Remove null mask and null count from column_view constructors (#13311)

This is a breaking change that removes default values. Removing the default null count value of `UNKNOWN_NULL_COUNT` is necessary since we are removing `UNKNOWN_NULL_COUNT` altogether. A potential alternative was setting the default to 0, which would correspond to a default null mask of `nullptr` (the current default). However, that change is potentially more dangerous if callers were previously setting the null mask to something other than `nullptr` without setting the null count and relying on the behavior of `UNKNOWN_NULL_COUNT`. Removing the default parameter altogether is therefore the safer option here.

Contributes to #11968.

Authors:
  - Vyas Ramasubramani (https://github.com/vyasr)

Approvers:
  - David Wendt (https://github.com/davidwendt)
  - Nghia Truong (https://github.com/ttnghia)
  - Vukasin Milovanovic (https://github.com/vuule)

URL: #13311

cpp/include/cudf/column/column_view.hpp

@@ -280,17 +280,17 @@ class column_view_base {
    * @param type The element type
    * @param size The number of elements
    * @param data Pointer to device memory containing the column elements
-   * @param null_mask Optional, pointer to device memory containing the null
+   * @param null_mask Pointer to device memory containing the null
    * indicator bitmask
-   * @param null_count Optional, the number of null elements.
-   * @param offset optional, index of the first element
+   * @param null_count The number of null elements.
+   * @param offset Optional, index of the first element
    */
   column_view_base(data_type type,
                    size_type size,
                    void const* data,
-                   bitmask_type const* null_mask = nullptr,
-                   size_type null_count          = UNKNOWN_NULL_COUNT,
-                   size_type offset              = 0);
+                   bitmask_type const* null_mask,
+                   size_type null_count,
+                   size_type offset = 0);
 };
 
 class mutable_column_view_base : public column_view_base {
@@ -374,18 +374,18 @@ class column_view : public detail::column_view_base {
    * @param type The element type
    * @param size The number of elements
    * @param data Pointer to device memory containing the column elements
-   * @param null_mask Optional, pointer to device memory containing the null
+   * @param null_mask Pointer to device memory containing the null
    * indicator bitmask
-   * @param null_count Optional, the number of null elements.
-   * @param offset optional, index of the first element
-   * @param children optional, depending on the element type, child columns may
+   * @param null_count The number of null elements.
+   * @param offset Optional, index of the first element
+   * @param children Optional, depending on the element type, child columns may
    * contain additional data
    */
   column_view(data_type type,
               size_type size,
               void const* data,
-              bitmask_type const* null_mask            = nullptr,
-              size_type null_count                     = UNKNOWN_NULL_COUNT,
+              bitmask_type const* null_mask,
+              size_type null_count,
               size_type offset                         = 0,
               std::vector<column_view> const& children = {});
 
@@ -528,19 +528,19 @@ class mutable_column_view : public detail::column_view_base {
    * @param type The element type
    * @param size The number of elements
    * @param data Pointer to device memory containing the column elements
-   * @param null_mask Optional, pointer to device memory containing the null
+   * @param null_mask Pointer to device memory containing the null
    indicator
    * bitmask
-   * @param null_count Optional, the number of null elements.
-   * @param offset optional, index of the first element
-   * @param children optional, depending on the element type, child columns may
+   * @param null_count The number of null elements.
+   * @param offset Optional, index of the first element
+   * @param children Optional, depending on the element type, child columns may
    * contain additional data
    */
   mutable_column_view(data_type type,
                       size_type size,
                       void* data,
-                      bitmask_type* null_mask                          = nullptr,
-                      size_type null_count                             = cudf::UNKNOWN_NULL_COUNT,
+                      bitmask_type* null_mask,
+                      size_type null_count,
                       size_type offset                                 = 0,
                       std::vector<mutable_column_view> const& children = {});
 

cpp/include/cudf/strings/convert/convert_datetime.hpp

@@ -243,7 +243,7 @@ std::unique_ptr<column> from_timestamps(
   column_view const& timestamps,
   std::string_view format             = "%Y-%m-%dT%H:%M:%SZ",
   strings_column_view const& names    = strings_column_view(column_view{
-    data_type{type_id::STRING}, 0, nullptr}),
+    data_type{type_id::STRING}, 0, nullptr, nullptr, 0}),
   rmm::mr::device_memory_resource* mr = rmm::mr::get_current_device_resource());
 
 /** @} */  // end of doxygen group

cpp/include/cudf/strings/convert/convert_lists.hpp

@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2021-2022, NVIDIA CORPORATION.
+ * Copyright (c) 2021-2023, NVIDIA CORPORATION.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -60,7 +60,7 @@ std::unique_ptr<column> format_list_column(
   lists_column_view const& input,
   string_scalar const& na_rep           = string_scalar("NULL"),
   strings_column_view const& separators = strings_column_view(column_view{
-    data_type{type_id::STRING}, 0, nullptr}),
+    data_type{type_id::STRING}, 0, nullptr, nullptr, 0}),
   rmm::mr::device_memory_resource* mr   = rmm::mr::get_current_device_resource());
 
 /** @} */  // end of doxygen group

cpp/include/cudf_test/tdigest_utilities.cuh

@@ -179,7 +179,7 @@ void tdigest_minmax_compare(cudf::tdigest::tdigest_column_view const& tdv,
                     spans.end(),
                     expected_min->mutable_view().template begin<double>(),
                     column_min<T>{});
-  column_view result_min(data_type{type_id::FLOAT64}, tdv.size(), tdv.min_begin());
+  column_view result_min(data_type{type_id::FLOAT64}, tdv.size(), tdv.min_begin(), nullptr, 0);
   CUDF_TEST_EXPECT_COLUMNS_EQUAL(result_min, *expected_min);
 
   auto expected_max = cudf::make_fixed_width_column(
@@ -189,7 +189,7 @@ void tdigest_minmax_compare(cudf::tdigest::tdigest_column_view const& tdv,
                     spans.end(),
                     expected_max->mutable_view().template begin<double>(),
                     column_max<T>{});
-  column_view result_max(data_type{type_id::FLOAT64}, tdv.size(), tdv.max_begin());
+  column_view result_max(data_type{type_id::FLOAT64}, tdv.size(), tdv.max_begin(), nullptr, 0);
   CUDF_TEST_EXPECT_COLUMNS_EQUAL(result_max, *expected_max);
 }
 

cpp/src/binaryop/compiled/binary_ops.cu

@@ -50,8 +50,11 @@ struct scalar_as_column_view {
   return_type operator()(scalar const& s, rmm::cuda_stream_view, rmm::mr::device_memory_resource*)
   {
     auto& h_scalar_type_view = static_cast<cudf::scalar_type_t<T>&>(const_cast<scalar&>(s));
-    auto col_v =
-      column_view(s.type(), 1, h_scalar_type_view.data(), (bitmask_type const*)s.validity_data());
+    auto col_v               = column_view(s.type(),
+                             1,
+                             h_scalar_type_view.data(),
+                             reinterpret_cast<bitmask_type const*>(s.validity_data()),
+                             !s.is_valid());
     return std::pair{col_v, std::unique_ptr<column>(nullptr)};
   }
   template <typename T, CUDF_ENABLE_IF(!is_fixed_width<T>())>
@@ -74,8 +77,8 @@ scalar_as_column_view::return_type scalar_as_column_view::operator()<cudf::strin
   auto offsets_column = std::get<0>(cudf::detail::make_offsets_child_column(
     offsets_transformer_itr, offsets_transformer_itr + 1, stream, mr));
 
-  auto chars_column_v =
-    column_view(data_type{type_id::INT8}, h_scalar_type_view.size(), h_scalar_type_view.data());
+  auto chars_column_v = column_view(
+    data_type{type_id::INT8}, h_scalar_type_view.size(), h_scalar_type_view.data(), nullptr, 0);
   // Construct string column_view
   auto col_v = column_view(s.type(),
                            1,

cpp/src/column/column_factories.cu

@@ -57,7 +57,7 @@ std::unique_ptr<cudf::column> column_from_scalar_dispatch::operator()<cudf::stri
 
   // Since we are setting every row to the scalar, the fill() never needs to access
   // any of the children in the strings column which would otherwise cause an exception.
-  column_view sc{value.type(), size, nullptr};
+  column_view sc{value.type(), size, nullptr, nullptr, 0};
   auto& sv = static_cast<scalar_type_t<cudf::string_view> const&>(value);
 
   // fill the column with the scalar

cpp/src/copying/copy.cpp

@@ -66,7 +66,7 @@ struct scalar_empty_like_functor_impl<cudf::list_view> {
     auto ls = static_cast<list_scalar const*>(&input);
 
     // TODO:  add a manual constructor for lists_column_view.
-    column_view offsets{cudf::data_type{cudf::type_id::INT32}, 0, nullptr};
+    column_view offsets{cudf::data_type{cudf::type_id::INT32}, 0, nullptr, nullptr, 0};
     std::vector<column_view> children;
     children.push_back(offsets);
     children.push_back(ls->view());

cpp/src/copying/copy.cu

@@ -207,7 +207,9 @@ std::unique_ptr<column> scatter_gather_based_if_else(cudf::scalar const& lhs,
   auto scatter_source          = std::vector<std::reference_wrapper<const scalar>>{std::ref(lhs)};
   auto scatter_map_column_view = cudf::column_view{cudf::data_type{cudf::type_id::INT32},
                                                    static_cast<cudf::size_type>(scatter_map_size),
-                                                   scatter_map.begin()};
+                                                   scatter_map.begin(),
+                                                   nullptr,
+                                                   0};
 
   auto result = cudf::detail::scatter(
     scatter_source, scatter_map_column_view, table_view{std::vector<column_view>{rhs}}, stream, mr);

cpp/src/copying/gather.cu

@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2019-2022, NVIDIA CORPORATION.
+ * Copyright (c) 2019-2023, NVIDIA CORPORATION.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -68,7 +68,9 @@ std::unique_ptr<table> gather(table_view const& source_table,
                "invalid gather map size");
   auto map_col = column_view(data_type{type_to_id<size_type>()},
                              static_cast<size_type>(gather_map.size()),
-                             gather_map.data());
+                             gather_map.data(),
+                             nullptr,
+                             0);
   return gather(source_table, map_col, bounds_policy, neg_indices, stream, mr);
 }
 

cpp/src/copying/scatter.cu

@@ -324,7 +324,9 @@ std::unique_ptr<table> scatter(table_view const& source,
                "invalid scatter map size");
   auto map_col = column_view(data_type{type_to_id<size_type>()},
                              static_cast<size_type>(scatter_map.size()),
-                             scatter_map.data());
+                             scatter_map.data(),
+                             nullptr,
+                             0);
   return scatter(source, map_col, target, stream, mr);
 }
 

cpp/src/dictionary/detail/concatenate.cu

@@ -216,7 +216,7 @@ std::unique_ptr<column> concatenate(host_span<column_view const> columns,
   std::transform(columns.begin(), columns.end(), keys_views.begin(), [keys_type](auto cv) {
     auto dict_view = dictionary_column_view(cv);
     // empty column may not have keys so we create an empty column_view place-holder
-    if (dict_view.is_empty()) return column_view{keys_type, 0, nullptr};
+    if (dict_view.is_empty()) return column_view{keys_type, 0, nullptr, nullptr, 0};
     auto keys = dict_view.keys();
     CUDF_EXPECTS(keys.type() == keys_type, "key types of all dictionary columns must match");
     return keys;
@@ -245,7 +245,9 @@ std::unique_ptr<column> concatenate(host_span<column_view const> columns,
   std::vector<column_view> indices_views(columns.size());
   std::transform(columns.begin(), columns.end(), indices_views.begin(), [](auto cv) {
     auto dict_view = dictionary_column_view(cv);
-    if (dict_view.is_empty()) return column_view{data_type{type_id::UINT32}, 0, nullptr};
+    if (dict_view.is_empty()) {
+      return column_view{data_type{type_id::UINT32}, 0, nullptr, nullptr, 0};
+    }
     return dict_view.get_indices_annotated();  // nicely includes validity mask and view offset
   });
   auto all_indices        = cudf::detail::concatenate(indices_views, stream, mr);

cpp/src/dictionary/dictionary_factories.cu

@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2020-2021, NVIDIA CORPORATION.
+ * Copyright (c) 2020-2023, NVIDIA CORPORATION.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -137,7 +137,8 @@ std::unique_ptr<column> make_dictionary_column(std::unique_ptr<column> keys,
         new_type, indices_size, std::move(*(contents.data.release())), rmm::device_buffer{}, 0);
     }
     // If the new type does not match, then convert the data.
-    cudf::column_view cast_view{cudf::data_type{indices_type}, indices_size, contents.data->data()};
+    cudf::column_view cast_view{
+      cudf::data_type{indices_type}, indices_size, contents.data->data(), nullptr, 0};
     return cudf::detail::cast(cast_view, new_type, stream, mr);
   }();
 

cpp/src/dictionary/remove_keys.cu

@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2020-2022, NVIDIA CORPORATION.
+ * Copyright (c) 2020-2023, NVIDIA CORPORATION.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -178,7 +178,8 @@ std::unique_ptr<column> remove_unused_keys(dictionary_column_view const& diction
     rmm::device_uvector<uint32_t> keys_positions(keys_size, stream);
     thrust::sequence(rmm::exec_policy(stream), keys_positions.begin(), keys_positions.end());
     // wrap the indices for comparison in contains()
-    column_view keys_positions_view(data_type{type_id::UINT32}, keys_size, keys_positions.data());
+    column_view keys_positions_view(
+      data_type{type_id::UINT32}, keys_size, keys_positions.data(), nullptr, 0);
     return cudf::detail::contains(indices_view, keys_positions_view, stream, mr);
   }();
   auto d_matches = matches->view().data<bool>();

cpp/src/groupby/hash/groupby.cu

@@ -250,7 +250,9 @@ class hash_compound_agg_finalizer final : public cudf::detail::aggregation_final
     column_view null_removed_map(
       data_type(type_to_id<size_type>()),
       arg_result->size(),
-      static_cast<void const*>(arg_result->view().template data<size_type>()));
+      static_cast<void const*>(arg_result->view().template data<size_type>()),
+      nullptr,
+      0);
     auto gather_argminmax =
       cudf::detail::gather(table_view({col}),
                            null_removed_map,

cpp/src/groupby/sort/aggregate.cpp

@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2019-2022, NVIDIA CORPORATION.
+ * Copyright (c) 2019-2023, NVIDIA CORPORATION.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -167,7 +167,9 @@ void aggregate_result_functor::operator()<aggregation::MIN>(aggregation const& a
       column_view null_removed_map(
         data_type(type_to_id<size_type>()),
         argmin_result.size(),
-        static_cast<void const*>(argmin_result.template data<size_type>()));
+        static_cast<void const*>(argmin_result.template data<size_type>()),
+        nullptr,
+        0);
       auto transformed_result =
         cudf::detail::gather(table_view({values}),
                              null_removed_map,
@@ -207,7 +209,9 @@ void aggregate_result_functor::operator()<aggregation::MAX>(aggregation const& a
       column_view null_removed_map(
         data_type(type_to_id<size_type>()),
         argmax_result.size(),
-        static_cast<void const*>(argmax_result.template data<size_type>()));
+        static_cast<void const*>(argmax_result.template data<size_type>()),
+        nullptr,
+        0);
       auto transformed_result =
         cudf::detail::gather(table_view({values}),
                              null_removed_map,

cpp/src/groupby/sort/sort_helper.cu

@@ -215,8 +215,11 @@ column_view sort_groupby_helper::unsorted_keys_labels(rmm::cuda_stream_view stre
   column_ptr temp_labels = make_numeric_column(
     data_type(type_to_id<size_type>()), _keys.num_rows(), mask_state::ALL_NULL, stream);
 
-  auto group_labels_view = cudf::column_view(
-    data_type(type_to_id<size_type>()), group_labels(stream).size(), group_labels(stream).data());
+  auto group_labels_view = cudf::column_view(data_type(type_to_id<size_type>()),
+                                             group_labels(stream).size(),
+                                             group_labels(stream).data(),
+                                             nullptr,
+                                             0);
 
   auto scatter_map = key_sort_order(stream);
 

cpp/src/io/csv/writer_impl.cu

@@ -251,7 +251,7 @@ struct column_to_strings_fn {
     return cudf::strings::detail::from_timestamps(
       column,
       format,
-      strings_column_view(column_view{data_type{type_id::STRING}, 0, nullptr}),
+      strings_column_view(make_empty_column(type_id::STRING)->view()),
       stream_,
       mr_);
   }

cpp/src/io/json/write_json.cu

@@ -499,7 +499,7 @@ struct column_to_strings_fn {
     return cudf::strings::detail::from_timestamps(
       column,
       format,
-      strings_column_view(column_view{data_type{type_id::STRING}, 0, nullptr}),
+      strings_column_view(column_view{data_type{type_id::STRING}, 0, nullptr, nullptr, 0}),
       stream_,
       mr_);
   }

cpp/src/sort/segmented_sort_impl.cuh

@@ -273,8 +273,8 @@ std::unique_ptr<column> segmented_sorted_order_common(
   // insert segment id before all columns.
   std::vector<column_view> keys_with_segid;
   keys_with_segid.reserve(keys.num_columns() + 1);
-  keys_with_segid.push_back(
-    column_view(data_type(type_to_id<size_type>()), segment_ids.size(), segment_ids.data()));
+  keys_with_segid.push_back(column_view(
+    data_type(type_to_id<size_type>()), segment_ids.size(), segment_ids.data(), nullptr, 0));
   keys_with_segid.insert(keys_with_segid.end(), keys.begin(), keys.end());
   auto segid_keys = table_view(keys_with_segid);
 

cpp/src/text/generate_ngrams.cu

@@ -99,8 +99,11 @@ std::unique_ptr<cudf::column> generate_ngrams(cudf::strings_column_view const& s
 
   // first create a new offsets vector removing nulls and empty strings from the input column
   std::unique_ptr<cudf::column> non_empty_offsets_column = [&] {
-    cudf::column_view offsets_view(
-      cudf::data_type{cudf::type_id::INT32}, strings_count + 1, strings.offsets_begin());
+    cudf::column_view offsets_view(cudf::data_type{cudf::type_id::INT32},
+                                   strings_count + 1,
+                                   strings.offsets_begin(),
+                                   nullptr,
+                                   0);
     auto table_offsets = cudf::detail::copy_if(
                            cudf::table_view({offsets_view}),
                            [d_strings, strings_count] __device__(cudf::size_type idx) {

cpp/src/text/tokenize.cu

@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2020-2022, NVIDIA CORPORATION.
+ * Copyright (c) 2020-2023, NVIDIA CORPORATION.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -215,7 +215,8 @@ std::unique_ptr<cudf::column> character_tokenize(cudf::strings_column_view const
     });
 
   // create the output chars column -- just a copy of the input's chars column
-  cudf::column_view chars_view(cudf::data_type{cudf::type_id::INT8}, chars_bytes, d_chars);
+  cudf::column_view chars_view(
+    cudf::data_type{cudf::type_id::INT8}, chars_bytes, d_chars, nullptr, 0);
   auto chars_column = std::make_unique<cudf::column>(chars_view, stream, mr);
 
   // return new strings column

cpp/tests/interop/dlpack_test.cpp

@@ -375,7 +375,8 @@ TYPED_TEST(DLPackNumericTests, ToDlpack1D)
 
   // Verify that data matches input column
   constexpr cudf::data_type type{cudf::type_to_id<TypeParam>()};
-  cudf::column_view const result_view(type, tensor.shape[0], tensor.data, col_view.null_mask());
+  cudf::column_view const result_view(
+    type, tensor.shape[0], tensor.data, col_view.null_mask(), col_view.null_count());
   CUDF_TEST_EXPECT_COLUMNS_EQUAL(col_view, result_view);
 }
 

cpp/tests/iterator/sizes_to_offsets_iterator_test.cu

@@ -63,8 +63,8 @@ TYPED_TEST(SizesToOffsetsIteratorTestTyped, ExclusiveScan)
 
   auto expected =
     cudf::test::fixed_width_column_wrapper<T>(expected_values.begin(), expected_values.end());
-  auto result_col =
-    cudf::column_view(cudf::data_type(cudf::type_to_id<T>()), d_view.size(), result.data());
+  auto result_col = cudf::column_view(
+    cudf::data_type(cudf::type_to_id<T>()), d_view.size(), result.data(), nullptr, 0);
 
   CUDF_TEST_EXPECT_COLUMNS_EQUIVALENT(result_col, expected);
   EXPECT_EQ(last.value(stream), expected_reduce);