diff --git a/cpp/src/groupby/sort/group_single_pass_reduction_util.cuh b/cpp/src/groupby/sort/group_single_pass_reduction_util.cuh
index dde4e00eb4a..8e1463f7964 100644
--- a/cpp/src/groupby/sort/group_single_pass_reduction_util.cuh
+++ b/cpp/src/groupby/sort/group_single_pass_reduction_util.cuh
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2019-2021, NVIDIA CORPORATION.
+ * Copyright (c) 2019-2022, NVIDIA CORPORATION.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -74,12 +74,16 @@ struct element_arg_minmax_fn {
 /**
  * @brief Value accessor for column which supports dictionary column too.
  *
+ * This is similar to `value_accessor` in `column_device_view.cuh` but with support of dictionary
+ * type.
+ *
  * @tparam T Type of the underlying column. For dictionary column, type of the key column.
  */
 template <typename T>
 struct value_accessor {
   column_device_view const col;
   bool const is_dict;
+
   value_accessor(column_device_view const& col) : col(col), is_dict(cudf::is_dictionary(col.type()))
   {
   }
@@ -93,6 +97,7 @@ struct value_accessor {
       return col.element<T>(i);
     }
   }
+
   __device__ auto operator()(size_type i) const { return value(i); }
 };
 
@@ -100,20 +105,28 @@ struct value_accessor {
  * @brief Null replaced value accessor for column which supports dictionary column too.
  * For null value, returns null `init` value
  *
- * @tparam T Type of the underlying column. For dictionary column, type of the key column.
+ * @tparam SourceType Type of the underlying column. For dictionary column, type of the key column.
+ * @tparam TargetType Type that is used for computation.
  */
-template <typename T>
-struct null_replaced_value_accessor : value_accessor<T> {
-  using super_t = value_accessor<T>;
+template <typename SourceType, typename TargetType>
+struct null_replaced_value_accessor : value_accessor<SourceType> {
+  using super_t = value_accessor<SourceType>;
+
+  TargetType const init;
   bool const has_nulls;
-  T const init;
-  null_replaced_value_accessor(column_device_view const& col, T const& init, bool const has_nulls)
+
+  null_replaced_value_accessor(column_device_view const& col,
+                               TargetType const& init,
+                               bool const has_nulls)
     : super_t(col), init(init), has_nulls(has_nulls)
   {
   }
-  __device__ T operator()(size_type i) const
+
+  __device__ TargetType operator()(size_type i) const
   {
-    return has_nulls && super_t::col.is_null_nocheck(i) ? init : super_t::value(i);
+    return has_nulls && super_t::col.is_null_nocheck(i)
+             ? init
+             : static_cast<TargetType>(super_t::value(i));
   }
 };
 
@@ -168,7 +181,7 @@ struct group_reduction_functor<K, T, std::enable_if_t<is_group_reduction_support
                                         rmm::mr::device_memory_resource* mr)
 
   {
-    using DeviceType  = device_storage_type_t<T>;
+    using SourceDType = device_storage_type_t<T>;
     using ResultType  = cudf::detail::target_type_t<T, K>;
     using ResultDType = device_storage_type_t<ResultType>;
 
@@ -203,9 +216,11 @@ struct group_reduction_functor<K, T, std::enable_if_t<is_group_reduction_support
       do_reduction(count_iter, result_begin, binop);
     } else {
       using OpType    = cudf::detail::corresponding_operator_t<K>;
-      auto init       = OpType::template identity<DeviceType>();
+      auto init       = OpType::template identity<ResultDType>();
       auto inp_values = cudf::detail::make_counting_transform_iterator(
-        0, null_replaced_value_accessor{*d_values_ptr, init, values.has_nulls()});
+        0,
+        null_replaced_value_accessor<SourceDType, ResultDType>{
+          *d_values_ptr, init, values.has_nulls()});
       do_reduction(inp_values, result_begin, OpType{});
     }
 
diff --git a/cpp/tests/groupby/sum_tests.cpp b/cpp/tests/groupby/sum_tests.cpp
index 5947e309bec..be7da4a784c 100644
--- a/cpp/tests/groupby/sum_tests.cpp
+++ b/cpp/tests/groupby/sum_tests.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2019-2021, NVIDIA CORPORATION.
+ * Copyright (c) 2019-2022, NVIDIA CORPORATION.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -156,6 +156,27 @@ TYPED_TEST(groupby_sum_test, dictionary)
                   force_use_sort_impl::YES);
 }
 
+struct overflow_test : public cudf::test::BaseFixture {
+};
+TEST_F(overflow_test, overflow_integer)
+{
+  using int32_col = fixed_width_column_wrapper<int32_t>;
+  using int64_col = fixed_width_column_wrapper<int64_t>;
+
+  auto const keys        = int32_col{0, 0};
+  auto const vals        = int32_col{-2147483648, -2147483648};
+  auto const expect_keys = int32_col{0};
+  auto const expect_vals = int64_col{-4294967296L};
+
+  auto test_sum = [&](auto const use_sort) {
+    auto agg = make_sum_aggregation<groupby_aggregation>();
+    test_single_agg(keys, vals, expect_keys, expect_vals, std::move(agg), use_sort);
+  };
+
+  test_sum(force_use_sort_impl::NO);
+  test_sum(force_use_sort_impl::YES);
+}
+
 template <typename T>
 struct FixedPointTestAllReps : public cudf::test::BaseFixture {
 };