Coverage Report

Created: 2026-07-14 05:14

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
2
// or more contributor license agreements.  See the NOTICE file
3
// distributed with this work for additional information
4
// 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
7
// 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
15
// specific language governing permissions and limitations
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// under the License.
17
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
120
Status IcebergParquetReader::on_before_init_reader(ReaderInitContext* ctx) {
133
120
    _column_descs = ctx->column_descs;
134
120
    _fill_col_name_to_block_idx = ctx->col_name_to_block_idx;
135
120
    _file_format = Fileformat::PARQUET;
136
137
    // Get file metadata schema first (available because _open_file() already ran)
138
120
    const FieldDescriptor* field_desc = nullptr;
139
120
    RETURN_IF_ERROR(this->get_file_metadata_schema(&field_desc));
140
120
    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
120
    if (!get_scan_params().__isset.history_schema_info ||
146
120
        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
119
    } else {
150
119
        RETURN_IF_ERROR(BuildTableInfoUtil::by_parquet_field_id_with_name_mapping(
151
119
                get_scan_params().history_schema_info.front().root_field, *field_desc,
152
119
                ctx->table_info_node));
153
119
    }
154
155
120
    std::unordered_set<std::string> partition_col_names;
156
120
    if (ctx->range->__isset.columns_from_path_keys) {
157
38
        partition_col_names.insert(ctx->range->columns_from_path_keys.begin(),
158
38
                                   ctx->range->columns_from_path_keys.end());
159
38
    }
160
161
    // Single pass: classify columns, detect $row_id, handle partition fallback.
162
120
    bool has_partition_from_path = false;
163
767
    for (const auto& desc : *ctx->column_descs) {
164
767
        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
767
        } else if (desc.category == ColumnCategory::PARTITION_KEY) {
182
38
            bool has_partition_value = partition_col_names.contains(desc.name);
183
38
            bool exists_in_file = ctx->table_info_node->children_column_exists(desc.name);
184
38
            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
38
                ctx->column_names.push_back(desc.name);
188
38
                continue;
189
38
            }
190
0
            has_partition_from_path = true;
191
729
        } else if (desc.category == ColumnCategory::REGULAR) {
192
729
            ctx->column_names.push_back(desc.name);
193
729
        } 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
767
    }
213
214
    // Set up partition value extraction if any partition columns need filling from path
215
120
    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
120
    _all_required_col_names = ctx->column_names;
222
223
    // Create column IDs from field descriptor
224
120
    auto column_id_result =
225
120
            _create_column_ids(field_desc, ctx->tuple_descriptor, ctx->table_info_node);
226
120
    ctx->column_ids = std::move(column_id_result.column_ids);
227
120
    ctx->filter_column_ids = std::move(column_id_result.filter_column_ids);
228
229
    // Build field_id -> block_column_name mapping for equality delete filtering.
230
    // This was previously done in init_reader() column matching (pre-CRTP refactoring).
231
771
    for (const auto* slot : ctx->tuple_descriptor->slots()) {
232
771
        _id_to_block_column_name.emplace(slot->col_unique_id(), slot->col_name());
233
771
    }
234
235
    // Process delete files (must happen before _do_init_reader so expand col IDs are included)
236
120
    RETURN_IF_ERROR(_init_row_filters());
237
238
    // Add expand column IDs for equality delete and remap expand column names
239
    // to match master's behavior:
240
    // - Use field_id to find the actual file column name in Parquet schema
241
    // - Prefix with __equality_delete_column__ to avoid name conflicts
242
    // - Correctly map table_col_name → file_col_name in table_info_node
243
112
    const static std::string EQ_DELETE_PRE = "__equality_delete_column__";
244
112
    std::unordered_map<int, const FieldSchema*> field_id_to_file_column;
245
112
    bool all_file_columns_have_field_ids = true;
246
1.00k
    for (int i = 0; i < field_desc->size(); ++i) {
247
888
        const auto* field_schema = field_desc->get_column(i);
248
888
        if (field_schema) {
249
886
            field_id_to_file_column[field_schema->field_id] = field_schema;
250
886
            if (field_schema->field_id < 0) {
251
2
                all_file_columns_have_field_ids = false;
252
2
            }
253
886
        }
254
888
    }
255
112
    const auto struct_node =
256
112
            std::dynamic_pointer_cast<TableSchemaChangeHelper::StructNode>(ctx->table_info_node);
257
112
    DORIS_CHECK(struct_node != nullptr);
258
259
    // Rebuild _expand_col_names with proper file-column-based names
260
112
    std::vector<std::string> new_expand_col_names;
261
113
    for (size_t i = 0; i < _expand_col_names.size(); ++i) {
262
1
        const auto& old_name = _expand_col_names[i];
263
        // Find the field_id for this expand column
264
1
        int field_id = -1;
265
1
        for (auto& [fid, name] : _id_to_block_column_name) {
266
1
            if (name == old_name) {
267
1
                field_id = fid;
268
1
                break;
269
1
            }
270
1
        }
271
272
1
        const FieldSchema* file_column = nullptr;
273
1
        if (!all_file_columns_have_field_ids && struct_node->get_children().contains(old_name) &&
274
1
            struct_node->children_column_exists(old_name)) {
275
            // Iceberg files written without field ids must use schema.name-mapping.default. The
276
            // root schema mapper deliberately switches the whole file to BY_NAME when even one
277
            // top-level field id is absent. Hidden equality keys must make the same choice: a
278
            // different physical column may still carry this key's stale id after migration.
279
1
            const auto& mapped_name = struct_node->children_file_column_name(old_name);
280
2
            for (int j = 0; j < field_desc->size(); ++j) {
281
2
                const auto* candidate = field_desc->get_column(j);
282
2
                if (candidate != nullptr && candidate->name == mapped_name) {
283
1
                    file_column = candidate;
284
1
                    break;
285
1
                }
286
2
            }
287
1
            DORIS_CHECK(file_column != nullptr);
288
1
        } else if (all_file_columns_have_field_ids) {
289
0
            auto id_it = field_id_to_file_column.find(field_id);
290
0
            if (id_it != field_id_to_file_column.end()) {
291
0
                file_column = id_it->second;
292
0
            }
293
0
        }
294
295
1
        const std::string file_col_name = file_column == nullptr ? old_name : file_column->name;
296
1
        std::string table_col_name = EQ_DELETE_PRE + file_col_name;
297
298
        // Update _id_to_block_column_name
299
1
        if (field_id >= 0) {
300
1
            _id_to_block_column_name[field_id] = table_col_name;
301
1
        }
302
303
        // Update _expand_columns name
304
1
        if (i < _expand_columns.size()) {
305
1
            _expand_columns[i].name = table_col_name;
306
1
        }
307
308
1
        if (file_column == nullptr) {
309
0
            DORIS_CHECK(i < _expand_columns.size());
310
0
            RETURN_IF_ERROR(_register_missing_equality_delete_column(field_id, table_col_name,
311
0
                                                                     _expand_columns[i].type));
312
            // The old data file predates this equality key. Keep it in the expand block so the
313
            // synthesized-column hook can materialize its logical initial default before reader
314
            // filtering, but do not advertise it to Parquet as a physical child.
315
0
            new_expand_col_names.push_back(table_col_name);
316
0
            continue;
317
0
        }
318
319
1
        new_expand_col_names.push_back(table_col_name);
320
321
        // Add column IDs
322
1
        ctx->column_ids.insert(file_column->get_column_id());
323
324
        // Register in table_info_node: table_col_name → file_col_name
325
1
        ctx->column_names.push_back(table_col_name);
326
1
        ctx->table_info_node->add_children(table_col_name, file_col_name,
327
1
                                           TableSchemaChangeHelper::ConstNode::get_instance());
328
1
    }
329
112
    _expand_col_names = std::move(new_expand_col_names);
330
331
    // Enable group filtering for Iceberg
332
112
    _filter_groups = true;
333
334
112
    return Status::OK();
335
112
}
336
337
// ============================================================================
338
// IcebergParquetReader: _create_column_ids
339
// ============================================================================
340
ColumnIdResult IcebergParquetReader::_create_column_ids(
341
        const FieldDescriptor* field_desc, const TupleDescriptor* tuple_descriptor,
342
124
        const std::shared_ptr<TableSchemaChangeHelper::Node>& table_info_node) {
343
124
    auto* mutable_field_desc = const_cast<FieldDescriptor*>(field_desc);
344
124
    mutable_field_desc->assign_ids();
345
346
124
    std::unordered_map<int, const FieldSchema*> iceberg_id_to_field_schema_map;
347
1.07k
    for (int i = 0; i < field_desc->size(); ++i) {
348
950
        auto field_schema = field_desc->get_column(i);
349
950
        if (!field_schema) continue;
350
950
        int iceberg_id = field_schema->field_id;
351
950
        iceberg_id_to_field_schema_map[iceberg_id] = field_schema;
352
950
    }
353
354
124
    std::set<uint64_t> column_ids;
355
124
    std::set<uint64_t> filter_column_ids;
356
357
124
    auto process_access_paths = [](const FieldSchema* parquet_field,
358
124
                                   const std::vector<TColumnAccessPath>& access_paths,
359
124
                                   std::set<uint64_t>& out_ids) {
360
14
        process_nested_access_paths(
361
14
                parquet_field, access_paths, out_ids,
362
14
                [](const FieldSchema* field) { return field->get_column_id(); },
363
14
                [](const FieldSchema* field) { return field->get_max_column_id(); },
364
14
                IcebergParquetNestedColumnUtils::extract_nested_column_ids);
365
14
    };
366
367
784
    for (const auto* slot : tuple_descriptor->slots()) {
368
784
        const FieldSchema* field_schema = nullptr;
369
784
        if (table_info_node != nullptr) {
370
771
            if (table_info_node->children_column_exists(slot->col_name())) {
371
                // Use the physical child selected by the schema-mapping pass. This keeps partial-id
372
                // files in BY_NAME mode from binding a projected column through an unrelated stale
373
                // field id.
374
749
                const auto& file_column_name =
375
749
                        table_info_node->children_file_column_name(slot->col_name());
376
6.03k
                for (int i = 0; i < field_desc->size(); ++i) {
377
6.03k
                    const auto* candidate = field_desc->get_column(i);
378
6.03k
                    if (candidate != nullptr && candidate->name == file_column_name) {
379
749
                        field_schema = candidate;
380
749
                        break;
381
749
                    }
382
6.03k
                }
383
749
                DORIS_CHECK(field_schema != nullptr);
384
749
            }
385
771
        } else {
386
13
            auto it = iceberg_id_to_field_schema_map.find(slot->col_unique_id());
387
13
            if (it != iceberg_id_to_field_schema_map.end()) {
388
13
                field_schema = it->second;
389
13
            }
390
13
        }
391
784
        if (field_schema == nullptr) {
392
18
            continue;
393
18
        }
394
395
766
        if ((slot->col_type() != TYPE_STRUCT && slot->col_type() != TYPE_ARRAY &&
396
766
             slot->col_type() != TYPE_MAP)) {
397
748
            column_ids.insert(field_schema->column_id);
398
748
            if (slot->is_predicate()) {
399
0
                filter_column_ids.insert(field_schema->column_id);
400
0
            }
401
748
            continue;
402
748
        }
403
404
18
        const auto& all_access_paths = slot->all_access_paths();
405
18
        process_access_paths(field_schema, all_access_paths, column_ids);
406
407
18
        const auto& predicate_access_paths = slot->predicate_access_paths();
408
18
        if (!predicate_access_paths.empty()) {
409
6
            process_access_paths(field_schema, predicate_access_paths, filter_column_ids);
410
6
        }
411
18
    }
412
124
    return {std::move(column_ids), std::move(filter_column_ids)};
413
124
}
414
415
// ============================================================================
416
// IcebergParquetReader: _read_position_delete_file
417
// ============================================================================
418
Status IcebergParquetReader::_read_position_delete_file(const TFileRangeDesc* delete_range,
419
1
                                                        DeleteFile* position_delete) {
420
1
    ParquetReader parquet_delete_reader(get_profile(), get_scan_params(), *delete_range,
421
1
                                        READ_DELETE_FILE_BATCH_SIZE, &get_state()->timezone_obj(),
422
1
                                        get_io_ctx(), get_state(), _meta_cache);
423
    // The delete file range has size=-1 (read whole file). We must disable
424
    // row group filtering before init; otherwise _do_init_reader returns EndOfFile
425
    // when _filter_groups && _range_size < 0.
426
1
    ParquetInitContext delete_ctx;
427
1
    delete_ctx.filter_groups = false;
428
1
    delete_ctx.column_names = delete_file_col_names;
429
1
    delete_ctx.col_name_to_block_idx =
430
1
            const_cast<std::unordered_map<std::string, uint32_t>*>(&DELETE_COL_NAME_TO_BLOCK_IDX);
431
1
    RETURN_IF_ERROR(parquet_delete_reader.init_reader(&delete_ctx));
432
433
0
    const tparquet::FileMetaData* meta_data = parquet_delete_reader.get_meta_data();
434
0
    bool dictionary_coded = true;
435
0
    for (const auto& row_group : meta_data->row_groups) {
436
0
        const auto& column_chunk = row_group.columns[ICEBERG_FILE_PATH_INDEX];
437
0
        if (!(column_chunk.__isset.meta_data && has_dict_page(column_chunk.meta_data))) {
438
0
            dictionary_coded = false;
439
0
            break;
440
0
        }
441
0
    }
442
0
    DataTypePtr data_type_file_path = make_nullable(std::make_shared<DataTypeString>());
443
0
    DataTypePtr data_type_pos = make_nullable(std::make_shared<DataTypeInt64>());
444
0
    bool eof = false;
445
0
    while (!eof) {
446
0
        Block block = {
447
0
                dictionary_coded
448
0
                        ? ColumnWithTypeAndName {ColumnNullable::create(ColumnDictI32::create(),
449
0
                                                                        ColumnUInt8::create()),
450
0
                                                 data_type_file_path, ICEBERG_FILE_PATH}
451
0
                        : ColumnWithTypeAndName {data_type_file_path, ICEBERG_FILE_PATH},
452
453
0
                {data_type_pos, ICEBERG_ROW_POS}};
454
0
        size_t read_rows = 0;
455
0
        RETURN_IF_ERROR(parquet_delete_reader.get_next_block(&block, &read_rows, &eof));
456
457
0
        if (read_rows <= 0) {
458
0
            break;
459
0
        }
460
0
        RETURN_IF_ERROR(_gen_position_delete_file_range(block, position_delete, read_rows,
461
0
                                                        dictionary_coded));
462
0
    }
463
0
    return Status::OK();
464
0
};
465
466
// ============================================================================
467
// IcebergOrcReader: on_before_init_reader (ORC-specific schema matching)
468
// ============================================================================
469
101
Status IcebergOrcReader::on_before_init_reader(ReaderInitContext* ctx) {
470
101
    _column_descs = ctx->column_descs;
471
101
    _fill_col_name_to_block_idx = ctx->col_name_to_block_idx;
472
101
    _file_format = Fileformat::ORC;
473
474
    // Get ORC file type first (available because _create_file_reader() already ran)
475
101
    const orc::Type* orc_type_ptr = nullptr;
476
101
    RETURN_IF_ERROR(this->get_file_type(&orc_type_ptr));
477
478
    // Build table_info_node by field_id or name matching.
479
    // This must happen BEFORE column classification so we can use children_column_exists
480
    // to check if a column exists in the file (by field ID, not name).
481
101
    if (!get_scan_params().__isset.history_schema_info ||
482
101
        get_scan_params().history_schema_info.empty()) [[unlikely]] {
483
1
        RETURN_IF_ERROR(BuildTableInfoUtil::by_orc_name(ctx->tuple_descriptor, orc_type_ptr,
484
1
                                                        ctx->table_info_node));
485
100
    } else {
486
100
        RETURN_IF_ERROR(BuildTableInfoUtil::by_orc_field_id_with_name_mapping(
487
100
                get_scan_params().history_schema_info.front().root_field, orc_type_ptr,
488
100
                ICEBERG_ORC_ATTRIBUTE, ctx->table_info_node));
489
100
    }
490
491
101
    std::unordered_set<std::string> partition_col_names;
492
101
    if (ctx->range->__isset.columns_from_path_keys) {
493
0
        partition_col_names.insert(ctx->range->columns_from_path_keys.begin(),
494
0
                                   ctx->range->columns_from_path_keys.end());
495
0
    }
496
497
    // Single pass: classify columns, detect $row_id, handle partition fallback.
498
101
    bool has_partition_from_path = false;
499
162
    for (const auto& desc : *ctx->column_descs) {
500
162
        if (desc.category == ColumnCategory::SYNTHESIZED) {
501
0
            if (desc.name == BeConsts::ICEBERG_ROWID_COL) {
502
0
                this->register_synthesized_column_handler(
503
0
                        BeConsts::ICEBERG_ROWID_COL, [this](Block* block, size_t rows) -> Status {
504
0
                            return _fill_iceberg_row_id(block, rows);
505
0
                        });
506
0
                continue;
507
0
            } else if (desc.name.starts_with(BeConsts::GLOBAL_ROWID_COL)) {
508
0
                auto topn_row_id_column_iter = _create_topn_row_id_column_iterator();
509
0
                this->register_synthesized_column_handler(
510
0
                        desc.name,
511
0
                        [iter = std::move(topn_row_id_column_iter), this, &desc](
512
0
                                Block* block, size_t rows) -> Status {
513
0
                            return fill_topn_row_id(iter, desc.name, block, rows);
514
0
                        });
515
0
                continue;
516
0
            }
517
162
        } else if (desc.category == ColumnCategory::PARTITION_KEY) {
518
0
            bool has_partition_value = partition_col_names.contains(desc.name);
519
0
            bool exists_in_file = ctx->table_info_node->children_column_exists(desc.name);
520
0
            if (!has_partition_value || exists_in_file) {
521
0
                ctx->column_names.push_back(desc.name);
522
0
                continue;
523
0
            }
524
0
            has_partition_from_path = true;
525
164
        } else if (desc.category == ColumnCategory::REGULAR) {
526
164
            ctx->column_names.push_back(desc.name);
527
18.4E
        } else if (desc.category == ColumnCategory::GENERATED) {
528
0
            _init_row_lineage_columns();
529
0
            if (desc.name == ROW_LINEAGE_ROW_ID) {
530
0
                ctx->column_names.push_back(desc.name);
531
0
                this->register_generated_column_handler(
532
0
                        ROW_LINEAGE_ROW_ID, [this](Block* block, size_t rows) -> Status {
533
0
                            return _fill_row_lineage_row_id(block, rows);
534
0
                        });
535
0
                continue;
536
0
            } else if (desc.name == ROW_LINEAGE_LAST_UPDATED_SEQ_NUMBER) {
537
0
                ctx->column_names.push_back(desc.name);
538
0
                this->register_generated_column_handler(
539
0
                        ROW_LINEAGE_LAST_UPDATED_SEQ_NUMBER,
540
0
                        [this](Block* block, size_t rows) -> Status {
541
0
                            return _fill_row_lineage_last_updated_sequence_number(block, rows);
542
0
                        });
543
0
                continue;
544
0
            }
545
0
        }
546
162
    }
547
548
101
    if (has_partition_from_path) {
549
0
        RETURN_IF_ERROR(_extract_partition_values(*ctx->range, ctx->tuple_descriptor,
550
0
                                                  _fill_partition_values,
551
0
                                                  &_fill_partition_value_is_null));
552
0
    }
553
554
101
    _all_required_col_names = ctx->column_names;
555
556
    // Create column IDs from ORC type
557
101
    auto column_id_result =
558
101
            _create_column_ids(orc_type_ptr, ctx->tuple_descriptor, ctx->table_info_node);
559
101
    ctx->column_ids = std::move(column_id_result.column_ids);
560
101
    ctx->filter_column_ids = std::move(column_id_result.filter_column_ids);
561
562
    // Build field_id -> block_column_name mapping for equality delete filtering.
563
162
    for (const auto* slot : ctx->tuple_descriptor->slots()) {
564
162
        _id_to_block_column_name.emplace(slot->col_unique_id(), slot->col_name());
565
162
    }
566
567
    // Process delete files (must happen before _do_init_reader so expand col IDs are included)
568
101
    RETURN_IF_ERROR(_init_row_filters());
569
570
    // Add expand column IDs for equality delete and remap expand column names
571
    // (matching master's behavior with __equality_delete_column__ prefix)
572
101
    const static std::string EQ_DELETE_PRE = "__equality_delete_column__";
573
101
    std::unordered_map<int, const orc::Type*> field_id_to_file_column;
574
101
    bool all_file_columns_have_field_ids = true;
575
356
    for (uint64_t i = 0; i < orc_type_ptr->getSubtypeCount(); ++i) {
576
255
        const orc::Type* sub_type = orc_type_ptr->getSubtype(i);
577
255
        if (sub_type->hasAttributeKey(ICEBERG_ORC_ATTRIBUTE)) {
578
255
            int fid = std::stoi(sub_type->getAttributeValue(ICEBERG_ORC_ATTRIBUTE));
579
255
            field_id_to_file_column[fid] = sub_type;
580
255
        } else {
581
0
            all_file_columns_have_field_ids = false;
582
0
        }
583
255
    }
584
101
    const auto struct_node =
585
101
            std::dynamic_pointer_cast<TableSchemaChangeHelper::StructNode>(ctx->table_info_node);
586
101
    DORIS_CHECK(struct_node != nullptr);
587
588
101
    std::vector<std::string> new_expand_col_names;
589
103
    for (size_t i = 0; i < _expand_col_names.size(); ++i) {
590
2
        const auto& old_name = _expand_col_names[i];
591
2
        int field_id = -1;
592
2
        for (auto& [fid, name] : _id_to_block_column_name) {
593
2
            if (name == old_name) {
594
2
                field_id = fid;
595
2
                break;
596
2
            }
597
2
        }
598
599
2
        const orc::Type* file_column = nullptr;
600
2
        if (!all_file_columns_have_field_ids && struct_node->get_children().contains(old_name) &&
601
2
            struct_node->children_column_exists(old_name)) {
602
            // Match the root ORC schema mapper's all-or-nothing BY_NAME decision. Accepting a
603
            // matching id in a partial-id file could bind this hidden key to an unrelated stale
604
            // column instead of the current name or historical alias selected by table_info_node.
605
1
            const auto& mapped_name = struct_node->children_file_column_name(old_name);
606
2
            for (uint64_t j = 0; j < orc_type_ptr->getSubtypeCount(); ++j) {
607
2
                if (orc_type_ptr->getFieldName(j) == mapped_name) {
608
1
                    file_column = orc_type_ptr->getSubtype(j);
609
1
                    break;
610
1
                }
611
2
            }
612
1
            DORIS_CHECK(file_column != nullptr);
613
1
        } else if (all_file_columns_have_field_ids) {
614
1
            auto id_it = field_id_to_file_column.find(field_id);
615
1
            if (id_it != field_id_to_file_column.end()) {
616
0
                file_column = id_it->second;
617
0
            }
618
1
        }
619
620
2
        std::string file_col_name = old_name;
621
2
        if (file_column != nullptr) {
622
2
            for (uint64_t j = 0; j < orc_type_ptr->getSubtypeCount(); ++j) {
623
2
                if (orc_type_ptr->getSubtype(j) == file_column) {
624
1
                    file_col_name = orc_type_ptr->getFieldName(j);
625
1
                    break;
626
1
                }
627
2
            }
628
1
        }
629
2
        std::string table_col_name = EQ_DELETE_PRE + file_col_name;
630
631
2
        if (field_id >= 0) {
632
2
            _id_to_block_column_name[field_id] = table_col_name;
633
2
        }
634
2
        if (i < _expand_columns.size()) {
635
2
            _expand_columns[i].name = table_col_name;
636
2
        }
637
2
        if (file_column == nullptr) {
638
1
            DORIS_CHECK(i < _expand_columns.size());
639
1
            RETURN_IF_ERROR(_register_missing_equality_delete_column(field_id, table_col_name,
640
1
                                                                     _expand_columns[i].type));
641
            // The old data file predates this equality key. Keep it in the expand block so the
642
            // synthesized-column hook can materialize its logical initial default before ORC's
643
            // block-size checks. Adding it to column_names/table_info_node would mark it as an
644
            // existing ORC child and make OrcReader read a column that is not present in the file.
645
1
            new_expand_col_names.push_back(table_col_name);
646
1
            continue;
647
1
        }
648
1
        new_expand_col_names.push_back(table_col_name);
649
650
        // Add column IDs
651
1
        ctx->column_ids.insert(file_column->getColumnId());
652
653
1
        ctx->column_names.push_back(table_col_name);
654
1
        ctx->table_info_node->add_children(table_col_name, file_col_name,
655
1
                                           TableSchemaChangeHelper::ConstNode::get_instance());
656
1
    }
657
101
    _expand_col_names = std::move(new_expand_col_names);
658
659
101
    return Status::OK();
660
101
}
661
662
// ============================================================================
663
// IcebergOrcReader: _create_column_ids
664
// ============================================================================
665
ColumnIdResult IcebergOrcReader::_create_column_ids(
666
        const orc::Type* orc_type, const TupleDescriptor* tuple_descriptor,
667
105
        const std::shared_ptr<TableSchemaChangeHelper::Node>& table_info_node) {
668
105
    std::unordered_map<int, const orc::Type*> iceberg_id_to_orc_type_map;
669
410
    for (uint64_t i = 0; i < orc_type->getSubtypeCount(); ++i) {
670
305
        const auto* orc_sub_type = orc_type->getSubtype(i);
671
305
        if (!orc_sub_type) {
672
0
            continue;
673
0
        }
674
305
        if (!orc_sub_type->hasAttributeKey(ICEBERG_ORC_ATTRIBUTE)) {
675
2
            continue;
676
2
        }
677
303
        int iceberg_id = std::stoi(orc_sub_type->getAttributeValue(ICEBERG_ORC_ATTRIBUTE));
678
303
        iceberg_id_to_orc_type_map[iceberg_id] = orc_sub_type;
679
303
    }
680
681
105
    std::set<uint64_t> column_ids;
682
105
    std::set<uint64_t> filter_column_ids;
683
684
105
    auto process_access_paths = [](const orc::Type* orc_field,
685
105
                                   const std::vector<TColumnAccessPath>& access_paths,
686
105
                                   std::set<uint64_t>& out_ids) {
687
14
        process_nested_access_paths(
688
14
                orc_field, access_paths, out_ids,
689
14
                [](const orc::Type* type) { return type->getColumnId(); },
690
14
                [](const orc::Type* type) { return type->getMaximumColumnId(); },
691
14
                IcebergOrcNestedColumnUtils::extract_nested_column_ids);
692
14
    };
693
694
175
    for (const auto* slot : tuple_descriptor->slots()) {
695
175
        const orc::Type* orc_field = nullptr;
696
175
        if (table_info_node != nullptr) {
697
164
            if (table_info_node->children_column_exists(slot->col_name())) {
698
                // Select the physical child resolved by the shared schema-mapping pass. Hidden
699
                // equality keys and projected columns must obey the same BY_NAME decision for
700
                // partial-id ORC files.
701
144
                const auto& file_column_name =
702
144
                        table_info_node->children_file_column_name(slot->col_name());
703
343
                for (uint64_t i = 0; i < orc_type->getSubtypeCount(); ++i) {
704
343
                    if (orc_type->getFieldName(i) == file_column_name) {
705
146
                        orc_field = orc_type->getSubtype(i);
706
146
                        break;
707
146
                    }
708
343
                }
709
144
                DORIS_CHECK(orc_field != nullptr);
710
144
            }
711
164
        } else {
712
11
            auto it = iceberg_id_to_orc_type_map.find(slot->col_unique_id());
713
13
            if (it != iceberg_id_to_orc_type_map.end()) {
714
13
                orc_field = it->second;
715
13
            }
716
11
        }
717
175
        if (orc_field == nullptr) {
718
18
            continue;
719
18
        }
720
721
157
        if ((slot->col_type() != TYPE_STRUCT && slot->col_type() != TYPE_ARRAY &&
722
157
             slot->col_type() != TYPE_MAP)) {
723
147
            column_ids.insert(orc_field->getColumnId());
724
147
            if (slot->is_predicate()) {
725
0
                filter_column_ids.insert(orc_field->getColumnId());
726
0
            }
727
147
            continue;
728
147
        }
729
730
10
        const auto& all_access_paths = slot->all_access_paths();
731
10
        process_access_paths(orc_field, all_access_paths, column_ids);
732
733
10
        const auto& predicate_access_paths = slot->predicate_access_paths();
734
10
        if (!predicate_access_paths.empty()) {
735
6
            process_access_paths(orc_field, predicate_access_paths, filter_column_ids);
736
6
        }
737
10
    }
738
739
105
    return {std::move(column_ids), std::move(filter_column_ids)};
740
105
}
741
742
// ============================================================================
743
// IcebergOrcReader: _read_position_delete_file
744
// ============================================================================
745
Status IcebergOrcReader::_read_position_delete_file(const TFileRangeDesc* delete_range,
746
0
                                                    DeleteFile* position_delete) {
747
0
    OrcReader orc_delete_reader(get_profile(), get_state(), get_scan_params(), *delete_range,
748
0
                                READ_DELETE_FILE_BATCH_SIZE, get_state()->timezone(), get_io_ctx(),
749
0
                                _meta_cache);
750
0
    OrcInitContext delete_ctx;
751
0
    delete_ctx.column_names = delete_file_col_names;
752
0
    delete_ctx.col_name_to_block_idx =
753
0
            const_cast<std::unordered_map<std::string, uint32_t>*>(&DELETE_COL_NAME_TO_BLOCK_IDX);
754
0
    RETURN_IF_ERROR(orc_delete_reader.init_reader(&delete_ctx));
755
756
0
    bool eof = false;
757
0
    DataTypePtr data_type_file_path {new DataTypeString};
758
0
    DataTypePtr data_type_pos {new DataTypeInt64};
759
0
    while (!eof) {
760
0
        Block block = {{data_type_file_path, ICEBERG_FILE_PATH}, {data_type_pos, ICEBERG_ROW_POS}};
761
762
0
        size_t read_rows = 0;
763
0
        RETURN_IF_ERROR(orc_delete_reader.get_next_block(&block, &read_rows, &eof));
764
765
0
        RETURN_IF_ERROR(_gen_position_delete_file_range(block, position_delete, read_rows, false));
766
0
    }
767
0
    return Status::OK();
768
0
}
769
770
} // namespace doris