diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/RandomDataGenerator.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/RandomDataGenerator.scala
index 8ae3ff5043e6..d361e6248e2f 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/RandomDataGenerator.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/RandomDataGenerator.scala
@@ -17,8 +17,6 @@
 
 package org.apache.spark.sql
 
-import java.lang.Double.longBitsToDouble
-import java.lang.Float.intBitsToFloat
 import java.math.MathContext
 
 import scala.collection.mutable
@@ -69,6 +67,28 @@ object RandomDataGenerator {
     Some(f)
   }
 
+  /**
+   * A wrapper of Float.intBitsToFloat to use a unique NaN value for all NaN values.
+   * This prevents `checkEvaluationWithUnsafeProjection` from failing due to
+   * the difference between `UnsafeRow` binary presentation for NaN.
+   * This is visible for testing.
+   */
+  def intBitsToFloat(bits: Int): Float = {
+    val value = java.lang.Float.intBitsToFloat(bits)
+    if (value.isNaN) Float.NaN else value
+  }
+
+  /**
+   * A wrapper of Double.longBitsToDouble to use a unique NaN value for all NaN values.
+   * This prevents `checkEvaluationWithUnsafeProjection` from failing due to
+   * the difference between `UnsafeRow` binary presentation for NaN.
+   * This is visible for testing.
+   */
+  def longBitsToDouble(bits: Long): Double = {
+    val value = java.lang.Double.longBitsToDouble(bits)
+    if (value.isNaN) Double.NaN else value
+  }
+
   /**
    * Returns a randomly generated schema, based on the given accepted types.
    *
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/RandomDataGeneratorSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/RandomDataGeneratorSuite.scala
index 3c2f8a28875f..3e62ca069e9e 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/RandomDataGeneratorSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/RandomDataGeneratorSuite.scala
@@ -17,6 +17,9 @@
 
 package org.apache.spark.sql
 
+import java.nio.ByteBuffer
+import java.util.Arrays
+
 import scala.util.Random
 
 import org.apache.spark.SparkFunSuite
@@ -106,4 +109,32 @@ class RandomDataGeneratorSuite extends SparkFunSuite {
       assert(deviation.toDouble / expectedTotalElements < 2e-1)
     }
   }
+
+  test("Use Float.NaN for all NaN values") {
+    val bits = -6966608
+    val nan1 = java.lang.Float.intBitsToFloat(bits)
+    val nan2 = RandomDataGenerator.intBitsToFloat(bits)
+    assert(nan1.isNaN)
+    assert(nan2.isNaN)
+
+    val arrayExpected = ByteBuffer.allocate(4).putFloat(Float.NaN).array
+    val array1 = ByteBuffer.allocate(4).putFloat(nan1).array
+    val array2 = ByteBuffer.allocate(4).putFloat(nan2).array
+    assert(!Arrays.equals(array1, arrayExpected))
+    assert(Arrays.equals(array2, arrayExpected))
+  }
+
+  test("Use Double.NaN for all NaN values") {
+    val bits = -6966608
+    val nan1 = java.lang.Double.longBitsToDouble(bits)
+    val nan2 = RandomDataGenerator.longBitsToDouble(bits)
+    assert(nan1.isNaN)
+    assert(nan2.isNaN)
+
+    val arrayExpected = ByteBuffer.allocate(8).putDouble(Double.NaN).array
+    val array1 = ByteBuffer.allocate(8).putDouble(nan1).array
+    val array2 = ByteBuffer.allocate(8).putDouble(nan2).array
+    assert(!Arrays.equals(array1, arrayExpected))
+    assert(Arrays.equals(array2, arrayExpected))
+  }
 }