Coverage Report

Created: 2026-03-27 23:22

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/format/table/iceberg_reader.cpp
Line
Count
Source
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// Licensed to the Apache Software Foundation (ASF) under one
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// or more contributor license agreements.  See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
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// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
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//   http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
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#include "format/table/iceberg_reader.h"
19
20
#include <gen_cpp/Descriptors_types.h>
21
#include <gen_cpp/Metrics_types.h>
22
#include <gen_cpp/PlanNodes_types.h>
23
#include <gen_cpp/parquet_types.h>
24
#include <glog/logging.h>
25
#include <parallel_hashmap/phmap.h>
26
#include <rapidjson/document.h>
27
28
#include <algorithm>
29
#include <cstring>
30
#include <functional>
31
#include <memory>
32
#include <set>
33
34
#include "common/compiler_util.h" // IWYU pragma: keep
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#include "common/status.h"
36
#include "core/assert_cast.h"
37
#include "core/block/block.h"
38
#include "core/block/column_with_type_and_name.h"
39
#include "core/column/column.h"
40
#include "core/column/column_string.h"
41
#include "core/column/column_vector.h"
42
#include "core/data_type/data_type_factory.hpp"
43
#include "core/data_type/define_primitive_type.h"
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#include "core/data_type/primitive_type.h"
45
#include "core/string_ref.h"
46
#include "exprs/aggregate/aggregate_function.h"
47
#include "format/format_common.h"
48
#include "format/generic_reader.h"
49
#include "format/orc/vorc_reader.h"
50
#include "format/parquet/schema_desc.h"
51
#include "format/parquet/vparquet_column_chunk_reader.h"
52
#include "format/table/deletion_vector_reader.h"
53
#include "format/table/iceberg/iceberg_orc_nested_column_utils.h"
54
#include "format/table/iceberg/iceberg_parquet_nested_column_utils.h"
55
#include "format/table/nested_column_access_helper.h"
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#include "format/table/table_format_reader.h"
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#include "runtime/runtime_state.h"
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#include "util/coding.h"
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namespace cctz {
61
#include "common/compile_check_begin.h"
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class time_zone;
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} // namespace cctz
64
namespace doris {
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class RowDescriptor;
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class SlotDescriptor;
67
class TupleDescriptor;
68
69
namespace io {
70
struct IOContext;
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} // namespace io
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class VExprContext;
73
} // namespace doris
74
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namespace doris {
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const std::string IcebergOrcReader::ICEBERG_ORC_ATTRIBUTE = "iceberg.id";
77
78
IcebergTableReader::IcebergTableReader(std::unique_ptr<GenericReader> file_format_reader,
79
                                       RuntimeProfile* profile, RuntimeState* state,
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                                       const TFileScanRangeParams& params,
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                                       const TFileRangeDesc& range, ShardedKVCache* kv_cache,
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                                       io::IOContext* io_ctx, FileMetaCache* meta_cache)
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16
        : TableFormatReader(std::move(file_format_reader), state, profile, params, range, io_ctx,
84
16
                            meta_cache),
85
16
          _kv_cache(kv_cache) {
86
16
    static const char* iceberg_profile = "IcebergProfile";
87
16
    ADD_TIMER(_profile, iceberg_profile);
88
16
    _iceberg_profile.num_delete_files =
89
16
            ADD_CHILD_COUNTER(_profile, "NumDeleteFiles", TUnit::UNIT, iceberg_profile);
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16
    _iceberg_profile.num_delete_rows =
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16
            ADD_CHILD_COUNTER(_profile, "NumDeleteRows", TUnit::UNIT, iceberg_profile);
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16
    _iceberg_profile.delete_files_read_time =
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16
            ADD_CHILD_TIMER(_profile, "DeleteFileReadTime", iceberg_profile);
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16
    _iceberg_profile.delete_rows_sort_time =
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16
            ADD_CHILD_TIMER(_profile, "DeleteRowsSortTime", iceberg_profile);
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16
    _iceberg_profile.parse_delete_file_time =
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16
            ADD_CHILD_TIMER(_profile, "ParseDeleteFileTime", iceberg_profile);
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16
}
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100
2
Status IcebergTableReader::get_next_block_inner(Block* block, size_t* read_rows, bool* eof) {
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2
    RETURN_IF_ERROR(_expand_block_if_need(block));
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103
2
    RETURN_IF_ERROR(_file_format_reader->get_next_block(block, read_rows, eof));
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105
2
    if (_equality_delete_impls.size() > 0) {
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0
        std::unique_ptr<IColumn::Filter> filter =
107
0
                std::make_unique<IColumn::Filter>(block->rows(), 1);
108
0
        for (auto& equality_delete_impl : _equality_delete_impls) {
109
0
            RETURN_IF_ERROR(equality_delete_impl->filter_data_block(
110
0
                    block, _col_name_to_block_idx, _id_to_block_column_name, *filter));
111
0
        }
112
0
        Block::filter_block_internal(block, *filter, block->columns());
113
0
    }
114
115
2
    *read_rows = block->rows();
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2
    return _shrink_block_if_need(block);
117
2
}
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119
2
Status IcebergTableReader::init_row_filters() {
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    // We get the count value by doris's be, so we don't need to read the delete file
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2
    if (_push_down_agg_type == TPushAggOp::type::COUNT && _table_level_row_count > 0) {
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0
        return Status::OK();
123
0
    }
124
125
2
    const auto& table_desc = _range.table_format_params.iceberg_params;
126
2
    const auto& version = table_desc.format_version;
127
2
    if (version < MIN_SUPPORT_DELETE_FILES_VERSION) {
128
2
        return Status::OK();
129
2
    }
130
131
    // Initialize file information for $row_id generation
132
    // Extract from table_desc which contains current file's metadata
133
0
    if (_need_row_id_column) {
134
0
        std::string file_path = table_desc.original_file_path;
135
0
        int32_t partition_spec_id = 0;
136
0
        std::string partition_data_json;
137
0
        if (table_desc.__isset.partition_spec_id) {
138
0
            partition_spec_id = table_desc.partition_spec_id;
139
0
        }
140
0
        if (table_desc.__isset.partition_data_json) {
141
0
            partition_data_json = table_desc.partition_data_json;
142
0
        }
143
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0
        if (auto* parquet_reader = dynamic_cast<ParquetReader*>(_file_format_reader.get())) {
145
0
            parquet_reader->set_iceberg_rowid_params(file_path, partition_spec_id,
146
0
                                                     partition_data_json, _row_id_column_position);
147
0
        } else if (auto* orc_reader = dynamic_cast<OrcReader*>(_file_format_reader.get())) {
148
0
            orc_reader->set_iceberg_rowid_params(file_path, partition_spec_id, partition_data_json,
149
0
                                                 _row_id_column_position);
150
0
        }
151
0
        LOG(INFO) << "Initialized $row_id generation for file: " << file_path
152
0
                  << ", partition_spec_id: " << partition_spec_id;
153
0
    }
154
155
0
    std::vector<TIcebergDeleteFileDesc> position_delete_files;
156
0
    std::vector<TIcebergDeleteFileDesc> equality_delete_files;
157
0
    std::vector<TIcebergDeleteFileDesc> deletion_vector_files;
158
0
    for (const TIcebergDeleteFileDesc& desc : table_desc.delete_files) {
159
0
        if (desc.content == POSITION_DELETE) {
160
0
            position_delete_files.emplace_back(desc);
161
0
        } else if (desc.content == EQUALITY_DELETE) {
162
0
            equality_delete_files.emplace_back(desc);
163
0
        } else if (desc.content == DELETION_VECTOR) {
164
0
            deletion_vector_files.emplace_back(desc);
165
0
        }
166
0
    }
167
168
0
    if (!equality_delete_files.empty()) {
169
0
        RETURN_IF_ERROR(_process_equality_delete(equality_delete_files));
170
0
        _file_format_reader->set_push_down_agg_type(TPushAggOp::NONE);
171
0
    }
172
173
0
    if (!deletion_vector_files.empty()) {
174
0
        if (deletion_vector_files.size() != 1) [[unlikely]] {
175
            /*
176
             * Deletion vectors are a binary representation of deletes for a single data file that is more efficient
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             * at execution time than position delete files. Unlike equality or position delete files, there can be
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             * at most one deletion vector for a given data file in a snapshot.
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             */
180
0
            return Status::DataQualityError("This iceberg data file has multiple DVs.");
181
0
        }
182
0
        RETURN_IF_ERROR(
183
0
                read_deletion_vector(table_desc.original_file_path, deletion_vector_files[0]));
184
185
0
        _file_format_reader->set_push_down_agg_type(TPushAggOp::NONE);
186
        // Readers can safely ignore position delete files if there is a DV for a data file.
187
0
    } else if (!position_delete_files.empty()) {
188
0
        RETURN_IF_ERROR(
189
0
                _position_delete_base(table_desc.original_file_path, position_delete_files));
190
0
        _file_format_reader->set_push_down_agg_type(TPushAggOp::NONE);
191
0
    }
192
193
0
    COUNTER_UPDATE(_iceberg_profile.num_delete_files, table_desc.delete_files.size());
194
0
    return Status::OK();
195
0
}
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void IcebergTableReader::_generate_equality_delete_block(
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        Block* block, const std::vector<std::string>& equality_delete_col_names,
199
0
        const std::vector<DataTypePtr>& equality_delete_col_types) {
200
0
    for (int i = 0; i < equality_delete_col_names.size(); ++i) {
201
0
        DataTypePtr data_type = make_nullable(equality_delete_col_types[i]);
202
0
        MutableColumnPtr data_column = data_type->create_column();
203
0
        block->insert(ColumnWithTypeAndName(std::move(data_column), data_type,
204
0
                                            equality_delete_col_names[i]));
205
0
    }
206
0
}
207
208
2
Status IcebergTableReader::_expand_block_if_need(Block* block) {
209
2
    std::set<std::string> names;
210
2
    auto block_names = block->get_names();
211
2
    names.insert(block_names.begin(), block_names.end());
212
2
    for (auto& col : _expand_columns) {
213
0
        col.column->assume_mutable()->clear();
214
0
        if (names.contains(col.name)) {
215
0
            return Status::InternalError("Wrong expand column '{}'", col.name);
216
0
        }
217
0
        names.insert(col.name);
218
0
        (*_col_name_to_block_idx)[col.name] = static_cast<uint32_t>(block->columns());
219
0
        block->insert(col);
220
0
    }
221
2
    return Status::OK();
222
2
}
223
224
2
Status IcebergTableReader::_shrink_block_if_need(Block* block) {
225
2
    std::set<size_t> positions_to_erase;
226
2
    for (const std::string& expand_col : _expand_col_names) {
227
0
        if (!_col_name_to_block_idx->contains(expand_col)) {
228
0
            return Status::InternalError("Wrong erase column '{}', block: {}", expand_col,
229
0
                                         block->dump_names());
230
0
        }
231
0
        positions_to_erase.emplace((*_col_name_to_block_idx)[expand_col]);
232
0
    }
233
2
    block->erase(positions_to_erase);
234
2
    for (const std::string& expand_col : _expand_col_names) {
235
0
        _col_name_to_block_idx->erase(expand_col);
236
0
    }
237
2
    return Status::OK();
238
2
}
239
240
Status IcebergTableReader::_position_delete_base(
241
0
        const std::string data_file_path, const std::vector<TIcebergDeleteFileDesc>& delete_files) {
242
0
    std::vector<DeleteRows*> delete_rows_array;
243
0
    int64_t num_delete_rows = 0;
244
0
    for (const auto& delete_file : delete_files) {
245
0
        SCOPED_TIMER(_iceberg_profile.delete_files_read_time);
246
0
        Status create_status = Status::OK();
247
0
        auto* delete_file_cache = _kv_cache->get<DeleteFile>(
248
0
                _delet_file_cache_key(delete_file.path), [&]() -> DeleteFile* {
249
0
                    auto* position_delete = new DeleteFile;
250
0
                    TFileRangeDesc delete_file_range;
251
                    // must use __set() method to make sure __isset is true
252
0
                    delete_file_range.__set_fs_name(_range.fs_name);
253
0
                    delete_file_range.path = delete_file.path;
254
0
                    delete_file_range.start_offset = 0;
255
0
                    delete_file_range.size = -1;
256
0
                    delete_file_range.file_size = -1;
257
                    //read position delete file base on delete_file_range , generate DeleteFile , add DeleteFile to kv_cache
258
0
                    create_status = _read_position_delete_file(&delete_file_range, position_delete);
259
260
0
                    if (!create_status) {
261
0
                        return nullptr;
262
0
                    }
263
264
0
                    return position_delete;
265
0
                });
266
0
        if (create_status.is<ErrorCode::END_OF_FILE>()) {
267
0
            continue;
268
0
        } else if (!create_status.ok()) {
269
0
            return create_status;
270
0
        }
271
272
0
        DeleteFile& delete_file_map = *((DeleteFile*)delete_file_cache);
273
0
        auto get_value = [&](const auto& v) {
274
0
            DeleteRows* row_ids = v.second.get();
275
0
            if (!row_ids->empty()) {
276
0
                delete_rows_array.emplace_back(row_ids);
277
0
                num_delete_rows += row_ids->size();
278
0
            }
279
0
        };
280
0
        delete_file_map.if_contains(data_file_path, get_value);
281
0
    }
282
    // Use a KV cache to store the delete rows corresponding to a data file path.
283
    // The Parquet/ORC reader holds a reference (pointer) to this cached entry.
284
    // This allows delete rows to be reused when a single data file is split into
285
    // multiple splits, avoiding excessive memory usage when delete rows are large.
286
0
    if (num_delete_rows > 0) {
287
0
        SCOPED_TIMER(_iceberg_profile.delete_rows_sort_time);
288
0
        _iceberg_delete_rows =
289
0
                _kv_cache->get<DeleteRows>(data_file_path,
290
0
                                           [&]() -> DeleteRows* {
291
0
                                               auto* data_file_position_delete = new DeleteRows;
292
0
                                               _sort_delete_rows(delete_rows_array, num_delete_rows,
293
0
                                                                 *data_file_position_delete);
294
295
0
                                               return data_file_position_delete;
296
0
                                           }
297
298
0
                );
299
0
        set_delete_rows();
300
0
        COUNTER_UPDATE(_iceberg_profile.num_delete_rows, num_delete_rows);
301
0
    }
302
0
    return Status::OK();
303
0
}
304
305
IcebergTableReader::PositionDeleteRange IcebergTableReader::_get_range(
306
0
        const ColumnDictI32& file_path_column) {
307
0
    IcebergTableReader::PositionDeleteRange range;
308
0
    size_t read_rows = file_path_column.get_data().size();
309
0
    const int* code_path = file_path_column.get_data().data();
310
0
    const int* code_path_start = code_path;
311
0
    const int* code_path_end = code_path + read_rows;
312
0
    while (code_path < code_path_end) {
313
0
        int code = code_path[0];
314
0
        const int* code_end = std::upper_bound(code_path, code_path_end, code);
315
0
        range.data_file_path.emplace_back(file_path_column.get_value(code).to_string());
316
0
        range.range.emplace_back(code_path - code_path_start, code_end - code_path_start);
317
0
        code_path = code_end;
318
0
    }
319
0
    return range;
320
0
}
321
322
IcebergTableReader::PositionDeleteRange IcebergTableReader::_get_range(
323
0
        const ColumnString& file_path_column) {
324
0
    IcebergTableReader::PositionDeleteRange range;
325
0
    size_t read_rows = file_path_column.size();
326
0
    size_t index = 0;
327
0
    while (index < read_rows) {
328
0
        StringRef data_path = file_path_column.get_data_at(index);
329
0
        size_t left = index - 1;
330
0
        size_t right = read_rows;
331
0
        while (left + 1 != right) {
332
0
            size_t mid = left + (right - left) / 2;
333
0
            if (file_path_column.get_data_at(mid) > data_path) {
334
0
                right = mid;
335
0
            } else {
336
0
                left = mid;
337
0
            }
338
0
        }
339
0
        range.data_file_path.emplace_back(data_path.to_string());
340
0
        range.range.emplace_back(index, left + 1);
341
0
        index = left + 1;
342
0
    }
343
0
    return range;
344
0
}
345
346
/**
347
 * https://iceberg.apache.org/spec/#position-delete-files
348
 * The rows in the delete file must be sorted by file_path then position to optimize filtering rows while scanning.
349
 * Sorting by file_path allows filter pushdown by file in columnar storage formats.
350
 * Sorting by position allows filtering rows while scanning, to avoid keeping deletes in memory.
351
 */
352
void IcebergTableReader::_sort_delete_rows(
353
        const std::vector<std::vector<int64_t>*>& delete_rows_array, int64_t num_delete_rows,
354
0
        std::vector<int64_t>& result) {
355
0
    if (delete_rows_array.empty()) {
356
0
        return;
357
0
    }
358
0
    if (delete_rows_array.size() == 1) {
359
0
        result.resize(num_delete_rows);
360
0
        memcpy(result.data(), delete_rows_array.front()->data(), sizeof(int64_t) * num_delete_rows);
361
0
        return;
362
0
    }
363
0
    if (delete_rows_array.size() == 2) {
364
0
        result.resize(num_delete_rows);
365
0
        std::merge(delete_rows_array.front()->begin(), delete_rows_array.front()->end(),
366
0
                   delete_rows_array.back()->begin(), delete_rows_array.back()->end(),
367
0
                   result.begin());
368
0
        return;
369
0
    }
370
371
0
    using vec_pair = std::pair<std::vector<int64_t>::iterator, std::vector<int64_t>::iterator>;
372
0
    result.resize(num_delete_rows);
373
0
    auto row_id_iter = result.begin();
374
0
    auto iter_end = result.end();
375
0
    std::vector<vec_pair> rows_array;
376
0
    for (auto* rows : delete_rows_array) {
377
0
        if (!rows->empty()) {
378
0
            rows_array.emplace_back(rows->begin(), rows->end());
379
0
        }
380
0
    }
381
0
    size_t array_size = rows_array.size();
382
0
    while (row_id_iter != iter_end) {
383
0
        int64_t min_index = 0;
384
0
        int64_t min = *rows_array[0].first;
385
0
        for (size_t i = 0; i < array_size; ++i) {
386
0
            if (*rows_array[i].first < min) {
387
0
                min_index = i;
388
0
                min = *rows_array[i].first;
389
0
            }
390
0
        }
391
0
        *row_id_iter++ = min;
392
0
        rows_array[min_index].first++;
393
0
        if (UNLIKELY(rows_array[min_index].first == rows_array[min_index].second)) {
394
0
            rows_array.erase(rows_array.begin() + min_index);
395
0
            array_size--;
396
0
        }
397
0
    }
398
0
}
399
400
void IcebergTableReader::_gen_position_delete_file_range(Block& block, DeleteFile* position_delete,
401
                                                         size_t read_rows,
402
0
                                                         bool file_path_column_dictionary_coded) {
403
0
    SCOPED_TIMER(_iceberg_profile.parse_delete_file_time);
404
    // todo: maybe do not need to build name to index map every time
405
0
    auto name_to_pos_map = block.get_name_to_pos_map();
406
0
    ColumnPtr path_column = block.get_by_position(name_to_pos_map[ICEBERG_FILE_PATH]).column;
407
0
    DCHECK_EQ(path_column->size(), read_rows);
408
0
    ColumnPtr pos_column = block.get_by_position(name_to_pos_map[ICEBERG_ROW_POS]).column;
409
0
    using ColumnType = typename PrimitiveTypeTraits<TYPE_BIGINT>::ColumnType;
410
0
    const int64_t* src_data = assert_cast<const ColumnType&>(*pos_column).get_data().data();
411
0
    IcebergTableReader::PositionDeleteRange range;
412
0
    if (file_path_column_dictionary_coded) {
413
0
        range = _get_range(assert_cast<const ColumnDictI32&>(*path_column));
414
0
    } else {
415
0
        range = _get_range(assert_cast<const ColumnString&>(*path_column));
416
0
    }
417
0
    for (int i = 0; i < range.range.size(); ++i) {
418
0
        std::string key = range.data_file_path[i];
419
0
        auto iter = position_delete->find(key);
420
0
        DeleteRows* delete_rows;
421
0
        if (iter == position_delete->end()) {
422
0
            delete_rows = new DeleteRows;
423
0
            std::unique_ptr<DeleteRows> delete_rows_ptr(delete_rows);
424
0
            (*position_delete)[key] = std::move(delete_rows_ptr);
425
0
        } else {
426
0
            delete_rows = iter->second.get();
427
0
        }
428
0
        const int64_t* cpy_start = src_data + range.range[i].first;
429
0
        const int64_t cpy_count = range.range[i].second - range.range[i].first;
430
0
        int64_t origin_size = delete_rows->size();
431
0
        delete_rows->resize(origin_size + cpy_count);
432
0
        int64_t* dest_position = &(*delete_rows)[origin_size];
433
0
        memcpy(dest_position, cpy_start, cpy_count * sizeof(int64_t));
434
0
    }
435
0
}
436
437
Status IcebergParquetReader::init_reader(
438
        const std::vector<std::string>& file_col_names,
439
        std::unordered_map<std::string, uint32_t>* col_name_to_block_idx,
440
        const VExprContextSPtrs& conjuncts,
441
        phmap::flat_hash_map<int, std::vector<std::shared_ptr<ColumnPredicate>>>&
442
                slot_id_to_predicates,
443
        const TupleDescriptor* tuple_descriptor, const RowDescriptor* row_descriptor,
444
        const std::unordered_map<std::string, int>* colname_to_slot_id,
445
        const VExprContextSPtrs* not_single_slot_filter_conjuncts,
446
1
        const std::unordered_map<int, VExprContextSPtrs>* slot_id_to_filter_conjuncts) {
447
1
    _file_format = Fileformat::PARQUET;
448
1
    _col_name_to_block_idx = col_name_to_block_idx;
449
1
    auto* parquet_reader = static_cast<ParquetReader*>(_file_format_reader.get());
450
1
    RETURN_IF_ERROR(parquet_reader->get_file_metadata_schema(&_data_file_field_desc));
451
1
    DCHECK(_data_file_field_desc != nullptr);
452
453
1
    auto column_id_result = _create_column_ids(_data_file_field_desc, tuple_descriptor);
454
1
    auto& column_ids = column_id_result.column_ids;
455
1
    const auto& filter_column_ids = column_id_result.filter_column_ids;
456
457
1
    RETURN_IF_ERROR(init_row_filters());
458
1
    _all_required_col_names = file_col_names;
459
460
1
    if (!_params.__isset.history_schema_info || _params.history_schema_info.empty()) [[unlikely]] {
461
1
        RETURN_IF_ERROR(BuildTableInfoUtil::by_parquet_name(
462
1
                tuple_descriptor, *_data_file_field_desc, table_info_node_ptr));
463
1
    } else {
464
0
        std::set<std::string> read_col_name_set(file_col_names.begin(), file_col_names.end());
465
466
0
        bool exist_field_id = true;
467
0
        for (int idx = 0; idx < _data_file_field_desc->size(); idx++) {
468
0
            if (_data_file_field_desc->get_column(idx)->field_id == -1) {
469
                // the data file may be from hive table migrated to iceberg, field id is missing
470
0
                exist_field_id = false;
471
0
                break;
472
0
            }
473
0
        }
474
0
        const auto& table_schema = _params.history_schema_info.front().root_field;
475
476
0
        table_info_node_ptr = std::make_shared<TableSchemaChangeHelper::StructNode>();
477
0
        if (exist_field_id) {
478
            // id -> table column name. columns that need read data file.
479
0
            std::unordered_map<int, std::shared_ptr<schema::external::TField>> id_to_table_field;
480
0
            for (const auto& table_field : table_schema.fields) {
481
0
                auto field = table_field.field_ptr;
482
0
                DCHECK(field->__isset.name);
483
0
                if (!read_col_name_set.contains(field->name)) {
484
0
                    continue;
485
0
                }
486
0
                id_to_table_field.emplace(field->id, field);
487
0
            }
488
489
0
            for (int idx = 0; idx < _data_file_field_desc->size(); idx++) {
490
0
                const auto& data_file_field = _data_file_field_desc->get_column(idx);
491
0
                auto data_file_column_id = _data_file_field_desc->get_column(idx)->field_id;
492
493
0
                if (id_to_table_field.contains(data_file_column_id)) {
494
0
                    const auto& table_field = id_to_table_field[data_file_column_id];
495
496
0
                    std::shared_ptr<TableSchemaChangeHelper::Node> field_node = nullptr;
497
0
                    RETURN_IF_ERROR(BuildTableInfoUtil::by_parquet_field_id(
498
0
                            *table_field, *data_file_field, exist_field_id, field_node));
499
0
                    table_info_node_ptr->add_children(table_field->name, data_file_field->name,
500
0
                                                      field_node);
501
502
0
                    _id_to_block_column_name.emplace(data_file_column_id, table_field->name);
503
0
                    id_to_table_field.erase(data_file_column_id);
504
0
                } else if (_equality_delete_col_ids.contains(data_file_column_id)) {
505
                    // Columns that need to be read for equality delete.
506
0
                    const static std::string EQ_DELETE_PRE = "__equality_delete_column__";
507
508
                    // Construct table column names that avoid duplication with current table schema.
509
                    // As the columns currently being read may have been deleted in the latest
510
                    // table structure or have undergone a series of schema changes...
511
0
                    std::string table_column_name = EQ_DELETE_PRE + data_file_field->name;
512
0
                    table_info_node_ptr->add_children(
513
0
                            table_column_name, data_file_field->name,
514
0
                            std::make_shared<TableSchemaChangeHelper::ConstNode>());
515
516
0
                    _id_to_block_column_name.emplace(data_file_column_id, table_column_name);
517
0
                    _expand_col_names.emplace_back(table_column_name);
518
0
                    auto expand_data_type = make_nullable(data_file_field->data_type);
519
0
                    _expand_columns.emplace_back(
520
0
                            ColumnWithTypeAndName {expand_data_type->create_column(),
521
0
                                                   expand_data_type, table_column_name});
522
523
0
                    _all_required_col_names.emplace_back(table_column_name);
524
0
                    column_ids.insert(data_file_field->get_column_id());
525
0
                }
526
0
            }
527
0
            for (const auto& [id, table_field] : id_to_table_field) {
528
0
                table_info_node_ptr->add_not_exist_children(table_field->name);
529
0
            }
530
0
        } else {
531
0
            if (!_equality_delete_col_ids.empty()) [[unlikely]] {
532
0
                return Status::InternalError(
533
0
                        "Can not read missing field id data file when have equality delete");
534
0
            }
535
0
            std::map<std::string, size_t> file_column_idx_map;
536
0
            for (size_t idx = 0; idx < _data_file_field_desc->size(); idx++) {
537
0
                file_column_idx_map.emplace(_data_file_field_desc->get_column(idx)->name, idx);
538
0
            }
539
540
0
            for (const auto& table_field : table_schema.fields) {
541
0
                DCHECK(table_field.__isset.field_ptr);
542
0
                DCHECK(table_field.field_ptr->__isset.name);
543
0
                const auto& table_column_name = table_field.field_ptr->name;
544
0
                if (!read_col_name_set.contains(table_column_name)) {
545
0
                    continue;
546
0
                }
547
0
                if (!table_field.field_ptr->__isset.name_mapping ||
548
0
                    table_field.field_ptr->name_mapping.size() == 0) {
549
0
                    return Status::DataQualityError(
550
0
                            "name_mapping must be set when read missing field id data file.");
551
0
                }
552
0
                bool have_mapping = false;
553
0
                for (const auto& mapped_name : table_field.field_ptr->name_mapping) {
554
0
                    if (file_column_idx_map.contains(mapped_name)) {
555
0
                        std::shared_ptr<TableSchemaChangeHelper::Node> field_node = nullptr;
556
0
                        const auto& file_field = _data_file_field_desc->get_column(
557
0
                                file_column_idx_map.at(mapped_name));
558
0
                        RETURN_IF_ERROR(BuildTableInfoUtil::by_parquet_field_id(
559
0
                                *table_field.field_ptr, *file_field, exist_field_id, field_node));
560
0
                        table_info_node_ptr->add_children(table_column_name, file_field->name,
561
0
                                                          field_node);
562
0
                        have_mapping = true;
563
0
                        break;
564
0
                    }
565
0
                }
566
0
                if (!have_mapping) {
567
0
                    table_info_node_ptr->add_not_exist_children(table_column_name);
568
0
                }
569
0
            }
570
0
        }
571
0
    }
572
573
1
    return parquet_reader->init_reader(
574
1
            _all_required_col_names, _col_name_to_block_idx, conjuncts, slot_id_to_predicates,
575
1
            tuple_descriptor, row_descriptor, colname_to_slot_id, not_single_slot_filter_conjuncts,
576
1
            slot_id_to_filter_conjuncts, table_info_node_ptr, true, column_ids, filter_column_ids);
577
1
}
578
579
ColumnIdResult IcebergParquetReader::_create_column_ids(const FieldDescriptor* field_desc,
580
7
                                                        const TupleDescriptor* tuple_descriptor) {
581
    // First, assign column IDs to the field descriptor
582
7
    auto* mutable_field_desc = const_cast<FieldDescriptor*>(field_desc);
583
7
    mutable_field_desc->assign_ids();
584
585
    // map top-level table column iceberg_id -> FieldSchema*
586
7
    std::unordered_map<int, const FieldSchema*> iceberg_id_to_field_schema_map;
587
588
58
    for (int i = 0; i < field_desc->size(); ++i) {
589
51
        auto field_schema = field_desc->get_column(i);
590
51
        if (!field_schema) continue;
591
592
51
        int iceberg_id = field_schema->field_id;
593
51
        iceberg_id_to_field_schema_map[iceberg_id] = field_schema;
594
51
    }
595
596
7
    std::set<uint64_t> column_ids;
597
7
    std::set<uint64_t> filter_column_ids;
598
599
    // helper to process access paths for a given top-level parquet field
600
7
    auto process_access_paths = [](const FieldSchema* parquet_field,
601
7
                                   const std::vector<TColumnAccessPath>& access_paths,
602
14
                                   std::set<uint64_t>& out_ids) {
603
14
        process_nested_access_paths(
604
14
                parquet_field, access_paths, out_ids,
605
14
                [](const FieldSchema* field) { return field->get_column_id(); },
606
14
                [](const FieldSchema* field) { return field->get_max_column_id(); },
607
14
                IcebergParquetNestedColumnUtils::extract_nested_column_ids);
608
14
    };
609
610
15
    for (const auto* slot : tuple_descriptor->slots()) {
611
15
        auto it = iceberg_id_to_field_schema_map.find(slot->col_unique_id());
612
15
        if (it == iceberg_id_to_field_schema_map.end()) {
613
            // Column not found in file (e.g., partition column, added column)
614
0
            continue;
615
0
        }
616
15
        auto field_schema = it->second;
617
618
        // primitive (non-nested) types: direct mapping by name
619
15
        if ((slot->col_type() != TYPE_STRUCT && slot->col_type() != TYPE_ARRAY &&
620
15
             slot->col_type() != TYPE_MAP)) {
621
7
            column_ids.insert(field_schema->column_id);
622
623
7
            if (slot->is_predicate()) {
624
0
                filter_column_ids.insert(field_schema->column_id);
625
0
            }
626
7
            continue;
627
7
        }
628
629
        // complex types:
630
8
        const auto& all_access_paths = slot->all_access_paths();
631
8
        process_access_paths(field_schema, all_access_paths, column_ids);
632
633
8
        const auto& predicate_access_paths = slot->predicate_access_paths();
634
8
        if (!predicate_access_paths.empty()) {
635
6
            process_access_paths(field_schema, predicate_access_paths, filter_column_ids);
636
6
        }
637
8
    }
638
7
    return ColumnIdResult(std::move(column_ids), std::move(filter_column_ids));
639
7
}
640
641
Status IcebergParquetReader ::_read_position_delete_file(const TFileRangeDesc* delete_range,
642
0
                                                         DeleteFile* position_delete) {
643
0
    ParquetReader parquet_delete_reader(_profile, _params, *delete_range,
644
0
                                        READ_DELETE_FILE_BATCH_SIZE, &_state->timezone_obj(),
645
0
                                        _io_ctx, _state, _meta_cache);
646
0
    phmap::flat_hash_map<int, std::vector<std::shared_ptr<ColumnPredicate>>> tmp;
647
0
    RETURN_IF_ERROR(parquet_delete_reader.init_reader(
648
0
            delete_file_col_names,
649
0
            const_cast<std::unordered_map<std::string, uint32_t>*>(&DELETE_COL_NAME_TO_BLOCK_IDX),
650
0
            {}, tmp, nullptr, nullptr, nullptr, nullptr, nullptr,
651
0
            TableSchemaChangeHelper::ConstNode::get_instance(), false));
652
653
0
    std::unordered_map<std::string, std::tuple<std::string, const SlotDescriptor*>>
654
0
            partition_columns;
655
0
    std::unordered_map<std::string, VExprContextSPtr> missing_columns;
656
0
    RETURN_IF_ERROR(parquet_delete_reader.set_fill_columns(partition_columns, missing_columns));
657
658
0
    const tparquet::FileMetaData* meta_data = parquet_delete_reader.get_meta_data();
659
0
    bool dictionary_coded = true;
660
0
    for (const auto& row_group : meta_data->row_groups) {
661
0
        const auto& column_chunk = row_group.columns[ICEBERG_FILE_PATH_INDEX];
662
0
        if (!(column_chunk.__isset.meta_data && has_dict_page(column_chunk.meta_data))) {
663
0
            dictionary_coded = false;
664
0
            break;
665
0
        }
666
0
    }
667
0
    DataTypePtr data_type_file_path {new DataTypeString};
668
0
    DataTypePtr data_type_pos {new DataTypeInt64};
669
0
    bool eof = false;
670
0
    while (!eof) {
671
0
        Block block = {dictionary_coded
672
0
                               ? ColumnWithTypeAndName {ColumnDictI32::create(
673
0
                                                                FieldType::OLAP_FIELD_TYPE_VARCHAR),
674
0
                                                        data_type_file_path, ICEBERG_FILE_PATH}
675
0
                               : ColumnWithTypeAndName {data_type_file_path, ICEBERG_FILE_PATH},
676
677
0
                       {data_type_pos, ICEBERG_ROW_POS}};
678
0
        size_t read_rows = 0;
679
0
        RETURN_IF_ERROR(parquet_delete_reader.get_next_block(&block, &read_rows, &eof));
680
681
0
        if (read_rows <= 0) {
682
0
            break;
683
0
        }
684
0
        _gen_position_delete_file_range(block, position_delete, read_rows, dictionary_coded);
685
0
    }
686
0
    return Status::OK();
687
0
};
688
689
Status IcebergOrcReader::init_reader(
690
        const std::vector<std::string>& file_col_names,
691
        std::unordered_map<std::string, uint32_t>* col_name_to_block_idx,
692
        const VExprContextSPtrs& conjuncts, const TupleDescriptor* tuple_descriptor,
693
        const RowDescriptor* row_descriptor,
694
        const std::unordered_map<std::string, int>* colname_to_slot_id,
695
        const VExprContextSPtrs* not_single_slot_filter_conjuncts,
696
1
        const std::unordered_map<int, VExprContextSPtrs>* slot_id_to_filter_conjuncts) {
697
1
    _file_format = Fileformat::ORC;
698
1
    _col_name_to_block_idx = col_name_to_block_idx;
699
1
    auto* orc_reader = static_cast<OrcReader*>(_file_format_reader.get());
700
1
    RETURN_IF_ERROR(orc_reader->get_file_type(&_data_file_type_desc));
701
1
    std::vector<std::string> data_file_col_names;
702
1
    std::vector<DataTypePtr> data_file_col_types;
703
1
    RETURN_IF_ERROR(orc_reader->get_parsed_schema(&data_file_col_names, &data_file_col_types));
704
705
1
    auto column_id_result = _create_column_ids(_data_file_type_desc, tuple_descriptor);
706
1
    auto& column_ids = column_id_result.column_ids;
707
1
    const auto& filter_column_ids = column_id_result.filter_column_ids;
708
709
1
    RETURN_IF_ERROR(init_row_filters());
710
711
1
    _all_required_col_names = file_col_names;
712
1
    if (!_params.__isset.history_schema_info || _params.history_schema_info.empty()) [[unlikely]] {
713
1
        RETURN_IF_ERROR(BuildTableInfoUtil::by_orc_name(tuple_descriptor, _data_file_type_desc,
714
1
                                                        table_info_node_ptr));
715
1
    } else {
716
0
        std::set<std::string> read_col_name_set(file_col_names.begin(), file_col_names.end());
717
718
0
        bool exist_field_id = true;
719
0
        for (size_t idx = 0; idx < _data_file_type_desc->getSubtypeCount(); idx++) {
720
0
            if (!_data_file_type_desc->getSubtype(idx)->hasAttributeKey(ICEBERG_ORC_ATTRIBUTE)) {
721
0
                exist_field_id = false;
722
0
                break;
723
0
            }
724
0
        }
725
726
0
        const auto& table_schema = _params.history_schema_info.front().root_field;
727
0
        table_info_node_ptr = std::make_shared<TableSchemaChangeHelper::StructNode>();
728
0
        if (exist_field_id) {
729
            // id -> table column name. columns that need read data file.
730
0
            std::unordered_map<int, std::shared_ptr<schema::external::TField>> id_to_table_field;
731
0
            for (const auto& table_field : table_schema.fields) {
732
0
                auto field = table_field.field_ptr;
733
0
                DCHECK(field->__isset.name);
734
0
                if (!read_col_name_set.contains(field->name)) {
735
0
                    continue;
736
0
                }
737
738
0
                id_to_table_field.emplace(field->id, field);
739
0
            }
740
741
0
            for (int idx = 0; idx < _data_file_type_desc->getSubtypeCount(); idx++) {
742
0
                const auto& data_file_field = _data_file_type_desc->getSubtype(idx);
743
0
                auto data_file_column_id =
744
0
                        std::stoi(data_file_field->getAttributeValue(ICEBERG_ORC_ATTRIBUTE));
745
0
                auto const& file_column_name = _data_file_type_desc->getFieldName(idx);
746
747
0
                if (id_to_table_field.contains(data_file_column_id)) {
748
0
                    const auto& table_field = id_to_table_field[data_file_column_id];
749
750
0
                    std::shared_ptr<TableSchemaChangeHelper::Node> field_node = nullptr;
751
0
                    RETURN_IF_ERROR(BuildTableInfoUtil::by_orc_field_id(
752
0
                            *table_field, data_file_field, ICEBERG_ORC_ATTRIBUTE, exist_field_id,
753
0
                            field_node));
754
0
                    table_info_node_ptr->add_children(table_field->name, file_column_name,
755
0
                                                      field_node);
756
757
0
                    _id_to_block_column_name.emplace(data_file_column_id, table_field->name);
758
0
                    id_to_table_field.erase(data_file_column_id);
759
0
                } else if (_equality_delete_col_ids.contains(data_file_column_id)) {
760
                    // Columns that need to be read for equality delete.
761
0
                    const static std::string EQ_DELETE_PRE = "__equality_delete_column__";
762
763
                    // Construct table column names that avoid duplication with current table schema.
764
                    // As the columns currently being read may have been deleted in the latest
765
                    // table structure or have undergone a series of schema changes...
766
0
                    std::string table_column_name = EQ_DELETE_PRE + file_column_name;
767
0
                    table_info_node_ptr->add_children(
768
0
                            table_column_name, file_column_name,
769
0
                            std::make_shared<TableSchemaChangeHelper::ConstNode>());
770
771
0
                    _id_to_block_column_name.emplace(data_file_column_id, table_column_name);
772
0
                    _expand_col_names.emplace_back(table_column_name);
773
774
0
                    auto expand_data_type = make_nullable(data_file_col_types[idx]);
775
0
                    _expand_columns.emplace_back(
776
0
                            ColumnWithTypeAndName {expand_data_type->create_column(),
777
0
                                                   expand_data_type, table_column_name});
778
779
0
                    _all_required_col_names.emplace_back(table_column_name);
780
0
                    column_ids.insert(data_file_field->getColumnId());
781
0
                }
782
0
            }
783
0
            for (const auto& [id, table_field] : id_to_table_field) {
784
0
                table_info_node_ptr->add_not_exist_children(table_field->name);
785
0
            }
786
0
        } else {
787
0
            if (!_equality_delete_col_ids.empty()) [[unlikely]] {
788
0
                return Status::InternalError(
789
0
                        "Can not read missing field id data file when have equality delete");
790
0
            }
791
0
            std::map<std::string, size_t> file_column_idx_map;
792
0
            for (int idx = 0; idx < _data_file_type_desc->getSubtypeCount(); idx++) {
793
0
                auto const& file_column_name = _data_file_type_desc->getFieldName(idx);
794
0
                file_column_idx_map.emplace(file_column_name, idx);
795
0
            }
796
797
0
            for (const auto& table_field : table_schema.fields) {
798
0
                DCHECK(table_field.__isset.field_ptr);
799
0
                DCHECK(table_field.field_ptr->__isset.name);
800
0
                const auto& table_column_name = table_field.field_ptr->name;
801
0
                if (!read_col_name_set.contains(table_column_name)) {
802
0
                    continue;
803
0
                }
804
0
                if (!table_field.field_ptr->__isset.name_mapping ||
805
0
                    table_field.field_ptr->name_mapping.size() == 0) {
806
0
                    return Status::DataQualityError(
807
0
                            "name_mapping must be set when read missing field id data file.");
808
0
                }
809
0
                auto have_mapping = false;
810
0
                for (const auto& mapped_name : table_field.field_ptr->name_mapping) {
811
0
                    if (file_column_idx_map.contains(mapped_name)) {
812
0
                        auto file_column_idx = file_column_idx_map.at(mapped_name);
813
0
                        std::shared_ptr<TableSchemaChangeHelper::Node> field_node = nullptr;
814
0
                        const auto& file_field = _data_file_type_desc->getSubtype(file_column_idx);
815
0
                        RETURN_IF_ERROR(BuildTableInfoUtil::by_orc_field_id(
816
0
                                *table_field.field_ptr, file_field, ICEBERG_ORC_ATTRIBUTE,
817
0
                                exist_field_id, field_node));
818
0
                        table_info_node_ptr->add_children(
819
0
                                table_column_name,
820
0
                                _data_file_type_desc->getFieldName(file_column_idx), field_node);
821
0
                        have_mapping = true;
822
0
                        break;
823
0
                    }
824
0
                }
825
0
                if (!have_mapping) {
826
0
                    table_info_node_ptr->add_not_exist_children(table_column_name);
827
0
                }
828
0
            }
829
0
        }
830
0
    }
831
832
1
    return orc_reader->init_reader(&_all_required_col_names, _col_name_to_block_idx, conjuncts,
833
1
                                   false, tuple_descriptor, row_descriptor,
834
1
                                   not_single_slot_filter_conjuncts, slot_id_to_filter_conjuncts,
835
1
                                   table_info_node_ptr, column_ids, filter_column_ids);
836
1
}
837
838
ColumnIdResult IcebergOrcReader::_create_column_ids(const orc::Type* orc_type,
839
7
                                                    const TupleDescriptor* tuple_descriptor) {
840
    // map top-level table column iceberg_id -> orc::Type*
841
7
    std::unordered_map<int, const orc::Type*> iceberg_id_to_orc_type_map;
842
58
    for (uint64_t i = 0; i < orc_type->getSubtypeCount(); ++i) {
843
51
        auto orc_sub_type = orc_type->getSubtype(i);
844
51
        if (!orc_sub_type) continue;
845
846
51
        if (!orc_sub_type->hasAttributeKey(ICEBERG_ORC_ATTRIBUTE)) {
847
0
            continue;
848
0
        }
849
51
        int iceberg_id = std::stoi(orc_sub_type->getAttributeValue(ICEBERG_ORC_ATTRIBUTE));
850
51
        iceberg_id_to_orc_type_map[iceberg_id] = orc_sub_type;
851
51
    }
852
853
7
    std::set<uint64_t> column_ids;
854
7
    std::set<uint64_t> filter_column_ids;
855
856
    // helper to process access paths for a given top-level orc field
857
7
    auto process_access_paths = [](const orc::Type* orc_field,
858
7
                                   const std::vector<TColumnAccessPath>& access_paths,
859
14
                                   std::set<uint64_t>& out_ids) {
860
14
        process_nested_access_paths(
861
14
                orc_field, access_paths, out_ids,
862
14
                [](const orc::Type* type) { return type->getColumnId(); },
863
14
                [](const orc::Type* type) { return type->getMaximumColumnId(); },
864
14
                IcebergOrcNestedColumnUtils::extract_nested_column_ids);
865
14
    };
866
867
15
    for (const auto* slot : tuple_descriptor->slots()) {
868
15
        auto it = iceberg_id_to_orc_type_map.find(slot->col_unique_id());
869
15
        if (it == iceberg_id_to_orc_type_map.end()) {
870
            // Column not found in file
871
0
            continue;
872
0
        }
873
15
        const orc::Type* orc_field = it->second;
874
875
        // primitive (non-nested) types
876
15
        if ((slot->col_type() != TYPE_STRUCT && slot->col_type() != TYPE_ARRAY &&
877
15
             slot->col_type() != TYPE_MAP)) {
878
7
            column_ids.insert(orc_field->getColumnId());
879
7
            if (slot->is_predicate()) {
880
0
                filter_column_ids.insert(orc_field->getColumnId());
881
0
            }
882
7
            continue;
883
7
        }
884
885
        // complex types
886
8
        const auto& all_access_paths = slot->all_access_paths();
887
8
        process_access_paths(orc_field, all_access_paths, column_ids);
888
889
8
        const auto& predicate_access_paths = slot->predicate_access_paths();
890
8
        if (!predicate_access_paths.empty()) {
891
6
            process_access_paths(orc_field, predicate_access_paths, filter_column_ids);
892
6
        }
893
8
    }
894
895
7
    return ColumnIdResult(std::move(column_ids), std::move(filter_column_ids));
896
7
}
897
898
Status IcebergOrcReader::_read_position_delete_file(const TFileRangeDesc* delete_range,
899
0
                                                    DeleteFile* position_delete) {
900
0
    OrcReader orc_delete_reader(_profile, _state, _params, *delete_range,
901
0
                                READ_DELETE_FILE_BATCH_SIZE, _state->timezone(), _io_ctx,
902
0
                                _meta_cache);
903
0
    RETURN_IF_ERROR(orc_delete_reader.init_reader(
904
0
            &delete_file_col_names,
905
0
            const_cast<std::unordered_map<std::string, uint32_t>*>(&DELETE_COL_NAME_TO_BLOCK_IDX),
906
0
            {}, false, {}, {}, nullptr, nullptr));
907
908
0
    std::unordered_map<std::string, std::tuple<std::string, const SlotDescriptor*>>
909
0
            partition_columns;
910
0
    std::unordered_map<std::string, VExprContextSPtr> missing_columns;
911
0
    RETURN_IF_ERROR(orc_delete_reader.set_fill_columns(partition_columns, missing_columns));
912
913
0
    bool eof = false;
914
0
    DataTypePtr data_type_file_path {new DataTypeString};
915
0
    DataTypePtr data_type_pos {new DataTypeInt64};
916
0
    while (!eof) {
917
0
        Block block = {{data_type_file_path, ICEBERG_FILE_PATH}, {data_type_pos, ICEBERG_ROW_POS}};
918
919
0
        size_t read_rows = 0;
920
0
        RETURN_IF_ERROR(orc_delete_reader.get_next_block(&block, &read_rows, &eof));
921
922
0
        _gen_position_delete_file_range(block, position_delete, read_rows, false);
923
0
    }
924
0
    return Status::OK();
925
0
}
926
927
// Directly read the deletion vector using the `content_offset` and
928
// `content_size_in_bytes` provided by FE in `delete_file_desc`.
929
// These two fields indicate the location of a blob in storage.
930
// Since the current format is `deletion-vector-v1`, which does not
931
// compress any blobs, we can temporarily skip parsing the Puffin footer.
932
Status IcebergTableReader::read_deletion_vector(const std::string& data_file_path,
933
0
                                                const TIcebergDeleteFileDesc& delete_file_desc) {
934
0
    Status create_status = Status::OK();
935
0
    SCOPED_TIMER(_iceberg_profile.delete_files_read_time);
936
0
    _iceberg_delete_rows = _kv_cache->get<DeleteRows>(data_file_path, [&]() -> DeleteRows* {
937
0
        auto* delete_rows = new DeleteRows;
938
939
0
        TFileRangeDesc delete_range;
940
        // must use __set() method to make sure __isset is true
941
0
        delete_range.__set_fs_name(_range.fs_name);
942
0
        delete_range.path = delete_file_desc.path;
943
0
        delete_range.start_offset = delete_file_desc.content_offset;
944
0
        delete_range.size = delete_file_desc.content_size_in_bytes;
945
0
        delete_range.file_size = -1;
946
947
        // We may consider caching the DeletionVectorReader when reading Puffin files,
948
        // where the underlying reader is an `InMemoryFileReader` and a single data file is
949
        // split into multiple splits. However, we need to ensure that the underlying
950
        // reader supports multi-threaded access.
951
0
        DeletionVectorReader dv_reader(_state, _profile, _params, delete_range, _io_ctx);
952
0
        create_status = dv_reader.open();
953
0
        if (!create_status.ok()) [[unlikely]] {
954
0
            return nullptr;
955
0
        }
956
957
0
        size_t buffer_size = delete_range.size;
958
0
        std::vector<char> buf(buffer_size);
959
0
        if (buffer_size < 12) [[unlikely]] {
960
            // Minimum size: 4 bytes length + 4 bytes magic + 4 bytes CRC32
961
0
            create_status = Status::DataQualityError("Deletion vector file size too small: {}",
962
0
                                                     buffer_size);
963
0
            return nullptr;
964
0
        }
965
966
0
        create_status = dv_reader.read_at(delete_range.start_offset, {buf.data(), buffer_size});
967
0
        if (!create_status) [[unlikely]] {
968
0
            return nullptr;
969
0
        }
970
        // The serialized blob contains:
971
        //
972
        // Combined length of the vector and magic bytes stored as 4 bytes, big-endian
973
        // A 4-byte magic sequence, D1 D3 39 64
974
        // The vector, serialized as described below
975
        // A CRC-32 checksum of the magic bytes and serialized vector as 4 bytes, big-endian
976
977
0
        auto total_length = BigEndian::Load32(buf.data());
978
0
        if (total_length + 8 != buffer_size) [[unlikely]] {
979
0
            create_status = Status::DataQualityError(
980
0
                    "Deletion vector length mismatch, expected: {}, actual: {}", total_length + 8,
981
0
                    buffer_size);
982
0
            return nullptr;
983
0
        }
984
985
0
        constexpr static char MAGIC_NUMBER[] = {'\xD1', '\xD3', '\x39', '\x64'};
986
0
        if (memcmp(buf.data() + sizeof(total_length), MAGIC_NUMBER, 4)) [[unlikely]] {
987
0
            create_status = Status::DataQualityError("Deletion vector magic number mismatch");
988
0
            return nullptr;
989
0
        }
990
991
0
        roaring::Roaring64Map bitmap;
992
0
        SCOPED_TIMER(_iceberg_profile.parse_delete_file_time);
993
0
        try {
994
0
            bitmap = roaring::Roaring64Map::readSafe(buf.data() + 8, buffer_size - 12);
995
0
        } catch (const std::runtime_error& e) {
996
0
            create_status = Status::DataQualityError("Decode roaring bitmap failed, {}", e.what());
997
0
            return nullptr;
998
0
        }
999
        // skip CRC-32 checksum
1000
1001
0
        delete_rows->reserve(bitmap.cardinality());
1002
0
        for (auto it = bitmap.begin(); it != bitmap.end(); it++) {
1003
0
            delete_rows->push_back(*it);
1004
0
        }
1005
0
        COUNTER_UPDATE(_iceberg_profile.num_delete_rows, delete_rows->size());
1006
0
        return delete_rows;
1007
0
    });
1008
1009
0
    RETURN_IF_ERROR(create_status);
1010
0
    if (!_iceberg_delete_rows->empty()) [[likely]] {
1011
0
        set_delete_rows();
1012
0
    }
1013
0
    return Status::OK();
1014
0
}
1015
1016
// Similar to the code structure of IcebergOrcReader::_process_equality_delete,
1017
// but considering the significant differences in how parquet/orc obtains
1018
// attributes/column IDs, it is not easy to combine them.
1019
Status IcebergParquetReader::_process_equality_delete(
1020
0
        const std::vector<TIcebergDeleteFileDesc>& delete_files) {
1021
0
    std::unordered_map<std::string, std::tuple<std::string, const SlotDescriptor*>>
1022
0
            partition_columns;
1023
0
    std::unordered_map<std::string, VExprContextSPtr> missing_columns;
1024
1025
0
    std::map<int, const FieldSchema*> data_file_id_to_field_schema;
1026
0
    for (int idx = 0; idx < _data_file_field_desc->size(); ++idx) {
1027
0
        auto field_schema = _data_file_field_desc->get_column(idx);
1028
0
        if (_data_file_field_desc->get_column(idx)->field_id == -1) {
1029
0
            return Status::DataQualityError("Iceberg equality delete data file missing field id.");
1030
0
        }
1031
0
        data_file_id_to_field_schema[_data_file_field_desc->get_column(idx)->field_id] =
1032
0
                field_schema;
1033
0
    }
1034
1035
0
    for (const auto& delete_file : delete_files) {
1036
0
        TFileRangeDesc delete_desc;
1037
        // must use __set() method to make sure __isset is true
1038
0
        delete_desc.__set_fs_name(_range.fs_name);
1039
0
        delete_desc.path = delete_file.path;
1040
0
        delete_desc.start_offset = 0;
1041
0
        delete_desc.size = -1;
1042
0
        delete_desc.file_size = -1;
1043
1044
0
        if (!delete_file.__isset.field_ids) [[unlikely]] {
1045
0
            return Status::InternalError(
1046
0
                    "missing delete field ids when reading equality delete file");
1047
0
        }
1048
0
        auto& read_column_field_ids = delete_file.field_ids;
1049
0
        std::set<int> read_column_field_ids_set;
1050
0
        for (const auto& field_id : read_column_field_ids) {
1051
0
            read_column_field_ids_set.insert(field_id);
1052
0
            _equality_delete_col_ids.insert(field_id);
1053
0
        }
1054
1055
0
        auto delete_reader = ParquetReader::create_unique(
1056
0
                _profile, _params, delete_desc, READ_DELETE_FILE_BATCH_SIZE,
1057
0
                &_state->timezone_obj(), _io_ctx, _state, _meta_cache);
1058
0
        RETURN_IF_ERROR(delete_reader->init_schema_reader());
1059
1060
        // the column that to read equality delete file.
1061
        // (delete file may be have extra columns that don't need to read)
1062
0
        std::vector<std::string> delete_col_names;
1063
0
        std::vector<DataTypePtr> delete_col_types;
1064
0
        std::vector<int> delete_col_ids;
1065
0
        std::unordered_map<std::string, uint32_t> delete_col_name_to_block_idx;
1066
1067
0
        const FieldDescriptor* delete_field_desc = nullptr;
1068
0
        RETURN_IF_ERROR(delete_reader->get_file_metadata_schema(&delete_field_desc));
1069
0
        DCHECK(delete_field_desc != nullptr);
1070
1071
0
        auto eq_file_node = std::make_shared<TableSchemaChangeHelper::StructNode>();
1072
0
        for (const auto& delete_file_field : delete_field_desc->get_fields_schema()) {
1073
0
            if (delete_file_field.field_id == -1) [[unlikely]] { // missing delete_file_field id
1074
                // equality delete file must have delete_file_field id to match column.
1075
0
                return Status::DataQualityError(
1076
0
                        "missing delete_file_field id when reading equality delete file");
1077
0
            } else if (read_column_field_ids_set.contains(delete_file_field.field_id)) {
1078
                // the column that need to read.
1079
0
                if (delete_file_field.children.size() > 0) [[unlikely]] { // complex column
1080
0
                    return Status::InternalError(
1081
0
                            "can not support read complex column in equality delete file");
1082
0
                } else if (!data_file_id_to_field_schema.contains(delete_file_field.field_id))
1083
0
                        [[unlikely]] {
1084
0
                    return Status::DataQualityError(
1085
0
                            "can not find delete field id in data file schema when reading "
1086
0
                            "equality delete file");
1087
0
                }
1088
0
                auto data_file_field = data_file_id_to_field_schema[delete_file_field.field_id];
1089
0
                if (data_file_field->data_type->get_primitive_type() !=
1090
0
                    delete_file_field.data_type->get_primitive_type()) [[unlikely]] {
1091
0
                    return Status::NotSupported(
1092
0
                            "Not Support type change in equality delete, field: {}, delete "
1093
0
                            "file type: {}, data file type: {}",
1094
0
                            delete_file_field.field_id, delete_file_field.data_type->get_name(),
1095
0
                            data_file_field->data_type->get_name());
1096
0
                }
1097
1098
0
                std::string filed_lower_name = to_lower(delete_file_field.name);
1099
0
                eq_file_node->add_children(filed_lower_name, delete_file_field.name,
1100
0
                                           std::make_shared<TableSchemaChangeHelper::ScalarNode>());
1101
1102
0
                delete_col_ids.emplace_back(delete_file_field.field_id);
1103
0
                delete_col_names.emplace_back(filed_lower_name);
1104
0
                delete_col_types.emplace_back(make_nullable(delete_file_field.data_type));
1105
1106
0
                read_column_field_ids_set.erase(delete_file_field.field_id);
1107
0
            } else {
1108
                // delete file may be have extra columns that don't need to read
1109
0
            }
1110
0
        }
1111
0
        if (!read_column_field_ids_set.empty()) [[unlikely]] {
1112
0
            return Status::DataQualityError("some field ids not found in equality delete file.");
1113
0
        }
1114
1115
0
        for (uint32_t idx = 0; idx < delete_col_names.size(); ++idx) {
1116
0
            delete_col_name_to_block_idx[delete_col_names[idx]] = idx;
1117
0
        }
1118
0
        phmap::flat_hash_map<int, std::vector<std::shared_ptr<ColumnPredicate>>> tmp;
1119
0
        RETURN_IF_ERROR(delete_reader->init_reader(delete_col_names, &delete_col_name_to_block_idx,
1120
0
                                                   {}, tmp, nullptr, nullptr, nullptr, nullptr,
1121
0
                                                   nullptr, eq_file_node, false));
1122
0
        RETURN_IF_ERROR(delete_reader->set_fill_columns(partition_columns, missing_columns));
1123
1124
0
        if (!_equality_delete_block_map.contains(delete_col_ids)) {
1125
0
            _equality_delete_block_map.emplace(delete_col_ids, _equality_delete_blocks.size());
1126
0
            Block block;
1127
0
            _generate_equality_delete_block(&block, delete_col_names, delete_col_types);
1128
0
            _equality_delete_blocks.emplace_back(block);
1129
0
        }
1130
0
        Block& eq_file_block = _equality_delete_blocks[_equality_delete_block_map[delete_col_ids]];
1131
0
        bool eof = false;
1132
0
        while (!eof) {
1133
0
            Block tmp_block;
1134
0
            _generate_equality_delete_block(&tmp_block, delete_col_names, delete_col_types);
1135
0
            size_t read_rows = 0;
1136
0
            RETURN_IF_ERROR(delete_reader->get_next_block(&tmp_block, &read_rows, &eof));
1137
0
            if (read_rows > 0) {
1138
0
                MutableBlock mutable_block(&eq_file_block);
1139
0
                RETURN_IF_ERROR(mutable_block.merge(tmp_block));
1140
0
            }
1141
0
        }
1142
0
    }
1143
1144
0
    for (const auto& [delete_col_ids, block_idx] : _equality_delete_block_map) {
1145
0
        auto& eq_file_block = _equality_delete_blocks[block_idx];
1146
0
        auto equality_delete_impl =
1147
0
                EqualityDeleteBase::get_delete_impl(&eq_file_block, delete_col_ids);
1148
0
        RETURN_IF_ERROR(equality_delete_impl->init(_profile));
1149
0
        _equality_delete_impls.emplace_back(std::move(equality_delete_impl));
1150
0
    }
1151
0
    return Status::OK();
1152
0
}
1153
1154
Status IcebergOrcReader::_process_equality_delete(
1155
0
        const std::vector<TIcebergDeleteFileDesc>& delete_files) {
1156
0
    std::unordered_map<std::string, std::tuple<std::string, const SlotDescriptor*>>
1157
0
            partition_columns;
1158
0
    std::unordered_map<std::string, VExprContextSPtr> missing_columns;
1159
1160
0
    std::map<int, int> data_file_id_to_field_idx;
1161
0
    for (int idx = 0; idx < _data_file_type_desc->getSubtypeCount(); ++idx) {
1162
0
        if (!_data_file_type_desc->getSubtype(idx)->hasAttributeKey(ICEBERG_ORC_ATTRIBUTE)) {
1163
0
            return Status::DataQualityError("Iceberg equality delete data file missing field id.");
1164
0
        }
1165
0
        auto field_id = std::stoi(
1166
0
                _data_file_type_desc->getSubtype(idx)->getAttributeValue(ICEBERG_ORC_ATTRIBUTE));
1167
0
        data_file_id_to_field_idx[field_id] = idx;
1168
0
    }
1169
1170
0
    for (const auto& delete_file : delete_files) {
1171
0
        TFileRangeDesc delete_desc;
1172
        // must use __set() method to make sure __isset is true
1173
0
        delete_desc.__set_fs_name(_range.fs_name);
1174
0
        delete_desc.path = delete_file.path;
1175
0
        delete_desc.start_offset = 0;
1176
0
        delete_desc.size = -1;
1177
0
        delete_desc.file_size = -1;
1178
1179
0
        if (!delete_file.__isset.field_ids) [[unlikely]] {
1180
0
            return Status::InternalError(
1181
0
                    "missing delete field ids when reading equality delete file");
1182
0
        }
1183
0
        auto& read_column_field_ids = delete_file.field_ids;
1184
0
        std::set<int> read_column_field_ids_set;
1185
0
        for (const auto& field_id : read_column_field_ids) {
1186
0
            read_column_field_ids_set.insert(field_id);
1187
0
            _equality_delete_col_ids.insert(field_id);
1188
0
        }
1189
1190
0
        auto delete_reader = OrcReader::create_unique(_profile, _state, _params, delete_desc,
1191
0
                                                      READ_DELETE_FILE_BATCH_SIZE,
1192
0
                                                      _state->timezone(), _io_ctx, _meta_cache);
1193
0
        RETURN_IF_ERROR(delete_reader->init_schema_reader());
1194
        // delete file schema
1195
0
        std::vector<std::string> delete_file_col_names;
1196
0
        std::vector<DataTypePtr> delete_file_col_types;
1197
0
        RETURN_IF_ERROR(
1198
0
                delete_reader->get_parsed_schema(&delete_file_col_names, &delete_file_col_types));
1199
1200
        // the column that to read equality delete file.
1201
        // (delete file maybe have extra columns that don't need to read)
1202
0
        std::vector<std::string> delete_col_names;
1203
0
        std::vector<DataTypePtr> delete_col_types;
1204
0
        std::vector<int> delete_col_ids;
1205
0
        std::unordered_map<std::string, uint32_t> delete_col_name_to_block_idx;
1206
1207
0
        const orc::Type* delete_field_desc = nullptr;
1208
0
        RETURN_IF_ERROR(delete_reader->get_file_type(&delete_field_desc));
1209
0
        DCHECK(delete_field_desc != nullptr);
1210
1211
0
        auto eq_file_node = std::make_shared<TableSchemaChangeHelper::StructNode>();
1212
1213
0
        for (size_t idx = 0; idx < delete_field_desc->getSubtypeCount(); idx++) {
1214
0
            auto delete_file_field = delete_field_desc->getSubtype(idx);
1215
1216
0
            if (!delete_file_field->hasAttributeKey(ICEBERG_ORC_ATTRIBUTE))
1217
0
                    [[unlikely]] { // missing delete_file_field id
1218
                // equality delete file must have delete_file_field id to match column.
1219
0
                return Status::DataQualityError(
1220
0
                        "missing delete_file_field id when reading equality delete file");
1221
0
            } else {
1222
0
                auto delete_field_id =
1223
0
                        std::stoi(delete_file_field->getAttributeValue(ICEBERG_ORC_ATTRIBUTE));
1224
0
                if (read_column_field_ids_set.contains(delete_field_id)) {
1225
                    // the column that need to read.
1226
0
                    if (is_complex_type(delete_file_col_types[idx]->get_primitive_type()))
1227
0
                            [[unlikely]] {
1228
0
                        return Status::InternalError(
1229
0
                                "can not support read complex column in equality delete file.");
1230
0
                    } else if (!data_file_id_to_field_idx.contains(delete_field_id)) [[unlikely]] {
1231
0
                        return Status::DataQualityError(
1232
0
                                "can not find delete field id in data file schema when reading "
1233
0
                                "equality delete file");
1234
0
                    }
1235
1236
0
                    auto data_file_field = _data_file_type_desc->getSubtype(
1237
0
                            data_file_id_to_field_idx[delete_field_id]);
1238
1239
0
                    if (delete_file_field->getKind() != data_file_field->getKind()) [[unlikely]] {
1240
0
                        return Status::NotSupported(
1241
0
                                "Not Support type change in equality delete, field: {}, delete "
1242
0
                                "file type: {}, data file type: {}",
1243
0
                                delete_field_id, delete_file_field->getKind(),
1244
0
                                data_file_field->getKind());
1245
0
                    }
1246
0
                    std::string filed_lower_name = to_lower(delete_field_desc->getFieldName(idx));
1247
0
                    eq_file_node->add_children(
1248
0
                            filed_lower_name, delete_field_desc->getFieldName(idx),
1249
0
                            std::make_shared<TableSchemaChangeHelper::ScalarNode>());
1250
1251
0
                    delete_col_ids.emplace_back(delete_field_id);
1252
0
                    delete_col_names.emplace_back(filed_lower_name);
1253
0
                    delete_col_types.emplace_back(make_nullable(delete_file_col_types[idx]));
1254
0
                    read_column_field_ids_set.erase(delete_field_id);
1255
0
                }
1256
0
            }
1257
0
        }
1258
0
        if (!read_column_field_ids_set.empty()) [[unlikely]] {
1259
0
            return Status::DataQualityError("some field ids not found in equality delete file.");
1260
0
        }
1261
1262
0
        for (uint32_t idx = 0; idx < delete_col_names.size(); ++idx) {
1263
0
            delete_col_name_to_block_idx[delete_col_names[idx]] = idx;
1264
0
        }
1265
1266
0
        RETURN_IF_ERROR(delete_reader->init_reader(&delete_col_names, &delete_col_name_to_block_idx,
1267
0
                                                   {}, false, nullptr, nullptr, nullptr, nullptr,
1268
0
                                                   eq_file_node));
1269
0
        RETURN_IF_ERROR(delete_reader->set_fill_columns(partition_columns, missing_columns));
1270
1271
0
        if (!_equality_delete_block_map.contains(delete_col_ids)) {
1272
0
            _equality_delete_block_map.emplace(delete_col_ids, _equality_delete_blocks.size());
1273
0
            Block block;
1274
0
            _generate_equality_delete_block(&block, delete_col_names, delete_col_types);
1275
0
            _equality_delete_blocks.emplace_back(block);
1276
0
        }
1277
0
        Block& eq_file_block = _equality_delete_blocks[_equality_delete_block_map[delete_col_ids]];
1278
0
        bool eof = false;
1279
0
        while (!eof) {
1280
0
            Block tmp_block;
1281
0
            _generate_equality_delete_block(&tmp_block, delete_col_names, delete_col_types);
1282
0
            size_t read_rows = 0;
1283
0
            RETURN_IF_ERROR(delete_reader->get_next_block(&tmp_block, &read_rows, &eof));
1284
0
            if (read_rows > 0) {
1285
0
                MutableBlock mutable_block(&eq_file_block);
1286
0
                RETURN_IF_ERROR(mutable_block.merge(tmp_block));
1287
0
            }
1288
0
        }
1289
0
    }
1290
1291
0
    for (const auto& [delete_col_ids, block_idx] : _equality_delete_block_map) {
1292
0
        auto& eq_file_block = _equality_delete_blocks[block_idx];
1293
0
        auto equality_delete_impl =
1294
0
                EqualityDeleteBase::get_delete_impl(&eq_file_block, delete_col_ids);
1295
0
        RETURN_IF_ERROR(equality_delete_impl->init(_profile));
1296
0
        _equality_delete_impls.emplace_back(std::move(equality_delete_impl));
1297
0
    }
1298
0
    return Status::OK();
1299
0
}
1300
#include "common/compile_check_end.h"
1301
} // namespace doris