// 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.

#pragma once

#include <gen_cpp/Types_types.h>

#include <gen_cpp/olap_common.pb.h>

#include <gen_cpp/olap_file.pb.h>

#include <gen_cpp/segment_v2.pb.h>

#include <parallel_hashmap/phmap.h>

#include <algorithm>

#include <cstdint>

#include <map>

#include <memory>

#include <string>

#include <unordered_map>

#include <unordered_set>

#include <utility>

#include <vector>

#include "common/consts.h"

#include "common/status.h"

#include "olap/inverted_index_parser.h"

#include "olap/metadata_adder.h"

#include "olap/olap_common.h"

#include "olap/rowset/segment_v2/options.h"

#include "runtime/define_primitive_type.h"

#include "runtime/descriptors.h"

#include "runtime/memory/lru_cache_policy.h"

#include "util/debug_points.h"

#include "util/string_parser.hpp"

#include "util/string_util.h"

#include "vec/aggregate_functions/aggregate_function.h"

#include "vec/common/string_ref.h"

#include "vec/common/string_utils/string_utils.h"

#include "vec/core/types.h"

#include "vec/json/path_in_data.h"

namespace doris {

namespace vectorized {

class Block;

class PathInData;

class IDataType;

} // namespace vectorized

#include "common/compile_check_begin.h"

struct OlapTableIndexSchema;

class TColumn;

class TOlapTableIndex;

class TabletColumn;

using TabletColumnPtr = std::shared_ptr<TabletColumn>;

class TabletColumn : public MetadataAdder<TabletColumn> {

public:

    TabletColumn();

    TabletColumn(const ColumnPB& column);

    TabletColumn(const TColumn& column);

    TabletColumn(FieldAggregationMethod agg, FieldType type);

    TabletColumn(FieldAggregationMethod agg, FieldType filed_type, bool is_nullable);

    TabletColumn(FieldAggregationMethod agg, FieldType filed_type, bool is_nullable,

                 int32_t unique_id, size_t length);

#ifdef BE_TEST

    virtual ~TabletColumn() = default;

#endif

    void init_from_pb(const ColumnPB& column);

    void init_from_thrift(const TColumn& column);

    void to_schema_pb(ColumnPB* column) const;

    int32_t unique_id() const { return _unique_id; }

    void set_unique_id(int32_t id) { _unique_id = id; }

    const std::string& name() const { return _col_name; }

    const std::string& name_lower_case() const { return _col_name_lower_case; }

    void set_name(std::string col_name) {

        _col_name = col_name;

        _col_name_lower_case = to_lower(_col_name);

    }

    MOCK_FUNCTION FieldType type() const { return _type; }

    void set_type(FieldType type) { _type = type; }

    bool is_key() const { return _is_key; }

    bool is_nullable() const { return _is_nullable; }

    bool is_auto_increment() const { return _is_auto_increment; }

    bool is_seqeunce_col() const { return _col_name == SEQUENCE_COL; }

    bool is_on_update_current_timestamp() const { return _is_on_update_current_timestamp; }

    bool is_variant_type() const { return _type == FieldType::OLAP_FIELD_TYPE_VARIANT; }

    bool is_bf_column() const { return _is_bf_column; }

    bool is_array_type() const { return _type == FieldType::OLAP_FIELD_TYPE_ARRAY; }

    bool is_agg_state_type() const { return _type == FieldType::OLAP_FIELD_TYPE_AGG_STATE; }

    bool is_jsonb_type() const { return _type == FieldType::OLAP_FIELD_TYPE_JSONB; }

    bool is_length_variable_type() const {

        return _type == FieldType::OLAP_FIELD_TYPE_CHAR ||

               _type == FieldType::OLAP_FIELD_TYPE_VARCHAR ||

               _type == FieldType::OLAP_FIELD_TYPE_STRING ||

               _type == FieldType::OLAP_FIELD_TYPE_HLL ||

               _type == FieldType::OLAP_FIELD_TYPE_BITMAP ||

               _type == FieldType::OLAP_FIELD_TYPE_QUANTILE_STATE ||

               _type == FieldType::OLAP_FIELD_TYPE_AGG_STATE;

    }

    // Such columns are not exist in frontend schema info, so we need to

    // add them into tablet_schema for later column indexing.

    static TabletColumn create_materialized_variant_column(const std::string& root,

                                                           const std::vector<std::string>& paths,

                                                           int32_t parent_unique_id,

                                                           int32_t max_subcolumns_count);

    bool has_default_value() const { return _has_default_value; }

    std::string default_value() const { return _default_value; }

    int32_t length() const { return _length; }

    void set_length(int32_t length) { _length = length; }

    void set_default_value(const std::string& default_value) {

        _default_value = default_value;

        _has_default_value = true;

    }

    int32_t index_length() const { return _index_length; }

    void set_index_length(int32_t index_length) { _index_length = index_length; }

    void set_is_key(bool is_key) { _is_key = is_key; }

    void set_is_nullable(bool is_nullable) { _is_nullable = is_nullable; }

    void set_is_auto_increment(bool is_auto_increment) { _is_auto_increment = is_auto_increment; }

    void set_is_on_update_current_timestamp(bool is_on_update_current_timestamp) {

        _is_on_update_current_timestamp = is_on_update_current_timestamp;

    }

    void set_path_info(const vectorized::PathInData& path);

    FieldAggregationMethod aggregation() const { return _aggregation; }

    vectorized::AggregateFunctionPtr get_aggregate_function_union(

            vectorized::DataTypePtr type, int current_be_exec_version) const;

    vectorized::AggregateFunctionPtr get_aggregate_function(std::string suffix,

                                                            int current_be_exec_version) const;

    int precision() const { return _precision; }

    int frac() const { return _frac; }

    inline bool visible() const { return _visible; }

    bool has_char_type() const;

    void set_aggregation_method(FieldAggregationMethod agg) {

        _aggregation = agg;

        _aggregation_name = get_string_by_aggregation_type(agg);

    }

    /**

     * Add a sub column.

     */

    void add_sub_column(TabletColumn& sub_column);

    uint32_t get_subtype_count() const { return _sub_column_count; }

    MOCK_FUNCTION const TabletColumn& get_sub_column(uint64_t i) const { return *_sub_columns[i]; }

    const std::vector<TabletColumnPtr>& get_sub_columns() const { return _sub_columns; }

    friend bool operator==(const TabletColumn& a, const TabletColumn& b);

    friend bool operator!=(const TabletColumn& a, const TabletColumn& b);

    static std::string get_string_by_field_type(FieldType type);

    static std::string get_string_by_aggregation_type(FieldAggregationMethod aggregation_type);

    static FieldType get_field_type_by_string(const std::string& str);

    static FieldType get_field_type_by_type(PrimitiveType type);

    static PrimitiveType get_primitive_type_by_field_type(FieldType type);

    static FieldAggregationMethod get_aggregation_type_by_string(const std::string& str);

    static uint32_t get_field_length_by_type(TPrimitiveType::type type, uint32_t string_length);

    bool is_row_store_column() const;

    std::string get_aggregation_name() const { return _aggregation_name; }

    bool get_result_is_nullable() const { return _result_is_nullable; }

    int get_be_exec_version() const { return _be_exec_version; }

    bool has_path_info() const { return _column_path != nullptr && !_column_path->empty(); }

    const vectorized::PathInDataPtr& path_info_ptr() const { return _column_path; }

    // If it is an extracted column from variant column

    bool is_extracted_column() const {

        return _column_path != nullptr && !_column_path->empty() && _parent_col_unique_id > 0;

    };

    std::string suffix_path() const {

        return is_extracted_column() ? _column_path->get_path() : "";

    }

    bool is_nested_subcolumn() const {

        return _column_path != nullptr && _column_path->has_nested_part();

    }

    int32_t parent_unique_id() const { return _parent_col_unique_id; }

    void set_parent_unique_id(int32_t col_unique_id) { _parent_col_unique_id = col_unique_id; }

    void set_is_bf_column(bool is_bf_column) { _is_bf_column = is_bf_column; }

    std::shared_ptr<const vectorized::IDataType> get_vec_type() const;

    Status check_valid() const {

        if (type() != FieldType::OLAP_FIELD_TYPE_ARRAY &&

            type() != FieldType::OLAP_FIELD_TYPE_STRUCT &&

            type() != FieldType::OLAP_FIELD_TYPE_MAP) {

            return Status::OK();

        }

        if (is_bf_column()) {

            return Status::NotSupported("Do not support bloom filter index, type={}",

                                        get_string_by_field_type(type()));

        }

        return Status::OK();

    }

    void set_precision(int precision) {

        _precision = precision;

        _is_decimal = true;

    }

    void set_frac(int frac) { _frac = frac; }

    void set_variant_max_subcolumns_count(int32_t variant_max_subcolumns_count) {

        _variant_max_subcolumns_count = variant_max_subcolumns_count;

    }

    void set_variant_enable_typed_paths_to_sparse(bool enable) {

        _variant_enable_typed_paths_to_sparse = enable;

    }

    void set_variant_max_sparse_column_statistics_size(

            int32_t variant_max_sparse_column_statistics_size) {

        _variant_max_sparse_column_statistics_size = variant_max_sparse_column_statistics_size;

    }

    void set_variant_sparse_hash_shard_count(int32_t variant_sparse_hash_shard_count) {

        _variant_sparse_hash_shard_count = variant_sparse_hash_shard_count;

    }

    int32_t variant_max_subcolumns_count() const { return _variant_max_subcolumns_count; }

    PatternTypePB pattern_type() const { return _pattern_type; }

    bool variant_enable_typed_paths_to_sparse() const {

        return _variant_enable_typed_paths_to_sparse;

    }

    int32_t variant_max_sparse_column_statistics_size() const {

        return _variant_max_sparse_column_statistics_size;

    }

    int32_t variant_sparse_hash_shard_count() const { return _variant_sparse_hash_shard_count; }

    bool is_decimal() const { return _is_decimal; }

private:

    int32_t _unique_id = -1;

    std::string _col_name;

    std::string _col_name_lower_case;

    // the field _type will change from TPrimitiveType

    // to string by 'EnumToString(TPrimitiveType, tcolumn.column_type.type, data_type);' (reference: TabletMeta::init_column_from_tcolumn)

    // to FieldType by 'TabletColumn::get_field_type_by_string' (reference: TabletColumn::init_from_pb).

    // And the _type in columnPB is string and it changed from FieldType by 'get_string_by_field_type' (reference: TabletColumn::to_schema_pb).

    FieldType _type;

    bool _is_key = false;

    FieldAggregationMethod _aggregation;

    std::string _aggregation_name;

    bool _is_nullable = false;

    bool _is_auto_increment = false;

    bool _is_on_update_current_timestamp {false};

    bool _has_default_value = false;

    std::string _default_value;

    bool _is_decimal = false;

    int32_t _precision = -1;

    int32_t _frac = -1;

    int32_t _length = -1;

    int32_t _index_length = -1;

    bool _is_bf_column = false;

    bool _visible = true;

    std::vector<TabletColumnPtr> _sub_columns;

    uint32_t _sub_column_count = 0;

    bool _result_is_nullable = false;

    int _be_exec_version = -1;

    // The extracted sub-columns from "variant" contain the following information:

    int32_t _parent_col_unique_id = -1;     // "variant" -> col_unique_id

    vectorized::PathInDataPtr _column_path; // the path of the sub-columns themselves

    int32_t _variant_max_subcolumns_count = 0;

    PatternTypePB _pattern_type = PatternTypePB::MATCH_NAME_GLOB;

    bool _variant_enable_typed_paths_to_sparse = false;

    // set variant_max_sparse_column_statistics_size

    int32_t _variant_max_sparse_column_statistics_size =

            BeConsts::DEFAULT_VARIANT_MAX_SPARSE_COLUMN_STATS_SIZE;

    // default to 0, no shard

    int32_t _variant_sparse_hash_shard_count = 0;

};

bool operator==(const TabletColumn& a, const TabletColumn& b);

bool operator!=(const TabletColumn& a, const TabletColumn& b);

class TabletIndex : public MetadataAdder<TabletIndex> {

public:

    TabletIndex() = default;

    void init_from_thrift(const TOlapTableIndex& index, const TabletSchema& tablet_schema);

    void init_from_thrift(const TOlapTableIndex& index, const std::vector<int32_t>& column_uids);

    void init_from_pb(const TabletIndexPB& index);

    void to_schema_pb(TabletIndexPB* index) const;

    int64_t index_id() const { return _index_id; }

    const std::string& index_name() const { return _index_name; }

    MOCK_FUNCTION IndexType index_type() const { return _index_type; }

    const std::vector<int32_t>& col_unique_ids() const { return _col_unique_ids; }

    MOCK_FUNCTION const std::map<std::string, std::string>& properties() const {

        return _properties;

    }

    int32_t get_gram_size() const {

        if (_properties.contains("gram_size")) {

            return std::stoi(_properties.at("gram_size"));

        }

        return 0;

    }

    int32_t get_gram_bf_size() const {

        if (_properties.contains("bf_size")) {

            return std::stoi(_properties.at("bf_size"));

        }

        return 0;

    }

    const std::string& get_index_suffix() const { return _escaped_index_suffix_path; }

    void set_escaped_escaped_index_suffix_path(const std::string& name);

    bool is_inverted_index() const { return _index_type == IndexType::INVERTED; }

    bool is_ann_index() const { return _index_type == IndexType::ANN; }

    void remove_parser_and_analyzer() {

        _properties.erase(INVERTED_INDEX_PARSER_KEY);

        _properties.erase(INVERTED_INDEX_PARSER_KEY_ALIAS);

        _properties.erase(INVERTED_INDEX_ANALYZER_NAME_KEY);

        _properties.erase(INVERTED_INDEX_NORMALIZER_NAME_KEY);

    }

    std::string field_pattern() const {

        if (_properties.contains("field_pattern")) {

            return _properties.at("field_pattern");

        }

        return "";

    }

    bool is_same_except_id(const TabletIndex* other) const {

        return _escaped_index_suffix_path == other->_escaped_index_suffix_path &&

               _index_name == other->_index_name && _index_type == other->_index_type &&

               _col_unique_ids == other->_col_unique_ids && _properties == other->_properties;

    }

private:

    int64_t _index_id = -1;

    // Identify the different index with the same _index_id

    std::string _escaped_index_suffix_path;

    std::string _index_name;

    IndexType _index_type;

    std::vector<int32_t> _col_unique_ids;

    std::map<std::string, std::string> _properties;

};

using TabletIndexPtr = std::shared_ptr<TabletIndex>;

using TabletIndexes = std::vector<std::shared_ptr<TabletIndex>>;

using PathSet = phmap::flat_hash_set<std::string>;

class TabletSchema : public MetadataAdder<TabletSchema> {

public:

    enum class ColumnType { NORMAL = 0, DROPPED = 1, VARIANT = 2 };

    // TODO(yingchun): better to make constructor as private to avoid

    // manually init members incorrectly, and define a new function like

    // void create_from_pb(const TabletSchemaPB& schema, TabletSchema* tablet_schema).

    TabletSchema();

    ~TabletSchema() override;

    // Init from pb

    // ignore_extracted_columns: ignore the extracted columns from variant column

    // reuse_cached_column: reuse the cached column in the schema if they are the same, to reduce memory usage

    void init_from_pb(const TabletSchemaPB& schema, bool ignore_extracted_columns = false,

                      bool reuse_cached_column = false);

    // Notice: Use deterministic way to serialize protobuf,

    // since serialize Map in protobuf may could lead to un-deterministic by default

    template <class PbType>

    static std::string deterministic_string_serialize(const PbType& pb) {

        std::string output;

        google::protobuf::io::StringOutputStream string_output_stream(&output);

        google::protobuf::io::CodedOutputStream output_stream(&string_output_stream);

        output_stream.SetSerializationDeterministic(true);

        pb.SerializeToCodedStream(&output_stream);

        return output;

    }

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    static std::string deterministic_string_serialize(const PbType& pb) {

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        std::string output;

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        google::protobuf::io::CodedOutputStream output_stream(&string_output_stream);

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        output_stream.SetSerializationDeterministic(true);

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        pb.SerializeToCodedStream(&output_stream);

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        return output;

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    }

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    static std::string deterministic_string_serialize(const PbType& pb) {

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        std::string output;

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        google::protobuf::io::StringOutputStream string_output_stream(&output);

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        google::protobuf::io::CodedOutputStream output_stream(&string_output_stream);

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        output_stream.SetSerializationDeterministic(true);

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        pb.SerializeToCodedStream(&output_stream);

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        return output;

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    }

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    static std::string deterministic_string_serialize(const PbType& pb) {

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        google::protobuf::io::CodedOutputStream output_stream(&string_output_stream);

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        output_stream.SetSerializationDeterministic(true);

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        pb.SerializeToCodedStream(&output_stream);

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        return output;

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    }

    void to_schema_pb(TabletSchemaPB* tablet_meta_pb) const;

    void append_column(TabletColumn column, ColumnType col_type = ColumnType::NORMAL);

    void append_index(TabletIndex&& index);

    void remove_index(int64_t index_id);

    void clear_index();

    // Must make sure the row column is always the last column

    void add_row_column();

    void copy_from(const TabletSchema& tablet_schema);

    // lightweight copy, take care of lifecycle of TabletColumn

    void shawdow_copy_without_columns(const TabletSchema& tablet_schema);

    void update_index_info_from(const TabletSchema& tablet_schema);

    std::string to_key() const;

    // get_metadata_size is only the memory of the TabletSchema itself, not include child objects.

    int64_t mem_size() const { return get_metadata_size(); }

    size_t row_size() const;

    int32_t field_index(const std::string& field_name) const;

    int32_t field_index(const vectorized::PathInData& path) const;

    int32_t field_index(int32_t col_unique_id) const;

    const TabletColumn& column(size_t ordinal) const;

    Result<const TabletColumn*> column(const std::string& field_name) const;

    Status have_column(const std::string& field_name) const;

    bool exist_column(const std::string& field_name) const;

    bool has_column_unique_id(int32_t col_unique_id) const;

    const TabletColumn& column_by_uid(int32_t col_unique_id) const;

    TabletColumn& mutable_column_by_uid(int32_t col_unique_id);

    TabletColumn& mutable_column(size_t ordinal);

    void replace_column(size_t pos, TabletColumn new_col);

    const std::vector<TabletColumnPtr>& columns() const;

    size_t num_columns() const { return _num_columns; }

    size_t num_key_columns() const { return _num_key_columns; }

    const std::vector<uint32_t>& cluster_key_uids() const { return _cluster_key_uids; }

    size_t num_null_columns() const { return _num_null_columns; }

    size_t num_short_key_columns() const { return _num_short_key_columns; }

    size_t num_rows_per_row_block() const { return _num_rows_per_row_block; }

    size_t num_variant_columns() const { return _num_variant_columns; };

    size_t num_virtual_columns() const { return _num_virtual_columns; }

    KeysType keys_type() const { return _keys_type; }

    SortType sort_type() const { return _sort_type; }

    size_t sort_col_num() const { return _sort_col_num; }

    CompressKind compress_kind() const { return _compress_kind; }

    size_t next_column_unique_id() const { return _next_column_unique_id; }

    bool has_bf_fpp() const { return _has_bf_fpp; }

    double bloom_filter_fpp() const { return _bf_fpp; }

    bool is_in_memory() const { return _is_in_memory; }

    void set_is_in_memory(bool is_in_memory) { _is_in_memory = is_in_memory; }

    void set_disable_auto_compaction(bool disable_auto_compaction) {

        _disable_auto_compaction = disable_auto_compaction;

    }

    bool disable_auto_compaction() const { return _disable_auto_compaction; }

    void set_enable_variant_flatten_nested(bool flatten_nested) {

        _enable_variant_flatten_nested = flatten_nested;

    }

    bool variant_flatten_nested() const { return _enable_variant_flatten_nested; }

    void set_enable_single_replica_compaction(bool enable_single_replica_compaction) {

        _enable_single_replica_compaction = enable_single_replica_compaction;

    }

    bool enable_single_replica_compaction() const { return _enable_single_replica_compaction; }

    // indicate if full row store column(all the columns encodes as row) exists

    bool has_row_store_for_all_columns() const {

        return _store_row_column && row_columns_uids().empty();

    }

    void set_skip_write_index_on_load(bool skip) { _skip_write_index_on_load = skip; }

    bool skip_write_index_on_load() const { return _skip_write_index_on_load; }

    int32_t delete_sign_idx() const { return _delete_sign_idx; }

    bool has_sequence_col() const { return _sequence_col_idx != -1; }

    int32_t sequence_col_idx() const { return _sequence_col_idx; }

    void set_version_col_idx(int32_t version_col_idx) { _version_col_idx = version_col_idx; }

    int32_t version_col_idx() const { return _version_col_idx; }

    bool has_skip_bitmap_col() const { return _skip_bitmap_col_idx != -1; }

    int32_t skip_bitmap_col_idx() const { return _skip_bitmap_col_idx; }

    segment_v2::CompressionTypePB compression_type() const { return _compression_type; }

    void set_row_store_page_size(long page_size) { _row_store_page_size = page_size; }

    long row_store_page_size() const { return _row_store_page_size; }

    void set_storage_page_size(long storage_page_size) { _storage_page_size = storage_page_size; }

    long storage_page_size() const { return _storage_page_size; }

    void set_storage_dict_page_size(long storage_dict_page_size) {

        _storage_dict_page_size = storage_dict_page_size;

    }

    long storage_dict_page_size() const { return _storage_dict_page_size; }

    bool has_global_row_id() const {

        for (auto [col_name, _] : _field_name_to_index) {

            if (col_name.start_with(StringRef(BeConsts::GLOBAL_ROWID_COL.data(),

                                              BeConsts::GLOBAL_ROWID_COL.size()))) {

                return true;

            }

        }

        return false;

    }

    const std::vector<const TabletIndex*> inverted_indexes() const {

        std::vector<const TabletIndex*> inverted_indexes;

        for (const auto& index : _indexes) {

            if (index->index_type() == IndexType::INVERTED) {

                inverted_indexes.emplace_back(index.get());

            }

        }

        return inverted_indexes;

    }

    bool has_inverted_index() const {

        for (const auto& index : _indexes) {

            DBUG_EXECUTE_IF("tablet_schema::has_inverted_index", {

                if (index->col_unique_ids().empty()) {

                    throw Exception(Status::InternalError("col unique ids cannot be empty"));

                }

            });

            if (index->index_type() == IndexType::INVERTED) {

                //if index_id == -1, ignore it.

                if (!index->col_unique_ids().empty() && index->col_unique_ids()[0] >= 0) {

                    return true;

                }

            }

        }

        return false;

    }

    bool has_ann_index() const {

        for (const auto& index : _indexes) {

            if (index->index_type() == IndexType::ANN) {

                if (!index->col_unique_ids().empty() && index->col_unique_ids()[0] >= 0) {

                    return true;

                }

            }

        }

        return false;

    }

    bool has_inverted_index_with_index_id(int64_t index_id) const;

    std::vector<const TabletIndex*> inverted_indexs(const TabletColumn& col) const;

    std::vector<const TabletIndex*> inverted_indexs(int32_t col_unique_id,

                                                    const std::string& suffix_path = "") const;

    const TabletIndex* ann_index(const TabletColumn& col) const;

    // Regardless of whether this column supports inverted index

    // TabletIndex information will be returned as long as it exists.

    const TabletIndex* ann_index(int32_t col_unique_id, const std::string& suffix_path = "") const;

    std::vector<TabletIndexPtr> inverted_index_by_field_pattern(

            int32_t col_unique_id, const std::string& field_pattern) const;

    bool has_ngram_bf_index(int32_t col_unique_id) const;

    const TabletIndex* get_ngram_bf_index(int32_t col_unique_id) const;

    const TabletIndex* get_index(int32_t col_unique_id, IndexType index_type,

                                 const std::string& suffix_path) const;

    void update_indexes_from_thrift(const std::vector<doris::TOlapTableIndex>& indexes);

    // If schema version is not set, it should be -1

    int32_t schema_version() const { return _schema_version; }

    void clear_columns();

    vectorized::Block create_block(

            const std::vector<uint32_t>& return_columns,

            const std::unordered_set<uint32_t>* tablet_columns_need_convert_null = nullptr) const;

    vectorized::Block create_block(bool ignore_dropped_col = true) const;

    void set_schema_version(int32_t version) { _schema_version = version; }

    void set_auto_increment_column(const std::string& auto_increment_column) {

        _auto_increment_column = auto_increment_column;

    }

    std::string auto_increment_column() const { return _auto_increment_column; }

    void set_table_id(int64_t table_id) { _table_id = table_id; }

    int64_t table_id() const { return _table_id; }

    void set_db_id(int64_t db_id) { _db_id = db_id; }

    int64_t db_id() const { return _db_id; }

    void build_current_tablet_schema(int64_t index_id, int32_t version,

                                     const OlapTableIndexSchema* index,

                                     const TabletSchema& out_tablet_schema);

    // Merge columns that not exit in current schema, these column is dropped in current schema

    // but they are useful in some cases. For example,

    // 1. origin schema is  ColA, ColB

    // 2. insert values     1, 2

    // 3. delete where ColB = 2

    // 4. drop ColB

    // 5. insert values  3

    // 6. add column ColB, although it is name ColB, but it is different with previous ColB, the new ColB we name could call ColB'

    // 7. insert value  4, 5

    // Then the read schema should be ColA, ColB, ColB' because the delete predicate need ColB to remove related data.

    // Because they have same name, so that the dropped column should not be added to the map, only with unique id.

    void merge_dropped_columns(const TabletSchema& src_schema);

    bool is_dropped_column(const TabletColumn& col) const;

    // copy extracted columns from src_schema

    void copy_extracted_columns(const TabletSchema& src_schema);

    // only reserve extracted columns

    void reserve_extracted_columns();

    std::string get_all_field_names() const {

        std::string str = "[";

        for (auto p : _field_name_to_index) {

            if (str.size() > 1) {

                str += ", ";

            }

            str += p.first.to_string() + "(" + std::to_string(_cols[p.second]->unique_id()) + ")";

        }

        str += "]";

        return str;

    }

    // Dump [(name, type, is_nullable), ...]

    std::string dump_structure() const {

        std::string str = "[";

        for (auto p : _cols) {

            if (str.size() > 1) {

                str += ", ";

            }

            str += "(";

            str += p->name();

            str += ", ";

            str += TabletColumn::get_string_by_field_type(p->type());

            str += ", ";

            str += "is_nullable:";

            str += (p->is_nullable() ? "true" : "false");

            str += ")";

        }

        str += "]";

        return str;

    }

    std::string dump_full_schema() const {

        std::string str = "[";

        for (auto p : _cols) {

            if (str.size() > 1) {

                str += ", ";

            }

            ColumnPB col_pb;

            p->to_schema_pb(&col_pb);

            str += "(";

            str += col_pb.ShortDebugString();

            str += ")";

        }

        str += "]";

        return str;

    }

    vectorized::Block create_block_by_cids(const std::vector<uint32_t>& cids) const;

    std::shared_ptr<TabletSchema> copy_without_variant_extracted_columns();

    InvertedIndexStorageFormatPB get_inverted_index_storage_format() const {

        return _inverted_index_storage_format;

    }

    void update_tablet_columns(const TabletSchema& tablet_schema,

                               const std::vector<TColumn>& t_columns);

    const std::vector<int32_t>& row_columns_uids() const { return _row_store_column_unique_ids; }

    int64_t get_metadata_size() const override;

    struct SubColumnInfo {

        TabletColumn column;

        TabletIndexes indexes;

    };

    // all path in path_set_info are relative to the parent column

    struct PathsSetInfo {

        std::unordered_map<std::string, SubColumnInfo> typed_path_set;    // typed columns

        std::unordered_map<std::string, TabletIndexes> subcolumn_indexes; // subcolumns indexes

        PathSet sub_path_set;                                             // extracted columns

        PathSet sparse_path_set;                                          // sparse columns

    };

    void set_path_set_info(std::unordered_map<int32_t, PathsSetInfo>&& path_set_info_map) {

        _path_set_info_map = std::move(path_set_info_map);

    }

    const PathsSetInfo& path_set_info(int32_t unique_id) const {

        return _path_set_info_map.at(unique_id);

    }

    bool need_record_variant_extended_schema() const { return variant_max_subcolumns_count() == 0; }

    int32_t variant_max_subcolumns_count() const {

        for (const auto& col : _cols) {

            if (col->is_variant_type()) {

                return col->variant_max_subcolumns_count();

            }

        }

        return 0;

    }

    const std::unordered_map<uint32_t, std::vector<uint32_t>>& seq_col_idx_to_value_cols_idx()

            const {

        return _seq_col_idx_to_value_cols_idx;

    }

    bool has_seq_map() const { return !_seq_col_idx_to_value_cols_idx.empty(); }

    const std::unordered_map<uint32_t, uint32_t>& value_col_idx_to_seq_col_idx() const {

        return _value_col_idx_to_seq_col_idx;

    }

    void add_pruned_columns_data_type(int32_t col_unique_id, vectorized::DataTypePtr data_type) {

        _pruned_columns_data_type[col_unique_id] = std::move(data_type);

    }

    void clear_pruned_columns_data_type() { _pruned_columns_data_type.clear(); }

    bool has_pruned_columns() const { return !_pruned_columns_data_type.empty(); }

    // Whether new segments use externalized ColumnMetaPB layout (CMO) by default

    bool is_external_segment_column_meta_used() const {

        return _is_external_segment_column_meta_used;

    }

    void set_external_segment_meta_used_default(bool v) {

        _is_external_segment_column_meta_used = v;

    }

    bool integer_type_default_use_plain_encoding() const {

        return _integer_type_default_use_plain_encoding;

    }

    void set_integer_type_default_use_plain_encoding(bool v) {

        _integer_type_default_use_plain_encoding = v;

    }

    BinaryPlainEncodingTypePB binary_plain_encoding_default_impl() const {

        return _binary_plain_encoding_default_impl;

    }

    void set_binary_plain_encoding_default_impl(BinaryPlainEncodingTypePB impl) {

        _binary_plain_encoding_default_impl = impl;

    }

private:

    friend bool operator==(const TabletSchema& a, const TabletSchema& b);

    friend bool operator!=(const TabletSchema& a, const TabletSchema& b);

    TabletSchema(const TabletSchema&) = default;

    KeysType _keys_type = DUP_KEYS;

    SortType _sort_type = SortType::LEXICAL;

    size_t _sort_col_num = 0;

    std::vector<TabletColumnPtr> _cols;

    std::vector<TabletIndexPtr> _indexes;

    std::unordered_map<StringRef, int32_t, StringRefHash> _field_name_to_index;

    std::unordered_map<int32_t, int32_t> _field_uniqueid_to_index;

    std::unordered_map<vectorized::PathInDataRef, int32_t, vectorized::PathInDataRef::Hash>

            _field_path_to_index;

    // index_type/col_unique_id/suffix -> idxs in _indexes

    using IndexKey = std::tuple<IndexType, int32_t, std::string>;

    struct IndexKeyHash {

        size_t operator()(const IndexKey& t) const {

            uint32_t seed = 0;

            seed = doris::HashUtil::hash((const char*)&std::get<0>(t), sizeof(std::get<0>(t)),

                                         seed);

            seed = doris::HashUtil::hash((const char*)&std::get<1>(t), sizeof(std::get<1>(t)),

                                         seed);

            seed = doris::HashUtil::hash((const char*)std::get<2>(t).c_str(),

                                         static_cast<uint32_t>(std::get<2>(t).size()), seed);

            return seed;

        }

    };

    std::unordered_map<IndexKey, std::vector<size_t>, IndexKeyHash> _col_id_suffix_to_index;

    int32_t _num_columns = 0;

    size_t _num_variant_columns = 0;

    size_t _num_virtual_columns = 0;

    size_t _num_key_columns = 0;

    std::vector<uint32_t> _cluster_key_uids;

    size_t _num_null_columns = 0;

    size_t _num_short_key_columns = 0;

    size_t _num_rows_per_row_block = 0;

    CompressKind _compress_kind = COMPRESS_NONE;

    segment_v2::CompressionTypePB _compression_type = segment_v2::CompressionTypePB::LZ4F;

    long _row_store_page_size = segment_v2::ROW_STORE_PAGE_SIZE_DEFAULT_VALUE;

    long _storage_page_size = segment_v2::STORAGE_PAGE_SIZE_DEFAULT_VALUE;

    long _storage_dict_page_size = segment_v2::STORAGE_DICT_PAGE_SIZE_DEFAULT_VALUE;

    size_t _next_column_unique_id = 0;

    std::string _auto_increment_column;

    bool _has_bf_fpp = false;

    double _bf_fpp = 0;

    bool _is_in_memory = false;

    int32_t _delete_sign_idx = -1;

    int32_t _sequence_col_idx = -1;

    int32_t _version_col_idx = -1;

    int32_t _skip_bitmap_col_idx = -1;

    int32_t _schema_version = -1;

    int64_t _table_id = -1;

    int64_t _db_id = -1;

    bool _disable_auto_compaction = false;

    bool _enable_single_replica_compaction = false;

    bool _store_row_column = false;

    bool _skip_write_index_on_load = false;

    InvertedIndexStorageFormatPB _inverted_index_storage_format = InvertedIndexStorageFormatPB::V1;

    // Contains column ids of which columns should be encoded into row store.

    // ATTN: For compability reason empty cids means all columns of tablet schema are encoded to row column

    std::vector<int32_t> _row_store_column_unique_ids;

    bool _enable_variant_flatten_nested = false;

    std::map<size_t, int32_t> _vir_col_idx_to_unique_id;

    std::map<int32_t, vectorized::DataTypePtr> _pruned_columns_data_type;

    // value: extracted path set and sparse path set

    std::unordered_map<int32_t, PathsSetInfo> _path_set_info_map;

    // key: field_pattern

    // value: indexes

    using PatternToIndex = std::unordered_map<std::string, std::vector<TabletIndexPtr>>;

    std::unordered_map<int32_t, PatternToIndex> _index_by_unique_id_with_pattern;

    // Default behavior for new segments: use external ColumnMeta region + CMO table if true

    bool _is_external_segment_column_meta_used = false;

    bool _integer_type_default_use_plain_encoding {false};

    BinaryPlainEncodingTypePB _binary_plain_encoding_default_impl {

            BinaryPlainEncodingTypePB::BINARY_PLAIN_ENCODING_V1};

    // Sequence column unique id mapping to value columns unique id

    std::unordered_map<uint32_t, std::vector<uint32_t>> _seq_col_uid_to_value_cols_uid;

    // Value column unique id mapping to sequence column unique id(also map sequence column it self)

    std::unordered_map<uint32_t, uint32_t> _value_col_uid_to_seq_col_uid;

    // Sequence column index mapping to value column index

    std::unordered_map<uint32_t, std::vector<uint32_t>> _seq_col_idx_to_value_cols_idx;

    // Value column index mapping to sequence column index(also map sequence column it self)

    std::unordered_map<uint32_t, uint32_t> _value_col_idx_to_seq_col_idx;

};

bool operator==(const TabletSchema& a, const TabletSchema& b);

bool operator!=(const TabletSchema& a, const TabletSchema& b);

using TabletSchemaSPtr = std::shared_ptr<TabletSchema>;

#include "common/compile_check_end.h"

} // namespace doris