Remove creation of new instance for default case

Signed-off-by: Partho Sarthi <[email protected]>

core/src/main/scala/com/nvidia/spark/rapids/tool/Platform.scala

@@ -15,6 +15,8 @@
  */
 package com.nvidia.spark.rapids.tool
 
+import scala.annotation.tailrec
+
 import org.apache.spark.internal.Logging
 
 /**
@@ -33,6 +35,7 @@ object PlatformNames {
   val EMR_A10 = "emr-a10"
   val EMR_T4 = "emr-t4"
   val ONPREM = "onprem"
+  val DEFAULT: String = ONPREM
 
   /**
    * Return a list of all platform names.
@@ -132,30 +135,28 @@ object PlatformFactory extends Logging {
    * @return An instance of the specified platform.
    * @throws IllegalArgumentException if the specified platform key is not supported.
    */
-  def createInstance(platformKey: String): Platform = {
+  @tailrec
+  def createInstance(platformKey: String = PlatformNames.DEFAULT): Platform = {
     platformKey match {
-      case PlatformNames.DATABRICKS_AWS => new DatabricksPlatform(PlatformNames.DATABRICKS_AWS)
-      case PlatformNames.DATABRICKS_AZURE => new DatabricksPlatform(PlatformNames.DATABRICKS_AZURE)
+      case PlatformNames.DATABRICKS_AWS | PlatformNames.DATABRICKS_AZURE =>
+        new DatabricksPlatform(platformKey)
       case PlatformNames.DATAPROC | PlatformNames.DATAPROC_T4 =>
         // if no GPU specified, then default to dataproc-t4 for backward compatibility
         new DataprocPlatform(PlatformNames.DATAPROC_T4)
-      case PlatformNames.DATAPROC_L4 => new DataprocPlatform(PlatformNames.DATAPROC_L4)
-      case PlatformNames.DATAPROC_SL_L4 => new DataprocPlatform(PlatformNames.DATAPROC_SL_L4)
-      case PlatformNames.DATAPROC_GKE_L4 => new DataprocPlatform(PlatformNames.DATAPROC_GKE_L4)
-      case PlatformNames.DATAPROC_GKE_T4 => new DataprocPlatform(PlatformNames.DATAPROC_GKE_T4)
+      case PlatformNames.DATAPROC_L4 | PlatformNames.DATAPROC_SL_L4 |
+           PlatformNames.DATAPROC_GKE_L4 | PlatformNames.DATAPROC_GKE_T4 =>
+        new DataprocPlatform(platformKey)
       case PlatformNames.EMR | PlatformNames.EMR_T4 =>
         // if no GPU specified, then default to emr-t4 for backward compatibility
         new EmrPlatform(PlatformNames.EMR_T4)
       case PlatformNames.EMR_A10 => new EmrPlatform(PlatformNames.EMR_A10)
       case PlatformNames.ONPREM => new OnPremPlatform
       case p if p.isEmpty =>
-        logInfo(s"Platform is not specified. Using ${PlatformFactory.getDefault.getName} " +
+        logInfo(s"Platform is not specified. Using ${PlatformNames.DEFAULT} " +
           "as default.")
-        PlatformFactory.getDefault
+        PlatformFactory.createInstance(PlatformNames.DEFAULT)
       case _ => throw new IllegalArgumentException(s"Unsupported platform: $platformKey. " +
         s"Options include ${PlatformNames.getAllNames.mkString(", ")}.")
     }
   }
-
-  def getDefault: Platform = new OnPremPlatform()
 }

core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/AutoTuner.scala

@@ -1075,7 +1075,7 @@ object AutoTuner extends Logging {
   def buildAutoTunerFromProps(
       clusterProps: String,
       singleAppProvider: AppSummaryInfoBaseProvider,
-      platform: Platform = PlatformFactory.getDefault): AutoTuner = {
+      platform: Platform = PlatformFactory.createInstance()): AutoTuner = {
     try {
       val clusterPropsOpt = loadClusterPropertiesFromContent(clusterProps)
       new AutoTuner(clusterPropsOpt.getOrElse(new ClusterProperties()), singleAppProvider, platform)
@@ -1088,7 +1088,7 @@ object AutoTuner extends Logging {
   def buildAutoTuner(
       filePath: String,
       singleAppProvider: AppSummaryInfoBaseProvider,
-      platform: Platform = PlatformFactory.getDefault): AutoTuner = {
+      platform: Platform = PlatformFactory.createInstance()): AutoTuner = {
     try {
       val clusterPropsOpt = loadClusterProps(filePath)
       new AutoTuner(clusterPropsOpt.getOrElse(new ClusterProperties()), singleAppProvider, platform)

core/src/main/scala/com/nvidia/spark/rapids/tool/profiling/ProfileArgs.scala

@@ -72,8 +72,8 @@ Usage: java -cp rapids-4-spark-tools_2.12-<version>.jar:$SPARK_HOME/jars/*
     opt[String](required = false,
       descr = "Cluster platform where Spark GPU workloads were executed. Options include " +
         s"${PlatformNames.getAllNames.mkString(", ")}. " +
-        s"Default is ${PlatformFactory.getDefault.getName}.",
-      default = Some(PlatformFactory.getDefault.getName))
+        s"Default is ${PlatformNames.DEFAULT}.",
+      default = Some(PlatformNames.DEFAULT))
   val generateTimeline: ScallopOption[Boolean] =
     opt[Boolean](required = false,
       descr = "Write an SVG graph out for the full application timeline.")

core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/PluginTypeChecker.scala

@@ -33,7 +33,7 @@ import org.apache.spark.internal.Logging
  * by the plugin which lists the formats and types supported.
  * The class also supports a custom speedup factor file as input.
  */
-class PluginTypeChecker(platform: Platform = PlatformFactory.getDefault,
+class PluginTypeChecker(platform: Platform = PlatformFactory.createInstance(),
                         speedupFactorFile: Option[String] = None) extends Logging {
 
   private val NS = "NS"

core/src/main/scala/com/nvidia/spark/rapids/tool/qualification/QualificationArgs.scala

@@ -157,8 +157,8 @@ Usage: java -cp rapids-4-spark-tools_2.12-<version>.jar:$SPARK_HOME/jars/*
     opt[String](required = false,
       descr = "Cluster platform where Spark CPU workloads were executed. Options include " +
         s"${PlatformNames.getAllNames.mkString(", ")}. " +
-        s"Default is ${PlatformFactory.getDefault.getName}.",
-      default = Some(PlatformFactory.getDefault.getName))
+        s"Default is ${PlatformNames.DEFAULT}.",
+      default = Some(PlatformNames.DEFAULT))
   val speedupFactorFile: ScallopOption[String] =
     opt[String](required = false,
       descr = "Custom speedup factor file used to get estimated GPU speedup that is specific " +