// Licensed to the Apache Software Foundation (ASF) under one

// or more contributor license agreements.  See the NOTICE file

// distributed with this work for additional information

// regarding copyright ownership.  The ASF licenses this file

// to you 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

//

//   http://www.apache.org/licenses/LICENSE-2.0

//

// Unless required by applicable law or agreed to in writing,

// software distributed under the License is distributed on an

// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY

// KIND, either express or implied.  See the License for the

// specific language governing permissions and limitations

// under the License.

#include <stddef.h>

#include <stdint.h>

#include <algorithm>

#include <boost/iterator/iterator_facade.hpp>

#include <memory>

#include <utility>

#include "common/status.h"

#include "core/assert_cast.h"

#include "core/block/block.h"

#include "core/block/column_numbers.h"

#include "core/block/column_with_type_and_name.h"

#include "core/column/column.h"

#include "core/column/column_vector.h"

#include "core/data_type/data_type.h"

#include "core/data_type/data_type_nullable.h"

#include "core/data_type/data_type_number.h"

#include "core/data_type/primitive_type.h"

#include "core/types.h"

#include "exprs/aggregate/aggregate_function.h"

#include "exprs/function/function.h"

#include "exprs/function/simple_function_factory.h"

namespace doris {

class FunctionContext;

} // namespace doris

namespace doris {

class FunctionWidthBucket : public IFunction {

public:

    static constexpr auto name = "width_bucket";

    static FunctionPtr create() { return std::make_shared<FunctionWidthBucket>(); }

    /// Get function name.

    String get_name() const override { return name; }

    bool is_variadic() const override { return false; }

    size_t get_number_of_arguments() const override { return 4; }

    DataTypePtr get_return_type_impl(const DataTypes& arguments) const override {

        return std::make_shared<DataTypeInt64>();

    }

    Status execute_impl(FunctionContext* context, Block& block, const ColumnNumbers& arguments,

                        uint32_t result, size_t input_rows_count) const override {

        ColumnPtr expr_ptr =

                block.get_by_position(arguments[0]).column->convert_to_full_column_if_const();

        ColumnPtr min_value_ptr =

                block.get_by_position(arguments[1]).column->convert_to_full_column_if_const();

        ColumnPtr max_value_ptr =

                block.get_by_position(arguments[2]).column->convert_to_full_column_if_const();

        ColumnPtr num_buckets_ptr = block.get_by_position(arguments[3]).column;

        int64_t num_buckets = num_buckets_ptr->get_int(0);

        if (num_buckets <= 0) {

            return Status::InternalError(

                    "The desired number({}) of buckets must be a positive integer value.",

                    num_buckets);

        }

        auto nested_column_ptr = ColumnInt64::create(input_rows_count, 0);

        DataTypePtr expr_type = block.get_by_position(arguments[0]).type;

        if (!_execute_by_type(*expr_ptr, *min_value_ptr, *max_value_ptr, num_buckets,

                              *nested_column_ptr, expr_type)) {

            return Status::InvalidArgument("Unsupported type for width_bucket: {}",

                                           expr_type->get_name());

        }

        block.replace_by_position(result, std::move(nested_column_ptr));

        return Status::OK();

    }

private:

    template <typename ColumnType>

    void _execute(const IColumn& expr_column, const IColumn& min_value_column,

                  const IColumn& max_value_column, const int64_t num_buckets,

                  IColumn& nested_column) const {

        const auto& expr_column_concrete = assert_cast<const ColumnType&>(expr_column);

        const auto& min_value_column_concrete = assert_cast<const ColumnType&>(min_value_column);

        const auto& max_value_column_concrete = assert_cast<const ColumnType&>(max_value_column);

        auto& nested_column_concrete = assert_cast<ColumnInt64&>(nested_column);

        size_t input_rows_count = expr_column.size();

        for (size_t i = 0; i < input_rows_count; ++i) {

            auto min_value = min_value_column_concrete.get_data()[i];

            auto max_value = max_value_column_concrete.get_data()[i];

            auto average_value = (max_value - min_value) / (1.0 * num_buckets);

            if (expr_column_concrete.get_data()[i] < min_value) {

                continue;

            } else if (expr_column_concrete.get_data()[i] >= max_value) {

                nested_column_concrete.get_data()[i] = num_buckets + 1;

            } else {

                if ((max_value - min_value) / num_buckets == 0) {

                    continue;

                }

                nested_column_concrete.get_data()[i] =

                        (int64_t)(1 +

                                  (expr_column_concrete.get_data()[i] - min_value) / average_value);

            }

        }

    }

Unexecuted instantiation: _ZNK5doris19FunctionWidthBucket8_executeINS_12ColumnVectorILNS_13PrimitiveTypeE3EEEEEvRKNS_7IColumnES7_S7_lRS5_

Unexecuted instantiation: _ZNK5doris19FunctionWidthBucket8_executeINS_12ColumnVectorILNS_13PrimitiveTypeE4EEEEEvRKNS_7IColumnES7_S7_lRS5_

Unexecuted instantiation: _ZNK5doris19FunctionWidthBucket8_executeINS_12ColumnVectorILNS_13PrimitiveTypeE5EEEEEvRKNS_7IColumnES7_S7_lRS5_

Unexecuted instantiation: _ZNK5doris19FunctionWidthBucket8_executeINS_12ColumnVectorILNS_13PrimitiveTypeE6EEEEEvRKNS_7IColumnES7_S7_lRS5_

Unexecuted instantiation: _ZNK5doris19FunctionWidthBucket8_executeINS_12ColumnVectorILNS_13PrimitiveTypeE8EEEEEvRKNS_7IColumnES7_S7_lRS5_

Unexecuted instantiation: _ZNK5doris19FunctionWidthBucket8_executeINS_12ColumnVectorILNS_13PrimitiveTypeE9EEEEEvRKNS_7IColumnES7_S7_lRS5_

    bool _execute_by_type(const IColumn& expr_column, const IColumn& min_value_column,

                          const IColumn& max_value_column, const int64_t num_buckets,

                          IColumn& nested_column_column, DataTypePtr& expr_type) const {

        switch (expr_type->get_primitive_type()) {

        case PrimitiveType::TYPE_TINYINT:

            _execute<ColumnInt8>(expr_column, min_value_column, max_value_column, num_buckets,

                                 nested_column_column);

            break;

        case PrimitiveType::TYPE_SMALLINT:

            _execute<ColumnInt16>(expr_column, min_value_column, max_value_column, num_buckets,

                                  nested_column_column);

            break;

        case PrimitiveType::TYPE_INT:

            _execute<ColumnInt32>(expr_column, min_value_column, max_value_column, num_buckets,

                                  nested_column_column);

            break;

        case PrimitiveType::TYPE_BIGINT:

            _execute<ColumnInt64>(expr_column, min_value_column, max_value_column, num_buckets,

                                  nested_column_column);

            break;

        case PrimitiveType::TYPE_FLOAT:

            _execute<ColumnFloat32>(expr_column, min_value_column, max_value_column, num_buckets,

                                    nested_column_column);

            break;

        case PrimitiveType::TYPE_DOUBLE:

            _execute<ColumnFloat64>(expr_column, min_value_column, max_value_column, num_buckets,

                                    nested_column_column);

            break;

        default:

            return false;

            break;

        }

        return true;

    }

};

void register_function_width_bucket(SimpleFunctionFactory& factory) {

    factory.register_function<FunctionWidthBucket>();

}

} // namespace doris