From 9916fd1f67234b1fa5608231181bdf3b08718981 Mon Sep 17 00:00:00 2001
From: chetkhatri <ckhatrimanjal@gmail.com>
Date: Sun, 24 Dec 2017 14:03:49 +0530
Subject: [PATCH 01/11] SPARK-22896 Improvement in String interpolation

---
 .../org/apache/spark/examples/ml/ChiSquareTestExample.scala | 6 +++---
 .../org/apache/spark/examples/ml/CorrelationExample.scala   | 4 ++--
 .../org/apache/spark/examples/ml/DataFrameExample.scala     | 4 ++--
 .../examples/ml/DecisionTreeClassificationExample.scala     | 4 ++--
 .../org/apache/spark/examples/ml/DeveloperApiExample.scala  | 6 +++---
 .../examples/ml/EstimatorTransformerParamExample.scala      | 6 +++---
 .../examples/ml/GradientBoostedTreeClassifierExample.scala  | 4 ++--
 .../examples/ml/GradientBoostedTreeRegressorExample.scala   | 4 ++--
 .../MulticlassLogisticRegressionWithElasticNetExample.scala | 2 +-
 .../examples/ml/MultilayerPerceptronClassifierExample.scala | 2 +-
 .../org/apache/spark/examples/ml/NaiveBayesExample.scala    | 2 +-
 .../spark/examples/ml/QuantileDiscretizerExample.scala      | 5 ++---
 .../spark/examples/ml/RandomForestClassifierExample.scala   | 4 ++--
 .../spark/examples/ml/RandomForestRegressorExample.scala    | 4 ++--
 14 files changed, 28 insertions(+), 29 deletions(-)

diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/ChiSquareTestExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/ChiSquareTestExample.scala
index dcee1e427ce58..5146fd0316467 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/ChiSquareTestExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/ChiSquareTestExample.scala
@@ -52,9 +52,9 @@ object ChiSquareTestExample {
 
     val df = data.toDF("label", "features")
     val chi = ChiSquareTest.test(df, "features", "label").head
-    println("pValues = " + chi.getAs[Vector](0))
-    println("degreesOfFreedom = " + chi.getSeq[Int](1).mkString("[", ",", "]"))
-    println("statistics = " + chi.getAs[Vector](2))
+    println(s"pValues = ${chi.getAs[Vector](0)}")
+    println(s"degreesOfFreedom ${chi.getSeq[Int](1).mkString("[", ",", "]")}")
+    println(s"statistics ${chi.getAs[Vector](2)}")
     // $example off$
 
     spark.stop()
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/CorrelationExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/CorrelationExample.scala
index 3f57dc342eb00..14f0b413ae0ac 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/CorrelationExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/CorrelationExample.scala
@@ -51,10 +51,10 @@ object CorrelationExample {
 
     val df = data.map(Tuple1.apply).toDF("features")
     val Row(coeff1: Matrix) = Correlation.corr(df, "features").head
-    println("Pearson correlation matrix:\n" + coeff1.toString)
+    println(s"Pearson correlation matrix:\n ${coeff1.toString}")
 
     val Row(coeff2: Matrix) = Correlation.corr(df, "features", "spearman").head
-    println("Spearman correlation matrix:\n" + coeff2.toString)
+    println(s"Spearman correlation matrix:\n ${coeff2.toString}")
     // $example off$
 
     spark.stop()
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/DataFrameExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/DataFrameExample.scala
index 0658bddf16961..ee4469faab3a0 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/DataFrameExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/DataFrameExample.scala
@@ -47,7 +47,7 @@ object DataFrameExample {
     val parser = new OptionParser[Params]("DataFrameExample") {
       head("DataFrameExample: an example app using DataFrame for ML.")
       opt[String]("input")
-        .text(s"input path to dataframe")
+        .text("input path to dataframe")
         .action((x, c) => c.copy(input = x))
       checkConfig { params =>
         success
@@ -93,7 +93,7 @@ object DataFrameExample {
     // Load the records back.
     println(s"Loading Parquet file with UDT from $outputDir.")
     val newDF = spark.read.parquet(outputDir)
-    println(s"Schema from Parquet:")
+    println("Schema from Parquet:")
     newDF.printSchema()
 
     spark.stop()
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/DecisionTreeClassificationExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/DecisionTreeClassificationExample.scala
index bc6d3275933ea..276cedab11abc 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/DecisionTreeClassificationExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/DecisionTreeClassificationExample.scala
@@ -83,10 +83,10 @@ object DecisionTreeClassificationExample {
       .setPredictionCol("prediction")
       .setMetricName("accuracy")
     val accuracy = evaluator.evaluate(predictions)
-    println("Test Error = " + (1.0 - accuracy))
+    println(s"Test Error = ${(1.0 - accuracy)}")
 
     val treeModel = model.stages(2).asInstanceOf[DecisionTreeClassificationModel]
-    println("Learned classification tree model:\n" + treeModel.toDebugString)
+    println(s"Learned classification tree model:\n ${treeModel.toDebugString}")
     // $example off$
 
     spark.stop()
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/DeveloperApiExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/DeveloperApiExample.scala
index d94d837d10e96..2dc11b07d88ef 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/DeveloperApiExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/DeveloperApiExample.scala
@@ -53,7 +53,7 @@ object DeveloperApiExample {
     // Create a LogisticRegression instance. This instance is an Estimator.
     val lr = new MyLogisticRegression()
     // Print out the parameters, documentation, and any default values.
-    println("MyLogisticRegression parameters:\n" + lr.explainParams() + "\n")
+    println(s"MyLogisticRegression parameters:\n ${lr.explainParams()}")
 
     // We may set parameters using setter methods.
     lr.setMaxIter(10)
@@ -169,10 +169,10 @@ private class MyLogisticRegressionModel(
     Vectors.dense(-margin, margin)
   }
 
-  /** Number of classes the label can take. 2 indicates binary classification. */
+  // Number of classes the label can take. 2 indicates binary classification.
   override val numClasses: Int = 2
 
-  /** Number of features the model was trained on. */
+  // Number of features the model was trained on.
   override val numFeatures: Int = coefficients.size
 
   /**
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/EstimatorTransformerParamExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/EstimatorTransformerParamExample.scala
index f18d86e1a6921..e5d91f132a3f2 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/EstimatorTransformerParamExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/EstimatorTransformerParamExample.scala
@@ -46,7 +46,7 @@ object EstimatorTransformerParamExample {
     // Create a LogisticRegression instance. This instance is an Estimator.
     val lr = new LogisticRegression()
     // Print out the parameters, documentation, and any default values.
-    println("LogisticRegression parameters:\n" + lr.explainParams() + "\n")
+    println(s"LogisticRegression parameters:\n ${lr.explainParams()}\n")
 
     // We may set parameters using setter methods.
     lr.setMaxIter(10)
@@ -58,7 +58,7 @@ object EstimatorTransformerParamExample {
     // we can view the parameters it used during fit().
     // This prints the parameter (name: value) pairs, where names are unique IDs for this
     // LogisticRegression instance.
-    println("Model 1 was fit using parameters: " + model1.parent.extractParamMap)
+    println(s"Model 1 was fit using parameters: ${model1.parent.extractParamMap}")
 
     // We may alternatively specify parameters using a ParamMap,
     // which supports several methods for specifying parameters.
@@ -73,7 +73,7 @@ object EstimatorTransformerParamExample {
     // Now learn a new model using the paramMapCombined parameters.
     // paramMapCombined overrides all parameters set earlier via lr.set* methods.
     val model2 = lr.fit(training, paramMapCombined)
-    println("Model 2 was fit using parameters: " + model2.parent.extractParamMap)
+    println(s"Model 2 was fit using parameters: ${model2.parent.extractParamMap}")
 
     // Prepare test data.
     val test = spark.createDataFrame(Seq(
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/GradientBoostedTreeClassifierExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/GradientBoostedTreeClassifierExample.scala
index 3656773c8b817..ef78c0a1145ef 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/GradientBoostedTreeClassifierExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/GradientBoostedTreeClassifierExample.scala
@@ -86,10 +86,10 @@ object GradientBoostedTreeClassifierExample {
       .setPredictionCol("prediction")
       .setMetricName("accuracy")
     val accuracy = evaluator.evaluate(predictions)
-    println("Test Error = " + (1.0 - accuracy))
+    println(s"Test Error = ${1.0 - accuracy}")
 
     val gbtModel = model.stages(2).asInstanceOf[GBTClassificationModel]
-    println("Learned classification GBT model:\n" + gbtModel.toDebugString)
+    println(s"Learned classification GBT model:\n ${gbtModel.toDebugString}")
     // $example off$
 
     spark.stop()
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/GradientBoostedTreeRegressorExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/GradientBoostedTreeRegressorExample.scala
index e53aab7f326d3..e7d5103bea89b 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/GradientBoostedTreeRegressorExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/GradientBoostedTreeRegressorExample.scala
@@ -73,10 +73,10 @@ object GradientBoostedTreeRegressorExample {
       .setPredictionCol("prediction")
       .setMetricName("rmse")
     val rmse = evaluator.evaluate(predictions)
-    println("Root Mean Squared Error (RMSE) on test data = " + rmse)
+    println(s"Root Mean Squared Error (RMSE) on test data = ${rmse}")
 
     val gbtModel = model.stages(1).asInstanceOf[GBTRegressionModel]
-    println("Learned regression GBT model:\n" + gbtModel.toDebugString)
+    println(s"Learned regression GBT model:\n ${gbtModel.toDebugString}")
     // $example off$
 
     spark.stop()
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/MulticlassLogisticRegressionWithElasticNetExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/MulticlassLogisticRegressionWithElasticNetExample.scala
index 42f0ace7a353d..3e61dbe628c20 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/MulticlassLogisticRegressionWithElasticNetExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/MulticlassLogisticRegressionWithElasticNetExample.scala
@@ -48,7 +48,7 @@ object MulticlassLogisticRegressionWithElasticNetExample {
 
     // Print the coefficients and intercept for multinomial logistic regression
     println(s"Coefficients: \n${lrModel.coefficientMatrix}")
-    println(s"Intercepts: ${lrModel.interceptVector}")
+    println(s"Intercepts: \n${lrModel.interceptVector}")
     // $example off$
 
     spark.stop()
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/MultilayerPerceptronClassifierExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/MultilayerPerceptronClassifierExample.scala
index 6fce82d294f8d..646f46a925062 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/MultilayerPerceptronClassifierExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/MultilayerPerceptronClassifierExample.scala
@@ -66,7 +66,7 @@ object MultilayerPerceptronClassifierExample {
     val evaluator = new MulticlassClassificationEvaluator()
       .setMetricName("accuracy")
 
-    println("Test set accuracy = " + evaluator.evaluate(predictionAndLabels))
+    println(s"Test set accuracy = ${evaluator.evaluate(predictionAndLabels)}")
     // $example off$
 
     spark.stop()
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/NaiveBayesExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/NaiveBayesExample.scala
index bd9fcc420a66c..50c70c626b128 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/NaiveBayesExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/NaiveBayesExample.scala
@@ -52,7 +52,7 @@ object NaiveBayesExample {
       .setPredictionCol("prediction")
       .setMetricName("accuracy")
     val accuracy = evaluator.evaluate(predictions)
-    println("Test set accuracy = " + accuracy)
+    println(s"Test set accuracy = $accuracy")
     // $example off$
 
     spark.stop()
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/QuantileDiscretizerExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/QuantileDiscretizerExample.scala
index aedb9e7d3bb70..3c398f96665b4 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/QuantileDiscretizerExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/QuantileDiscretizerExample.scala
@@ -31,12 +31,11 @@ object QuantileDiscretizerExample {
 
     // $example on$
     val data = Array((0, 18.0), (1, 19.0), (2, 8.0), (3, 5.0), (4, 2.2))
-    val df = spark.createDataFrame(data).toDF("id", "hour")
+    val df = spark.createDataFrame(data).toDF("id", "hour").repartition(1)
     // $example off$
     // Output of QuantileDiscretizer for such small datasets can depend on the number of
     // partitions. Here we force a single partition to ensure consistent results.
     // Note this is not necessary for normal use cases
-        .repartition(1)
 
     // $example on$
     val discretizer = new QuantileDiscretizer()
@@ -45,7 +44,7 @@ object QuantileDiscretizerExample {
       .setNumBuckets(3)
 
     val result = discretizer.fit(df).transform(df)
-    result.show()
+    result.show(false)
     // $example off$
 
     spark.stop()
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/RandomForestClassifierExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/RandomForestClassifierExample.scala
index 5eafda8ce4285..6265f83902528 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/RandomForestClassifierExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/RandomForestClassifierExample.scala
@@ -85,10 +85,10 @@ object RandomForestClassifierExample {
       .setPredictionCol("prediction")
       .setMetricName("accuracy")
     val accuracy = evaluator.evaluate(predictions)
-    println("Test Error = " + (1.0 - accuracy))
+    println(s"Test Error = ${(1.0 - accuracy)}")
 
     val rfModel = model.stages(2).asInstanceOf[RandomForestClassificationModel]
-    println("Learned classification forest model:\n" + rfModel.toDebugString)
+    println(s"Learned classification forest model:\n ${rfModel.toDebugString}")
     // $example off$
 
     spark.stop()
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/RandomForestRegressorExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/RandomForestRegressorExample.scala
index 9a0a001c26ef5..2679fcb353a8a 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/RandomForestRegressorExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/RandomForestRegressorExample.scala
@@ -72,10 +72,10 @@ object RandomForestRegressorExample {
       .setPredictionCol("prediction")
       .setMetricName("rmse")
     val rmse = evaluator.evaluate(predictions)
-    println("Root Mean Squared Error (RMSE) on test data = " + rmse)
+    println(s"Root Mean Squared Error (RMSE) on test data = $rmse")
 
     val rfModel = model.stages(1).asInstanceOf[RandomForestRegressionModel]
-    println("Learned regression forest model:\n" + rfModel.toDebugString)
+    println(s"Learned regression forest model:\n ${rfModel.toDebugString}")
     // $example off$
 
     spark.stop()

From 162ac276cfb5aa3215e3e0bdf2723f3e7aacf7d5 Mon Sep 17 00:00:00 2001
From: chetkhatri <ckhatrimanjal@gmail.com>
Date: Sun, 24 Dec 2017 14:07:25 +0530
Subject: [PATCH 02/11] SPARK-22896 Improvement in String interpolation - fixed
 typo

---
 .../spark/examples/ml/GradientBoostedTreeRegressorExample.scala | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/GradientBoostedTreeRegressorExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/GradientBoostedTreeRegressorExample.scala
index e7d5103bea89b..3feb2343f6a85 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/GradientBoostedTreeRegressorExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/GradientBoostedTreeRegressorExample.scala
@@ -73,7 +73,7 @@ object GradientBoostedTreeRegressorExample {
       .setPredictionCol("prediction")
       .setMetricName("rmse")
     val rmse = evaluator.evaluate(predictions)
-    println(s"Root Mean Squared Error (RMSE) on test data = ${rmse}")
+    println(s"Root Mean Squared Error (RMSE) on test data = $rmse")
 
     val gbtModel = model.stages(1).asInstanceOf[GBTRegressionModel]
     println(s"Learned regression GBT model:\n ${gbtModel.toDebugString}")

From 74d41d7070a0f6c0e11e8a081785ffbc95d86dba Mon Sep 17 00:00:00 2001
From: chetkhatri <ckhatrimanjal@gmail.com>
Date: Tue, 26 Dec 2017 22:31:08 +0530
Subject: [PATCH 03/11] graphx changed got merged to mllib example

---
 .../scala/org/apache/spark/examples/graphx/Analytics.scala | 4 ++--
 .../org/apache/spark/examples/graphx/SynthBenchmark.scala  | 6 +++---
 .../spark/examples/mllib/AssociationRulesExample.scala     | 7 +++----
 3 files changed, 8 insertions(+), 9 deletions(-)

diff --git a/examples/src/main/scala/org/apache/spark/examples/graphx/Analytics.scala b/examples/src/main/scala/org/apache/spark/examples/graphx/Analytics.scala
index 92936bd30dbc0..6c63b452d6d93 100644
--- a/examples/src/main/scala/org/apache/spark/examples/graphx/Analytics.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/graphx/Analytics.scala
@@ -145,9 +145,9 @@ object Analytics extends Logging {
           // TriangleCount requires the graph to be partitioned
           .partitionBy(partitionStrategy.getOrElse(RandomVertexCut)).cache()
         val triangles = TriangleCount.run(graph)
-        println("Triangles: " + triangles.vertices.map {
+        println(s"Triangles: ${triangles.vertices.map {
           case (vid, data) => data.toLong
-        }.reduce(_ + _) / 3)
+        }.reduce(_ + _) / 3}")
         sc.stop()
 
       case _ =>
diff --git a/examples/src/main/scala/org/apache/spark/examples/graphx/SynthBenchmark.scala b/examples/src/main/scala/org/apache/spark/examples/graphx/SynthBenchmark.scala
index 6d2228c8742aa..57b2edf992208 100644
--- a/examples/src/main/scala/org/apache/spark/examples/graphx/SynthBenchmark.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/graphx/SynthBenchmark.scala
@@ -52,7 +52,7 @@ object SynthBenchmark {
       arg =>
         arg.dropWhile(_ == '-').split('=') match {
           case Array(opt, v) => (opt -> v)
-          case _ => throw new IllegalArgumentException("Invalid argument: " + arg)
+          case _ => throw new IllegalArgumentException(s"Invalid argument: $arg")
         }
     }
 
@@ -76,7 +76,7 @@ object SynthBenchmark {
       case ("sigma", v) => sigma = v.toDouble
       case ("degFile", v) => degFile = v
       case ("seed", v) => seed = v.toInt
-      case (opt, _) => throw new IllegalArgumentException("Invalid option: " + opt)
+      case (opt, _) => throw new IllegalArgumentException(s"Invalid option: $opt")
     }
 
     val conf = new SparkConf()
@@ -86,7 +86,7 @@ object SynthBenchmark {
     val sc = new SparkContext(conf)
 
     // Create the graph
-    println(s"Creating graph...")
+    println("Creating graph...")
     val unpartitionedGraph = GraphGenerators.logNormalGraph(sc, numVertices,
       numEPart.getOrElse(sc.defaultParallelism), mu, sigma, seed)
     // Repartition the graph
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/AssociationRulesExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/AssociationRulesExample.scala
index ff44de56839e5..93bb7e237d134 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/AssociationRulesExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/AssociationRulesExample.scala
@@ -42,9 +42,8 @@ object AssociationRulesExample {
     val results = ar.run(freqItemsets)
 
     results.collect().foreach { rule =>
-      println("[" + rule.antecedent.mkString(",")
-        + "=>"
-        + rule.consequent.mkString(",") + "]," + rule.confidence)
+    println(s"[${rule.antecedent.mkString(",")}=>${rule.consequent.mkString(",")} ]" +
+        s" ${rule.confidence}")
     }
     // $example off$
 
@@ -52,4 +51,4 @@ object AssociationRulesExample {
   }
 
 }
-// scalastyle:on println
+// scalastyle:on println
\ No newline at end of file

From 8d729fa028c594523cbfdce4c5b315357330a88a Mon Sep 17 00:00:00 2001
From: chetkhatri <ckhatrimanjal@gmail.com>
Date: Wed, 27 Dec 2017 00:31:15 +0530
Subject: [PATCH 04/11] All examples under spark scala - String interpolation
 has implemented

---
 .../mllib/BinaryClassificationMetricsExample.scala        | 4 ++--
 .../mllib/DecisionTreeClassificationExample.scala         | 4 ++--
 .../examples/mllib/DecisionTreeRegressionExample.scala    | 4 ++--
 .../org/apache/spark/examples/mllib/FPGrowthExample.scala | 2 +-
 .../mllib/GradientBoostingClassificationExample.scala     | 4 ++--
 .../mllib/GradientBoostingRegressionExample.scala         | 4 ++--
 .../spark/examples/mllib/HypothesisTestingExample.scala   | 2 +-
 .../spark/examples/mllib/IsotonicRegressionExample.scala  | 2 +-
 .../org/apache/spark/examples/mllib/KMeansExample.scala   | 2 +-
 .../org/apache/spark/examples/mllib/LBFGSExample.scala    | 2 +-
 .../examples/mllib/LatentDirichletAllocationExample.scala | 6 +++---
 .../examples/mllib/LinearRegressionWithSGDExample.scala   | 2 +-
 .../org/apache/spark/examples/mllib/PCAExample.scala      | 4 ++--
 .../spark/examples/mllib/PMMLModelExportExample.scala     | 2 +-
 .../apache/spark/examples/mllib/PrefixSpanExample.scala   | 4 ++--
 .../mllib/RandomForestClassificationExample.scala         | 4 ++--
 .../examples/mllib/RandomForestRegressionExample.scala    | 4 ++--
 .../spark/examples/mllib/RecommendationExample.scala      | 2 +-
 .../apache/spark/examples/mllib/SVMWithSGDExample.scala   | 2 +-
 .../org/apache/spark/examples/mllib/SimpleFPGrowth.scala  | 8 +++-----
 .../spark/examples/mllib/StratifiedSamplingExample.scala  | 4 ++--
 .../org/apache/spark/examples/mllib/TallSkinnyPCA.scala   | 2 +-
 .../org/apache/spark/examples/mllib/TallSkinnySVD.scala   | 2 +-
 .../apache/spark/examples/streaming/CustomReceiver.scala  | 6 +++---
 .../apache/spark/examples/streaming/RawNetworkGrep.scala  | 2 +-
 .../examples/streaming/RecoverableNetworkWordCount.scala  | 8 ++++----
 .../streaming/clickstream/PageViewGenerator.scala         | 4 ++--
 .../examples/streaming/clickstream/PageViewStream.scala   | 4 ++--
 28 files changed, 49 insertions(+), 51 deletions(-)

diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/BinaryClassificationMetricsExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/BinaryClassificationMetricsExample.scala
index b9263ac6fcff6..c6312d71cc912 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/BinaryClassificationMetricsExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/BinaryClassificationMetricsExample.scala
@@ -86,7 +86,7 @@ object BinaryClassificationMetricsExample {
 
     // AUPRC
     val auPRC = metrics.areaUnderPR
-    println("Area under precision-recall curve = " + auPRC)
+    println(s"Area under precision-recall curve = $auPRC")
 
     // Compute thresholds used in ROC and PR curves
     val thresholds = precision.map(_._1)
@@ -96,7 +96,7 @@ object BinaryClassificationMetricsExample {
 
     // AUROC
     val auROC = metrics.areaUnderROC
-    println("Area under ROC = " + auROC)
+    println(s"Area under ROC = $auROC")
     // $example off$
     sc.stop()
   }
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/DecisionTreeClassificationExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/DecisionTreeClassificationExample.scala
index b50b4592777ce..c2f89b72c9a2e 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/DecisionTreeClassificationExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/DecisionTreeClassificationExample.scala
@@ -55,8 +55,8 @@ object DecisionTreeClassificationExample {
       (point.label, prediction)
     }
     val testErr = labelAndPreds.filter(r => r._1 != r._2).count().toDouble / testData.count()
-    println("Test Error = " + testErr)
-    println("Learned classification tree model:\n" + model.toDebugString)
+    println(s"Test Error = $testErr")
+    println(s"Learned classification tree model:\n ${model.toDebugString}")
 
     // Save and load model
     model.save(sc, "target/tmp/myDecisionTreeClassificationModel")
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/DecisionTreeRegressionExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/DecisionTreeRegressionExample.scala
index 2af45afae3d5b..1ecf6426e1f95 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/DecisionTreeRegressionExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/DecisionTreeRegressionExample.scala
@@ -54,8 +54,8 @@ object DecisionTreeRegressionExample {
       (point.label, prediction)
     }
     val testMSE = labelsAndPredictions.map{ case (v, p) => math.pow(v - p, 2) }.mean()
-    println("Test Mean Squared Error = " + testMSE)
-    println("Learned regression tree model:\n" + model.toDebugString)
+    println(s"Test Mean Squared Error = $testMSE")
+    println(s"Learned regression tree model:\n ${model.toDebugString}")
 
     // Save and load model
     model.save(sc, "target/tmp/myDecisionTreeRegressionModel")
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/FPGrowthExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/FPGrowthExample.scala
index 6435abc127752..f724ee1030f04 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/FPGrowthExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/FPGrowthExample.scala
@@ -74,7 +74,7 @@ object FPGrowthExample {
     println(s"Number of frequent itemsets: ${model.freqItemsets.count()}")
 
     model.freqItemsets.collect().foreach { itemset =>
-      println(itemset.items.mkString("[", ",", "]") + ", " + itemset.freq)
+      println(s"${itemset.items.mkString("[", ",", "]")}, ${itemset.freq}")
     }
 
     sc.stop()
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/GradientBoostingClassificationExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/GradientBoostingClassificationExample.scala
index 00bb3348d2a36..3c56e1941aeca 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/GradientBoostingClassificationExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/GradientBoostingClassificationExample.scala
@@ -54,8 +54,8 @@ object GradientBoostingClassificationExample {
       (point.label, prediction)
     }
     val testErr = labelAndPreds.filter(r => r._1 != r._2).count.toDouble / testData.count()
-    println("Test Error = " + testErr)
-    println("Learned classification GBT model:\n" + model.toDebugString)
+    println(s"Test Error = $testErr")
+    println(s"Learned classification GBT model:\n ${model.toDebugString}")
 
     // Save and load model
     model.save(sc, "target/tmp/myGradientBoostingClassificationModel")
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/GradientBoostingRegressionExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/GradientBoostingRegressionExample.scala
index d8c263460839b..c288bf29bf255 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/GradientBoostingRegressionExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/GradientBoostingRegressionExample.scala
@@ -53,8 +53,8 @@ object GradientBoostingRegressionExample {
       (point.label, prediction)
     }
     val testMSE = labelsAndPredictions.map{ case(v, p) => math.pow((v - p), 2)}.mean()
-    println("Test Mean Squared Error = " + testMSE)
-    println("Learned regression GBT model:\n" + model.toDebugString)
+    println(s"Test Mean Squared Error = $testMSE")
+    println(s"Learned regression GBT model:\n ${model.toDebugString}")
 
     // Save and load model
     model.save(sc, "target/tmp/myGradientBoostingRegressionModel")
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/HypothesisTestingExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/HypothesisTestingExample.scala
index 0d391a3637c07..07569c1069fcb 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/HypothesisTestingExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/HypothesisTestingExample.scala
@@ -68,7 +68,7 @@ object HypothesisTestingExample {
     // against the label.
     val featureTestResults: Array[ChiSqTestResult] = Statistics.chiSqTest(obs)
     featureTestResults.zipWithIndex.foreach { case (k, v) =>
-      println("Column " + (v + 1).toString + ":")
+      println(s"Column ${(v + 1).toString} :")
       println(k)
     }  // summary of the test
     // $example off$
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/IsotonicRegressionExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/IsotonicRegressionExample.scala
index 4aee951f5b04c..a10d6f0dda880 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/IsotonicRegressionExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/IsotonicRegressionExample.scala
@@ -56,7 +56,7 @@ object IsotonicRegressionExample {
 
     // Calculate mean squared error between predicted and real labels.
     val meanSquaredError = predictionAndLabel.map { case (p, l) => math.pow((p - l), 2) }.mean()
-    println("Mean Squared Error = " + meanSquaredError)
+    println(s"Mean Squared Error = $meanSquaredError")
 
     // Save and load model
     model.save(sc, "target/tmp/myIsotonicRegressionModel")
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/KMeansExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/KMeansExample.scala
index c4d71d862f375..b0a6f1671a898 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/KMeansExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/KMeansExample.scala
@@ -43,7 +43,7 @@ object KMeansExample {
 
     // Evaluate clustering by computing Within Set Sum of Squared Errors
     val WSSSE = clusters.computeCost(parsedData)
-    println("Within Set Sum of Squared Errors = " + WSSSE)
+    println(s"Within Set Sum of Squared Errors = $WSSSE")
 
     // Save and load model
     clusters.save(sc, "target/org/apache/spark/KMeansExample/KMeansModel")
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/LBFGSExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/LBFGSExample.scala
index fedcefa098381..123782fa6b9cf 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/LBFGSExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/LBFGSExample.scala
@@ -82,7 +82,7 @@ object LBFGSExample {
 
     println("Loss of each step in training process")
     loss.foreach(println)
-    println("Area under ROC = " + auROC)
+    println(s"Area under ROC = $auROC")
     // $example off$
 
     sc.stop()
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/LatentDirichletAllocationExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/LatentDirichletAllocationExample.scala
index f2c8ec01439f1..06d6f4e2a2542 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/LatentDirichletAllocationExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/LatentDirichletAllocationExample.scala
@@ -42,11 +42,11 @@ object LatentDirichletAllocationExample {
     val ldaModel = new LDA().setK(3).run(corpus)
 
     // Output topics. Each is a distribution over words (matching word count vectors)
-    println("Learned topics (as distributions over vocab of " + ldaModel.vocabSize + " words):")
+    println(s"Learned topics (as distributions over vocab of ${ldaModel.vocabSize} words):")
     val topics = ldaModel.topicsMatrix
     for (topic <- Range(0, 3)) {
-      print("Topic " + topic + ":")
-      for (word <- Range(0, ldaModel.vocabSize)) { print(" " + topics(word, topic)); }
+      print(s"Topic $topic :")
+      for (word <- Range(0, ldaModel.vocabSize)) { print(s" ${topics(word, topic)}") }
       println()
     }
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/LinearRegressionWithSGDExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/LinearRegressionWithSGDExample.scala
index d399618094487..449b725d1d173 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/LinearRegressionWithSGDExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/LinearRegressionWithSGDExample.scala
@@ -52,7 +52,7 @@ object LinearRegressionWithSGDExample {
       (point.label, prediction)
     }
     val MSE = valuesAndPreds.map{ case(v, p) => math.pow((v - p), 2) }.mean()
-    println("training Mean Squared Error = " + MSE)
+    println(s"training Mean Squared Error $MSE")
 
     // Save and load model
     model.save(sc, "target/tmp/scalaLinearRegressionWithSGDModel")
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/PCAExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/PCAExample.scala
index eb36697d94ba1..eff2393cc3abe 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/PCAExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/PCAExample.scala
@@ -65,8 +65,8 @@ object PCAExample {
     val MSE = valuesAndPreds.map { case (v, p) => math.pow((v - p), 2) }.mean()
     val MSE_pca = valuesAndPreds_pca.map { case (v, p) => math.pow((v - p), 2) }.mean()
 
-    println("Mean Squared Error = " + MSE)
-    println("PCA Mean Squared Error = " + MSE_pca)
+    println(s"Mean Squared Error = $MSE")
+    println(s"PCA Mean Squared Error = $MSE_pca")
     // $example off$
 
     sc.stop()
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/PMMLModelExportExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/PMMLModelExportExample.scala
index d74d74a37fb11..96deafd469bc7 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/PMMLModelExportExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/PMMLModelExportExample.scala
@@ -41,7 +41,7 @@ object PMMLModelExportExample {
     val clusters = KMeans.train(parsedData, numClusters, numIterations)
 
     // Export to PMML to a String in PMML format
-    println("PMML Model:\n" + clusters.toPMML)
+    println(s"PMML Model:\n ${clusters.toPMML}")
 
     // Export the model to a local file in PMML format
     clusters.toPMML("/tmp/kmeans.xml")
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/PrefixSpanExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/PrefixSpanExample.scala
index 69c72c4336576..8b789277774af 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/PrefixSpanExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/PrefixSpanExample.scala
@@ -42,8 +42,8 @@ object PrefixSpanExample {
     val model = prefixSpan.run(sequences)
     model.freqSequences.collect().foreach { freqSequence =>
       println(
-        freqSequence.sequence.map(_.mkString("[", ", ", "]")).mkString("[", ", ", "]") +
-          ", " + freqSequence.freq)
+        s"${freqSequence.sequence.map(_.mkString("[", ", ", "]")).mkString("[", ", ", "]")}," +
+          s" ${freqSequence.freq}")
     }
     // $example off$
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/RandomForestClassificationExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/RandomForestClassificationExample.scala
index f1ebdf1a733ed..246e71de25615 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/RandomForestClassificationExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/RandomForestClassificationExample.scala
@@ -55,8 +55,8 @@ object RandomForestClassificationExample {
       (point.label, prediction)
     }
     val testErr = labelAndPreds.filter(r => r._1 != r._2).count.toDouble / testData.count()
-    println("Test Error = " + testErr)
-    println("Learned classification forest model:\n" + model.toDebugString)
+    println(s"Test Error = $testErr")
+    println(s"Learned classification forest model:\n ${model.toDebugString}")
 
     // Save and load model
     model.save(sc, "target/tmp/myRandomForestClassificationModel")
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/RandomForestRegressionExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/RandomForestRegressionExample.scala
index 11d612e651b4b..770e30276bc30 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/RandomForestRegressionExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/RandomForestRegressionExample.scala
@@ -55,8 +55,8 @@ object RandomForestRegressionExample {
       (point.label, prediction)
     }
     val testMSE = labelsAndPredictions.map{ case(v, p) => math.pow((v - p), 2)}.mean()
-    println("Test Mean Squared Error = " + testMSE)
-    println("Learned regression forest model:\n" + model.toDebugString)
+    println(s"Test Mean Squared Error = $testMSE")
+    println(s"Learned regression forest model:\n ${model.toDebugString}")
 
     // Save and load model
     model.save(sc, "target/tmp/myRandomForestRegressionModel")
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/RecommendationExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/RecommendationExample.scala
index 6df742d737e70..0bb2b8c8c2b43 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/RecommendationExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/RecommendationExample.scala
@@ -56,7 +56,7 @@ object RecommendationExample {
       val err = (r1 - r2)
       err * err
     }.mean()
-    println("Mean Squared Error = " + MSE)
+    println(s"Mean Squared Error = $MSE")
 
     // Save and load model
     model.save(sc, "target/tmp/myCollaborativeFilter")
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/SVMWithSGDExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/SVMWithSGDExample.scala
index b73fe9b2b3faa..285e2ce512639 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/SVMWithSGDExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/SVMWithSGDExample.scala
@@ -57,7 +57,7 @@ object SVMWithSGDExample {
     val metrics = new BinaryClassificationMetrics(scoreAndLabels)
     val auROC = metrics.areaUnderROC()
 
-    println("Area under ROC = " + auROC)
+    println(s"Area under ROC = $auROC")
 
     // Save and load model
     model.save(sc, "target/tmp/scalaSVMWithSGDModel")
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/SimpleFPGrowth.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/SimpleFPGrowth.scala
index b5c3033bcba09..694c3bb18b045 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/SimpleFPGrowth.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/SimpleFPGrowth.scala
@@ -42,15 +42,13 @@ object SimpleFPGrowth {
     val model = fpg.run(transactions)
 
     model.freqItemsets.collect().foreach { itemset =>
-      println(itemset.items.mkString("[", ",", "]") + ", " + itemset.freq)
+      println(s"${itemset.items.mkString("[", ",", "]")},${itemset.freq}")
     }
 
     val minConfidence = 0.8
     model.generateAssociationRules(minConfidence).collect().foreach { rule =>
-      println(
-        rule.antecedent.mkString("[", ",", "]")
-          + " => " + rule.consequent .mkString("[", ",", "]")
-          + ", " + rule.confidence)
+      println(s"${rule.antecedent.mkString("[", ",", "]")}=> " +
+        s"${rule.consequent .mkString("[", ",", "]")},${rule.confidence}")
     }
     // $example off$
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/StratifiedSamplingExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/StratifiedSamplingExample.scala
index 16b074ef60699..0b7470c087bb1 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/StratifiedSamplingExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/StratifiedSamplingExample.scala
@@ -41,10 +41,10 @@ object StratifiedSamplingExample {
     val exactSample = data.sampleByKeyExact(withReplacement = false, fractions = fractions)
     // $example off$
 
-    println("approxSample size is " + approxSample.collect().size.toString)
+    println(s"approxSample size is ${approxSample.collect().size.toString}")
     approxSample.collect().foreach(println)
 
-    println("exactSample its size is " + exactSample.collect().size.toString)
+    println(s"exactSample its size is ${exactSample.collect().size.toString}")
     exactSample.collect().foreach(println)
 
     sc.stop()
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/TallSkinnyPCA.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/TallSkinnyPCA.scala
index 03bc675299c5a..071d341b81614 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/TallSkinnyPCA.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/TallSkinnyPCA.scala
@@ -54,7 +54,7 @@ object TallSkinnyPCA {
     // Compute principal components.
     val pc = mat.computePrincipalComponents(mat.numCols().toInt)
 
-    println("Principal components are:\n" + pc)
+    println(s"Principal components are:\n $pc")
 
     sc.stop()
   }
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/TallSkinnySVD.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/TallSkinnySVD.scala
index 067e49b9599e7..8ae6de16d80e7 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/TallSkinnySVD.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/TallSkinnySVD.scala
@@ -54,7 +54,7 @@ object TallSkinnySVD {
     // Compute SVD.
     val svd = mat.computeSVD(mat.numCols().toInt)
 
-    println("Singular values are " + svd.s)
+    println(s"Singular values are ${svd.s}")
 
     sc.stop()
   }
diff --git a/examples/src/main/scala/org/apache/spark/examples/streaming/CustomReceiver.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/CustomReceiver.scala
index 43044d01b1204..b4d06d350a79a 100644
--- a/examples/src/main/scala/org/apache/spark/examples/streaming/CustomReceiver.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/CustomReceiver.scala
@@ -82,9 +82,9 @@ class CustomReceiver(host: String, port: Int)
    var socket: Socket = null
    var userInput: String = null
    try {
-     logInfo("Connecting to " + host + ":" + port)
+     logInfo(s"Connecting to $host $port")
      socket = new Socket(host, port)
-     logInfo("Connected to " + host + ":" + port)
+     logInfo(s"Connected to $host : $port")
      val reader = new BufferedReader(
        new InputStreamReader(socket.getInputStream(), StandardCharsets.UTF_8))
      userInput = reader.readLine()
@@ -98,7 +98,7 @@ class CustomReceiver(host: String, port: Int)
      restart("Trying to connect again")
    } catch {
      case e: java.net.ConnectException =>
-       restart("Error connecting to " + host + ":" + port, e)
+       restart(s"Error connecting to $host : $port", e)
      case t: Throwable =>
        restart("Error receiving data", t)
    }
diff --git a/examples/src/main/scala/org/apache/spark/examples/streaming/RawNetworkGrep.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/RawNetworkGrep.scala
index 5322929d177b4..437ccf0898d7c 100644
--- a/examples/src/main/scala/org/apache/spark/examples/streaming/RawNetworkGrep.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/RawNetworkGrep.scala
@@ -54,7 +54,7 @@ object RawNetworkGrep {
       ssc.rawSocketStream[String](host, port, StorageLevel.MEMORY_ONLY_SER_2)).toArray
     val union = ssc.union(rawStreams)
     union.filter(_.contains("the")).count().foreachRDD(r =>
-      println("Grep count: " + r.collect().mkString))
+      println(s"Grep count: ${r.collect().mkString}"))
     ssc.start()
     ssc.awaitTermination()
   }
diff --git a/examples/src/main/scala/org/apache/spark/examples/streaming/RecoverableNetworkWordCount.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/RecoverableNetworkWordCount.scala
index 49c0427321133..f018f3a26d2e9 100644
--- a/examples/src/main/scala/org/apache/spark/examples/streaming/RecoverableNetworkWordCount.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/RecoverableNetworkWordCount.scala
@@ -130,10 +130,10 @@ object RecoverableNetworkWordCount {
           true
         }
       }.collect().mkString("[", ", ", "]")
-      val output = "Counts at time " + time + " " + counts
+      val output = s"Counts at time $time $counts"
       println(output)
-      println("Dropped " + droppedWordsCounter.value + " word(s) totally")
-      println("Appending to " + outputFile.getAbsolutePath)
+      println(s"Dropped ${droppedWordsCounter.value} word(s) totally")
+      println(s"Appending to ${outputFile.getAbsolutePath}")
       Files.append(output + "\n", outputFile, Charset.defaultCharset())
     }
     ssc
@@ -141,7 +141,7 @@ object RecoverableNetworkWordCount {
 
   def main(args: Array[String]) {
     if (args.length != 4) {
-      System.err.println("Your arguments were " + args.mkString("[", ", ", "]"))
+      System.err.println(s"Your arguments were ${args.mkString("[", ", ", "]")}")
       System.err.println(
         """
           |Usage: RecoverableNetworkWordCount <hostname> <port> <checkpoint-directory>
diff --git a/examples/src/main/scala/org/apache/spark/examples/streaming/clickstream/PageViewGenerator.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/clickstream/PageViewGenerator.scala
index 0ddd065f0db2b..2108bc63edea2 100644
--- a/examples/src/main/scala/org/apache/spark/examples/streaming/clickstream/PageViewGenerator.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/clickstream/PageViewGenerator.scala
@@ -90,13 +90,13 @@ object PageViewGenerator {
     val viewsPerSecond = args(1).toFloat
     val sleepDelayMs = (1000.0 / viewsPerSecond).toInt
     val listener = new ServerSocket(port)
-    println("Listening on port: " + port)
+    println(s"Listening on port: $port")
 
     while (true) {
       val socket = listener.accept()
       new Thread() {
         override def run(): Unit = {
-          println("Got client connected from: " + socket.getInetAddress)
+          println(s"Got client connected from: ${socket.getInetAddress}")
           val out = new PrintWriter(socket.getOutputStream(), true)
 
           while (true) {
diff --git a/examples/src/main/scala/org/apache/spark/examples/streaming/clickstream/PageViewStream.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/clickstream/PageViewStream.scala
index 1ba093f57b32c..b8e7c7e9e9152 100644
--- a/examples/src/main/scala/org/apache/spark/examples/streaming/clickstream/PageViewStream.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/clickstream/PageViewStream.scala
@@ -104,8 +104,8 @@ object PageViewStream {
           .foreachRDD((rdd, time) => rdd.join(userList)
             .map(_._2._2)
             .take(10)
-            .foreach(u => println("Saw user %s at time %s".format(u, time))))
-      case _ => println("Invalid metric entered: " + metric)
+            .foreach(u => println(s"Saw user $u at time $time")))
+      case _ => println(s"Invalid metric entered: $metric")
     }
 
     ssc.start()

From 5507cad0516b5bb4a6fb157a32510b30e85176f6 Mon Sep 17 00:00:00 2001
From: chetkhatri <ckhatrimanjal@gmail.com>
Date: Wed, 27 Dec 2017 00:44:38 +0530
Subject: [PATCH 05/11] All examples under spark scala - String interpolation
 has implemented - 2

---
 .../org/apache/spark/examples/SimpleSkewedGroupByTest.scala   | 4 ----
 .../spark/examples/ml/DecisionTreeRegressionExample.scala     | 4 ++--
 .../org/apache/spark/examples/ml/VectorIndexerExample.scala   | 4 ++--
 3 files changed, 4 insertions(+), 8 deletions(-)

diff --git a/examples/src/main/scala/org/apache/spark/examples/SimpleSkewedGroupByTest.scala b/examples/src/main/scala/org/apache/spark/examples/SimpleSkewedGroupByTest.scala
index e64dcbd182d94..2332a661f26a0 100644
--- a/examples/src/main/scala/org/apache/spark/examples/SimpleSkewedGroupByTest.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/SimpleSkewedGroupByTest.scala
@@ -60,10 +60,6 @@ object SimpleSkewedGroupByTest {
     pairs1.count
 
     println(s"RESULT: ${pairs1.groupByKey(numReducers).count}")
-    // Print how many keys each reducer got (for debugging)
-    // println("RESULT: " + pairs1.groupByKey(numReducers)
-    //                           .map{case (k,v) => (k, v.size)}
-    //                           .collectAsMap)
 
     spark.stop()
   }
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/DecisionTreeRegressionExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/DecisionTreeRegressionExample.scala
index ee61200ad1d0c..aaaecaea47081 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/DecisionTreeRegressionExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/DecisionTreeRegressionExample.scala
@@ -73,10 +73,10 @@ object DecisionTreeRegressionExample {
       .setPredictionCol("prediction")
       .setMetricName("rmse")
     val rmse = evaluator.evaluate(predictions)
-    println("Root Mean Squared Error (RMSE) on test data = " + rmse)
+    println(s"Root Mean Squared Error (RMSE) on test data = $rmse")
 
     val treeModel = model.stages(1).asInstanceOf[DecisionTreeRegressionModel]
-    println("Learned regression tree model:\n" + treeModel.toDebugString)
+    println(s"Learned regression tree model:\n ${treeModel.toDebugString}")
     // $example off$
 
     spark.stop()
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/VectorIndexerExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/VectorIndexerExample.scala
index afa761aee0b98..4d8f970923758 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/VectorIndexerExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/VectorIndexerExample.scala
@@ -41,8 +41,8 @@ object VectorIndexerExample {
     val indexerModel = indexer.fit(data)
 
     val categoricalFeatures: Set[Int] = indexerModel.categoryMaps.keys.toSet
-    println(s"Chose ${categoricalFeatures.size} categorical features: " +
-      categoricalFeatures.mkString(", "))
+    println(s"Chose ${categoricalFeatures.size} " +
+      s"categorical features: {$categoricalFeatures.mkString(", ")}")
 
     // Create new column "indexed" with categorical values transformed to indices
     val indexedData = indexerModel.transform(data)

From 79e6789e1c7621b374785e036f7132c37da6da21 Mon Sep 17 00:00:00 2001
From: chetkhatri <ckhatrimanjal@gmail.com>
Date: Thu, 28 Dec 2017 23:32:12 +0530
Subject: [PATCH 06/11] Spark scala code change for request addressed

---
 .../scala/org/apache/spark/examples/graphx/Analytics.scala  | 6 ++++--
 .../org/apache/spark/examples/ml/CorrelationExample.scala   | 4 ++--
 .../spark/examples/ml/QuantileDiscretizerExample.scala      | 3 ++-
 .../apache/spark/examples/streaming/CustomReceiver.scala    | 2 +-
 4 files changed, 9 insertions(+), 6 deletions(-)

diff --git a/examples/src/main/scala/org/apache/spark/examples/graphx/Analytics.scala b/examples/src/main/scala/org/apache/spark/examples/graphx/Analytics.scala
index 6c63b452d6d93..815404d1218b7 100644
--- a/examples/src/main/scala/org/apache/spark/examples/graphx/Analytics.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/graphx/Analytics.scala
@@ -145,9 +145,11 @@ object Analytics extends Logging {
           // TriangleCount requires the graph to be partitioned
           .partitionBy(partitionStrategy.getOrElse(RandomVertexCut)).cache()
         val triangles = TriangleCount.run(graph)
-        println(s"Triangles: ${triangles.vertices.map {
+        val triangleTypes = triangles.vertices.map {
           case (vid, data) => data.toLong
-        }.reduce(_ + _) / 3}")
+        }.reduce(_ + _) / 3
+
+        println(s"Triangles: ${triangleTypes}")
         sc.stop()
 
       case _ =>
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/CorrelationExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/CorrelationExample.scala
index 14f0b413ae0ac..d7f1fc8ed74d7 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/CorrelationExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/CorrelationExample.scala
@@ -51,10 +51,10 @@ object CorrelationExample {
 
     val df = data.map(Tuple1.apply).toDF("features")
     val Row(coeff1: Matrix) = Correlation.corr(df, "features").head
-    println(s"Pearson correlation matrix:\n ${coeff1.toString}")
+    println(s"Pearson correlation matrix:\n $coeff1")
 
     val Row(coeff2: Matrix) = Correlation.corr(df, "features", "spearman").head
-    println(s"Spearman correlation matrix:\n ${coeff2.toString}")
+    println(s"Spearman correlation matrix:\n $coeff2")
     // $example off$
 
     spark.stop()
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/QuantileDiscretizerExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/QuantileDiscretizerExample.scala
index 3c398f96665b4..0fe16fb6dfa9f 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/QuantileDiscretizerExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/QuantileDiscretizerExample.scala
@@ -31,11 +31,12 @@ object QuantileDiscretizerExample {
 
     // $example on$
     val data = Array((0, 18.0), (1, 19.0), (2, 8.0), (3, 5.0), (4, 2.2))
-    val df = spark.createDataFrame(data).toDF("id", "hour").repartition(1)
+    val df = spark.createDataFrame(data).toDF("id", "hour")
     // $example off$
     // Output of QuantileDiscretizer for such small datasets can depend on the number of
     // partitions. Here we force a single partition to ensure consistent results.
     // Note this is not necessary for normal use cases
+      .repartition(1)
 
     // $example on$
     val discretizer = new QuantileDiscretizer()
diff --git a/examples/src/main/scala/org/apache/spark/examples/streaming/CustomReceiver.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/CustomReceiver.scala
index b4d06d350a79a..25c7bf2871972 100644
--- a/examples/src/main/scala/org/apache/spark/examples/streaming/CustomReceiver.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/CustomReceiver.scala
@@ -82,7 +82,7 @@ class CustomReceiver(host: String, port: Int)
    var socket: Socket = null
    var userInput: String = null
    try {
-     logInfo(s"Connecting to $host $port")
+     logInfo(s"Connecting to $host : $port")
      socket = new Socket(host, port)
      logInfo(s"Connected to $host : $port")
      val reader = new BufferedReader(

From 70ce734681b0a6d7e833af35c6303bfc6c1aeac2 Mon Sep 17 00:00:00 2001
From: chetkhatri <ckhatrimanjal@gmail.com>
Date: Fri, 29 Dec 2017 10:04:13 +0530
Subject: [PATCH 07/11] new line at the end of file added

---
 .../apache/spark/examples/mllib/AssociationRulesExample.scala  | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/AssociationRulesExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/AssociationRulesExample.scala
index 93bb7e237d134..a07535bb5a38d 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/AssociationRulesExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/AssociationRulesExample.scala
@@ -51,4 +51,5 @@ object AssociationRulesExample {
   }
 
 }
-// scalastyle:on println
\ No newline at end of file
+// scalastyle:on println
+

From 0321faf054a94d7fc83b2a300529da2739813840 Mon Sep 17 00:00:00 2001
From: chetkhatri <ckhatrimanjal@gmail.com>
Date: Fri, 29 Dec 2017 22:13:29 +0530
Subject: [PATCH 08/11] typo fixed

---
 .../org/apache/spark/examples/ml/VectorIndexerExample.scala     | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/VectorIndexerExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/VectorIndexerExample.scala
index 4d8f970923758..96bb8ea2338af 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/VectorIndexerExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/VectorIndexerExample.scala
@@ -42,7 +42,7 @@ object VectorIndexerExample {
 
     val categoricalFeatures: Set[Int] = indexerModel.categoryMaps.keys.toSet
     println(s"Chose ${categoricalFeatures.size} " +
-      s"categorical features: {$categoricalFeatures.mkString(", ")}")
+      s"categorical features: ${categoricalFeatures.mkString(", ")}")
 
     // Create new column "indexed" with categorical values transformed to indices
     val indexedData = indexerModel.transform(data)

From c33e90c13ed42b121833783e4a1504cdce14ab23 Mon Sep 17 00:00:00 2001
From: chetkhatri <ckhatrimanjal@gmail.com>
Date: Sun, 31 Dec 2017 12:13:46 +0530
Subject: [PATCH 09/11] Review changes addressed

---
 .../spark/examples/mllib/HypothesisTestingExample.scala      | 2 +-
 .../examples/mllib/LatentDirichletAllocationExample.scala    | 5 ++++-
 2 files changed, 5 insertions(+), 2 deletions(-)

diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/HypothesisTestingExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/HypothesisTestingExample.scala
index 07569c1069fcb..add1719739539 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/HypothesisTestingExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/HypothesisTestingExample.scala
@@ -68,7 +68,7 @@ object HypothesisTestingExample {
     // against the label.
     val featureTestResults: Array[ChiSqTestResult] = Statistics.chiSqTest(obs)
     featureTestResults.zipWithIndex.foreach { case (k, v) =>
-      println(s"Column ${(v + 1).toString} :")
+      println(s"Column ${(v + 1)} :")
       println(k)
     }  // summary of the test
     // $example off$
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/LatentDirichletAllocationExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/LatentDirichletAllocationExample.scala
index 06d6f4e2a2542..d8eb3dcadc383 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/LatentDirichletAllocationExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/LatentDirichletAllocationExample.scala
@@ -46,7 +46,10 @@ object LatentDirichletAllocationExample {
     val topics = ldaModel.topicsMatrix
     for (topic <- Range(0, 3)) {
       print(s"Topic $topic :")
-      for (word <- Range(0, ldaModel.vocabSize)) { print(s" ${topics(word, topic)}") }
+      for (word <- Range(0, ldaModel.vocabSize))
+          {
+            print(s" ${topics(word, topic)}")
+          }
       println()
     }
 

From 18d047fa6164d6ae4d4d2f50081bb2c090172949 Mon Sep 17 00:00:00 2001
From: chetkhatri <ckhatrimanjal@gmail.com>
Date: Mon, 1 Jan 2018 15:30:41 +0530
Subject: [PATCH 10/11] Changes - II addressed

---
 .../spark/examples/ml/QuantileDiscretizerExample.scala     | 2 +-
 .../examples/mllib/LatentDirichletAllocationExample.scala  | 7 +++----
 2 files changed, 4 insertions(+), 5 deletions(-)

diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/QuantileDiscretizerExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/QuantileDiscretizerExample.scala
index 0fe16fb6dfa9f..2c1979792efb4 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/QuantileDiscretizerExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/QuantileDiscretizerExample.scala
@@ -45,7 +45,7 @@ object QuantileDiscretizerExample {
       .setNumBuckets(3)
 
     val result = discretizer.fit(df).transform(df)
-    result.show(false)
+    result.show()
     // $example off$
 
     spark.stop()
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/LatentDirichletAllocationExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/LatentDirichletAllocationExample.scala
index d8eb3dcadc383..d25962c5500ed 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/LatentDirichletAllocationExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/LatentDirichletAllocationExample.scala
@@ -46,10 +46,9 @@ object LatentDirichletAllocationExample {
     val topics = ldaModel.topicsMatrix
     for (topic <- Range(0, 3)) {
       print(s"Topic $topic :")
-      for (word <- Range(0, ldaModel.vocabSize))
-          {
-            print(s" ${topics(word, topic)}")
-          }
+      for (word <- Range(0, ldaModel.vocabSize)) {
+        print(s"${topics(word, topic)}")
+      }
       println()
     }
 

From e891f53dfd609ef9cb46f70147c59f1113c7c0cb Mon Sep 17 00:00:00 2001
From: chetkhatri <ckhatrimanjal@gmail.com>
Date: Mon, 1 Jan 2018 15:43:40 +0530
Subject: [PATCH 11/11] Changes - III addressed

---
 .../spark/examples/ml/JavaQuantileDiscretizerExample.java     | 2 +-
 .../apache/spark/examples/ml/QuantileDiscretizerExample.scala | 2 +-
 .../spark/examples/mllib/StratifiedSamplingExample.scala      | 4 ++--
 3 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaQuantileDiscretizerExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaQuantileDiscretizerExample.java
index dd20cac621102..43cc30c1a899b 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaQuantileDiscretizerExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaQuantileDiscretizerExample.java
@@ -66,7 +66,7 @@ public static void main(String[] args) {
       .setNumBuckets(3);
 
     Dataset<Row> result = discretizer.fit(df).transform(df);
-    result.show();
+    result.show(false);
     // $example off$
     spark.stop();
   }
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/QuantileDiscretizerExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/QuantileDiscretizerExample.scala
index 2c1979792efb4..0fe16fb6dfa9f 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/QuantileDiscretizerExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/QuantileDiscretizerExample.scala
@@ -45,7 +45,7 @@ object QuantileDiscretizerExample {
       .setNumBuckets(3)
 
     val result = discretizer.fit(df).transform(df)
-    result.show()
+    result.show(false)
     // $example off$
 
     spark.stop()
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/StratifiedSamplingExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/StratifiedSamplingExample.scala
index 0b7470c087bb1..3d41bef0af88c 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/StratifiedSamplingExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/StratifiedSamplingExample.scala
@@ -41,10 +41,10 @@ object StratifiedSamplingExample {
     val exactSample = data.sampleByKeyExact(withReplacement = false, fractions = fractions)
     // $example off$
 
-    println(s"approxSample size is ${approxSample.collect().size.toString}")
+    println(s"approxSample size is ${approxSample.collect().size}")
     approxSample.collect().foreach(println)
 
-    println(s"exactSample its size is ${exactSample.collect().size.toString}")
+    println(s"exactSample its size is ${exactSample.collect().size}")
     exactSample.collect().foreach(println)
 
     sc.stop()