diff --git a/integration_tests/src/main/python/orc_cast_test.py b/integration_tests/src/main/python/orc_cast_test.py
index 48dbad54e51..c10d0b01570 100644
--- a/integration_tests/src/main/python/orc_cast_test.py
+++ b/integration_tests/src/main/python/orc_cast_test.py
@@ -102,8 +102,6 @@ def test_casting_from_float_and_double(spark_tmp_path, to_type):
         lambda spark: spark.read.schema(schema_str).orc(orc_path)
     )
 
-
-@datagen_overrides(seed=0, reason='https://github.com/NVIDIA/spark-rapids/issues/10017')
 @pytest.mark.parametrize('data_gen', [DoubleGen(max_exp=32, special_cases=None),
                                       DoubleGen(max_exp=32, special_cases=[8.88e9, 9.99e10, 1.314e11])])
 @allow_non_gpu(*non_utc_allow_orc_scan)
diff --git a/sql-plugin/src/main/scala/com/nvidia/spark/rapids/GpuOrcScan.scala b/sql-plugin/src/main/scala/com/nvidia/spark/rapids/GpuOrcScan.scala
index cabd9258d11..f638a7ba26a 100644
--- a/sql-plugin/src/main/scala/com/nvidia/spark/rapids/GpuOrcScan.scala
+++ b/sql-plugin/src/main/scala/com/nvidia/spark/rapids/GpuOrcScan.scala
@@ -363,17 +363,39 @@ object GpuOrcScan {
         //     val doubleMillis = doubleValue * 1000,
         //     val milliseconds = Math.round(doubleMillis)
         //     if (noOverflow) { milliseconds } else { null }
+
+        // java.lang.Math.round is a true half up, meaning rounding towards positive infinity
+        // even for negative numbers
+        //   assert(Math.round(-1.5) = -1
+        //   assert(Math.round(1.5) = 2
+        //
+        // libcudf, Spark implement it half up in a half away from zero fashion
+        // >> sql("SELECT ROUND(-1.5D, 0), ROUND(-0.5D, 0), ROUND(0.5D, 0)").show(truncate=False)
+        // +--------------+--------------+-------------+
+        // |round(-1.5, 0)|round(-0.5, 0)|round(0.5, 0)|
+        // +--------------+--------------+-------------+
+        // |-2.0          |-1.0          |1.0          |
+        // +--------------+--------------+-------------+
+        //
+        // Math.round half up can be implemented in terms of floor
+        // Math.round(x) = n iff x is in [n-0.5, n+0.5) iff x+0.5 is in [n,n+1) iff floor(x+0.5) = n
+        //
         val milliseconds = withResource(Scalar.fromDouble(DateTimeConstants.MILLIS_PER_SECOND)) {
           thousand =>
           // ORC assumes value is in seconds
           withResource(col.mul(thousand, DType.FLOAT64)) { doubleMillis =>
-            withResource(doubleMillis.round()) { millis =>
-              withResource(getOverflowFlags(doubleMillis, millis)) { overflowFlags =>
-                millis.copyWithBooleanColumnAsValidity(overflowFlags)
+            withResource(Scalar.fromDouble(0.5)) { half =>
+              withResource(doubleMillis.add(half)) { doubleMillisPlusHalf =>
+                withResource(doubleMillisPlusHalf.floor()) { millis =>
+                  withResource(getOverflowFlags(doubleMillis, millis)) { overflowFlags =>
+                    millis.copyWithBooleanColumnAsValidity(overflowFlags)
+                  }
+                }
               }
             }
           }
         }
+
         // Cast milli-seconds to micro-seconds
         // We need to pay attention that when convert (milliSeconds * 1000) to INT64, there may be
         // INT64-overflow.