Coverage Report

Created: 2026-07-09 14:11

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/format/table/iceberg_reader.cpp
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Count
Source
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// Licensed to the Apache Software Foundation (ASF) under one
2
// or more contributor license agreements.  See the NOTICE file
3
// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
5
// to you under the Apache License, Version 2.0 (the
6
// "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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//
9
//   http://www.apache.org/licenses/LICENSE-2.0
10
//
11
// Unless required by applicable law or agreed to in writing,
12
// software distributed under the License is distributed on an
13
// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
14
// 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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18
#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
33
#include "common/compiler_util.h" // IWYU pragma: keep
34
#include "common/consts.h"
35
#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_nullable.h"
41
#include "core/column/column_string.h"
42
#include "core/column/column_vector.h"
43
#include "core/data_type/data_type_factory.hpp"
44
#include "core/data_type/data_type_nullable.h"
45
#include "core/data_type/define_primitive_type.h"
46
#include "core/data_type/primitive_type.h"
47
#include "core/string_ref.h"
48
#include "exprs/aggregate/aggregate_function.h"
49
#include "format/format_common.h"
50
#include "format/generic_reader.h"
51
#include "format/orc/vorc_reader.h"
52
#include "format/parquet/schema_desc.h"
53
#include "format/parquet/vparquet_column_chunk_reader.h"
54
#include "format/table/deletion_vector_reader.h"
55
#include "format/table/iceberg/iceberg_orc_nested_column_utils.h"
56
#include "format/table/iceberg/iceberg_parquet_nested_column_utils.h"
57
#include "format/table/nested_column_access_helper.h"
58
#include "format/table/table_schema_change_helper.h"
59
#include "runtime/runtime_state.h"
60
#include "util/coding.h"
61
62
namespace cctz {
63
class time_zone;
64
} // namespace cctz
65
namespace doris {
66
class RowDescriptor;
67
class SlotDescriptor;
68
class TupleDescriptor;
69
70
namespace io {
71
struct IOContext;
72
} // namespace io
73
class VExprContext;
74
} // namespace doris
75
76
namespace doris {
77
const std::string IcebergOrcReader::ICEBERG_ORC_ATTRIBUTE = "iceberg.id";
78
79
bool IcebergTableReader::_is_fully_dictionary_encoded(
80
8
        const tparquet::ColumnMetaData& column_metadata) {
81
14
    const auto is_dictionary_encoding = [](tparquet::Encoding::type encoding) {
82
14
        return encoding == tparquet::Encoding::PLAIN_DICTIONARY ||
83
14
               encoding == tparquet::Encoding::RLE_DICTIONARY;
84
14
    };
85
12
    const auto is_data_page = [](tparquet::PageType::type page_type) {
86
12
        return page_type == tparquet::PageType::DATA_PAGE ||
87
12
               page_type == tparquet::PageType::DATA_PAGE_V2;
88
12
    };
89
8
    const auto is_level_encoding = [](tparquet::Encoding::type encoding) {
90
2
        return encoding == tparquet::Encoding::RLE || encoding == tparquet::Encoding::BIT_PACKED;
91
2
    };
92
93
    // A column chunk may have a dictionary page but still contain plain-encoded data pages.
94
    // Only treat it as dictionary-coded when all data pages are dictionary encoded.
95
8
    if (column_metadata.__isset.encoding_stats) {
96
7
        bool has_data_page_stats = false;
97
12
        for (const tparquet::PageEncodingStats& enc_stat : column_metadata.encoding_stats) {
98
12
            if (is_data_page(enc_stat.page_type) && enc_stat.count > 0) {
99
8
                has_data_page_stats = true;
100
8
                if (!is_dictionary_encoding(enc_stat.encoding)) {
101
2
                    return false;
102
2
                }
103
8
            }
104
12
        }
105
5
        if (has_data_page_stats) {
106
4
            return true;
107
4
        }
108
5
    }
109
110
2
    bool has_dict_encoding = false;
111
2
    bool has_nondict_encoding = false;
112
3
    for (const tparquet::Encoding::type& encoding : column_metadata.encodings) {
113
3
        if (is_dictionary_encoding(encoding)) {
114
1
            has_dict_encoding = true;
115
1
        }
116
117
3
        if (!is_dictionary_encoding(encoding) && !is_level_encoding(encoding)) {
118
2
            has_nondict_encoding = true;
119
2
            break;
120
2
        }
121
3
    }
122
2
    if (!has_dict_encoding || has_nondict_encoding) {
123
2
        return false;
124
2
    }
125
126
0
    return true;
127
2
}
128
129
// ============================================================================
130
// IcebergParquetReader: on_before_init_reader (Parquet-specific schema matching)
131
// ============================================================================
132
1
Status IcebergParquetReader::on_before_init_reader(ReaderInitContext* ctx) {
133
1
    _column_descs = ctx->column_descs;
134
1
    _fill_col_name_to_block_idx = ctx->col_name_to_block_idx;
135
1
    _file_format = Fileformat::PARQUET;
136
137
    // Get file metadata schema first (available because _open_file() already ran)
138
1
    const FieldDescriptor* field_desc = nullptr;
139
1
    RETURN_IF_ERROR(this->get_file_metadata_schema(&field_desc));
140
1
    DCHECK(field_desc != nullptr);
141
142
    // Build table_info_node by field_id or name matching.
143
    // This must happen BEFORE column classification so we can use children_column_exists
144
    // to check if a column exists in the file (by field ID, not name).
145
1
    if (!get_scan_params().__isset.history_schema_info ||
146
1
        get_scan_params().history_schema_info.empty()) [[unlikely]] {
147
1
        RETURN_IF_ERROR(BuildTableInfoUtil::by_parquet_name(ctx->tuple_descriptor, *field_desc,
148
1
                                                            ctx->table_info_node));
149
1
    } else {
150
0
        RETURN_IF_ERROR(BuildTableInfoUtil::by_parquet_field_id_with_name_mapping(
151
0
                get_scan_params().history_schema_info.front().root_field, *field_desc,
152
0
                ctx->table_info_node));
153
0
    }
154
155
1
    std::unordered_set<std::string> partition_col_names;
156
1
    if (ctx->range->__isset.columns_from_path_keys) {
157
0
        partition_col_names.insert(ctx->range->columns_from_path_keys.begin(),
158
0
                                   ctx->range->columns_from_path_keys.end());
159
0
    }
160
161
    // Single pass: classify columns, detect $row_id, handle partition fallback.
162
1
    bool has_partition_from_path = false;
163
2
    for (const auto& desc : *ctx->column_descs) {
164
2
        if (desc.category == ColumnCategory::SYNTHESIZED) {
165
0
            if (desc.name == BeConsts::ICEBERG_ROWID_COL) {
166
0
                this->register_synthesized_column_handler(
167
0
                        BeConsts::ICEBERG_ROWID_COL, [this](Block* block, size_t rows) -> Status {
168
0
                            return _fill_iceberg_row_id(block, rows);
169
0
                        });
170
0
                continue;
171
0
            } else if (desc.name.starts_with(BeConsts::GLOBAL_ROWID_COL)) {
172
0
                auto topn_row_id_column_iter = _create_topn_row_id_column_iterator();
173
0
                this->register_synthesized_column_handler(
174
0
                        desc.name,
175
0
                        [iter = std::move(topn_row_id_column_iter), this, &desc](
176
0
                                Block* block, size_t rows) -> Status {
177
0
                            return fill_topn_row_id(iter, desc.name, block, rows);
178
0
                        });
179
0
                continue;
180
0
            }
181
2
        } else if (desc.category == ColumnCategory::PARTITION_KEY) {
182
0
            bool has_partition_value = partition_col_names.contains(desc.name);
183
0
            bool exists_in_file = ctx->table_info_node->children_column_exists(desc.name);
184
0
            if (!has_partition_value || exists_in_file) {
185
                // Keep PARTITION_KEY category stable for scan planning, but still read
186
                // from file when the column exists there.
187
0
                ctx->column_names.push_back(desc.name);
188
0
                continue;
189
0
            }
190
0
            has_partition_from_path = true;
191
2
        } else if (desc.category == ColumnCategory::REGULAR) {
192
2
            ctx->column_names.push_back(desc.name);
193
2
        } else if (desc.category == ColumnCategory::GENERATED) {
194
0
            _init_row_lineage_columns();
195
0
            if (desc.name == ROW_LINEAGE_ROW_ID) {
196
0
                ctx->column_names.push_back(desc.name);
197
0
                this->register_generated_column_handler(
198
0
                        ROW_LINEAGE_ROW_ID, [this](Block* block, size_t rows) -> Status {
199
0
                            return _fill_row_lineage_row_id(block, rows);
200
0
                        });
201
0
                continue;
202
0
            } else if (desc.name == ROW_LINEAGE_LAST_UPDATED_SEQ_NUMBER) {
203
0
                ctx->column_names.push_back(desc.name);
204
0
                this->register_generated_column_handler(
205
0
                        ROW_LINEAGE_LAST_UPDATED_SEQ_NUMBER,
206
0
                        [this](Block* block, size_t rows) -> Status {
207
0
                            return _fill_row_lineage_last_updated_sequence_number(block, rows);
208
0
                        });
209
0
                continue;
210
0
            }
211
0
        }
212
2
    }
213
214
    // Set up partition value extraction if any partition columns need filling from path
215
1
    if (has_partition_from_path) {
216
0
        RETURN_IF_ERROR(_extract_partition_values(*ctx->range, ctx->tuple_descriptor,
217
0
                                                  _fill_partition_values,
218
0
                                                  &_fill_partition_value_is_null));
219
0
    }
220
221
1
    _all_required_col_names = ctx->column_names;
222
223
    // Create column IDs from field descriptor
224
1
    auto column_id_result = _create_column_ids(field_desc, ctx->tuple_descriptor);
225
1
    ctx->column_ids = std::move(column_id_result.column_ids);
226
1
    ctx->filter_column_ids = std::move(column_id_result.filter_column_ids);
227
228
    // Build field_id -> block_column_name mapping for equality delete filtering.
229
    // This was previously done in init_reader() column matching (pre-CRTP refactoring).
230
2
    for (const auto* slot : ctx->tuple_descriptor->slots()) {
231
2
        _id_to_block_column_name.emplace(slot->col_unique_id(), slot->col_name());
232
2
    }
233
234
    // Process delete files (must happen before _do_init_reader so expand col IDs are included)
235
1
    RETURN_IF_ERROR(_init_row_filters());
236
237
    // Add expand column IDs for equality delete and remap expand column names
238
    // to match master's behavior:
239
    // - Use field_id to find the actual file column name in Parquet schema
240
    // - Prefix with __equality_delete_column__ to avoid name conflicts
241
    // - Correctly map table_col_name → file_col_name in table_info_node
242
1
    const static std::string EQ_DELETE_PRE = "__equality_delete_column__";
243
1
    std::unordered_map<int, std::string> field_id_to_file_col_name;
244
4
    for (int i = 0; i < field_desc->size(); ++i) {
245
3
        auto field_schema = field_desc->get_column(i);
246
3
        if (field_schema) {
247
3
            field_id_to_file_col_name[field_schema->field_id] = field_schema->name;
248
3
        }
249
3
    }
250
251
    // Rebuild _expand_col_names with proper file-column-based names
252
1
    std::vector<std::string> new_expand_col_names;
253
1
    for (size_t i = 0; i < _expand_col_names.size(); ++i) {
254
0
        const auto& old_name = _expand_col_names[i];
255
        // Find the field_id for this expand column
256
0
        int field_id = -1;
257
0
        for (auto& [fid, name] : _id_to_block_column_name) {
258
0
            if (name == old_name) {
259
0
                field_id = fid;
260
0
                break;
261
0
            }
262
0
        }
263
264
0
        std::string file_col_name = old_name;
265
0
        auto it = field_id_to_file_col_name.find(field_id);
266
0
        if (it != field_id_to_file_col_name.end()) {
267
0
            file_col_name = it->second;
268
0
        }
269
270
0
        std::string table_col_name = EQ_DELETE_PRE + file_col_name;
271
272
        // Update _id_to_block_column_name
273
0
        if (field_id >= 0) {
274
0
            _id_to_block_column_name[field_id] = table_col_name;
275
0
        }
276
277
        // Update _expand_columns name
278
0
        if (i < _expand_columns.size()) {
279
0
            _expand_columns[i].name = table_col_name;
280
0
        }
281
282
0
        new_expand_col_names.push_back(table_col_name);
283
284
        // Add column IDs
285
0
        if (it != field_id_to_file_col_name.end()) {
286
0
            for (int j = 0; j < field_desc->size(); ++j) {
287
0
                auto field_schema = field_desc->get_column(j);
288
0
                if (field_schema && field_schema->field_id == field_id) {
289
0
                    ctx->column_ids.insert(field_schema->get_column_id());
290
0
                    break;
291
0
                }
292
0
            }
293
0
        }
294
295
        // Register in table_info_node: table_col_name → file_col_name
296
0
        ctx->column_names.push_back(table_col_name);
297
0
        ctx->table_info_node->add_children(table_col_name, file_col_name,
298
0
                                           TableSchemaChangeHelper::ConstNode::get_instance());
299
0
    }
300
1
    _expand_col_names = std::move(new_expand_col_names);
301
302
    // Enable group filtering for Iceberg
303
1
    _filter_groups = true;
304
305
1
    return Status::OK();
306
1
}
307
308
// ============================================================================
309
// IcebergParquetReader: _create_column_ids
310
// ============================================================================
311
ColumnIdResult IcebergParquetReader::_create_column_ids(const FieldDescriptor* field_desc,
312
7
                                                        const TupleDescriptor* tuple_descriptor) {
313
7
    auto* mutable_field_desc = const_cast<FieldDescriptor*>(field_desc);
314
7
    mutable_field_desc->assign_ids();
315
316
7
    std::unordered_map<int, const FieldSchema*> iceberg_id_to_field_schema_map;
317
58
    for (int i = 0; i < field_desc->size(); ++i) {
318
51
        auto field_schema = field_desc->get_column(i);
319
51
        if (!field_schema) continue;
320
51
        int iceberg_id = field_schema->field_id;
321
51
        iceberg_id_to_field_schema_map[iceberg_id] = field_schema;
322
51
    }
323
324
7
    std::set<uint64_t> column_ids;
325
7
    std::set<uint64_t> filter_column_ids;
326
327
7
    auto process_access_paths = [](const FieldSchema* parquet_field,
328
7
                                   const std::vector<TColumnAccessPath>& access_paths,
329
14
                                   std::set<uint64_t>& out_ids) {
330
14
        process_nested_access_paths(
331
14
                parquet_field, access_paths, out_ids,
332
14
                [](const FieldSchema* field) { return field->get_column_id(); },
333
14
                [](const FieldSchema* field) { return field->get_max_column_id(); },
334
14
                IcebergParquetNestedColumnUtils::extract_nested_column_ids);
335
14
    };
336
337
15
    for (const auto* slot : tuple_descriptor->slots()) {
338
15
        auto it = iceberg_id_to_field_schema_map.find(slot->col_unique_id());
339
15
        if (it == iceberg_id_to_field_schema_map.end()) {
340
0
            continue;
341
0
        }
342
15
        auto field_schema = it->second;
343
344
15
        if ((slot->col_type() != TYPE_STRUCT && slot->col_type() != TYPE_ARRAY &&
345
15
             slot->col_type() != TYPE_MAP)) {
346
7
            column_ids.insert(field_schema->column_id);
347
7
            if (slot->is_predicate()) {
348
0
                filter_column_ids.insert(field_schema->column_id);
349
0
            }
350
7
            continue;
351
7
        }
352
353
8
        const auto& all_access_paths = slot->all_access_paths();
354
8
        process_access_paths(field_schema, all_access_paths, column_ids);
355
356
8
        const auto& predicate_access_paths = slot->predicate_access_paths();
357
8
        if (!predicate_access_paths.empty()) {
358
6
            process_access_paths(field_schema, predicate_access_paths, filter_column_ids);
359
6
        }
360
8
    }
361
7
    return ColumnIdResult(std::move(column_ids), std::move(filter_column_ids));
362
7
}
363
364
// ============================================================================
365
// IcebergParquetReader: _read_position_delete_file
366
// ============================================================================
367
Status IcebergParquetReader::_read_position_delete_file(const TFileRangeDesc* delete_range,
368
0
                                                        DeleteFile* position_delete) {
369
0
    ParquetReader parquet_delete_reader(get_profile(), get_scan_params(), *delete_range,
370
0
                                        READ_DELETE_FILE_BATCH_SIZE, &get_state()->timezone_obj(),
371
0
                                        get_io_ctx(), get_state(), _meta_cache);
372
    // The delete file range has size=-1 (read whole file). We must disable
373
    // row group filtering before init; otherwise _do_init_reader returns EndOfFile
374
    // when _filter_groups && _range_size < 0.
375
0
    ParquetInitContext delete_ctx;
376
0
    delete_ctx.filter_groups = false;
377
0
    delete_ctx.column_names = delete_file_col_names;
378
0
    delete_ctx.col_name_to_block_idx =
379
0
            const_cast<std::unordered_map<std::string, uint32_t>*>(&DELETE_COL_NAME_TO_BLOCK_IDX);
380
0
    RETURN_IF_ERROR(parquet_delete_reader.init_reader(&delete_ctx));
381
382
0
    const tparquet::FileMetaData* meta_data = parquet_delete_reader.get_meta_data();
383
0
    bool dictionary_coded = true;
384
0
    for (const auto& row_group : meta_data->row_groups) {
385
0
        const auto& column_chunk = row_group.columns[ICEBERG_FILE_PATH_INDEX];
386
0
        if (!(column_chunk.__isset.meta_data && has_dict_page(column_chunk.meta_data))) {
387
0
            dictionary_coded = false;
388
0
            break;
389
0
        }
390
0
    }
391
0
    DataTypePtr data_type_file_path = make_nullable(std::make_shared<DataTypeString>());
392
0
    DataTypePtr data_type_pos = make_nullable(std::make_shared<DataTypeInt64>());
393
0
    bool eof = false;
394
0
    while (!eof) {
395
0
        Block block = {
396
0
                dictionary_coded
397
0
                        ? ColumnWithTypeAndName {ColumnNullable::create(ColumnDictI32::create(),
398
0
                                                                        ColumnUInt8::create()),
399
0
                                                 data_type_file_path, ICEBERG_FILE_PATH}
400
0
                        : ColumnWithTypeAndName {data_type_file_path, ICEBERG_FILE_PATH},
401
402
0
                {data_type_pos, ICEBERG_ROW_POS}};
403
0
        size_t read_rows = 0;
404
0
        RETURN_IF_ERROR(parquet_delete_reader.get_next_block(&block, &read_rows, &eof));
405
406
0
        if (read_rows <= 0) {
407
0
            break;
408
0
        }
409
0
        RETURN_IF_ERROR(_gen_position_delete_file_range(block, position_delete, read_rows,
410
0
                                                        dictionary_coded));
411
0
    }
412
0
    return Status::OK();
413
0
};
414
415
// ============================================================================
416
// IcebergOrcReader: on_before_init_reader (ORC-specific schema matching)
417
// ============================================================================
418
1
Status IcebergOrcReader::on_before_init_reader(ReaderInitContext* ctx) {
419
1
    _column_descs = ctx->column_descs;
420
1
    _fill_col_name_to_block_idx = ctx->col_name_to_block_idx;
421
1
    _file_format = Fileformat::ORC;
422
423
    // Get ORC file type first (available because _create_file_reader() already ran)
424
1
    const orc::Type* orc_type_ptr = nullptr;
425
1
    RETURN_IF_ERROR(this->get_file_type(&orc_type_ptr));
426
427
    // Build table_info_node by field_id or name matching.
428
    // This must happen BEFORE column classification so we can use children_column_exists
429
    // to check if a column exists in the file (by field ID, not name).
430
1
    if (!get_scan_params().__isset.history_schema_info ||
431
1
        get_scan_params().history_schema_info.empty()) [[unlikely]] {
432
1
        RETURN_IF_ERROR(BuildTableInfoUtil::by_orc_name(ctx->tuple_descriptor, orc_type_ptr,
433
1
                                                        ctx->table_info_node));
434
1
    } else {
435
0
        RETURN_IF_ERROR(BuildTableInfoUtil::by_orc_field_id_with_name_mapping(
436
0
                get_scan_params().history_schema_info.front().root_field, orc_type_ptr,
437
0
                ICEBERG_ORC_ATTRIBUTE, ctx->table_info_node));
438
0
    }
439
440
1
    std::unordered_set<std::string> partition_col_names;
441
1
    if (ctx->range->__isset.columns_from_path_keys) {
442
0
        partition_col_names.insert(ctx->range->columns_from_path_keys.begin(),
443
0
                                   ctx->range->columns_from_path_keys.end());
444
0
    }
445
446
    // Single pass: classify columns, detect $row_id, handle partition fallback.
447
1
    bool has_partition_from_path = false;
448
2
    for (const auto& desc : *ctx->column_descs) {
449
2
        if (desc.category == ColumnCategory::SYNTHESIZED) {
450
0
            if (desc.name == BeConsts::ICEBERG_ROWID_COL) {
451
0
                this->register_synthesized_column_handler(
452
0
                        BeConsts::ICEBERG_ROWID_COL, [this](Block* block, size_t rows) -> Status {
453
0
                            return _fill_iceberg_row_id(block, rows);
454
0
                        });
455
0
                continue;
456
0
            } else if (desc.name.starts_with(BeConsts::GLOBAL_ROWID_COL)) {
457
0
                auto topn_row_id_column_iter = _create_topn_row_id_column_iterator();
458
0
                this->register_synthesized_column_handler(
459
0
                        desc.name,
460
0
                        [iter = std::move(topn_row_id_column_iter), this, &desc](
461
0
                                Block* block, size_t rows) -> Status {
462
0
                            return fill_topn_row_id(iter, desc.name, block, rows);
463
0
                        });
464
0
                continue;
465
0
            }
466
2
        } else if (desc.category == ColumnCategory::PARTITION_KEY) {
467
0
            bool has_partition_value = partition_col_names.contains(desc.name);
468
0
            bool exists_in_file = ctx->table_info_node->children_column_exists(desc.name);
469
0
            if (!has_partition_value || exists_in_file) {
470
0
                ctx->column_names.push_back(desc.name);
471
0
                continue;
472
0
            }
473
0
            has_partition_from_path = true;
474
2
        } else if (desc.category == ColumnCategory::REGULAR) {
475
2
            ctx->column_names.push_back(desc.name);
476
2
        } else if (desc.category == ColumnCategory::GENERATED) {
477
0
            _init_row_lineage_columns();
478
0
            if (desc.name == ROW_LINEAGE_ROW_ID) {
479
0
                ctx->column_names.push_back(desc.name);
480
0
                this->register_generated_column_handler(
481
0
                        ROW_LINEAGE_ROW_ID, [this](Block* block, size_t rows) -> Status {
482
0
                            return _fill_row_lineage_row_id(block, rows);
483
0
                        });
484
0
                continue;
485
0
            } else if (desc.name == ROW_LINEAGE_LAST_UPDATED_SEQ_NUMBER) {
486
0
                ctx->column_names.push_back(desc.name);
487
0
                this->register_generated_column_handler(
488
0
                        ROW_LINEAGE_LAST_UPDATED_SEQ_NUMBER,
489
0
                        [this](Block* block, size_t rows) -> Status {
490
0
                            return _fill_row_lineage_last_updated_sequence_number(block, rows);
491
0
                        });
492
0
                continue;
493
0
            }
494
0
        }
495
2
    }
496
497
1
    if (has_partition_from_path) {
498
0
        RETURN_IF_ERROR(_extract_partition_values(*ctx->range, ctx->tuple_descriptor,
499
0
                                                  _fill_partition_values,
500
0
                                                  &_fill_partition_value_is_null));
501
0
    }
502
503
1
    _all_required_col_names = ctx->column_names;
504
505
    // Create column IDs from ORC type
506
1
    auto column_id_result = _create_column_ids(orc_type_ptr, ctx->tuple_descriptor);
507
1
    ctx->column_ids = std::move(column_id_result.column_ids);
508
1
    ctx->filter_column_ids = std::move(column_id_result.filter_column_ids);
509
510
    // Build field_id -> block_column_name mapping for equality delete filtering.
511
2
    for (const auto* slot : ctx->tuple_descriptor->slots()) {
512
2
        _id_to_block_column_name.emplace(slot->col_unique_id(), slot->col_name());
513
2
    }
514
515
    // Process delete files (must happen before _do_init_reader so expand col IDs are included)
516
1
    RETURN_IF_ERROR(_init_row_filters());
517
518
    // Add expand column IDs for equality delete and remap expand column names
519
    // (matching master's behavior with __equality_delete_column__ prefix)
520
1
    const static std::string EQ_DELETE_PRE = "__equality_delete_column__";
521
1
    std::unordered_map<int, std::string> field_id_to_file_col_name;
522
4
    for (uint64_t i = 0; i < orc_type_ptr->getSubtypeCount(); ++i) {
523
3
        std::string col_name = orc_type_ptr->getFieldName(i);
524
3
        const orc::Type* sub_type = orc_type_ptr->getSubtype(i);
525
3
        if (sub_type->hasAttributeKey(ICEBERG_ORC_ATTRIBUTE)) {
526
3
            int fid = std::stoi(sub_type->getAttributeValue(ICEBERG_ORC_ATTRIBUTE));
527
3
            field_id_to_file_col_name[fid] = col_name;
528
3
        }
529
3
    }
530
531
1
    std::vector<std::string> new_expand_col_names;
532
1
    for (size_t i = 0; i < _expand_col_names.size(); ++i) {
533
0
        const auto& old_name = _expand_col_names[i];
534
0
        int field_id = -1;
535
0
        for (auto& [fid, name] : _id_to_block_column_name) {
536
0
            if (name == old_name) {
537
0
                field_id = fid;
538
0
                break;
539
0
            }
540
0
        }
541
542
0
        std::string file_col_name = old_name;
543
0
        auto it = field_id_to_file_col_name.find(field_id);
544
0
        if (it != field_id_to_file_col_name.end()) {
545
0
            file_col_name = it->second;
546
0
        }
547
548
0
        std::string table_col_name = EQ_DELETE_PRE + file_col_name;
549
550
0
        if (field_id >= 0) {
551
0
            _id_to_block_column_name[field_id] = table_col_name;
552
0
        }
553
0
        if (i < _expand_columns.size()) {
554
0
            _expand_columns[i].name = table_col_name;
555
0
        }
556
0
        new_expand_col_names.push_back(table_col_name);
557
558
        // Add column IDs
559
0
        if (it != field_id_to_file_col_name.end()) {
560
0
            for (uint64_t j = 0; j < orc_type_ptr->getSubtypeCount(); ++j) {
561
0
                const orc::Type* sub_type = orc_type_ptr->getSubtype(j);
562
0
                if (orc_type_ptr->getFieldName(j) == file_col_name) {
563
0
                    ctx->column_ids.insert(sub_type->getColumnId());
564
0
                    break;
565
0
                }
566
0
            }
567
0
        }
568
569
0
        ctx->column_names.push_back(table_col_name);
570
0
        ctx->table_info_node->add_children(table_col_name, file_col_name,
571
0
                                           TableSchemaChangeHelper::ConstNode::get_instance());
572
0
    }
573
1
    _expand_col_names = std::move(new_expand_col_names);
574
575
1
    return Status::OK();
576
1
}
577
578
// ============================================================================
579
// IcebergOrcReader: _create_column_ids
580
// ============================================================================
581
ColumnIdResult IcebergOrcReader::_create_column_ids(const orc::Type* orc_type,
582
7
                                                    const TupleDescriptor* tuple_descriptor) {
583
7
    std::unordered_map<int, const orc::Type*> iceberg_id_to_orc_type_map;
584
58
    for (uint64_t i = 0; i < orc_type->getSubtypeCount(); ++i) {
585
51
        auto orc_sub_type = orc_type->getSubtype(i);
586
51
        if (!orc_sub_type) continue;
587
51
        if (!orc_sub_type->hasAttributeKey(ICEBERG_ORC_ATTRIBUTE)) {
588
0
            continue;
589
0
        }
590
51
        int iceberg_id = std::stoi(orc_sub_type->getAttributeValue(ICEBERG_ORC_ATTRIBUTE));
591
51
        iceberg_id_to_orc_type_map[iceberg_id] = orc_sub_type;
592
51
    }
593
594
7
    std::set<uint64_t> column_ids;
595
7
    std::set<uint64_t> filter_column_ids;
596
597
7
    auto process_access_paths = [](const orc::Type* orc_field,
598
7
                                   const std::vector<TColumnAccessPath>& access_paths,
599
14
                                   std::set<uint64_t>& out_ids) {
600
14
        process_nested_access_paths(
601
14
                orc_field, access_paths, out_ids,
602
14
                [](const orc::Type* type) { return type->getColumnId(); },
603
14
                [](const orc::Type* type) { return type->getMaximumColumnId(); },
604
14
                IcebergOrcNestedColumnUtils::extract_nested_column_ids);
605
14
    };
606
607
15
    for (const auto* slot : tuple_descriptor->slots()) {
608
15
        auto it = iceberg_id_to_orc_type_map.find(slot->col_unique_id());
609
15
        if (it == iceberg_id_to_orc_type_map.end()) {
610
0
            continue;
611
0
        }
612
15
        const orc::Type* orc_field = it->second;
613
614
15
        if ((slot->col_type() != TYPE_STRUCT && slot->col_type() != TYPE_ARRAY &&
615
15
             slot->col_type() != TYPE_MAP)) {
616
7
            column_ids.insert(orc_field->getColumnId());
617
7
            if (slot->is_predicate()) {
618
0
                filter_column_ids.insert(orc_field->getColumnId());
619
0
            }
620
7
            continue;
621
7
        }
622
623
8
        const auto& all_access_paths = slot->all_access_paths();
624
8
        process_access_paths(orc_field, all_access_paths, column_ids);
625
626
8
        const auto& predicate_access_paths = slot->predicate_access_paths();
627
8
        if (!predicate_access_paths.empty()) {
628
6
            process_access_paths(orc_field, predicate_access_paths, filter_column_ids);
629
6
        }
630
8
    }
631
632
7
    return ColumnIdResult(std::move(column_ids), std::move(filter_column_ids));
633
7
}
634
635
// ============================================================================
636
// IcebergOrcReader: _read_position_delete_file
637
// ============================================================================
638
Status IcebergOrcReader::_read_position_delete_file(const TFileRangeDesc* delete_range,
639
0
                                                    DeleteFile* position_delete) {
640
0
    OrcReader orc_delete_reader(get_profile(), get_state(), get_scan_params(), *delete_range,
641
0
                                READ_DELETE_FILE_BATCH_SIZE, get_state()->timezone(), get_io_ctx(),
642
0
                                _meta_cache);
643
0
    OrcInitContext delete_ctx;
644
0
    delete_ctx.column_names = delete_file_col_names;
645
0
    delete_ctx.col_name_to_block_idx =
646
0
            const_cast<std::unordered_map<std::string, uint32_t>*>(&DELETE_COL_NAME_TO_BLOCK_IDX);
647
0
    RETURN_IF_ERROR(orc_delete_reader.init_reader(&delete_ctx));
648
649
0
    bool eof = false;
650
0
    DataTypePtr data_type_file_path {new DataTypeString};
651
0
    DataTypePtr data_type_pos {new DataTypeInt64};
652
0
    while (!eof) {
653
0
        Block block = {{data_type_file_path, ICEBERG_FILE_PATH}, {data_type_pos, ICEBERG_ROW_POS}};
654
655
0
        size_t read_rows = 0;
656
0
        RETURN_IF_ERROR(orc_delete_reader.get_next_block(&block, &read_rows, &eof));
657
658
0
        RETURN_IF_ERROR(_gen_position_delete_file_range(block, position_delete, read_rows, false));
659
0
    }
660
0
    return Status::OK();
661
0
}
662
663
} // namespace doris