Improve contains_column by invoking contains_table (rapidsai#14238)

Part of #rapidsai#12261

This PR simplifies the `contains_column` implementation by invoking `contains_table` and gets rid of the use of the cudf `unordered_multiset`. It also removes the `unordered_multiset` header file from libcudf.

Authors:
  - Yunsong Wang (https://github.com/PointKernel)

Approvers:
  - Nghia Truong (https://github.com/ttnghia)
  - Bradley Dice (https://github.com/bdice)

URL: rapidsai#14238

cpp/src/search/contains_column.cu

@@ -14,85 +14,22 @@
  * limitations under the License.
  */
 
-#include <hash/unordered_multiset.cuh>
-
-#include <cudf/column/column_factories.hpp>
 #include <cudf/detail/null_mask.hpp>
 #include <cudf/detail/nvtx/ranges.hpp>
 #include <cudf/detail/search.hpp>
 #include <cudf/dictionary/detail/search.hpp>
 #include <cudf/dictionary/detail/update_keys.hpp>
 #include <cudf/table/table_view.hpp>
-#include <cudf/utilities/default_stream.hpp>
 
 #include <rmm/cuda_stream_view.hpp>
-#include <rmm/exec_policy.hpp>
-
-#include <thrust/iterator/counting_iterator.h>
-#include <thrust/transform.h>
-#include <thrust/uninitialized_fill.h>
 
 namespace cudf {
 namespace detail {
 
 namespace {
 
 struct contains_column_dispatch {
-  template <typename Element, typename Haystack>
-  struct contains_fn {
-    bool __device__ operator()(size_type const idx) const
-    {
-      if (needles_have_nulls && needles.is_null_nocheck(idx)) {
-        // Exit early. The value doesn't matter, and will be masked as a null element.
-        return true;
-      }
-
-      return haystack.contains(needles.template element<Element>(idx));
-    }
-
-    Haystack const haystack;
-    column_device_view const needles;
-    bool const needles_have_nulls;
-  };
-
-  template <typename Element, CUDF_ENABLE_IF(!is_nested<Element>())>
-  std::unique_ptr<column> operator()(column_view const& haystack,
-                                     column_view const& needles,
-                                     rmm::cuda_stream_view stream,
-                                     rmm::mr::device_memory_resource* mr) const
-  {
-    auto result = make_numeric_column(data_type{type_to_id<bool>()},
-                                      needles.size(),
-                                      copy_bitmask(needles, stream, mr),
-                                      needles.null_count(),
-                                      stream,
-                                      mr);
-    if (needles.is_empty()) { return result; }
-
-    auto const out_begin = result->mutable_view().template begin<bool>();
-    if (haystack.is_empty()) {
-      thrust::uninitialized_fill(
-        rmm::exec_policy(stream), out_begin, out_begin + needles.size(), false);
-      return result;
-    }
-
-    auto const haystack_set = cudf::detail::unordered_multiset<Element>::create(haystack, stream);
-    auto const haystack_set_dv = haystack_set.to_device();
-    auto const needles_cdv_ptr = column_device_view::create(needles, stream);
-
-    thrust::transform(rmm::exec_policy(stream),
-                      thrust::make_counting_iterator<size_type>(0),
-                      thrust::make_counting_iterator<size_type>(needles.size()),
-                      out_begin,
-                      contains_fn<Element, decltype(haystack_set_dv)>{
-                        haystack_set_dv, *needles_cdv_ptr, needles.has_nulls()});
-
-    result->set_null_count(needles.null_count());
-
-    return result;
-  }
-
-  template <typename Element, CUDF_ENABLE_IF(is_nested<Element>())>
+  template <typename Element>
   std::unique_ptr<column> operator()(column_view const& haystack,
                                      column_view const& needles,
                                      rmm::cuda_stream_view stream,
@@ -144,8 +81,6 @@ std::unique_ptr<column> contains(column_view const& haystack,
                                  rmm::cuda_stream_view stream,
                                  rmm::mr::device_memory_resource* mr)
 {
-  CUDF_EXPECTS(haystack.type() == needles.type(), "DTYPE mismatch");
-
   return cudf::type_dispatcher(
     haystack.type(), contains_column_dispatch{}, haystack, needles, stream, mr);
 }