dmlc.xgboost4j.java.Communicator
import ml.dmlc.xgboost4j.scala.Booster
import scala.collection.JavaConverters._
@@ -25,7 +25,7 @@ import org.scalatest.FunSuite
import org.apache.spark.SparkException
class XGBoostRabitRegressionSuite extends FunSuite with PerTest {
class XGBoostCommunicatorRegressionSuite extends FunSuite with PerTest {
val predictionErrorMin = 0.00001f
val maxFailure = 2;
@@ -47,8 +47,8 @@ class XGBoostRabitRegressionSuite extends FunSuite with PerTest {
val model2 = new XGBoostClassifier(xgbSettings ++ Map("rabit_ring_reduce_threshold" -> 1))
.fit(training)
assert(Rabit.rabitEnvs.asScala.size > 3)
Rabit.rabitEnvs.asScala.foreach( item => {
assert(Communicator.communicatorEnvs.asScala.size > 3)
Communicator.communicatorEnvs.asScala.foreach( item => {
if (item._1.toString == "rabit_reduce_ring_mincount") assert(item._2 == "1")
})
@@ -70,8 +70,8 @@ class XGBoostRabitRegressionSuite extends FunSuite with PerTest {
val model2 = new XGBoostRegressor(xgbSettings ++ Map("rabit_ring_reduce_threshold" -> 1)
).fit(training)
assert(Rabit.rabitEnvs.asScala.size > 3)
Rabit.rabitEnvs.asScala.foreach( item => {
assert(Communicator.communicatorEnvs.asScala.size > 3)
Communicator.communicatorEnvs.asScala.foreach( item => {
if (item._1.toString == "rabit_reduce_ring_mincount") assert(item._2 == "1")
})
// check the equality of single instance prediction
@@ -85,7 +85,7 @@ class XGBoostRabitRegressionSuite extends FunSuite with PerTest {
test("test rabit timeout fail handle") {
val training = buildDataFrame(Classification.train)
// mock rank 0 failure during 8th allreduce synchronization
Rabit.mockList = Array("0,8,0,0").toList.asJava
Communicator.mockList = Array("0,8,0,0").toList.asJava
intercept[SparkException] {
new XGBoostClassifier(Map(
@@ -98,6 +98,8 @@ class XGBoostRabitRegressionSuite extends FunSuite with PerTest {
"rabit_timeout" -> 0))
.fit(training)
}
Communicator.mockList = Array.empty.toList.asJava
}
}