From b92bd5a2f29f7a9ce270540b6a828fa7ff205cbe Mon Sep 17 00:00:00 2001 From: "Joseph K. Bradley" Date: Wed, 8 Oct 2014 14:23:21 -0700 Subject: [SPARK-3841] [mllib] Pretty-print params for ML examples Provide a parent class for the Params case classes used in many MLlib examples, where the parent class pretty-prints the case class fields: Param1Name Param1Value Param2Name Param2Value ... Using this class will make it easier to print test settings to logs. Also, updated DecisionTreeRunner to print a little more info. CC: mengxr Author: Joseph K. Bradley Closes #2700 from jkbradley/dtrunner-update and squashes the following commits: cff873f [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into dtrunner-update 7a08ae4 [Joseph K. Bradley] code review comment updates b4d2043 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into dtrunner-update d8228a7 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into dtrunner-update 0fc9c64 [Joseph K. Bradley] Added abstract TestParams class for mllib example parameters 12b7798 [Joseph K. Bradley] Added abstract class TestParams for pretty-printing Params values 5f84f03 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into dtrunner-update f7441b6 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into dtrunner-update 19eb6fc [Joseph K. Bradley] Updated DecisionTreeRunner to print training time. --- .../spark/examples/mllib/AbstractParams.scala | 53 ++++++++++++++++++++++ .../examples/mllib/BinaryClassification.scala | 2 +- .../apache/spark/examples/mllib/Correlations.scala | 1 + .../spark/examples/mllib/CosineSimilarity.scala | 1 + .../spark/examples/mllib/DecisionTreeRunner.scala | 15 +++++- .../apache/spark/examples/mllib/DenseKMeans.scala | 2 +- .../spark/examples/mllib/LinearRegression.scala | 2 +- .../apache/spark/examples/mllib/MovieLensALS.scala | 2 +- .../examples/mllib/MultivariateSummarizer.scala | 1 + .../apache/spark/examples/mllib/SampledRDDs.scala | 1 + .../spark/examples/mllib/SparseNaiveBayes.scala | 2 +- 11 files changed, 75 insertions(+), 7 deletions(-) create mode 100644 examples/src/main/scala/org/apache/spark/examples/mllib/AbstractParams.scala (limited to 'examples/src') diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/AbstractParams.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/AbstractParams.scala new file mode 100644 index 0000000000..ae6057758d --- /dev/null +++ b/examples/src/main/scala/org/apache/spark/examples/mllib/AbstractParams.scala @@ -0,0 +1,53 @@ +/* + * 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.examples.mllib + +import scala.reflect.runtime.universe._ + +/** + * Abstract class for parameter case classes. + * This overrides the [[toString]] method to print all case class fields by name and value. + * @tparam T Concrete parameter class. + */ +abstract class AbstractParams[T: TypeTag] { + + private def tag: TypeTag[T] = typeTag[T] + + /** + * Finds all case class fields in concrete class instance, and outputs them in JSON-style format: + * { + * [field name]:\t[field value]\n + * [field name]:\t[field value]\n + * ... + * } + */ + override def toString: String = { + val tpe = tag.tpe + val allAccessors = tpe.declarations.collect { + case m: MethodSymbol if m.isCaseAccessor => m + } + val mirror = runtimeMirror(getClass.getClassLoader) + val instanceMirror = mirror.reflect(this) + allAccessors.map { f => + val paramName = f.name.toString + val fieldMirror = instanceMirror.reflectField(f) + val paramValue = fieldMirror.get + s" $paramName:\t$paramValue" + }.mkString("{\n", ",\n", "\n}") + } +} diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/BinaryClassification.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/BinaryClassification.scala index a6f78d2441..1edd2432a0 100644 --- a/examples/src/main/scala/org/apache/spark/examples/mllib/BinaryClassification.scala +++ b/examples/src/main/scala/org/apache/spark/examples/mllib/BinaryClassification.scala @@ -55,7 +55,7 @@ object BinaryClassification { stepSize: Double = 1.0, algorithm: Algorithm = LR, regType: RegType = L2, - regParam: Double = 0.1) + regParam: Double = 0.1) extends AbstractParams[Params] def main(args: Array[String]) { val defaultParams = Params() diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/Correlations.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/Correlations.scala index d6b2fe430e..e49129c4e7 100644 --- a/examples/src/main/scala/org/apache/spark/examples/mllib/Correlations.scala +++ b/examples/src/main/scala/org/apache/spark/examples/mllib/Correlations.scala @@ -35,6 +35,7 @@ import org.apache.spark.{SparkConf, SparkContext} object Correlations { case class Params(input: String = "data/mllib/sample_linear_regression_data.txt") + extends AbstractParams[Params] def main(args: Array[String]) { diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/CosineSimilarity.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/CosineSimilarity.scala index 6a3b0241ce..cb1abbd18f 100644 --- a/examples/src/main/scala/org/apache/spark/examples/mllib/CosineSimilarity.scala +++ b/examples/src/main/scala/org/apache/spark/examples/mllib/CosineSimilarity.scala @@ -43,6 +43,7 @@ import org.apache.spark.{SparkConf, SparkContext} */ object CosineSimilarity { case class Params(inputFile: String = null, threshold: Double = 0.1) + extends AbstractParams[Params] def main(args: Array[String]) { val defaultParams = Params() diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/DecisionTreeRunner.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/DecisionTreeRunner.scala index 4adc91d2fb..837d059147 100644 --- a/examples/src/main/scala/org/apache/spark/examples/mllib/DecisionTreeRunner.scala +++ b/examples/src/main/scala/org/apache/spark/examples/mllib/DecisionTreeRunner.scala @@ -62,7 +62,7 @@ object DecisionTreeRunner { minInfoGain: Double = 0.0, numTrees: Int = 1, featureSubsetStrategy: String = "auto", - fracTest: Double = 0.2) + fracTest: Double = 0.2) extends AbstractParams[Params] def main(args: Array[String]) { val defaultParams = Params() @@ -138,9 +138,11 @@ object DecisionTreeRunner { def run(params: Params) { - val conf = new SparkConf().setAppName("DecisionTreeRunner") + val conf = new SparkConf().setAppName(s"DecisionTreeRunner with $params") val sc = new SparkContext(conf) + println(s"DecisionTreeRunner with parameters:\n$params") + // Load training data and cache it. val origExamples = params.dataFormat match { case "dense" => MLUtils.loadLabeledPoints(sc, params.input).cache() @@ -235,7 +237,10 @@ object DecisionTreeRunner { minInstancesPerNode = params.minInstancesPerNode, minInfoGain = params.minInfoGain) if (params.numTrees == 1) { + val startTime = System.nanoTime() val model = DecisionTree.train(training, strategy) + val elapsedTime = (System.nanoTime() - startTime) / 1e9 + println(s"Training time: $elapsedTime seconds") if (model.numNodes < 20) { println(model.toDebugString) // Print full model. } else { @@ -259,8 +264,11 @@ object DecisionTreeRunner { } else { val randomSeed = Utils.random.nextInt() if (params.algo == Classification) { + val startTime = System.nanoTime() val model = RandomForest.trainClassifier(training, strategy, params.numTrees, params.featureSubsetStrategy, randomSeed) + val elapsedTime = (System.nanoTime() - startTime) / 1e9 + println(s"Training time: $elapsedTime seconds") if (model.totalNumNodes < 30) { println(model.toDebugString) // Print full model. } else { @@ -275,8 +283,11 @@ object DecisionTreeRunner { println(s"Test accuracy = $testAccuracy") } if (params.algo == Regression) { + val startTime = System.nanoTime() val model = RandomForest.trainRegressor(training, strategy, params.numTrees, params.featureSubsetStrategy, randomSeed) + val elapsedTime = (System.nanoTime() - startTime) / 1e9 + println(s"Training time: $elapsedTime seconds") if (model.totalNumNodes < 30) { println(model.toDebugString) // Print full model. } else { diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/DenseKMeans.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/DenseKMeans.scala index 89dfa26c22..11e35598ba 100644 --- a/examples/src/main/scala/org/apache/spark/examples/mllib/DenseKMeans.scala +++ b/examples/src/main/scala/org/apache/spark/examples/mllib/DenseKMeans.scala @@ -44,7 +44,7 @@ object DenseKMeans { input: String = null, k: Int = -1, numIterations: Int = 10, - initializationMode: InitializationMode = Parallel) + initializationMode: InitializationMode = Parallel) extends AbstractParams[Params] def main(args: Array[String]) { val defaultParams = Params() diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/LinearRegression.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/LinearRegression.scala index 05b7d66f8d..e1f9622350 100644 --- a/examples/src/main/scala/org/apache/spark/examples/mllib/LinearRegression.scala +++ b/examples/src/main/scala/org/apache/spark/examples/mllib/LinearRegression.scala @@ -47,7 +47,7 @@ object LinearRegression extends App { numIterations: Int = 100, stepSize: Double = 1.0, regType: RegType = L2, - regParam: Double = 0.1) + regParam: Double = 0.1) extends AbstractParams[Params] val defaultParams = Params() diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/MovieLensALS.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/MovieLensALS.scala index 98aaedb9d7..fc6678013b 100644 --- a/examples/src/main/scala/org/apache/spark/examples/mllib/MovieLensALS.scala +++ b/examples/src/main/scala/org/apache/spark/examples/mllib/MovieLensALS.scala @@ -55,7 +55,7 @@ object MovieLensALS { rank: Int = 10, numUserBlocks: Int = -1, numProductBlocks: Int = -1, - implicitPrefs: Boolean = false) + implicitPrefs: Boolean = false) extends AbstractParams[Params] def main(args: Array[String]) { val defaultParams = Params() diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/MultivariateSummarizer.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/MultivariateSummarizer.scala index 4532512c01..6e4e2d07f2 100644 --- a/examples/src/main/scala/org/apache/spark/examples/mllib/MultivariateSummarizer.scala +++ b/examples/src/main/scala/org/apache/spark/examples/mllib/MultivariateSummarizer.scala @@ -36,6 +36,7 @@ import org.apache.spark.{SparkConf, SparkContext} object MultivariateSummarizer { case class Params(input: String = "data/mllib/sample_linear_regression_data.txt") + extends AbstractParams[Params] def main(args: Array[String]) { diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/SampledRDDs.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/SampledRDDs.scala index f01b8266e3..663c12734a 100644 --- a/examples/src/main/scala/org/apache/spark/examples/mllib/SampledRDDs.scala +++ b/examples/src/main/scala/org/apache/spark/examples/mllib/SampledRDDs.scala @@ -33,6 +33,7 @@ import org.apache.spark.SparkContext._ object SampledRDDs { case class Params(input: String = "data/mllib/sample_binary_classification_data.txt") + extends AbstractParams[Params] def main(args: Array[String]) { val defaultParams = Params() diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/SparseNaiveBayes.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/SparseNaiveBayes.scala index 952fa2a510..f1ff4e6911 100644 --- a/examples/src/main/scala/org/apache/spark/examples/mllib/SparseNaiveBayes.scala +++ b/examples/src/main/scala/org/apache/spark/examples/mllib/SparseNaiveBayes.scala @@ -37,7 +37,7 @@ object SparseNaiveBayes { input: String = null, minPartitions: Int = 0, numFeatures: Int = -1, - lambda: Double = 1.0) + lambda: Double = 1.0) extends AbstractParams[Params] def main(args: Array[String]) { val defaultParams = Params() -- cgit v1.2.3