diff --git a/sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala b/sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala
index becb05cf72aba..e98cab8b56d13 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala
@@ -49,9 +49,17 @@ private[sql] object SQLUtils extends Logging {
       sparkConfigMap: JMap[Object, Object],
       enableHiveSupport: Boolean): SparkSession = {
     val spark =
-      if (SparkSession.hiveClassesArePresent && enableHiveSupport &&
+      if (enableHiveSupport &&
           jsc.sc.conf.get(CATALOG_IMPLEMENTATION.key, "hive").toLowerCase(Locale.ROOT) ==
-            "hive") {
+            "hive" &&
+          // Note that the order of conditions here are on purpose.
+          // `SparkSession.hiveClassesArePresent` checks if Hive's `HiveConf` is loadable or not;
+          // however, `HiveConf` itself has some static logic to check if Hadoop version is
+          // supported or not, which throws an `IllegalArgumentException` if unsupported.
+          // If this is checked first, there's no way to disable Hive support in the case above.
+          // So, we intentionally check if Hive classes are loadable or not only when
+          // Hive support is explicitly enabled by short-circuiting. See also SPARK-26422.
+          SparkSession.hiveClassesArePresent) {
         SparkSession.builder().sparkContext(withHiveExternalCatalog(jsc.sc)).getOrCreate()
       } else {
         if (enableHiveSupport) {