Add missing documentation in aggregation.hpp

cpp/include/cudf/aggregation.hpp

@@ -120,18 +120,56 @@ class aggregation {
   };
 
   aggregation() = delete;
+
+  /**
+   * @brief Construct a new aggregation object
+   *
+   * @param a aggregation::Kind enum value
+   */
   aggregation(aggregation::Kind a) : kind{a} {}
   Kind kind;  ///< The aggregation to perform
   virtual ~aggregation() = default;
 
+  /**
+   * @brief Compares two aggregation objects for equality
+   *
+   * @param other The other aggregation to compare with
+   * @return True if the two aggregations are equal
+   */
   [[nodiscard]] virtual bool is_equal(aggregation const& other) const { return kind == other.kind; }
+
+  /**
+   * @brief Computes the hash value of the aggregation
+   *
+   * @return The hash value of the aggregation
+   */
   [[nodiscard]] virtual size_t do_hash() const { return std::hash<int>{}(kind); }
+
+  /**
+   * @pure @brief Clones the aggregation object
+   *
+   * @return A copy of the aggregation object
+   */
   [[nodiscard]] virtual std::unique_ptr<aggregation> clone() const = 0;
 
   // override functions for compound aggregations
+  /**
+   * @pure @brief Get the simple aggregations that this aggregation requires to compute.
+   *
+   * @param col_type The type of the column to aggregate
+   * @param collector The collector visitor pattern to use to collect the simple aggregations
+   * @return Vector of pre-requisite simple aggregations
+   */
   virtual std::vector<std::unique_ptr<aggregation>> get_simple_aggregations(
     data_type col_type, cudf::detail::simple_aggregations_collector& collector) const = 0;
-  virtual void finalize(cudf::detail::aggregation_finalizer& finalizer) const         = 0;
+
+  /**
+   * @pure @brief Compute the aggregation after pre-requisite simple aggregations have been
+   * computed.
+   *
+   * @param finalizer The finalizer visitor pattern to use to compute the aggregation
+   */
+  virtual void finalize(cudf::detail::aggregation_finalizer& finalizer) const = 0;
 };
 
 /**
@@ -147,7 +185,8 @@ class rolling_aggregation : public virtual aggregation {
 
  protected:
   rolling_aggregation() {}
-  rolling_aggregation(aggregation::Kind a) : aggregation{a} {}
+  /// constructor inherited from cudf::aggregation
+  using aggregation::aggregation;
 };
 
 /**
@@ -205,46 +244,57 @@ class segmented_reduce_aggregation : public virtual aggregation {
   segmented_reduce_aggregation() {}
 };
 
+/// Type of code in the user defined function string.
 enum class udf_type : bool { CUDA, PTX };
+/// Type of correlation method.
 enum class correlation_type : int32_t { PEARSON, KENDALL, SPEARMAN };
 
 /// Factory to create a SUM aggregation
+/// @return A SUM aggregation object
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_sum_aggregation();
 
 /// Factory to create a PRODUCT aggregation
+/// @return A PRODUCT aggregation object
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_product_aggregation();
 
 /// Factory to create a MIN aggregation
+/// @return A MIN aggregation object
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_min_aggregation();
 
 /// Factory to create a MAX aggregation
+/// @return A MAX aggregation object
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_max_aggregation();
 
 /**
  * @brief Factory to create a COUNT aggregation
  *
- * @param null_handling Indicates if null values will be counted.
+ * @param null_handling Indicates if null values will be counted
+ * @return A COUNT aggregation object
  */
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_count_aggregation(null_policy null_handling = null_policy::EXCLUDE);
 
 /// Factory to create an ANY aggregation
+/// @return A ANY aggregation object
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_any_aggregation();
 
 /// Factory to create a ALL aggregation
+/// @return A ALL aggregation object
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_all_aggregation();
 
 /// Factory to create a SUM_OF_SQUARES aggregation
+/// @return A SUM_OF_SQUARES aggregation object
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_sum_of_squares_aggregation();
 
 /// Factory to create a MEAN aggregation
+/// @return A MEAN aggregation object
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_mean_aggregation();
 
@@ -258,6 +308,7 @@ std::unique_ptr<Base> make_mean_aggregation();
  * deviation across multiple discrete sets. See
  * `https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Parallel_algorithm` for more
  * detail.
+ * @return A M2 aggregation object
  */
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_m2_aggregation();
@@ -269,6 +320,7 @@ std::unique_ptr<Base> make_m2_aggregation();
  *             `variance` is `N - ddof`, where `N` is the population size.
  *
  * @throw cudf::logic_error if input type is chrono or compound types.
+ * @return A VARIANCE aggregation object
  */
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_variance_aggregation(size_type ddof = 1);
@@ -280,11 +332,13 @@ std::unique_ptr<Base> make_variance_aggregation(size_type ddof = 1);
  *             `std` is `N - ddof`, where `N` is the population size.
  *
  * @throw cudf::logic_error if input type is chrono or compound types.
+ * @return A STD aggregation object
  */
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_std_aggregation(size_type ddof = 1);
 
 /// Factory to create a MEDIAN aggregation
+/// @return A MEDIAN aggregation object
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_median_aggregation();
 
@@ -293,54 +347,60 @@ std::unique_ptr<Base> make_median_aggregation();
  *
  * @param quantiles The desired quantiles
  * @param interp The desired interpolation
+ * @return A QUANTILE aggregation object
  */
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_quantile_aggregation(std::vector<double> const& quantiles,
                                                 interpolation interp = interpolation::LINEAR);
 
 /**
- * @brief Factory to create an `argmax` aggregation
+ * @brief Factory to create an ARGMAX aggregation
  *
- * `argmax` returns the index of the maximum element.
+ * ARGMAX returns the index of the maximum element.
+ * @return A ARGMAX aggregation object
  */
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_argmax_aggregation();
 
 /**
- * @brief Factory to create an `argmin` aggregation
+ * @brief Factory to create an ARGMIN aggregation
  *
  * `argmin` returns the index of the minimum element.
+ * @return A ARGMIN aggregation object
  */
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_argmin_aggregation();
 
 /**
- * @brief Factory to create a `nunique` aggregation
+ * @brief Factory to create a NUNIQUE aggregation
  *
- * `nunique` returns the number of unique elements.
- * @param null_handling Indicates if null values will be counted.
+ * NUNIQUE returns the number of unique elements.
+ * @param null_handling Indicates if null values will be counted
+ * @return A NUNIQUE aggregation object
  */
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_nunique_aggregation(null_policy null_handling = null_policy::EXCLUDE);
 
 /**
- * @brief Factory to create a `nth_element` aggregation
+ * @brief Factory to create a NTH_ELEMENT aggregation
  *
- * `nth_element` returns the n'th element of the group/series.
+ * NTH_ELEMENT returns the n'th element of the group/series.
  *
  * If @p n is not within the range `[-group_size, group_size)`, the result of
  * the respective group will be null. Negative indices `[-group_size, -1]`
  * corresponds to `[0, group_size-1]` indices respectively where `group_size` is
  * the size of each group.
  *
- * @param n index of nth element in each group.
- * @param null_handling Indicates to include/exclude nulls during indexing.
+ * @param n index of nth element in each group
+ * @param null_handling Indicates to include/exclude nulls during indexing
+ * @return A NTH_ELEMENT aggregation object
  */
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_nth_element_aggregation(
   size_type n, null_policy null_handling = null_policy::INCLUDE);
 
 /// Factory to create a ROW_NUMBER aggregation
+/// @return A ROW_NUMBER aggregation object
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_row_number_aggregation();
 
@@ -408,12 +468,13 @@ std::unique_ptr<Base> make_row_number_aggregation();
  *
  * @endcode
  *
- * @param method The ranking method used for tie breaking (same values).
+ * @param method The ranking method used for tie breaking (same values)
  * @param column_order The desired sort order for ranking
- * @param null_handling  flag to include nulls during ranking. If nulls are not included,
+ * @param null_handling  flag to include nulls during ranking If nulls are not included,
  * the corresponding rank will be null.
  * @param null_precedence The desired order of null compared to other elements for column
  * @param percentage enum to denote the type of conversion of ranks to percentage in range (0,1]
+ * @return A RANK aggregation object
  */
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_rank_aggregation(rank_method method,
@@ -430,7 +491,8 @@ std::unique_ptr<Base> make_rank_aggregation(rank_method method,
  * If `null_handling` is set to `EXCLUDE`, null elements are dropped from each
  * of the list rows.
  *
- * @param null_handling Indicates whether to include/exclude nulls in list elements.
+ * @param null_handling Indicates whether to include/exclude nulls in list elements
+ * @return A COLLECT_LIST aggregation object
  */
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_collect_list_aggregation(
@@ -450,17 +512,28 @@ std::unique_ptr<Base> make_collect_list_aggregation(
  *        equal.
  * @param nans_equal Flag to specify whether NaN values in floating point column should be
  *        considered equal.
+ * @return A COLLECT_SET aggregation object
  */
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_collect_set_aggregation(null_policy null_handling = null_policy::INCLUDE,
                                                    null_equality nulls_equal = null_equality::EQUAL,
                                                    nan_equality nans_equal = nan_equality::UNEQUAL);
 
-/// Factory to create a LAG aggregation
+/**
+ * @brief Factory to create a LAG aggregation
+ *
+ * @param offset The number of rows to lag the input
+ * @return A LAG aggregation object
+ */
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_lag_aggregation(size_type offset);
 
-/// Factory to create a LEAD aggregation
+/**
+ * @brief Factory to create a LEAD aggregation
+ *
+ * @param offset The number of rows to lead the input
+ * @return A LEAD aggregation object
+ */
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_lead_aggregation(size_type offset);
 
@@ -471,7 +544,7 @@ std::unique_ptr<Base> make_lead_aggregation(size_type offset);
  * @param[in] user_defined_aggregator A string containing the aggregator code
  * @param[in] output_type expected output type
  *
- * @return aggregation unique pointer housing user_defined_aggregator string.
+ * @return An aggregation containing a user-defined aggregator string
  */
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_udf_aggregation(udf_type type,
@@ -486,6 +559,8 @@ std::unique_ptr<Base> make_udf_aggregation(udf_type type,
  * groupby `COLLECT_LIST` aggregations into a final `COLLECT_LIST` result. As such, it requires the
  * input lists column to be non-nullable (the child column containing list entries is not subjected
  * to this requirement).
+ *
+ * @return A MERGE_LISTS aggregation object
  */
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_merge_lists_aggregation();
@@ -510,6 +585,7 @@ std::unique_ptr<Base> make_merge_lists_aggregation();
  *        during dropping duplicate list entries.
  * @param nans_equal Flag to specify whether NaN values in floating point column should be
  *        considered equal during dropping duplicate list entries.
+ * @return A MERGE_SETS aggregation object
  */
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_merge_sets_aggregation(null_equality nulls_equal = null_equality::EQUAL,
@@ -526,6 +602,8 @@ std::unique_ptr<Base> make_merge_sets_aggregation(null_equality nulls_equal = nu
  *
  * The input `M2` aggregation values are expected to be all non-negative numbers, since they
  * were output from `M2` aggregation.
+ *
+ * @return A MERGE_M2 aggregation object
  */
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_merge_m2_aggregation();
@@ -535,9 +613,10 @@ std::unique_ptr<Base> make_merge_m2_aggregation();
  *
  * Compute covariance between two columns.
  * The input columns are child columns of a non-nullable struct columns.
- * @param min_periods Minimum number of non-null observations required to produce a result.
+ * @param min_periods Minimum number of non-null observations required to produce a result
  * @param ddof Delta Degrees of Freedom. The divisor used in calculations is N - ddof, where N is
  *        the number of non-null observations.
+ * @return A COVARIANCE aggregation object
  */
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_covariance_aggregation(size_type min_periods = 1, size_type ddof = 1);
@@ -549,7 +628,8 @@ std::unique_ptr<Base> make_covariance_aggregation(size_type min_periods = 1, siz
  * The input columns are child columns of a non-nullable struct columns.
  *
  * @param type correlation_type
- * @param min_periods Minimum number of non-null observations required to produce a result.
+ * @param min_periods Minimum number of non-null observations required to produce a result
+ * @return A CORRELATION aggregation object
  */
 template <typename Base = aggregation>
 std::unique_ptr<Base> make_correlation_aggregation(correlation_type type,
@@ -587,7 +667,7 @@ std::unique_ptr<Base> make_correlation_aggregation(correlation_type type,
  * the computed tdigests: A value of 1000 will result in a tdigest containing no
  * more than 1000 centroids (32 bytes each). Higher result in more accurate tdigest information.
  *
- * @returns A TDIGEST aggregation object.
+ * @return A TDIGEST aggregation object
  */
 template <typename Base>
 std::unique_ptr<Base> make_tdigest_aggregation(int max_centroids = 1000);
@@ -625,7 +705,7 @@ std::unique_ptr<Base> make_tdigest_aggregation(int max_centroids = 1000);
  * the computed tdigests: A value of 1000 will result in a tdigest containing no
  * more than 1000 centroids (32 bytes each). Higher result in more accurate tdigest information.
  *
- * @returns A MERGE_TDIGEST aggregation object.
+ * @return A MERGE_TDIGEST aggregation object
  */
 template <typename Base>
 std::unique_ptr<Base> make_merge_tdigest_aggregation(int max_centroids = 1000);

cpp/include/cudf/concatenate.hpp

@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2020-2021, NVIDIA CORPORATION.
+ * Copyright (c) 2020-2022, NVIDIA CORPORATION.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -53,8 +53,8 @@ rmm::device_buffer concatenate_masks(
  *
  * @param columns_to_concat host_span of column views to be concatenated into a single column
  * @param mr Device memory resource used to allocate the returned column's device memory.
- * @return Unique pointer to a single table having all the rows from the
- * elements of `columns_to_concat` respectively in the same order.
+ * @return A single column having all the rows from the elements of `columns_to_concat` respectively
+ * in the same order.
  */
 std::unique_ptr<column> concatenate(
   host_span<column_view const> columns_to_concat,
@@ -83,8 +83,8 @@ std::unique_ptr<column> concatenate(
  *
  * @param tables_to_concat host_span of table views to be concatenated into a single table
  * @param mr Device memory resource used to allocate the returned table's device memory.
- * @return Unique pointer to a single table having all the rows from the
- * elements of `tables_to_concat` respectively in the same order.
+ * @return A single table having all the rows from the elements of `tables_to_concat` respectively
+ * in the same order.
  */
 std::unique_ptr<table> concatenate(
   host_span<table_view const> tables_to_concat,

cpp/include/cudf/reduction.hpp

@@ -138,7 +138,7 @@ std::unique_ptr<column> segmented_reduce(
  * null_policy::EXCLUDE. Include nulls if null_policy::INCLUDE.
  * Any operation with a null results in a null.
  * @param[in] mr Device memory resource used to allocate the returned scalar's device memory
- * @returns unique pointer to new output column
+ * @returns Scanned output column
  */
 std::unique_ptr<column> scan(
   const column_view& input,