// 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/Exprs_types.h>

#include <stddef.h>

#include <stdint.h>

#include <map>

#include <memory>

#include <ostream>

#include <roaring/roaring.hh>

#include <set>

#include <string>

#include <unordered_map>

#include <utility>

#include <vector>

#include "common/status.h"

#include "core/block/block.h"

#include "core/block/column_with_type_and_name.h"

#include "core/block/columns_with_type_and_name.h"

#include "core/column/column.h"

#include "core/data_type/data_type.h"

#include "core/data_type/primitive_type.h"

#include "core/field.h"

#include "exec/common/variant_util.h"

#include "exprs/score_runtime.h"

#include "exprs/vexpr_fwd.h"

#include "io/fs/file_reader_writer_fwd.h"

#include "runtime/runtime_profile.h"

#include "storage/field.h"

#include "storage/index/ann/ann_topn_runtime.h"

#include "storage/index/index_iterator.h"

#include "storage/iterators.h"

#include "storage/olap_common.h"

#include "storage/predicate/block_column_predicate.h"

#include "storage/predicate/column_predicate.h"

#include "storage/row_cursor.h"

#include "storage/schema.h"

#include "storage/segment/adaptive_block_size_predictor.h"

#include "storage/segment/common.h"

#include "storage/segment/segment.h"

#include "util/slice.h"

namespace doris {

class ObjectPool;

class MatchPredicate;

class VExpr;

class VExprContext;

struct RowLocation;

namespace segment_v2 {

class ColumnIterator;

class InvertedIndexIterator;

class RowRanges;

class IndexIterator;

struct ColumnPredicateInfo {

    ColumnPredicateInfo() = default;

    std::string debug_string() const {

        std::stringstream ss;

        ss << "column_name=" << column_name << ", query_op=" << query_op

           << ", query_value=" << boost::join(query_values, ",");

        return ss.str();

    }

    bool is_empty() const {

        return column_name.empty() && query_values.empty() && query_op.empty();

    }

    bool is_equal(const ColumnPredicateInfo& column_pred_info) const {

        if (column_pred_info.column_name != column_name) {

            return false;

        }

        if (column_pred_info.query_values != query_values) {

            return false;

        }

        if (column_pred_info.query_op != query_op) {

            return false;

        }

        return true;

    }

    std::string column_name;

    // use set to ensure the consistent order of predicate_result_sign generated by inlist.

    std::set<std::string> query_values;

    std::string query_op;

    int32_t column_id;

};

class SegmentIterator : public RowwiseIterator {

public:

    SegmentIterator(std::shared_ptr<Segment> segment, SchemaSPtr schema);

    ~SegmentIterator() override;

    [[nodiscard]] Status init_iterators();

    [[nodiscard]] Status init(const StorageReadOptions& opts) override;

    [[nodiscard]] Status next_batch(Block* block) override;

    // Get current block row locations. This function should be called

    // after the `next_batch` function.

    // Only vectorized version is supported.

    [[nodiscard]] Status current_block_row_locations(

            std::vector<RowLocation>* block_row_locations) override;

    const Schema& schema() const override { return *_schema; }

    Segment& segment() { return *_segment; }

    StorageReadOptions& storage_read_options() { return _opts; }

    uint64_t data_id() const override { return _segment->id(); }

    RowsetId rowset_id() const { return _segment->rowset_id(); }

    int64_t tablet_id() const { return _tablet_id; }

    void update_profile(RuntimeProfile* profile) override {

        _update_profile(profile, _short_cir_eval_predicate, "ShortCircuitPredicates");

        _update_profile(profile, _pre_eval_block_predicate, "PreEvaluatePredicates");

        if (_opts.delete_condition_predicates != nullptr) {

            std::set<std::shared_ptr<const ColumnPredicate>> delete_predicate_set;

            _opts.delete_condition_predicates->get_all_column_predicate(delete_predicate_set);

            _update_profile(profile, delete_predicate_set, "DeleteConditionPredicates");

        }

    }

    bool has_index_in_iterators() const {

        return std::any_of(_index_iterators.begin(), _index_iterators.end(),

                           [](const auto& iterator) { return iterator != nullptr; });

    }

private:

    Status _next_batch_internal(Block* block);

    Status _check_output_block(Block* block);

    template <typename Container>

    void _update_profile(RuntimeProfile* profile, const Container& predicates,

                         const std::string& title) {

        if (predicates.empty()) {

            return;

        }

        std::string info;

        for (auto pred : predicates) {

            info += "\n" + pred->debug_string();

        }

        profile->add_info_string(title, info);

    }

Unexecuted instantiation: _ZN5doris10segment_v215SegmentIterator15_update_profileISt6vectorISt10shared_ptrINS_15ColumnPredicateEESaIS6_EEEEvPNS_14RuntimeProfileERKT_RKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEE

Unexecuted instantiation: _ZN5doris10segment_v215SegmentIterator15_update_profileISt3setISt10shared_ptrIKNS_15ColumnPredicateEESt4lessIS7_ESaIS7_EEEEvPNS_14RuntimeProfileERKT_RKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEE

    [[nodiscard]] Status _lazy_init(Block* block);

    [[nodiscard]] Status _init_impl(const StorageReadOptions& opts);

    [[nodiscard]] Status _init_return_column_iterators();

    [[nodiscard]] Status _init_index_iterators();

    // calculate row ranges that fall into requested key ranges using short key index

    [[nodiscard]] Status _get_row_ranges_by_keys();

    [[nodiscard]] Status _prepare_seek(const StorageReadOptions::KeyRange& key_range);

    [[nodiscard]] Status _lookup_ordinal(const RowCursor& key, bool is_include, rowid_t upper_bound,

                                         rowid_t* rowid);

    // lookup the ordinal of given key from short key index

    // the returned rowid is rowid in primary index, not the rowid encoded in primary key

    [[nodiscard]] Status _lookup_ordinal_from_sk_index(const RowCursor& key, bool is_include,

                                                       rowid_t upper_bound, rowid_t* rowid);

    // lookup the ordinal of given key from primary key index

    [[nodiscard]] Status _lookup_ordinal_from_pk_index(const RowCursor& key, bool is_include,

                                                       rowid_t* rowid);

    [[nodiscard]] Status _seek_and_peek(rowid_t rowid);

    // calculate row ranges that satisfy requested column conditions using various column index

    [[nodiscard]] Status _get_row_ranges_by_column_conditions();

    [[nodiscard]] Status _get_row_ranges_from_conditions(RowRanges* condition_row_ranges);

    [[nodiscard]] Status _apply_inverted_index();

    [[nodiscard]] Status _apply_inverted_index_on_column_predicate(

            std::shared_ptr<ColumnPredicate> pred,

            std::vector<std::shared_ptr<ColumnPredicate>>& remaining_predicates,

            bool* continue_apply);

    [[nodiscard]] Status _apply_ann_topn_predicate();

    [[nodiscard]] Status _apply_index_expr();

    bool _column_has_fulltext_index(int32_t cid);

    bool _column_has_ann_index(int32_t cid);

    bool _downgrade_without_index(Status res, bool need_remaining = false);

    inline bool _inverted_index_not_support_pred_type(const PredicateType& type);

    bool _is_literal_node(const TExprNodeType::type& node_type);

    Status _vec_init_lazy_materialization();

    // TODO: Fix Me

    // CHAR type in storage layer padding the 0 in length. But query engine need ignore the padding 0.

    // so segment iterator need to shrink char column before output it. only use in vec query engine.

    void _vec_init_char_column_id(Block* block);

    bool _has_char_type(const StorageField& column_desc);

    uint32_t segment_id() const { return _segment->id(); }

    uint32_t num_rows() const { return _segment->num_rows(); }

    [[nodiscard]] Status _seek_columns(const std::vector<ColumnId>& column_ids, rowid_t pos);

    // read `nrows` of columns specified by `column_ids` into `block` at `row_offset`.

    // for vectorization implementation

    [[nodiscard]] Status _read_columns(const std::vector<ColumnId>& column_ids,

                                       MutableColumns& column_block, size_t nrows);

    [[nodiscard]] Status _read_columns_by_index(uint32_t nrows_read_limit, uint16_t& nrows_read);

    void _replace_version_col_if_needed(const std::vector<ColumnId>& column_ids, size_t num_rows);

    Status _init_current_block(Block* block, std::vector<MutableColumnPtr>& non_pred_vector,

                               uint32_t nrows_read_limit);

    uint16_t _evaluate_vectorization_predicate(uint16_t* sel_rowid_idx, uint16_t selected_size);

    uint16_t _evaluate_short_circuit_predicate(uint16_t* sel_rowid_idx, uint16_t selected_size);

    void _collect_runtime_filter_predicate();

    Status _output_non_pred_columns(Block* block);

    [[nodiscard]] Status _read_columns_by_rowids(std::vector<ColumnId>& read_column_ids,

                                                 std::vector<rowid_t>& rowid_vector,

                                                 uint16_t* sel_rowid_idx, size_t select_size,

                                                 MutableColumns* mutable_columns,

                                                 bool init_condition_cache = false);

    Status copy_column_data_by_selector(IColumn* input_col_ptr, MutableColumnPtr& output_col,

                                        uint16_t* sel_rowid_idx, uint16_t select_size,

                                        size_t batch_size);

    template <class Container>

    [[nodiscard]] Status _output_column_by_sel_idx(Block* block, const Container& column_ids,

                                                   uint16_t* sel_rowid_idx, uint16_t select_size) {

        SCOPED_RAW_TIMER(&_opts.stats->output_col_ns);

        for (auto cid : column_ids) {

            int block_cid = _schema_block_id_map[cid];

            // Only the additional deleted filter condition need to materialize column be at the end of the block

            // We should not to materialize the column of query engine do not need. So here just return OK.

            // Eg:

            //      `delete from table where a = 10;`

            //      `select b from table;`

            // a column only effective in segment iterator, the block from query engine only contain the b column.

            // so the `block_cid >= data.size()` is true

            if (block_cid >= block->columns()) {

                continue;

            }

            DataTypePtr storage_type =

                    _segment->get_data_type_of(_schema->column(cid)->get_desc(), _opts);

            if (storage_type && !storage_type->equals(*block->get_by_position(block_cid).type)) {

                // Do additional cast

                MutableColumnPtr tmp = storage_type->create_column();

                RETURN_IF_ERROR(copy_column_data_by_selector(_current_return_columns[cid].get(),

                                                             tmp, sel_rowid_idx, select_size,

                                                             _opts.block_row_max));

                RETURN_IF_ERROR(variant_util::cast_column(

                        {tmp->get_ptr(), storage_type, ""}, block->get_by_position(block_cid).type,

                        &block->get_by_position(block_cid).column));

            } else {

                MutableColumnPtr output_column =

                        block->get_by_position(block_cid).column->assume_mutable();

                RETURN_IF_ERROR(copy_column_data_by_selector(_current_return_columns[cid].get(),

                                                             output_column, sel_rowid_idx,

                                                             select_size, _opts.block_row_max));

            }

        }

        return Status::OK();

    }

    bool _can_evaluated_by_vectorized(std::shared_ptr<ColumnPredicate> predicate);

    [[nodiscard]] Status _extract_common_expr_columns(const VExprSPtr& expr);

    // same with _extract_common_expr_columns, but only extract columns that can be used for index

    [[nodiscard]] Status _execute_common_expr(uint16_t* sel_rowid_idx, uint16_t& selected_size,

                                              Block* block);

    Status _process_common_expr(uint16_t* sel_rowid_idx, uint16_t& selected_size, Block* block);

    uint16_t _evaluate_common_expr_filter(uint16_t* sel_rowid_idx, uint16_t selected_size,

                                          const IColumn::Filter& filter);

    // Dictionary column should do something to initial.

    void _convert_dict_code_for_predicate_if_necessary();

    void _convert_dict_code_for_predicate_if_necessary_impl(

            std::shared_ptr<ColumnPredicate> predicate);

    bool _check_apply_by_inverted_index(std::shared_ptr<ColumnPredicate> pred);

    void _output_index_result_column(const std::vector<VExprContext*>& expr_ctxs,

                                     uint16_t* sel_rowid_idx, uint16_t select_size, Block* block);

    bool _need_read_data(ColumnId cid);

    bool _prune_column(ColumnId cid, MutableColumnPtr& column, bool fill_defaults,

                       size_t num_of_defaults);

    Status _construct_compound_expr_context();

    int _compare_short_key_with_seek_block(const RowCursor& key,

                                           const std::vector<ColumnId>& col_ids) {

        for (auto cid : col_ids) {

            auto ord = key.field(cid) <=> (*_seek_block[cid])[0];

            if (ord != std::strong_ordering::equal) {

                return ord < 0 ? -1 : 1;

            }

        }

        return 0;

    }

    Status _convert_to_expected_type(const std::vector<ColumnId>& col_ids);

    bool _no_need_read_key_data(ColumnId cid, MutableColumnPtr& column, size_t nrows_read);

    bool _has_delete_predicate(ColumnId cid);

    bool _can_opt_topn_reads();

    void _initialize_predicate_results();

    bool _check_all_conditions_passed_inverted_index_for_column(ColumnId cid,

                                                                bool default_return = false);

    void _calculate_expr_in_remaining_conjunct_root();

    Status _process_eof(Block* block);

    Status _process_column_predicate();

    void _fill_column_nothing();

    Status _process_columns(const std::vector<ColumnId>& column_ids, Block* block);

    // Initialize virtual columns in the block, set all virtual columns in the block to ColumnNothing

    void _init_virtual_columns(Block* block);

    // Fallback logic for virtual column materialization, materializing all unmaterialized virtual columns through expressions

    Status _materialization_of_virtual_column(Block* block);

    void _prepare_score_column_materialization();

    void _init_row_bitmap_by_condition_cache();

    void _init_segment_prefetchers();

    class BitmapRangeIterator;

    class BackwardBitmapRangeIterator;

    std::shared_ptr<Segment> _segment;

    // read schema from scanner

    SchemaSPtr _schema;

    // storage type schema related to _schema, since column in segment may be different with type in _schema

    std::vector<IndexFieldNameAndTypePair> _storage_name_and_type;

    // vector idx -> column iterarator

    std::vector<std::unique_ptr<ColumnIterator>> _column_iterators;

    std::vector<std::unique_ptr<IndexIterator>> _index_iterators;

    // after init(), `_row_bitmap` contains all rowid to scan

    roaring::Roaring _row_bitmap;

    // an iterator for `_row_bitmap` that can be used to extract row range to scan

    std::unique_ptr<BitmapRangeIterator> _range_iter;

    // the next rowid to read

    rowid_t _cur_rowid;

    // members related to lazy materialization read

    // --------------------------------------------

    // whether lazy materialization read should be used.

    bool _lazy_materialization_read;

    // columns to read after predicate evaluation and remaining expr execute

    std::vector<ColumnId> _non_predicate_columns;

    std::set<ColumnId> _common_expr_columns;

    // remember the rowids we've read for the current row block.

    // could be a local variable of next_batch(), kept here to reuse vector memory

    std::vector<rowid_t> _block_rowids;

    bool _is_need_vec_eval = false;

    bool _is_need_short_eval = false;

    bool _is_need_expr_eval = false;

    // fields for vectorization execution

    std::vector<ColumnId>

            _vec_pred_column_ids; // keep columnId of columns for vectorized predicate evaluation

    std::vector<ColumnId>

            _short_cir_pred_column_ids; // keep columnId of columns for short circuit predicate evaluation

    std::vector<bool> _is_pred_column; // columns hold _init segmentIter

    std::map<uint32_t, bool> _need_read_data_indices;

    std::vector<bool> _is_common_expr_column;

    MutableColumns _current_return_columns;

    std::vector<std::shared_ptr<ColumnPredicate>> _pre_eval_block_predicate;

    std::vector<std::shared_ptr<ColumnPredicate>> _short_cir_eval_predicate;

    std::vector<uint32_t> _delete_range_column_ids;

    std::vector<uint32_t> _delete_bloom_filter_column_ids;

    // when lazy materialization is enabled, segmentIter need to read data at least twice

    // first, read predicate columns by various index

    // second, read non-predicate columns

    // so we need a field to stand for columns first time to read

    std::vector<ColumnId> _predicate_column_ids;

    std::vector<ColumnId> _common_expr_column_ids;

    // TODO: Should use std::vector<size_t>

    std::vector<ColumnId> _columns_to_filter;

    std::vector<bool> _converted_column_ids;

    // TODO: Should use std::vector<size_t>

    std::vector<int> _schema_block_id_map; // map from schema column id to column idx in Block

    // the actual init process is delayed to the first call to next_batch()

    bool _lazy_inited;

    bool _inited;

    StorageReadOptions _opts;

    // Adaptive batch size predictor; null when the feature is disabled.

    std::unique_ptr<AdaptiveBlockSizePredictor> _block_size_predictor;

    // Build the AdaptiveBlockSizePredictor for this segment based on segment footer

    // metadata for the projected output columns. Returns nullptr if the feature is

    // disabled or the byte budget is non-positive.

    std::unique_ptr<AdaptiveBlockSizePredictor> _make_block_size_predictor() const;

    // Snapshot of _opts.block_row_max at init time; used as the hard upper bound so that

    // dynamic adjustments never exceed the capacity of pre-allocated buffers.

    uint32_t _initial_block_row_max = 0;

    // make a copy of `_opts.column_predicates` in order to make local changes

    std::vector<std::shared_ptr<ColumnPredicate>> _col_predicates;

    VExprContextSPtrs _common_expr_ctxs_push_down;

    bool _enable_common_expr_pushdown = false;

    std::vector<VExprSPtr> _remaining_conjunct_roots;

    std::set<ColumnId> _not_apply_index_pred;

    // row schema of the key to seek

    // only used in `_get_row_ranges_by_keys`

    std::unique_ptr<Schema> _seek_schema;

    // used to binary search the rowid for a given key

    // only used in `_get_row_ranges_by_keys`

    MutableColumns _seek_block;

    io::FileReaderSPtr _file_reader;

    // char_type or array<char> type columns cid

    std::vector<size_t> _char_type_idx;

    std::vector<bool> _is_char_type;

    // used for compaction, record selectd rowids of current batch

    uint16_t _selected_size;

    std::vector<uint16_t> _sel_rowid_idx;

    std::unique_ptr<ObjectPool> _pool;

    // used to collect filter information.

    std::vector<std::shared_ptr<ColumnPredicate>> _filter_info_id;

    bool _record_rowids = false;

    int64_t _tablet_id = 0;

    std::set<int32_t> _output_columns;

    std::vector<uint8_t> _ret_flags;

    /*

    * column and column_predicates on it.

    * a boolean value to indicate whether the column has been read by the index.

    */

    std::unordered_map<ColumnId, std::unordered_map<std::shared_ptr<ColumnPredicate>, bool>>

            _column_predicate_index_exec_status;

    /*

    * column and common expr on it.

    * a boolean value to indicate whether the column has been read by the index.

    */

    std::unordered_map<ColumnId, std::unordered_map<const VExpr*, bool>>

            _common_expr_index_exec_status;

    /*

    * common expr context to slotref map

    * slot ref map is used to get slot ref expr by using column id.

    */

    std::unordered_map<VExprContext*, std::unordered_map<ColumnId, VExpr*>>

            _common_expr_to_slotref_map;

    ScoreRuntimeSPtr _score_runtime;

    std::shared_ptr<segment_v2::AnnTopNRuntime> _ann_topn_runtime;

    // cid to virtual column expr

    std::map<ColumnId, VExprContextSPtr> _virtual_column_exprs;

    std::map<ColumnId, size_t> _vir_cid_to_idx_in_block;

    IndexQueryContextPtr _index_query_context;

    // key is column uid, value is the sparse column cache

    std::unordered_map<int32_t, PathToBinaryColumnCacheUPtr> _variant_sparse_column_cache;

    bool _find_condition_cache = false;

    std::shared_ptr<std::vector<bool>> _condition_cache;

    static constexpr int CONDITION_CACHE_OFFSET = 2048;

};

} // namespace segment_v2

} // namespace doris