HyukjinKwon commented on a change in pull request #23263: [SPARK-23674][ML] Adds Spark ML Events to Instrumentation URL: https://github.com/apache/spark/pull/23263#discussion_r249334748
########## File path: mllib/src/test/scala/org/apache/spark/ml/MLEventsSuite.scala ########## @@ -0,0 +1,255 @@ +/* + * 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. + */ + +package org.apache.spark.ml + +import scala.collection.mutable +import scala.concurrent.duration._ +import scala.language.postfixOps + +import org.apache.hadoop.fs.Path +import org.mockito.ArgumentMatchers.{any, eq => meq} +import org.mockito.Mockito.when +import org.scalatest.BeforeAndAfterEach +import org.scalatest.concurrent.Eventually +import org.scalatest.mockito.MockitoSugar.mock + +import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.param.ParamMap +import org.apache.spark.ml.util.{DefaultParamsReader, DefaultParamsWriter, MLWriter} +import org.apache.spark.mllib.util.MLlibTestSparkContext +import org.apache.spark.scheduler.{SparkListener, SparkListenerEvent} +import org.apache.spark.sql._ + + +class MLEventsSuite + extends SparkFunSuite with BeforeAndAfterEach with MLlibTestSparkContext with Eventually { + + private val events = mutable.ArrayBuffer.empty[MLEvent] + private val listener: SparkListener = new SparkListener { + override def onOtherEvent(event: SparkListenerEvent): Unit = event match { + case e: MLEvent => events.append(e) + case _ => + } + } + + override def beforeAll(): Unit = { + super.beforeAll() + spark.sparkContext.addSparkListener(listener) + } + + override def afterEach(): Unit = { + try { + events.clear() + } finally { + super.afterEach() + } + } + + override def afterAll(): Unit = { + try { + if (spark != null) { + spark.sparkContext.removeSparkListener(listener) + } + } finally { + super.afterAll() + } + } + + abstract class MyModel extends Model[MyModel] + + test("pipeline fit events") { + val estimator1 = mock[Estimator[MyModel]] + val model1 = mock[MyModel] + val transformer1 = mock[Transformer] + val estimator2 = mock[Estimator[MyModel]] + val model2 = mock[MyModel] + + when(estimator1.copy(any[ParamMap])).thenReturn(estimator1) + when(model1.copy(any[ParamMap])).thenReturn(model1) + when(transformer1.copy(any[ParamMap])).thenReturn(transformer1) + when(estimator2.copy(any[ParamMap])).thenReturn(estimator2) + when(model2.copy(any[ParamMap])).thenReturn(model2) + + val dataset1 = mock[DataFrame] + val dataset2 = mock[DataFrame] + val dataset3 = mock[DataFrame] + val dataset4 = mock[DataFrame] + val dataset5 = mock[DataFrame] + + when(dataset1.toDF).thenReturn(dataset1) + when(dataset2.toDF).thenReturn(dataset2) + when(dataset3.toDF).thenReturn(dataset3) + when(dataset4.toDF).thenReturn(dataset4) + when(dataset5.toDF).thenReturn(dataset5) + + when(estimator1.fit(meq(dataset1))).thenReturn(model1) + when(model1.transform(meq(dataset1))).thenReturn(dataset2) + when(model1.parent).thenReturn(estimator1) + when(transformer1.transform(meq(dataset2))).thenReturn(dataset3) + when(estimator2.fit(meq(dataset3))).thenReturn(model2) + + val pipeline = new Pipeline() + .setStages(Array(estimator1, transformer1, estimator2)) + assert(events.isEmpty) + val pipelineModel = pipeline.fit(dataset1) + val expected = + FitStart(pipeline, dataset1) :: + FitStart(estimator1, dataset1) :: + FitEnd(estimator1, model1) :: + TransformStart(model1, dataset1) :: + TransformEnd(model1, dataset2) :: + TransformStart(transformer1, dataset2) :: + TransformEnd(transformer1, dataset3) :: + FitStart(estimator2, dataset3) :: + FitEnd(estimator2, model2) :: + FitEnd(pipeline, pipelineModel) :: Nil + eventually(timeout(10 seconds), interval(1 second)) { + assert(events === expected) + } + } + + test("pipeline model transform events") { + val dataset1 = mock[DataFrame] + val dataset2 = mock[DataFrame] + val dataset3 = mock[DataFrame] + val dataset4 = mock[DataFrame] + when(dataset1.toDF).thenReturn(dataset1) + when(dataset2.toDF).thenReturn(dataset2) + when(dataset3.toDF).thenReturn(dataset3) + when(dataset4.toDF).thenReturn(dataset4) + + val transformer1 = mock[Transformer] + val model = mock[MyModel] + val transformer2 = mock[Transformer] + when(transformer1.transform(meq(dataset1))).thenReturn(dataset2) + when(model.transform(meq(dataset2))).thenReturn(dataset3) + when(transformer2.transform(meq(dataset3))).thenReturn(dataset4) + + val newPipelineModel = new PipelineModel( + "pipeline0", Array(transformer1, model, transformer2)) + assert(events.isEmpty) + val output = newPipelineModel.transform(dataset1) + val expected = + TransformStart(newPipelineModel, dataset1) :: + TransformStart(transformer1, dataset1) :: + TransformEnd(transformer1, dataset2) :: + TransformStart(model, dataset2) :: + TransformEnd(model, dataset3) :: + TransformStart(transformer2, dataset3) :: + TransformEnd(transformer2, dataset4) :: + TransformEnd(newPipelineModel, output) :: Nil + eventually(timeout(10 seconds), interval(1 second)) { + assert(events === expected) + } + } + + test("pipeline read/write events") { + def getInstance(w: MLWriter): AnyRef = + w.getClass.getDeclaredMethod("instance").invoke(w) + + withTempDir { dir => + val path = new Path(dir.getCanonicalPath, "pipeline").toUri.toString + val writableStage = new WritableStage("writableStage") + val newPipeline = new Pipeline().setStages(Array(writableStage)) + val pipelineWriter = newPipeline.write + assert(events.isEmpty) + pipelineWriter.save(path) + eventually(timeout(10 seconds), interval(1 second)) { + events.foreach { + case e: SaveInstanceStart if e.writer.isInstanceOf[DefaultParamsWriter] => + assert(e.path.endsWith("writableStage")) + case e: SaveInstanceEnd if e.writer.isInstanceOf[DefaultParamsWriter] => + assert(e.path.endsWith("writableStage")) + case e: SaveInstanceStart if getInstance(e.writer).isInstanceOf[Pipeline] => + assert(getInstance(e.writer).asInstanceOf[Pipeline].uid === newPipeline.uid) + case e: SaveInstanceEnd if getInstance(e.writer).isInstanceOf[Pipeline] => + assert(getInstance(e.writer).asInstanceOf[Pipeline].uid === newPipeline.uid) + case e => fail(s"Unexpected event thrown: $e") + } + } + + events.clear() + val pipelineReader = Pipeline.read + assert(events.isEmpty) + pipelineReader.load(path) + eventually(timeout(10 seconds), interval(1 second)) { + events.foreach { + case e: LoadInstanceStart[PipelineStage] + if e.reader.isInstanceOf[DefaultParamsReader[PipelineStage]] => + assert(e.path.endsWith("writableStage")) + case e: LoadInstanceEnd[PipelineStage] + if e.reader.isInstanceOf[DefaultParamsReader[PipelineStage]] => + assert(e.instance.isInstanceOf[PipelineStage]) + case e: LoadInstanceStart[Pipeline] => + assert(e.reader === pipelineReader) + case e: LoadInstanceEnd[Pipeline] => + assert(e.instance.uid === newPipeline.uid) + case e => fail(s"Unexpected event thrown: $e") + } + } + } + } + + test("pipeline model read/write events") { + def getInstance(w: MLWriter): AnyRef = + w.getClass.getDeclaredMethod("instance").invoke(w) + + withTempDir { dir => + val path = new Path(dir.getCanonicalPath, "pipeline").toUri.toString + val writableStage = new WritableStage("writableStage") + val pipelineModel = + new PipelineModel("pipeline_89329329", Array(writableStage.asInstanceOf[Transformer])) + val pipelineWriter = pipelineModel.write + assert(events.isEmpty) + pipelineWriter.save(path) + eventually(timeout(10 seconds), interval(1 second)) { + events.foreach { + case e: SaveInstanceStart if e.writer.isInstanceOf[DefaultParamsWriter] => + assert(e.path.endsWith("writableStage")) + case e: SaveInstanceEnd if e.writer.isInstanceOf[DefaultParamsWriter] => + assert(e.path.endsWith("writableStage")) + case e: SaveInstanceStart if getInstance(e.writer).isInstanceOf[PipelineModel] => Review comment: Yea .. I was wondering why it emitted that event when I wrote the test initially. `WritableStage` seems having `DefaultParamsWriter`.. so it's called from there. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected] With regards, Apache Git Services --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
