diff --git a/.travis.yml b/.travis.yml
index afac7b8f..5de6600f 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -5,10 +5,10 @@ script: mvn ${SPARK} -Dmaven.javadoc.skip=true -B clean compile
 jdk: openjdk8
 matrix:
   include:
-    # Covers Spark 2.3.x
+    # Covers Spark 2.4.x + Scala 2.11
     - env: SPARK=
-    # Covers Spark 2.4.x + Scala 2.12
-    - env: SPARK="-Pspark-2.4 -Pscala-2.12"
+    # Covers Spark 3.0.x + Scala 2.12
+    - env: SPARK="-Pspark-3.0 -Pscala-2.12"
 cache:
   directories:
     - $HOME/.m2
diff --git a/ch05-kmeans/src/main/scala/com/cloudera/datascience/kmeans/RunKMeans.scala b/ch05-kmeans/src/main/scala/com/cloudera/datascience/kmeans/RunKMeans.scala
index f29afa7d..0f38ddf6 100644
--- a/ch05-kmeans/src/main/scala/com/cloudera/datascience/kmeans/RunKMeans.scala
+++ b/ch05-kmeans/src/main/scala/com/cloudera/datascience/kmeans/RunKMeans.scala
@@ -107,7 +107,7 @@ class RunKMeans(private val spark: SparkSession) {
     val pipeline = new Pipeline().setStages(Array(assembler, kmeans))
 
     val kmeansModel = pipeline.fit(data).stages.last.asInstanceOf[KMeansModel]
-    kmeansModel.computeCost(assembler.transform(data)) / data.count()
+    kmeansModel.summary.trainingCost
   }
 
   def clusteringScore1(data: DataFrame, k: Int): Double = {
@@ -126,7 +126,7 @@ class RunKMeans(private val spark: SparkSession) {
     val pipeline = new Pipeline().setStages(Array(assembler, kmeans))
 
     val kmeansModel = pipeline.fit(data).stages.last.asInstanceOf[KMeansModel]
-    kmeansModel.computeCost(assembler.transform(data)) / data.count()
+    kmeansModel.summary.trainingCost
   }
 
   def clusteringTake1(data: DataFrame): Unit = {
@@ -161,7 +161,7 @@ class RunKMeans(private val spark: SparkSession) {
     val pipelineModel = pipeline.fit(data)
 
     val kmeansModel = pipelineModel.stages.last.asInstanceOf[KMeansModel]
-    kmeansModel.computeCost(pipelineModel.transform(data)) / data.count()
+    kmeansModel.summary.trainingCost
   }
 
   def clusteringTake2(data: DataFrame): Unit = {
@@ -215,7 +215,7 @@ class RunKMeans(private val spark: SparkSession) {
     val pipelineModel = pipeline.fit(data)
 
     val kmeansModel = pipelineModel.stages.last.asInstanceOf[KMeansModel]
-    kmeansModel.computeCost(pipelineModel.transform(data)) / data.count()
+    kmeansModel.summary.trainingCost
   }
 
   def clusteringTake3(data: DataFrame): Unit = {
diff --git a/ch09-risk/src/main/scala/com/cloudera/datascience/risk/RunRisk.scala b/ch09-risk/src/main/scala/com/cloudera/datascience/risk/RunRisk.scala
index e10a50a3..2c19c6e5 100644
--- a/ch09-risk/src/main/scala/com/cloudera/datascience/risk/RunRisk.scala
+++ b/ch09-risk/src/main/scala/com/cloudera/datascience/risk/RunRisk.scala
@@ -225,7 +225,7 @@ class RunRisk(private val spark: SparkSession) {
     val bandwidth = 1.06 * stddev * math.pow(samples.size, -.2)
 
     // Using toList before toArray avoids a Scala bug
-    val domain = Range.Double(min, max, (max - min) / 100).toList.toArray
+    val domain = Range.BigDecimal(min, max, (max - min) / 100).map(_.toDouble).toList.toArray
     val kd = new KernelDensity().
       setSample(samples.toSeq.toDS.rdd).
       setBandwidth(bandwidth)
@@ -248,7 +248,7 @@ class RunRisk(private val spark: SparkSession) {
     val bandwidth = 1.06 * stddev * math.pow(count, -.2)
 
     // Using toList before toArray avoids a Scala bug
-    val domain = Range.Double(min, max, (max - min) / 100).toList.toArray
+    val domain = Range.BigDecimal(min, max, (max - min) / 100).map(_.toDouble).toList.toArray
     val kd = new KernelDensity().
       setSample(samples.rdd).
       setBandwidth(bandwidth)
diff --git a/pom.xml b/pom.xml
index 35daeefd..10880638 100644
--- a/pom.xml
+++ b/pom.xml
@@ -198,7 +198,7 @@
     <java.version>1.8</java.version>
     <scala.minor.version>2.11</scala.minor.version>
     <scala.complete.version>${scala.minor.version}.12</scala.complete.version>
-    <spark.version>2.3.3</spark.version>
+    <spark.version>2.4.4</spark.version>
   </properties>
 
   <dependencies>
@@ -416,16 +416,16 @@
 
   <profiles>
     <profile>
-      <id>spark-2.4</id>
+      <id>spark-3.0</id>
       <properties>
-        <spark.version>2.4.3</spark.version>
+        <spark.version>3.0.0-preview</spark.version>
       </properties>
     </profile>
     <profile>
       <id>scala-2.12</id>
       <properties>
         <scala.minor.version>2.12</scala.minor.version>
-        <scala.complete.version>${scala.minor.version}.8</scala.complete.version>
+        <scala.complete.version>${scala.minor.version}.10</scala.complete.version>
       </properties>
     </profile>
   </profiles>