be/src/vec/functions/function_hash.cpp

// 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.
// This file is copied from
// https://github.com/ClickHouse/ClickHouse/blob/master/src/Functions/FunctionHash.cpp
// and modified by Doris

#include "vec/functions/function_hash.h"

#include "common/status.h"
#include "util/hash_util.hpp"
#include "util/murmur_hash3.h"
#include "vec/columns/column.h"
#include "vec/columns/column_const.h"
#include "vec/columns/column_string.h"
#include "vec/columns/column_vector.h"
#include "vec/common/assert_cast.h"
#include "vec/core/field.h"
#include "vec/data_types/data_type.h"
#include "vec/data_types/data_type_number.h"
#include "vec/functions/function_helpers.h"
#include "vec/functions/function_variadic_arguments.h"
#include "vec/functions/simple_function_factory.h"
#include "vec/utils/template_helpers.hpp"

namespace doris::vectorized {
#include "common/compile_check_begin.h"
constexpr uint64_t emtpy_value = 0xe28dbde7fe22e41c;

template <PrimitiveType ReturnType>
struct MurmurHash3Impl {
    static constexpr auto name = ReturnType == TYPE_INT ? "murmur_hash3_32" : "murmur_hash3_64";

    static Status empty_apply(IColumn& icolumn, size_t input_rows_count) {
        ColumnVector<ReturnType>& vec_to = assert_cast<ColumnVector<ReturnType>&>(icolumn);
        vec_to.get_data().assign(
                input_rows_count,
                static_cast<typename PrimitiveTypeTraits<ReturnType>::ColumnItemType>(emtpy_value));
        return Status::OK();
    }

    static Status first_apply(const IDataType* type, const IColumn* column, size_t input_rows_count,
                              IColumn& icolumn) {
        return execute<true>(type, column, input_rows_count, icolumn);
    }

    static Status combine_apply(const IDataType* type, const IColumn* column,
                                size_t input_rows_count, IColumn& icolumn) {
        return execute<false>(type, column, input_rows_count, icolumn);
    }

    template <bool first>
    static Status execute(const IDataType* type, const IColumn* column, size_t input_rows_count,
                          IColumn& col_to) {
        auto& to_column = assert_cast<ColumnVector<ReturnType>&>(col_to);
        if constexpr (first) {
            if constexpr (ReturnType == TYPE_INT) {
                to_column.insert_many_vals(static_cast<Int32>(HashUtil::MURMUR3_32_SEED),
                                           input_rows_count);
            } else {
                to_column.insert_many_defaults(input_rows_count);
            }
        }
        auto& col_to_data = to_column.get_data();
        if (const auto* col_from = check_and_get_column<ColumnString>(column)) {
            const typename ColumnString::Chars& data = col_from->get_chars();
            const typename ColumnString::Offsets& offsets = col_from->get_offsets();
            size_t size = offsets.size();
            ColumnString::Offset current_offset = 0;
            for (size_t i = 0; i < size; ++i) {
                if constexpr (ReturnType == TYPE_INT) {
                    col_to_data[i] = HashUtil::murmur_hash3_32(
                            reinterpret_cast<const char*>(&data[current_offset]),
                            offsets[i] - current_offset, col_to_data[i]);
                } else {
                    murmur_hash3_x64_64(reinterpret_cast<const char*>(&data[current_offset]),
                                        offsets[i] - current_offset, col_to_data[i],
                                        col_to_data.data() + i);
                }
                current_offset = offsets[i];
            }
        } else if (const ColumnConst* col_from_const =
                           check_and_get_column_const_string_or_fixedstring(column)) {
            auto value = col_from_const->get_value<String>();
            for (size_t i = 0; i < input_rows_count; ++i) {
                if constexpr (ReturnType == TYPE_INT) {
                    col_to_data[i] =
                            HashUtil::murmur_hash3_32(value.data(), value.size(), col_to_data[i]);
                } else {
                    murmur_hash3_x64_64(value.data(), value.size(), col_to_data[i],
                                        col_to_data.data() + i);
                }
            }
        } else {
            DCHECK(false);
            return Status::NotSupported("Illegal column {} of argument of function {}",
                                        column->get_name(), name);
        }
        return Status::OK();
    }
};

using FunctionMurmurHash3_32 =
        FunctionVariadicArgumentsBase<DataTypeInt32, MurmurHash3Impl<TYPE_INT>>;
using FunctionMurmurHash3_64 =
        FunctionVariadicArgumentsBase<DataTypeInt64, MurmurHash3Impl<TYPE_BIGINT>>;

template <PrimitiveType ReturnType>
struct XxHashImpl {
    static constexpr auto name = ReturnType == TYPE_INT ? "xxhash_32" : "xxhash_64";

    static Status empty_apply(IColumn& icolumn, size_t input_rows_count) {
        ColumnVector<ReturnType>& vec_to = assert_cast<ColumnVector<ReturnType>&>(icolumn);
        vec_to.get_data().assign(
                input_rows_count,
                static_cast<typename PrimitiveTypeTraits<ReturnType>::ColumnItemType>(emtpy_value));
        return Status::OK();
    }

    static Status first_apply(const IDataType* type, const IColumn* column, size_t input_rows_count,
                              IColumn& icolumn) {
        return execute<true>(type, column, input_rows_count, icolumn);
    }

    static Status combine_apply(const IDataType* type, const IColumn* column,
                                size_t input_rows_count, IColumn& icolumn) {
        return execute<false>(type, column, input_rows_count, icolumn);
    }

    template <bool first>
    static Status execute(const IDataType* type, const IColumn* column, size_t input_rows_count,
                          IColumn& col_to) {
        auto& to_column = assert_cast<ColumnVector<ReturnType>&>(col_to);
        if constexpr (first) {
            to_column.insert_many_defaults(input_rows_count);
        }
        auto& col_to_data = to_column.get_data();
        if (const auto* col_from = check_and_get_column<ColumnString>(column)) {
            const typename ColumnString::Chars& data = col_from->get_chars();
            const typename ColumnString::Offsets& offsets = col_from->get_offsets();
            size_t size = offsets.size();
            ColumnString::Offset current_offset = 0;
            for (size_t i = 0; i < size; ++i) {
                if constexpr (ReturnType == TYPE_INT) {
                    col_to_data[i] = HashUtil::xxHash32WithSeed(
                            reinterpret_cast<const char*>(&data[current_offset]),
                            offsets[i] - current_offset, col_to_data[i]);
                } else {
                    col_to_data[i] = HashUtil::xxHash64WithSeed(
                            reinterpret_cast<const char*>(&data[current_offset]),
                            offsets[i] - current_offset, col_to_data[i]);
                }
                current_offset = offsets[i];
            }
        } else if (const ColumnConst* col_from_const =
                           check_and_get_column_const_string_or_fixedstring(column)) {
            auto value = col_from_const->get_value<String>();
            for (size_t i = 0; i < input_rows_count; ++i) {
                if constexpr (ReturnType == TYPE_INT) {
                    col_to_data[i] =
                            HashUtil::xxHash32WithSeed(value.data(), value.size(), col_to_data[i]);
                } else {
                    col_to_data[i] =
                            HashUtil::xxHash64WithSeed(value.data(), value.size(), col_to_data[i]);
                }
            }
        } else {
            DCHECK(false);
            return Status::NotSupported("Illegal column {} of argument of function {}",
                                        column->get_name(), name);
        }
        return Status::OK();
    }
};

using FunctionXxHash_32 = FunctionVariadicArgumentsBase<DataTypeInt32, XxHashImpl<TYPE_INT>>;
using FunctionXxHash_64 = FunctionVariadicArgumentsBase<DataTypeInt64, XxHashImpl<TYPE_BIGINT>>;

void register_function_hash(SimpleFunctionFactory& factory) {
    factory.register_function<FunctionMurmurHash3_32>();
    factory.register_function<FunctionMurmurHash3_64>();
    factory.register_function<FunctionXxHash_32>();
    factory.register_function<FunctionXxHash_64>();
}
} // namespace doris::vectorized