diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/FrequentItems.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/FrequentItems.scala
index 34bd243d58de9efc149956f2c27bed243616c92e..b19344f04383f7dfabe17ccbf244af24a97fd8bd 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/FrequentItems.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/FrequentItems.scala
@@ -40,7 +40,7 @@ private[sql] object FrequentItems extends Logging {
         if (baseMap.size < size) {
           baseMap += key -> count
         } else {
-          val minCount = baseMap.values.min
+          val minCount = if (baseMap.values.isEmpty) 0 else baseMap.values.min
           val remainder = count - minCount
           if (remainder >= 0) {
             baseMap += key -> count // something will get kicked out, so we can add this
@@ -83,7 +83,7 @@ private[sql] object FrequentItems extends Logging {
       df: DataFrame,
       cols: Seq[String],
       support: Double): DataFrame = {
-    require(support >= 1e-4, s"support ($support) must be greater than 1e-4.")
+    require(support >= 1e-4 && support <= 1.0, s"Support must be in [1e-4, 1], but got $support.")
     val numCols = cols.length
     // number of max items to keep counts for
     val sizeOfMap = (1 / support).toInt
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameStatSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameStatSuite.scala
index ab7733b239f283fba7465c03f2d52df000051880..73026c749db450afb61f00f4fc85dbde797edec4 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameStatSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameStatSuite.scala
@@ -235,6 +235,17 @@ class DataFrameStatSuite extends QueryTest with SharedSQLContext {
     assert(items.length === 1)
   }
 
+  test("SPARK-15709: Prevent `UnsupportedOperationException: empty.min` in `freqItems`") {
+    val ds = spark.createDataset(Seq(1, 2, 2, 3, 3, 3))
+
+    intercept[IllegalArgumentException] {
+      ds.stat.freqItems(Seq("value"), 0)
+    }
+    intercept[IllegalArgumentException] {
+      ds.stat.freqItems(Seq("value"), 2)
+    }
+  }
+
   test("sampleBy") {
     val df = spark.range(0, 100).select((col("id") % 3).as("key"))
     val sampled = df.stat.sampleBy("key", Map(0 -> 0.1, 1 -> 0.2), 0L)