Thread stream and mr through empty output construction

Since we call make_lists_column in some cases, we need a stream and mr around.
rapidsai · Dec 17, 2024 · 3bb751d · 3bb751d
1 parent 4591523
commit 3bb751d
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Showing 4 changed files with 25 additions and 10 deletions.
diff --git a/cpp/src/rolling/detail/rolling.cuh b/cpp/src/rolling/detail/rolling.cuh
@@ -51,6 +51,7 @@
 
 #include <rmm/cuda_stream_view.hpp>
 #include <rmm/exec_policy.hpp>
+#include <rmm/resource_ref.hpp>
 
 #include <cuda/std/climits>
 #include <cuda/std/limits>
@@ -453,7 +454,10 @@ struct DeviceRollingRowNumber {
 
 struct agg_specific_empty_output {
   template <typename InputType, aggregation::Kind op>
-  std::unique_ptr<column> operator()(column_view const& input, rolling_aggregation const&) const
+  std::unique_ptr<column> operator()(column_view const& input,
+                                     rolling_aggregation const&,
+                                     rmm::cuda_stream_view stream,
+                                     rmm::device_async_resource_ref mr) const
   {
     using target_type = cudf::detail::target_type_t<InputType, op>;
 
@@ -467,15 +471,18 @@ struct agg_specific_empty_output {
 
     if constexpr (op == aggregation::COLLECT_LIST) {
       return cudf::make_lists_column(
-        0, make_empty_column(type_to_id<size_type>()), empty_like(input), 0, {});
+        0, make_empty_column(type_to_id<size_type>()), empty_like(input), 0, {}, stream, mr);
     }
 
     return empty_like(input);
   }
 };
 
-static std::unique_ptr<column> empty_output_for_rolling_aggregation(column_view const& input,
-                                                                    rolling_aggregation const& agg)
+static std::unique_ptr<column> empty_output_for_rolling_aggregation(
+  column_view const& input,
+  rolling_aggregation const& agg,
+  rmm::cuda_stream_view stream,
+  rmm::device_async_resource_ref mr)
 {
   // TODO:
   //  Ideally, for UDF aggregations, the returned column would match
@@ -490,7 +497,7 @@ static std::unique_ptr<column> empty_output_for_rolling_aggregation(column_view
   return agg.kind == aggregation::CUDA || agg.kind == aggregation::PTX
            ? empty_like(input)
            : cudf::detail::dispatch_type_and_aggregation(
-               input.type(), agg.kind, agg_specific_empty_output{}, input, agg);
+               input.type(), agg.kind, agg_specific_empty_output{}, input, agg, stream, mr);
 }
 
 /**
@@ -1326,7 +1333,9 @@ std::unique_ptr<column> rolling_window(column_view const& input,
   static_assert(warp_size == cudf::detail::size_in_bits<cudf::bitmask_type>(),
                 "bitmask_type size does not match CUDA warp size");
 
-  if (input.is_empty()) { return cudf::detail::empty_output_for_rolling_aggregation(input, agg); }
+  if (input.is_empty()) {
+    return cudf::detail::empty_output_for_rolling_aggregation(input, agg, stream, mr);
+  }
 
   if (cudf::is_dictionary(input.type())) {
     CUDF_EXPECTS(agg.kind == aggregation::COUNT_ALL || agg.kind == aggregation::COUNT_VALID ||

diff --git a/cpp/src/rolling/detail/rolling_fixed_window.cu b/cpp/src/rolling/detail/rolling_fixed_window.cu
@@ -40,7 +40,9 @@ std::unique_ptr<column> rolling_window(column_view const& input,
 {
   CUDF_FUNC_RANGE();
 
-  if (input.is_empty()) { return cudf::detail::empty_output_for_rolling_aggregation(input, agg); }
+  if (input.is_empty()) {
+    return cudf::detail::empty_output_for_rolling_aggregation(input, agg, stream, mr);
+  }
 
   CUDF_EXPECTS((min_periods >= 0), "min_periods must be non-negative");
 

diff --git a/cpp/src/rolling/detail/rolling_variable_window.cu b/cpp/src/rolling/detail/rolling_variable_window.cu
@@ -39,7 +39,7 @@ std::unique_ptr<column> rolling_window(column_view const& input,
   CUDF_FUNC_RANGE();
 
   if (preceding_window.is_empty() || following_window.is_empty() || input.is_empty()) {
-    return cudf::detail::empty_output_for_rolling_aggregation(input, agg);
+    return cudf::detail::empty_output_for_rolling_aggregation(input, agg, stream, mr);
   }
 
   CUDF_EXPECTS(preceding_window.type().id() == type_id::INT32 &&

diff --git a/cpp/src/rolling/grouped_rolling.cu b/cpp/src/rolling/grouped_rolling.cu
@@ -158,7 +158,9 @@ std::unique_ptr<column> grouped_rolling_window(table_view const& group_keys,
 {
   CUDF_FUNC_RANGE();
 
-  if (input.is_empty()) { return cudf::detail::empty_output_for_rolling_aggregation(input, aggr); }
+  if (input.is_empty()) {
+    return cudf::detail::empty_output_for_rolling_aggregation(input, aggr, stream, mr);
+  }
 
   CUDF_EXPECTS((group_keys.num_columns() == 0 || group_keys.num_rows() == input.size()),
                "Size mismatch between group_keys and input vector.");
@@ -1152,7 +1154,9 @@ std::unique_ptr<column> grouped_range_rolling_window(table_view const& group_key
 {
   CUDF_FUNC_RANGE();
 
-  if (input.is_empty()) { return cudf::detail::empty_output_for_rolling_aggregation(input, aggr); }
+  if (input.is_empty()) {
+    return cudf::detail::empty_output_for_rolling_aggregation(input, aggr, stream, mr);
+  }
 
   CUDF_EXPECTS((group_keys.num_columns() == 0 || group_keys.num_rows() == input.size()),
                "Size mismatch between group_keys and input vector.");