fix so RDDsServlet class is Spark 3.5 compatible (see h2oai/sparkling…

…-water#5620); bump version to evg2

core/src/main/scala/ai/h2o/sparkling/backend/api/rdds/RDDsServlet.scala

@@ -26,6 +26,7 @@ import org.apache.spark.mllib.regression.LabeledPoint
 import org.apache.spark.rdd.RDD
 import org.apache.spark.sql.Row
 import org.apache.spark.sql.catalyst.ScalaReflection
+import org.apache.spark.sql.catalyst.ScalaReflection.universe._
 import org.apache.spark.sql.types.{StructField, StructType}
 import water.exceptions.H2ONotFoundArgumentException
 
@@ -89,14 +90,17 @@ private[api] class RDDsServlet extends ServletBase {
         case _: java.sql.Timestamp =>
           hc.asH2OFrame(rdd.asInstanceOf[RDD[java.sql.Timestamp]], name)
         case _: Product =>
-          val first = rdd.asInstanceOf[RDD[Product]].first()
-          val fields = ScalaReflection.getConstructorParameters(first.getClass).map { v =>
+          val cls = rdd.asInstanceOf[RDD[Product]].first().getClass
+          val rm = runtimeMirror(cls.getClassLoader)
+          val classSymbol = rm.staticClass(cls.getName)
+          val tpe = classSymbol.selfType
+          val fields = ScalaReflection.getConstructorParameters(tpe).map { v =>
             val schema = ScalaReflection.schemaFor(v._2)
             StructField(v._1, schema.dataType, schema.nullable)
           }
           val df = SparkSessionUtils.active
             .createDataFrame(rdd.asInstanceOf[RDD[Product]].map(Row.fromTuple), StructType(fields))
-          hc.asH2OFrame(df, name)
+          hc.asH2OFrame(df, name)        
         case t => throw new IllegalArgumentException(s"Do not understand type $t")
       }
     }

gradle.properties

@@ -29,7 +29,7 @@ pythonEnvironments=2.7 3.6 3.7 3.8
 # Select for which Spark version is Sparkling Water built by default
 spark=3.5
 # Sparkling Water Version
-version=3.36.1.6-1-SNAPSHOT
+version=3.36.1.5-1-evg2
 # Spark version from which is Kubernetes Supported
 kubernetesSupportSinceSpark=2.4
 databricksTestSinceSpark=2.4