Merge branch 'branch-25.02' into cross-link-cudf-pandas-profiler

cpp/CMakeLists.txt

@@ -1,5 +1,5 @@
 # =============================================================================
-# Copyright (c) 2018-2024, NVIDIA CORPORATION.
+# Copyright (c) 2018-2025, NVIDIA CORPORATION.
 #
 # Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except
 # in compliance with the License. You may obtain a copy of the License at
@@ -274,11 +274,8 @@ endif()
 # add third party dependencies using CPM
 rapids_cpm_init()
 
-# Not using rapids-cmake since we never want to find, always download.
-CPMAddPackage(
-  NAME rapids_logger GITHUB_REPOSITORY rapidsai/rapids-logger GIT_SHALLOW FALSE GIT_TAG
-  c510947ae9d3a67530cfe3e5eaccb5a3b8ea0e55 VERSION c510947ae9d3a67530cfe3e5eaccb5a3b8ea0e55
-)
+include(${rapids-cmake-dir}/cpm/rapids_logger.cmake)
+rapids_cpm_rapids_logger()
 rapids_make_logger(cudf EXPORT_SET cudf-exports)
 
 # find jitify

cpp/benchmarks/join/distinct_join.cu

@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2024, NVIDIA CORPORATION.
+ * Copyright (c) 2024-2025, NVIDIA CORPORATION.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -23,13 +23,8 @@ void distinct_inner_join(nvbench::state& state,
   auto join = [](cudf::table_view const& probe_input,
                  cudf::table_view const& build_input,
                  cudf::null_equality compare_nulls) {
-    auto const has_nulls =
-      cudf::has_nested_nulls(build_input) || cudf::has_nested_nulls(probe_input)
-        ? cudf::nullable_join::YES
-        : cudf::nullable_join::NO;
-    auto hj_obj = cudf::distinct_hash_join<cudf::has_nested::NO>{
-      build_input, probe_input, has_nulls, compare_nulls};
-    return hj_obj.inner_join();
+    auto hj_obj = cudf::distinct_hash_join{build_input, compare_nulls};
+    return hj_obj.inner_join(probe_input);
   };
 
   BM_join<Key, Nullable>(state, join);
@@ -42,13 +37,8 @@ void distinct_left_join(nvbench::state& state,
   auto join = [](cudf::table_view const& probe_input,
                  cudf::table_view const& build_input,
                  cudf::null_equality compare_nulls) {
-    auto const has_nulls =
-      cudf::has_nested_nulls(build_input) || cudf::has_nested_nulls(probe_input)
-        ? cudf::nullable_join::YES
-        : cudf::nullable_join::NO;
-    auto hj_obj = cudf::distinct_hash_join<cudf::has_nested::NO>{
-      build_input, probe_input, has_nulls, compare_nulls};
-    return hj_obj.left_join();
+    auto hj_obj = cudf::distinct_hash_join{build_input, compare_nulls};
+    return hj_obj.left_join(probe_input);
   };
 
   BM_join<Key, Nullable>(state, join);

cpp/include/cudf/detail/distinct_hash_join.cuh

@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2024, NVIDIA CORPORATION.
+ * Copyright (c) 2024-2025, NVIDIA CORPORATION.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -36,19 +36,24 @@ using cudf::experimental::row::lhs_index_type;
 using cudf::experimental::row::rhs_index_type;
 
 /**
- * @brief An comparator adapter wrapping both self comparator and two table comparator
+ * @brief A custom comparator used for the build table insertion
  */
-template <typename Equal>
-struct comparator_adapter {
-  comparator_adapter(Equal const& d_equal) : _d_equal{d_equal} {}
-
-  __device__ constexpr auto operator()(
+struct always_not_equal {
+  __device__ constexpr bool operator()(
     cuco::pair<hash_value_type, rhs_index_type> const&,
     cuco::pair<hash_value_type, rhs_index_type> const&) const noexcept
   {
     // All build table keys are distinct thus `false` no matter what
     return false;
   }
+};
+
+/**
+ * @brief An comparator adapter wrapping the two table comparator
+ */
+template <typename Equal>
+struct comparator_adapter {
+  comparator_adapter(Equal const& d_equal) : _d_equal{d_equal} {}
 
   __device__ constexpr auto operator()(
     cuco::pair<hash_value_type, lhs_index_type> const& lhs,
@@ -62,56 +67,14 @@ struct comparator_adapter {
   Equal _d_equal;
 };
 
-template <typename Hasher>
-struct hasher_adapter {
-  hasher_adapter(Hasher const& d_hasher = {}) : _d_hasher{d_hasher} {}
-
-  template <typename T>
-  __device__ constexpr auto operator()(cuco::pair<hash_value_type, T> const& key) const noexcept
-  {
-    return _d_hasher(key.first);
-  }
-
- private:
-  Hasher _d_hasher;
-};
-
 /**
  * @brief Distinct hash join that builds hash table in creation and probes results in subsequent
  * `*_join` member functions.
  *
- * @tparam HasNested Flag indicating whether there are nested columns in build/probe table
+ * This class enables the distinct hash join scheme that builds hash table once, and probes as many
+ * times as needed (possibly in parallel).
  */
-template <cudf::has_nested HasNested>
-struct distinct_hash_join {
- private:
-  /// Device row equal type
-  using d_equal_type = cudf::experimental::row::equality::strong_index_comparator_adapter<
-    cudf::experimental::row::equality::device_row_comparator<HasNested == cudf::has_nested::YES,
-                                                             cudf::nullate::DYNAMIC>>;
-  using hasher              = hasher_adapter<thrust::identity<hash_value_type>>;
-  using probing_scheme_type = cuco::linear_probing<1, hasher>;
-  using cuco_storage_type   = cuco::storage<1>;
-
-  /// Hash table type
-  using hash_table_type = cuco::static_set<cuco::pair<hash_value_type, rhs_index_type>,
-                                           cuco::extent<size_type>,
-                                           cuda::thread_scope_device,
-                                           comparator_adapter<d_equal_type>,
-                                           probing_scheme_type,
-                                           cudf::detail::cuco_allocator<char>,
-                                           cuco_storage_type>;
-
-  bool _has_nulls;  ///< true if nulls are present in either build table or probe table
-  cudf::null_equality _nulls_equal;  ///< whether to consider nulls as equal
-  cudf::table_view _build;           ///< input table to build the hash map
-  cudf::table_view _probe;           ///< input table to probe the hash map
-  std::shared_ptr<cudf::experimental::row::equality::preprocessed_table>
-    _preprocessed_build;  ///< input table preprocssed for row operators
-  std::shared_ptr<cudf::experimental::row::equality::preprocessed_table>
-    _preprocessed_probe;        ///< input table preprocssed for row operators
-  hash_table_type _hash_table;  ///< hash table built on `_build`
-
+class distinct_hash_join {
  public:
   distinct_hash_join()                                     = delete;
   ~distinct_hash_join()                                    = default;
@@ -120,21 +83,28 @@ struct distinct_hash_join {
   distinct_hash_join& operator=(distinct_hash_join const&) = delete;
   distinct_hash_join& operator=(distinct_hash_join&&)      = delete;
 
+  /**
+   * @brief Hasher adapter used by distinct hash join
+   */
+  struct hasher {
+    template <typename T>
+    __device__ constexpr hash_value_type operator()(
+      cuco::pair<hash_value_type, T> const& key) const noexcept
+    {
+      return key.first;
+    }
+  };
+
   /**
    * @brief Constructor that internally builds the hash table based on the given `build` table.
    *
    * @throw cudf::logic_error if the number of columns in `build` table is 0.
    *
    * @param build The build table, from which the hash table is built
-   * @param probe The probe table
-   * @param has_nulls Flag to indicate if any nulls exist in the `build` table or
-   *        any `probe` table that will be used later for join.
    * @param compare_nulls Controls whether null join-key values should match or not.
    * @param stream CUDA stream used for device memory operations and kernel launches.
    */
   distinct_hash_join(cudf::table_view const& build,
-                     cudf::table_view const& probe,
-                     bool has_nulls,
                      cudf::null_equality compare_nulls,
                      rmm::cuda_stream_view stream);
 
@@ -143,12 +113,36 @@ struct distinct_hash_join {
    */
   std::pair<std::unique_ptr<rmm::device_uvector<size_type>>,
             std::unique_ptr<rmm::device_uvector<size_type>>>
-  inner_join(rmm::cuda_stream_view stream, rmm::device_async_resource_ref mr) const;
+  inner_join(cudf::table_view const& probe,
+             rmm::cuda_stream_view stream,
+             rmm::device_async_resource_ref mr) const;
 
   /**
    * @copydoc cudf::distinct_hash_join::left_join
    */
   std::unique_ptr<rmm::device_uvector<size_type>> left_join(
-    rmm::cuda_stream_view stream, rmm::device_async_resource_ref mr) const;
+    cudf::table_view const& probe,
+    rmm::cuda_stream_view stream,
+    rmm::device_async_resource_ref mr) const;
+
+ private:
+  using probing_scheme_type = cuco::linear_probing<1, hasher>;
+  using cuco_storage_type   = cuco::storage<1>;
+
+  /// Hash table type
+  using hash_table_type = cuco::static_set<cuco::pair<hash_value_type, rhs_index_type>,
+                                           cuco::extent<size_type>,
+                                           cuda::thread_scope_device,
+                                           always_not_equal,
+                                           probing_scheme_type,
+                                           cudf::detail::cuco_allocator<char>,
+                                           cuco_storage_type>;
+
+  bool _has_nested_columns;  ///< True if nested columns are present in build and probe tables
+  cudf::null_equality _nulls_equal;  ///< Whether to consider nulls as equal
+  cudf::table_view _build;           ///< Input table to build the hash map
+  std::shared_ptr<cudf::experimental::row::equality::preprocessed_table>
+    _preprocessed_build;        ///< Input table preprocssed for row operators
+  hash_table_type _hash_table;  ///< Hash table built on `_build`
 };
 }  // namespace cudf::detail

cpp/include/cudf/join.hpp

@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2019-2024, NVIDIA CORPORATION.
+ * Copyright (c) 2019-2025, NVIDIA CORPORATION.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -34,13 +34,6 @@
 
 namespace CUDF_EXPORT cudf {
 
-/**
- * @brief Enum to indicate whether the distinct join table has nested columns or not
- *
- * @ingroup column_join
- */
-enum class has_nested : bool { YES, NO };
-
 // forward declaration
 namespace hashing::detail {
 
@@ -61,7 +54,6 @@ class hash_join;
 /**
  * @brief Forward declaration for our distinct hash join
  */
-template <cudf::has_nested HasNested>
 class distinct_hash_join;
 }  // namespace detail
 
@@ -469,20 +461,19 @@ class hash_join {
     rmm::device_async_resource_ref mr = cudf::get_current_device_resource_ref()) const;
 
  private:
-  const std::unique_ptr<impl_type const> _impl;
+  std::unique_ptr<impl_type const> _impl;
 };
 
 /**
  * @brief Distinct hash join that builds hash table in creation and probes results in subsequent
  * `*_join` member functions
  *
+ * This class enables the distinct hash join scheme that builds hash table once, and probes as many
+ * times as needed (possibly in parallel).
+ *
  * @note Behavior is undefined if the build table contains duplicates.
  * @note All NaNs are considered as equal
- *
- * @tparam HasNested Flag indicating whether there are nested columns in build/probe table
  */
-// TODO: `HasNested` to be removed via dispatching
-template <cudf::has_nested HasNested>
 class distinct_hash_join {
  public:
   distinct_hash_join() = delete;
@@ -496,32 +487,29 @@ class distinct_hash_join {
    * @brief Constructs a distinct hash join object for subsequent probe calls
    *
    * @param build The build table that contains distinct elements
-   * @param probe The probe table, from which the keys are probed
-   * @param has_nulls Flag to indicate if there exists any nulls in the `build` table or
-   *        any `probe` table that will be used later for join
    * @param compare_nulls Controls whether null join-key values should match or not
    * @param stream CUDA stream used for device memory operations and kernel launches
    */
   distinct_hash_join(cudf::table_view const& build,
-                     cudf::table_view const& probe,
-                     nullable_join has_nulls      = nullable_join::YES,
                      null_equality compare_nulls  = null_equality::EQUAL,
                      rmm::cuda_stream_view stream = cudf::get_default_stream());
 
   /**
    * @brief Returns the row indices that can be used to construct the result of performing
    * an inner join between two tables. @see cudf::inner_join().
    *
+   * @param probe The probe table, from which the keys are probed
    * @param stream CUDA stream used for device memory operations and kernel launches
    * @param mr Device memory resource used to allocate the returned indices' device memory.
    *
-   * @return A pair of columns [`build_indices`, `probe_indices`] that can be used to
+   * @return A pair of columns [`probe_indices`, `build_indices`] that can be used to
    * construct the result of performing an inner join between two tables
    * with `build` and `probe` as the join keys.
    */
   [[nodiscard]] std::pair<std::unique_ptr<rmm::device_uvector<size_type>>,
                           std::unique_ptr<rmm::device_uvector<size_type>>>
-  inner_join(rmm::cuda_stream_view stream      = cudf::get_default_stream(),
+  inner_join(cudf::table_view const& probe,
+             rmm::cuda_stream_view stream      = cudf::get_default_stream(),
              rmm::device_async_resource_ref mr = cudf::get_current_device_resource_ref()) const;
 
   /**
@@ -532,19 +520,22 @@ class distinct_hash_join {
    * the row index of the matched row from the build table if there is a match. Otherwise, contains
    * `JoinNoneValue`.
    *
+   * @param probe The probe table, from which the keys are probed
    * @param stream CUDA stream used for device memory operations and kernel launches
    * @param mr Device memory resource used to allocate the returned table and columns' device
    * memory.
+   *
    * @return A `build_indices` column that can be used to construct the result of
    * performing a left join between two tables with `build` and `probe` as the join
    * keys.
    */
   [[nodiscard]] std::unique_ptr<rmm::device_uvector<size_type>> left_join(
+    cudf::table_view const& probe,
     rmm::cuda_stream_view stream      = cudf::get_default_stream(),
     rmm::device_async_resource_ref mr = cudf::get_current_device_resource_ref()) const;
 
  private:
-  using impl_type = typename cudf::detail::distinct_hash_join<HasNested>;  ///< Implementation type
+  using impl_type = cudf::detail::distinct_hash_join;  ///< Implementation type
 
   std::unique_ptr<impl_type> _impl;  ///< Distinct hash join implementation
 };

cpp/src/io/fst/agent_dfa.cuh

@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2022-2024, NVIDIA CORPORATION.
+ * Copyright (c) 2022-2025, NVIDIA CORPORATION.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -308,12 +308,14 @@ class WriteCoalescingCallbackWrapper {
   {
     __syncthreads();
     if constexpr (!DiscardTranslatedOutput) {
-      for (uint32_t out_char = threadIdx.x; out_char < tile_out_count; out_char += blockDim.x) {
+      for (thread_index_type out_char = threadIdx.x; out_char < tile_out_count;
+           out_char += blockDim.x) {
         out_it[tile_out_offset + out_char] = temp_storage.compacted_symbols[out_char];
       }
     }
     if constexpr (!DiscardIndexOutput) {
-      for (uint32_t out_char = threadIdx.x; out_char < tile_out_count; out_char += blockDim.x) {
+      for (thread_index_type out_char = threadIdx.x; out_char < tile_out_count;
+           out_char += blockDim.x) {
         out_idx_it[tile_out_offset + out_char] =
           temp_storage.compacted_offset[out_char] + tile_in_offset;
       }