Coverage Report

Created: 2026-03-16 16:11

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/format/parquet/schema_desc.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
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// 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
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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
10
//
11
// Unless required by applicable law or agreed to in writing,
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// 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/parquet/schema_desc.h"
19
20
#include <ctype.h>
21
22
#include <algorithm>
23
#include <ostream>
24
#include <utility>
25
26
#include "common/cast_set.h"
27
#include "common/logging.h"
28
#include "core/data_type/data_type_array.h"
29
#include "core/data_type/data_type_factory.hpp"
30
#include "core/data_type/data_type_map.h"
31
#include "core/data_type/data_type_struct.h"
32
#include "core/data_type/define_primitive_type.h"
33
#include "format/table/table_format_reader.h"
34
#include "format/table/table_schema_change_helper.h"
35
#include "util/slice.h"
36
#include "util/string_util.h"
37
38
namespace doris {
39
#include "common/compile_check_begin.h"
40
41
141k
static bool is_group_node(const tparquet::SchemaElement& schema) {
42
141k
    return schema.num_children > 0;
43
141k
}
44
45
16.3k
static bool is_list_node(const tparquet::SchemaElement& schema) {
46
16.3k
    return schema.__isset.converted_type && schema.converted_type == tparquet::ConvertedType::LIST;
47
16.3k
}
48
49
24.0k
static bool is_map_node(const tparquet::SchemaElement& schema) {
50
24.0k
    return schema.__isset.converted_type &&
51
24.0k
           (schema.converted_type == tparquet::ConvertedType::MAP ||
52
18.0k
            schema.converted_type == tparquet::ConvertedType::MAP_KEY_VALUE);
53
24.0k
}
54
55
120k
static bool is_repeated_node(const tparquet::SchemaElement& schema) {
56
120k
    return schema.__isset.repetition_type &&
57
120k
           schema.repetition_type == tparquet::FieldRepetitionType::REPEATED;
58
120k
}
59
60
7.73k
static bool is_required_node(const tparquet::SchemaElement& schema) {
61
7.73k
    return schema.__isset.repetition_type &&
62
7.73k
           schema.repetition_type == tparquet::FieldRepetitionType::REQUIRED;
63
7.73k
}
64
65
122k
static bool is_optional_node(const tparquet::SchemaElement& schema) {
66
122k
    return schema.__isset.repetition_type &&
67
122k
           schema.repetition_type == tparquet::FieldRepetitionType::OPTIONAL;
68
122k
}
69
70
10.3k
static int num_children_node(const tparquet::SchemaElement& schema) {
71
10.3k
    return schema.__isset.num_children ? schema.num_children : 0;
72
10.3k
}
73
74
/**
75
 * `repeated_parent_def_level` is the definition level of the first ancestor node whose repetition_type equals REPEATED.
76
 * Empty array/map values are not stored in doris columns, so have to use `repeated_parent_def_level` to skip the
77
 * empty or null values in ancestor node.
78
 *
79
 * For instance, considering an array of strings with 3 rows like the following:
80
 * null, [], [a, b, c]
81
 * We can store four elements in data column: null, a, b, c
82
 * and the offsets column is: 1, 1, 4
83
 * and the null map is: 1, 0, 0
84
 * For the i-th row in array column: range from `offsets[i - 1]` until `offsets[i]` represents the elements in this row,
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 * so we can't store empty array/map values in doris data column.
86
 * As a comparison, spark does not require `repeated_parent_def_level`,
87
 * because the spark column stores empty array/map values , and use anther length column to indicate empty values.
88
 * Please reference: https://github.com/apache/spark/blob/master/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/ParquetColumnVector.java
89
 *
90
 * Furthermore, we can also avoid store null array/map values in doris data column.
91
 * The same three rows as above, We can only store three elements in data column: a, b, c
92
 * and the offsets column is: 0, 0, 3
93
 * and the null map is: 1, 0, 0
94
 *
95
 * Inherit the repetition and definition level from parent node, if the parent node is repeated,
96
 * we should set repeated_parent_def_level = definition_level, otherwise as repeated_parent_def_level.
97
 * @param parent parent node
98
 * @param repeated_parent_def_level the first ancestor node whose repetition_type equals REPEATED
99
 */
100
24.1k
static void set_child_node_level(FieldSchema* parent, int16_t repeated_parent_def_level) {
101
40.4k
    for (auto& child : parent->children) {
102
40.4k
        child.repetition_level = parent->repetition_level;
103
40.4k
        child.definition_level = parent->definition_level;
104
40.4k
        child.repeated_parent_def_level = repeated_parent_def_level;
105
40.4k
    }
106
24.1k
}
107
108
10.2k
static bool is_struct_list_node(const tparquet::SchemaElement& schema) {
109
10.2k
    const std::string& name = schema.name;
110
10.2k
    static const Slice array_slice("array", 5);
111
10.2k
    static const Slice tuple_slice("_tuple", 6);
112
10.2k
    Slice slice(name);
113
10.2k
    return slice == array_slice || slice.ends_with(tuple_slice);
114
10.2k
}
115
116
0
std::string FieldSchema::debug_string() const {
117
0
    std::stringstream ss;
118
0
    ss << "FieldSchema(name=" << name << ", R=" << repetition_level << ", D=" << definition_level;
119
0
    if (children.size() > 0) {
120
0
        ss << ", type=" << data_type->get_name() << ", children=[";
121
0
        for (int i = 0; i < children.size(); ++i) {
122
0
            if (i != 0) {
123
0
                ss << ", ";
124
0
            }
125
0
            ss << children[i].debug_string();
126
0
        }
127
0
        ss << "]";
128
0
    } else {
129
0
        ss << ", physical_type=" << physical_type;
130
0
        ss << " , doris_type=" << data_type->get_name();
131
0
    }
132
0
    ss << ")";
133
0
    return ss.str();
134
0
}
135
136
11.3k
Status FieldDescriptor::parse_from_thrift(const std::vector<tparquet::SchemaElement>& t_schemas) {
137
11.3k
    if (t_schemas.size() == 0 || !is_group_node(t_schemas[0])) {
138
0
        return Status::InvalidArgument("Wrong parquet root schema element");
139
0
    }
140
11.3k
    const auto& root_schema = t_schemas[0];
141
11.3k
    _fields.resize(root_schema.num_children);
142
11.3k
    _next_schema_pos = 1;
143
144
94.0k
    for (int i = 0; i < root_schema.num_children; ++i) {
145
82.6k
        RETURN_IF_ERROR(parse_node_field(t_schemas, _next_schema_pos, &_fields[i]));
146
82.6k
        if (_name_to_field.find(_fields[i].name) != _name_to_field.end()) {
147
0
            return Status::InvalidArgument("Duplicated field name: {}", _fields[i].name);
148
0
        }
149
82.6k
        _name_to_field.emplace(_fields[i].name, &_fields[i]);
150
82.6k
    }
151
152
11.3k
    if (_next_schema_pos != t_schemas.size()) {
153
0
        return Status::InvalidArgument("Remaining {} unparsed schema elements",
154
0
                                       t_schemas.size() - _next_schema_pos);
155
0
    }
156
157
11.3k
    return Status::OK();
158
11.3k
}
159
160
Status FieldDescriptor::parse_node_field(const std::vector<tparquet::SchemaElement>& t_schemas,
161
122k
                                         size_t curr_pos, FieldSchema* node_field) {
162
122k
    if (curr_pos >= t_schemas.size()) {
163
0
        return Status::InvalidArgument("Out-of-bounds index of schema elements");
164
0
    }
165
122k
    auto& t_schema = t_schemas[curr_pos];
166
122k
    if (is_group_node(t_schema)) {
167
        // nested structure or nullable list
168
24.0k
        return parse_group_field(t_schemas, curr_pos, node_field);
169
24.0k
    }
170
98.7k
    if (is_repeated_node(t_schema)) {
171
        // repeated <primitive-type> <name> (LIST)
172
        // produce required list<element>
173
36
        node_field->repetition_level++;
174
36
        node_field->definition_level++;
175
36
        node_field->children.resize(1);
176
36
        set_child_node_level(node_field, node_field->definition_level);
177
36
        auto child = &node_field->children[0];
178
36
        parse_physical_field(t_schema, false, child);
179
180
36
        node_field->name = t_schema.name;
181
36
        node_field->lower_case_name = to_lower(t_schema.name);
182
36
        node_field->data_type = std::make_shared<DataTypeArray>(make_nullable(child->data_type));
183
36
        _next_schema_pos = curr_pos + 1;
184
36
        node_field->field_id = t_schema.__isset.field_id ? t_schema.field_id : -1;
185
98.7k
    } else {
186
98.7k
        bool is_optional = is_optional_node(t_schema);
187
98.7k
        if (is_optional) {
188
75.3k
            node_field->definition_level++;
189
75.3k
        }
190
98.7k
        parse_physical_field(t_schema, is_optional, node_field);
191
98.7k
        _next_schema_pos = curr_pos + 1;
192
98.7k
    }
193
98.7k
    return Status::OK();
194
122k
}
195
196
void FieldDescriptor::parse_physical_field(const tparquet::SchemaElement& physical_schema,
197
98.8k
                                           bool is_nullable, FieldSchema* physical_field) {
198
98.8k
    physical_field->name = physical_schema.name;
199
98.8k
    physical_field->lower_case_name = to_lower(physical_field->name);
200
98.8k
    physical_field->parquet_schema = physical_schema;
201
98.8k
    physical_field->physical_type = physical_schema.type;
202
98.8k
    physical_field->column_id = UNASSIGNED_COLUMN_ID; // Initialize column_id
203
98.8k
    _physical_fields.push_back(physical_field);
204
98.8k
    physical_field->physical_column_index = cast_set<int>(_physical_fields.size() - 1);
205
98.8k
    auto type = get_doris_type(physical_schema, is_nullable);
206
98.8k
    physical_field->data_type = type.first;
207
98.8k
    physical_field->is_type_compatibility = type.second;
208
98.8k
    physical_field->field_id = physical_schema.__isset.field_id ? physical_schema.field_id : -1;
209
98.8k
}
210
211
std::pair<DataTypePtr, bool> FieldDescriptor::get_doris_type(
212
98.8k
        const tparquet::SchemaElement& physical_schema, bool nullable) {
213
98.8k
    std::pair<DataTypePtr, bool> ans = {std::make_shared<DataTypeNothing>(), false};
214
98.8k
    try {
215
98.8k
        if (physical_schema.__isset.logicalType) {
216
40.9k
            ans = convert_to_doris_type(physical_schema.logicalType, nullable);
217
57.8k
        } else if (physical_schema.__isset.converted_type) {
218
12.1k
            ans = convert_to_doris_type(physical_schema, nullable);
219
12.1k
        }
220
98.8k
    } catch (...) {
221
        // now the Not supported exception are ignored
222
        // so those byte_array maybe be treated as varbinary(now) : string(before)
223
56
    }
224
98.8k
    if (ans.first->get_primitive_type() == PrimitiveType::INVALID_TYPE) {
225
45.9k
        switch (physical_schema.type) {
226
3.42k
        case tparquet::Type::BOOLEAN:
227
3.42k
            ans.first = DataTypeFactory::instance().create_data_type(TYPE_BOOLEAN, nullable);
228
3.42k
            break;
229
17.4k
        case tparquet::Type::INT32:
230
17.4k
            ans.first = DataTypeFactory::instance().create_data_type(TYPE_INT, nullable);
231
17.4k
            break;
232
10.5k
        case tparquet::Type::INT64:
233
10.5k
            ans.first = DataTypeFactory::instance().create_data_type(TYPE_BIGINT, nullable);
234
10.5k
            break;
235
1.26k
        case tparquet::Type::INT96:
236
1.26k
            if (_enable_mapping_timestamp_tz) {
237
                // treat INT96 as TIMESTAMPTZ
238
8
                ans.first = DataTypeFactory::instance().create_data_type(TYPE_TIMESTAMPTZ, nullable,
239
8
                                                                         0, 6);
240
1.26k
            } else {
241
                // in most cases, it's a nano timestamp
242
1.26k
                ans.first = DataTypeFactory::instance().create_data_type(TYPE_DATETIMEV2, nullable,
243
1.26k
                                                                         0, 6);
244
1.26k
            }
245
1.26k
            break;
246
6.64k
        case tparquet::Type::FLOAT:
247
6.64k
            ans.first = DataTypeFactory::instance().create_data_type(TYPE_FLOAT, nullable);
248
6.64k
            break;
249
5.44k
        case tparquet::Type::DOUBLE:
250
5.44k
            ans.first = DataTypeFactory::instance().create_data_type(TYPE_DOUBLE, nullable);
251
5.44k
            break;
252
1.17k
        case tparquet::Type::BYTE_ARRAY:
253
1.17k
            if (_enable_mapping_varbinary) {
254
                // if physical_schema not set logicalType and converted_type,
255
                // we treat BYTE_ARRAY as VARBINARY by default, so that we can read all data directly.
256
170
                ans.first = DataTypeFactory::instance().create_data_type(TYPE_VARBINARY, nullable);
257
1.00k
            } else {
258
1.00k
                ans.first = DataTypeFactory::instance().create_data_type(TYPE_STRING, nullable);
259
1.00k
            }
260
1.17k
            break;
261
20
        case tparquet::Type::FIXED_LEN_BYTE_ARRAY:
262
20
            ans.first = DataTypeFactory::instance().create_data_type(TYPE_STRING, nullable);
263
20
            break;
264
0
        default:
265
0
            throw Exception(Status::InternalError("Not supported parquet logicalType{}",
266
0
                                                  physical_schema.type));
267
0
            break;
268
45.9k
        }
269
45.9k
    }
270
98.7k
    return ans;
271
98.7k
}
272
273
std::pair<DataTypePtr, bool> FieldDescriptor::convert_to_doris_type(
274
40.8k
        tparquet::LogicalType logicalType, bool nullable) {
275
40.8k
    std::pair<DataTypePtr, bool> ans = {std::make_shared<DataTypeNothing>(), false};
276
40.8k
    bool& is_type_compatibility = ans.second;
277
40.8k
    if (logicalType.__isset.STRING) {
278
22.1k
        ans.first = DataTypeFactory::instance().create_data_type(TYPE_STRING, nullable);
279
22.1k
    } else if (logicalType.__isset.DECIMAL) {
280
10.9k
        ans.first = DataTypeFactory::instance().create_data_type(TYPE_DECIMAL128I, nullable,
281
10.9k
                                                                 logicalType.DECIMAL.precision,
282
10.9k
                                                                 logicalType.DECIMAL.scale);
283
10.9k
    } else if (logicalType.__isset.DATE) {
284
2.20k
        ans.first = DataTypeFactory::instance().create_data_type(TYPE_DATEV2, nullable);
285
5.67k
    } else if (logicalType.__isset.INTEGER) {
286
2.51k
        if (logicalType.INTEGER.isSigned) {
287
2.24k
            if (logicalType.INTEGER.bitWidth <= 8) {
288
676
                ans.first = DataTypeFactory::instance().create_data_type(TYPE_TINYINT, nullable);
289
1.57k
            } else if (logicalType.INTEGER.bitWidth <= 16) {
290
1.12k
                ans.first = DataTypeFactory::instance().create_data_type(TYPE_SMALLINT, nullable);
291
1.12k
            } else if (logicalType.INTEGER.bitWidth <= 32) {
292
198
                ans.first = DataTypeFactory::instance().create_data_type(TYPE_INT, nullable);
293
246
            } else {
294
246
                ans.first = DataTypeFactory::instance().create_data_type(TYPE_BIGINT, nullable);
295
246
            }
296
2.24k
        } else {
297
264
            is_type_compatibility = true;
298
264
            if (logicalType.INTEGER.bitWidth <= 8) {
299
66
                ans.first = DataTypeFactory::instance().create_data_type(TYPE_SMALLINT, nullable);
300
198
            } else if (logicalType.INTEGER.bitWidth <= 16) {
301
66
                ans.first = DataTypeFactory::instance().create_data_type(TYPE_INT, nullable);
302
132
            } else if (logicalType.INTEGER.bitWidth <= 32) {
303
70
                ans.first = DataTypeFactory::instance().create_data_type(TYPE_BIGINT, nullable);
304
70
            } else {
305
62
                ans.first = DataTypeFactory::instance().create_data_type(TYPE_LARGEINT, nullable);
306
62
            }
307
264
        }
308
3.16k
    } else if (logicalType.__isset.TIME) {
309
40
        ans.first = DataTypeFactory::instance().create_data_type(TYPE_TIMEV2, nullable);
310
3.12k
    } else if (logicalType.__isset.TIMESTAMP) {
311
3.08k
        if (_enable_mapping_timestamp_tz) {
312
76
            if (logicalType.TIMESTAMP.isAdjustedToUTC) {
313
                // treat TIMESTAMP with isAdjustedToUTC as TIMESTAMPTZ
314
76
                ans.first = DataTypeFactory::instance().create_data_type(
315
76
                        TYPE_TIMESTAMPTZ, nullable, 0,
316
76
                        logicalType.TIMESTAMP.unit.__isset.MILLIS ? 3 : 6);
317
76
                return ans;
318
76
            }
319
76
        }
320
3.00k
        ans.first = DataTypeFactory::instance().create_data_type(
321
3.00k
                TYPE_DATETIMEV2, nullable, 0, logicalType.TIMESTAMP.unit.__isset.MILLIS ? 3 : 6);
322
3.00k
    } else if (logicalType.__isset.JSON) {
323
4
        ans.first = DataTypeFactory::instance().create_data_type(TYPE_STRING, nullable);
324
36
    } else if (logicalType.__isset.UUID) {
325
12
        if (_enable_mapping_varbinary) {
326
7
            ans.first = DataTypeFactory::instance().create_data_type(TYPE_VARBINARY, nullable, -1,
327
7
                                                                     -1, 16);
328
7
        } else {
329
5
            ans.first = DataTypeFactory::instance().create_data_type(TYPE_STRING, nullable);
330
5
        }
331
24
    } else if (logicalType.__isset.FLOAT16) {
332
20
        ans.first = DataTypeFactory::instance().create_data_type(TYPE_FLOAT, nullable);
333
20
    } else {
334
4
        throw Exception(Status::InternalError("Not supported parquet logicalType"));
335
4
    }
336
40.8k
    return ans;
337
40.8k
}
338
339
std::pair<DataTypePtr, bool> FieldDescriptor::convert_to_doris_type(
340
12.1k
        const tparquet::SchemaElement& physical_schema, bool nullable) {
341
12.1k
    std::pair<DataTypePtr, bool> ans = {std::make_shared<DataTypeNothing>(), false};
342
12.1k
    bool& is_type_compatibility = ans.second;
343
12.1k
    switch (physical_schema.converted_type) {
344
7.88k
    case tparquet::ConvertedType::type::UTF8:
345
7.88k
        ans.first = DataTypeFactory::instance().create_data_type(TYPE_STRING, nullable);
346
7.88k
        break;
347
1.72k
    case tparquet::ConvertedType::type::DECIMAL:
348
1.72k
        ans.first = DataTypeFactory::instance().create_data_type(
349
1.72k
                TYPE_DECIMAL128I, nullable, physical_schema.precision, physical_schema.scale);
350
1.72k
        break;
351
1.17k
    case tparquet::ConvertedType::type::DATE:
352
1.17k
        ans.first = DataTypeFactory::instance().create_data_type(TYPE_DATEV2, nullable);
353
1.17k
        break;
354
0
    case tparquet::ConvertedType::type::TIME_MILLIS:
355
0
        [[fallthrough]];
356
0
    case tparquet::ConvertedType::type::TIME_MICROS:
357
0
        ans.first = DataTypeFactory::instance().create_data_type(TYPE_TIMEV2, nullable);
358
0
        break;
359
24
    case tparquet::ConvertedType::type::TIMESTAMP_MILLIS:
360
24
        ans.first = DataTypeFactory::instance().create_data_type(TYPE_DATETIMEV2, nullable, 0, 3);
361
24
        break;
362
52
    case tparquet::ConvertedType::type::TIMESTAMP_MICROS:
363
52
        ans.first = DataTypeFactory::instance().create_data_type(TYPE_DATETIMEV2, nullable, 0, 6);
364
52
        break;
365
340
    case tparquet::ConvertedType::type::INT_8:
366
340
        ans.first = DataTypeFactory::instance().create_data_type(TYPE_TINYINT, nullable);
367
340
        break;
368
8
    case tparquet::ConvertedType::type::UINT_8:
369
8
        is_type_compatibility = true;
370
8
        [[fallthrough]];
371
355
    case tparquet::ConvertedType::type::INT_16:
372
355
        ans.first = DataTypeFactory::instance().create_data_type(TYPE_SMALLINT, nullable);
373
355
        break;
374
8
    case tparquet::ConvertedType::type::UINT_16:
375
8
        is_type_compatibility = true;
376
8
        [[fallthrough]];
377
48
    case tparquet::ConvertedType::type::INT_32:
378
48
        ans.first = DataTypeFactory::instance().create_data_type(TYPE_INT, nullable);
379
48
        break;
380
24
    case tparquet::ConvertedType::type::UINT_32:
381
24
        is_type_compatibility = true;
382
24
        [[fallthrough]];
383
360
    case tparquet::ConvertedType::type::INT_64:
384
360
        ans.first = DataTypeFactory::instance().create_data_type(TYPE_BIGINT, nullable);
385
360
        break;
386
148
    case tparquet::ConvertedType::type::UINT_64:
387
148
        is_type_compatibility = true;
388
148
        ans.first = DataTypeFactory::instance().create_data_type(TYPE_LARGEINT, nullable);
389
148
        break;
390
4
    case tparquet::ConvertedType::type::JSON:
391
4
        ans.first = DataTypeFactory::instance().create_data_type(TYPE_STRING, nullable);
392
4
        break;
393
20
    default:
394
20
        throw Exception(Status::InternalError("Not supported parquet ConvertedType: {}",
395
20
                                              physical_schema.converted_type));
396
12.1k
    }
397
12.1k
    return ans;
398
12.1k
}
399
400
Status FieldDescriptor::parse_group_field(const std::vector<tparquet::SchemaElement>& t_schemas,
401
24.0k
                                          size_t curr_pos, FieldSchema* group_field) {
402
24.0k
    auto& group_schema = t_schemas[curr_pos];
403
24.0k
    if (is_map_node(group_schema)) {
404
        // the map definition:
405
        // optional group <name> (MAP) {
406
        //   repeated group map (MAP_KEY_VALUE) {
407
        //     required <type> key;
408
        //     optional <type> value;
409
        //   }
410
        // }
411
7.73k
        return parse_map_field(t_schemas, curr_pos, group_field);
412
7.73k
    }
413
16.3k
    if (is_list_node(group_schema)) {
414
        // the list definition:
415
        // optional group <name> (LIST) {
416
        //   repeated group [bag | list] { // hive or spark
417
        //     optional <type> [array_element | element]; // hive or spark
418
        //   }
419
        // }
420
10.3k
        return parse_list_field(t_schemas, curr_pos, group_field);
421
10.3k
    }
422
423
5.97k
    if (is_repeated_node(group_schema)) {
424
32
        group_field->repetition_level++;
425
32
        group_field->definition_level++;
426
32
        group_field->children.resize(1);
427
32
        set_child_node_level(group_field, group_field->definition_level);
428
32
        auto struct_field = &group_field->children[0];
429
        // the list of struct:
430
        // repeated group <name> (LIST) {
431
        //   optional/required <type> <name>;
432
        //   ...
433
        // }
434
        // produce a non-null list<struct>
435
32
        RETURN_IF_ERROR(parse_struct_field(t_schemas, curr_pos, struct_field));
436
437
32
        group_field->name = group_schema.name;
438
32
        group_field->lower_case_name = to_lower(group_field->name);
439
32
        group_field->column_id = UNASSIGNED_COLUMN_ID; // Initialize column_id
440
32
        group_field->data_type =
441
32
                std::make_shared<DataTypeArray>(make_nullable(struct_field->data_type));
442
32
        group_field->field_id = group_schema.__isset.field_id ? group_schema.field_id : -1;
443
5.94k
    } else {
444
5.94k
        RETURN_IF_ERROR(parse_struct_field(t_schemas, curr_pos, group_field));
445
5.94k
    }
446
447
5.97k
    return Status::OK();
448
5.97k
}
449
450
Status FieldDescriptor::parse_list_field(const std::vector<tparquet::SchemaElement>& t_schemas,
451
10.3k
                                         size_t curr_pos, FieldSchema* list_field) {
452
    // the list definition:
453
    // spark and hive have three level schemas but with different schema name
454
    // spark: <column-name> - "list" - "element"
455
    // hive: <column-name> - "bag" - "array_element"
456
    // parse three level schemas to two level primitive like: LIST<INT>,
457
    // or nested structure like: LIST<MAP<INT, INT>>
458
10.3k
    auto& first_level = t_schemas[curr_pos];
459
10.3k
    if (first_level.num_children != 1) {
460
0
        return Status::InvalidArgument("List element should have only one child");
461
0
    }
462
463
10.3k
    if (curr_pos + 1 >= t_schemas.size()) {
464
0
        return Status::InvalidArgument("List element should have the second level schema");
465
0
    }
466
467
10.3k
    if (first_level.repetition_type == tparquet::FieldRepetitionType::REPEATED) {
468
0
        return Status::InvalidArgument("List element can't be a repeated schema");
469
0
    }
470
471
    // the repeated schema element
472
10.3k
    auto& second_level = t_schemas[curr_pos + 1];
473
10.3k
    if (second_level.repetition_type != tparquet::FieldRepetitionType::REPEATED) {
474
0
        return Status::InvalidArgument("The second level of list element should be repeated");
475
0
    }
476
477
    // This indicates if this list is nullable.
478
10.3k
    bool is_optional = is_optional_node(first_level);
479
10.3k
    if (is_optional) {
480
9.48k
        list_field->definition_level++;
481
9.48k
    }
482
10.3k
    list_field->repetition_level++;
483
10.3k
    list_field->definition_level++;
484
10.3k
    list_field->children.resize(1);
485
10.3k
    FieldSchema* list_child = &list_field->children[0];
486
487
10.3k
    size_t num_children = num_children_node(second_level);
488
10.3k
    if (num_children > 0) {
489
10.3k
        if (num_children == 1 && !is_struct_list_node(second_level)) {
490
            // optional field, and the third level element is the nested structure in list
491
            // produce nested structure like: LIST<INT>, LIST<MAP>, LIST<LIST<...>>
492
            // skip bag/list, it's a repeated element.
493
10.2k
            set_child_node_level(list_field, list_field->definition_level);
494
10.2k
            RETURN_IF_ERROR(parse_node_field(t_schemas, curr_pos + 2, list_child));
495
10.2k
        } else {
496
            // required field, produce the list of struct
497
34
            set_child_node_level(list_field, list_field->definition_level);
498
34
            RETURN_IF_ERROR(parse_struct_field(t_schemas, curr_pos + 1, list_child));
499
34
        }
500
10.3k
    } else if (num_children == 0) {
501
        // required two level list, for compatibility reason.
502
48
        set_child_node_level(list_field, list_field->definition_level);
503
48
        parse_physical_field(second_level, false, list_child);
504
48
        _next_schema_pos = curr_pos + 2;
505
48
    }
506
507
10.3k
    list_field->name = first_level.name;
508
10.3k
    list_field->lower_case_name = to_lower(first_level.name);
509
10.3k
    list_field->column_id = UNASSIGNED_COLUMN_ID; // Initialize column_id
510
10.3k
    list_field->data_type =
511
10.3k
            std::make_shared<DataTypeArray>(make_nullable(list_field->children[0].data_type));
512
10.3k
    if (is_optional) {
513
9.48k
        list_field->data_type = make_nullable(list_field->data_type);
514
9.48k
    }
515
10.3k
    list_field->field_id = first_level.__isset.field_id ? first_level.field_id : -1;
516
517
10.3k
    return Status::OK();
518
10.3k
}
519
520
Status FieldDescriptor::parse_map_field(const std::vector<tparquet::SchemaElement>& t_schemas,
521
7.73k
                                        size_t curr_pos, FieldSchema* map_field) {
522
    // the map definition in parquet:
523
    // optional group <name> (MAP) {
524
    //   repeated group map (MAP_KEY_VALUE) {
525
    //     required <type> key;
526
    //     optional <type> value;
527
    //   }
528
    // }
529
    // Map value can be optional, the map without values is a SET
530
7.73k
    if (curr_pos + 2 >= t_schemas.size()) {
531
0
        return Status::InvalidArgument("Map element should have at least three levels");
532
0
    }
533
7.73k
    auto& map_schema = t_schemas[curr_pos];
534
7.73k
    if (map_schema.num_children != 1) {
535
2
        return Status::InvalidArgument(
536
2
                "Map element should have only one child(name='map', type='MAP_KEY_VALUE')");
537
2
    }
538
7.73k
    if (is_repeated_node(map_schema)) {
539
0
        return Status::InvalidArgument("Map element can't be a repeated schema");
540
0
    }
541
7.73k
    auto& map_key_value = t_schemas[curr_pos + 1];
542
7.73k
    if (!is_group_node(map_key_value) || !is_repeated_node(map_key_value)) {
543
0
        return Status::InvalidArgument(
544
0
                "the second level in map must be a repeated group(key and value)");
545
0
    }
546
7.73k
    auto& map_key = t_schemas[curr_pos + 2];
547
7.73k
    if (!is_required_node(map_key)) {
548
452
        LOG(WARNING) << "Filed " << map_schema.name << " is map type, but with nullable key column";
549
452
    }
550
551
7.73k
    if (map_key_value.num_children == 1) {
552
        // The map with three levels is a SET
553
0
        return parse_list_field(t_schemas, curr_pos, map_field);
554
0
    }
555
7.73k
    if (map_key_value.num_children != 2) {
556
        // A standard map should have four levels
557
0
        return Status::InvalidArgument(
558
0
                "the second level in map(MAP_KEY_VALUE) should have two children");
559
0
    }
560
    // standard map
561
7.73k
    bool is_optional = is_optional_node(map_schema);
562
7.73k
    if (is_optional) {
563
7.10k
        map_field->definition_level++;
564
7.10k
    }
565
7.73k
    map_field->repetition_level++;
566
7.73k
    map_field->definition_level++;
567
568
    // Directly create key and value children instead of intermediate key_value node
569
7.73k
    map_field->children.resize(2);
570
    // map is a repeated node, we should set the `repeated_parent_def_level` of its children as `definition_level`
571
7.73k
    set_child_node_level(map_field, map_field->definition_level);
572
573
7.73k
    auto key_field = &map_field->children[0];
574
7.73k
    auto value_field = &map_field->children[1];
575
576
    // Parse key and value fields directly from the key_value group's children
577
7.73k
    _next_schema_pos = curr_pos + 2; // Skip key_value group, go directly to key
578
7.73k
    RETURN_IF_ERROR(parse_node_field(t_schemas, _next_schema_pos, key_field));
579
7.73k
    RETURN_IF_ERROR(parse_node_field(t_schemas, _next_schema_pos, value_field));
580
581
7.73k
    map_field->name = map_schema.name;
582
7.73k
    map_field->lower_case_name = to_lower(map_field->name);
583
7.73k
    map_field->column_id = UNASSIGNED_COLUMN_ID; // Initialize column_id
584
7.73k
    map_field->data_type = std::make_shared<DataTypeMap>(make_nullable(key_field->data_type),
585
7.73k
                                                         make_nullable(value_field->data_type));
586
7.73k
    if (is_optional) {
587
7.10k
        map_field->data_type = make_nullable(map_field->data_type);
588
7.10k
    }
589
7.73k
    map_field->field_id = map_schema.__isset.field_id ? map_schema.field_id : -1;
590
591
7.73k
    return Status::OK();
592
7.73k
}
593
594
Status FieldDescriptor::parse_struct_field(const std::vector<tparquet::SchemaElement>& t_schemas,
595
6.02k
                                           size_t curr_pos, FieldSchema* struct_field) {
596
    // the nested column in parquet, parse group to struct.
597
6.02k
    auto& struct_schema = t_schemas[curr_pos];
598
6.02k
    bool is_optional = is_optional_node(struct_schema);
599
6.02k
    if (is_optional) {
600
5.18k
        struct_field->definition_level++;
601
5.18k
    }
602
6.02k
    auto num_children = struct_schema.num_children;
603
6.02k
    struct_field->children.resize(num_children);
604
6.02k
    set_child_node_level(struct_field, struct_field->repeated_parent_def_level);
605
6.02k
    _next_schema_pos = curr_pos + 1;
606
20.5k
    for (int i = 0; i < num_children; ++i) {
607
14.5k
        RETURN_IF_ERROR(parse_node_field(t_schemas, _next_schema_pos, &struct_field->children[i]));
608
14.5k
    }
609
6.01k
    struct_field->name = struct_schema.name;
610
6.01k
    struct_field->lower_case_name = to_lower(struct_field->name);
611
6.01k
    struct_field->column_id = UNASSIGNED_COLUMN_ID; // Initialize column_id
612
613
6.01k
    struct_field->field_id = struct_schema.__isset.field_id ? struct_schema.field_id : -1;
614
6.01k
    DataTypes res_data_types;
615
6.01k
    std::vector<String> names;
616
20.5k
    for (int i = 0; i < num_children; ++i) {
617
14.5k
        res_data_types.push_back(make_nullable(struct_field->children[i].data_type));
618
14.5k
        names.push_back(struct_field->children[i].name);
619
14.5k
    }
620
6.01k
    struct_field->data_type = std::make_shared<DataTypeStruct>(res_data_types, names);
621
6.01k
    if (is_optional) {
622
5.18k
        struct_field->data_type = make_nullable(struct_field->data_type);
623
5.18k
    }
624
6.01k
    return Status::OK();
625
6.02k
}
626
627
5
int FieldDescriptor::get_column_index(const std::string& column) const {
628
15
    for (int32_t i = 0; i < _fields.size(); i++) {
629
15
        if (_fields[i].name == column) {
630
5
            return i;
631
5
        }
632
15
    }
633
0
    return -1;
634
5
}
635
636
973k
FieldSchema* FieldDescriptor::get_column(const std::string& name) const {
637
973k
    auto it = _name_to_field.find(name);
638
974k
    if (it != _name_to_field.end()) {
639
974k
        return it->second;
640
974k
    }
641
18.4E
    throw Exception(Status::InternalError("Name {} not found in FieldDescriptor!", name));
642
0
    return nullptr;
643
973k
}
644
645
35.1k
void FieldDescriptor::get_column_names(std::unordered_set<std::string>* names) const {
646
35.1k
    names->clear();
647
315k
    for (const FieldSchema& f : _fields) {
648
315k
        names->emplace(f.name);
649
315k
    }
650
35.1k
}
651
652
0
std::string FieldDescriptor::debug_string() const {
653
0
    std::stringstream ss;
654
0
    ss << "fields=[";
655
0
    for (int i = 0; i < _fields.size(); ++i) {
656
0
        if (i != 0) {
657
0
            ss << ", ";
658
0
        }
659
0
        ss << _fields[i].debug_string();
660
0
    }
661
0
    ss << "]";
662
0
    return ss.str();
663
0
}
664
665
29.6k
void FieldDescriptor::assign_ids() {
666
29.6k
    uint64_t next_id = 1;
667
217k
    for (auto& field : _fields) {
668
217k
        field.assign_ids(next_id);
669
217k
    }
670
29.6k
}
671
672
0
const FieldSchema* FieldDescriptor::find_column_by_id(uint64_t column_id) const {
673
0
    for (const auto& field : _fields) {
674
0
        if (auto result = field.find_column_by_id(column_id)) {
675
0
            return result;
676
0
        }
677
0
    }
678
0
    return nullptr;
679
0
}
680
681
308k
void FieldSchema::assign_ids(uint64_t& next_id) {
682
308k
    column_id = next_id++;
683
684
308k
    for (auto& child : children) {
685
91.1k
        child.assign_ids(next_id);
686
91.1k
    }
687
688
308k
    max_column_id = next_id - 1;
689
308k
}
690
691
0
const FieldSchema* FieldSchema::find_column_by_id(uint64_t target_id) const {
692
0
    if (column_id == target_id) {
693
0
        return this;
694
0
    }
695
696
0
    for (const auto& child : children) {
697
0
        if (auto result = child.find_column_by_id(target_id)) {
698
0
            return result;
699
0
        }
700
0
    }
701
702
0
    return nullptr;
703
0
}
704
705
272k
uint64_t FieldSchema::get_column_id() const {
706
272k
    return column_id;
707
272k
}
708
709
0
void FieldSchema::set_column_id(uint64_t id) {
710
0
    column_id = id;
711
0
}
712
713
33.5k
uint64_t FieldSchema::get_max_column_id() const {
714
33.5k
    return max_column_id;
715
33.5k
}
716
717
#include "common/compile_check_end.h"
718
719
} // namespace doris